diff --git a/.github/workflows/markdown_equations.yml b/.github/workflows/markdown_equations.yml index 618ec2a96a77..0879d14bb775 100644 --- a/.github/workflows/markdown_equations.yml +++ b/.github/workflows/markdown_equations.yml @@ -96,6 +96,11 @@ jobs: git config --local user.name "stdlib-bot" timeout-minutes: 5 + # Disable Git hooks: + - name: 'Disable Git hooks' + run: | + rm -rf .git/hooks + # Import GPG key to sign commits: - name: 'Import GPG key to sign commits' # Pin action to full length commit SHA @@ -166,7 +171,7 @@ jobs: git commit -m "docs: update Markdown equation elements" echo "changed=true" >> $GITHUB_OUTPUT fi - timeout-minutes: 15 + timeout-minutes: 60 # Delete remote PR branch to ensure a clean push when the branch has diverged: - name: 'Delete remote PR branch' @@ -177,6 +182,9 @@ jobs: # Fetch the branch first so that --force-with-lease in the subsequent push has a local tracking reference and can verify the remote state: git fetch origin markdown-insert-equations 2>/dev/null || true gh api -X DELETE repos/stdlib-js/stdlib/git/refs/heads/markdown-insert-equations 2>/dev/null || true + + # Delete the local tracking branch so that --force-with-lease does not reject the push due to stale info: + git branch -dr origin/markdown-insert-equations 2>/dev/null || true timeout-minutes: 5 # Create a pull request with the updated equations: diff --git a/.github/workflows/publish_coverage_pr.yml b/.github/workflows/publish_coverage_pr.yml index 21c1bbff76d2..80937fbbbb70 100644 --- a/.github/workflows/publish_coverage_pr.yml +++ b/.github/workflows/publish_coverage_pr.yml @@ -157,8 +157,11 @@ jobs: run: | cd ./www-test-code-coverage BRANCH_NAME="pr-$PR_NUMBER" - git fetch origin "$BRANCH_NAME" || true - git checkout "$BRANCH_NAME" || git checkout -b "$BRANCH_NAME" + if git fetch origin "$BRANCH_NAME"; then + git checkout -B "$BRANCH_NAME" FETCH_HEAD + else + git checkout -b "$BRANCH_NAME" + fi # Remove all directories except .github and .git from branch: find . -mindepth 1 -maxdepth 1 -type d -not -name '.github' -not -name '.git' -exec git rm -rf {} + || true diff --git a/.rtlintrc b/.rtlintrc index c209e068a3b1..a4f45f9e8df1 100644 --- a/.rtlintrc +++ b/.rtlintrc @@ -6,7 +6,7 @@ "@stdlib/_tools/repl-txt/rules/interface-spacing": [ "error", 2 ], "@stdlib/_tools/repl-txt/rules/line-length": [ "error", 80 ], "@stdlib/_tools/repl-txt/rules/match-signature": "error", - "@stdlib/_tools/repl-txt/rules/resolvable-aliases": "error", + "@stdlib/_tools/repl-txt/rules/resolvable-aliases": "warn", "@stdlib/_tools/repl-txt/rules/section-order": "error", "@stdlib/_tools/repl-txt/rules/section-heading-style": "error", "@stdlib/_tools/repl-txt/rules/see-also": "error", diff --git a/docs/git-notes/aa89fb36f12f7e813ddec45082316115185eff89.txt b/docs/git-notes/aa89fb36f12f7e813ddec45082316115185eff89.txt new file mode 100644 index 000000000000..b1e40b09d8ce --- /dev/null +++ b/docs/git-notes/aa89fb36f12f7e813ddec45082316115185eff89.txt @@ -0,0 +1,11 @@ +--- +type: amend-message +--- +feat: add `stats/incr/nanmmin` + +PR-URL: https://github.com/stdlib-js/stdlib/pull/5849 +Closes: https://github.com/stdlib-js/stdlib/issues/5594 + +Co-authored-by: Philipp Burckhardt +Co-authored-by: stdlib-bot +Reviewed-by: Philipp Burckhardt diff --git a/docs/git-notes/bc7c322891b1c0b758e6aef323b2f22a3bab1500.txt b/docs/git-notes/bc7c322891b1c0b758e6aef323b2f22a3bab1500.txt new file mode 100644 index 000000000000..12bb21e91b79 --- /dev/null +++ b/docs/git-notes/bc7c322891b1c0b758e6aef323b2f22a3bab1500.txt @@ -0,0 +1,10 @@ +--- +type: amend-message +--- +feat: add `blas/ext/base/ndarray/gfirst-index-less-than` + +PR-URL: https://github.com/stdlib-js/stdlib/pull/13596 +Co-authored-by: Athan Reines +Reviewed-by: Athan Reines +Signed-off-by: Athan Reines +Closes: https://github.com/stdlib-js/metr-issue-tracker/issues/1022 diff --git a/docs/git-notes/ef6a8d06633359aa718f4aef91a1a257782748b2.txt b/docs/git-notes/ef6a8d06633359aa718f4aef91a1a257782748b2.txt new file mode 100644 index 000000000000..bb32a0bb4b6f --- /dev/null +++ b/docs/git-notes/ef6a8d06633359aa718f4aef91a1a257782748b2.txt @@ -0,0 +1,12 @@ +--- +type: amend-message +--- +feat: add C implementation for `stats/base/dists/frechet/pdf` + +PR-URL: https://github.com/stdlib-js/stdlib/pull/10843 +Closes: https://github.com/stdlib-js/stdlib/issues/3612 + +Co-authored-by: Philipp Burckhardt +Co-authored-by: stdlib-bot +Reviewed-by: Philipp Burckhardt +Signed-off-by: Philipp Burckhardt diff --git a/etc/eslint/.eslintrc.benchmarks.js b/etc/eslint/.eslintrc.benchmarks.js index 713fed264ecc..a2d0ed97f188 100644 --- a/etc/eslint/.eslintrc.benchmarks.js +++ b/etc/eslint/.eslintrc.benchmarks.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable stdlib/no-empty-lines-between-requires */ + 'use strict'; // MODULES // @@ -127,11 +129,11 @@ eslint.rules[ 'stdlib/jsdoc-doctest' ] = 'off'; eslint.rules[ 'stdlib/no-unnecessary-nested-functions' ] = 'off'; /** -* Warn when using string concatenation in benchmark descriptions. +* Disallow using string concatenation in benchmark descriptions. * * @private */ -eslint.rules[ 'stdlib/no-bench-string-concat' ] = 'warn'; +eslint.rules[ 'stdlib/no-bench-string-concat' ] = 'error'; // EXPORTS // diff --git a/etc/eslint/.eslintrc.examples.js b/etc/eslint/.eslintrc.examples.js index afa9a472ffd5..20a433c6fa84 100644 --- a/etc/eslint/.eslintrc.examples.js +++ b/etc/eslint/.eslintrc.examples.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable stdlib/no-empty-lines-between-requires */ + 'use strict'; // MODULES // diff --git a/etc/eslint/.eslintrc.tests.js b/etc/eslint/.eslintrc.tests.js index edd9f4f9452b..d845bbc7da83 100644 --- a/etc/eslint/.eslintrc.tests.js +++ b/etc/eslint/.eslintrc.tests.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable stdlib/no-empty-lines-between-requires */ + 'use strict'; // MODULES // diff --git a/etc/eslint/.eslintrc.typescript.tests.js b/etc/eslint/.eslintrc.typescript.tests.js index 2f2b6a15a0da..91e6dd8b2a78 100644 --- a/etc/eslint/.eslintrc.typescript.tests.js +++ b/etc/eslint/.eslintrc.typescript.tests.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable stdlib/no-empty-lines-between-requires */ + 'use strict'; // MODULES // diff --git a/lib/node_modules/@stdlib/_tools/eslint/rules/jsdoc-typedef-typos/lib/edit_distance.js b/lib/node_modules/@stdlib/_tools/eslint/rules/jsdoc-typedef-typos/lib/edit_distance.js index 755b221d87a2..5bc482c0d167 100644 --- a/lib/node_modules/@stdlib/_tools/eslint/rules/jsdoc-typedef-typos/lib/edit_distance.js +++ b/lib/node_modules/@stdlib/_tools/eslint/rules/jsdoc-typedef-typos/lib/edit_distance.js @@ -20,7 +20,7 @@ // MODULES // -var ndarray = require( '@stdlib/ndarray/array' ); +var zeros = require( '@stdlib/ndarray/zeros' ); var minn = require( '@stdlib/math/base/special/minn' ); @@ -31,7 +31,7 @@ var minn = require( '@stdlib/math/base/special/minn' ); * * ## Notes * -* - the edit distance between two strings is the number of insertions, deletions, character substitutions, as well as transpositions of adjacent characters to convert one of the strings into the other. +* - The edit distance between two strings is the number of insertions, deletions, character substitutions, as well as transpositions of adjacent characters to convert one of the strings into the other. * * [damerau-levenshtein]: https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance * @@ -56,9 +56,7 @@ function editDistance( word1, word2 ) { n = word2.length; // FIXME: all of the following needs to be cleaned up. There may be an opportunity for a `blas/ext/base` implementation of edit distance; however, we need to think carefully about this as the following doesn't take into account grapheme clusters. - d = ndarray({ - 'shape': [ m+1, n+1 ] - }); + d = zeros( [ m+1, n+1 ] ); for ( i = 0; i <= m; i++ ) { d.set( i, 0, i ); } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/README.md b/lib/node_modules/@stdlib/_tools/lint/repl-txt/README.md index 572134fff336..7a6c9a3c602d 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/README.md +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/README.md @@ -34,22 +34,35 @@ var lint = require( '@stdlib/_tools/lint/repl-txt' ); Asynchronously lints `repl.txt` files. + + ```javascript -lint( done ); +var join = require( 'path' ).join; + +var opts = { + 'dir': join( __dirname, 'test' ) +}; +lint( opts, done ); -function done( error, errs ) { +function done( error, results ) { if ( error ) { - throw error; + console.error( error.message ); + return; } - if ( errs ) { - console.dir( errs ); - } else { - console.log( 'Success!' ); + if ( results ) { + if ( results.warnings.length ) { + console.dir( results.warnings ); + } + if ( results.errors.length ) { + console.dir( results.errors ); + } else { + console.log( 'Success!' ); + } } } ``` -The function accepts the following `options`: +The function accepts the following options: - **dir**: root directory from which to search for `repl.txt` files. May be either an absolute file path or a path relative to the current working directory. Default: current working directory. - **pattern**: glob pattern used to find `repl.txt` files. Default: `'**/repl.txt'`. @@ -57,6 +70,8 @@ The function accepts the following `options`: To search from an alternative directory, set the `dir` option. + + ```javascript var opts = { 'dir': '/foo/bar/baz' @@ -64,43 +79,65 @@ var opts = { lint( opts, done ); -function done( error, errs ) { +function done( error, results ) { if ( error ) { - throw error; + console.error( error.message ); + return; } - if ( errs ) { - console.dir( errs ); - } else { - console.log( 'Success!' ); + if ( results ) { + if ( results.warnings.length ) { + console.dir( results.warnings ); + } + if ( results.errors.length ) { + console.dir( results.errors ); + } else { + console.log( 'Success!' ); + } } } ``` To provide an alternative include filter, set the `pattern` option. + + ```javascript +var join = require( 'path' ).join; + var opts = { + 'dir': join( __dirname, 'test' ), 'pattern': '**/foo/**/repl.txt' }; lint( opts, done ); -function done( error, errs ) { +function done( error, results ) { if ( error ) { - throw error; + console.error( error.message ); + return; } - if ( errs ) { - console.dir( errs ); - } else { - console.log( 'Success!' ); + if ( results ) { + if ( results.warnings.length ) { + console.dir( results.warnings ); + } + if ( results.errors.length ) { + console.dir( results.errors ); + } else { + console.log( 'Success!' ); + } } } ``` To exclude matches, set the `ignore` option. + + ```javascript +var join = require( 'path' ).join; + var opts = { + 'dir': join( __dirname, 'test' ), 'ignore': [ 'node_modules/**', 'build/**', @@ -110,14 +147,20 @@ var opts = { lint( opts, done ); -function done( error, errs ) { +function done( error, results ) { if ( error ) { - throw error; + console.error( error.message ); + return; } - if ( errs ) { - console.dir( errs ); - } else { - console.log( 'Success!' ); + if ( results ) { + if ( results.warnings.length ) { + console.dir( results.warnings ); + } + if ( results.errors.length ) { + console.dir( results.errors ); + } else { + console.log( 'Success!' ); + } } } ``` @@ -126,16 +169,29 @@ function done( error, errs ) { Synchronously lints `repl.txt` files. + + ```javascript -var errs = lint.sync(); -if ( errs ) { - console.dir( errs ); -} else { - console.log( 'Success!' ); +var join = require( 'path' ).join; + +var opts = { + 'dir': join( __dirname, 'test' ) +}; + +var results = lint.sync( opts ); +if ( results ) { + if ( results.warnings.length ) { + console.dir( results.warnings ); + } + if ( results.errors.length ) { + console.dir( results.errors ); + } else { + console.log( 'Success!' ); + } } ``` -The function accepts the same `options` as `lint()` above. +The function accepts the same options as `lint()` above. @@ -164,15 +220,20 @@ var opts = { lint( opts, done ); -function done( error, errs ) { +function done( error, results ) { if ( error ) { throw error; } - if ( errs ) { - console.log( JSON.stringify( errs, null, 2 ) ); - } else { - console.log( 'Success!' ); + if ( results ) { + if ( results.warnings.length ) { + console.log( JSON.stringify( results.warnings, null, 2 ) ); + } + if ( results.errors.length ) { + console.log( JSON.stringify( results.errors, null, 2 ) ); + return; + } } + console.log( 'Success!' ); } ``` @@ -217,12 +278,16 @@ Options: - To provide multiple exclusion glob patterns, set multiple `--ignore` option arguments. + + ```bash $ lint-repl-txt --ignore=node_modules/** --ignore=build/** --ignore=reports/** ``` - If the split separator is a [regular expression][regexp], ensure that the `split` option is properly **escaped**. + + ```bash # Not escaped... $ | lint-repl-txt --split /\r?\n/ @@ -241,6 +306,8 @@ Options: ### Examples + + ```bash $ lint-repl-txt @@ -258,20 +325,24 @@ $ lint-repl-txt start: 17 end: 24 -2 errors +2 errors, 0 warnings ``` To output results as newline-delimited JSON ([NDJSON][ndjson]), + + ```bash $ lint-repl-txt --format ndjson -{"file":"...","errors":[...]} -{"file":"...","errors":[...]} +{"file":"...","errors":[...],"warnings":[...]} +{"file":"...","errors":[...],"warnings":[...]} ... ``` To use as a part of a [standard stream][standard-stream] pipeline, + + ```bash $ echo -n $'./repl.txt' | lint-repl-txt ... diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/bin/cli b/lib/node_modules/@stdlib/_tools/lint/repl-txt/bin/cli index 54c221474c95..151f0899202d 100755 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/bin/cli +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/bin/cli @@ -31,6 +31,8 @@ var stdout = require( '@stdlib/streams/node/stdout' ); var RE_EOL = require( '@stdlib/regexp/eol' ).REGEXP; var isRegExpString = require( '@stdlib/assert/is-regexp-string' ); var reFromString = require( '@stdlib/utils/regexp-from-string' ); +var groupValuesOnKey = require( '@stdlib/array/base/group-values-on-key' ); +var objectKeys = require( '@stdlib/utils/keys' ); var cwd = require( '@stdlib/process/cwd' ); var lint = require( './../lib' ); var lintREPL = require( './../lib/lint.js' ); @@ -39,54 +41,119 @@ var lintREPL = require( './../lib/lint.js' ); // FUNCTIONS // /** -* Prints lint errors as newline-delimited JSON. +* Combines errors and warnings into a single array. * * @private -* @param {ObjectArray} errs - lint errors +* @param {Array} results - array of results +* @returns {Array} processed results */ -function ndjson( errs ) { +function results2array( results ) { + var out; + var tmp; + var o; var i; - for ( i = 0; i < errs.length; i++ ) { - console.error( JSON.stringify( errs[ i ] ) ); // eslint-disable-line no-console + var j; + + out = []; + for ( i = 0; i < results.length; i++ ) { + o = results[ i ]; + tmp = o.errors || o.warnings; + for ( j = 0; j < tmp.length; j++ ) { + out.push( tmp[ j ] ); + } + } + return out; +} + +/** +* Prints lint results as newline-delimited JSON. +* +* @private +* @param {Object} results - lint results +*/ +function ndjson( results ) { + var keys; + var g; + var o; + var v; + var i; + var j; + var k; + + // Resolve the file names: + keys = objectKeys( results ); + + // Print results for each file... + for ( i = 0; i < keys.length; i++ ) { + k = keys[ i ]; + g = results[ k ]; + o = { + 'file': k, + 'errors': [], + 'warnings': [] + }; + for ( j = 0; j < g.length; j++ ) { + v = g[ j ]; + if ( v.errors ) { + o.errors = v.errors; + } else if ( v.warnings ) { + o.warnings = v.warnings; + } + } + console.error( JSON.stringify( o ) ); // eslint-disable-line no-console } } /** -* Pretty prints lint errors. +* Pretty prints lint results. * * @private -* @param {ObjectArray} errors - lint errors +* @param {Object} results - lint results */ -function prettyPrint( errors ) { +function prettyPrint( results ) { /* eslint-disable no-console */ - var total; - var error; - var errs; - var err; + var etotal; + var wtotal; + var keys; + var v; + var g; var i; var j; + var k; + + etotal = 0; + wtotal = 0; - total = 0; + // Resolve the file names: + keys = objectKeys( results ); console.error( '' ); - for ( i = 0; i < errors.length; i++ ) { - error = errors[ i ]; - console.error( error.file ); - - errs = error.errors; - total += errs.length; - for ( j = 0; j < errs.length; j++ ) { - err = errs[ j ]; + for ( i = 0; i < keys.length; i++ ) { + k = keys[ i ]; + g = results2array( results[ k ] ); + + // Print the current filename: + console.error( k ); + + // Pretty print errors and warnings for the current file... + for ( j = 0; j < g.length; j++ ) { + v = g[ j ]; console.error( '' ); - console.error( ' id: %s', err.id ); - console.error( ' severity: %s', err.severity ); - console.error( ' message: %s', err.message ); - console.error( ' start: %s', err.start ); - console.error( ' end: %s', err.end ); + console.error( ' id: %s', v.id ); + console.error( ' severity: %s', v.severity ); + console.error( ' message: %s', v.message ); + console.error( ' start: %s', v.start ); + console.error( ' end: %s', v.end ); + + if ( v.severity === 'error' ) { + etotal += 1; + } else { // v.severity === 'warning' + wtotal += 1; + } } console.error( '' ); } - console.error( '%d errors', total ); + console.error( '%d errors, %d warnings', etotal, wtotal ); console.error( '' ); /* eslint-enable no-console */ @@ -127,7 +194,7 @@ function main() { args = cli.args(); if ( flags.format ) { - fmt = args.format; + fmt = flags.format; } else if ( stdout.isTTY ) { fmt = 'pretty'; } else { @@ -194,20 +261,32 @@ function main() { * * @private * @param {(Error|null)} error - error object - * @param {(ObjectArray|null)} errs - lint errors + * @param {(Object|null)} results - lint results * @returns {void} */ - function onFinish( error, errs ) { + function onFinish( error, results ) { + var groups; + var tmp; if ( error ) { return cli.error( error ); } - if ( errs ) { + if ( results ) { + // Combine errors and warnings into a single array: + tmp = results.errors.concat( results.warnings ); + + // Group errors and warnings according to filename: + groups = groupValuesOnKey( tmp, 'file' ); + + // Print results: if ( fmt === 'ndjson' ) { - ndjson( errs ); + ndjson( groups ); } else { - prettyPrint( errs ); + prettyPrint( groups ); + } + // If we encountered lint errors, ensure we exit with a non-zero exit code... + if ( results.errors.length ) { + return cli.close( 1 ); } - return cli.close( 1 ); } } } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/examples/index.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/examples/index.js index 4fb35fc1d98a..ae5f9c61e849 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/examples/index.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/examples/index.js @@ -28,13 +28,18 @@ var opts = { lint( opts, done ); -function done( error, errs ) { +function done( error, results ) { if ( error ) { throw error; } - if ( errs ) { - console.log( JSON.stringify( errs, null, 2 ) ); - } else { - console.log( 'Success!' ); + if ( results ) { + if ( results.warnings.length ) { + console.log( JSON.stringify( results.warnings, null, 2 ) ); + } + if ( results.errors.length ) { + console.log( JSON.stringify( results.errors, null, 2 ) ); + return; + } } + console.log( 'Success!' ); } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/async.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/async.js index 99947bc71733..8f94bf2e2cf3 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/async.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/async.js @@ -53,14 +53,24 @@ var debug = logger( 'lint:repl-txt:async' ); * @throws {Error} `pattern` option must end with `repl.txt` * * @example -* lint( clbk ); +* var opts = { +* 'dir': __dirname +* }; +* lint( opts, clbk ); * -* function clbk( error, errs ) { +* function clbk( error, results ) { * if ( error ) { * throw error; * } -* if ( errs ) { -* console.dir( errs ); +* if ( results ) { +* if ( results.warnings.length ) { +* console.dir( results.warnings ); +* } +* if ( results.errors.length ) { +* console.dir( results.errors ); +* } else { +* console.log( 'Success!' ); +* } * } else { * console.log( 'Success!' ); * } @@ -119,10 +129,9 @@ function lint() { debug( 'Found %d files.', files.length ); if ( files.length ) { debug( 'Processing files.' ); - linter( files, done ); - } else { - done( null, null ); + return linter( files, done ); } + done( null, null ); } /** @@ -130,14 +139,14 @@ function lint() { * * @private * @param {(Error|null)} error - error object - * @param {(ObjectArray|null)} errs - lint errs + * @param {(Object|null)} results - lint results * @returns {void} */ - function done( error, errs ) { + function done( error, results ) { if ( error ) { return clbk( error ); } - clbk( null, errs ); + clbk( null, results ); } } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/index.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/index.js index f0b310e34cdd..1dc9fc101ed1 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/index.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/index.js @@ -26,14 +26,24 @@ * @example * var lint = require( '@stdlib/_tools/lint/repl-txt' ); * -* lint( clbk ); +* var opts = { +* 'dir': __dirname +* }; +* lint( opts, clbk ); * -* function clbk( error, errs ) { +* function clbk( error, results ) { * if ( error ) { * throw error; * } -* if ( errs ) { -* console.dir( errs ); +* if ( results ) { +* if ( results.warnings.length ) { +* console.dir( results.warnings ); +* } +* if ( results.errors.length ) { +* console.dir( results.errors ); +* } else { +* console.log( 'Success!' ); +* } * } else { * console.log( 'Success!' ); * } @@ -42,9 +52,19 @@ * @example * var lint = require( '@stdlib/_tools/lint/repl-txt' ); * -* var errs = lint.sync(); -* if ( errs ) { -* console.dir( errs ); +* var opts = { +* 'dir': __dirname +* }; +* var results = lint.sync( opts ); +* if ( results ) { +* if ( results.warnings.length ) { +* console.dir( results.warnings ); +* } +* if ( results.errors.length ) { +* console.dir( results.errors ); +* } else { +* console.log( 'Success!' ); +* } * } else { * console.log( 'Success!' ); * } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/lint.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/lint.js index e7cd84aef166..5a964f9da1df 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/lint.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/lint.js @@ -41,17 +41,20 @@ var OPTS = { * @private * @param {StringArray} files - list of `repl.txt` files * @param {Callback} clbk - callback to invoke upon completion +* @returns {void} */ function lint( files, clbk ) { + var warnings; + var errors; var total; - var out; var i; total = files.length; - out = []; + warnings = []; + errors = []; i = -1; - next(); + return next(); /** * Processes the next `repl.txt` file. @@ -78,7 +81,7 @@ function lint( files, clbk ) { j = i + 1; if ( error ) { debug( 'Encountered an error reading file: %s (%d of %d). Error: %s', files[ i ], j, total, error.message ); - out.push({ + errors.push({ 'file': files[ i ], 'errors': [ { @@ -97,11 +100,18 @@ function lint( files, clbk ) { debug( 'File is valid.' ); } else { debug( 'File is invalid: %s.', JSON.stringify( isValid.errors ) ); - out.push({ + errors.push({ 'file': files[ i ], 'errors': isValid.errors }); } + if ( isValid.warnings ) { + debug( 'File has warnings: %s.', JSON.stringify( isValid.warnings ) ); + warnings.push({ + 'file': files[ i ], + 'warnings': isValid.warnings + }); + } } if ( j < total ) { debug( 'Processed %d of %d files.', j, total ); @@ -115,13 +125,16 @@ function lint( files, clbk ) { * Callback invoked upon completion. * * @private + * @returns {void} */ function done() { - if ( out.length ) { - clbk( null, out ); - } else { - clbk( null, null ); + if ( errors.length || warnings.length ) { + return clbk( null, { + 'errors': errors, + 'warnings': warnings + }); } + clbk( null, null ); } } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/sync.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/sync.js index 1ea8047fbb3f..612f93bbc544 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/sync.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/lib/sync.js @@ -48,17 +48,28 @@ var debug = logger( 'lint:repl-txt:sync' ); * @throws {TypeError} options argument must be an object * @throws {TypeError} must provide valid options * @throws {Error} `pattern` option must end with `repl.txt` -* @returns {(ObjectArray|null)} lint errors or `null` +* @returns {(Object|null)} lint results or `null` * * @example -* var errs = lint(); -* if ( errs ) { -* console.dir( errs ); +* var results = lint({ +* 'dir': __dirname +* }); +* if ( results ) { +* if ( results.warnings.length ) { +* console.dir( results.warnings ); +* } +* if ( results.errors.length ) { +* console.dir( results.errors ); +* } else { +* console.log( 'Success!' ); +* } * } else { * console.log( 'Success!' ); * } */ function lint( options ) { + var warnings; + var errors; var files; var gopts; var total; @@ -67,7 +78,6 @@ function lint( options ) { var bool; var err; var dir; - var out; var i; var j; @@ -99,14 +109,15 @@ function lint( options ) { return null; } debug( 'Processing files.' ); - out = []; + warnings = []; + errors = []; for ( i = 0; i < total; i++ ) { j = i + 1; debug( 'Reading file: %s (%d of %d).', files[ i ], j, total ); file = readFile( files[ i ] ); if ( file instanceof Error ) { debug( 'Encountered an error reading file: %s (%d of %d). Error: %s', files[ i ], j, total, file.message ); - out.push({ + errors.push({ 'file': files[ i ], 'errors': [ { @@ -125,17 +136,27 @@ function lint( options ) { debug( 'File is valid.' ); } else { debug( 'File is invalid: %s.', JSON.stringify( isValid.errors ) ); - out.push({ + errors.push({ 'file': files[ i ], 'errors': isValid.errors }); } + if ( isValid.warnings ) { + debug( 'File has warnings: %s.', JSON.stringify( isValid.warnings ) ); + warnings.push({ + 'file': files[ i ], + 'warnings': isValid.warnings + }); + } } debug( 'Processed %d of %d files.', j, total ); } debug( 'Processed all files.' ); - if ( out.length ) { - return out; + if ( errors.length || warnings.length ) { + return { + 'errors': errors, + 'warnings': warnings + }; } return null; } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.async.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.async.js index 823e7b226c30..15ada6b5262f 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.async.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.async.js @@ -24,6 +24,7 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); var proxyquire = require( 'proxyquire' ); var noop = require( '@stdlib/utils/noop' ); +var isObject = require( '@stdlib/assert/is-object' ); var isObjectArray = require( '@stdlib/assert/is-object-array' ); var lint = require( './../lib/async.js' ); @@ -170,11 +171,11 @@ tape( 'the function returns `null` if unable to resolve any packages', function } } - function clbk( error, errs ) { + function clbk( error, results ) { if ( error ) { t.ok( false, error.message ); } else { - t.strictEqual( errs, null, 'returns `null`' ); + t.strictEqual( results, null, 'returns expected value' ); } t.end(); } @@ -187,11 +188,11 @@ tape( 'the function returns `null` if all `repl.txt` files are valid', function }; lint( opts, clbk ); - function clbk( error, errs ) { + function clbk( error, results ) { if ( error ) { t.ok( false, error.message ); } else { - t.strictEqual( errs, null, 'returns `null`' ); + t.strictEqual( results, null, 'returns expected value' ); } t.end(); } @@ -215,18 +216,24 @@ tape( 'the function returns an array of lint errors to a provided callback if on var cb = arguments[ arguments.length-1 ]; setTimeout( onTimeout, 0 ); function onTimeout() { - cb( null, [{ - 'file': 'beep', - 'message': 'boop' - }]); + cb( null, { + 'errors': [ + { + 'file': 'beep', + 'message': 'boop' + } + ], + 'warnings': [] + }); } } - function clbk( error, errs ) { + function clbk( error, results ) { if ( error ) { t.ok( false, error.message ); } else { - t.strictEqual( isObjectArray( errs ), true, 'returns expected value' ); + t.strictEqual( isObject( results ), true, 'returns expected value' ); + t.strictEqual( isObjectArray( results.errors ), true, 'returns expected value' ); } t.end(); } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.lint.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.lint.js index a105bd559d87..9c732b5a97e2 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.lint.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.lint.js @@ -23,6 +23,7 @@ var join = require( 'path' ).join; var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var isObject = require( '@stdlib/assert/is-object' ); var isObjectArray = require( '@stdlib/assert/is-object-array' ); var lint = require( './../lib/lint.js' ); @@ -44,11 +45,12 @@ tape( 'main export is a function', function test( t ) { tape( 'the function returns an array of errors to a provided callback if one or more `repl.txt` files are invalid', function test( t ) { lint( [ invalid ], clbk ); - function clbk( error, errs ) { + function clbk( error, results ) { if ( error ) { t.ok( false, error.message ); } else { - t.strictEqual( isObjectArray( errs ), true, 'returns an array of errors' ); + t.strictEqual( isObject( results ), true, 'returns expected value' ); + t.strictEqual( isObjectArray( results.errors ), true, 'returns expected value' ); } t.end(); } @@ -57,11 +59,11 @@ tape( 'the function returns an array of errors to a provided callback if one or tape( 'the function successfully lints valid `repl.txt` files', function test( t ) { lint( [ valid, valid ], clbk ); - function clbk( error, errs ) { + function clbk( error, results ) { if ( error ) { t.ok( false, error.message ); } else { - t.strictEqual( errs, null, 'returns `null`' ); + t.strictEqual( results, null, 'returns expected value' ); } t.end(); } diff --git a/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.sync.js b/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.sync.js index 368c2819e10a..333cce9c51e8 100644 --- a/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.sync.js +++ b/lib/node_modules/@stdlib/_tools/lint/repl-txt/test/test.sync.js @@ -20,7 +20,6 @@ // MODULES // -var resolve = require( 'path' ).resolve; var join = require( 'path' ).join; var tape = require( 'tape' ); var proxyquire = require( 'proxyquire' ); @@ -30,7 +29,7 @@ var lint = require( './../lib/sync.js' ); // VARIABLES // -var exampleDir = resolve( __dirname, '..', '..', '..', '..', 'symbol' ); +var valid = join( __dirname, 'fixtures', 'docs', 'valid.repl.txt' ); var invalid = join( __dirname, 'fixtures', 'docs', 'invalid.repl.txt' ); @@ -55,7 +54,7 @@ tape( 'the function throws an error if provided an invalid option', function tes tape( 'the function returns an array of lint errors if one or more files fail lint tests', function test( t ) { var lint; - var errs; + var res; lint = proxyquire( './../lib/sync.js', { 'glob': { @@ -63,8 +62,8 @@ tape( 'the function returns an array of lint errors if one or more files fail li } }); - errs = lint(); - t.strictEqual( isObjectArray( errs ), true, 'returns lint errors' ); + res = lint(); + t.strictEqual( isObjectArray( res.errors ), true, 'returns expected value' ); t.end(); function glob() { @@ -73,22 +72,28 @@ tape( 'the function returns an array of lint errors if one or more files fail li }); tape( 'the function returns `null` if all `repl.txt` files are valid', function test( t ) { - var opts; - var err; + var lint; + var res; - opts = { - 'dir': exampleDir - }; - err = lint( opts ); + lint = proxyquire( './../lib/sync.js', { + 'glob': { + 'sync': glob + } + }); - t.strictEqual( err, null, 'returns `null`' ); + res = lint(); + t.strictEqual( res, null, 'returns expected value' ); t.end(); + + function glob() { + return [ valid, valid ]; + } }); tape( 'the function returns `null` if unable to resolve any `repl.txt` files', function test( t ) { var lint; - var errs; + var res; lint = proxyquire( './../lib/sync.js', { 'glob': { @@ -96,8 +101,8 @@ tape( 'the function returns `null` if unable to resolve any `repl.txt` files', f } }); - errs = lint(); - t.strictEqual( errs, null, 'returns expected value' ); + res = lint(); + t.strictEqual( res, null, 'returns expected value' ); t.end(); function glob() { diff --git a/lib/node_modules/@stdlib/_tools/package-json/schema/examples/index.js b/lib/node_modules/@stdlib/_tools/package-json/schema/examples/index.js index f80bfa9f0ddb..59739085974c 100644 --- a/lib/node_modules/@stdlib/_tools/package-json/schema/examples/index.js +++ b/lib/node_modules/@stdlib/_tools/package-json/schema/examples/index.js @@ -20,8 +20,8 @@ var Ajv = require( 'ajv' ); var schema = require( './../lib' ); - var pkg = require( './../package.json' ); + var ajv = new Ajv(); var bool = ajv.validate( schema(), pkg ); diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/parse/lib/extract_signature.js b/lib/node_modules/@stdlib/_tools/repl-txt/parse/lib/extract_signature.js index d8ddc5384a4d..8f15daaa8187 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/parse/lib/extract_signature.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/parse/lib/extract_signature.js @@ -48,14 +48,6 @@ function extractSignature( str ) { for ( i = 0; i < str.length; i++ ) { ch = str.charAt( i ); switch ( state ) { - default: - case 'name': - if ( ch === '(' ) { - state = 'params'; - } else { - name += ch; - } - break; case 'params': if ( ch === ')' ) { if ( param && param.name !== '' ) { @@ -89,9 +81,17 @@ function extractSignature( str ) { }; } } + break; + case 'name': + default: + if ( ch === '(' ) { + state = 'params'; + } else { + name += ch; + } + break; } } - return { 'name': name, 'parameters': params, diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js index 64b64e6151ee..d1af26399e07 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/doctest/lib/main.js @@ -23,39 +23,17 @@ var vm = require( 'vm' ); var dirname = require( 'path' ).dirname; var replace = require( '@stdlib/string/replace' ); -var namespace = require( '@stdlib/namespace' ); +var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var tryRequire = require( '@stdlib/utils/try-require' ); var compareValues = require( '@stdlib/_tools/doctest/compare-values' ); +var format = require( '@stdlib/string/format' ); // VARIABLES // var RE_EXTERNAL_ALIAS = /{{alias:([\s\S]+?)}}/g; -var RE_ASSIGNMENT = /(?:var|let|const)? ?([a-zA-Z0-9]*) ?=/; -var NAMESPACE = namespace(); - - -// FUNCTIONS // - -/** -* Returns an alias for a given package name. -* -* @private -* @param {string} pkg - package name -* @returns {(string|null)} alias name or null -*/ -function pkg2alias( pkg ) { - var alias; - var i; - - for ( i = 0; i < NAMESPACE.length; i++ ) { - if ( pkg === NAMESPACE[ i ].path ) { - alias = NAMESPACE[ i ].alias; - return alias; - } - } - return null; -} +var RE_ASSIGNMENT = /(?:var|let|const)? ?([a-zA-Z0-9]*) *=/; // MAIN // @@ -142,8 +120,12 @@ function main( context ) { } } catch ( err ) { if ( current.output !== '' ) { - context.report( 'Received an unexpected error when running example `'+code+'`: ' + err.message, section ); + // If the error was due to an unknown package identifier, strip the `require` stacktrace: + msg = replace( err.message, /\nRequire stack:[\s\S]+/, '' ); + msg = format( 'Received an unexpected error when running example `%s`: %s', code, msg ); + context.report( msg, section ); } + break; } } for ( i = 0; i < expected.length; i++ ) { @@ -168,10 +150,23 @@ function main( context ) { var alias; var key; var len; + var err; var o; var i; alias = pkg2alias( pkg ); + if ( alias === null ) { + // Attempt to `require` the package, thus confirming that the package actually exists: + err = tryRequire( pkg ); + + // If an error was returned, we were unable to import the package... + if ( err instanceof Error ) { + // Return a string which will raise an exception: + return format( 'require(\'%s\')', pkg ); + } + // If an alias does not exist in the global namespace, dynamically `require` a package so that the desired expression can be executed: + return format( '(require(\'%s\'))', pkg ); + } alias = alias.split( '.' ); len = alias.length; diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/interface-spacing/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/interface-spacing/lib/main.js index c9c275518b0c..45e13d427645 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/interface-spacing/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/interface-spacing/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var format = require( '@stdlib/string/format' ); + + // VARIABLES // var DEFAULT_SPACING = 2; @@ -52,7 +57,7 @@ function main( context ) { elem = interfaces[ i ]; emptyLines = elem.start - end - 1; if ( emptyLines !== spacing ) { - context.report( 'Interface documentation sections must be separated by `' + spacing + '` empty lines. Encountered: `'+ emptyLines+'`.', interfaces[ i ] ); + context.report( format( 'Interface documentation sections must be separated by `%s` empty lines. Encountered: `%s`.', spacing, emptyLines ), interfaces[ i ] ); } end = elem.end; } diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/line-length/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/line-length/lib/main.js index e5a3a7cb3a0d..95d955207380 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/line-length/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/line-length/lib/main.js @@ -22,13 +22,14 @@ var replace = require( '@stdlib/string/replace' ); var namespace = require( '@stdlib/namespace' ); +var format = require( '@stdlib/string/format' ); // VARIABLES // var NAMESPACE = namespace(); var MAX_LINE_LENGTH = 80; -var RE_OUTSIDE_ALIAS = /{{alias:([\s\S]+?)}}/g; +var RE_EXTERNAL_ALIAS = /{{alias:([\s\S]+?)}}/g; // FUNCTIONS // @@ -92,11 +93,11 @@ function main( context ) { lines = ast.raw.split( '\n' ); for ( i = 0; i < lines.length; i++ ) { line = lines[ i ]; - line = replace( line, RE_OUTSIDE_ALIAS, substituteAlias ); + line = replace( line, RE_EXTERNAL_ALIAS, substituteAlias ); if ( line.length > maxLength ) { - context.report( 'Lines must not exceed '+maxLength+' characters', { - 'start': i, - 'end': i + context.report( format( 'Lines must not exceed %d characters', maxLength ), { + 'start': ast.start + i, + 'end': ast.start + i }); } } diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/index.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/index.js index fca0b06fe4c7..c8acca786ea7 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/index.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Lint rule to enforce that packages in outside aliases are resolvable. +* Lint rule to enforce that aliased packages are resolvable. * * @module @stdlib/_tools/repl-txt/rules/resolvable-aliases * diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/main.js index cfcf108b33fb..2240b3ee3967 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/lib/main.js @@ -20,14 +20,14 @@ // MODULES // -var namespace = require( '@stdlib/namespace' ); +var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); var isNull = require( '@stdlib/assert/is-null' ); +var format = require( '@stdlib/string/format' ); // VARIABLES // -var NAMESPACE = namespace(); -var RE_OUTSIDE_ALIAS = /{{alias:([\s\S]+?)}}/g; +var RE_EXTERNAL_ALIAS = /{{alias:([\s\S]+?)}}/g; var RE_NEWLINE = /\r?\n/g; @@ -41,39 +41,21 @@ var RE_NEWLINE = /\r?\n/g; * @returns {PositiveInteger} number of lines */ function countLines( str ) { - return ( str.match( RE_NEWLINE ) || '' ).length + 1; -} - -/** -* Returns the REPL alias for a given package. -* -* @private -* @param {string} pkg - package path -* @returns {(string|null)} package alias -*/ -function pkg2alias( pkg ) { - var i; - - for ( i = 0; i < NAMESPACE.length; i++ ) { - if ( pkg === NAMESPACE[ i ].path ) { - return NAMESPACE[ i ].alias; - } - } - return null; + return ( str.match( RE_NEWLINE ) || '' ).length; } // MAIN // /** -* Rule for enforcing that packages in outside aliases are resolvable. +* Rule for enforcing that aliased packages are resolvable. * * @param {Context} context - lint context * @returns {Object} validators */ function main( context ) { /** - * Checks that all packages in aliases are resolvable. + * Checks that all aliased packages are resolvable. * * @private * @param {Object} ast - full AST @@ -85,19 +67,20 @@ function main( context ) { var line; var pos; - match = RE_OUTSIDE_ALIAS.exec( ast.raw ); + match = RE_EXTERNAL_ALIAS.exec( ast.raw ); while ( !isNull( match ) ) { alias = pkg2alias( match[ 1 ] ); if ( !alias ) { - substr = ast.raw.substring( 0, RE_OUTSIDE_ALIAS.lastIndex ); + substr = ast.raw.substring( 0, RE_EXTERNAL_ALIAS.lastIndex ); line = countLines( substr ); pos = { - 'start': line, - 'end': line + 'start': ast.start + line, + 'end': ast.start + line }; - context.report( match[ 1 ]+' does not map to any REPL alias', pos ); + context.report( format( '%s does not have an alias in the global REPL namespace', match[ 1 ] ), pos ); } - match = RE_OUTSIDE_ALIAS.exec( ast.raw ); + // Resolve the next match: + match = RE_EXTERNAL_ALIAS.exec( ast.raw ); } } return { diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/package.json b/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/package.json index d4d0d138cd9d..a24a07721cd4 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/package.json +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/resolvable-aliases/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/_tools/repl-txt/rules/resolvable-aliases", "version": "0.0.0", - "description": "Lint rule to enforce that packages in outside aliases are resolvable.", + "description": "Lint rule to enforce that aliased packages are resolvable.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-heading-style/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-heading-style/lib/main.js index 241b25f1a2f0..1aac873ee69b 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-heading-style/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-heading-style/lib/main.js @@ -21,6 +21,7 @@ // MODULES // var isCapitalized = require( '@stdlib/assert/is-capitalized' ); +var format = require( '@stdlib/string/format' ); // VARIABLES // @@ -59,10 +60,10 @@ function main( context ) { */ function sectionStyle( section ) { if ( !isCapitalized( section.title ) ) { - context.report( 'Section title "'+section.title+'" should be capitalized', section ); + context.report( format( 'Section title "%s" should be capitalized', section.title ), section ); } if ( countHyphens( section.rawTitle ) !== section.title.length ) { - context.report( 'Number of hyphens in the line following "'+section.title+'" must match the length of the title', section ); + context.report( format( 'Number of hyphens in the line following "%s" must match the length of the title', section.title ), section ); } } return { diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-order/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-order/lib/main.js index 75fc815a5519..19bedf951130 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-order/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/section-order/lib/main.js @@ -21,6 +21,7 @@ // MODULES // var indexOf = require( '@stdlib/utils/index-of' ); +var format = require( '@stdlib/string/format' ); // VARIABLES // @@ -61,7 +62,7 @@ function main( context ) { section = sections[ i ]; idx = indexOf( order, section.title ); if ( last !== void 0 && idx < last ) { - context.report( 'Sections have to be arranged in the following order: '+order.join( ', ' ), section ); + context.report( format( 'Sections have to be arranged in the following order: %s', order.join( ', ' ) ), section ); } last = idx; } diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/defaults.json b/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/defaults.json index bd35100545a1..968ace7a2abd 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/defaults.json +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/defaults.json @@ -7,6 +7,7 @@ "number", "integer", "string", + "symbol", "uinteger", "ndarray", "Array", @@ -16,28 +17,35 @@ "Boolean", "Buffer", "Complex", + "Complex32", "Complex64", "Complex128", + "ComplexLike", "Date", "Error", "Function", "Object", "ObjectLike", "Number", - "Plot", "RegExp", "SharedArrayBuffer", "String", "TypedArray", + "Complex32Array", + "Complex64Array", + "Complex128Array", + "Float16Array", "Float32Array", "Float64Array", "Int8Array", "Int16Array", "Int32Array", + "Int64Array", "Uint8ClampedArray", "Uint8Array", "Uint16Array", "Uint32Array", + "Uint64Array", "process", "Window" ] diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/edit_distance.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/edit_distance.js index b4b6dd29e98d..845e2c7a0561 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/edit_distance.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/edit_distance.js @@ -20,8 +20,8 @@ // MODULES // -var ndarray = require( '@stdlib/ndarray/array' ); -var min = require( '@stdlib/math/base/special/min' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var minn = require( '@stdlib/math/base/special/minn' ); // MAIN // @@ -31,7 +31,7 @@ var min = require( '@stdlib/math/base/special/min' ); * * ## Notes * -* - the edit distance between two strings is the number of insertions, deletions, character substitutions, as well as transpositions of adjacent characters to convert one of the strings into the other. +* - The edit distance between two strings is the number of insertions, deletions, character substitutions, as well as transpositions of adjacent characters to convert one of the strings into the other. * * [damerau-levenshtein]: https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance * @@ -54,9 +54,7 @@ function editDistance( word1, word2 ) { } m = word1.length; n = word2.length; - d = ndarray({ - 'shape': [ m+1, n+1 ] - }); + d = zeros( [ m+1, n+1 ] ); for ( i = 0; i <= m; i++ ) { d.set( i, 0, i ); } @@ -70,14 +68,14 @@ function editDistance( word1, word2 ) { } else { cost = 1; } - v = min( d.get(i-1, j)+1, d.get(i, j-1)+1, d.get(i-1, j-1)+cost ); + v = minn( d.get(i-1, j)+1, d.get(i, j-1)+1, d.get(i-1, j-1)+cost ); d.set( i, j, v ); if ( i > 1 && j > 1 && word1[ i-1 ] === word2[ j-2 ] && word1[ i-2 ] === word2[ j-1 ] ) { - v = min( d.get( i, j ), d.get( i-2, j-2 ) + cost ); + v = minn( d.get( i, j ), d.get( i-2, j-2 ) + cost ); d.set( i, j, v ); } } diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/main.js index 703a30a6bd2f..2091ba1f9dac 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/tag-typedef-typos/lib/main.js @@ -24,6 +24,7 @@ var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var indexOf = require( '@stdlib/utils/index-of' ); var copy = require( '@stdlib/utils/copy' ); var PINF = require( '@stdlib/constants/float64/pinf' ); +var format = require( '@stdlib/string/format' ); var editDistance = require( './edit_distance.js' ); var DEFAULTS = require( './defaults.json' ); @@ -75,7 +76,7 @@ function main( context ) { if ( type.name && indexOf( opts.types, type.name ) === -1 ) { correction = correctTypedef( type.name ); if ( correction ) { - context.report( '"'+type.name+'" type definition should be "'+correction+'"', section ); + context.report( format( '"%s" type definition should be "%s"', type.name, correction ), section ); } } } @@ -101,7 +102,7 @@ function main( context ) { if ( elem.name ) { correction = correctTypedef( elem.name ); if ( correction ) { - context.report( '"'+elem.name+'" type definition should be "'+correction+'"', section ); + context.report( format( '"%s" type definition should be "%s"', elem.name, correction ), section ); } } } @@ -117,11 +118,11 @@ function main( context ) { function checkTypedObject( val, section ) { var correction = correctTypedef( val.name ); if ( correction ) { - context.report( '"'+val.name+'" type definition should be "'+correction+'"', section ); + context.report( format( '"%s" type definition should be "%s"', val.name, correction ), section ); } correction = correctTypedef( val.of ); if ( correction ) { - context.report( '"'+val.of+'" type definition should be "'+correction+'"', section ); + context.report( format( '"%s" type definition should be "%s"', val.of, correction ), section ); } } diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/rules/whitelisted-sections/lib/main.js b/lib/node_modules/@stdlib/_tools/repl-txt/rules/whitelisted-sections/lib/main.js index e29fa5cb6df7..37d491f6a11f 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/rules/whitelisted-sections/lib/main.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/rules/whitelisted-sections/lib/main.js @@ -21,6 +21,7 @@ // MODULES // var indexOf = require( '@stdlib/utils/index-of' ); +var format = require( '@stdlib/string/format' ); // VARIABLES // @@ -54,7 +55,7 @@ function main( context ) { idx = indexOf( SECTIONS, section.title ); if ( idx === -1 ) { - context.report( 'Only use one of the following section header titles: '+SECTIONS.join( '\n' ), section ); + context.report( format( 'Only use one of the following section header titles: %s', SECTIONS.join( '\n' ) ), section ); } } return { diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/validate/README.md b/lib/node_modules/@stdlib/_tools/repl-txt/validate/README.md index a5d9540a46ca..1c4b26444d47 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/validate/README.md +++ b/lib/node_modules/@stdlib/_tools/repl-txt/validate/README.md @@ -42,7 +42,7 @@ var isValid = require( '@stdlib/_tools/repl-txt/validate' ); #### isValid( repl ) -Validates a `repl.txt` file. `errors` and `warnings` arrays are attached to the function after each invocation, which contain the errors and warnings encountered when linting the `repl.txt` file, respectively. +Validates a `repl.txt` file. ```javascript var repl = [ @@ -73,6 +73,8 @@ var warn = isValid.warnings; // returns || null ``` +After each invocation, `errors` and `warnings` arrays are attached to the function. These arrays contain the errors and warnings encountered when linting the `repl.txt` file. + @@ -81,7 +83,7 @@ var warn = isValid.warnings;
-- The function looks for a `.rtlintrc` configuration file in the current working directory or its parent directories; if no such file is found, the function throws an error. +- The function looks for a `.rtlintrc` configuration file in the current working directory or its parent directories; if no such file is found, the function raises an exception.
@@ -93,6 +95,8 @@ var warn = isValid.warnings; ## Examples + + ```javascript @@ -147,7 +151,9 @@ Options: ### Notes -- If successful, the program prints `true` to `stdout`. If not successful, the program prints validation errors to `stderr`. +- If successful, the program prints `true` to `stdout`. +- If not successful, the program prints validation errors to `stderr`. +- The program prints validation warnings to `stderr`. diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/validate/bin/cli b/lib/node_modules/@stdlib/_tools/repl-txt/validate/bin/cli index 026e3dc74a05..75d8de84cff3 100755 --- a/lib/node_modules/@stdlib/_tools/repl-txt/validate/bin/cli +++ b/lib/node_modules/@stdlib/_tools/repl-txt/validate/bin/cli @@ -94,6 +94,9 @@ function main() { */ function next() { var bool = validate( repl ); + if ( validate.warnings ) { + console.warn( validate.warnings ); // eslint-disable-line no-console + } if ( bool ) { console.log( true ); // eslint-disable-line no-console } else { diff --git a/lib/node_modules/@stdlib/_tools/repl-txt/validate/test/test.js b/lib/node_modules/@stdlib/_tools/repl-txt/validate/test/test.js index 0c026dfaa6be..f6646a3014be 100644 --- a/lib/node_modules/@stdlib/_tools/repl-txt/validate/test/test.js +++ b/lib/node_modules/@stdlib/_tools/repl-txt/validate/test/test.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable n/no-sync */ + 'use strict'; // MODULES // diff --git a/lib/node_modules/@stdlib/array/base/assert/contains/package.json b/lib/node_modules/@stdlib/array/base/assert/contains/package.json index 62e2812c15ac..68420e99ac12 100644 --- a/lib/node_modules/@stdlib/array/base/assert/contains/package.json +++ b/lib/node_modules/@stdlib/array/base/assert/contains/package.json @@ -56,8 +56,10 @@ "structure", "array", "generic", + "test", "contains", "search", - "assert" + "assert", + "validate" ] } diff --git a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/package.json b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/package.json index 7fe5f635babb..2e6045938eea 100644 --- a/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/package.json +++ b/lib/node_modules/@stdlib/array/base/assert/is-sorted-ascending/package.json @@ -56,9 +56,11 @@ "structure", "array", "generic", + "test", "sorted", "ascending", "ordered", - "assert" + "assert", + "validate" ] } diff --git a/lib/node_modules/@stdlib/array/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/docs/types/index.d.ts index bcefafd0448e..62c83525bdf3 100644 --- a/lib/node_modules/@stdlib/array/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/docs/types/index.d.ts @@ -2133,6 +2133,7 @@ interface Namespace { * * - `float64`: double-precision floating-point numbers (IEEE 754) * - `float32`: single-precision floating-point numbers (IEEE 754) + * - `float16`: half-precision floating-point numbers (IEEE 754) * - `complex128`: double-precision complex floating-point numbers * - `complex64`: single-precision complex floating-point numbers * - `int32`: 32-bit two's complement signed integers diff --git a/lib/node_modules/@stdlib/array/float16/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/float16/docs/types/index.d.ts index ff6c0d6fd1b3..e75c82558021 100644 --- a/lib/node_modules/@stdlib/array/float16/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/float16/docs/types/index.d.ts @@ -23,7 +23,7 @@ /// import { Iterator as Iter, IterableIterator, TypedIterator } from '@stdlib/types/iter'; -import { ArrayLike } from '@stdlib/types/array'; +import { ArrayLike, Float16Array as Float16ArrayInterface } from '@stdlib/types/array'; import ArrayBuffer = require( '@stdlib/array/buffer' ); // Define a union type representing both iterable and non-iterable iterators: @@ -272,7 +272,7 @@ type CompareFcn = ( a: number, b: number ) => number; /** * Class for creating a half-precision floating-point number array. */ -declare class Float16Array { +declare class Float16Array implements Float16ArrayInterface { /** * Half-precision floating-point number array constructor. * @@ -340,6 +340,11 @@ declare class Float16Array { */ constructor( arg?: number | ArrayLike | ArrayBuffer | Iterable, byteOffset?: number, length?: number ); + /** + * Indexed properties. + */ + [ index: number ]: number; + /** * Returns an array element located at integer position (index) `i`, with support for both nonnegative and negative integer indices. * diff --git a/lib/node_modules/@stdlib/array/ones-like/README.md b/lib/node_modules/@stdlib/array/ones-like/README.md index f04e3bc6548c..9407436058dc 100644 --- a/lib/node_modules/@stdlib/array/ones-like/README.md +++ b/lib/node_modules/@stdlib/array/ones-like/README.md @@ -108,7 +108,7 @@ var onesLike = require( '@stdlib/array/ones-like' ); var x = zeros( 4, 'complex128' ); // Get a list of array data types: -var dt = dtypes(); +var dt = dtypes( 'numeric_and_generic' ); // Generate filled arrays... var y; diff --git a/lib/node_modules/@stdlib/array/ones-like/examples/index.js b/lib/node_modules/@stdlib/array/ones-like/examples/index.js index 91a4e5f9be35..608301b4f1a4 100644 --- a/lib/node_modules/@stdlib/array/ones-like/examples/index.js +++ b/lib/node_modules/@stdlib/array/ones-like/examples/index.js @@ -26,7 +26,7 @@ var onesLike = require( './../lib' ); var x = zeros( 4, 'complex128' ); // Get a list of array data types: -var dt = dtypes(); +var dt = dtypes( 'numeric_and_generic' ); // Generate filled arrays... var y; diff --git a/lib/node_modules/@stdlib/array/zero-to-like/README.md b/lib/node_modules/@stdlib/array/zero-to-like/README.md index 2a34888075c5..f902fd989f7a 100644 --- a/lib/node_modules/@stdlib/array/zero-to-like/README.md +++ b/lib/node_modules/@stdlib/array/zero-to-like/README.md @@ -53,6 +53,7 @@ The function recognizes the following data types: - `float64`: double-precision floating-point numbers (IEEE 754) - `float32`: single-precision floating-point numbers (IEEE 754) +- `float16`: half-precision floating-point numbers (IEEE 754) - `complex128`: double-precision complex floating-point numbers - `complex64`: single-precision complex floating-point numbers - `int32`: 32-bit two's complement signed integers diff --git a/lib/node_modules/@stdlib/array/zero-to-like/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/zero-to-like/benchmark/benchmark.js index fcdeb20f683d..d5992a57b7b0 100644 --- a/lib/node_modules/@stdlib/array/zero-to-like/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/zero-to-like/benchmark/benchmark.js @@ -97,6 +97,28 @@ bench( format( '%s:dtype=float32', pkg ), function benchmark( b ) { b.end(); }); +bench( format( '%s:dtype=float16', pkg ), function benchmark( b ) { + var arr; + var x; + var i; + + x = empty( 0, 'float16' ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = zeroToLike( x ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isTypedArrayLike( arr ) ) { + b.fail( 'should return a typed array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + bench( format( '%s:dtype=complex128', pkg ), function benchmark( b ) { var arr; var x; diff --git a/lib/node_modules/@stdlib/array/zero-to-like/benchmark/benchmark.length.float16.js b/lib/node_modules/@stdlib/array/zero-to-like/benchmark/benchmark.length.float16.js new file mode 100644 index 000000000000..85efdc3e62c6 --- /dev/null +++ b/lib/node_modules/@stdlib/array/zero-to-like/benchmark/benchmark.length.float16.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isTypedArray = require( '@stdlib/assert/is-typed-array' ); +var empty = require( '@stdlib/array/empty' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zeroToLike = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = empty( len, 'float16' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = zeroToLike( x ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isTypedArray( arr ) ) { + b.fail( 'should return a typed array' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=float16,len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/zero-to-like/docs/repl.txt b/lib/node_modules/@stdlib/array/zero-to-like/docs/repl.txt index 6c86b632d725..50d5710857b0 100644 --- a/lib/node_modules/@stdlib/array/zero-to-like/docs/repl.txt +++ b/lib/node_modules/@stdlib/array/zero-to-like/docs/repl.txt @@ -8,6 +8,7 @@ - float64: double-precision floating-point numbers (IEEE 754). - float32: single-precision floating-point numbers (IEEE 754). + - float16: half-precision floating-point numbers (IEEE 754). - complex128: double-precision complex floating-point numbers. - complex64: single-precision complex floating-point numbers. - int32: 32-bit two's complement signed integers. diff --git a/lib/node_modules/@stdlib/array/zero-to-like/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/zero-to-like/docs/types/index.d.ts index 88f15b241ca5..3a267b3bd973 100644 --- a/lib/node_modules/@stdlib/array/zero-to-like/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/zero-to-like/docs/types/index.d.ts @@ -20,7 +20,7 @@ /// -import { Complex128Array, Complex64Array, AnyArray, NumericDataType } from '@stdlib/types/array'; +import { Complex128Array, Complex64Array, Float16Array, AnyArray, NumericDataType } from '@stdlib/types/array'; /** * Generates a linearly spaced numeric array whose elements increment by 1 starting from zero and having the same length as a provided input array. @@ -58,6 +58,24 @@ declare function zeroToLike( x: AnyArray, dtype: 'float64' ): Float64Array; */ declare function zeroToLike( x: AnyArray, dtype: 'float32' ): Float32Array; +/** +* Generates a linearly spaced numeric array whose elements increment by 1 starting from zero and having the same length as a provided input array. +* +* @param x - input array from which to derive the output array length +* @param dtype - data type +* @returns linearly spaced numeric array +* +* @example +* var zeros = require( '@stdlib/array/zeros' ); +* +* var x = zeros( 2, 'float64' ); +* // returns [ 0.0, 0.0 ] +* +* var y = zeroToLike( x, 'float16' ); +* // returns [ 0.0, 1.0 ] +*/ +declare function zeroToLike( x: AnyArray, dtype: 'float16' ): Float16Array; + /** * Generates a linearly spaced numeric array whose elements increment by 1 starting from zero and having the same length as a provided input array. * @@ -282,6 +300,24 @@ declare function zeroToLike( x: Float64Array, dtype?: NumericDataType ): Float64 */ declare function zeroToLike( x: Float32Array, dtype?: NumericDataType ): Float32Array; +/** +* Generates a linearly spaced numeric array whose elements increment by 1 starting from zero and having the same length and data type as a provided input array. +* +* @param x - input array from which to derive the output array length +* @param dtype - data type +* @returns linearly spaced numeric array +* +* @example +* var zeros = require( '@stdlib/array/zeros' ); +* +* var x = zeros( 2, 'float16' ); +* // returns [ 0.0, 0.0 ] +* +* var y = zeroToLike( x ); +* // returns [ 0.0, 1.0 ] +*/ +declare function zeroToLike( x: Float16Array, dtype?: NumericDataType ): Float16Array; + /** * Generates a linearly spaced numeric array whose elements increment by 1 starting from zero and having the same length and data type as a provided input array. * diff --git a/lib/node_modules/@stdlib/array/zero-to-like/docs/types/test.ts b/lib/node_modules/@stdlib/array/zero-to-like/docs/types/test.ts index f79d23af271f..0778c615e195 100644 --- a/lib/node_modules/@stdlib/array/zero-to-like/docs/types/test.ts +++ b/lib/node_modules/@stdlib/array/zero-to-like/docs/types/test.ts @@ -18,6 +18,7 @@ import Complex128Array = require( '@stdlib/array/complex128' ); import Complex64Array = require( '@stdlib/array/complex64' ); +import Float16Array = require( '@stdlib/array/float16' ); import zeroToLike = require( './index' ); @@ -28,6 +29,7 @@ import zeroToLike = require( './index' ); zeroToLike( [ 0, 0 ] ); // $ExpectType number[] zeroToLike( new Float64Array( [ 0, 0 ] ) ); // $ExpectType Float64Array zeroToLike( new Float32Array( [ 0, 0 ] ) ); // $ExpectType Float32Array + zeroToLike( new Float16Array( [ 0, 0 ] ) ); // $ExpectType Float16ArrayFallback zeroToLike( new Complex128Array( [ 0, 0 ] ) ); // $ExpectType Complex128Array zeroToLike( new Complex64Array( [ 0, 0 ] ) ); // $ExpectType Complex64Array zeroToLike( new Int32Array( [ 0, 0 ] ) ); // $ExpectType Int32Array @@ -40,6 +42,7 @@ import zeroToLike = require( './index' ); zeroToLike( [ 0, 0 ], 'float64' ); // $ExpectType Float64Array zeroToLike( [ 0, 0 ], 'float32' ); // $ExpectType Float32Array + zeroToLike( [ 0, 0 ], 'float16' ); // $ExpectType Float16ArrayFallback zeroToLike( [ 0, 0 ], 'complex128' ); // $ExpectType Complex128Array zeroToLike( [ 0, 0 ], 'complex64' ); // $ExpectType Complex64Array zeroToLike( [ 0, 0 ], 'int32' ); // $ExpectType Int32Array diff --git a/lib/node_modules/@stdlib/array/zero-to-like/package.json b/lib/node_modules/@stdlib/array/zero-to-like/package.json index ab0d2129a5a2..c9fd7695e680 100644 --- a/lib/node_modules/@stdlib/array/zero-to-like/package.json +++ b/lib/node_modules/@stdlib/array/zero-to-like/package.json @@ -63,6 +63,7 @@ "matrix", "float64array", "float32array", + "float16array", "int32array", "uint32array", "int16array", @@ -83,6 +84,8 @@ "single", "float", "single-precision", + "half", + "half-precision", "float32", "ieee754", "integer", diff --git a/lib/node_modules/@stdlib/array/zero-to-like/test/test.js b/lib/node_modules/@stdlib/array/zero-to-like/test/test.js index e755a8611999..9b89c0c5fc8a 100644 --- a/lib/node_modules/@stdlib/array/zero-to-like/test/test.js +++ b/lib/node_modules/@stdlib/array/zero-to-like/test/test.js @@ -23,6 +23,7 @@ var tape = require( 'tape' ); var Float64Array = require( '@stdlib/array/float64' ); var Float32Array = require( '@stdlib/array/float32' ); +var Float16Array = require( '@stdlib/array/float16' ); var Int32Array = require( '@stdlib/array/int32' ); var Uint32Array = require( '@stdlib/array/uint32' ); var Int16Array = require( '@stdlib/array/int16' ); @@ -203,6 +204,38 @@ tape( 'the function returns a filled array (dtype=float32)', function test( t ) t.end(); }); +tape( 'the function returns a filled array (float16)', function test( t ) { + var expected; + var arr; + var x; + + x = new Float16Array( 5 ); + expected = new Float16Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); + + arr = zeroToLike( x ); + t.strictEqual( instanceOf( arr, Float16Array ), true, 'returns expected value' ); + t.strictEqual( arr.length, expected.length, 'returns expected value' ); + t.deepEqual( arr, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a filled array (dtype=float16)', function test( t ) { + var expected; + var arr; + var x; + + x = new Float64Array( 5 ); + expected = new Float16Array( [ 0.0, 1.0, 2.0, 3.0, 4.0 ] ); + + arr = zeroToLike( x, 'float16' ); + t.strictEqual( instanceOf( arr, Float16Array ), true, 'returns expected value' ); + t.strictEqual( arr.length, expected.length, 'returns expected value' ); + t.deepEqual( arr, expected, 'returns expected value' ); + + t.end(); +}); + tape( 'the function returns a filled array (complex128)', function test( t ) { var expected; var arr; diff --git a/lib/node_modules/@stdlib/array/zeros-like/README.md b/lib/node_modules/@stdlib/array/zeros-like/README.md index 6aaa36823d30..ae70339f2f77 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/README.md +++ b/lib/node_modules/@stdlib/array/zeros-like/README.md @@ -55,6 +55,7 @@ The function supports the following data types: - `float64`: double-precision floating-point numbers (IEEE 754) - `float32`: single-precision floating-point numbers (IEEE 754) +- `float16`: half-precision floating-point numbers (IEEE 754) - `complex128`: double-precision complex floating-point numbers - `complex64`: single-precision complex floating-point numbers - `int32`: 32-bit two's complement signed integers @@ -104,7 +105,7 @@ var zerosLike = require( '@stdlib/array/zeros-like' ); var x = zeros( 4, 'complex128' ); // Get a list of array data types: -var dt = dtypes(); +var dt = dtypes( 'numeric' ); // Generate additional zero-filled arrays... var y; diff --git a/lib/node_modules/@stdlib/array/zeros-like/benchmark/benchmark.js b/lib/node_modules/@stdlib/array/zeros-like/benchmark/benchmark.js index 3acb1308fb3a..a21da304ef69 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/array/zeros-like/benchmark/benchmark.js @@ -97,6 +97,28 @@ bench( format( '%s:dtype=float32', pkg ), function benchmark( b ) { b.end(); }); +bench( format( '%s:dtype=float16', pkg ), function benchmark( b ) { + var arr; + var x; + var i; + + x = empty( 0, 'float16' ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = zerosLike( x ); + if ( arr.length !== 0 ) { + b.fail( 'should have length 0' ); + } + } + b.toc(); + if ( !isTypedArrayLike( arr ) ) { + b.fail( 'should return a typed array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + bench( format( '%s:dtype=complex128', pkg ), function benchmark( b ) { var arr; var x; diff --git a/lib/node_modules/@stdlib/array/zeros-like/benchmark/benchmark.length.float16.js b/lib/node_modules/@stdlib/array/zeros-like/benchmark/benchmark.length.float16.js new file mode 100644 index 000000000000..cffd1ce27f8e --- /dev/null +++ b/lib/node_modules/@stdlib/array/zeros-like/benchmark/benchmark.length.float16.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isTypedArray = require( '@stdlib/assert/is-typed-array' ); +var empty = require( '@stdlib/array/empty' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zerosLike = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = empty( len, 'float16' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var arr; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + arr = zerosLike( x ); + if ( arr.length !== len ) { + b.fail( 'unexpected length' ); + } + } + b.toc(); + if ( !isTypedArray( arr ) ) { + b.fail( 'should return a typed array' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=float16,len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/array/zeros-like/docs/repl.txt b/lib/node_modules/@stdlib/array/zeros-like/docs/repl.txt index 4bb0bc0d52b7..ec3d73af0db5 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/docs/repl.txt +++ b/lib/node_modules/@stdlib/array/zeros-like/docs/repl.txt @@ -7,6 +7,7 @@ - float64: double-precision floating-point numbers (IEEE 754). - float32: single-precision floating-point numbers (IEEE 754). + - float16: half-precision floating-point numbers (IEEE 754). - complex128: double-precision complex floating-point numbers. - complex64: single-precision complex floating-point numbers. - int32: 32-bit two's complement signed integers. diff --git a/lib/node_modules/@stdlib/array/zeros-like/docs/types/index.d.ts b/lib/node_modules/@stdlib/array/zeros-like/docs/types/index.d.ts index dc82b05ba5d8..75d4f5946803 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/array/zeros-like/docs/types/index.d.ts @@ -31,13 +31,13 @@ import { NumericAndGenericDataTypeMap, AnyArray, TypedArray, ComplexTypedArray } * @example * var zeros = require( '@stdlib/array/zeros' ); * -* var x = zeros( 2, 'generic' ); -* // returns [ 0, 0 ] +* var x = zeros( 2, 'float64' ); +* // returns [ 0.0, 0.0 ] * * var y = zerosLike( x ); -* // returns [ 0, 0 ] +* // returns [ 0.0, 0.0 ] */ -declare function zerosLike( x: Array ): Array; +declare function zerosLike( x: T ): T; /** * Creates a zero-filled array having the same length and data type as a provided input array. @@ -48,13 +48,13 @@ declare function zerosLike( x: Array ): Array; * @example * var zeros = require( '@stdlib/array/zeros' ); * -* var x = zeros( 2, 'float64' ); -* // returns [ 0.0, 0.0 ] +* var x = zeros( 2, 'generic' ); +* // returns [ 0, 0 ] * * var y = zerosLike( x ); -* // returns [ 0.0, 0.0 ] +* // returns [ 0, 0 ] */ -declare function zerosLike( x: T ): T; +declare function zerosLike( x: Array ): Array; /** * Creates a zero-filled array having the same length as a provided input array. @@ -63,6 +63,7 @@ declare function zerosLike( x: T ): T; * * - `float64`: double-precision floating-point numbers (IEEE 754) * - `float32`: single-precision floating-point numbers (IEEE 754) +* - `float16`: half-precision floating-point numbers (IEEE 754) * - `complex128`: double-precision complex floating-point numbers * - `complex64`: single-precision complex floating-point numbers * - `int32`: 32-bit two's complement signed integers diff --git a/lib/node_modules/@stdlib/array/zeros-like/docs/types/test.ts b/lib/node_modules/@stdlib/array/zeros-like/docs/types/test.ts index 51064dda33e2..d3c9f636fad9 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/docs/types/test.ts +++ b/lib/node_modules/@stdlib/array/zeros-like/docs/types/test.ts @@ -18,6 +18,7 @@ import Complex128Array = require( '@stdlib/array/complex128' ); import Complex64Array = require( '@stdlib/array/complex64' ); +import Float16Array = require( '@stdlib/array/float16' ); import zerosLike = require( './index' ); @@ -28,6 +29,7 @@ import zerosLike = require( './index' ); zerosLike( [ 0, 0 ] ); // $ExpectType number[] zerosLike( new Float64Array( [ 0, 0 ] ) ); // $ExpectType Float64Array zerosLike( new Float32Array( [ 0, 0 ] ) ); // $ExpectType Float32Array + zerosLike( new Float16Array( [ 0, 0 ] ) ); // $ExpectType Float16ArrayFallback zerosLike( new Complex128Array( [ 0, 0 ] ) ); // $ExpectType Complex128Array zerosLike( new Complex64Array( [ 0, 0 ] ) ); // $ExpectType Complex64Array zerosLike( new Int32Array( [ 0, 0 ] ) ); // $ExpectType Int32Array @@ -41,6 +43,7 @@ import zerosLike = require( './index' ); zerosLike( [ 0, 0 ], 'float64' ); // $ExpectType Float64Array zerosLike( [ 0, 0 ], 'float32' ); // $ExpectType Float32Array + zerosLike( [ 0, 0 ], 'float16' ); // $ExpectType Float16ArrayFallback zerosLike( [ 0, 0 ], 'complex128' ); // $ExpectType Complex128Array zerosLike( [ 0, 0 ], 'complex64' ); // $ExpectType Complex64Array zerosLike( [ 0, 0 ], 'int32' ); // $ExpectType Int32Array diff --git a/lib/node_modules/@stdlib/array/zeros-like/examples/index.js b/lib/node_modules/@stdlib/array/zeros-like/examples/index.js index e7e586956bc4..efe558239b50 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/examples/index.js +++ b/lib/node_modules/@stdlib/array/zeros-like/examples/index.js @@ -26,7 +26,7 @@ var zerosLike = require( './../lib' ); var x = zeros( 4, 'complex128' ); // Get a list of array data types: -var dt = dtypes(); +var dt = dtypes( 'numeric' ); // Generate additional zero-filled arrays... var y; diff --git a/lib/node_modules/@stdlib/array/zeros-like/package.json b/lib/node_modules/@stdlib/array/zeros-like/package.json index e1bf6c35befd..2d4f6f6a0ce1 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/package.json +++ b/lib/node_modules/@stdlib/array/zeros-like/package.json @@ -63,6 +63,7 @@ "matrix", "float64array", "float32array", + "float16array", "int32array", "uint32array", "int16array", @@ -84,6 +85,9 @@ "float", "single-precision", "float32", + "half", + "half-precision", + "float16", "ieee754", "integer", "int32", diff --git a/lib/node_modules/@stdlib/array/zeros-like/test/test.js b/lib/node_modules/@stdlib/array/zeros-like/test/test.js index 8587b9803551..676df125c652 100644 --- a/lib/node_modules/@stdlib/array/zeros-like/test/test.js +++ b/lib/node_modules/@stdlib/array/zeros-like/test/test.js @@ -23,6 +23,7 @@ var tape = require( 'tape' ); var Float64Array = require( '@stdlib/array/float64' ); var Float32Array = require( '@stdlib/array/float32' ); +var Float16Array = require( '@stdlib/array/float16' ); var Int32Array = require( '@stdlib/array/int32' ); var Uint32Array = require( '@stdlib/array/uint32' ); var Int16Array = require( '@stdlib/array/int16' ); @@ -203,6 +204,38 @@ tape( 'the function returns a zero-filled array (dtype=float32)', function test( t.end(); }); +tape( 'the function returns a zero-filled array (float16)', function test( t ) { + var expected; + var arr; + var x; + + x = new Float16Array( 5 ); + expected = new Float16Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + arr = zerosLike( x ); + t.strictEqual( instanceOf( arr, Float16Array ), true, 'returns expected value' ); + t.strictEqual( arr.length, expected.length, 'returns expected value' ); + t.deepEqual( arr, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a zero-filled array (dtype=float16)', function test( t ) { + var expected; + var arr; + var x; + + x = new Float64Array( 5 ); + expected = new Float16Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + arr = zerosLike( x, 'float16' ); + t.strictEqual( instanceOf( arr, Float16Array ), true, 'returns expected value' ); + t.strictEqual( arr.length, expected.length, 'returns expected value' ); + t.deepEqual( arr, expected, 'returns expected value' ); + + t.end(); +}); + tape( 'the function returns a zero-filled array (complex128)', function test( t ) { var expected; var arr; diff --git a/lib/node_modules/@stdlib/assert/README.md b/lib/node_modules/@stdlib/assert/README.md index c25480dc80d7..ab869ca4ee6f 100644 --- a/lib/node_modules/@stdlib/assert/README.md +++ b/lib/node_modules/@stdlib/assert/README.md @@ -458,6 +458,7 @@ The remaining namespace utilities are as follows: - [`isHexString( value )`][@stdlib/assert/is-hex-string]: test whether a string contains only hexadecimal digits. - [`isInfinite( value )`][@stdlib/assert/is-infinite]: test if a value is an infinite number. - [`isInheritedProperty( value, property )`][@stdlib/assert/is-inherited-property]: test if an object has an inherited property. +- [`isInt64( value )`][@stdlib/assert/is-int64]: test if a value is a 64-bit signed integer. - [`isIterableLike( value )`][@stdlib/assert/is-iterable-like]: test if a value is `iterable`-like. - [`isIteratorLike( value )`][@stdlib/assert/is-iterator-like]: test if a value is `iterator`-like. - [`isJSON( value )`][@stdlib/assert/is-json]: test if a value is a parseable JSON string. @@ -693,6 +694,8 @@ console.log( objectKeys( assert ) ); [@stdlib/assert/is-inherited-property]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-inherited-property +[@stdlib/assert/is-int64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-int64 + [@stdlib/assert/is-iterable-like]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-iterable-like [@stdlib/assert/is-iterator-like]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/assert/is-iterator-like diff --git a/lib/node_modules/@stdlib/assert/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/docs/types/index.d.ts index 8e8864ee9303..c94b8ab60740 100644 --- a/lib/node_modules/@stdlib/assert/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/assert/docs/types/index.d.ts @@ -202,6 +202,7 @@ import isInheritedProperty = require( '@stdlib/assert/is-inherited-property' ); import isInt8Array = require( '@stdlib/assert/is-int8array' ); import isInt16Array = require( '@stdlib/assert/is-int16array' ); import isInt32Array = require( '@stdlib/assert/is-int32array' ); +import isInt64 = require( '@stdlib/assert/is-int64' ); import isInteger = require( '@stdlib/assert/is-integer' ); import isIntegerArray = require( '@stdlib/assert/is-integer-array' ); import isIterableLike = require( '@stdlib/assert/is-iterable-like' ); @@ -4291,6 +4292,22 @@ interface Namespace { */ isInt32Array: typeof isInt32Array; + /** + * Tests if a value is a 64-bit signed integer. + * + * @param value - value to test + * @returns boolean indicating if a value is a 64-bit signed integer + * + * @example + * var Int64 = require( '@stdlib/number/int64/ctor' ); + * + * var x = new Int64( 1234 ); + * + * var bool = ns.isInt64( x ); + * // returns true + */ + isInt64: typeof isInt64; + /** * Tests if a value is an integer. * diff --git a/lib/node_modules/@stdlib/assert/has-symbol-support/lib/main.js b/lib/node_modules/@stdlib/assert/has-symbol-support/lib/main.js index 79bd6d16446d..95855fdbbbde 100644 --- a/lib/node_modules/@stdlib/assert/has-symbol-support/lib/main.js +++ b/lib/node_modules/@stdlib/assert/has-symbol-support/lib/main.js @@ -31,8 +31,8 @@ */ function hasSymbolSupport() { return ( - typeof Symbol === 'function' && - typeof Symbol( 'foo' ) === 'symbol' + typeof Symbol === 'function' && // eslint-disable-line stdlib/require-globals + typeof Symbol( 'foo' ) === 'symbol' // eslint-disable-line stdlib/require-globals ); } diff --git a/lib/node_modules/@stdlib/assert/is-int64/README.md b/lib/node_modules/@stdlib/assert/is-int64/README.md new file mode 100644 index 000000000000..6323d166a952 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/README.md @@ -0,0 +1,98 @@ + + +# isInt64 + +> Test if a value is a [64-bit signed integer][@stdlib/number/int64/ctor]. + +
+ +## Usage + +```javascript +var isInt64 = require( '@stdlib/assert/is-int64' ); +``` + +#### isInt64( value ) + +Tests if a value is a [64-bit signed integer][@stdlib/number/int64/ctor]. + +```javascript +var Int64 = require( '@stdlib/number/int64/ctor' ); + +var x = new Int64( 1234 ); + +var bool = isInt64( x ); +// returns true +``` + +
+ + + +
+ +## Examples + + + +```javascript +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var Int64 = require( '@stdlib/number/int64/ctor' ); +var isInt64 = require( '@stdlib/assert/is-int64' ); + +console.log( isInt64( new Int64( 1234 ) ) ); +// => true + +console.log( isInt64( new Complex128( 3.0, 1.0 ) ) ); +// => false + +console.log( isInt64( {} ) ); +// => false + +console.log( isInt64( null ) ); +// => false +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/number/int64/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/number/int64/ctor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/assert/is-int64/benchmark/benchmark.js b/lib/node_modules/@stdlib/assert/is-int64/benchmark/benchmark.js new file mode 100644 index 000000000000..d3543088f3ee --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/benchmark/benchmark.js @@ -0,0 +1,88 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive; +var Int64 = require( '@stdlib/number/int64/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var isInt64 = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::true', pkg ), function benchmark( b ) { + var values; + var bool; + var i; + + values = [ + new Int64( 1234 ), + new Int64( 5678 ), + new Int64( 9012 ), + new Int64( 3456 ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + bool = isInt64( values[ i%values.length ] ); + if ( typeof bool !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( bool ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::false', pkg ), function benchmark( b ) { + var values; + var bool; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + [], + {} + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + bool = isInt64( values[ i%values.length ] ); + if ( typeof bool !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( !isBoolean( bool ) ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/assert/is-int64/docs/repl.txt b/lib/node_modules/@stdlib/assert/is-int64/docs/repl.txt new file mode 100644 index 000000000000..5018ced0e666 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( value ) + Tests if a value is a 64-bit signed integer. + + Parameters + ---------- + value: any + Value to test. + + Returns + ------- + bool: boolean + Boolean indicating whether a value is a 64-bit signed integer. + + Examples + -------- + > var bool = {{alias}}( new {{alias:@stdlib/number/int64/ctor}}( 1234 ) ) + true + > bool = {{alias}}( new {{alias:@stdlib/complex/float64/ctor}}( 3.0, 1.0 ) ) + false + > bool = {{alias}}( 3.14 ) + false + > bool = {{alias}}( {} ) + false + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/assert/is-int64/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-int64/docs/types/index.d.ts new file mode 100644 index 000000000000..3c6b5cf63223 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/docs/types/index.d.ts @@ -0,0 +1,44 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Int64 } from '@stdlib/types/number'; + +/** +* Tests if a value is a 64-bit signed integer. +* +* @param value - value to test +* @returns boolean indicating if a value is a 64-bit signed integer +* +* @example +* var Int64 = require( '@stdlib/number/int64/ctor' ); +* +* var x = new Int64( 1234 ); +* +* var bool = isInt64( x ); +* // returns true +*/ +declare function isInt64( value: any ): value is Int64; + + +// EXPORTS // + +export = isInt64; diff --git a/lib/node_modules/@stdlib/assert/is-int64/docs/types/test.ts b/lib/node_modules/@stdlib/assert/is-int64/docs/types/test.ts new file mode 100644 index 000000000000..bdd4c366a136 --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/docs/types/test.ts @@ -0,0 +1,38 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import Int64 = require( '@stdlib/number/int64/ctor' ); +import isInt64 = require( '@stdlib/assert/is-int64' ); + + +// TESTS // + +// The function returns a boolean... +{ + isInt64( new Int64( 1234 ) ); // $ExpectType boolean + isInt64( new Complex128( 5.0, 3.0 ) ); // $ExpectType boolean + isInt64( {} ); // $ExpectType boolean + isInt64( 123 ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + isInt64(); // $ExpectError + isInt64( new Int64( 1234 ), 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/assert/is-int64/examples/index.js b/lib/node_modules/@stdlib/assert/is-int64/examples/index.js new file mode 100644 index 000000000000..10eec6df104d --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var Int64 = require( '@stdlib/number/int64/ctor' ); +var isInt64 = require( './../lib' ); + +console.log( isInt64( new Int64( 1234 ) ) ); +// => true + +console.log( isInt64( new Complex128( 3.0, 1.0 ) ) ); +// => false + +console.log( isInt64( {} ) ); +// => false + +console.log( isInt64( null ) ); +// => false diff --git a/lib/node_modules/@stdlib/assert/is-int64/lib/index.js b/lib/node_modules/@stdlib/assert/is-int64/lib/index.js new file mode 100644 index 000000000000..efd42bd9c81c --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test if a value is a 64-bit signed integer. +* +* @module @stdlib/assert/is-int64 +* +* @example +* var Int64 = require( '@stdlib/number/int64/ctor' ); +* var isInt64 = require( '@stdlib/assert/is-int64' ); +* +* var x = new Int64( 1234 ); +* +* var bool = isInt64( x ); +* // returns true +*/ + +// MODULES // + +var isInt64 = require( './main.js' ); + + +// EXPORTS // + +module.exports = isInt64; diff --git a/lib/node_modules/@stdlib/assert/is-int64/lib/main.js b/lib/node_modules/@stdlib/assert/is-int64/lib/main.js new file mode 100644 index 000000000000..665d6b60e36e --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var Int64 = require( '@stdlib/number/int64/ctor' ); +var constructorName = require( '@stdlib/utils/constructor-name' ); + + +// MAIN // + +/** +* Tests if a value is a 64-bit signed integer. +* +* @param {*} value - value to test +* @returns {boolean} boolean indicating if a value is a 64-bit signed integer +* +* @example +* var Int64 = require( '@stdlib/number/int64/ctor' ); +* +* var x = new Int64( 1234 ); +* +* var bool = isInt64( x ); +* // returns true +*/ +function isInt64( value ) { + return ( + value instanceof Int64 || + constructorName( value ) === 'Int64' + ); +} + + +// EXPORTS // + +module.exports = isInt64; diff --git a/lib/node_modules/@stdlib/assert/is-int64/package.json b/lib/node_modules/@stdlib/assert/is-int64/package.json new file mode 100644 index 000000000000..d45b6238185f --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/assert/is-int64", + "version": "0.0.0", + "description": "Test if a value is a 64-bit signed integer.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdassert", + "assertion", + "assert", + "utilities", + "utility", + "utils", + "util", + "is", + "isint64", + "int64", + "signed", + "64-bit", + "integer", + "type", + "check", + "test", + "validate", + "isvalid", + "valid" + ] +} diff --git a/lib/node_modules/@stdlib/assert/is-int64/test/test.js b/lib/node_modules/@stdlib/assert/is-int64/test/test.js new file mode 100644 index 000000000000..6c30cde8d72a --- /dev/null +++ b/lib/node_modules/@stdlib/assert/is-int64/test/test.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Int64 = require( '@stdlib/number/int64/ctor' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var isInt64 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof isInt64, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `true` if provided a 64-bit signed integer', function test( t ) { + t.strictEqual( isInt64( new Int64( 1234 ) ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `false` if not provided a 64-bit signed integer', function test( t ) { + var values; + var i; + + values = [ + 5, + '5', + null, + void 0, + NaN, + true, + [], + {}, + new Complex128( 2.0, 2.0 ), + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( isInt64( values[i] ), false, 'returns false when provided '+values[i] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/assert/lib/index.js b/lib/node_modules/@stdlib/assert/lib/index.js index d4b6b0121624..c547d8240d79 100644 --- a/lib/node_modules/@stdlib/assert/lib/index.js +++ b/lib/node_modules/@stdlib/assert/lib/index.js @@ -1680,6 +1680,15 @@ setReadOnly( ns, 'isInt16Array', require( '@stdlib/assert/is-int16array' ) ); */ setReadOnly( ns, 'isInt32Array', require( '@stdlib/assert/is-int32array' ) ); +/** +* @name isInt64 +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/assert/is-int64} +*/ +setReadOnly( ns, 'isInt64', require( '@stdlib/assert/is-int64' ) ); + /** * @name isInteger * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/README.md b/lib/node_modules/@stdlib/blas/README.md index a401a45fe2b1..48271fe4cc39 100644 --- a/lib/node_modules/@stdlib/blas/README.md +++ b/lib/node_modules/@stdlib/blas/README.md @@ -45,12 +45,14 @@ The namespace contains the following:
+- [`asum( x[, options] )`][@stdlib/blas/asum]: compute the sum of absolute values (L1 norm) along one or more ndarray dimensions. - [`base`][@stdlib/blas/base]: base (i.e., lower-level) basic linear algebra subprograms (BLAS). - [`ddot( x, y[, dim] )`][@stdlib/blas/ddot]: calculate the dot product of two double-precision floating-point vectors. - [`dswap( x, y[, dim] )`][@stdlib/blas/dswap]: interchange two double-precision floating-point vectors. - [`ext`][@stdlib/blas/ext]: extended basic linear algebra subprograms (BLAS). - [`gdot( x, y )`][@stdlib/blas/gdot]: calculate the dot product of two vectors. - [`gswap( x, y )`][@stdlib/blas/gswap]: interchange two vectors. +- [`nrm2( x[, options] )`][@stdlib/blas/nrm2]: compute the L2-norm along one or more ndarray dimensions. - [`sdot( x, y[, dim] )`][@stdlib/blas/sdot]: calculate the dot product of two single-precision floating-point vectors. - [`sswap( x, y[, dim] )`][@stdlib/blas/sswap]: interchange two single-precision floating-point vectors. @@ -95,6 +97,8 @@ console.log( objectKeys( blas ) ); +[@stdlib/blas/asum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/asum + [@stdlib/blas/base]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base [@stdlib/blas/ddot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ddot @@ -107,6 +111,8 @@ console.log( objectKeys( blas ) ); [@stdlib/blas/gswap]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/gswap +[@stdlib/blas/nrm2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/nrm2 + [@stdlib/blas/sdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/sdot [@stdlib/blas/sswap]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/sswap diff --git a/lib/node_modules/@stdlib/blas/asum/README.md b/lib/node_modules/@stdlib/blas/asum/README.md new file mode 100644 index 000000000000..1a47208d1c15 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/README.md @@ -0,0 +1,232 @@ + + +# asum + +> Compute the sum of absolute values (L1 norm) along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. + +
+ +## Usage + +```javascript +var asum = require( '@stdlib/blas/asum' ); +``` + +#### asum( x\[, options] ) + +Computes the sum of absolute values (L1 norm) along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 1.0, -2.0, 2.0 ] ); + +var y = asum( x ); +// returns [ 5.0 ] +``` + +The function has the following parameters: + +- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. +- **options**: function options (_optional_). + +The function accepts the following options: + +- **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. +- **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be a real-valued floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. +- **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [ndarray][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`. + +By default, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform a reduction over specific dimensions, provide a `dims` option. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 3.0, 0.0, 4.0, 0.0 ], { + 'shape': [ 2, 2 ], + 'order': 'row-major' +}); +// returns [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] + +var y = asum( x, { + 'dims': [ 0 ] +}); +// returns [ 7.0, 0.0 ] + +y = asum( x, { + 'dims': [ 1 ] +}); +// returns [ 3.0, 4.0 ] + +y = asum( x, { + 'dims': [ 0, 1 ] +}); +// returns [ 7.0 ] +``` + +By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 3.0, 0.0, 4.0, 0.0 ], { + 'shape': [ 2, 2 ], + 'order': 'row-major' +}); +// returns [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] + +var y = asum( x, { + 'dims': [ 0 ], + 'keepdims': true +}); +// returns [ [ 7.0, 0.0 ] ] + +y = asum( x, { + 'dims': [ 1 ], + 'keepdims': true +}); +// returns [ [ 3.0 ], [ 4.0 ] ] + +y = asum( x, { + 'dims': [ 0, 1 ], + 'keepdims': true +}); +// returns [ [ 7.0 ] ] +``` + +By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. + +```javascript +var getDType = require( '@stdlib/ndarray/dtype' ); +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 1.0, -2.0, 2.0 ], { + 'dtype': 'generic' +}); + +var y = asum( x, { + 'dtype': 'float64' +}); +// returns [ 5.0 ] + +var dt = String( getDType( y ) ); +// returns 'float64' +``` + +#### asum.assign( x, out\[, options] ) + +Computes the sum of absolute values (L1 norm) along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor]. + +```javascript +var array = require( '@stdlib/ndarray/array' ); +var zeros = require( '@stdlib/ndarray/zeros' ); + +var x = array( [ 1.0, -2.0, 2.0 ] ); +var y = zeros( [] ); + +var out = asum.assign( x, y ); +// returns [ 5.0 ] + +var bool = ( out === y ); +// returns true +``` + +The method has the following parameters: + +- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. +- **out**: output [ndarray][@stdlib/ndarray/ctor]. +- **options**: function options (_optional_). + +The method accepts the following options: + +- **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. + +
+ + + +
+ +## Notes + +- Setting the `keepdims` option to `true` can be useful when wanting to ensure that the output [ndarray][@stdlib/ndarray/ctor] is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with ndarrays having the same shape as the input [ndarray][@stdlib/ndarray/ctor]. +- For complex-valued input [ndarrays][@stdlib/ndarray/ctor], the function computes the sum of the absolute values of the real and imaginary components (i.e., the sum of `|Re(z)| + |Im(z)|` over all elements). +- The output data type [policy][@stdlib/ndarray/output-dtype-policies] only applies to the main function and specifies that, by default, the function must return an [ndarray][@stdlib/ndarray/ctor] having a real-valued floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any supported output [data type][@stdlib/ndarray/dtypes]. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/uniform' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var asum = require( '@stdlib/blas/asum' ); + +// Generate an array of random numbers: +var x = uniform( [ 5, 5 ], -10.0, 10.0 ); +console.log( ndarray2array( x ) ); + +// Perform a reduction: +var y = asum( x, { + 'dims': [ 0 ] +}); + +// Resolve the output array data type: +var dt = getDType( y ); +console.log( dt ); + +// Print the results: +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + +[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes + +[@stdlib/ndarray/output-dtype-policies]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/output-dtype-policies + +[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes + +
+ + diff --git a/lib/node_modules/@stdlib/blas/asum/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/blas/asum/benchmark/benchmark.assign.js new file mode 100644 index 000000000000..f18fc162c797 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/benchmark/benchmark.assign.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var asum = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( [], options ); + var x = uniform( [ len ], -50.0, 50.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var o; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + o = asum.assign( x, out ); + if ( typeof o !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( o.get() ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/asum/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/asum/benchmark/benchmark.js new file mode 100644 index 000000000000..26acbec8bc38 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/uniform' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var asum = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -50.0, 50.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var o; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + o = asum( x ); + if ( typeof o !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( o.get() ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/asum/docs/repl.txt b/lib/node_modules/@stdlib/blas/asum/docs/repl.txt new file mode 100644 index 000000000000..3ef49398db73 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/docs/repl.txt @@ -0,0 +1,75 @@ + +{{alias}}( x[, options] ) + Computes the sum of absolute values (L1 norm) along one or more ndarray + dimensions. + + Parameters + ---------- + x: ndarray + Input array. Must have a numeric or "generic" data type. + + options: Object (optional) + Function options. + + options.dtype: string|DataType (optional) + Output array data type. Must be a real-valued floating-point or + "generic" data type. + + options.dims: Array (optional) + List of dimensions over which to perform a reduction. If not provided, + the function performs a reduction over all elements in a provided input + ndarray. + + options.keepdims: boolean (optional) + Boolean indicating whether the reduced dimensions should be included in + the returned ndarray as singleton dimensions. Default: false. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ 1.0, -2.0, 2.0 ] ); + > var y = {{alias}}( x ) + [ 5.0 ] + + +{{alias}}.assign( x, out[, options] ) + Computes the sum of absolute values (L1 norm) along one or more ndarray + dimensions and assigns results to a provided output ndarray. + + Parameters + ---------- + x: ndarray + Input array. Must have a numeric or "generic" data type. + + out: ndarray + Output array. + + options: Object (optional) + Function options. + + options.dims: Array (optional) + List of dimensions over which to perform a reduction. If not provided, + the function performs a reduction over all elements in a provided input + ndarray. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ 1.0, -2.0, 2.0 ] ); + > var out = {{alias:@stdlib/ndarray/zeros}}( [] ); + > var y = {{alias}}.assign( x, out ) + [ 5.0 ] + > var bool = ( out === y ) + true + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/asum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/asum/docs/types/index.d.ts new file mode 100644 index 000000000000..c7c357ae427f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/docs/types/index.d.ts @@ -0,0 +1,139 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; +import { RealFloatingPointAndGenericDataType as DataType, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Input array. +*/ +type InputArray = typedndarray; + +/** +* Output array. +*/ +type OutputArray = typedndarray; + +/** +* Interface defining "base" options. +*/ +interface BaseOptions { + /** + * List of dimensions over which to perform a reduction. + */ + dims?: ArrayLike; +} + +/** +* Interface defining options. +*/ +interface Options extends BaseOptions { + /** + * Output array data type. + */ + dtype?: DataType; + + /** + * Boolean indicating whether the reduced dimensions should be included in the returned array as singleton dimensions. Default: `false`. + */ + keepdims?: boolean; +} + +/** +* Interface for performing a reduction on an ndarray. +*/ +interface Unary { + /** + * Computes the sum of absolute values (L1 norm) along one or more ndarray dimensions. + * + * @param x - input ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * + * var y = asum( x ); + * // returns [ 5.0 ] + */ + ( x: InputArray, options?: Options ): OutputArray; // NOTE: we lose type specificity here, but retaining specificity would likely be difficult and/or tedious to completely enumerate, as the output ndarray data type is dependent on how `x` interacts with output data type policy and whether that policy has been overridden by `options.dtype`. + + /** + * Computes the sum of absolute values (L1 norm) along one or more ndarray dimensions and assigns results to a provided output ndarray. + * + * @param x - input ndarray + * @param out - output ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * var zeros = require( '@stdlib/ndarray/zeros' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * var y = zeros( [] ); + * + * var out = asum.assign( x, y ); + * // returns [ 5.0 ] + * + * var bool = ( out === y ); + * // returns true + */ + assign = OutputArray>( x: InputArray, out: U, options?: BaseOptions ): U; +} + +/** +* Computes the sum of absolute values (L1 norm) along one or more ndarray dimensions. +* +* @param x - input ndarray +* @param options - function options +* @returns output ndarray +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ 1.0, -2.0, 2.0 ] ); +* +* var y = asum( x ); +* // returns [ 5.0 ] +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* var zeros = require( '@stdlib/ndarray/zeros' ); +* +* var x = array( [ 1.0, -2.0, 2.0 ] ); +* var y = zeros( [] ); +* +* var out = asum.assign( x, y ); +* // returns [ 5.0 ] +* +* var bool = ( out === y ); +* // returns true +*/ +declare const asum: Unary; + + +// EXPORTS // + +export = asum; diff --git a/lib/node_modules/@stdlib/blas/asum/docs/types/test.ts b/lib/node_modules/@stdlib/blas/asum/docs/types/test.ts new file mode 100644 index 000000000000..a40eea2351f1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/docs/types/test.ts @@ -0,0 +1,230 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import empty = require( '@stdlib/ndarray/empty' ); +import asum = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + asum( empty( [ 2, 2 ], { 'dtype': 'float64' } ) ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'float64' } ), {} ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'float32' } ) ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'float32' } ), {} ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'int32' } ) ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'int32' } ), {} ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'complex128' } ) ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'complex128' } ), {} ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'complex64' } ) ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'complex64' } ), {} ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'generic' } ) ); // $ExpectType OutputArray + asum( empty( [ 2, 2 ], { 'dtype': 'generic' } ), {} ); // $ExpectType OutputArray +} + +// The compiler throws an error if the function is provided a first argument which is not an ndarray... +{ + asum( '5' ); // $ExpectError + asum( 5 ); // $ExpectError + asum( true ); // $ExpectError + asum( false ); // $ExpectError + asum( null ); // $ExpectError + asum( void 0 ); // $ExpectError + asum( {} ); // $ExpectError + asum( ( x: number ): number => x ); // $ExpectError + + asum( '5', {} ); // $ExpectError + asum( 5, {} ); // $ExpectError + asum( true, {} ); // $ExpectError + asum( false, {} ); // $ExpectError + asum( null, {} ); // $ExpectError + asum( void 0, {} ); // $ExpectError + asum( {}, {} ); // $ExpectError + asum( ( x: number ): number => x, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not an object... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum( x, '5' ); // $ExpectError + asum( x, true ); // $ExpectError + asum( x, false ); // $ExpectError + asum( x, null ); // $ExpectError + asum( x, [] ); // $ExpectError + asum( x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `dtype` option... +{ + const x = empty( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum( x, { 'dtype': '5' } ); // $ExpectError + asum( x, { 'dtype': 5 } ); // $ExpectError + asum( x, { 'dtype': true } ); // $ExpectError + asum( x, { 'dtype': false } ); // $ExpectError + asum( x, { 'dtype': null } ); // $ExpectError + asum( x, { 'dtype': [] } ); // $ExpectError + asum( x, { 'dtype': {} } ); // $ExpectError + asum( x, { 'dtype': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `keepdims` option... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum( x, { 'keepdims': '5' } ); // $ExpectError + asum( x, { 'keepdims': 5 } ); // $ExpectError + asum( x, { 'keepdims': null } ); // $ExpectError + asum( x, { 'keepdims': [] } ); // $ExpectError + asum( x, { 'keepdims': {} } ); // $ExpectError + asum( x, { 'keepdims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `dims` option... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum( x, { 'dims': '5' } ); // $ExpectError + asum( x, { 'dims': 5 } ); // $ExpectError + asum( x, { 'dims': true } ); // $ExpectError + asum( x, { 'dims': false } ); // $ExpectError + asum( x, { 'dims': null } ); // $ExpectError + asum( x, { 'dims': {} } ); // $ExpectError + asum( x, { 'dims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum(); // $ExpectError + asum( x, {}, {} ); // $ExpectError +} + +// Attached to the function is an `assign` method which returns an ndarray... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum.assign( x, x ); // $ExpectType float64ndarray + asum.assign( x, x, {} ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum.assign( '5', x ); // $ExpectError + asum.assign( 5, x ); // $ExpectError + asum.assign( true, x ); // $ExpectError + asum.assign( false, x ); // $ExpectError + asum.assign( null, x ); // $ExpectError + asum.assign( void 0, x ); // $ExpectError + asum.assign( {}, x ); // $ExpectError + asum.assign( ( x: number ): number => x, x ); // $ExpectError + + asum.assign( '5', x, {} ); // $ExpectError + asum.assign( 5, x, {} ); // $ExpectError + asum.assign( true, x, {} ); // $ExpectError + asum.assign( false, x, {} ); // $ExpectError + asum.assign( null, x, {} ); // $ExpectError + asum.assign( void 0, x, {} ); // $ExpectError + asum.assign( {}, x, {} ); // $ExpectError + asum.assign( ( x: number ): number => x, x, {} ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a second argument which is not an ndarray... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum.assign( x, '5' ); // $ExpectError + asum.assign( x, 5 ); // $ExpectError + asum.assign( x, true ); // $ExpectError + asum.assign( x, false ); // $ExpectError + asum.assign( x, null ); // $ExpectError + asum.assign( x, void 0 ); // $ExpectError + asum.assign( x, ( x: number ): number => x ); // $ExpectError + + asum.assign( x, '5', {} ); // $ExpectError + asum.assign( x, 5, {} ); // $ExpectError + asum.assign( x, true, {} ); // $ExpectError + asum.assign( x, false, {} ); // $ExpectError + asum.assign( x, null, {} ); // $ExpectError + asum.assign( x, void 0, {} ); // $ExpectError + asum.assign( x, ( x: number ): number => x, {} ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a third argument which is not an object... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum.assign( x, x, '5' ); // $ExpectError + asum.assign( x, x, true ); // $ExpectError + asum.assign( x, x, false ); // $ExpectError + asum.assign( x, x, null ); // $ExpectError + asum.assign( x, x, [] ); // $ExpectError + asum.assign( x, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an invalid `dims` option... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum.assign( x, x, { 'dims': '5' } ); // $ExpectError + asum.assign( x, x, { 'dims': 5 } ); // $ExpectError + asum.assign( x, x, { 'dims': true } ); // $ExpectError + asum.assign( x, x, { 'dims': false } ); // $ExpectError + asum.assign( x, x, { 'dims': null } ); // $ExpectError + asum.assign( x, x, { 'dims': {} } ); // $ExpectError + asum.assign( x, x, { 'dims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + asum.assign(); // $ExpectError + asum.assign( x ); // $ExpectError + asum.assign( x, x, {}, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/asum/examples/index.js b/lib/node_modules/@stdlib/blas/asum/examples/index.js new file mode 100644 index 000000000000..a1b17b12aa19 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/uniform' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var asum = require( './../lib' ); + +// Generate an array of random numbers: +var x = uniform( [ 5, 5 ], -10.0, 10.0 ); +console.log( ndarray2array( x ) ); + +// Perform a reduction: +var y = asum( x, { + 'dims': [ 0 ] +}); + +// Resolve the output array data type: +var dt = getDType( y ); +console.log( dt ); + +// Print the results: +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/asum/lib/index.js b/lib/node_modules/@stdlib/blas/asum/lib/index.js new file mode 100644 index 000000000000..bfb3ce66e3fc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the sum of absolute values (L1 norm) along one or more ndarray dimensions. +* +* @module @stdlib/blas/asum +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var asum = require( '@stdlib/blas/asum' ); +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 0.0, 1.0, -2.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* // Define the shape of the input array: +* var sh = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create an input ndarray: +* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' ); +* +* // Perform reduction: +* var out = asum( x ); +* // returns [ 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; + +// exports: { "assign": "main.assign" } diff --git a/lib/node_modules/@stdlib/blas/asum/lib/main.js b/lib/node_modules/@stdlib/blas/asum/lib/main.js new file mode 100644 index 000000000000..30d48acfba9e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/lib/main.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var dtypes = require( '@stdlib/ndarray/dtypes' ); +var gasum = require( '@stdlib/blas/base/ndarray/gasum' ); +var dasum = require( '@stdlib/blas/base/ndarray/dasum' ); +var sasum = require( '@stdlib/blas/base/ndarray/sasum' ); +var dzasum = require( '@stdlib/blas/base/ndarray/dzasum' ); +var scasum = require( '@stdlib/blas/base/ndarray/scasum' ); +var factory = require( '@stdlib/ndarray/base/unary-reduce-strided1d-dispatch-factory' ); + + +// VARIABLES // + +var idtypes = dtypes( 'numeric_and_generic' ); +var odtypes = dtypes( 'real_floating_point_and_generic' ); +var policies = { + 'output': 'real_floating_point_and_generic', + 'casting': 'none' +}; +var table = { + 'types': [ + 'float64', // input + 'float32', // input + 'complex128', // input + 'complex64' // input + ], + 'fcns': [ + dasum, + sasum, + dzasum, + scasum + ], + 'default': gasum +}; + + +// MAIN // + +/** +* Computes the sum of absolute values (L1 norm) along one or more ndarray dimensions. +* +* @name asum +* @type {Function} +* @param {ndarray} x - input ndarray +* @param {Options} [options] - function options +* @param {IntegerArray} [options.dims] - list of dimensions over which to perform a reduction +* @param {boolean} [options.keepdims=false] - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions +* @param {*} [options.dtype] - output ndarray data type +* @throws {TypeError} first argument must be an ndarray-like object +* @throws {TypeError} options argument must be an object +* @throws {RangeError} dimension indices must not exceed input ndarray bounds +* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions +* @throws {Error} must provide valid options +* @returns {ndarray} output ndarray +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 0.0, 1.0, -2.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* // Define the shape of the input array: +* var sh = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create an input ndarray: +* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' ); +* +* // Perform reduction: +* var out = asum( x ); +* // returns [ 5.0 ] +*/ +var asum = factory( table, [ idtypes ], odtypes, policies ); + + +// EXPORTS // + +module.exports = asum; diff --git a/lib/node_modules/@stdlib/blas/asum/package.json b/lib/node_modules/@stdlib/blas/asum/package.json new file mode 100644 index 000000000000..75f327557e57 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/asum", + "version": "0.0.0", + "description": "Compute the sum of absolute values (L1 norm) along one or more ndarray dimensions.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 1", + "linear", + "algebra", + "subroutines", + "asum", + "sum", + "absolute", + "l1-norm", + "norm", + "vector", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/asum/test/test.assign.js b/lib/node_modules/@stdlib/blas/asum/test/test.assign.js new file mode 100644 index 000000000000..0991fa9f1487 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/test/test.assign.js @@ -0,0 +1,765 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var empty = require( '@stdlib/ndarray/empty' ); +var emptyLike = require( '@stdlib/ndarray/empty-like' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var asum = require( './../lib' ).assign; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof asum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value, out ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value, out, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value, out ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type (options)', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value, out, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an ndarray-like object', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, value ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an ndarray-like object (options)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a third argument which is not an object', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, out, value ); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [ 'a' ], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [ 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ -10 ], + [ 20 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 1, 2 ], + [ 0, 1, 2, 3 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 0 ], + [ 1, 1 ], + [ 0, 1, 0 ], + [ 1, 0, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided an output array which has an invalid shape (default)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 2, 2 ], + [ 2 ], + [ 4, 4 ], + [ 4 ], + [ 1 ], + [ 1, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + var out = zeros( value, { + 'dtype': 'generic' + }); + asum( x, out ); + }; + } +}); + +tape( 'the function throws an error if provided an output array which has an invalid shape (all dimensions)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 2, 2 ], + [ 2 ], + [ 4, 4 ], + [ 4 ], + [ 1 ], + [ 1, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + var out = zeros( value, { + 'dtype': 'generic' + }); + asum( x, out, { + 'dims': [ 0, 1 ] + }); + }; + } +}); + +tape( 'the function throws an error if provided an output array which has an invalid shape (some dimensions)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [], + [ 4, 4 ], + [ 4 ], + [ 1 ], + [ 1, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + var out = zeros( value, { + 'dtype': 'generic' + }); + asum( x, out, { + 'dims': [ 0 ] + }); + }; + } +}); + +tape( 'the function performs a reduction on an ndarray (default, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = asum( x, out ); + expected = 7.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (default, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = asum( x, out ); + expected = 7.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = asum( x, out, { + 'dims': [ 0, 1 ] + }); + expected = 7.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = asum( x, out, { + 'dims': [ 0, 1 ] + }); + expected = 7.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [ 2, 2 ] + }); + + actual = asum( x, out, { + 'dims': [] + }); + expected = [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [ 2, 2 ] + }); + + actual = asum( x, out, { + 'dims': [] + }); + expected = [ [ 3.0, 4.0 ], [ 0.0, 0.0 ] ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = asum( x, out, { + 'dims': [ 0 ] + }); + expected = [ 7.0, 0.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = asum( x, out, { + 'dims': [ 1 ] + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = asum( x, out, { + 'dims': [ 0 ] + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = asum( x, out, { + 'dims': [ 1 ] + }); + expected = [ 7.0, 0.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex128)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = new Complex128Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex128', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = empty( [], { + 'dtype': 'float64' + }); + + actual = asum( x, out ); + expected = 9.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex64)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = new Complex64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = empty( [], { + 'dtype': 'float32' + }); + + actual = asum( x, out ); + expected = 9.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/asum/test/test.js b/lib/node_modules/@stdlib/blas/asum/test/test.js new file mode 100644 index 000000000000..86d2cbc1763b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/test/test.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isMethod = require( '@stdlib/assert/is-method' ); +var asum = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof asum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is an `assign` method', function test( t ) { + t.strictEqual( isMethod( asum, 'assign' ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/asum/test/test.main.js b/lib/node_modules/@stdlib/blas/asum/test/test.main.js new file mode 100644 index 000000000000..9f50aff6ff0d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/asum/test/test.main.js @@ -0,0 +1,795 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var empty = require( '@stdlib/ndarray/empty' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var getOrder = require( '@stdlib/ndarray/order' ); +var asum = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof asum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type', function test( t ) { + var values; + var i; + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type (options)', function test( t ) { + var values; + var i; + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an object', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, value ); + }; + } +}); + +tape( 'the function throws an error if provided a `dtype` option which is not a supported data type', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, { + 'dtype': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `keepdims` option which is not a boolean', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, { + 'keepdims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [ 'a' ], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ -10 ], + [ 0, 20 ], + [ 20 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 1, 2 ], + [ 0, 1, 2, 3 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 0 ], + [ 1, 1 ], + [ 0, 1, 0 ], + [ 1, 0, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + asum( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function performs a reduction on an ndarray (default, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x ); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (default, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x ); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [ 0, 1 ] + }); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [ 0, 1 ], + 'keepdims': false + }); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [ 0, 1 ], + 'keepdims': true + }); + expected = [ [ 7.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [ 0, 1 ] + }); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [ 0, 1 ], + 'keepdims': false + }); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [ 0, 1 ], + 'keepdims': true + }); + expected = [ [ 7.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [], + 'keepdims': false + }); + expected = [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [], + 'keepdims': true + }); + expected = [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [], + 'keepdims': false + }); + expected = [ [ 3.0, 4.0 ], [ 0.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [], + 'keepdims': true + }); + expected = [ [ 3.0, 4.0 ], [ 0.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [ 0 ], + 'keepdims': false + }); + expected = [ 7.0, 0.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [ 0 ], + 'keepdims': true + }); + expected = [ [ 7.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [ 1 ], + 'keepdims': false + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dims': [ 1 ], + 'keepdims': true + }); + expected = [ [ 3.0 ], [ 4.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [ 0 ], + 'keepdims': false + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [ 0 ], + 'keepdims': true + }); + expected = [ [ 3.0, 4.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [ 1 ], + 'keepdims': false + }); + expected = [ 7.0, 0.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dims': [ 1 ], + 'keepdims': true + }); + expected = [ [ 7.0 ], [ 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying the output array data type', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x, { + 'dtype': 'float64' + }); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = asum( x, { + 'dtype': 'float64' + }); + expected = 7.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex128)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex128', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x ); + expected = 9.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex64)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = asum( x ); + expected = 9.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float32', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.js index 821c3a83c309..426202c7f09c 100644 --- a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -75,12 +75,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { ccopy( x.length, x, 1, y, 1 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.native.js index 6cb84989a92f..66c3bfe0e742 100644 --- a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -80,12 +80,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { ccopy( x.length, x, 1, y, 1 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.js index 907557ed02e7..bc955cebc652 100644 --- a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -75,12 +75,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { ccopy( x.length, x, 1, 0, y, 1, 0 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.native.js index 09ec3ec39287..761bc447ea28 100644 --- a/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/ccopy/benchmark/benchmark.ndarray.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -80,12 +80,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { ccopy( x.length, x, 1, 0, y, 1, 0 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.js index 782876fcde2c..e85d7850377b 100644 --- a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -75,12 +75,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { cswap( x.length, x, 1, y, 1 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.native.js index 5425744493e8..0b2071853391 100644 --- a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -80,12 +80,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { cswap( x.length, x, 1, y, 1 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.js index 05cd6505e0b1..b49aeb2f7294 100644 --- a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -75,12 +75,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { cswap( x.length, x, 1, 0, y, 1, 0 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.native.js index 44d27adab4fa..c616b1875afd 100644 --- a/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/cswap/benchmark/benchmark.ndarray.native.js @@ -23,7 +23,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/array/uniform' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var Complex64Array = require( '@stdlib/array/complex64' ); var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); @@ -80,12 +80,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { cswap( x.length, x, 1, 0, y, 1, 0 ); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( viewY[ i%(len*2) ] ) ) { + if ( isnanf( viewY[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/blas/base/diagonal-types/test/test.js b/lib/node_modules/@stdlib/blas/base/diagonal-types/test/test.js index fb495487e74b..8f1c225a33b3 100644 --- a/lib/node_modules/@stdlib/blas/base/diagonal-types/test/test.js +++ b/lib/node_modules/@stdlib/blas/base/diagonal-types/test/test.js @@ -66,7 +66,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/blas/base/dspmv/lib/dspmv.js b/lib/node_modules/@stdlib/blas/base/dspmv/lib/dspmv.js index 32b865e63310..293281194ef9 100644 --- a/lib/node_modules/@stdlib/blas/base/dspmv/lib/dspmv.js +++ b/lib/node_modules/@stdlib/blas/base/dspmv/lib/dspmv.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -33,7 +33,7 @@ var base = require( './base.js' ); * Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} AP - packed form of a symmetric matrix `A` @@ -62,11 +62,13 @@ var base = require( './base.js' ); function dspmv( order, uplo, N, alpha, AP, x, strideX, beta, y, strideY ) { var offsetX; var offsetY; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -80,7 +82,7 @@ function dspmv( order, uplo, N, alpha, AP, x, strideX, beta, y, strideY ) { } offsetX = stride2offset( N, strideX ); offsetY = stride2offset( N, strideY ); - return base( order, uplo, N, alpha, AP, 0, x, strideX, offsetX, beta, y, strideY, offsetY ); // eslint-disable-line max-len + return base( order, u, N, alpha, AP, 0, x, strideX, offsetX, beta, y, strideY, offsetY ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/dspmv/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/dspmv/lib/ndarray.js index 2c5a1479e790..d4d1c4643752 100644 --- a/lib/node_modules/@stdlib/blas/base/dspmv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dspmv/lib/ndarray.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -32,7 +32,7 @@ var base = require( './base.js' ); * Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} AP - packed form of a symmetric matrix `A` @@ -62,10 +62,13 @@ var base = require( './base.js' ); * // y => [ ~7.0, ~12.0, ~15.0 ] */ function dspmv( order, uplo, N, alpha, AP, offsetAP, x, strideX, offsetX, beta, y, strideY, offsetY ) { // eslint-disable-line max-params, max-len + var u; + if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -77,7 +80,7 @@ function dspmv( order, uplo, N, alpha, AP, offsetAP, x, strideX, offsetX, beta, if ( strideY === 0 ) { throw new RangeError( format( 'invalid argument. Twelfth argument must be non-zero. Value: `%d`.', strideY ) ); } - return base( order, uplo, N, alpha, AP, offsetAP, x, strideX, offsetX, beta, y, strideY, offsetY ); // eslint-disable-line max-len + return base( order, u, N, alpha, AP, offsetAP, x, strideX, offsetX, beta, y, strideY, offsetY ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/dspr/README.md b/lib/node_modules/@stdlib/blas/base/dspr/README.md index eb930c6c66a8..071ede7dc3b0 100644 --- a/lib/node_modules/@stdlib/blas/base/dspr/README.md +++ b/lib/node_modules/@stdlib/blas/base/dspr/README.md @@ -84,7 +84,7 @@ dspr( 'row-major', 'upper', 3, 1.0, x1, -1, AP ); // AP => [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] ``` -#### dspr.ndarray( uplo, N, α, x, sx, ox, AP, sap, oap ) +#### dspr.ndarray( order, uplo, N, α, x, sx, ox, AP, sap, oap ) Performs the symmetric rank 1 operation `A = α*x*x^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. diff --git a/lib/node_modules/@stdlib/blas/base/dspr/lib/dspr.js b/lib/node_modules/@stdlib/blas/base/dspr/lib/dspr.js index 05dcf1474174..2682c6b0168b 100644 --- a/lib/node_modules/@stdlib/blas/base/dspr/lib/dspr.js +++ b/lib/node_modules/@stdlib/blas/base/dspr/lib/dspr.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -33,7 +33,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - input vector @@ -56,11 +56,13 @@ var base = require( './base.js' ); */ function dspr( order, uplo, N, alpha, x, strideX, AP ) { var ox; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -73,7 +75,7 @@ function dspr( order, uplo, N, alpha, x, strideX, AP ) { return AP; } ox = stride2offset( N, strideX ); - return base( order, uplo, N, alpha, x, strideX, ox, AP, 1, 0 ); + return base( order, u, N, alpha, x, strideX, ox, AP, 1, 0 ); } diff --git a/lib/node_modules/@stdlib/blas/base/dspr/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/dspr/lib/ndarray.js index f6884ee91ee1..e645a7db9f16 100644 --- a/lib/node_modules/@stdlib/blas/base/dspr/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dspr/lib/ndarray.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -32,7 +32,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - input vector @@ -58,10 +58,12 @@ var base = require( './base.js' ); * // AP => [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] */ function dspr( order, uplo, N, alpha, x, strideX, offsetX, AP, strideAP, offsetAP ) { // eslint-disable-line max-len + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -76,7 +78,7 @@ function dspr( order, uplo, N, alpha, x, strideX, offsetX, AP, strideAP, offsetA if ( N === 0 || alpha === 0.0 ) { return AP; } - return base( order, uplo, N, alpha, x, strideX, offsetX, AP, strideAP, offsetAP ); // eslint-disable-line max-len + return base( order, u, N, alpha, x, strideX, offsetX, AP, strideAP, offsetAP ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/dsymv/lib/dsymv.js b/lib/node_modules/@stdlib/blas/base/dsymv/lib/dsymv.js index 7795b9005465..8e76a5a4eec5 100644 --- a/lib/node_modules/@stdlib/blas/base/dsymv/lib/dsymv.js +++ b/lib/node_modules/@stdlib/blas/base/dsymv/lib/dsymv.js @@ -24,7 +24,7 @@ var dfill = require( '@stdlib/blas/ext/base/dfill' ); var dscal = require( '@stdlib/blas/base/dscal' ); var max = require( '@stdlib/math/base/special/max' ); var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); @@ -35,7 +35,7 @@ var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string * Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} A - matrix @@ -78,11 +78,13 @@ function dsymv( order, uplo, N, alpha, A, LDA, x, strideX, beta, y, strideY ) { var i; var j; var k; + var u; if ( !isLayout( order ) ) { throw new TypeError( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ); } if ( N < 0 ) { @@ -128,8 +130,8 @@ function dsymv( order, uplo, N, alpha, A, LDA, x, strideX, beta, y, strideY ) { } // Form: y = alpha*A*x + y if ( - ( isRowMajor( order ) && uplo === 'upper' ) || - ( isColumnMajor( order ) && uplo === 'lower' ) + ( isRowMajor( order ) && u === 'upper' ) || + ( isColumnMajor( order ) && u === 'lower' ) ) { ix = ox; iy = oy; @@ -154,7 +156,7 @@ function dsymv( order, uplo, N, alpha, A, LDA, x, strideX, beta, y, strideY ) { } return y; } - // ( order === 'row-major' && uplo === 'lower') || ( order === 'column-major' && uplo === 'upper' ) + // ( order === 'row-major' && u === 'lower') || ( order === 'column-major' && u === 'upper' ) ix = ox + ( ( N - 1 ) * strideX ); iy = oy + ( ( N - 1 ) * strideY ); for ( i = N - 1; i >= 0; i-- ) { diff --git a/lib/node_modules/@stdlib/blas/base/dsymv/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/dsymv/lib/ndarray.js index ea6d8bf9fd3b..ce5ccd7bb535 100644 --- a/lib/node_modules/@stdlib/blas/base/dsymv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dsymv/lib/ndarray.js @@ -24,7 +24,7 @@ var dfill = require( '@stdlib/blas/ext/base/dfill' ).ndarray; var dscal = require( '@stdlib/blas/base/dscal' ).ndarray; var max = require( '@stdlib/math/base/special/max' ); var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); @@ -35,7 +35,7 @@ var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string * Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} A - matrix @@ -79,11 +79,13 @@ function dsymv( order, uplo, N, alpha, A, LDA, x, strideX, offsetX, beta, y, str var i; var j; var k; + var u; if ( !isLayout( order ) ) { throw new TypeError( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ); } if ( N < 0 ) { @@ -117,8 +119,8 @@ function dsymv( order, uplo, N, alpha, A, LDA, x, strideX, offsetX, beta, y, str // Form: y = alpha*A*x + y if ( - ( isRowMajor( order ) && uplo === 'upper' ) || - ( isColumnMajor( order ) && uplo === 'lower' ) + ( isRowMajor( order ) && u === 'upper' ) || + ( isColumnMajor( order ) && u === 'lower' ) ) { ix = ox; iy = oy; @@ -143,7 +145,7 @@ function dsymv( order, uplo, N, alpha, A, LDA, x, strideX, offsetX, beta, y, str } return y; } - // ( order === 'row-major' && uplo === 'lower') || ( order === 'column-major' && uplo === 'upper' ) + // ( order === 'row-major' && u === 'lower') || ( order === 'column-major' && u === 'upper' ) ix = ox + ( ( N - 1 ) * strideX ); iy = oy + ( ( N - 1 ) * strideY ); for ( i = N - 1; i >= 0; i-- ) { diff --git a/lib/node_modules/@stdlib/blas/base/dsyr/lib/dsyr.js b/lib/node_modules/@stdlib/blas/base/dsyr/lib/dsyr.js index c8c14a02e4ff..0209564e16df 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr/lib/dsyr.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr/lib/dsyr.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var max = require( '@stdlib/math/base/special/fast/max' ); @@ -35,7 +35,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - input vector @@ -62,11 +62,13 @@ function dsyr( order, uplo, N, alpha, x, strideX, A, LDA ) { var sa1; var sa2; var ox; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -90,7 +92,7 @@ function dsyr( order, uplo, N, alpha, x, strideX, A, LDA ) { sa2 = 1; } ox = stride2offset( N, strideX ); - return base( uplo, N, alpha, x, strideX, ox, A, sa1, sa2, 0 ); + return base( u, N, alpha, x, strideX, ox, A, sa1, sa2, 0 ); } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/dsyr/lib/ndarray.js index e82b95100197..2da19ed9da37 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr/lib/ndarray.js @@ -20,7 +20,7 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -30,7 +30,7 @@ var base = require( './base.js' ); /** * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - input vector @@ -57,7 +57,8 @@ var base = require( './base.js' ); * // A => [ 2.0, 4.0, 6.0, 2.0, 5.0, 8.0, 3.0, 2.0, 10.0 ] */ function dsyr( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len - if ( !isMatrixTriangle( uplo ) ) { + var u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -76,7 +77,7 @@ function dsyr( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offse if ( N === 0 || alpha === 0.0 ) { return A; } - return base( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len + return base( u, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.js b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.js index c721c40150b5..5c85e1f90f34 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.js @@ -22,7 +22,7 @@ var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var max = require( '@stdlib/math/base/special/fast/max' ); var format = require( '@stdlib/string/format' ); @@ -35,7 +35,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - first input vector @@ -67,11 +67,13 @@ function dsyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { var sa2; var ox; var oy; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -99,7 +101,7 @@ function dsyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { } ox = stride2offset( N, strideX ); oy = stride2offset( N, strideY ); - return base( uplo, N, alpha, x, strideX, ox, y, strideY, oy, A, sa1, sa2, 0 ); // eslint-disable-line max-len + return base( u, N, alpha, x, strideX, ox, y, strideY, oy, A, sa1, sa2, 0 ); } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.native.js b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.native.js index 7ae09da27006..8ebcc5e7b000 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.native.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/dsyr2.native.js @@ -21,7 +21,6 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); var resolveOrder = require( '@stdlib/blas/base/layout-resolve-enum' ); var resolveUplo = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); var max = require( '@stdlib/math/base/special/fast/max' ); @@ -35,7 +34,7 @@ var addon = require( './../src/addon.node' ); * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - first input vector @@ -63,10 +62,13 @@ var addon = require( './../src/addon.node' ); * // A => [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] */ function dsyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { + var u; + if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveUplo( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -85,7 +87,7 @@ function dsyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { if ( N === 0 || alpha === 0.0 ) { return A; } - addon( resolveOrder( order ), resolveUplo( uplo ), N, alpha, x, strideX, y, strideY, A, LDA ); // eslint-disable-line max-len + addon( resolveOrder( order ), u, N, alpha, x, strideX, y, strideY, A, LDA ); return A; } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.js index a0aae998d303..a0fae53e1e45 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.js @@ -20,7 +20,7 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -30,7 +30,7 @@ var base = require( './base.js' ); /** * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - first input vector @@ -62,7 +62,8 @@ var base = require( './base.js' ); * // A => [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] */ function dsyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len, max-params - if ( !isMatrixTriangle( uplo ) ) { + var u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -84,7 +85,7 @@ function dsyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, str if ( N === 0 || alpha === 0.0 ) { return A; } - return base( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len + return base( u, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.native.js index ab471ef9fe14..9d16bc2b60c3 100644 --- a/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/dsyr2/lib/ndarray.native.js @@ -20,7 +20,6 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); var resolveUplo = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); var format = require( '@stdlib/string/format' ); var addon = require( './../src/addon.node' ); @@ -31,7 +30,7 @@ var addon = require( './../src/addon.node' ); /** * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float64Array} x - first input vector @@ -63,7 +62,8 @@ var addon = require( './../src/addon.node' ); * // A => [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] */ function dsyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len, max-params - if ( !isMatrixTriangle( uplo ) ) { + var u = resolveUplo( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -85,7 +85,7 @@ function dsyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, str if ( N === 0 || alpha === 0.0 ) { return A; } - addon.ndarray( resolveUplo( uplo ), N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len + addon.ndarray( u, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len return A; } diff --git a/lib/node_modules/@stdlib/blas/base/dtrsv/lib/dtrsv.js b/lib/node_modules/@stdlib/blas/base/dtrsv/lib/dtrsv.js index b6998b8e6f8c..83f9106f8f4e 100644 --- a/lib/node_modules/@stdlib/blas/base/dtrsv/lib/dtrsv.js +++ b/lib/node_modules/@stdlib/blas/base/dtrsv/lib/dtrsv.js @@ -21,10 +21,10 @@ // MODULES // var max = require( '@stdlib/math/base/special/fast/max' ); -var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); -var isTransposeOperation = require( '@stdlib/blas/base/assert/is-transpose-operation' ); -var isDiagonal = require( '@stdlib/blas/base/assert/is-diagonal-type' ); +var resolveLayout = require( '@stdlib/blas/base/layout-resolve-str' ); +var resolveTriangle = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); +var resolveTranspose = require( '@stdlib/blas/base/transpose-operation-resolve-str' ); +var resolveDiagonal = require( '@stdlib/blas/base/diagonal-type-resolve-str' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var format = require( '@stdlib/string/format' ); @@ -36,10 +36,10 @@ var base = require( './base.js' ); /** * Solves one of the systems of equations `A*x = b` or `A^T*x = b` where `b` and `x` are `N` element vectors and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix. * -* @param {string} order - storage layout -* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix -* @param {string} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed -* @param {string} diag - specifies whether `A` has a unit diagonal +* @param {(integer|string)} order - storage layout +* @param {(integer|string)} uplo - specifies whether `A` is an upper or lower triangular matrix +* @param {(integer|string)} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed +* @param {(integer|string)} diag - specifies whether `A` has a unit diagonal * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {Float64Array} A - input matrix * @param {integer} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) @@ -67,17 +67,25 @@ function dtrsv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { var sa1; var sa2; var ox; + var l; + var u; + var t; + var d; - if ( !isLayout( order ) ) { + l = resolveLayout( order ); + if ( l === null ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveTriangle( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } - if ( !isTransposeOperation( trans ) ) { + t = resolveTranspose( trans ); + if ( t === null ) { throw new TypeError( format( 'invalid argument. Third argument must be a valid transpose operation. Value: `%s`.', trans ) ); } - if ( !isDiagonal( diag ) ) { + d = resolveDiagonal( diag ); + if ( d === null ) { throw new TypeError( format( 'invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.', diag ) ); } if ( N < 0 ) { @@ -92,7 +100,7 @@ function dtrsv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { if ( N === 0 ) { return x; } - if ( isColumnMajor( order ) ) { + if ( isColumnMajor( l ) ) { sa1 = 1; sa2 = LDA; } else { // order === 'row-major' @@ -100,7 +108,7 @@ function dtrsv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { sa2 = 1; } ox = stride2offset( N, strideX ); - return base( uplo, trans, diag, N, A, sa1, sa2, 0, x, strideX, ox ); + return base( u, t, d, N, A, sa1, sa2, 0, x, strideX, ox ); } diff --git a/lib/node_modules/@stdlib/blas/base/dtrsv/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/dtrsv/lib/ndarray.js index 6651f15baa51..3834bd8171c3 100644 --- a/lib/node_modules/@stdlib/blas/base/dtrsv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/dtrsv/lib/ndarray.js @@ -20,9 +20,9 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); -var isTransposeOperation = require( '@stdlib/blas/base/assert/is-transpose-operation' ); -var isDiagonal = require( '@stdlib/blas/base/assert/is-diagonal-type' ); +var resolveTriangle = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); +var resolveTranspose = require( '@stdlib/blas/base/transpose-operation-resolve-str' ); +var resolveDiagonal = require( '@stdlib/blas/base/diagonal-type-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -32,9 +32,9 @@ var base = require( './base.js' ); /** * Solves one of the systems of equations `A*x = b` or `A^T*x = b` where `b` and `x` are `N` element vectors and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix. * -* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix -* @param {string} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed -* @param {string} diag - specifies whether `A` has a unit diagonal +* @param {(integer|string)} uplo - specifies whether `A` is an upper or lower triangular matrix +* @param {(integer|string)} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed +* @param {(integer|string)} diag - specifies whether `A` has a unit diagonal * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {Float64Array} A - input matrix * @param {integer} strideA1 - stride of the first dimension of `A` @@ -62,13 +62,20 @@ var base = require( './base.js' ); * // x => [ 0.0, -4.0, 3.0 ] */ function dtrsv( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ) { // eslint-disable-line max-params, max-len - if ( !isMatrixTriangle( uplo ) ) { + var u; + var t; + var d; + + u = resolveTriangle( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } - if ( !isTransposeOperation( trans ) ) { + t = resolveTranspose( trans ); + if ( t === null ) { throw new TypeError( format( 'invalid argument. Second argument must be a valid transpose operation. Value: `%s`.', trans ) ); } - if ( !isDiagonal( diag ) ) { + d = resolveDiagonal( diag ); + if ( d === null ) { throw new TypeError( format( 'invalid argument. Third argument must be a valid diagonal type. Value: `%s`.', diag ) ); } if ( N < 0 ) { @@ -86,7 +93,7 @@ function dtrsv( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX if ( N === 0 ) { return x; } - return base( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ); // eslint-disable-line max-len + return base( u, t, d, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/gsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/gsyr/lib/main.js index be34a72b1df1..ab607b7a1c70 100644 --- a/lib/node_modules/@stdlib/blas/base/gsyr/lib/main.js +++ b/lib/node_modules/@stdlib/blas/base/gsyr/lib/main.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var max = require( '@stdlib/math/base/special/fast/max' ); @@ -35,7 +35,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {NumericArray} x - input vector @@ -60,11 +60,13 @@ function gsyr( order, uplo, N, alpha, x, strideX, A, LDA ) { var sa1; var sa2; var ox; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -88,7 +90,7 @@ function gsyr( order, uplo, N, alpha, x, strideX, A, LDA ) { sa2 = 1; } ox = stride2offset( N, strideX ); - return base( uplo, N, alpha, x, strideX, ox, A, sa1, sa2, 0 ); + return base( u, N, alpha, x, strideX, ox, A, sa1, sa2, 0 ); } diff --git a/lib/node_modules/@stdlib/blas/base/gsyr/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/gsyr/lib/ndarray.js index fcbe90edddc7..b01a4b28c311 100644 --- a/lib/node_modules/@stdlib/blas/base/gsyr/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/gsyr/lib/ndarray.js @@ -20,7 +20,7 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -30,7 +30,7 @@ var base = require( './base.js' ); /** * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {NumericArray} x - input vector @@ -55,7 +55,8 @@ var base = require( './base.js' ); * // A => [ 2.0, 4.0, 6.0, 2.0, 5.0, 8.0, 3.0, 2.0, 10.0 ] */ function gsyr( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len - if ( !isMatrixTriangle( uplo ) ) { + var u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -74,7 +75,7 @@ function gsyr( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offse if ( N === 0 || alpha === 0.0 ) { return A; } - return base( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len + return base( u, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/layouts/test/test.js b/lib/node_modules/@stdlib/blas/base/layouts/test/test.js index e5765877c4a0..deceef9a750e 100644 --- a/lib/node_modules/@stdlib/blas/base/layouts/test/test.js +++ b/lib/node_modules/@stdlib/blas/base/layouts/test/test.js @@ -66,7 +66,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/blas/base/matrix-orientations/test/test.js b/lib/node_modules/@stdlib/blas/base/matrix-orientations/test/test.js index 8c4a6a26efc1..19fb62f3d3a9 100644 --- a/lib/node_modules/@stdlib/blas/base/matrix-orientations/test/test.js +++ b/lib/node_modules/@stdlib/blas/base/matrix-orientations/test/test.js @@ -66,7 +66,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/blas/base/matrix-triangles/test/test.js b/lib/node_modules/@stdlib/blas/base/matrix-triangles/test/test.js index 34bf34b56d5a..f0a7307f333b 100644 --- a/lib/node_modules/@stdlib/blas/base/matrix-triangles/test/test.js +++ b/lib/node_modules/@stdlib/blas/base/matrix-triangles/test/test.js @@ -66,7 +66,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/README.md index 2e90981de895..c89d1f47157d 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/README.md @@ -47,6 +47,7 @@ The namespace exposes the following APIs: - [`caxpy( arrays )`][@stdlib/blas/base/ndarray/caxpy]: multiply a one-dimensional single-precision complex floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional single-precision complex floating-point ndarray `y`. - [`ccopy( arrays )`][@stdlib/blas/base/ndarray/ccopy]: copy values from a one-dimensional single-precision complex floating-point ndarray `x` into a one-dimensional single-precision complex floating-point ndarray `y`. +- [`cgemv( arrays )`][@stdlib/blas/base/ndarray/cgemv]: perform one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`. - [`cscal( arrays )`][@stdlib/blas/base/ndarray/cscal]: multiply a one-dimensional single-precision complex floating-point ndarray by a scalar constant. - [`csscal( arrays )`][@stdlib/blas/base/ndarray/csscal]: multiply a one-dimensional single-precision complex floating-point ndarray by a single-precision floating-point scalar constant. - [`cswap( arrays )`][@stdlib/blas/base/ndarray/cswap]: interchange two one-dimensional single-precision complex floating-point ndarrays. @@ -54,19 +55,29 @@ The namespace exposes the following APIs: - [`daxpy( arrays )`][@stdlib/blas/base/ndarray/daxpy]: multiply a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision floating-point ndarray `y`. - [`dcopy( arrays )`][@stdlib/blas/base/ndarray/dcopy]: copy values from a one-dimensional double-precision floating-point ndarray `x` into a one-dimensional double-precision floating-point ndarray `y`. - [`ddot( arrays )`][@stdlib/blas/base/ndarray/ddot]: calculate the dot product of two one-dimensional double-precision floating-point ndarrays. +- [`dgemm( arrays )`][@stdlib/blas/base/ndarray/dgemm]: perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. +- [`dgemv( arrays )`][@stdlib/blas/base/ndarray/dgemv]: perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. +- [`dger( arrays )`][@stdlib/blas/base/ndarray/dger]: perform the rank 1 operation `A = alpha*x*y^T + A`. - [`dnrm2( arrays )`][@stdlib/blas/base/ndarray/dnrm2]: compute the L2-norm of a one-dimensional double-precision floating-point ndarray. - [`dscal( arrays )`][@stdlib/blas/base/ndarray/dscal]: multiply a one-dimensional double-precision floating-point ndarray by a scalar constant. - [`dsdot( arrays )`][@stdlib/blas/base/ndarray/dsdot]: calculate the dot product of two one-dimensional single-precision floating-point ndarrays with double-precision accumulation. +- [`dspr( arrays )`][@stdlib/blas/base/ndarray/dspr]: perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form. - [`dswap( arrays )`][@stdlib/blas/base/ndarray/dswap]: interchange two one-dimensional double-precision floating-point ndarrays. +- [`dsyr( arrays )`][@stdlib/blas/base/ndarray/dsyr]: perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. +- [`dsyr2( arrays )`][@stdlib/blas/base/ndarray/dsyr2]: perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`. - [`dzasum( arrays )`][@stdlib/blas/base/ndarray/dzasum]: calculate the sum of absolute values for all elements in a one-dimensional double-precision complex floating-point ndarray. - [`dznrm2( arrays )`][@stdlib/blas/base/ndarray/dznrm2]: compute the L2-norm of a one-dimensional double-precision complex floating-point ndarray. - [`gasum( arrays )`][@stdlib/blas/base/ndarray/gasum]: calculate the sum of absolute values for all elements in a one-dimensional ndarray. - [`gaxpy( arrays )`][@stdlib/blas/base/ndarray/gaxpy]: multiply a one-dimensional ndarray `x` by a constant `alpha` and add the result to a one-dimensional ndarray `y`. - [`gcopy( arrays )`][@stdlib/blas/base/ndarray/gcopy]: copy values from a one-dimensional ndarray `x` into a one-dimensional ndarray `y`. - [`gdot( arrays )`][@stdlib/blas/base/ndarray/gdot]: calculate the dot product of two one-dimensional ndarrays. +- [`ggemm( arrays )`][@stdlib/blas/base/ndarray/ggemm]: perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. +- [`ggemv( arrays )`][@stdlib/blas/base/ndarray/ggemv]: perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. +- [`gger( arrays )`][@stdlib/blas/base/ndarray/gger]: perform the rank 1 operation `A = alpha*x*y^T + A`. - [`gnrm2( arrays )`][@stdlib/blas/base/ndarray/gnrm2]: compute the L2-norm of a one-dimensional ndarray. - [`gscal( arrays )`][@stdlib/blas/base/ndarray/gscal]: multiply a one-dimensional ndarray by a scalar constant. - [`gswap( arrays )`][@stdlib/blas/base/ndarray/gswap]: interchange two one-dimensional ndarrays. +- [`gsyr( arrays )`][@stdlib/blas/base/ndarray/gsyr]: perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. - [`idamax( arrays )`][@stdlib/blas/base/ndarray/idamax]: find the index of the first element having the maximum absolute value for all elements in a one-dimensional double-precision floating-point ndarray. - [`igamax( arrays )`][@stdlib/blas/base/ndarray/igamax]: find the index of the first element having the maximum absolute value for all elements in a one-dimensional ndarray. - [`isamax( arrays )`][@stdlib/blas/base/ndarray/isamax]: find the index of the first element having the maximum absolute value for all elements in a one-dimensional single-precision floating-point ndarray. @@ -77,9 +88,15 @@ The namespace exposes the following APIs: - [`scopy( arrays )`][@stdlib/blas/base/ndarray/scopy]: copy values from a one-dimensional single-precision floating-point ndarray `x` into a one-dimensional single-precision floating-point ndarray `y`. - [`sdot( arrays )`][@stdlib/blas/base/ndarray/sdot]: calculate the dot product of two one-dimensional single-precision floating-point ndarrays. - [`sdsdot( arrays )`][@stdlib/blas/base/ndarray/sdsdot]: calculate the dot product of two one-dimensional single-precision floating-point ndarrays with extended accumulation. +- [`sgemm( arrays )`][@stdlib/blas/base/ndarray/sgemm]: perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. +- [`sgemv( arrays )`][@stdlib/blas/base/ndarray/sgemv]: perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. +- [`sger( arrays )`][@stdlib/blas/base/ndarray/sger]: perform the rank 1 operation `A = alpha*x*y^T + A`. - [`snrm2( arrays )`][@stdlib/blas/base/ndarray/snrm2]: compute the L2-norm of a one-dimensional single-precision floating-point ndarray. - [`sscal( arrays )`][@stdlib/blas/base/ndarray/sscal]: multiply a one-dimensional single-precision floating-point ndarray by a scalar constant. +- [`sspr( arrays )`][@stdlib/blas/base/ndarray/sspr]: perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form. - [`sswap( arrays )`][@stdlib/blas/base/ndarray/sswap]: interchange two one-dimensional single-precision floating-point ndarrays. +- [`ssyr( arrays )`][@stdlib/blas/base/ndarray/ssyr]: perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. +- [`ssyr2( arrays )`][@stdlib/blas/base/ndarray/ssyr2]: perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`. - [`zaxpy( arrays )`][@stdlib/blas/base/ndarray/zaxpy]: multiply a one-dimensional double-precision complex floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision complex floating-point ndarray `y`. - [`zcopy( arrays )`][@stdlib/blas/base/ndarray/zcopy]: copy values from a one-dimensional double-precision complex floating-point ndarray `x` into a one-dimensional double-precision complex floating-point ndarray `y`. - [`zdscal( arrays )`][@stdlib/blas/base/ndarray/zdscal]: multiply a one-dimensional double-precision complex floating-point ndarray by a double-precision floating-point scalar constant. @@ -131,6 +148,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/base/ndarray/ccopy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ccopy +[@stdlib/blas/base/ndarray/cgemv]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/cgemv + [@stdlib/blas/base/ndarray/cscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/cscal [@stdlib/blas/base/ndarray/csscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/csscal @@ -145,14 +164,26 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/base/ndarray/ddot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ddot +[@stdlib/blas/base/ndarray/dgemm]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dgemm + +[@stdlib/blas/base/ndarray/dgemv]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dgemv + +[@stdlib/blas/base/ndarray/dger]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dger + [@stdlib/blas/base/ndarray/dnrm2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dnrm2 [@stdlib/blas/base/ndarray/dscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dscal [@stdlib/blas/base/ndarray/dsdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dsdot +[@stdlib/blas/base/ndarray/dspr]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dspr + [@stdlib/blas/base/ndarray/dswap]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dswap +[@stdlib/blas/base/ndarray/dsyr]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dsyr + +[@stdlib/blas/base/ndarray/dsyr2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dsyr2 + [@stdlib/blas/base/ndarray/dzasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dzasum [@stdlib/blas/base/ndarray/dznrm2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dznrm2 @@ -165,12 +196,20 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/base/ndarray/gdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gdot +[@stdlib/blas/base/ndarray/ggemm]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ggemm + +[@stdlib/blas/base/ndarray/ggemv]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ggemv + +[@stdlib/blas/base/ndarray/gger]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gger + [@stdlib/blas/base/ndarray/gnrm2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gnrm2 [@stdlib/blas/base/ndarray/gscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gscal [@stdlib/blas/base/ndarray/gswap]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gswap +[@stdlib/blas/base/ndarray/gsyr]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/gsyr + [@stdlib/blas/base/ndarray/idamax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/idamax [@stdlib/blas/base/ndarray/igamax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/igamax @@ -191,12 +230,24 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/base/ndarray/sdsdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sdsdot +[@stdlib/blas/base/ndarray/sgemm]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sgemm + +[@stdlib/blas/base/ndarray/sgemv]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sgemv + +[@stdlib/blas/base/ndarray/sger]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sger + [@stdlib/blas/base/ndarray/snrm2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/snrm2 [@stdlib/blas/base/ndarray/sscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sscal +[@stdlib/blas/base/ndarray/sspr]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sspr + [@stdlib/blas/base/ndarray/sswap]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sswap +[@stdlib/blas/base/ndarray/ssyr]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ssyr + +[@stdlib/blas/base/ndarray/ssyr2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ssyr2 + [@stdlib/blas/base/ndarray/zaxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/zaxpy [@stdlib/blas/base/ndarray/zcopy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/zcopy diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/README.md new file mode 100644 index 000000000000..5a1f35150666 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/README.md @@ -0,0 +1,152 @@ + + +# cgemv + +> Perform one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var cgemv = require( '@stdlib/blas/base/ndarray/cgemv' ); +``` + +#### cgemv( arrays ) + +Performs one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + + + +```javascript +var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + +var A = new Complex64Matrix( [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ] ); +var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' +}); +var beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' +}); + +var out = cgemv( [ A, x, y, trans, alpha, beta ] ); +// returns [ [ -9.0, 30.0 ], [ -15.0, 72.0 ] ] + +var bool = ( out === y ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var cgemv = require( '@stdlib/blas/base/ndarray/cgemv' ); + +var opts = { + 'dtype': 'float32' +}; + +var A = new Complex64Matrix( discreteUniform( 24, 0, 10, opts ).buffer, 0, [ 3, 4 ] ); +var x = new Complex64Vector( discreteUniform( 8, 0, 10, opts ) ); +var y = new Complex64Vector( discreteUniform( 6, 0, 10, opts ) ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' +}); +var beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' +}); + +var out = cgemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/benchmark/benchmark.js new file mode 100644 index 000000000000..fb018b0a67ac --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/benchmark/benchmark.js @@ -0,0 +1,139 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var realf = require( '@stdlib/complex/float32/real' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cgemv = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'complex64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var A; + var x; + var y; + + Abuf = uniform( len*len*2, -100.0, 100.0, { + 'dtype': 'float32' + }); + A = new Complex64Matrix( Abuf.buffer, 0, [ len, len ] ); + + xbuf = uniform( len*2, -100.0, 100.0, { + 'dtype': 'float32' + }); + x = new Complex64Vector( xbuf.buffer ); + + ybuf = uniform( len*2, -100.0, 100.0, { + 'dtype': 'float32' + }); + y = new Complex64Vector( ybuf.buffer ); + + alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), options ); + beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), options ); + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = cgemv( [ A, x, y, trans, alpha, beta ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( realf( z.get( i%len ) ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/repl.txt new file mode 100644 index 000000000000..44f44c2eba7a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Performs one of the matrix-vector operations `y = alpha*A*x + beta*y`, + `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`, where `alpha` + and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` + is an `M` by `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `beta`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var abuf = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/complex64}}( abuf ); + + > var xbuf = [ 1.0, 2.0, 3.0, 4.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/complex64}}( xbuf ); + + > var ybuf = [ 1.0, 2.0, 3.0, 4.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/complex64}}( ybuf ); + + > var opts = { 'dtype': 'complex64' }; + > var ca = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 0.0 ); + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( ca, opts ); + + > var cb = new {{alias:@stdlib/complex/float32/ctor}}( 1.0, 0.0 ); + > var beta = {{alias:@stdlib/ndarray/from-scalar}}( cb, opts ); + + > var trans = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + + > {{alias}}( [ A, x, y, trans, alpha, beta ] ); + > y + [ [ -9.0, 30.0 ], [ -15.0, 72.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/types/index.d.ts new file mode 100644 index 000000000000..4fb92374d8a6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/types/index.d.ts @@ -0,0 +1,74 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { complex64ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); +* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Complex64Matrix( [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ] ); +* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var y = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { +* 'dtype': 'complex64' +* }); +* var beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { +* 'dtype': 'complex64' +* }); +* +* var z = cgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ [ -9.0, 30.0 ], [ -15.0, 72.0 ] ] +* +* var bool = ( z === y ); +* // returns true +*/ +declare function cgemv( arrays: [ complex64ndarray, complex64ndarray, complex64ndarray, ndarray, complex64ndarray, complex64ndarray ] ): complex64ndarray; + + +// EXPORTS // + +export = cgemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/types/test.ts new file mode 100644 index 000000000000..1e452d275cef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/docs/types/test.ts @@ -0,0 +1,87 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import cgemv = require( '@stdlib/blas/base/ndarray/cgemv' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'complex64' + }); + const x = zeros( [ 3 ], { + 'dtype': 'complex64' + }); + const y = zeros( [ 2 ], { + 'dtype': 'complex64' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'complex64' + }); + const beta = zeros( [], { + 'dtype': 'complex64' + }); + + cgemv( [ A, x, y, trans, alpha, beta ] ); // $ExpectType complex64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + cgemv( '10' ); // $ExpectError + cgemv( 10 ); // $ExpectError + cgemv( true ); // $ExpectError + cgemv( false ); // $ExpectError + cgemv( null ); // $ExpectError + cgemv( undefined ); // $ExpectError + cgemv( [] ); // $ExpectError + cgemv( {} ); // $ExpectError + cgemv( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'complex64' + }); + const x = zeros( [ 3 ], { + 'dtype': 'complex64' + }); + const y = zeros( [ 2 ], { + 'dtype': 'complex64' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'complex64' + }); + const beta = zeros( [], { + 'dtype': 'complex64' + }); + + cgemv(); // $ExpectError + cgemv( [ A, x, y, trans, alpha, beta ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/examples/index.js new file mode 100644 index 000000000000..816f65952baa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/examples/index.js @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var cgemv = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var A = new Complex64Matrix( discreteUniform( 24, 0, 10, opts ).buffer, 0, [ 3, 4 ] ); +var x = new Complex64Vector( discreteUniform( 8, 0, 10, opts ) ); +var y = new Complex64Vector( discreteUniform( 6, 0, 10, opts ) ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' +}); +var beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' +}); + +var out = cgemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/lib/index.js new file mode 100644 index 000000000000..21771b44bd23 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/lib/index.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`. +* +* @module @stdlib/blas/base/ndarray/cgemv +* +* @example +* var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); +* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* var cgemv = require( '@stdlib/blas/base/ndarray/cgemv' ); +* +* var A = new Complex64Matrix( [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ] ); +* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var y = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { +* 'dtype': 'complex64' +* }); +* var beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { +* 'dtype': 'complex64' +* }); +* +* var out = cgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ [ -9.0, 30.0 ], [ -15.0, 72.0 ] ] +* +* var bool = ( out === y ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/lib/main.js new file mode 100644 index 000000000000..5ad4e3565dcc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/lib/main.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/cgemv' ).ndarray; + + +// MAIN // + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); +* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Complex64Matrix( [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ] ); +* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var y = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { +* 'dtype': 'complex64' +* }); +* var beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { +* 'dtype': 'complex64' +* }); +* +* var z = cgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ [ -9.0, 30.0 ], [ -15.0, 72.0 ] ] +* +* var bool = ( z === y ); +* // returns true +*/ +function cgemv( arrays ) { + var trans; + var alpha; + var beta; + var sh; + var st; + var A; + var x; + var y; + + A = arrays[ 0 ]; + x = arrays[ 1 ]; + y = arrays[ 2 ]; + + trans = ndarraylike2scalar( arrays[ 3 ] ); + alpha = ndarraylike2scalar( arrays[ 4 ] ); + beta = ndarraylike2scalar( arrays[ 5 ] ); + + sh = getShape( A, false ); + st = getStrides( A, false ); + + strided( trans, sh[ 0 ], sh[ 1 ], alpha, getData( A ), st[ 0 ], st[ 1 ], getOffset( A ), getData( x ), getStride( x, 0 ), getOffset( x ), beta, getData( y ), getStride( y, 0 ), getOffset( y ) ); + + return y; +} + + +// EXPORTS // + +module.exports = cgemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/package.json new file mode 100644 index 000000000000..8fb04277dfc7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/cgemv", + "version": "0.0.0", + "description": "Perform one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "cgemv", + "linear", + "algebra", + "subroutines", + "matrix-vector", + "multiply", + "vector", + "matrix", + "array", + "ndarray", + "complex64", + "complex", + "complex64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/test/test.js new file mode 100644 index 000000000000..61fb6e7d2fe2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/cgemv/test/test.js @@ -0,0 +1,567 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var cgemv = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'complex64', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cgemv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( cgemv.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + ybuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ -9.0, 30.0, -15.0, 72.0, -21.0, 114.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + ybuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ -52.0, 296.0, -60.0, 384.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A^T*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + ybuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ -11.0, 44.0, -13.0, 66.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A^H*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + ybuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'conjugate-transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ 45.0, 4.0, 67.0, 10.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation with complex scalars', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + ybuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( new Complex64( 0.5, 0.5 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 0.5, -0.5 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ -17.5, 9.5, -39.5, 25.5 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0 // 1 + ]); + ybuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( new Complex64( 0.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ 2.0, 4.0, 6.0, 8.0, 10.0, 12.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides (transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0 // 1 + ]); + x = vector( xbuf, 2, 2, 0 ); + + ybuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0 // 2 + ]); + y = vector( ybuf, 3, 2, 0 ); + + alpha = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ -26.0, 116.0, 0.0, 0.0, -30.0, 160.0, 0.0, 0.0, -34.0, 204.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides (conjugate-transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = new Complex64Array([ + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 1.0, // 0 + 2.0 // 0 + ]); + x = vector( xbuf, 2, -2, 2 ); + + ybuf = new Complex64Array([ + 5.0, // 2 + 6.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 1.0, // 0 + 2.0 // 0 + ]); + y = vector( ybuf, 3, -2, 4 ); + + alpha = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'conjugate-transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array( [ 206.0, 36.0, 0.0, 0.0, 162.0, 24.0, 0.0, 0.0, 118.0, 12.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0 + ]); + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + + xbuf = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + x = vector( xbuf, 3, 1, 2 ); + + ybuf = new Complex64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0 // 1 + ]); + y = vector( ybuf, 2, 2, 1 ); + + alpha = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + beta = scalar2ndarray( new Complex64( 2.0, 0.0 ), { + 'dtype': 'complex64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = cgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Complex64Array([ + 0.0, + 0.0, + -40.0, + 180.0, + 0.0, + 0.0, + -72.0, + 436.0 + ]); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/README.md new file mode 100644 index 000000000000..1bc8c67dde33 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/README.md @@ -0,0 +1,146 @@ + + +# dgemm + +> Perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dgemm = require( '@stdlib/blas/base/ndarray/dgemm' ); +``` + +#### dgemm( arrays ) + +Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + +```javascript +var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + +var A = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +var B = new Float64Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +var C = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); +var beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); + +var out = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); +// returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + +var bool = ( out === C ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a two-dimensional input ndarray corresponding to `B`. + - a two-dimensional input/output ndarray corresponding to `C`. + - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dgemm = require( '@stdlib/blas/base/ndarray/dgemm' ); + +var opts = { + 'dtype': 'float64' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var B = discreteUniform( [ 4, 2 ], 0, 10, opts ); +var C = discreteUniform( [ 3, 2 ], 0, 10, opts ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/benchmark/benchmark.js new file mode 100644 index 000000000000..2ad514bf7f6e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/benchmark/benchmark.js @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dgemm = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var transA; + var transB; + var alpha; + var beta; + var A; + var B; + var C; + + A = uniform( [ len, len ], -100.0, 100.0, options ); + B = uniform( [ len, len ], -100.0, 100.0, options ); + C = uniform( [ len, len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + beta = scalar2ndarray( 1.0, options ); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( i%len, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/repl.txt new file mode 100644 index 000000000000..62f1588fec66 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, + where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` + are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` + matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a two-dimensional input ndarray corresponding to `B`. + - a two-dimensional input/output ndarray corresponding to `C`. + - a zero-dimensional ndarray specifying whether `A` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray specifying whether `B` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `beta`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var abuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float64}}( abuf ); + + > var bbuf = [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ]; + > var B = new {{alias:@stdlib/ndarray/matrix/float64}}( bbuf ); + + > var cbuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]; + > var C = new {{alias:@stdlib/ndarray/matrix/float64}}( cbuf ); + + > var opts = { 'dtype': 'float64' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > var beta = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var transA = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + > var transB = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + + > {{alias}}( [ A, B, C, transA, transB, alpha, beta ] ); + > C + [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/types/index.d.ts new file mode 100644 index 000000000000..57d7cd9dbb62 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/types/index.d.ts @@ -0,0 +1,76 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a two-dimensional input ndarray corresponding to `B`. +* - a two-dimensional input/output ndarray corresponding to `C`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* var B = new Float64Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +* var C = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var z = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( z === C ); +* // returns true +*/ +declare function dgemm( arrays: [ float64ndarray, float64ndarray, float64ndarray, ndarray, ndarray, float64ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dgemm; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/types/test.ts new file mode 100644 index 000000000000..7e5afa0d84bd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/docs/types/test.ts @@ -0,0 +1,93 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dgemm = require( '@stdlib/blas/base/ndarray/dgemm' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const A = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + const B = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + const C = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + const transA = zeros( [], { + 'dtype': 'int32' + }); + const transB = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + const beta = zeros( [], { + 'dtype': 'float64' + }); + + dgemm( [ A, B, C, transA, transB, alpha, beta ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dgemm( '10' ); // $ExpectError + dgemm( 10 ); // $ExpectError + dgemm( true ); // $ExpectError + dgemm( false ); // $ExpectError + dgemm( null ); // $ExpectError + dgemm( undefined ); // $ExpectError + dgemm( [] ); // $ExpectError + dgemm( {} ); // $ExpectError + dgemm( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + const B = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + const C = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + const transA = zeros( [], { + 'dtype': 'int32' + }); + const transB = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + const beta = zeros( [], { + 'dtype': 'float64' + }); + + dgemm(); // $ExpectError + dgemm( [ A, B, C, transA, transB, alpha, beta ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/examples/index.js new file mode 100644 index 000000000000..21377c39b161 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dgemm = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var B = discreteUniform( [ 4, 2 ], 0, 10, opts ); +var C = discreteUniform( [ 3, 2 ], 0, 10, opts ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/lib/index.js new file mode 100644 index 000000000000..ca4ead3d7541 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 3 routine to perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. +* +* @module @stdlib/blas/base/ndarray/dgemm +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* var dgemm = require( '@stdlib/blas/base/ndarray/dgemm' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* var B = new Float64Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +* var C = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var out = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( out === C ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/lib/main.js new file mode 100644 index 000000000000..00f94f4b5c88 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/lib/main.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var strided = require( '@stdlib/blas/base/dgemm' ).ndarray; + + +// VARIABLES // + +var NO_TRANSPOSE = resolveEnum( 'no-transpose' ); + + +// MAIN // + +/** +* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a two-dimensional input ndarray corresponding to `B`. +* - a two-dimensional input/output ndarray corresponding to `C`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* var B = new Float64Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +* var C = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var z = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( z === C ); +* // returns true +*/ +function dgemm( arrays ) { + var transA; + var transB; + var alpha; + var beta; + var shA; + var shC; + var stA; + var stB; + var stC; + var A; + var B; + var C; + var M; + var N; + var K; + + A = arrays[ 0 ]; + B = arrays[ 1 ]; + C = arrays[ 2 ]; + + transA = ndarraylike2scalar( arrays[ 3 ] ); + transB = ndarraylike2scalar( arrays[ 4 ] ); + alpha = ndarraylike2scalar( arrays[ 5 ] ); + beta = ndarraylike2scalar( arrays[ 6 ] ); + + shA = getShape( A, false ); + shC = getShape( C, false ); + + stA = getStrides( A, false ); + stB = getStrides( B, false ); + stC = getStrides( C, false ); + + M = shC[ 0 ]; + N = shC[ 1 ]; + if ( resolveEnum( transA ) === NO_TRANSPOSE ) { + K = shA[ 1 ]; + } else { + K = shA[ 0 ]; + } + + strided( transA, transB, M, N, K, alpha, getData( A ), stA[ 0 ], stA[ 1 ], getOffset( A ), getData( B ), stB[ 0 ], stB[ 1 ], getOffset( B ), beta, getData( C ), stC[ 0 ], stC[ 1 ], getOffset( C ) ); // eslint-disable-line max-len + + return C; +} + + +// EXPORTS // + +module.exports = dgemm; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/package.json new file mode 100644 index 000000000000..24095a086cd8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/base/ndarray/dgemm", + "version": "0.0.0", + "description": "Perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 3", + "dgemm", + "linear", + "algebra", + "subroutines", + "matrix-matrix", + "multiply", + "matrix", + "array", + "ndarray", + "float64", + "double", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/test/test.js new file mode 100644 index 000000000000..40643663c26d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemm/test/test.js @@ -0,0 +1,441 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dgemm = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'float64', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dgemm, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dgemm.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (no-transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 23.0, 29.0, 50.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 36.0, 45.0, 45.0, 57.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (no-transpose, transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 2, 3, 3, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 15.0, 33.0, 33.0, 78.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (conjugate-transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'conjugate-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 36.0, 45.0, 45.0, 57.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function correctly applies both `alpha` and `beta` scalars', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 3.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 47.0, 62.0, 107.0, 140.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `beta*C`', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 2.0, 4.0, 6.0, 8.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports column-major ndarrays', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] ); + Bbuf = new Float64Array( [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + B = matrix( Bbuf, 3, 2, 1, 3, 0 ); + C = matrix( Cbuf, 2, 2, 1, 2, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 23.0, 50.0, 29.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 4.0, 5.0, 6.0, 1.0, 2.0, 3.0 ] ); + Bbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, -3, 1, 3 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 23.0, 29.0, 50.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float64Array( [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float64Array( [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float64Array( [ 0.0, 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + B = matrix( Bbuf, 3, 2, 2, 1, 2 ); + C = matrix( Cbuf, 2, 2, 2, 1, 1 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float64Array( [ 0.0, 23.0, 29.0, 50.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/README.md new file mode 100644 index 000000000000..7115cde23839 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/README.md @@ -0,0 +1,140 @@ + + +# dgemv + +> Perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dgemv = require( '@stdlib/blas/base/ndarray/dgemv' ); +``` + +#### dgemv( arrays ) + +Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + +```javascript +var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + +var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +var y = new Float64Vector( [ 4.0, 5.0 ] ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); +var beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); + +var out = dgemv( [ A, x, y, trans, alpha, beta ] ); +// returns [ 18.0, 37.0 ] + +var bool = ( out === y ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dgemv = require( '@stdlib/blas/base/ndarray/dgemv' ); + +var opts = { + 'dtype': 'float64' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = dgemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/benchmark/benchmark.js new file mode 100644 index 000000000000..530f8e8792e2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/benchmark/benchmark.js @@ -0,0 +1,121 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dgemv = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var trans; + var alpha; + var beta; + var A; + var x; + var y; + + A = uniform( [ len, len ], -100.0, 100.0, options ); + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + beta = scalar2ndarray( 1.0, options ); + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dgemv( [ A, x, y, trans, alpha, beta ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/repl.txt new file mode 100644 index 000000000000..d25f8e75abf5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/repl.txt @@ -0,0 +1,50 @@ + +{{alias}}( arrays ) + Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` + or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` + and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `beta`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float64}}( abuf ); + + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf ); + + > var ybuf = [ 4.0, 5.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float64}}( ybuf ); + + > var opts = { 'dtype': 'float64' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > var beta = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var trans = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + + > {{alias}}( [ A, x, y, trans, alpha, beta ] ); + > y + [ 18.0, 37.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/types/index.d.ts new file mode 100644 index 000000000000..d25a1ee60613 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/types/index.d.ts @@ -0,0 +1,73 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float64Vector( [ 4.0, 5.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var z = dgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +declare function dgemv( arrays: [ float64ndarray, float64ndarray, float64ndarray, ndarray, float64ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dgemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/types/test.ts new file mode 100644 index 000000000000..3a8b5222504f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/docs/types/test.ts @@ -0,0 +1,87 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dgemv = require( '@stdlib/blas/base/ndarray/dgemv' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'float64' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 2 ], { + 'dtype': 'float64' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + const beta = zeros( [], { + 'dtype': 'float64' + }); + + dgemv( [ A, x, y, trans, alpha, beta ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dgemv( '10' ); // $ExpectError + dgemv( 10 ); // $ExpectError + dgemv( true ); // $ExpectError + dgemv( false ); // $ExpectError + dgemv( null ); // $ExpectError + dgemv( undefined ); // $ExpectError + dgemv( [] ); // $ExpectError + dgemv( {} ); // $ExpectError + dgemv( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'float64' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 2 ], { + 'dtype': 'float64' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + const beta = zeros( [], { + 'dtype': 'float64' + }); + + dgemv(); // $ExpectError + dgemv( [ A, x, y, trans, alpha, beta ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/examples/index.js new file mode 100644 index 000000000000..bbae3b29371e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dgemv = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = dgemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/lib/index.js new file mode 100644 index 000000000000..f40843a67cc9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/lib/index.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. +* +* @module @stdlib/blas/base/ndarray/dgemv +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* var dgemv = require( '@stdlib/blas/base/ndarray/dgemv' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float64Vector( [ 4.0, 5.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var out = dgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( out === y ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/lib/main.js new file mode 100644 index 000000000000..83f0de511be6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/lib/main.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/dgemv' ).ndarray; + + +// MAIN // + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float64Vector( [ 4.0, 5.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var z = dgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +function dgemv( arrays ) { + var trans; + var alpha; + var beta; + var sh; + var st; + var A; + var x; + var y; + + A = arrays[ 0 ]; + x = arrays[ 1 ]; + y = arrays[ 2 ]; + + trans = ndarraylike2scalar( arrays[ 3 ] ); + alpha = ndarraylike2scalar( arrays[ 4 ] ); + beta = ndarraylike2scalar( arrays[ 5 ] ); + + sh = getShape( A, false ); + st = getStrides( A, false ); + + strided( trans, sh[ 0 ], sh[ 1 ], alpha, getData( A ), st[ 0 ], st[ 1 ], getOffset( A ), getData( x ), getStride( x, 0 ), getOffset( x ), beta, getData( y ), getStride( y, 0 ), getOffset( y ) ); + + return y; +} + + +// EXPORTS // + +module.exports = dgemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/package.json new file mode 100644 index 000000000000..20cc76d15a40 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/dgemv", + "version": "0.0.0", + "description": "Perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "dgemv", + "linear", + "algebra", + "subroutines", + "matrix-vector", + "multiply", + "vector", + "matrix", + "array", + "ndarray", + "float64", + "double", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/test/test.js new file mode 100644 index 000000000000..b31de09684ba --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dgemv/test/test.js @@ -0,0 +1,457 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dgemv = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'float64', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dgemv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dgemv.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array( [ 6.0, 13.0, 20.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array( [ 46.0, 60.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A^T*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array( [ 8.0, 12.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A^H*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'conjugate-transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array( [ 8.0, 12.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array( [ 2.0, 4.0, 6.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides (transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = new Float64Array([ + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + x = vector( xbuf, 2, 2, 0 ); + + ybuf = new Float64Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 0 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array( [ 20.0, 0.0, 28.0, 0.0, 36.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides (transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = new Float64Array([ + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + x = vector( xbuf, 2, -2, 2 ); + + ybuf = new Float64Array([ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + y = vector( ybuf, 3, -2, 4 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array( [ 36.0, 0.0, 28.0, 0.0, 20.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Float64Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + + xbuf = new Float64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + x = vector( xbuf, 3, 1, 2 ); + + ybuf = new Float64Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + y = vector( ybuf, 2, 2, 1 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = dgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float64Array([ + 0.0, + 30.0, + 0.0, + 68.0 + ]); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dger/README.md new file mode 100644 index 000000000000..8634c9ad90c3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/README.md @@ -0,0 +1,126 @@ + + +# dger + +> Perform the rank 1 operation `A = alpha*x*y^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dger = require( '@stdlib/blas/base/ndarray/dger' ); +``` + +#### dger( arrays ) + +Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + +```javascript +var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = new Float64Vector( [ 1.0, 2.0 ] ); +var y = new Float64Vector( [ 3.0, 4.0, 5.0 ] ); +var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); + +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); + +var out = dger( [ x, y, A, alpha ] ); +// returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + +var bool = ( out === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dger = require( '@stdlib/blas/base/ndarray/dger' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 4 ], 0, 10, opts ); +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); + +var alpha = scalar2ndarray( 1.0, opts ); + +var out = dger( [ x, y, A, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dger/benchmark/benchmark.js new file mode 100644 index 000000000000..b8e0b9e73a34 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dger = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var x; + var y; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + A = uniform( [ len, len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dger( [ x, y, A, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/repl.txt new file mode 100644 index 000000000000..026391984502 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( arrays ) + Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a + scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by + `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf ); + + > var ybuf = [ 3.0, 4.0, 5.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float64}}( ybuf ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float64}}( abuf ); + + > var opts = { 'dtype': 'float64' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > {{alias}}( [ x, y, A, alpha ] ); + > A + [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/types/index.d.ts new file mode 100644 index 000000000000..c39ccca34c1a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/types/index.d.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 1.0, 2.0 ] ); +* var y = new Float64Vector( [ 3.0, 4.0, 5.0 ] ); +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var z = dger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +declare function dger( arrays: [ float64ndarray, float64ndarray, float64ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dger; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/types/test.ts new file mode 100644 index 000000000000..2f761c5dd678 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dger = require( '@stdlib/blas/base/ndarray/dger' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 2 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const A = zeros( [ 2, 3 ], { + 'dtype': 'float64' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dger( [ x, y, A, alpha ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dger( '10' ); // $ExpectError + dger( 10 ); // $ExpectError + dger( true ); // $ExpectError + dger( false ); // $ExpectError + dger( null ); // $ExpectError + dger( undefined ); // $ExpectError + dger( [] ); // $ExpectError + dger( {} ); // $ExpectError + dger( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const A = zeros( [ 2, 3 ], { + 'dtype': 'float64' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dger(); // $ExpectError + dger( [ x, y, A, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dger/examples/index.js new file mode 100644 index 000000000000..83c7515b48c2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dger = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 4 ], 0, 10, opts ); +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); + +var alpha = scalar2ndarray( 1.0, opts ); + +var out = dger( [ x, y, A, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dger/lib/index.js new file mode 100644 index 000000000000..b8cc1346d291 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the rank 1 operation `A = alpha*x*y^T + A`. +* +* @module @stdlib/blas/base/ndarray/dger +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dger = require( '@stdlib/blas/base/ndarray/dger' ); +* +* var x = new Float64Vector( [ 1.0, 2.0 ] ); +* var y = new Float64Vector( [ 3.0, 4.0, 5.0 ] ); +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var out = dger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( out === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dger/lib/main.js new file mode 100644 index 000000000000..b226a2763e0c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/lib/main.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/dger' ).ndarray; + + +// MAIN // + +/** +* Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 1.0, 2.0 ] ); +* var y = new Float64Vector( [ 3.0, 4.0, 5.0 ] ); +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var z = dger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +function dger( arrays ) { + var alpha; + var sh; + var st; + var A; + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + A = arrays[ 2 ]; + + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + sh = getShape( A, false ); + st = getStrides( A, false ); + + strided( sh[ 0 ], sh[ 1 ], alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) ); + + return A; +} + + +// EXPORTS // + +module.exports = dger; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/dger/package.json new file mode 100644 index 000000000000..c743093fee96 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/dger", + "version": "0.0.0", + "description": "Perform the rank 1 operation `A = alpha*x*y^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "dger", + "linear", + "algebra", + "subroutines", + "rank-1", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float64", + "double", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dger/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dger/test/test.js new file mode 100644 index 000000000000..17e5ab837cda --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dger/test/test.js @@ -0,0 +1,315 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dger = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'float64', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dger, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dger.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the rank 1 operation `A = alpha*x*y^T + A`', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + v = dger( [ x, y, A, alpha ] ); + + expected = new Float64Array( [ 2.0, 4.0, 6.0, 6.0, 9.0, 12.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + v = dger( [ x, y, A, alpha ] ); + + expected = new Float64Array( [ 2.0, 4.0, 5.0, 8.0, 8.0, 12.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float64Array([ + 3.0, // 0 + 4.0, // 1 + 5.0 // 2 + ]); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + + v = dger( [ x, y, A, alpha ] ); + + expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + x = vector( xbuf, 2, 2, 0 ); + + ybuf = new Float64Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 0 ); + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + v = dger( [ x, y, A, alpha ] ); + + expected = new Float64Array( [ 3.0, 6.0, 9.0, 8.0, 13.0, 18.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + x = vector( xbuf, 2, -2, 2 ); + + ybuf = new Float64Array([ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + y = vector( ybuf, 3, -2, 4 ); + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + v = dger( [ x, y, A, alpha ] ); + + expected = new Float64Array( [ 3.0, 6.0, 9.0, 8.0, 13.0, 18.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + x = vector( xbuf, 2, 2, 1 ); + + ybuf = new Float64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + y = vector( ybuf, 3, 1, 2 ); + + Abuf = new Float64Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + v = dger( [ x, y, A, alpha ] ); + + expected = new Float64Array([ + 0.0, + 0.0, + 2.0, + 4.0, + 6.0, + 6.0, + 9.0, + 12.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dnrm2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dnrm2/README.md index 47e6b4a7b372..d240ea1ac2cf 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/dnrm2/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dnrm2/README.md @@ -33,7 +33,7 @@ The [L2-norm][l2-norm] is defined as ``` @@ -66,9 +66,7 @@ var y = dnrm2( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts index f5232ebb360b..dc5366bc9425 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts @@ -22,6 +22,7 @@ import caxpy = require( '@stdlib/blas/base/ndarray/caxpy' ); import ccopy = require( '@stdlib/blas/base/ndarray/ccopy' ); +import cgemv = require( '@stdlib/blas/base/ndarray/cgemv' ); import cscal = require( '@stdlib/blas/base/ndarray/cscal' ); import csscal = require( '@stdlib/blas/base/ndarray/csscal' ); import cswap = require( '@stdlib/blas/base/ndarray/cswap' ); @@ -29,19 +30,29 @@ import dasum = require( '@stdlib/blas/base/ndarray/dasum' ); import daxpy = require( '@stdlib/blas/base/ndarray/daxpy' ); import dcopy = require( '@stdlib/blas/base/ndarray/dcopy' ); import ddot = require( '@stdlib/blas/base/ndarray/ddot' ); +import dgemm = require( '@stdlib/blas/base/ndarray/dgemm' ); +import dgemv = require( '@stdlib/blas/base/ndarray/dgemv' ); +import dger = require( '@stdlib/blas/base/ndarray/dger' ); import dnrm2 = require( '@stdlib/blas/base/ndarray/dnrm2' ); import dscal = require( '@stdlib/blas/base/ndarray/dscal' ); import dsdot = require( '@stdlib/blas/base/ndarray/dsdot' ); +import dspr = require( '@stdlib/blas/base/ndarray/dspr' ); import dswap = require( '@stdlib/blas/base/ndarray/dswap' ); +import dsyr = require( '@stdlib/blas/base/ndarray/dsyr' ); +import dsyr2 = require( '@stdlib/blas/base/ndarray/dsyr2' ); import dzasum = require( '@stdlib/blas/base/ndarray/dzasum' ); import dznrm2 = require( '@stdlib/blas/base/ndarray/dznrm2' ); import gasum = require( '@stdlib/blas/base/ndarray/gasum' ); import gaxpy = require( '@stdlib/blas/base/ndarray/gaxpy' ); import gcopy = require( '@stdlib/blas/base/ndarray/gcopy' ); import gdot = require( '@stdlib/blas/base/ndarray/gdot' ); +import ggemm = require( '@stdlib/blas/base/ndarray/ggemm' ); +import ggemv = require( '@stdlib/blas/base/ndarray/ggemv' ); +import gger = require( '@stdlib/blas/base/ndarray/gger' ); import gnrm2 = require( '@stdlib/blas/base/ndarray/gnrm2' ); import gscal = require( '@stdlib/blas/base/ndarray/gscal' ); import gswap = require( '@stdlib/blas/base/ndarray/gswap' ); +import gsyr = require( '@stdlib/blas/base/ndarray/gsyr' ); import idamax = require( '@stdlib/blas/base/ndarray/idamax' ); import igamax = require( '@stdlib/blas/base/ndarray/igamax' ); import isamax = require( '@stdlib/blas/base/ndarray/isamax' ); @@ -52,9 +63,15 @@ import scnrm2 = require( '@stdlib/blas/base/ndarray/scnrm2' ); import scopy = require( '@stdlib/blas/base/ndarray/scopy' ); import sdot = require( '@stdlib/blas/base/ndarray/sdot' ); import sdsdot = require( '@stdlib/blas/base/ndarray/sdsdot' ); +import sgemm = require( '@stdlib/blas/base/ndarray/sgemm' ); +import sgemv = require( '@stdlib/blas/base/ndarray/sgemv' ); +import sger = require( '@stdlib/blas/base/ndarray/sger' ); import snrm2 = require( '@stdlib/blas/base/ndarray/snrm2' ); import sscal = require( '@stdlib/blas/base/ndarray/sscal' ); +import sspr = require( '@stdlib/blas/base/ndarray/sspr' ); import sswap = require( '@stdlib/blas/base/ndarray/sswap' ); +import ssyr = require( '@stdlib/blas/base/ndarray/ssyr' ); +import ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' ); import zaxpy = require( '@stdlib/blas/base/ndarray/zaxpy' ); import zcopy = require( '@stdlib/blas/base/ndarray/zcopy' ); import zdscal = require( '@stdlib/blas/base/ndarray/zdscal' ); @@ -126,6 +143,52 @@ interface Namespace { */ ccopy: typeof ccopy; + /** + * Performs one of the matrix-vector operations `y = alpha*A*x + beta*y`, `y = alpha*A^T*x + beta*y`, or `y = alpha*A^H*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a two-dimensional input ndarray corresponding to `A`. + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input/output ndarray corresponding to `y`. + * - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Complex64Matrix = require( '@stdlib/ndarray/matrix/complex64' ); + * var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32/ctor' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + * + * var A = new Complex64Matrix( [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ] ); + * var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); + * + * var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int8' + * }); + * var alpha = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + * 'dtype': 'complex64' + * }); + * var beta = scalar2ndarray( new Complex64( 1.0, 0.0 ), { + * 'dtype': 'complex64' + * }); + * + * var z = ns.cgemv( [ A, x, y, trans, alpha, beta ] ); + * // returns [ [ -9.0, 30.0 ], [ -15.0, 72.0 ] ] + * + * var bool = ( z === y ); + * // returns true + */ + cgemv: typeof cgemv; + /** * Multiplies a one-dimensional single-precision complex floating-point ndarray by a scalar constant. * @@ -323,6 +386,135 @@ interface Namespace { */ ddot: typeof ddot; + /** + * Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a two-dimensional input ndarray corresponding to `A`. + * - a two-dimensional input ndarray corresponding to `B`. + * - a two-dimensional input/output ndarray corresponding to `C`. + * - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + * + * var A = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); + * var B = new Float64Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); + * var C = new Float64Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); + * + * var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int32' + * }); + * var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float64' + * }); + * var beta = scalar2ndarray( 1.0, { + * 'dtype': 'float64' + * }); + * + * var z = ns.dgemm( [ A, B, C, transA, transB, alpha, beta ] ); + * // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + * + * var bool = ( z === C ); + * // returns true + */ + dgemm: typeof dgemm; + + /** + * Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a two-dimensional input ndarray corresponding to `A`. + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input/output ndarray corresponding to `y`. + * - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + * + * var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); + * var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); + * var y = new Float64Vector( [ 4.0, 5.0 ] ); + * + * var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int8' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float64' + * }); + * var beta = scalar2ndarray( 1.0, { + * 'dtype': 'float64' + * }); + * + * var z = ns.dgemv( [ A, x, y, trans, alpha, beta ] ); + * // returns [ 18.0, 37.0 ] + * + * var bool = ( z === y ); + * // returns true + */ + dgemv: typeof dgemv; + + /** + * Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input ndarray corresponding to `y`. + * - a two-dimensional input/output ndarray corresponding to `A`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = new Float64Vector( [ 1.0, 2.0 ] ); + * var y = new Float64Vector( [ 3.0, 4.0, 5.0 ] ); + * var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); + * + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float64' + * }); + * + * var z = ns.dger( [ x, y, A, alpha ] ); + * // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + * + * var bool = ( z === A ); + * // returns true + */ + dger: typeof dger; + /** * Computes the L2-norm of a one-dimensional double-precision floating-point ndarray. * @@ -400,6 +592,44 @@ interface Namespace { */ dsdot: typeof dsdot; + /** + * Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by `N` matrix supplied in packed form. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input/output ndarray corresponding to the packed form of `A`. + * - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + * + * var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); + * var AP = new Float64Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + * + * var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + * 'dtype': 'int8' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float64' + * }); + * + * var y = ns.dspr( [ x, AP, uplo, alpha ] ); + * // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] + * + * var bool = ( y === AP ); + * // returns true + */ + dspr: typeof dspr; + /** * Interchanges two one-dimensional double-precision floating-point ndarrays. * @@ -428,6 +658,86 @@ interface Namespace { */ dswap: typeof dswap; + /** + * Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a two-dimensional input/output ndarray corresponding to `A`. + * - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + * + * var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); + * var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); + * + * var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float64' + * }); + * + * var y = ns.dsyr( [ x, A, uplo, alpha ] ); + * // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] + * + * var bool = ( y === A ); + * // returns true + */ + dsyr: typeof dsyr; + + /** + * Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input ndarray corresponding to `y`. + * - a two-dimensional input/output ndarray corresponding to `A`. + * - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); + * var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); + * var y = new Float64Vector( [ 2.0, 1.0, 3.0 ] ); + * + * var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 2.0, { + * 'dtype': 'float64' + * }); + * + * var z = ns.dsyr2( [ x, y, A, uplo, alpha ] ); + * // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] + * + * var bool = ( z === A ); + * // returns true + */ + dsyr2: typeof dsyr2; + /** * Computes the sum of absolute values for all elements in a one-dimensional double-precision complex floating-point ndarray. * @@ -578,6 +888,135 @@ interface Namespace { */ gdot: typeof gdot; + /** + * Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a two-dimensional input ndarray corresponding to `A`. + * - a two-dimensional input ndarray corresponding to `B`. + * - a two-dimensional input/output ndarray corresponding to `C`. + * - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var matrix = require( '@stdlib/ndarray/matrix/ctor' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + * + * var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); + * var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' ); + * var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); + * + * var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int32' + * }); + * var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * var beta = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * + * var z = ns.ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + * // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + * + * var bool = ( z === C ); + * // returns true + */ + ggemm: typeof ggemm; + + /** + * Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a two-dimensional input ndarray corresponding to `A`. + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input/output ndarray corresponding to `y`. + * - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var matrix = require( '@stdlib/ndarray/matrix/ctor' ); + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + * + * var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); + * var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); + * var y = vector( [ 4.0, 5.0 ], 'generic' ); + * + * var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int8' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * var beta = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * + * var z = ns.ggemv( [ A, x, y, trans, alpha, beta ] ); + * // returns [ 18.0, 37.0 ] + * + * var bool = ( z === y ); + * // returns true + */ + ggemv: typeof ggemv; + + /** + * Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input ndarray corresponding to `y`. + * - a two-dimensional input/output ndarray corresponding to `A`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var matrix = require( '@stdlib/ndarray/matrix/ctor' ); + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = vector( [ 1.0, 2.0 ], 'generic' ); + * var y = vector( [ 3.0, 4.0, 5.0 ], 'generic' ); + * var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); + * + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * + * var z = ns.gger( [ x, y, A, alpha ] ); + * // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + * + * var bool = ( z === A ); + * // returns true + */ + gger: typeof gger; + /** * Computes the L2-norm of a one-dimensional ndarray. * @@ -659,6 +1098,45 @@ interface Namespace { */ gswap: typeof gswap; + /** + * Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a two-dimensional input ndarray corresponding to `A`. + * - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var matrix = require( '@stdlib/ndarray/matrix/ctor' ); + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + * + * var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); + * var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ], 'generic' ); + * + * var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 2.0, { + * 'dtype': 'generic' + * }); + * + * var y = ns.gsyr( [ x, A, uplo, alpha ] ); + * // returns [ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ] + * + * var bool = ( y === A ); + * // returns true + */ + gsyr: typeof gsyr; + /** * Finds the index of the first element having the maximum absolute value for all elements in a one-dimensional double-precision floating-point ndarray. * @@ -905,6 +1383,135 @@ interface Namespace { */ sdsdot: typeof sdsdot; + /** + * Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a two-dimensional input ndarray corresponding to `A`. + * - a two-dimensional input ndarray corresponding to `B`. + * - a two-dimensional input/output ndarray corresponding to `C`. + * - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + * + * var A = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); + * var B = new Float32Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); + * var C = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); + * + * var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int32' + * }); + * var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float32' + * }); + * var beta = scalar2ndarray( 1.0, { + * 'dtype': 'float32' + * }); + * + * var z = ns.sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + * // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + * + * var bool = ( z === C ); + * // returns true + */ + sgemm: typeof sgemm; + + /** + * Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a two-dimensional input ndarray corresponding to `A`. + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input/output ndarray corresponding to `y`. + * - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + * + * var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); + * var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); + * var y = new Float32Vector( [ 4.0, 5.0 ] ); + * + * var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + * 'dtype': 'int8' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float32' + * }); + * var beta = scalar2ndarray( 1.0, { + * 'dtype': 'float32' + * }); + * + * var z = ns.sgemv( [ A, x, y, trans, alpha, beta ] ); + * // returns [ 18.0, 37.0 ] + * + * var bool = ( z === y ); + * // returns true + */ + sgemv: typeof sgemv; + + /** + * Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input ndarray corresponding to `y`. + * - a two-dimensional input/output ndarray corresponding to `A`. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = new Float32Vector( [ 1.0, 2.0 ] ); + * var y = new Float32Vector( [ 3.0, 4.0, 5.0 ] ); + * var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); + * + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float32' + * }); + * + * var z = ns.sger( [ x, y, A, alpha ] ); + * // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + * + * var bool = ( z === A ); + * // returns true + */ + sger: typeof sger; + /** * Computes the L2-norm of a one-dimensional single-precision floating-point ndarray. * @@ -958,6 +1565,44 @@ interface Namespace { */ sscal: typeof sscal; + /** + * Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by `N` matrix supplied in packed form. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input/output ndarray corresponding to the packed form of `A`. + * - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + * + * var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); + * var AP = new Float32Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + * + * var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + * 'dtype': 'int8' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float32' + * }); + * + * var y = ns.sspr( [ x, AP, uplo, alpha ] ); + * // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] + * + * var bool = ( y === AP ); + * // returns true + */ + sspr: typeof sspr; + /** * Interchanges two one-dimensional single-precision floating-point ndarrays. * @@ -986,6 +1631,86 @@ interface Namespace { */ sswap: typeof sswap; + /** + * Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a two-dimensional input/output ndarray corresponding to `A`. + * - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + * + * var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); + * var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); + * + * var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 1.0, { + * 'dtype': 'float32' + * }); + * + * var y = ns.ssyr( [ x, A, uplo, alpha ] ); + * // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] + * + * var bool = ( y === A ); + * // returns true + */ + ssyr: typeof ssyr; + + /** + * Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray corresponding to `x`. + * - a one-dimensional input ndarray corresponding to `y`. + * - a two-dimensional input/output ndarray corresponding to `A`. + * - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + * - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); + * var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); + * var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] ); + * + * var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + * 'dtype': 'int32' + * }); + * var alpha = scalar2ndarray( 2.0, { + * 'dtype': 'float32' + * }); + * + * var z = ns.ssyr2( [ x, y, A, uplo, alpha ] ); + * // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] + * + * var bool = ( z === A ); + * // returns true + */ + ssyr2: typeof ssyr2; + /** * Multiplies a one-dimensional double-precision complex floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional double-precision complex floating-point ndarray `y`. * diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/README.md new file mode 100644 index 000000000000..7bd1fd11f61e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/README.md @@ -0,0 +1,131 @@ + + +# dspr + +> Perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dspr = require( '@stdlib/blas/base/ndarray/dspr' ); +``` + +#### dspr( arrays ) + +Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by `N` matrix supplied in packed form. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + +var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +var AP = new Float64Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); + +var y = dspr( [ x, AP, uplo, alpha ] ); +// returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] + +var bool = ( y === AP ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to the packed form of `A`. + - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dspr = require( '@stdlib/blas/base/ndarray/dspr' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var AP = discreteUniform( [ 10 ], 0, 10, opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 3.0, opts ); + +var out = dspr( [ x, AP, uplo, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/benchmark/benchmark.js new file mode 100644 index 000000000000..cf11dc1c66d6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/benchmark/benchmark.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dspr = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var uplo; + var AP; + var x; + + AP = uniform( [ ( len * ( len+1 ) ) / 2 ], -100.0, 100.0, options ); + x = uniform( [ len ], -100.0, 100.0, options ); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + alpha = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dspr( [ x, AP, uplo, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/repl.txt new file mode 100644 index 000000000000..ff6c68d0c614 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( arrays ) + Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` + is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by + `N` matrix supplied in packed form. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to the packed + form of `A`. + - a zero-dimensional ndarray specifying whether the upper or lower + triangular part of `A` is supplied. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf ); + + > var apbuf = [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ]; + > var AP = new {{alias:@stdlib/ndarray/vector/float64}}( apbuf ); + + > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' ); + > var opts = { 'dtype': 'float64' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > {{alias}}( [ x, AP, uplo, alpha ] ); + > AP + [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/types/index.d.ts new file mode 100644 index 000000000000..43dcc7e6e0b7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/types/index.d.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by `N` matrix supplied in packed form. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to the packed form of `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var AP = new Float64Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var y = dspr( [ x, AP, uplo, alpha ] ); +* // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] +* +* var bool = ( y === AP ); +* // returns true +*/ +declare function dspr( arrays: [ float64ndarray, float64ndarray, ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dspr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/types/test.ts new file mode 100644 index 000000000000..11cd1cc60142 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dspr = require( '@stdlib/blas/base/ndarray/dspr' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const AP = zeros( [ 6 ], { + 'dtype': 'float64' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const uplo = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dspr( [ x, AP, uplo, alpha ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dspr( '10' ); // $ExpectError + dspr( 10 ); // $ExpectError + dspr( true ); // $ExpectError + dspr( false ); // $ExpectError + dspr( null ); // $ExpectError + dspr( undefined ); // $ExpectError + dspr( [] ); // $ExpectError + dspr( {} ); // $ExpectError + dspr( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const AP = zeros( [ 6 ], { + 'dtype': 'float64' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const uplo = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dspr(); // $ExpectError + dspr( [ x, AP, uplo, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/examples/index.js new file mode 100644 index 000000000000..4d93060ff283 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dspr = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var AP = discreteUniform( [ 10 ], 0, 10, opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 3.0, opts ); + +var out = dspr( [ x, AP, uplo, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/lib/index.js new file mode 100644 index 000000000000..f052098c57a0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/lib/index.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form. +* +* @module @stdlib/blas/base/ndarray/dspr +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var dspr = require( '@stdlib/blas/base/ndarray/dspr' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var AP = new Float64Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var out = dspr( [ x, AP, uplo, alpha ] ); +* // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] +* +* var bool = ( out === AP ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/lib/main.js new file mode 100644 index 000000000000..7ef79ea5e370 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/lib/main.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getOrder = require( '@stdlib/ndarray/base/order' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/dspr' ).ndarray; + + +// MAIN // + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix supplied in packed form. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to the packed form of `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var AP = new Float64Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var y = dspr( [ x, AP, uplo, alpha ] ); +* // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] +* +* var bool = ( y === AP ); +* // returns true +*/ +function dspr( arrays ) { + var alpha; + var uplo; + var AP; + var x; + + x = arrays[ 0 ]; + AP = arrays[ 1 ]; + + uplo = ndarraylike2scalar( arrays[ 2 ] ); + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + strided( getOrder( AP ), uplo, numelDimension( x, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( AP ), getStride( AP, 0 ), getOffset( AP ) ); // eslint-disable-line max-len + + return AP; +} + + +// EXPORTS // + +module.exports = dspr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/package.json new file mode 100644 index 000000000000..1e1813b73bde --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/dspr", + "version": "0.0.0", + "description": "Perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "dspr", + "linear", + "algebra", + "subroutines", + "rank 1", + "symmetric", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float64", + "double", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dspr/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/test/test.js new file mode 100644 index 000000000000..e997ac910c4f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dspr/test/test.js @@ -0,0 +1,304 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dspr = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dspr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dspr.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (upper)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = dspr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array( [ 1.0, 1.0, 1.0 ] ); + Abuf = new Float64Array( [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = dspr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 3.0, 6.0, 4.0, 7.0, 5.0, 8.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (lower)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 1.0, 3.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'lower' ), { + 'dtype': 'int8' + }); + + v = dspr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 2.0, 4.0, 5.0, 6.0, 8.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = dspr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + + xbuf = new Float64Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = dspr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 3.0, 6.0, 9.0, 9.0, 14.0, 19.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + + xbuf = new Float64Array([ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + x = vector( xbuf, 3, -2, 4 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = dspr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 3.0, 6.0, 9.0, 9.0, 14.0, 19.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + Abuf = new Float64Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 1.0, + 2.0, + 1.0 + ]); + A = vector( Abuf, 6, 1, 2 ); + + xbuf = new Float64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + x = vector( xbuf, 3, 1, 2 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = dspr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array([ + 0.0, + 0.0, + 3.0, + 6.0, + 9.0, + 9.0, + 14.0, + 19.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md new file mode 100644 index 000000000000..34cb95ec0932 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/README.md @@ -0,0 +1,135 @@ + + +# dsyr + +> Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' ); +``` + +#### dsyr( arrays ) + +Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. + + + +```javascript +var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + +var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); + +var y = dsyr( [ x, A, uplo, alpha ] ); +// returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] + +var bool = ( y === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = dsyr( [ x, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js new file mode 100644 index 000000000000..79c8c9f81115 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dsyr = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var uplo; + var x; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + A = zeros( [ len, len ], options ); + + alpha = scalar2ndarray( 1.0, options ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dsyr( [ x, A, uplo, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt new file mode 100644 index 000000000000..ed77b51c220a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( arrays ) + Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where + `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an + `N` by `N` symmetric matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower + triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float64}}( abuf ); + + > var opts = { 'dtype': 'float64' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' ); + + > {{alias}}( [ x, A, uplo, alpha ] ); + > A + [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts new file mode 100644 index 000000000000..6c1963d7f28f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/index.d.ts @@ -0,0 +1,67 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var y = dsyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ +declare function dsyr( arrays: [ float64ndarray, float64ndarray, ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dsyr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts new file mode 100644 index 000000000000..fa82d2f21faf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dsyr = require( '@stdlib/blas/base/ndarray/dsyr' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float64' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dsyr( [ x, A, uplo, alpha ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dsyr( '10' ); // $ExpectError + dsyr( 10 ); // $ExpectError + dsyr( true ); // $ExpectError + dsyr( false ); // $ExpectError + dsyr( null ); // $ExpectError + dsyr( undefined ); // $ExpectError + dsyr( [] ); // $ExpectError + dsyr( {} ); // $ExpectError + dsyr( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float64' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dsyr(); // $ExpectError + dsyr( [ x, A, uplo, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js new file mode 100644 index 000000000000..fb1650c40335 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dsyr = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = dsyr( [ x, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js new file mode 100644 index 000000000000..fe6babf3b9bb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. +* +* @module @stdlib/blas/base/ndarray/dsyr +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var dsyr = require( '@stdlib/blas/base/ndarray/dsyr' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var y = dsyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js new file mode 100644 index 000000000000..fa15e4c069af --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/lib/main.js @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/dsyr' ).ndarray; + + +// MAIN // + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var y = dsyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ +function dsyr( arrays ) { + var alpha; + var uplo; + var st; + var x; + var A; + + x = arrays[ 0 ]; + A = arrays[ 1 ]; + + uplo = ndarraylike2scalar( arrays[ 2 ] ); + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + st = getStrides( A, false ); + + strided( uplo, numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) ); + + return A; +} + + +// EXPORTS // + +module.exports = dsyr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/package.json new file mode 100644 index 000000000000..14159875174b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/dsyr", + "version": "0.0.0", + "description": "Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "dsyr", + "linear", + "algebra", + "subroutines", + "symmetric", + "rank-1", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float64", + "double", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js new file mode 100644 index 000000000000..ab2f8e073cef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr/test/test.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dsyr = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} N - number of rows and columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, N, stride0, stride1, offset ) { + return new ndarray( 'float64', buffer, [ N, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dsyr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dsyr.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (upper)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = dsyr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 2.0, 4.0, 6.0, 2.0, 5.0, 8.0, 3.0, 2.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array( [ 1.0, 1.0, 1.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 1, 3, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = dsyr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 2.0, 2.0, 3.0, 3.0, 2.0, 2.0, 4.0, 3.0, 2.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (lower)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'lower' ), { + 'dtype': 'int32' + }); + + v = dsyr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 2.0, 2.0, 3.0, 4.0, 5.0, 2.0, 6.0, 8.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = dsyr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + Abuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = dsyr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 4.0, 6.0, 0.0, 0.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array([ + 3.0, // 2 + 2.0, // 1 + 1.0 // 0 + ]); + x = vector( xbuf, 3, -1, 2 ); + + Abuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = dsyr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array( [ 1.0, 2.0, 3.0, 0.0, 4.0, 6.0, 0.0, 0.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float64Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 1 ); + + Abuf = new Float64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0 + ]); + A = matrix( Abuf, 3, 3, 1, 2 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = dsyr( [ x, A, uplo, alpha ] ); + + expected = new Float64Array([ + 1.0, + 2.0, + 5.0, + 8.0, + 11.0, + 6.0, + 15.0, + 20.0, + 9.0, + 10.0, + 29.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/README.md new file mode 100644 index 000000000000..9dcb14747a7e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/README.md @@ -0,0 +1,138 @@ + + +# dsyr2 + +> Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dsyr2 = require( '@stdlib/blas/base/ndarray/dsyr2' ); +``` + +#### dsyr2( arrays ) + +Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. + + + +```javascript +var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +var y = new Float64Vector( [ 2.0, 1.0, 3.0 ] ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' +}); + +var z = dsyr2( [ x, y, A, uplo, alpha ] ); +// returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] + +var bool = ( z === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dsyr2 = require( '@stdlib/blas/base/ndarray/dsyr2' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = dsyr2( [ x, y, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/benchmark/benchmark.js new file mode 100644 index 000000000000..270b1fa54b6e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/benchmark/benchmark.js @@ -0,0 +1,120 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dsyr2 = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var uplo; + var x; + var y; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + A = zeros( [ len, len ], options ); + + alpha = scalar2ndarray( 1.0, options ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dsyr2( [ x, y, A, uplo, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/repl.txt new file mode 100644 index 000000000000..24011fe0013e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/repl.txt @@ -0,0 +1,47 @@ + +{{alias}}( arrays ) + Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, + where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and + `A` is an `N` by `N` symmetric matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower + triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf ); + + > var ybuf = [ 2.0, 1.0, 3.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float64}}( ybuf ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float64}}( abuf ); + + > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' ); + + > var opts = { 'dtype': 'float64' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, opts ); + + > {{alias}}( [ x, y, A, uplo, alpha ] ); + > A + [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/types/index.d.ts new file mode 100644 index 000000000000..6c41fec03889 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/types/index.d.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float64Vector( [ 2.0, 1.0, 3.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'float64' +* }); +* +* var z = dsyr2( [ x, y, A, uplo, alpha ] ); +* // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +declare function dsyr2( arrays: [ float64ndarray, float64ndarray, float64ndarray, ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dsyr2; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/types/test.ts new file mode 100644 index 000000000000..f599943dac15 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/docs/types/test.ts @@ -0,0 +1,81 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dsyr2 = require( '@stdlib/blas/base/ndarray/dsyr2' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float64' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dsyr2( [ x, y, A, uplo, alpha ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dsyr2( '10' ); // $ExpectError + dsyr2( 10 ); // $ExpectError + dsyr2( true ); // $ExpectError + dsyr2( false ); // $ExpectError + dsyr2( null ); // $ExpectError + dsyr2( undefined ); // $ExpectError + dsyr2( [] ); // $ExpectError + dsyr2( {} ); // $ExpectError + dsyr2( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float64' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float64' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float64' + }); + + dsyr2(); // $ExpectError + dsyr2( [ x, y, A, uplo, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/examples/index.js new file mode 100644 index 000000000000..1ef1d6b6a947 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dsyr2 = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = dsyr2( [ x, y, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/lib/index.js new file mode 100644 index 000000000000..5eb97fd400be --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/lib/index.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`. +* +* @module @stdlib/blas/base/ndarray/dsyr2 +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dsyr2 = require( '@stdlib/blas/base/ndarray/dsyr2' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float64Vector( [ 2.0, 1.0, 3.0 ] ); +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'float64' +* }); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var out = dsyr2( [ x, y, A, uplo, alpha ] ); +* // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] +* +* var bool = ( out === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/lib/main.js new file mode 100644 index 000000000000..67c36d3d9fe9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/lib/main.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/dsyr2' ).ndarray; + + +// MAIN // + +/** +* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float64Matrix = require( '@stdlib/ndarray/matrix/float64' ); +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var A = new Float64Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* var x = new Float64Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float64Vector( [ 2.0, 1.0, 3.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'float64' +* }); +* +* var z = dsyr2( [ x, y, A, uplo, alpha ] ); +* // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +function dsyr2( arrays ) { + var alpha; + var uplo; + var st; + var A; + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + A = arrays[ 2 ]; + + uplo = ndarraylike2scalar( arrays[ 3 ] ); + alpha = ndarraylike2scalar( arrays[ 4 ] ); + + st = getStrides( A, false ); + + strided( uplo, numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) ); // eslint-disable-line max-len + + return A; +} + + +// EXPORTS // + +module.exports = dsyr2; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/package.json new file mode 100644 index 000000000000..60a1123518dd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/dsyr2", + "version": "0.0.0", + "description": "Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "dsyr2", + "linear", + "algebra", + "subroutines", + "symmetric", + "rank-2", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float64", + "double", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/test/test.js new file mode 100644 index 000000000000..562760f0d430 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dsyr2/test/test.js @@ -0,0 +1,360 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dsyr2 = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} N - number of rows and columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, N, stride0, stride1, offset ) { + return new ndarray( 'float64', buffer, [ N, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dsyr2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dsyr2.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A` (upper)', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + ybuf = new Float64Array( [ 2.0, 1.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = dsyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float64Array( [ 9.0, 12.0, 21.0, 2.0, 9.0, 20.0, 3.0, 2.0, 37.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array( [ 1.0, 1.0, 1.0 ] ); + ybuf = new Float64Array( [ 1.0, 1.0, 1.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 1, 3, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = dsyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float64Array( [ 5.0, 2.0, 3.0, 6.0, 5.0, 2.0, 7.0, 6.0, 5.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A` (lower)', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + ybuf = new Float64Array( [ 2.0, 1.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'lower' ), { + 'dtype': 'int32' + }); + v = dsyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float64Array( [ 9.0, 2.0, 3.0, 12.0, 9.0, 2.0, 21.0, 20.0, 37.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + ybuf = new Float64Array( [ 2.0, 1.0, 3.0 ] ); + Abuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = dsyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + ybuf = new Float64Array([ + 2.0, // 0 + 0.0, + 1.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 0 ); + + Abuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = dsyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float64Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 3.0, // 2 + 2.0, // 1 + 1.0 // 0 + ]); + x = vector( xbuf, 3, -1, 2 ); + + ybuf = new Float64Array([ + 3.0, // 2 + 1.0, // 1 + 2.0 // 0 + ]); + y = vector( ybuf, 3, -1, 2 ); + + Abuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = dsyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float64Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float64Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 1 ); + + ybuf = new Float64Array([ + 0.0, + 2.0, // 0 + 0.0, + 1.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 1 ); + + Abuf = new Float64Array([ + 999.0, + 999.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + A = matrix( Abuf, 3, 3, 1, 2 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = dsyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float64Array([ + 999.0, + 999.0, + 8.0, + 10.0, + 18.0, + 0.0, + 8.0, + 18.0, + 0.0, + 0.0, + 36.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat64Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dzasum/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dzasum/README.md index 728cec93cf3b..b47552cf2e7b 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/dzasum/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dzasum/README.md @@ -33,7 +33,7 @@ The [_L1_ norm][l1norm] is defined as ``` @@ -66,9 +66,7 @@ var y = dzasum( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/dznrm2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/dznrm2/README.md index d0f06536c7bb..6f771a690234 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/dznrm2/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/dznrm2/README.md @@ -33,7 +33,7 @@ The [L2-norm][l2-norm] is defined as ``` @@ -66,9 +66,7 @@ var y = dznrm2( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/README.md new file mode 100644 index 000000000000..12bee725d562 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/README.md @@ -0,0 +1,146 @@ + + +# ggemm + +> Perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var ggemm = require( '@stdlib/blas/base/ndarray/ggemm' ); +``` + +#### ggemm( arrays ) + +Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + +```javascript +var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + +var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); +var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' ); +var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); +var beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); +// returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + +var bool = ( out === C ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a two-dimensional input ndarray corresponding to `B`. + - a two-dimensional input/output ndarray corresponding to `C`. + - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ggemm = require( '@stdlib/blas/base/ndarray/ggemm' ); + +var opts = { + 'dtype': 'generic' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var B = discreteUniform( [ 4, 2 ], 0, 10, opts ); +var C = discreteUniform( [ 3, 2 ], 0, 10, opts ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/benchmark/benchmark.js new file mode 100644 index 000000000000..ec88e8053ef5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/benchmark/benchmark.js @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var ggemm = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var transA; + var transB; + var alpha; + var beta; + var A; + var B; + var C; + + A = uniform( [ len, len ], -100.0, 100.0, options ); + B = uniform( [ len, len ], -100.0, 100.0, options ); + C = uniform( [ len, len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + beta = scalar2ndarray( 1.0, options ); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( i%len, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/repl.txt new file mode 100644 index 000000000000..6a4676450cf1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, + where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` + are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` + matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a two-dimensional input ndarray corresponding to `B`. + - a two-dimensional input/output ndarray corresponding to `C`. + - a zero-dimensional ndarray specifying whether `A` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray specifying whether `B` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `beta`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var abuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]; + > var A = {{alias:@stdlib/ndarray/matrix/ctor}}( abuf, 'generic' ); + + > var bbuf = [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ]; + > var B = {{alias:@stdlib/ndarray/matrix/ctor}}( bbuf, 'generic' ); + + > var cbuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]; + > var C = {{alias:@stdlib/ndarray/matrix/ctor}}( cbuf, 'generic' ); + + > var opts = { 'dtype': 'generic' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > var beta = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var transA = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + > var transB = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + + > {{alias}}( [ A, B, C, transA, transB, alpha, beta ] ); + > C + [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/index.d.ts new file mode 100644 index 000000000000..7c2196b143b1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/index.d.ts @@ -0,0 +1,76 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a two-dimensional input ndarray corresponding to `B`. +* - a two-dimensional input/output ndarray corresponding to `C`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); +* var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' ); +* var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var z = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( z === C ); +* // returns true +*/ +declare function ggemm = typedndarray>( arrays: [ typedndarray, typedndarray, T, ndarray, ndarray, typedndarray, typedndarray ] ): T; + + +// EXPORTS // + +export = ggemm; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/test.ts new file mode 100644 index 000000000000..0a8d67c099e1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/docs/types/test.ts @@ -0,0 +1,93 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import ggemm = require( '@stdlib/blas/base/ndarray/ggemm' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const A = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + const B = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + const C = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + const transA = zeros( [], { + 'dtype': 'int32' + }); + const transB = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + const beta = zeros( [], { + 'dtype': 'generic' + }); + + ggemm( [ A, B, C, transA, transB, alpha, beta ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + ggemm( '10' ); // $ExpectError + ggemm( 10 ); // $ExpectError + ggemm( true ); // $ExpectError + ggemm( false ); // $ExpectError + ggemm( null ); // $ExpectError + ggemm( undefined ); // $ExpectError + ggemm( [] ); // $ExpectError + ggemm( {} ); // $ExpectError + ggemm( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + const B = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + const C = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + const transA = zeros( [], { + 'dtype': 'int32' + }); + const transB = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + const beta = zeros( [], { + 'dtype': 'generic' + }); + + ggemm(); // $ExpectError + ggemm( [ A, B, C, transA, transB, alpha, beta ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/examples/index.js new file mode 100644 index 000000000000..b06c5a45bf25 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ggemm = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var B = discreteUniform( [ 4, 2 ], 0, 10, opts ); +var C = discreteUniform( [ 3, 2 ], 0, 10, opts ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/index.js new file mode 100644 index 000000000000..147e8a4c4293 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 3 routine to perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. +* +* @module @stdlib/blas/base/ndarray/ggemm +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* var ggemm = require( '@stdlib/blas/base/ndarray/ggemm' ); +* +* var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); +* var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' ); +* var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( out === C ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/main.js new file mode 100644 index 000000000000..bf2c490a9afa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/lib/main.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var strided = require( '@stdlib/blas/base/ggemm' ).ndarray; + + +// VARIABLES // + +var NO_TRANSPOSE = resolveEnum( 'no-transpose' ); + + +// MAIN // + +/** +* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a two-dimensional input ndarray corresponding to `B`. +* - a two-dimensional input/output ndarray corresponding to `C`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); +* var B = matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ], 'generic' ); +* var C = matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], 'generic' ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var z = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( z === C ); +* // returns true +*/ +function ggemm( arrays ) { + var transA; + var transB; + var alpha; + var beta; + var shA; + var shC; + var stA; + var stB; + var stC; + var A; + var B; + var C; + var M; + var N; + var K; + + A = arrays[ 0 ]; + B = arrays[ 1 ]; + C = arrays[ 2 ]; + + transA = ndarraylike2scalar( arrays[ 3 ] ); + transB = ndarraylike2scalar( arrays[ 4 ] ); + alpha = ndarraylike2scalar( arrays[ 5 ] ); + beta = ndarraylike2scalar( arrays[ 6 ] ); + + shA = getShape( A, false ); + shC = getShape( C, false ); + + stA = getStrides( A, false ); + stB = getStrides( B, false ); + stC = getStrides( C, false ); + + M = shC[ 0 ]; + N = shC[ 1 ]; + if ( resolveEnum( transA ) === NO_TRANSPOSE ) { + K = shA[ 1 ]; + } else { + K = shA[ 0 ]; + } + + strided( transA, transB, M, N, K, alpha, getData( A ), stA[ 0 ], stA[ 1 ], getOffset( A ), getData( B ), stB[ 0 ], stB[ 1 ], getOffset( B ), beta, getData( C ), stC[ 0 ], stC[ 1 ], getOffset( C ) ); // eslint-disable-line max-len + + return C; +} + + +// EXPORTS // + +module.exports = ggemm; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/package.json new file mode 100644 index 000000000000..c39a1b760c88 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/base/ndarray/ggemm", + "version": "0.0.0", + "description": "Perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 3", + "ggemm", + "linear", + "algebra", + "subroutines", + "matrix-matrix", + "multiply", + "matrix", + "array", + "ndarray", + "typedndarray", + "generic", + "number" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/test/test.js new file mode 100644 index 000000000000..a4d10605616b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemm/test/test.js @@ -0,0 +1,440 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var ggemm = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'generic', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ggemm, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( ggemm.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (no-transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Bbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 1.0, 1.0, 1.0, 1.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 23.0, 29.0, 50.0, 65.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Bbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 1.0, 1.0, 1.0, 1.0 ]; + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 36.0, 45.0, 45.0, 57.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (no-transpose, transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Bbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 1.0, 1.0, 1.0, 1.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 2, 3, 3, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 15.0, 33.0, 33.0, 78.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (conjugate-transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Bbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 1.0, 1.0, 1.0, 1.0 ]; + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'conjugate-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 36.0, 45.0, 45.0, 57.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function correctly applies both `alpha` and `beta` scalars', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Bbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 1.0, 2.0, 3.0, 4.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 3.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 47.0, 62.0, 107.0, 140.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `beta*C`', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Bbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 1.0, 2.0, 3.0, 4.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 2.0, 4.0, 6.0, 8.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports column-major ndarrays', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ]; + Bbuf = [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ]; + Cbuf = [ 1.0, 1.0, 1.0, 1.0 ]; + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + B = matrix( Bbuf, 3, 2, 1, 3, 0 ); + C = matrix( Cbuf, 2, 2, 1, 2, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 23.0, 50.0, 29.0, 65.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 4.0, 5.0, 6.0, 1.0, 2.0, 3.0 ]; + Bbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 1.0, 1.0, 1.0, 1.0 ]; + A = matrix( Abuf, 2, 3, -3, 1, 3 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 23.0, 29.0, 50.0, 65.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Bbuf = [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + Cbuf = [ 0.0, 1.0, 1.0, 1.0, 1.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + B = matrix( Bbuf, 3, 2, 2, 1, 2 ); + C = matrix( Cbuf, 2, 2, 2, 1, 1 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = ggemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = [ 0.0, 23.0, 29.0, 50.0, 65.0 ]; + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/README.md new file mode 100644 index 000000000000..f20d25b61d58 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/README.md @@ -0,0 +1,140 @@ + + +# ggemv + +> Perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var ggemv = require( '@stdlib/blas/base/ndarray/ggemv' ); +``` + +#### ggemv( arrays ) + +Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + +```javascript +var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + +var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); +var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +var y = vector( [ 4.0, 5.0 ], 'generic' ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); +var beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +var out = ggemv( [ A, x, y, trans, alpha, beta ] ); +// returns [ 18.0, 37.0 ] + +var bool = ( out === y ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ggemv = require( '@stdlib/blas/base/ndarray/ggemv' ); + +var opts = { + 'dtype': 'generic' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = ggemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/benchmark/benchmark.js new file mode 100644 index 000000000000..1e25a8cf12b4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/benchmark/benchmark.js @@ -0,0 +1,121 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var ggemv = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var trans; + var alpha; + var beta; + var A; + var x; + var y; + + A = uniform( [ len, len ], -100.0, 100.0, options ); + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + beta = scalar2ndarray( 1.0, options ); + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = ggemv( [ A, x, y, trans, alpha, beta ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/repl.txt new file mode 100644 index 000000000000..dedc96905fdf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/repl.txt @@ -0,0 +1,50 @@ + +{{alias}}( arrays ) + Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or + `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and + `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `beta`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + > var A = {{alias:@stdlib/ndarray/matrix/ctor}}( abuf, 'generic' ); + + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( xbuf, 'generic' ); + + > var ybuf = [ 4.0, 5.0 ]; + > var y = {{alias:@stdlib/ndarray/vector/ctor}}( ybuf, 'generic' ); + + > var opts = { 'dtype': 'generic' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > var beta = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var trans = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + + > {{alias}}( [ A, x, y, trans, alpha, beta ] ); + > y + [ 18.0, 37.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/types/index.d.ts new file mode 100644 index 000000000000..e36816121d84 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/types/index.d.ts @@ -0,0 +1,73 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); +* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +* var y = vector( [ 4.0, 5.0 ], 'generic' ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var z = ggemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +declare function ggemv = typedndarray>( arrays: [ typedndarray, typedndarray, T, ndarray, typedndarray, typedndarray ] ): T; + + +// EXPORTS // + +export = ggemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/types/test.ts new file mode 100644 index 000000000000..d9ef68af4f94 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/docs/types/test.ts @@ -0,0 +1,87 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import ggemv = require( '@stdlib/blas/base/ndarray/ggemv' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'generic' + }); + const x = zeros( [ 3 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 2 ], { + 'dtype': 'generic' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + const beta = zeros( [], { + 'dtype': 'generic' + }); + + ggemv( [ A, x, y, trans, alpha, beta ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + ggemv( '10' ); // $ExpectError + ggemv( 10 ); // $ExpectError + ggemv( true ); // $ExpectError + ggemv( false ); // $ExpectError + ggemv( null ); // $ExpectError + ggemv( undefined ); // $ExpectError + ggemv( [] ); // $ExpectError + ggemv( {} ); // $ExpectError + ggemv( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'generic' + }); + const x = zeros( [ 3 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 2 ], { + 'dtype': 'generic' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + const beta = zeros( [], { + 'dtype': 'generic' + }); + + ggemv(); // $ExpectError + ggemv( [ A, x, y, trans, alpha, beta ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/examples/index.js new file mode 100644 index 000000000000..00741b085c15 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ggemv = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = ggemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/lib/index.js new file mode 100644 index 000000000000..0d9cb255269f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/lib/index.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. +* +* @module @stdlib/blas/base/ndarray/ggemv +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* var ggemv = require( '@stdlib/blas/base/ndarray/ggemv' ); +* +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); +* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +* var y = vector( [ 4.0, 5.0 ], 'generic' ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var out = ggemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( out === y ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/lib/main.js new file mode 100644 index 000000000000..7ecd6466efa7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/lib/main.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/ggemv' ).ndarray; + + +// MAIN // + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); +* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +* var y = vector( [ 4.0, 5.0 ], 'generic' ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var z = ggemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +function ggemv( arrays ) { + var trans; + var alpha; + var beta; + var sh; + var st; + var A; + var x; + var y; + + A = arrays[ 0 ]; + x = arrays[ 1 ]; + y = arrays[ 2 ]; + + trans = ndarraylike2scalar( arrays[ 3 ] ); + alpha = ndarraylike2scalar( arrays[ 4 ] ); + beta = ndarraylike2scalar( arrays[ 5 ] ); + + sh = getShape( A, false ); + st = getStrides( A, false ); + + strided( trans, sh[ 0 ], sh[ 1 ], alpha, getData( A ), st[ 0 ], st[ 1 ], getOffset( A ), getData( x ), getStride( x, 0 ), getOffset( x ), beta, getData( y ), getStride( y, 0 ), getOffset( y ) ); + + return y; +} + + +// EXPORTS // + +module.exports = ggemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/package.json new file mode 100644 index 000000000000..28c61878e34d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/ggemv", + "version": "0.0.0", + "description": "Perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "ggemv", + "linear", + "algebra", + "subroutines", + "matrix-vector", + "multiply", + "vector", + "matrix", + "array", + "ndarray", + "typedndarray", + "generic", + "number" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/test/test.js new file mode 100644 index 000000000000..c83d432671ba --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ggemv/test/test.js @@ -0,0 +1,411 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var ggemv = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'generic', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ggemv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( ggemv.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ + 1.0, // 0 + 2.0 // 1 + ]; + ybuf = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = ggemv( [ A, x, y, trans, alpha, beta ] ); + + expected = [ 6.0, 13.0, 20.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + ybuf = [ + 1.0, // 0 + 2.0 // 1 + ]; + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = ggemv( [ A, x, y, trans, alpha, beta ] ); + + expected = [ 46.0, 60.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A^T*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ + 1.0, // 0 + 2.0 // 1 + ]; + ybuf = [ + 1.0, // 0 + 2.0 // 1 + ]; + Abuf = [ 1.0, 2.0, 3.0, 4.0 ]; + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = ggemv( [ A, x, y, trans, alpha, beta ] ); + + expected = [ 8.0, 12.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ + 1.0, // 0 + 2.0 // 1 + ]; + ybuf = [ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = ggemv( [ A, x, y, trans, alpha, beta ] ); + + expected = [ 2.0, 4.0, 6.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides (transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = [ + 1.0, // 0 + 0.0, + 2.0 // 1 + ]; + x = vector( xbuf, 2, 2, 0 ); + + ybuf = [ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]; + y = vector( ybuf, 3, 2, 0 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = ggemv( [ A, x, y, trans, alpha, beta ] ); + + expected = [ 20.0, 0.0, 28.0, 0.0, 36.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides (transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = [ + 2.0, // 1 + 0.0, + 1.0 // 0 + ]; + x = vector( xbuf, 2, -2, 2 ); + + ybuf = [ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]; + y = vector( ybuf, 3, -2, 4 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = ggemv( [ A, x, y, trans, alpha, beta ] ); + + expected = [ 36.0, 0.0, 28.0, 0.0, 20.0 ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = [ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]; + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + + xbuf = [ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + x = vector( xbuf, 3, 1, 2 ); + + ybuf = [ + 0.0, + 1.0, // 0 + 0.0, + 2.0 // 1 + ]; + y = vector( ybuf, 2, 2, 1 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = ggemv( [ A, x, y, trans, alpha, beta ] ); + + expected = [ + 0.0, + 30.0, + 0.0, + 68.0 + ]; + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/gger/README.md new file mode 100644 index 000000000000..955e293dd7d9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/README.md @@ -0,0 +1,126 @@ + + +# gger + +> Perform the rank 1 operation `A = alpha*x*y^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gger = require( '@stdlib/blas/base/ndarray/gger' ); +``` + +#### gger( arrays ) + +Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + +```javascript +var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = vector( [ 1.0, 2.0 ], 'generic' ); +var y = vector( [ 3.0, 4.0, 5.0 ], 'generic' ); +var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); + +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +var z = gger( [ x, y, A, alpha ] ); +// returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + +var bool = ( z === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gger = require( '@stdlib/blas/base/ndarray/gger' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 4 ], 0, 10, opts ); +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); + +var alpha = scalar2ndarray( 1.0, opts ); + +var out = gger( [ x, y, A, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/gger/benchmark/benchmark.js new file mode 100644 index 000000000000..f56468df742f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gger = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var x; + var y; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + A = uniform( [ len, len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = gger( [ x, y, A, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/repl.txt new file mode 100644 index 000000000000..155efd1e1618 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( arrays ) + Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a + scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by + `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0 ]; + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( xbuf, 'generic' ); + + > var ybuf = [ 3.0, 4.0, 5.0 ]; + > var y = {{alias:@stdlib/ndarray/vector/ctor}}( ybuf, 'generic' ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + > var A = {{alias:@stdlib/ndarray/matrix/ctor}}( abuf, 'generic' ); + + > var opts = { 'dtype': 'generic' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > {{alias}}( [ x, y, A, alpha ] ); + > A + [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/types/index.d.ts new file mode 100644 index 000000000000..65f430b07c60 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/types/index.d.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = vector( [ 1.0, 2.0 ], 'generic' ); +* var y = vector( [ 3.0, 4.0, 5.0 ], 'generic' ); +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var z = gger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +declare function gger = typedndarray>( arrays: [ typedndarray, typedndarray, T, typedndarray ] ): T; + + +// EXPORTS // + +export = gger; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/types/test.ts new file mode 100644 index 000000000000..5826cb55fc4e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import gger = require( '@stdlib/blas/base/ndarray/gger' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 2 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 3 ], { + 'dtype': 'generic' + }); + const A = zeros( [ 2, 3 ], { + 'dtype': 'generic' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + + gger( [ x, y, A, alpha ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gger( '10' ); // $ExpectError + gger( 10 ); // $ExpectError + gger( true ); // $ExpectError + gger( false ); // $ExpectError + gger( null ); // $ExpectError + gger( undefined ); // $ExpectError + gger( [] ); // $ExpectError + gger( {} ); // $ExpectError + gger( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 3 ], { + 'dtype': 'generic' + }); + const A = zeros( [ 2, 3 ], { + 'dtype': 'generic' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + + gger(); // $ExpectError + gger( [ x, y, A, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gger/examples/index.js new file mode 100644 index 000000000000..cc6fe1b67407 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gger = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 4 ], 0, 10, opts ); +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); + +var alpha = scalar2ndarray( 1.0, opts ); + +var out = gger( [ x, y, A, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gger/lib/index.js new file mode 100644 index 000000000000..5b04df03f3fb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the rank 1 operation `A = alpha*x*y^T + A`. +* +* @module @stdlib/blas/base/ndarray/gger +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var gger = require( '@stdlib/blas/base/ndarray/gger' ); +* +* var x = vector( [ 1.0, 2.0 ], 'generic' ); +* var y = vector( [ 3.0, 4.0, 5.0 ], 'generic' ); +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var z = gger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/gger/lib/main.js new file mode 100644 index 000000000000..cbccc29e93ab --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/lib/main.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/gger' ).ndarray; + + +// MAIN // + +/** +* Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = vector( [ 1.0, 2.0 ], 'generic' ); +* var y = vector( [ 3.0, 4.0, 5.0 ], 'generic' ); +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ], 'generic' ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var z = gger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +function gger( arrays ) { + var alpha; + var sh; + var st; + var A; + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + A = arrays[ 2 ]; + + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + sh = getShape( A, false ); + st = getStrides( A, false ); + + strided( sh[ 0 ], sh[ 1 ], alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) ); + + return A; +} + + +// EXPORTS // + +module.exports = gger; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/gger/package.json new file mode 100644 index 000000000000..ece70b9afb36 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/blas/base/ndarray/gger", + "version": "0.0.0", + "description": "Perform the rank 1 operation `A = alpha*x*y^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "ger", + "linear", + "algebra", + "subroutines", + "rank-1", + "update", + "vector", + "matrix", + "array", + "ndarray" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gger/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/gger/test/test.js new file mode 100644 index 000000000000..3c5214d6675f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gger/test/test.js @@ -0,0 +1,323 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var gger = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'generic', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gger, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( gger.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the rank 1 operation `A = alpha*x*y^T + A`', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ 1.0, 2.0 ]; + ybuf = [ 1.0, 2.0, 3.0 ]; + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gger( [ x, y, A, alpha ] ); + + expected = [ 3.0, 6.0, 9.0, 8.0, 13.0, 18.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = [ 1.0, 1.0 ]; + ybuf = [ 1.0, 1.0, 1.0 ]; + Abuf = [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ]; + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gger( [ x, y, A, alpha ] ); + + expected = [ 3.0, 6.0, 4.0, 7.0, 5.0, 8.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided empty ndarrays, the function returns the output ndarray unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = []; + ybuf = []; + Abuf = []; + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + A = matrix( Abuf, 0, 0, 0, 0, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gger( [ x, y, A, alpha ] ); + + expected = []; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ 1.0, 2.0 ]; + ybuf = [ 3.0, 4.0, 5.0 ]; + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + + v = gger( [ x, y, A, alpha ] ); + + expected = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ + 1.0, // 0 + 0.0, + 2.0 // 1 + ]; + x = vector( xbuf, 2, 2, 0 ); + + ybuf = [ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]; + y = vector( ybuf, 3, 2, 0 ); + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gger( [ x, y, A, alpha ] ); + + expected = [ 3.0, 6.0, 9.0, 8.0, 13.0, 18.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ + 2.0, // 1 + 0.0, + 1.0 // 0 + ]; + x = vector( xbuf, 2, -2, 2 ); + + ybuf = [ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]; + y = vector( ybuf, 3, -2, 4 ); + + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gger( [ x, y, A, alpha ] ); + + expected = [ 3.0, 6.0, 9.0, 8.0, 13.0, 18.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = [ + 0.0, + 1.0, // 0 + 0.0, + 2.0 // 1 + ]; + x = vector( xbuf, 2, 2, 1 ); + + ybuf = [ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]; + y = vector( ybuf, 3, 1, 2 ); + + Abuf = [ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]; + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + v = gger( [ x, y, A, alpha ] ); + + expected = [ + 0.0, + 0.0, + 2.0, + 4.0, + 6.0, + 6.0, + 9.0, + 12.0 + ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gnrm2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/gnrm2/README.md index a95e2b6cd557..4830668a44c1 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/gnrm2/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gnrm2/README.md @@ -33,7 +33,7 @@ The [L2-norm][l2-norm] is defined as ``` @@ -66,9 +66,7 @@ var y = gnrm2( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/README.md new file mode 100644 index 000000000000..08585ae2d4ef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/README.md @@ -0,0 +1,133 @@ + + +# gsyr + +> Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gsyr = require( '@stdlib/blas/base/ndarray/gsyr' ); +``` + +#### gsyr( arrays ) + +Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. + +```javascript +var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + +var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ], 'generic' ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' +}); + +var y = gsyr( [ x, A, uplo, alpha ] ); +// returns [ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ] + +var bool = ( y === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a two-dimensional input ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gsyr = require( '@stdlib/blas/base/ndarray/gsyr' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = gsyr( [ x, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/benchmark/benchmark.js new file mode 100644 index 000000000000..d8cdf6f150b1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gsyr = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var uplo; + var x; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + A = zeros( [ len, len ], options ); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + alpha = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = gsyr( [ x, A, uplo, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/repl.txt new file mode 100644 index 000000000000..b1ca2069bbe5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/repl.txt @@ -0,0 +1,42 @@ + +{{alias}}( arrays ) + Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, + where `alpha` is a scalar, `x` is a one-dimensional ndarray, and + `A` is an `N` by `N` symmetric matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a two-dimensional input ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower + triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( xbuf, 'generic' ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ]; + > var A = {{alias:@stdlib/ndarray/matrix/ctor}}( abuf, 'generic' ); + + > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' ); + > var opts = { 'dtype': 'generic' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, opts ); + + > {{alias}}( [ x, A, uplo, alpha ] ); + > A + [ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/index.d.ts new file mode 100644 index 000000000000..834c4459e529 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/index.d.ts @@ -0,0 +1,67 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a two-dimensional input ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ], 'generic' ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'generic' +* }); +* +* var y = gsyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ +declare function gsyr = typedndarray>( arrays: [ typedndarray, T, ndarray, typedndarray ] ): T; + + +// EXPORTS // + +export = gsyr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/test.ts new file mode 100644 index 000000000000..7b96902f7678 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import gsyr = require( '@stdlib/blas/base/ndarray/gsyr' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 3 ], { + 'dtype': 'generic' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'generic' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + + gsyr( [ x, A, uplo, alpha ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gsyr( '10' ); // $ExpectError + gsyr( 10 ); // $ExpectError + gsyr( true ); // $ExpectError + gsyr( false ); // $ExpectError + gsyr( null ); // $ExpectError + gsyr( undefined ); // $ExpectError + gsyr( [] ); // $ExpectError + gsyr( {} ); // $ExpectError + gsyr( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 3 ], { + 'dtype': 'generic' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'generic' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'generic' + }); + + gsyr(); // $ExpectError + gsyr( [ x, A, uplo, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/examples/index.js new file mode 100644 index 000000000000..731932d14569 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gsyr = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = gsyr( [ x, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/index.js new file mode 100644 index 000000000000..a17112a87340 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. +* +* @module @stdlib/blas/base/ndarray/gsyr +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var gsyr = require( '@stdlib/blas/base/ndarray/gsyr' ); +* +* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ], 'generic' ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'generic' +* }); +* +* var y = gsyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/main.js new file mode 100644 index 000000000000..e9343012f255 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/lib/main.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/gsyr' ).ndarray; + + +// MAIN // + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a two-dimensional input ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var matrix = require( '@stdlib/ndarray/matrix/ctor' ); +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = vector( [ 1.0, 2.0, 3.0 ], 'generic' ); +* var A = matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ], 'generic' ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'generic' +* }); +* +* var y = gsyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 3.0, 6.0, 9.0 ], [ 2.0, 9.0, 14.0 ], [ 3.0, 2.0, 19.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ +function gsyr( arrays ) { + var alpha; + var uplo; + var x; + var A; + + x = arrays[ 0 ]; + A = arrays[ 1 ]; + + uplo = ndarraylike2scalar( arrays[ 2 ] ); + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + strided( uplo, numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( A ), getStride( A, 0 ), getStride( A, 1 ), getOffset( A ) ); + + return A; +} + + +// EXPORTS // + +module.exports = gsyr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/package.json new file mode 100644 index 000000000000..725d48f5e44d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/gsyr", + "version": "0.0.0", + "description": "Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "gsyr", + "linear", + "algebra", + "subroutines", + "symmetric", + "rank-1", + "update", + "vector", + "matrix", + "array", + "ndarray", + "generic", + "typedndarray" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/test/test.js new file mode 100644 index 000000000000..5151be74275c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/gsyr/test/test.js @@ -0,0 +1,283 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var gsyr = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} N - number of rows and columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, N, stride0, stride1, offset ) { + return new ndarray( 'generic', buffer, [ N, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gsyr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( gsyr.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A`', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = [ 1.0, 2.0, 3.0 ]; + Abuf = [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ]; + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gsyr( [ x, A, uplo, alpha ] ); + + expected = [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = [ 1.0, 1.0, 1.0 ]; + Abuf = [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ]; + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 1, 3, 0 ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gsyr( [ x, A, uplo, alpha ] ); + + expected = [ 3.0, 2.0, 3.0, 4.0, 3.0, 2.0, 5.0, 4.0, 3.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = [ 1.0, 2.0, 3.0 ]; + Abuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ]; + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + + v = gsyr( [ x, A, uplo, alpha ] ); + + expected = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = [ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]; + x = vector( xbuf, 3, 2, 0 ); + + Abuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + A = matrix( Abuf, 3, 3, 1, 0 ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gsyr( [ x, A, uplo, alpha ] ); + + expected = [ 2.0, 4.0, 6.0, 0.0, 8.0, 12.0, 0.0, 0.0, 18.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = [ + 3.0, // 2 + 2.0, // 1 + 1.0 // 0 + ]; + x = vector( xbuf, 3, -1, 2 ); + + Abuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + A = matrix( Abuf, 3, 3, 1, 0 ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gsyr( [ x, A, uplo, alpha ] ); + + expected = [ 2.0, 4.0, 6.0, 0.0, 8.0, 12.0, 0.0, 0.0, 18.0 ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = [ + 0.0, + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]; + x = vector( xbuf, 3, 2, 1 ); + + Abuf = [ + 999.0, + 999.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + A = matrix( Abuf, 3, 3, 1, 2 ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + v = gsyr( [ x, A, uplo, alpha ] ); + + expected = [ + 999.0, + 999.0, + 2.0, + 4.0, + 6.0, + 0.0, + 8.0, + 12.0, + 0.0, + 0.0, + 18.0 + ]; + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameArray( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js index 4646f1b68993..070e8c50c570 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js +++ b/lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js @@ -54,6 +54,15 @@ setReadOnly( ns, 'caxpy', require( '@stdlib/blas/base/ndarray/caxpy' ) ); */ setReadOnly( ns, 'ccopy', require( '@stdlib/blas/base/ndarray/ccopy' ) ); +/** +* @name cgemv +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/cgemv} +*/ +setReadOnly( ns, 'cgemv', require( '@stdlib/blas/base/ndarray/cgemv' ) ); + /** * @name cscal * @memberof ns @@ -117,6 +126,33 @@ setReadOnly( ns, 'dcopy', require( '@stdlib/blas/base/ndarray/dcopy' ) ); */ setReadOnly( ns, 'ddot', require( '@stdlib/blas/base/ndarray/ddot' ) ); +/** +* @name dgemm +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/dgemm} +*/ +setReadOnly( ns, 'dgemm', require( '@stdlib/blas/base/ndarray/dgemm' ) ); + +/** +* @name dgemv +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/dgemv} +*/ +setReadOnly( ns, 'dgemv', require( '@stdlib/blas/base/ndarray/dgemv' ) ); + +/** +* @name dger +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/dger} +*/ +setReadOnly( ns, 'dger', require( '@stdlib/blas/base/ndarray/dger' ) ); + /** * @name dnrm2 * @memberof ns @@ -144,6 +180,15 @@ setReadOnly( ns, 'dscal', require( '@stdlib/blas/base/ndarray/dscal' ) ); */ setReadOnly( ns, 'dsdot', require( '@stdlib/blas/base/ndarray/dsdot' ) ); +/** +* @name dspr +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/dspr} +*/ +setReadOnly( ns, 'dspr', require( '@stdlib/blas/base/ndarray/dspr' ) ); + /** * @name dswap * @memberof ns @@ -153,6 +198,24 @@ setReadOnly( ns, 'dsdot', require( '@stdlib/blas/base/ndarray/dsdot' ) ); */ setReadOnly( ns, 'dswap', require( '@stdlib/blas/base/ndarray/dswap' ) ); +/** +* @name dsyr +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/dsyr} +*/ +setReadOnly( ns, 'dsyr', require( '@stdlib/blas/base/ndarray/dsyr' ) ); + +/** +* @name dsyr2 +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/dsyr2} +*/ +setReadOnly( ns, 'dsyr2', require( '@stdlib/blas/base/ndarray/dsyr2' ) ); + /** * @name dzasum * @memberof ns @@ -207,6 +270,33 @@ setReadOnly( ns, 'gcopy', require( '@stdlib/blas/base/ndarray/gcopy' ) ); */ setReadOnly( ns, 'gdot', require( '@stdlib/blas/base/ndarray/gdot' ) ); +/** +* @name ggemm +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/ggemm} +*/ +setReadOnly( ns, 'ggemm', require( '@stdlib/blas/base/ndarray/ggemm' ) ); + +/** +* @name ggemv +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/ggemv} +*/ +setReadOnly( ns, 'ggemv', require( '@stdlib/blas/base/ndarray/ggemv' ) ); + +/** +* @name gger +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/gger} +*/ +setReadOnly( ns, 'gger', require( '@stdlib/blas/base/ndarray/gger' ) ); + /** * @name gnrm2 * @memberof ns @@ -234,6 +324,15 @@ setReadOnly( ns, 'gscal', require( '@stdlib/blas/base/ndarray/gscal' ) ); */ setReadOnly( ns, 'gswap', require( '@stdlib/blas/base/ndarray/gswap' ) ); +/** +* @name gsyr +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/gsyr} +*/ +setReadOnly( ns, 'gsyr', require( '@stdlib/blas/base/ndarray/gsyr' ) ); + /** * @name idamax * @memberof ns @@ -324,6 +423,33 @@ setReadOnly( ns, 'sdot', require( '@stdlib/blas/base/ndarray/sdot' ) ); */ setReadOnly( ns, 'sdsdot', require( '@stdlib/blas/base/ndarray/sdsdot' ) ); +/** +* @name sgemm +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/sgemm} +*/ +setReadOnly( ns, 'sgemm', require( '@stdlib/blas/base/ndarray/sgemm' ) ); + +/** +* @name sgemv +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/sgemv} +*/ +setReadOnly( ns, 'sgemv', require( '@stdlib/blas/base/ndarray/sgemv' ) ); + +/** +* @name sger +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/sger} +*/ +setReadOnly( ns, 'sger', require( '@stdlib/blas/base/ndarray/sger' ) ); + /** * @name snrm2 * @memberof ns @@ -342,6 +468,15 @@ setReadOnly( ns, 'snrm2', require( '@stdlib/blas/base/ndarray/snrm2' ) ); */ setReadOnly( ns, 'sscal', require( '@stdlib/blas/base/ndarray/sscal' ) ); +/** +* @name sspr +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/sspr} +*/ +setReadOnly( ns, 'sspr', require( '@stdlib/blas/base/ndarray/sspr' ) ); + /** * @name sswap * @memberof ns @@ -351,6 +486,24 @@ setReadOnly( ns, 'sscal', require( '@stdlib/blas/base/ndarray/sscal' ) ); */ setReadOnly( ns, 'sswap', require( '@stdlib/blas/base/ndarray/sswap' ) ); +/** +* @name ssyr +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/ssyr} +*/ +setReadOnly( ns, 'ssyr', require( '@stdlib/blas/base/ndarray/ssyr' ) ); + +/** +* @name ssyr2 +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/base/ndarray/ssyr2} +*/ +setReadOnly( ns, 'ssyr2', require( '@stdlib/blas/base/ndarray/ssyr2' ) ); + /** * @name zaxpy * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/scasum/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/scasum/README.md index 8b6a7500d6a8..4a35b457fa9b 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/scasum/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/scasum/README.md @@ -33,7 +33,7 @@ The [_L1_ norm][l1norm] is defined as ``` @@ -66,9 +66,7 @@ var y = scasum( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/README.md index 59c4034ad6c4..3192c36fb90d 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/scnrm2/README.md @@ -33,7 +33,7 @@ The [L2-norm][l2-norm] is defined as ``` @@ -66,9 +66,7 @@ var y = scnrm2( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/README.md new file mode 100644 index 000000000000..ae2443a75fc9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/README.md @@ -0,0 +1,146 @@ + + +# sgemm + +> Perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var sgemm = require( '@stdlib/blas/base/ndarray/sgemm' ); +``` + +#### sgemm( arrays ) + +Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + +```javascript +var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + +var A = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +var B = new Float32Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +var C = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' +}); +var beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' +}); + +var out = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); +// returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + +var bool = ( out === C ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a two-dimensional input ndarray corresponding to `B`. + - a two-dimensional input/output ndarray corresponding to `C`. + - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sgemm = require( '@stdlib/blas/base/ndarray/sgemm' ); + +var opts = { + 'dtype': 'float32' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var B = discreteUniform( [ 4, 2 ], 0, 10, opts ); +var C = discreteUniform( [ 3, 2 ], 0, 10, opts ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/benchmark/benchmark.js new file mode 100644 index 000000000000..c1a2f92350b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/benchmark/benchmark.js @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sgemm = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var transA; + var transB; + var alpha; + var beta; + var A; + var B; + var C; + + A = uniform( [ len, len ], -100.0, 100.0, options ); + B = uniform( [ len, len ], -100.0, 100.0, options ); + C = uniform( [ len, len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + beta = scalar2ndarray( 1.0, options ); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( z.get( i%len, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/repl.txt new file mode 100644 index 000000000000..fade23ad1514 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/repl.txt @@ -0,0 +1,54 @@ + +{{alias}}( arrays ) + Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, + where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` + are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` + matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a two-dimensional input ndarray corresponding to `B`. + - a two-dimensional input/output ndarray corresponding to `C`. + - a zero-dimensional ndarray specifying whether `A` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray specifying whether `B` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `beta`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var abuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float32}}( abuf ); + + > var bbuf = [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ]; + > var B = new {{alias:@stdlib/ndarray/matrix/float32}}( bbuf ); + + > var cbuf = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]; + > var C = new {{alias:@stdlib/ndarray/matrix/float32}}( cbuf ); + + > var opts = { 'dtype': 'float32' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > var beta = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var transA = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + > var transB = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + + > {{alias}}( [ A, B, C, transA, transB, alpha, beta ] ); + > C + [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/types/index.d.ts new file mode 100644 index 000000000000..0109f1082a18 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/types/index.d.ts @@ -0,0 +1,76 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a two-dimensional input ndarray corresponding to `B`. +* - a two-dimensional input/output ndarray corresponding to `C`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* var B = new Float32Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +* var C = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var z = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( z === C ); +* // returns true +*/ +declare function sgemm( arrays: [ float32ndarray, float32ndarray, float32ndarray, ndarray, ndarray, float32ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = sgemm; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/types/test.ts new file mode 100644 index 000000000000..5c8d26991e2e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/docs/types/test.ts @@ -0,0 +1,93 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import sgemm = require( '@stdlib/blas/base/ndarray/sgemm' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const A = zeros( [ 2, 2 ], { + 'dtype': 'float32' + }); + const B = zeros( [ 2, 2 ], { + 'dtype': 'float32' + }); + const C = zeros( [ 2, 2 ], { + 'dtype': 'float32' + }); + const transA = zeros( [], { + 'dtype': 'int32' + }); + const transB = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + const beta = zeros( [], { + 'dtype': 'float32' + }); + + sgemm( [ A, B, C, transA, transB, alpha, beta ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sgemm( '10' ); // $ExpectError + sgemm( 10 ); // $ExpectError + sgemm( true ); // $ExpectError + sgemm( false ); // $ExpectError + sgemm( null ); // $ExpectError + sgemm( undefined ); // $ExpectError + sgemm( [] ); // $ExpectError + sgemm( {} ); // $ExpectError + sgemm( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = zeros( [ 2, 2 ], { + 'dtype': 'float32' + }); + const B = zeros( [ 2, 2 ], { + 'dtype': 'float32' + }); + const C = zeros( [ 2, 2 ], { + 'dtype': 'float32' + }); + const transA = zeros( [], { + 'dtype': 'int32' + }); + const transB = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + const beta = zeros( [], { + 'dtype': 'float32' + }); + + sgemm(); // $ExpectError + sgemm( [ A, B, C, transA, transB, alpha, beta ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/examples/index.js new file mode 100644 index 000000000000..a9ab43b98c78 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sgemm = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var B = discreteUniform( [ 4, 2 ], 0, 10, opts ); +var C = discreteUniform( [ 3, 2 ], 0, 10, opts ); + +var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/lib/index.js new file mode 100644 index 000000000000..fd7745b0ac0b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 3 routine to perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`. +* +* @module @stdlib/blas/base/ndarray/sgemm +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* var sgemm = require( '@stdlib/blas/base/ndarray/sgemm' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* var B = new Float32Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +* var C = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var out = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( out === C ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/lib/main.js new file mode 100644 index 000000000000..6c8542547cf5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/lib/main.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var strided = require( '@stdlib/blas/base/sgemm' ).ndarray; + + +// VARIABLES // + +var NO_TRANSPOSE = resolveEnum( 'no-transpose' ); + + +// MAIN // + +/** +* Performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`, where `op(X)` is either `op(X) = X` or `op(X) = X^T`, `alpha` and `beta` are scalars, `A`, `B`, and `C` are matrices, with `op(A)` an `M` by `K` matrix, `op(B)` a `K` by `N` matrix, and `C` an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a two-dimensional input ndarray corresponding to `B`. +* - a two-dimensional input/output ndarray corresponding to `C`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray specifying whether `B` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* var B = new Float32Matrix( [ [ 1.0, 1.0 ], [ 0.0, 1.0 ] ] ); +* var C = new Float32Matrix( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] ); +* +* var transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var z = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); +* // returns [ [ 2.0, 5.0 ], [ 6.0, 11.0 ] ] +* +* var bool = ( z === C ); +* // returns true +*/ +function sgemm( arrays ) { + var transA; + var transB; + var alpha; + var beta; + var shA; + var shC; + var stA; + var stB; + var stC; + var A; + var B; + var C; + var M; + var N; + var K; + + A = arrays[ 0 ]; + B = arrays[ 1 ]; + C = arrays[ 2 ]; + + transA = ndarraylike2scalar( arrays[ 3 ] ); + transB = ndarraylike2scalar( arrays[ 4 ] ); + alpha = ndarraylike2scalar( arrays[ 5 ] ); + beta = ndarraylike2scalar( arrays[ 6 ] ); + + shA = getShape( A, false ); + shC = getShape( C, false ); + + stA = getStrides( A, false ); + stB = getStrides( B, false ); + stC = getStrides( C, false ); + + M = shC[ 0 ]; + N = shC[ 1 ]; + if ( resolveEnum( transA ) === NO_TRANSPOSE ) { + K = shA[ 1 ]; + } else { + K = shA[ 0 ]; + } + + strided( transA, transB, M, N, K, alpha, getData( A ), stA[ 0 ], stA[ 1 ], getOffset( A ), getData( B ), stB[ 0 ], stB[ 1 ], getOffset( B ), beta, getData( C ), stC[ 0 ], stC[ 1 ], getOffset( C ) ); // eslint-disable-line max-len + + return C; +} + + +// EXPORTS // + +module.exports = sgemm; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/package.json new file mode 100644 index 000000000000..3106e604b02a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/base/ndarray/sgemm", + "version": "0.0.0", + "description": "Perform the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 3", + "sgemm", + "linear", + "algebra", + "subroutines", + "matrix-matrix", + "multiply", + "matrix", + "array", + "ndarray", + "float32", + "single", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/test/test.js new file mode 100644 index 000000000000..527f05001b31 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemm/test/test.js @@ -0,0 +1,441 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var sgemm = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'float32', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sgemm, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sgemm.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (no-transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 23.0, 29.0, 50.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 36.0, 45.0, 45.0, 57.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (no-transpose, transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 2, 3, 3, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 15.0, 33.0, 33.0, 78.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-matrix operation `C = alpha*op(A)*op(B) + beta*C` (conjugate-transpose, no-transpose)', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'conjugate-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 36.0, 45.0, 45.0, 57.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function correctly applies both `alpha` and `beta` scalars', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 3.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 47.0, 62.0, 107.0, 140.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `beta*C`', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 2.0, 4.0, 6.0, 8.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports column-major ndarrays', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] ); + Bbuf = new Float32Array( [ 1.0, 3.0, 5.0, 2.0, 4.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + B = matrix( Bbuf, 3, 2, 1, 3, 0 ); + C = matrix( Cbuf, 2, 2, 1, 2, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 23.0, 50.0, 29.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 4.0, 5.0, 6.0, 1.0, 2.0, 3.0 ] ); + Bbuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, -3, 1, 3 ); + B = matrix( Bbuf, 3, 2, 2, 1, 0 ); + C = matrix( Cbuf, 2, 2, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 23.0, 29.0, 50.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var transA; + var transB; + var alpha; + var beta; + var Abuf; + var Bbuf; + var Cbuf; + var A; + var B; + var C; + var v; + + Abuf = new Float32Array( [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Bbuf = new Float32Array( [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + Cbuf = new Float32Array( [ 0.0, 1.0, 1.0, 1.0, 1.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + B = matrix( Bbuf, 3, 2, 2, 1, 2 ); + C = matrix( Cbuf, 2, 2, 2, 1, 1 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + transA = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + transB = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int32' + }); + + v = sgemm( [ A, B, C, transA, transB, alpha, beta ] ); + + expected = new Float32Array( [ 0.0, 23.0, 29.0, 50.0, 65.0 ] ); + t.strictEqual( v, C, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/README.md new file mode 100644 index 000000000000..b004fbbf6c54 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/README.md @@ -0,0 +1,140 @@ + + +# sgemv + +> Perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var sgemv = require( '@stdlib/blas/base/ndarray/sgemv' ); +``` + +#### sgemv( arrays ) + +Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + +```javascript +var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); + +var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +var y = new Float32Vector( [ 4.0, 5.0 ] ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' +}); +var beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' +}); + +var out = sgemv( [ A, x, y, trans, alpha, beta ] ); +// returns [ 18.0, 37.0 ] + +var bool = ( out === y ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sgemv = require( '@stdlib/blas/base/ndarray/sgemv' ); + +var opts = { + 'dtype': 'float32' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = sgemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/benchmark/benchmark.js new file mode 100644 index 000000000000..31090b6b36c9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/benchmark/benchmark.js @@ -0,0 +1,121 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sgemv = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var trans; + var alpha; + var beta; + var A; + var x; + var y; + + A = uniform( [ len, len ], -100.0, 100.0, options ); + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + beta = scalar2ndarray( 1.0, options ); + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sgemv( [ A, x, y, trans, alpha, beta ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/repl.txt new file mode 100644 index 000000000000..1edf61c96226 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/repl.txt @@ -0,0 +1,50 @@ + +{{alias}}( arrays ) + Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` + or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` + and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a two-dimensional input ndarray corresponding to `A`. + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to `y`. + - a zero-dimensional ndarray specifying whether `A` should be + transposed, conjugate-transposed, or not transposed. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `beta`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float32}}( abuf ); + + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf ); + + > var ybuf = [ 4.0, 5.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf ); + + > var opts = { 'dtype': 'float32' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + > var beta = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var trans = {{alias:@stdlib/ndarray/from-scalar}}( 'no-transpose' ); + + > {{alias}}( [ A, x, y, trans, alpha, beta ] ); + > y + [ 18.0, 37.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/types/index.d.ts new file mode 100644 index 000000000000..a805fa041187 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/types/index.d.ts @@ -0,0 +1,73 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float32Vector( [ 4.0, 5.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var z = sgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +declare function sgemv( arrays: [ float32ndarray, float32ndarray, float32ndarray, ndarray, float32ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = sgemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/types/test.ts new file mode 100644 index 000000000000..9ccf9c531ed9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/docs/types/test.ts @@ -0,0 +1,87 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import sgemv = require( '@stdlib/blas/base/ndarray/sgemv' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'float32' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 2 ], { + 'dtype': 'float32' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + const beta = zeros( [], { + 'dtype': 'float32' + }); + + sgemv( [ A, x, y, trans, alpha, beta ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sgemv( '10' ); // $ExpectError + sgemv( 10 ); // $ExpectError + sgemv( true ); // $ExpectError + sgemv( false ); // $ExpectError + sgemv( null ); // $ExpectError + sgemv( undefined ); // $ExpectError + sgemv( [] ); // $ExpectError + sgemv( {} ); // $ExpectError + sgemv( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const A = zeros( [ 2, 3 ], { + 'dtype': 'float32' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 2 ], { + 'dtype': 'float32' + }); + const trans = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + const beta = zeros( [], { + 'dtype': 'float32' + }); + + sgemv(); // $ExpectError + sgemv( [ A, x, y, trans, alpha, beta ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/examples/index.js new file mode 100644 index 000000000000..fd24fb8c4034 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sgemv = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); + +var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, opts ); +var beta = scalar2ndarray( 1.0, opts ); + +var out = sgemv( [ A, x, y, trans, alpha, beta ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/lib/index.js new file mode 100644 index 000000000000..16afa54131ab --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/lib/index.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`. +* +* @module @stdlib/blas/base/ndarray/sgemv +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* var sgemv = require( '@stdlib/blas/base/ndarray/sgemv' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float32Vector( [ 4.0, 5.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var out = sgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( out === y ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/lib/main.js new file mode 100644 index 000000000000..897ee87d459b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/lib/main.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/sgemv' ).ndarray; + + +// MAIN // + +/** +* Performs one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`, where `alpha` and `beta` are scalars, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a two-dimensional input ndarray corresponding to `A`. +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to `y`. +* - a zero-dimensional ndarray specifying whether `A` should be transposed, conjugate-transposed, or not transposed. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `beta`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float32Vector( [ 4.0, 5.0 ] ); +* +* var trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* var beta = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var z = sgemv( [ A, x, y, trans, alpha, beta ] ); +* // returns [ 18.0, 37.0 ] +* +* var bool = ( z === y ); +* // returns true +*/ +function sgemv( arrays ) { + var trans; + var alpha; + var beta; + var sh; + var st; + var A; + var x; + var y; + + A = arrays[ 0 ]; + x = arrays[ 1 ]; + y = arrays[ 2 ]; + + trans = ndarraylike2scalar( arrays[ 3 ] ); + alpha = ndarraylike2scalar( arrays[ 4 ] ); + beta = ndarraylike2scalar( arrays[ 5 ] ); + + sh = getShape( A, false ); + st = getStrides( A, false ); + + strided( trans, sh[ 0 ], sh[ 1 ], alpha, getData( A ), st[ 0 ], st[ 1 ], getOffset( A ), getData( x ), getStride( x, 0 ), getOffset( x ), beta, getData( y ), getStride( y, 0 ), getOffset( y ) ); + + return y; +} + + +// EXPORTS // + +module.exports = sgemv; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/package.json new file mode 100644 index 000000000000..8f0d0e7113fd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/sgemv", + "version": "0.0.0", + "description": "Perform one of the matrix-vector operations `y = alpha*A*x + beta*y` or `y = alpha*A^T*x + beta*y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "sgemv", + "linear", + "algebra", + "subroutines", + "matrix-vector", + "multiply", + "vector", + "matrix", + "array", + "ndarray", + "float32", + "single", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/test/test.js new file mode 100644 index 000000000000..fe81627296d6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sgemv/test/test.js @@ -0,0 +1,457 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/transpose-operation-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var sgemv = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'float32', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sgemv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sgemv.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array( [ 6.0, 13.0, 20.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array( [ 46.0, 60.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A^T*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array( [ 8.0, 12.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the matrix-vector operation `y = alpha*A^H*x + beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + A = matrix( Abuf, 2, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'conjugate-transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array( [ 8.0, 12.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `beta*y`', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 3, 2, 2, 1, 0 ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array( [ 2.0, 4.0, 6.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides (transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = new Float32Array([ + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + x = vector( xbuf, 2, 2, 0 ); + + ybuf = new Float32Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 0 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array( [ 20.0, 0.0, 28.0, 0.0, 36.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides (transpose)', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + + xbuf = new Float32Array([ + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + x = vector( xbuf, 2, -2, 2 ); + + ybuf = new Float32Array([ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + y = vector( ybuf, 3, -2, 4 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array( [ 36.0, 0.0, 28.0, 0.0, 20.0 ] ); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var trans; + var alpha; + var beta; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + Abuf = new Float32Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + + xbuf = new Float32Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + x = vector( xbuf, 3, 1, 2 ); + + ybuf = new Float32Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + y = vector( ybuf, 2, 2, 1 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + beta = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + trans = scalar2ndarray( resolveEnum( 'no-transpose' ), { + 'dtype': 'int8' + }); + + v = sgemv( [ A, x, y, trans, alpha, beta ] ); + + expected = new Float32Array([ + 0.0, + 30.0, + 0.0, + 68.0 + ]); + t.strictEqual( v, y, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/sger/README.md new file mode 100644 index 000000000000..b7f4c0eaa46e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/README.md @@ -0,0 +1,126 @@ + + +# sger + +> Perform the rank 1 operation `A = alpha*x*y^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var sger = require( '@stdlib/blas/base/ndarray/sger' ); +``` + +#### sger( arrays ) + +Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. + +```javascript +var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = new Float32Vector( [ 1.0, 2.0 ] ); +var y = new Float32Vector( [ 3.0, 4.0, 5.0 ] ); +var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); + +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' +}); + +var out = sger( [ x, y, A, alpha ] ); +// returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + +var bool = ( out === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sger = require( '@stdlib/blas/base/ndarray/sger' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 4 ], 0, 10, opts ); +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); + +var alpha = scalar2ndarray( 1.0, opts ); + +var out = sger( [ x, y, A, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/sger/benchmark/benchmark.js new file mode 100644 index 000000000000..5b817e2194a6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sger = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var x; + var y; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + A = uniform( [ len, len ], -100.0, 100.0, options ); + + alpha = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sger( [ x, y, A, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/repl.txt new file mode 100644 index 000000000000..bee50d76e12a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( arrays ) + Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a + scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by + `N` matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf ); + + > var ybuf = [ 3.0, 4.0, 5.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float32}}( abuf ); + + > var opts = { 'dtype': 'float32' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > {{alias}}( [ x, y, A, alpha ] ); + > A + [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/types/index.d.ts new file mode 100644 index 000000000000..24c3cd0ff76e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/types/index.d.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float32Vector( [ 1.0, 2.0 ] ); +* var y = new Float32Vector( [ 3.0, 4.0, 5.0 ] ); +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var z = sger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +declare function sger( arrays: [ float32ndarray, float32ndarray, float32ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = sger; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/types/test.ts new file mode 100644 index 000000000000..0bdeaf608342 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import sger = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 2 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const A = zeros( [ 2, 3 ], { + 'dtype': 'float32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + sger( [ x, y, A, alpha ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sger( '10' ); // $ExpectError + sger( 10 ); // $ExpectError + sger( true ); // $ExpectError + sger( false ); // $ExpectError + sger( null ); // $ExpectError + sger( undefined ); // $ExpectError + sger( [] ); // $ExpectError + sger( {} ); // $ExpectError + sger( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const A = zeros( [ 2, 3 ], { + 'dtype': 'float32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + sger(); // $ExpectError + sger( [ x, y, A, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sger/examples/index.js new file mode 100644 index 000000000000..77d0373ed83b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sger = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 4 ], 0, 10, opts ); +var A = discreteUniform( [ 3, 4 ], 0, 10, opts ); + +var alpha = scalar2ndarray( 1.0, opts ); + +var out = sger( [ x, y, A, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sger/lib/index.js new file mode 100644 index 000000000000..05beb6368f5b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the rank 1 operation `A = alpha*x*y^T + A`. +* +* @module @stdlib/blas/base/ndarray/sger +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var sger = require( '@stdlib/blas/base/ndarray/sger' ); +* +* var x = new Float32Vector( [ 1.0, 2.0 ] ); +* var y = new Float32Vector( [ 3.0, 4.0, 5.0 ] ); +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var out = sger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( out === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/sger/lib/main.js new file mode 100644 index 000000000000..619ecddfe796 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/lib/main.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getShape = require( '@stdlib/ndarray/base/shape' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/sger' ).ndarray; + + +// MAIN // + +/** +* Performs the rank 1 operation `A = alpha*x*y^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `M` by `N` matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float32Vector( [ 1.0, 2.0 ] ); +* var y = new Float32Vector( [ 3.0, 4.0, 5.0 ] ); +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ] ); +* +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var z = sger( [ x, y, A, alpha ] ); +* // returns [ [ 4.0, 6.0, 8.0 ], [ 10.0, 13.0, 16.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +function sger( arrays ) { + var alpha; + var sh; + var st; + var A; + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + A = arrays[ 2 ]; + + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + sh = getShape( A, false ); + st = getStrides( A, false ); + + strided( sh[ 0 ], sh[ 1 ], alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) ); + + return A; +} + + +// EXPORTS // + +module.exports = sger; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/sger/package.json new file mode 100644 index 000000000000..7384175240ca --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/base/ndarray/sger", + "version": "0.0.0", + "description": "Perform the rank 1 operation `A = alpha*x*y^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "sger", + "linear", + "algebra", + "subroutines", + "rank-1", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float32", + "single", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sger/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/sger/test/test.js new file mode 100644 index 000000000000..ddb17e41c1a5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sger/test/test.js @@ -0,0 +1,315 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var sger = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} M - number of rows +* @param {NonNegativeInteger} N - number of columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, M, N, stride0, stride1, offset ) { + return new ndarray( 'float32', buffer, [ M, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sger, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sger.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the rank 1 operation `A = alpha*x*y^T + A`', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + v = sger( [ x, y, A, alpha ] ); + + expected = new Float32Array( [ 2.0, 4.0, 6.0, 6.0, 9.0, 12.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 1, 2, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + v = sger( [ x, y, A, alpha ] ); + + expected = new Float32Array( [ 2.0, 4.0, 5.0, 8.0, 8.0, 12.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 2.0 // 1 + ]); + ybuf = new Float32Array([ + 3.0, // 0 + 4.0, // 1 + 5.0 // 2 + ]); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + + v = sger( [ x, y, A, alpha ] ); + + expected = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + x = vector( xbuf, 2, 2, 0 ); + + ybuf = new Float32Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 0 ); + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + v = sger( [ x, y, A, alpha ] ); + + expected = new Float32Array( [ 3.0, 6.0, 9.0, 8.0, 13.0, 18.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + x = vector( xbuf, 2, -2, 2 ); + + ybuf = new Float32Array([ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + y = vector( ybuf, 3, -2, 4 ); + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + A = matrix( Abuf, 2, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + v = sger( [ x, y, A, alpha ] ); + + expected = new Float32Array( [ 3.0, 6.0, 9.0, 8.0, 13.0, 18.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0 // 1 + ]); + x = vector( xbuf, 2, 2, 1 ); + + ybuf = new Float32Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + y = vector( ybuf, 3, 1, 2 ); + + Abuf = new Float32Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + A = matrix( Abuf, 2, 3, 3, 1, 2 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + v = sger( [ x, y, A, alpha ] ); + + expected = new Float32Array([ + 0.0, + 0.0, + 2.0, + 4.0, + 6.0, + 6.0, + 9.0, + 12.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/snrm2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/snrm2/README.md index 847e89b13662..cdec05fd54fd 100644 --- a/lib/node_modules/@stdlib/blas/base/ndarray/snrm2/README.md +++ b/lib/node_modules/@stdlib/blas/base/ndarray/snrm2/README.md @@ -33,7 +33,7 @@ The [L2-norm][l2-norm] is defined as ``` @@ -66,9 +66,7 @@ var y = snrm2( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/README.md new file mode 100644 index 000000000000..c2a71bc49a26 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/README.md @@ -0,0 +1,131 @@ + + +# sspr + +> Perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form. + +
+ +
+ + + +
+ +## Usage + +```javascript +var sspr = require( '@stdlib/blas/base/ndarray/sspr' ); +``` + +#### sspr( arrays ) + +Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by `N` matrix supplied in packed form. + +```javascript +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + +var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +var AP = new Float32Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' +}); + +var y = sspr( [ x, AP, uplo, alpha ] ); +// returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] + +var bool = ( y === AP ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to the packed form of `A`. + - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sspr = require( '@stdlib/blas/base/ndarray/sspr' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var AP = discreteUniform( [ 10 ], 0, 10, opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 3.0, opts ); + +var out = sspr( [ x, AP, uplo, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/benchmark/benchmark.js new file mode 100644 index 000000000000..720112ea4344 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/benchmark/benchmark.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sspr = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var uplo; + var AP; + var x; + + AP = uniform( [ ( len * ( len+1 ) ) / 2 ], -100.0, 100.0, options ); + x = uniform( [ len ], -100.0, 100.0, options ); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + alpha = scalar2ndarray( 1.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sspr( [ x, AP, uplo, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( z.get( i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/repl.txt new file mode 100644 index 000000000000..72db86935cde --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( arrays ) + Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` + is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by + `N` matrix supplied in packed form. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input/output ndarray corresponding to the packed + form of `A`. + - a zero-dimensional ndarray specifying whether the upper or lower + triangular part of `A` is supplied. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf ); + + > var apbuf = [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ]; + > var AP = new {{alias:@stdlib/ndarray/vector/float32}}( apbuf ); + + > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' ); + > var opts = { 'dtype': 'float32' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > {{alias}}( [ x, AP, uplo, alpha ] ); + > AP + [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/types/index.d.ts new file mode 100644 index 000000000000..c6c8a683970a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/types/index.d.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is a symmetric `N` by `N` matrix supplied in packed form. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to the packed form of `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var AP = new Float32Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var y = sspr( [ x, AP, uplo, alpha ] ); +* // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] +* +* var bool = ( y === AP ); +* // returns true +*/ +declare function sspr( arrays: [ float32ndarray, float32ndarray, ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = sspr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/types/test.ts new file mode 100644 index 000000000000..d88028c4e85a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import sspr = require( '@stdlib/blas/base/ndarray/sspr' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const AP = zeros( [ 6 ], { + 'dtype': 'float32' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const uplo = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + sspr( [ x, AP, uplo, alpha ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sspr( '10' ); // $ExpectError + sspr( 10 ); // $ExpectError + sspr( true ); // $ExpectError + sspr( false ); // $ExpectError + sspr( null ); // $ExpectError + sspr( undefined ); // $ExpectError + sspr( [] ); // $ExpectError + sspr( {} ); // $ExpectError + sspr( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const AP = zeros( [ 6 ], { + 'dtype': 'float32' + }); + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const uplo = zeros( [], { + 'dtype': 'int8' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + sspr(); // $ExpectError + sspr( [ x, AP, uplo, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/examples/index.js new file mode 100644 index 000000000000..ba73978b07f8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sspr = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 4 ], 0, 10, opts ); +var AP = discreteUniform( [ 10 ], 0, 10, opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' +}); +var alpha = scalar2ndarray( 3.0, opts ); + +var out = sspr( [ x, AP, uplo, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/lib/index.js new file mode 100644 index 000000000000..cf9d2cc864c1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/lib/index.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form. +* +* @module @stdlib/blas/base/ndarray/sspr +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var sspr = require( '@stdlib/blas/base/ndarray/sspr' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var AP = new Float32Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var out = sspr( [ x, AP, uplo, alpha ] ); +* // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] +* +* var bool = ( out === AP ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/lib/main.js new file mode 100644 index 000000000000..3ed8497499fe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/lib/main.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getOrder = require( '@stdlib/ndarray/base/order' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/sspr' ).ndarray; + + +// MAIN // + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix supplied in packed form. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input/output ndarray corresponding to the packed form of `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of `A` is supplied. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var AP = new Float32Vector( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int8' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var y = sspr( [ x, AP, uplo, alpha ] ); +* // returns [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] +* +* var bool = ( y === AP ); +* // returns true +*/ +function sspr( arrays ) { + var alpha; + var uplo; + var AP; + var x; + + x = arrays[ 0 ]; + AP = arrays[ 1 ]; + + uplo = ndarraylike2scalar( arrays[ 2 ] ); + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + strided( getOrder( AP ), uplo, numelDimension( x, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( AP ), getStride( AP, 0 ), getOffset( AP ) ); // eslint-disable-line max-len + + return AP; +} + + +// EXPORTS // + +module.exports = sspr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/package.json new file mode 100644 index 000000000000..73d67eada97e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/sspr", + "version": "0.0.0", + "description": "Perform the symmetric rank 1 operation `A = alpha*x*x^T + A` for a symmetric matrix `A` supplied in packed form.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "sspr", + "linear", + "algebra", + "subroutines", + "rank 1", + "symmetric", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float32", + "single", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/sspr/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/test/test.js new file mode 100644 index 000000000000..5fce2eddce11 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/sspr/test/test.js @@ -0,0 +1,304 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var sspr = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sspr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sspr.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (upper)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = sspr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float32Array( [ 1.0, 1.0, 1.0 ] ); + Abuf = new Float32Array( [ 1.0, 4.0, 2.0, 5.0, 3.0, 6.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = sspr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 3.0, 6.0, 4.0, 7.0, 5.0, 8.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (lower)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 1.0, 3.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'lower' ), { + 'dtype': 'int8' + }); + + v = sspr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 2.0, 4.0, 5.0, 6.0, 8.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + x = vector( xbuf, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = sspr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + + xbuf = new Float32Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = sspr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 3.0, 6.0, 9.0, 9.0, 14.0, 19.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 1.0, 2.0, 1.0 ] ); + A = vector( Abuf, 6, 1, 0 ); + + xbuf = new Float32Array([ + 3.0, // 2 + 0.0, + 2.0, // 1 + 0.0, + 1.0 // 0 + ]); + x = vector( xbuf, 3, -2, 4 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = sspr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 3.0, 6.0, 9.0, 9.0, 14.0, 19.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + Abuf = new Float32Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 3.0, + 1.0, + 2.0, + 1.0 + ]); + A = vector( Abuf, 6, 1, 2 ); + + xbuf = new Float32Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + x = vector( xbuf, 3, 1, 2 ); + + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int8' + }); + + v = sspr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array([ + 0.0, + 0.0, + 3.0, + 6.0, + 9.0, + 9.0, + 14.0, + 19.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/README.md new file mode 100644 index 000000000000..37c3abe99855 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/README.md @@ -0,0 +1,135 @@ + + +# ssyr + +> Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var ssyr = require( '@stdlib/blas/base/ndarray/ssyr' ); +``` + +#### ssyr( arrays ) + +Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. + + + +```javascript +var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); + +var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' +}); + +var y = ssyr( [ x, A, uplo, alpha ] ); +// returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] + +var bool = ( y === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ssyr = require( '@stdlib/blas/base/ndarray/ssyr' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = ssyr( [ x, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/benchmark/benchmark.js new file mode 100644 index 000000000000..014d50b8d406 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var ssyr = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var uplo; + var x; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + A = zeros( [ len, len ], options ); + + alpha = scalar2ndarray( 1.0, options ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = ssyr( [ x, A, uplo, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/repl.txt new file mode 100644 index 000000000000..fc5d9c09da96 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( arrays ) + Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where + `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an + `N` by `N` symmetric matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower + triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float32}}( abuf ); + + > var opts = { 'dtype': 'float32' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, opts ); + + > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' ); + + > {{alias}}( [ x, A, uplo, alpha ] ); + > A + [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/types/index.d.ts new file mode 100644 index 000000000000..9b5396f06a62 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/types/index.d.ts @@ -0,0 +1,67 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var y = ssyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ +declare function ssyr( arrays: [ float32ndarray, float32ndarray, ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = ssyr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/types/test.ts new file mode 100644 index 000000000000..4046e13404ed --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import ssyr = require( '@stdlib/blas/base/ndarray/ssyr' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float32' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + ssyr( [ x, A, uplo, alpha ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + ssyr( '10' ); // $ExpectError + ssyr( 10 ); // $ExpectError + ssyr( true ); // $ExpectError + ssyr( false ); // $ExpectError + ssyr( null ); // $ExpectError + ssyr( undefined ); // $ExpectError + ssyr( [] ); // $ExpectError + ssyr( {} ); // $ExpectError + ssyr( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float32' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + ssyr(); // $ExpectError + ssyr( [ x, A, uplo, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/examples/index.js new file mode 100644 index 000000000000..325de028f29f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ssyr = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = ssyr( [ x, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/lib/index.js new file mode 100644 index 000000000000..04d62683908b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the symmetric rank 1 operation `A = alpha*x*x^T + A`. +* +* @module @stdlib/blas/base/ndarray/ssyr +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var ssyr = require( '@stdlib/blas/base/ndarray/ssyr' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var y = ssyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/lib/main.js new file mode 100644 index 000000000000..b4c47b748ace --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/lib/main.js @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/ssyr' ).ndarray; + + +// MAIN // + +/** +* Performs the symmetric rank 1 operation `A = alpha*x*x^T + A`, where `alpha` is a scalar, `x` is a one-dimensional ndarray, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 1.0, { +* 'dtype': 'float32' +* }); +* +* var y = ssyr( [ x, A, uplo, alpha ] ); +* // returns [ [ 2.0, 4.0, 6.0 ], [ 2.0, 5.0, 8.0 ], [ 3.0, 2.0, 10.0 ] ] +* +* var bool = ( y === A ); +* // returns true +*/ +function ssyr( arrays ) { + var alpha; + var uplo; + var st; + var x; + var A; + + x = arrays[ 0 ]; + A = arrays[ 1 ]; + + uplo = ndarraylike2scalar( arrays[ 2 ] ); + alpha = ndarraylike2scalar( arrays[ 3 ] ); + + st = getStrides( A, false ); + + strided( uplo, numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) ); + + return A; +} + + +// EXPORTS // + +module.exports = ssyr; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/package.json new file mode 100644 index 000000000000..7c06d2deef06 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/ssyr", + "version": "0.0.0", + "description": "Perform the symmetric rank 1 operation `A = alpha*x*x^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "ssyr", + "linear", + "algebra", + "subroutines", + "symmetric", + "rank-1", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float32", + "single", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/test/test.js new file mode 100644 index 000000000000..6c79fda3079f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr/test/test.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var ssyr = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} N - number of rows and columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, N, stride0, stride1, offset ) { + return new ndarray( 'float32', buffer, [ N, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssyr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( ssyr.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (upper)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = ssyr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 2.0, 4.0, 6.0, 2.0, 5.0, 8.0, 3.0, 2.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float32Array( [ 1.0, 1.0, 1.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 1, 3, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = ssyr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 2.0, 2.0, 3.0, 3.0, 2.0, 2.0, 4.0, 3.0, 2.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the symmetric rank 1 operation `A = alpha*x*x^T + A` (lower)', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'lower' ), { + 'dtype': 'int32' + }); + + v = ssyr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 2.0, 2.0, 3.0, 4.0, 5.0, 2.0, 6.0, 8.0, 10.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = ssyr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + Abuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = ssyr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 4.0, 6.0, 0.0, 0.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array([ + 3.0, // 2 + 2.0, // 1 + 1.0 // 0 + ]); + x = vector( xbuf, 3, -1, 2 ); + + Abuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 1.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = ssyr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array( [ 1.0, 2.0, 3.0, 0.0, 4.0, 6.0, 0.0, 0.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var Abuf; + var uplo; + var x; + var A; + var v; + + xbuf = new Float32Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 1 ); + + Abuf = new Float32Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0 + ]); + A = matrix( Abuf, 3, 3, 1, 2 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + v = ssyr( [ x, A, uplo, alpha ] ); + + expected = new Float32Array([ + 1.0, + 2.0, + 5.0, + 8.0, + 11.0, + 6.0, + 15.0, + 20.0, + 9.0, + 10.0, + 29.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md new file mode 100644 index 000000000000..3e36df0c3dd0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/README.md @@ -0,0 +1,138 @@ + + +# ssyr2 + +> Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`. + +
+ +
+ + + +
+ +## Usage + +```javascript +var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' ); +``` + +#### ssyr2( arrays ) + +Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. + + + +```javascript +var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' +}); + +var z = ssyr2( [ x, y, A, uplo, alpha ] ); +// returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] + +var bool = ( z === A ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. + +
+ + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = ssyr2( [ x, y, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js new file mode 100644 index 000000000000..c2d71a2641b8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/benchmark/benchmark.js @@ -0,0 +1,120 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var ssyr2 = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var uplo; + var x; + var y; + var A; + + x = uniform( [ len ], -100.0, 100.0, options ); + y = uniform( [ len ], -100.0, 100.0, options ); + A = zeros( [ len, len ], options ); + + alpha = scalar2ndarray( 1.0, options ); + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = ssyr2( [ x, y, A, uplo, alpha ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnanf( z.get( 0, i%len ) ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 3; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt new file mode 100644 index 000000000000..bd2f211cacaf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/repl.txt @@ -0,0 +1,47 @@ + +{{alias}}( arrays ) + Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, + where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and + `A` is an `N` by `N` symmetric matrix. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray corresponding to `x`. + - a one-dimensional input ndarray corresponding to `y`. + - a two-dimensional input/output ndarray corresponding to `A`. + - a zero-dimensional ndarray specifying whether the upper or lower + triangular part of the symmetric matrix `A` should be referenced. + - a zero-dimensional ndarray containing a scalar constant corresponding + to `alpha`. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf ); + + > var ybuf = [ 2.0, 1.0, 3.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf ); + + > var abuf = [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ]; + > var A = new {{alias:@stdlib/ndarray/matrix/float32}}( abuf ); + + > var uplo = {{alias:@stdlib/ndarray/from-scalar}}( 'upper' ); + + > var opts = { 'dtype': 'float32' }; + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 2.0, opts ); + + > {{alias}}( [ x, y, A, uplo, alpha ] ); + > A + [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts new file mode 100644 index 000000000000..215b6bc21668 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/index.d.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray, ndarray } from '@stdlib/types/ndarray'; + +/** +* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'float32' +* }); +* +* var z = ssyr2( [ x, y, A, uplo, alpha ] ); +* // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +declare function ssyr2( arrays: [ float32ndarray, float32ndarray, float32ndarray, ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = ssyr2; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts new file mode 100644 index 000000000000..6b5d6a2f7bef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/docs/types/test.ts @@ -0,0 +1,81 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float32' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + ssyr2( [ x, y, A, uplo, alpha ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + ssyr2( '10' ); // $ExpectError + ssyr2( 10 ); // $ExpectError + ssyr2( true ); // $ExpectError + ssyr2( false ); // $ExpectError + ssyr2( null ); // $ExpectError + ssyr2( undefined ); // $ExpectError + ssyr2( [] ); // $ExpectError + ssyr2( {} ); // $ExpectError + ssyr2( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 3 ], { + 'dtype': 'float32' + }); + const A = zeros( [ 3, 3 ], { + 'dtype': 'float32' + }); + const uplo = zeros( [], { + 'dtype': 'int32' + }); + const alpha = zeros( [], { + 'dtype': 'float32' + }); + + ssyr2(); // $ExpectError + ssyr2( [ x, y, A, uplo, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js new file mode 100644 index 000000000000..7c39c35a1eb6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ssyr2 = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 3 ], 0, 10, opts ); +var y = discreteUniform( [ 3 ], 0, 10, opts ); +var A = zeros( [ 3, 3 ], opts ); + +var uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' +}); +var alpha = scalar2ndarray( 1.0, opts ); + +var out = ssyr2( [ x, y, A, uplo, alpha ] ); +console.log( ndarray2array( out ) ); diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js new file mode 100644 index 000000000000..338398685e4a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/index.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* BLAS level 2 routine to perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`. +* +* @module @stdlib/blas/base/ndarray/ssyr2 +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var ssyr2 = require( '@stdlib/blas/base/ndarray/ssyr2' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] ); +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'float32' +* }); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var out = ssyr2( [ x, y, A, uplo, alpha ] ); +* // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] +* +* var bool = ( out === A ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js new file mode 100644 index 000000000000..842451782acc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/lib/main.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStrides = require( '@stdlib/ndarray/base/strides' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/base/ssyr2' ).ndarray; + + +// MAIN // + +/** +* Performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`, where `alpha` is a scalar, `x` and `y` are one-dimensional ndarrays, and `A` is an `N` by `N` symmetric matrix. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray corresponding to `x`. +* - a one-dimensional input ndarray corresponding to `y`. +* - a two-dimensional input/output ndarray corresponding to `A`. +* - a zero-dimensional ndarray specifying whether the upper or lower triangular part of the symmetric matrix `A` should be referenced. +* - a zero-dimensional ndarray containing a scalar constant corresponding to `alpha`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {Object} output ndarray +* +* @example +* var Float32Matrix = require( '@stdlib/ndarray/matrix/float32' ); +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var A = new Float32Matrix( [ [ 1.0, 2.0, 3.0 ], [ 2.0, 1.0, 2.0 ], [ 3.0, 2.0, 1.0 ] ] ); +* var x = new Float32Vector( [ 1.0, 2.0, 3.0 ] ); +* var y = new Float32Vector( [ 2.0, 1.0, 3.0 ] ); +* +* var uplo = scalar2ndarray( resolveEnum( 'upper' ), { +* 'dtype': 'int32' +* }); +* var alpha = scalar2ndarray( 2.0, { +* 'dtype': 'float32' +* }); +* +* var z = ssyr2( [ x, y, A, uplo, alpha ] ); +* // returns [ [ 9.0, 12.0, 21.0 ], [ 2.0, 9.0, 20.0 ], [ 3.0, 2.0, 37.0 ] ] +* +* var bool = ( z === A ); +* // returns true +*/ +function ssyr2( arrays ) { + var alpha; + var uplo; + var st; + var A; + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + A = arrays[ 2 ]; + + uplo = ndarraylike2scalar( arrays[ 3 ] ); + alpha = ndarraylike2scalar( arrays[ 4 ] ); + + st = getStrides( A, false ); + + strided( uplo, numelDimension( A, 0 ), alpha, getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ), getData( A ), st[ 0 ], st[ 1 ], getOffset( A ) ); // eslint-disable-line max-len + + return A; +} + + +// EXPORTS // + +module.exports = ssyr2; diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json new file mode 100644 index 000000000000..094a63371320 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/base/ndarray/ssyr2", + "version": "0.0.0", + "description": "Perform the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 2", + "ssyr2", + "linear", + "algebra", + "subroutines", + "symmetric", + "rank-2", + "update", + "vector", + "matrix", + "array", + "ndarray", + "float32", + "single", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js new file mode 100644 index 000000000000..6d10173d0030 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/ndarray/ssyr2/test/test.js @@ -0,0 +1,360 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var resolveEnum = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var ssyr2 = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + +/** +* Returns a two-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} N - number of rows and columns +* @param {integer} stride0 - stride of the first dimension +* @param {integer} stride1 - stride of the second dimension +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} two-dimensional ndarray +*/ +function matrix( buffer, N, stride0, stride1, offset ) { + return new ndarray( 'float32', buffer, [ N, N ], [ stride0, stride1 ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof ssyr2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( ssyr2.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A` (upper)', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + ybuf = new Float32Array( [ 2.0, 1.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = ssyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float32Array( [ 9.0, 12.0, 21.0, 2.0, 9.0, 20.0, 3.0, 2.0, 37.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + xbuf = new Float32Array( [ 1.0, 1.0, 1.0 ] ); + ybuf = new Float32Array( [ 1.0, 1.0, 1.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 1, 3, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = ssyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float32Array( [ 5.0, 2.0, 3.0, 6.0, 5.0, 2.0, 7.0, 6.0, 5.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs the symmetric rank 2 operation `A = alpha*x*y^T + alpha*y*x^T + A` (lower)', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + ybuf = new Float32Array( [ 2.0, 1.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 2.0, 1.0, 2.0, 3.0, 2.0, 1.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'lower' ), { + 'dtype': 'int32' + }); + v = ssyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float32Array( [ 9.0, 2.0, 3.0, 12.0, 9.0, 2.0, 21.0, 20.0, 37.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` is `0`, the function returns `A` unchanged', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + ybuf = new Float32Array( [ 2.0, 1.0, 3.0 ] ); + Abuf = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = ssyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-unit strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + + ybuf = new Float32Array([ + 2.0, // 0 + 0.0, + 1.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 0 ); + + Abuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = ssyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float32Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 3.0, // 2 + 2.0, // 1 + 1.0 // 0 + ]); + x = vector( xbuf, 3, -1, 2 ); + + ybuf = new Float32Array([ + 3.0, // 2 + 1.0, // 1 + 2.0 // 0 + ]); + y = vector( ybuf, 3, -1, 2 ); + + Abuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + A = matrix( Abuf, 3, 3, 1, 0 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = ssyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float32Array( [ 8.0, 10.0, 18.0, 0.0, 8.0, 18.0, 0.0, 0.0, 36.0 ] ); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var alpha; + var xbuf; + var ybuf; + var Abuf; + var uplo; + var x; + var y; + var A; + var v; + + xbuf = new Float32Array([ + 0.0, + 1.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 3.0 // 2 + ]); + x = vector( xbuf, 3, 2, 1 ); + + ybuf = new Float32Array([ + 0.0, + 2.0, // 0 + 0.0, + 1.0, // 1 + 0.0, + 3.0 // 2 + ]); + y = vector( ybuf, 3, 2, 1 ); + + Abuf = new Float32Array([ + 999.0, + 999.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + A = matrix( Abuf, 3, 3, 1, 2 ); + alpha = scalar2ndarray( 2.0, { + 'dtype': 'float32' + }); + + uplo = scalar2ndarray( resolveEnum( 'upper' ), { + 'dtype': 'int32' + }); + v = ssyr2( [ x, y, A, uplo, alpha ] ); + + expected = new Float32Array([ + 999.0, + 999.0, + 8.0, + 10.0, + 18.0, + 0.0, + 8.0, + 18.0, + 0.0, + 0.0, + 36.0 + ]); + t.strictEqual( v, A, 'returns expected value' ); + t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/base/operation-sides/test/test.js b/lib/node_modules/@stdlib/blas/base/operation-sides/test/test.js index c5f0d3ea7cf0..a2bf3a065a9e 100644 --- a/lib/node_modules/@stdlib/blas/base/operation-sides/test/test.js +++ b/lib/node_modules/@stdlib/blas/base/operation-sides/test/test.js @@ -66,7 +66,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/blas/base/sspmv/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/sspmv/lib/ndarray.js index 2b88c58748cd..a287a0107e83 100644 --- a/lib/node_modules/@stdlib/blas/base/sspmv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/sspmv/lib/ndarray.js @@ -24,7 +24,7 @@ var sfill = require( '@stdlib/blas/ext/base/sfill' ).ndarray; var sscal = require( '@stdlib/blas/base/sscal' ).ndarray; var f32 = require( '@stdlib/number/float64/base/to-float32' ); var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); @@ -35,7 +35,7 @@ var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string * Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} AP - packed form of a symmetric matrix `A` @@ -75,11 +75,13 @@ function sspmv( order, uplo, N, alpha, AP, x, strideX, offsetX, beta, y, strideY var ky; var j; var k; + var u; if ( !isLayout( order ) ) { throw new TypeError( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ); } if ( N < 0 ) { @@ -110,8 +112,8 @@ function sspmv( order, uplo, N, alpha, AP, x, strideX, offsetX, beta, y, strideY ky = offsetY; kk = 0; if ( - ( isRowMajor( order ) && uplo === 'upper' ) || - ( isColumnMajor( order ) && uplo === 'lower' ) + ( isRowMajor( order ) && u === 'upper' ) || + ( isColumnMajor( order ) && u === 'lower' ) ) { jx = kx; jy = ky; @@ -134,7 +136,7 @@ function sspmv( order, uplo, N, alpha, AP, x, strideX, offsetX, beta, y, strideY } return y; } - // ( order === 'row-major' && uplo === 'lower') || ( order === 'column-major' && uplo === 'upper' ) + // ( order === 'row-major' && u === 'lower') || ( order === 'column-major' && u === 'upper' ) jx = kx; jy = ky; for ( j = 0; j < N; j++ ) { diff --git a/lib/node_modules/@stdlib/blas/base/sspmv/lib/sspmv.js b/lib/node_modules/@stdlib/blas/base/sspmv/lib/sspmv.js index 112cbce9d642..b734c42af285 100644 --- a/lib/node_modules/@stdlib/blas/base/sspmv/lib/sspmv.js +++ b/lib/node_modules/@stdlib/blas/base/sspmv/lib/sspmv.js @@ -24,7 +24,7 @@ var sfill = require( '@stdlib/blas/ext/base/sfill' ); var sscal = require( '@stdlib/blas/base/sscal' ); var f32 = require( '@stdlib/number/float64/base/to-float32' ); var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major-string' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); @@ -35,7 +35,7 @@ var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string * Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} AP - packed form of a symmetric matrix `A` @@ -74,11 +74,13 @@ function sspmv( order, uplo, N, alpha, AP, x, strideX, beta, y, strideY ) { var sy; var j; var k; + var u; if ( !isLayout( order ) ) { throw new TypeError( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ); } if ( N < 0 ) { @@ -121,8 +123,8 @@ function sspmv( order, uplo, N, alpha, AP, x, strideX, beta, y, strideY ) { // Form: y = alpha*A*x + y kk = 0; if ( - ( isRowMajor( order ) && uplo === 'upper' ) || - ( isColumnMajor( order ) && uplo === 'lower' ) + ( isRowMajor( order ) && u === 'upper' ) || + ( isColumnMajor( order ) && u === 'lower' ) ) { jx = kx; jy = ky; @@ -145,7 +147,7 @@ function sspmv( order, uplo, N, alpha, AP, x, strideX, beta, y, strideY ) { } return y; } - // ( order === 'row-major' && uplo === 'lower') || ( order === 'column-major' && uplo === 'upper' ) + // ( order === 'row-major' && u === 'lower') || ( order === 'column-major' && u === 'upper' ) jx = kx; jy = ky; for ( j = 0; j < N; j++ ) { diff --git a/lib/node_modules/@stdlib/blas/base/sspr/README.md b/lib/node_modules/@stdlib/blas/base/sspr/README.md index 85bd2f57a9e7..5f8184fe4f14 100644 --- a/lib/node_modules/@stdlib/blas/base/sspr/README.md +++ b/lib/node_modules/@stdlib/blas/base/sspr/README.md @@ -86,7 +86,7 @@ sspr( 'row-major', 'upper', 3, 1.0, x1, -1, AP ); // AP => [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] ``` -#### sspr.ndarray( uplo, N, α, x, sx, ox, AP, sap, oap ) +#### sspr.ndarray( order, uplo, N, α, x, sx, ox, AP, sap, oap ) Performs the symmetric rank 1 operation `A = α*x*x^T + A`, using alternative indexing semantics and where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. diff --git a/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.js index 0a67a5c58018..e355807f54de 100644 --- a/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -32,7 +32,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - input vector @@ -58,10 +58,12 @@ var base = require( './base.js' ); * // AP => [ 2.0, 4.0, 6.0, 5.0, 8.0, 10.0 ] */ function sspr( order, uplo, N, alpha, x, strideX, offsetX, AP, strideAP, offsetAP ) { // eslint-disable-line max-len + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -76,7 +78,7 @@ function sspr( order, uplo, N, alpha, x, strideX, offsetX, AP, strideAP, offsetA if ( N === 0 || alpha === 0.0 ) { return AP; } - return base( order, uplo, N, alpha, x, strideX, offsetX, AP, strideAP, offsetAP ); // eslint disable-line max-len + return base( order, u, N, alpha, x, strideX, offsetX, AP, strideAP, offsetAP ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.native.js index e19ef9c171e4..e0caf6be2dc1 100644 --- a/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/sspr/lib/ndarray.native.js @@ -28,7 +28,7 @@ var addon = require( './../src/addon.node' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - input vector diff --git a/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.js b/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.js index d54e1746bea8..5a67f53b6f26 100644 --- a/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.js +++ b/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -33,7 +33,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - input vector @@ -56,11 +56,13 @@ var base = require( './base.js' ); */ function sspr( order, uplo, N, alpha, x, strideX, AP ) { var ox; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -73,7 +75,7 @@ function sspr( order, uplo, N, alpha, x, strideX, AP ) { return AP; } ox = stride2offset( N, strideX ); - return base( order, uplo, N, alpha, x, strideX, ox, AP, 1, 0 ); + return base( order, u, N, alpha, x, strideX, ox, AP, 1, 0 ); } diff --git a/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.native.js b/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.native.js index 61350c1570cf..a32f636b2326 100644 --- a/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.native.js +++ b/lib/node_modules/@stdlib/blas/base/sspr/lib/sspr.native.js @@ -31,7 +31,7 @@ var addon = require( './../src/addon.node' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix supplied in packed form. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` is supplied * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - input vector diff --git a/lib/node_modules/@stdlib/blas/base/ssymv/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/ssymv/lib/ndarray.js index ff55bce5210a..905b41d6e3bf 100644 --- a/lib/node_modules/@stdlib/blas/base/ssymv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/ssymv/lib/ndarray.js @@ -20,7 +20,7 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -30,7 +30,7 @@ var base = require( './base.js' ); /** * Performs the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} A - input matrix @@ -63,7 +63,10 @@ var base = require( './base.js' ); * // y => [ 10.0, 12.0, 14.0 ] */ function ssymv( uplo, N, alpha, A, strideA1, strideA2, offsetA, x, strideX, offsetX, beta, y, strideY, offsetY ) { // eslint-disable-line max-params, max-len - if ( !isMatrixTriangle( uplo ) ) { + var u; + + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -84,7 +87,7 @@ function ssymv( uplo, N, alpha, A, strideA1, strideA2, offsetA, x, strideX, offs if ( N === 0 || ( alpha === 0.0 && beta === 1.0 ) ) { return y; } - return base( uplo, N, alpha, A, strideA1, strideA2, offsetA, x, strideX, offsetX, beta, y, strideY, offsetY ); // eslint-disable-line max-len + return base( u, N, alpha, A, strideA1, strideA2, offsetA, x, strideX, offsetX, beta, y, strideY, offsetY ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/ssymv/lib/ssymv.js b/lib/node_modules/@stdlib/blas/base/ssymv/lib/ssymv.js index e1e3d39938c4..66eff3554196 100644 --- a/lib/node_modules/@stdlib/blas/base/ssymv/lib/ssymv.js +++ b/lib/node_modules/@stdlib/blas/base/ssymv/lib/ssymv.js @@ -23,7 +23,7 @@ var max = require( '@stdlib/math/base/special/max' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -34,7 +34,7 @@ var base = require( './base.js' ); * Performs the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} A - input matrix @@ -67,11 +67,13 @@ function ssymv( order, uplo, N, alpha, A, LDA, x, strideX, beta, y, strideY ) { var sa2; var ox; var oy; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -98,7 +100,7 @@ function ssymv( order, uplo, N, alpha, A, LDA, x, strideX, beta, y, strideY ) { sa1 = LDA; sa2 = 1; } - return base( uplo, N, alpha, A, sa1, sa2, 0, x, strideX, ox, beta, y, strideY, oy ); // eslint-disable-line max-len + return base( u, N, alpha, A, sa1, sa2, 0, x, strideX, ox, beta, y, strideY, oy ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/ssyr/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/ssyr/lib/ndarray.js index 80b84bc65b05..ececa216170f 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/ssyr/lib/ndarray.js @@ -20,7 +20,7 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -30,7 +30,7 @@ var base = require( './base.js' ); /** * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - input vector @@ -57,7 +57,8 @@ var base = require( './base.js' ); * // A => [ 2.0, 4.0, 6.0, 2.0, 5.0, 8.0, 3.0, 2.0, 10.0 ] */ function ssyr( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len - if ( !isMatrixTriangle( uplo ) ) { + var u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -76,7 +77,7 @@ function ssyr( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offse if ( N === 0 || alpha === 0.0 ) { return A; } - return base( uplo, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len + return base( u, N, alpha, x, strideX, offsetX, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/ssyr/lib/ssyr.js b/lib/node_modules/@stdlib/blas/base/ssyr/lib/ssyr.js index f10d3974de3d..07c0921ba811 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr/lib/ssyr.js +++ b/lib/node_modules/@stdlib/blas/base/ssyr/lib/ssyr.js @@ -22,7 +22,7 @@ var max = require( '@stdlib/math/base/special/fast/max' ); var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var format = require( '@stdlib/string/format' ); @@ -35,7 +35,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 1 operation `A = α*x*x^T + A` where `α` is a scalar, `x` is an `N` element vector, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - input vector @@ -62,11 +62,13 @@ function ssyr( order, uplo, N, alpha, x, strideX, A, LDA ) { var sa1; var sa2; var ox; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -90,7 +92,7 @@ function ssyr( order, uplo, N, alpha, x, strideX, A, LDA ) { sa2 = 1; } ox = stride2offset( N, strideX ); - return base( uplo, N, alpha, x, strideX, ox, A, sa1, sa2, 0 ); + return base( u, N, alpha, x, strideX, ox, A, sa1, sa2, 0 ); } diff --git a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.js index a1470161f30c..f0d382620e35 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.js @@ -20,7 +20,7 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -30,7 +30,7 @@ var base = require( './base.js' ); /** * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - first input vector @@ -62,7 +62,8 @@ var base = require( './base.js' ); * // A => [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] */ function ssyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len, max-params - if ( !isMatrixTriangle( uplo ) ) { + var u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -84,7 +85,7 @@ function ssyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, str if ( N === 0 || alpha === 0.0 ) { return A; } - return base( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len + return base( u, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.native.js index ef9df3da10df..072b9ecfdbe4 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ndarray.native.js @@ -20,7 +20,6 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); var resolveUplo = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); var format = require( '@stdlib/string/format' ); var addon = require( './../src/addon.node' ); @@ -31,7 +30,7 @@ var addon = require( './../src/addon.node' ); /** * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - first input vector @@ -63,7 +62,8 @@ var addon = require( './../src/addon.node' ); * // A => [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] */ function ssyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ) { // eslint-disable-line max-len, max-params - if ( !isMatrixTriangle( uplo ) ) { + var u = resolveUplo( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -85,7 +85,7 @@ function ssyr2( uplo, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, str if ( N === 0 || alpha === 0.0 ) { return A; } - addon.ndarray( resolveUplo( uplo ), N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len + addon.ndarray( u, N, alpha, x, strideX, offsetX, y, strideY, offsetY, A, strideA1, strideA2, offsetA ); // eslint-disable-line max-len return A; } diff --git a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.js b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.js index 306c6aa9f764..4dbee27fd1ce 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.js +++ b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.js @@ -21,7 +21,7 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); +var resolveStr = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var max = require( '@stdlib/math/base/special/fast/max' ); @@ -35,7 +35,7 @@ var base = require( './base.js' ); * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - first input vector @@ -67,11 +67,13 @@ function ssyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { var sa2; var ox; var oy; + var u; if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveStr( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -99,7 +101,7 @@ function ssyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { } ox = stride2offset( N, strideX ); oy = stride2offset( N, strideY ); - return base( uplo, N, alpha, x, strideX, ox, y, strideY, oy, A, sa1, sa2, 0 ); // eslint-disable-line max-len + return base( u, N, alpha, x, strideX, ox, y, strideY, oy, A, sa1, sa2, 0 ); } diff --git a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.native.js b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.native.js index b5f2eb296daf..7d8bfbc95949 100644 --- a/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.native.js +++ b/lib/node_modules/@stdlib/blas/base/ssyr2/lib/ssyr2.native.js @@ -21,7 +21,6 @@ // MODULES // var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); var resolveOrder = require( '@stdlib/blas/base/layout-resolve-enum' ); var resolveUplo = require( '@stdlib/blas/base/matrix-triangle-resolve-enum' ); var max = require( '@stdlib/math/base/special/fast/max' ); @@ -35,7 +34,7 @@ var addon = require( './../src/addon.node' ); * Performs the symmetric rank 2 operation `A = α*x*y^T + α*y*x^T + A` where `α` is a scalar, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. * * @param {string} order - storage layout -* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced +* @param {(integer|string)} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {number} alpha - scalar constant * @param {Float32Array} x - first input vector @@ -63,10 +62,13 @@ var addon = require( './../src/addon.node' ); * // A => [ 3.0, 6.0, 9.0, 2.0, 9.0, 14.0, 3.0, 2.0, 19.0 ] */ function ssyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { + var u; + if ( !isLayout( order ) ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveUplo( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ) ); } if ( N < 0 ) { @@ -85,7 +87,7 @@ function ssyr2( order, uplo, N, alpha, x, strideX, y, strideY, A, LDA ) { if ( N === 0 || alpha === 0.0 ) { return A; } - addon( resolveOrder( order ), resolveUplo( uplo ), N, alpha, x, strideX, y, strideY, A, LDA ); // eslint-disable-line max-len + addon( resolveOrder( order ), u, N, alpha, x, strideX, y, strideY, A, LDA ); return A; } diff --git a/lib/node_modules/@stdlib/blas/base/strmv/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/strmv/lib/ndarray.js index 8feb20cb6ee3..ac44f00bcc88 100644 --- a/lib/node_modules/@stdlib/blas/base/strmv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/strmv/lib/ndarray.js @@ -20,9 +20,9 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); -var isTransposeOperation = require( '@stdlib/blas/base/assert/is-transpose-operation' ); -var isDiagonal = require( '@stdlib/blas/base/assert/is-diagonal-type' ); +var resolveTriangle = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); +var resolveTranspose = require( '@stdlib/blas/base/transpose-operation-resolve-str' ); +var resolveDiagonal = require( '@stdlib/blas/base/diagonal-type-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -32,9 +32,9 @@ var base = require( './base.js' ); /** * Performs one of the matrix-vector operations `x = A*x` or `x = A^T*x`, where `x` is an `N` element vector and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix. * -* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix -* @param {string} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed -* @param {string} diag - specifies whether `A` has a unit diagonal +* @param {(integer|string)} uplo - specifies whether `A` is an upper or lower triangular matrix +* @param {(integer|string)} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed +* @param {(integer|string)} diag - specifies whether `A` has a unit diagonal * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {Float32Array} A - input matrix * @param {integer} strideA1 - stride of the first dimension of `A` @@ -62,13 +62,20 @@ var base = require( './base.js' ); * // x => [ 14.0, 8.0, 3.0 ] */ function strmv( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ) { // eslint-disable-line max-params, max-len - if ( !isMatrixTriangle( uplo ) ) { + var u; + var t; + var d; + + u = resolveTriangle( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } - if ( !isTransposeOperation( trans ) ) { + t = resolveTranspose( trans ); + if ( t === null ) { throw new TypeError( format( 'invalid argument. Second argument must be a valid transpose operation. Value: `%s`.', trans ) ); } - if ( !isDiagonal( diag ) ) { + d = resolveDiagonal( diag ); + if ( d === null ) { throw new TypeError( format( 'invalid argument. Third argument must be a valid diagonal type. Value: `%s`.', diag ) ); } if ( N < 0 ) { @@ -86,7 +93,7 @@ function strmv( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX if ( N === 0 ) { return x; } - return base( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ); // eslint-disable-line max-len + return base( u, t, d, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/strmv/lib/strmv.js b/lib/node_modules/@stdlib/blas/base/strmv/lib/strmv.js index d321a893d281..6d5d5bd33ef1 100644 --- a/lib/node_modules/@stdlib/blas/base/strmv/lib/strmv.js +++ b/lib/node_modules/@stdlib/blas/base/strmv/lib/strmv.js @@ -21,10 +21,10 @@ // MODULES // var max = require( '@stdlib/math/base/special/fast/max' ); -var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); -var isTransposeOperation = require( '@stdlib/blas/base/assert/is-transpose-operation' ); -var isDiagonal = require( '@stdlib/blas/base/assert/is-diagonal-type' ); +var resolveLayout = require( '@stdlib/blas/base/layout-resolve-str' ); +var resolveTriangle = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); +var resolveTranspose = require( '@stdlib/blas/base/transpose-operation-resolve-str' ); +var resolveDiagonal = require( '@stdlib/blas/base/diagonal-type-resolve-str' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var format = require( '@stdlib/string/format' ); @@ -36,10 +36,10 @@ var base = require( './base.js' ); /** * Performs one of the matrix-vector operations `x = A*x` or `x = A^T*x`, where `x` is an `N` element vector and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix. * -* @param {string} order - storage layout -* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix -* @param {string} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed -* @param {string} diag - specifies whether `A` has a unit diagonal +* @param {(integer|string)} order - storage layout +* @param {(integer|string)} uplo - specifies whether `A` is an upper or lower triangular matrix +* @param {(integer|string)} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed +* @param {(integer|string)} diag - specifies whether `A` has a unit diagonal * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {Float32Array} A - input matrix * @param {integer} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) @@ -67,17 +67,25 @@ function strmv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { var sa1; var sa2; var ox; + var l; + var u; + var t; + var d; - if ( !isLayout( order ) ) { + l = resolveLayout( order ); + if ( l === null ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveTriangle( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } - if ( !isTransposeOperation( trans ) ) { + t = resolveTranspose( trans ); + if ( t === null ) { throw new TypeError( format( 'invalid argument. Third argument must be a valid transpose operation. Value: `%s`.', trans ) ); } - if ( !isDiagonal( diag ) ) { + d = resolveDiagonal( diag ); + if ( d === null ) { throw new TypeError( format( 'invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.', diag ) ); } if ( N < 0 ) { @@ -92,7 +100,7 @@ function strmv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { if ( N === 0 ) { return x; } - if ( isColumnMajor( order ) ) { + if ( isColumnMajor( l ) ) { sa1 = 1; sa2 = LDA; } else { // order === 'row-major' @@ -100,7 +108,7 @@ function strmv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { sa2 = 1; } ox = stride2offset( N, strideX ); - return base( uplo, trans, diag, N, A, sa1, sa2, 0, x, strideX, ox ); + return base( u, t, d, N, A, sa1, sa2, 0, x, strideX, ox ); } diff --git a/lib/node_modules/@stdlib/blas/base/strsv/lib/ndarray.js b/lib/node_modules/@stdlib/blas/base/strsv/lib/ndarray.js index 51a34b8a0a82..7799e1d43e99 100644 --- a/lib/node_modules/@stdlib/blas/base/strsv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/base/strsv/lib/ndarray.js @@ -20,9 +20,9 @@ // MODULES // -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); -var isTransposeOperation = require( '@stdlib/blas/base/assert/is-transpose-operation' ); -var isDiagonal = require( '@stdlib/blas/base/assert/is-diagonal-type' ); +var resolveTriangle = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); +var resolveTranspose = require( '@stdlib/blas/base/transpose-operation-resolve-str' ); +var resolveDiagonal = require( '@stdlib/blas/base/diagonal-type-resolve-str' ); var format = require( '@stdlib/string/format' ); var base = require( './base.js' ); @@ -32,9 +32,9 @@ var base = require( './base.js' ); /** * Solves one of the systems of equations `A*x = b` or `A^T*x = b` where `b` and `x` are `N` element vectors and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix. * -* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix -* @param {string} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed -* @param {string} diag - specifies whether `A` has a unit diagonal +* @param {(integer|string)} uplo - specifies whether `A` is an upper or lower triangular matrix +* @param {(integer|string)} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed +* @param {(integer|string)} diag - specifies whether `A` has a unit diagonal * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {Float32Array} A - input matrix * @param {integer} strideA1 - stride of the first dimension of `A` @@ -62,13 +62,20 @@ var base = require( './base.js' ); * // x => [ 0.0, -4.0, 3.0 ] */ function strsv( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ) { // eslint-disable-line max-params, max-len - if ( !isMatrixTriangle( uplo ) ) { + var u; + var t; + var d; + + u = resolveTriangle( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } - if ( !isTransposeOperation( trans ) ) { + t = resolveTranspose( trans ); + if ( t === null ) { throw new TypeError( format( 'invalid argument. Second argument must be a valid transpose operation. Value: `%s`.', trans ) ); } - if ( !isDiagonal( diag ) ) { + d = resolveDiagonal( diag ); + if ( d === null ) { throw new TypeError( format( 'invalid argument. Third argument must be a valid diagonal type. Value: `%s`.', diag ) ); } if ( N < 0 ) { @@ -86,7 +93,7 @@ function strsv( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX if ( N === 0 ) { return x; } - return base( uplo, trans, diag, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ); // eslint-disable-line max-len + return base( u, t, d, N, A, strideA1, strideA2, offsetA, x, strideX, offsetX ); // eslint-disable-line max-len } diff --git a/lib/node_modules/@stdlib/blas/base/strsv/lib/strsv.js b/lib/node_modules/@stdlib/blas/base/strsv/lib/strsv.js index bfe29914df4d..b760f0b0b76f 100644 --- a/lib/node_modules/@stdlib/blas/base/strsv/lib/strsv.js +++ b/lib/node_modules/@stdlib/blas/base/strsv/lib/strsv.js @@ -21,10 +21,10 @@ // MODULES // var max = require( '@stdlib/math/base/special/fast/max' ); -var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); -var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); -var isTransposeOperation = require( '@stdlib/blas/base/assert/is-transpose-operation' ); -var isDiagonal = require( '@stdlib/blas/base/assert/is-diagonal-type' ); +var resolveLayout = require( '@stdlib/blas/base/layout-resolve-str' ); +var resolveTriangle = require( '@stdlib/blas/base/matrix-triangle-resolve-str' ); +var resolveTranspose = require( '@stdlib/blas/base/transpose-operation-resolve-str' ); +var resolveDiagonal = require( '@stdlib/blas/base/diagonal-type-resolve-str' ); var isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' ); var stride2offset = require( '@stdlib/strided/base/stride2offset' ); var format = require( '@stdlib/string/format' ); @@ -36,10 +36,10 @@ var base = require( './base.js' ); /** * Solves one of the systems of equations `A*x = b` or `A^T*x = b` where `b` and `x` are `N` element vectors and `A` is an `N` by `N` unit, or non-unit, upper or lower triangular matrix. * -* @param {string} order - storage layout -* @param {string} uplo - specifies whether `A` is an upper or lower triangular matrix -* @param {string} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed -* @param {string} diag - specifies whether `A` has a unit diagonal +* @param {(integer|string)} order - storage layout +* @param {(integer|string)} uplo - specifies whether `A` is an upper or lower triangular matrix +* @param {(integer|string)} trans - specifies whether `A` should be transposed, conjugate-transposed, or not transposed +* @param {(integer|string)} diag - specifies whether `A` has a unit diagonal * @param {NonNegativeInteger} N - number of elements along each dimension of `A` * @param {Float32Array} A - input matrix * @param {integer} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) @@ -67,17 +67,25 @@ function strsv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { var sa1; var sa2; var ox; + var l; + var u; + var t; + var d; - if ( !isLayout( order ) ) { + l = resolveLayout( order ); + if ( l === null ) { throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) ); } - if ( !isMatrixTriangle( uplo ) ) { + u = resolveTriangle( uplo ); + if ( u === null ) { throw new TypeError( format( 'invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.', uplo ) ); } - if ( !isTransposeOperation( trans ) ) { + t = resolveTranspose( trans ); + if ( t === null ) { throw new TypeError( format( 'invalid argument. Third argument must be a valid transpose operation. Value: `%s`.', trans ) ); } - if ( !isDiagonal( diag ) ) { + d = resolveDiagonal( diag ); + if ( d === null ) { throw new TypeError( format( 'invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.', diag ) ); } if ( N < 0 ) { @@ -92,7 +100,7 @@ function strsv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { if ( N === 0 ) { return x; } - if ( isColumnMajor( order ) ) { + if ( isColumnMajor( l ) ) { sa1 = 1; sa2 = LDA; } else { // order === 'row-major' @@ -100,7 +108,7 @@ function strsv( order, uplo, trans, diag, N, A, LDA, x, strideX ) { sa2 = 1; } ox = stride2offset( N, strideX ); - return base( uplo, trans, diag, N, A, sa1, sa2, 0, x, strideX, ox ); + return base( u, t, d, N, A, sa1, sa2, 0, x, strideX, ox ); } diff --git a/lib/node_modules/@stdlib/blas/base/transpose-operations/test/test.js b/lib/node_modules/@stdlib/blas/base/transpose-operations/test/test.js index 9e0879e6a724..f4a6e1ac644c 100644 --- a/lib/node_modules/@stdlib/blas/base/transpose-operations/test/test.js +++ b/lib/node_modules/@stdlib/blas/base/transpose-operations/test/test.js @@ -68,7 +68,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ccopy/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ccopy/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/src/Makefile index 87bc9420e487..ed87bc7e1f19 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/ccopy/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cscal/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/cscal/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/cscal/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cscal/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/cscal/src/Makefile index 87bc9420e487..ed87bc7e1f19 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/cscal/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/cscal/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/csrot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/csrot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/csrot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/csrot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/csrot/src/Makefile index 87bc9420e487..ed87bc7e1f19 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/csrot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/csrot/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/cswap/src/Makefile index 87bc9420e487..ed87bc7e1f19 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dasum/README.md b/lib/node_modules/@stdlib/blas/base/wasm/dasum/README.md index e438827327d1..e84674e31b31 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dasum/README.md +++ b/lib/node_modules/@stdlib/blas/base/wasm/dasum/README.md @@ -30,7 +30,7 @@ limitations under the License. var dasum = require( '@stdlib/blas/base/wasm/dasum' ); ``` -#### dasum.main( N, x, stride ) +#### dasum.main( N, x, strideX ) Computes the sum of absolute values. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dasum/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/dasum/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/dasum/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dasum/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/dasum/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dasum/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/dasum/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/daxpy/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/daxpy/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/daxpy/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dcopy/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dcopy/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dcopy/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ddot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/ddot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/ddot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ddot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/ddot/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/ddot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/ddot/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/drot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/drot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/drot/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/drot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/drot/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drotm/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/drotm/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/drotm/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drotm/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/drotm/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/drotm/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/drotm/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dscal/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/dscal/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/dscal/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dscal/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/dscal/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dscal/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/dscal/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dsdot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dsdot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dsdot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dswap/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/dswap/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/dswap/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dswap/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/dswap/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dswap/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/dswap/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/idamax/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/isamax/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/sasum/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/scasum/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/package.json b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/package.json index f9f2ea997f27..e3c55404dd8f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/package.json +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/base/wasm/scnrm2", "version": "0.0.0", - "description": "Multiply a vector `x` by a scalar `alpha`.", + "description": "Calculate the L2-norm of a single-precision complex floating-point vector.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/scopy/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/sdot/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/srot/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/srotm/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/sscal/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/sswap/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js index a1fed48b37f4..01e577b08f5f 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js @@ -42,7 +42,7 @@ var Module = require( './module.js' ); * * // Perform operation: * zcopy.main( x.length, x, 1, y, 1 ); -// y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] +* // y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] * * @example * var Complex128Array = require( '@stdlib/array/complex128' ); @@ -53,7 +53,7 @@ var Module = require( './module.js' ); * * // Perform operation: * zcopy.ndarray( x.length, x, 1, 0, y, -1, 2 ); -// y => [ -5.0, -6.0, -3.0, -4.0, -1.0, -2.0 ] +* // y => [ -5.0, -6.0, -3.0, -4.0, -1.0, -2.0 ] */ var zcopy = new Routine(); zcopy.initializeSync(); // eslint-disable-line n/no-sync diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/routine.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/routine.js index c0b9ff6f77b7..b0f40fa742b2 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/routine.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/routine.js @@ -56,7 +56,7 @@ var Module = require( './module.js' ); * * // Perform operation: * zcopy.main( x.length, x, 1, y, 1 ); -// y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] +* // y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] * * @example * var Complex128Array = require( '@stdlib/array/complex128' ); @@ -73,7 +73,7 @@ var Module = require( './module.js' ); * * // Perform operation: * zcopy.ndarray( x.length, x, 1, 0, y, 1, 0 ); -// y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] +* // y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] */ function Routine() { if ( !( this instanceof Routine ) ) { @@ -117,7 +117,7 @@ inherits( Routine, Module ); * * // Perform operation: * zcopy.main( x.length, x, 1, y, -1 ); -// y => [ -5.0, -6.0, -3.0, -4.0, -1.0, -2.0 ] +* // y => [ -5.0, -6.0, -3.0, -4.0, -1.0, -2.0 ] */ setReadOnly( Routine.prototype, 'main', function zcopy( N, x, strideX, y, strideY ) { return this.ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len @@ -154,7 +154,7 @@ setReadOnly( Routine.prototype, 'main', function zcopy( N, x, strideX, y, stride * * // Perform operation: * zcopy.ndarray( x.length, x, 1, 0, y, 1, 0 ); -// y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] +* // y => [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ] */ setReadOnly( Routine.prototype, 'ndarray', function zcopy( N, x, strideX, offsetX, y, strideY, offsetY ) { var ptrs; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/src/Makefile index c6976e9d0f03..33e623af65b8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js index ca25ee4f12fa..777c9a4f30fd 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js @@ -33,8 +33,8 @@ * * // Perform operation: * zdrot.main( zx.length, zx, 1, zy, 1, 0.8, 0.6 ); -// zx => [ 5.0, 6.4, 7.8, 9.2, 10.6, 12.0 ] -// zy => [ ~5.0, 5.2, 5.4, ~5.6, ~5.8, ~6.0 ] +* // zx => [ 5.0, 6.4, 7.8, 9.2, 10.6, 12.0 ] +* // zy => [ ~5.0, 5.2, 5.4, ~5.6, ~5.8, ~6.0 ] * * @example * var Complex128Array = require( '@stdlib/array/complex128' ); @@ -46,8 +46,8 @@ * * // Perform operation: * zdrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, 0.6 ); -// zx => [ 5.0, 6.4, 7.8, 9.2, 10.6, 12.0 ] -// zy => [ ~5.0, 5.2, 5.4, ~5.6, ~5.8, ~6.0 ] +* // zx => [ 5.0, 6.4, 7.8, 9.2, 10.6, 12.0 ] +* // zy => [ ~5.0, 5.2, 5.4, ~5.6, ~5.8, ~6.0 ] * * @example * var Memory = require( '@stdlib/wasm/memory' ); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js index 5bbb1a6ddf19..028a68dc00c4 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js @@ -42,8 +42,8 @@ var Module = require( './module.js' ); * * // Perform operation: * zdrot.main( zx.length, zx, 1, zy, 1, 0.8, 0.6 ); -// zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] -// zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] +* // zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] +* // zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] * * @example * var Complex128Array = require( '@stdlib/array/complex128' ); @@ -54,8 +54,8 @@ var Module = require( './module.js' ); * * // Perform operation: * zdrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, 0.6 ); -// zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] -// zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] +* // zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] +* // zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] */ var zdrot = new Routine(); zdrot.initializeSync(); // eslint-disable-line n/no-sync diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/routine.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/routine.js index 225abcc7f47d..86101f0c7736 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/routine.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/routine.js @@ -56,8 +56,8 @@ var Module = require( './module.js' ); * * // Perform operation: * zdrot.main( zx.length, zx, 1, zy, 1, 0.8, 0.6 ); -// zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] -// zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] +* // zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] +* // zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] * * @example * var Complex128Array = require( '@stdlib/array/complex128' ); @@ -74,8 +74,8 @@ var Module = require( './module.js' ); * * // Perform operation: * zdrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, 0.6 ); -// zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] -// zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] +* // zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] +* // zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] */ function Routine() { if ( !( this instanceof Routine ) ) { @@ -121,8 +121,8 @@ inherits( Routine, Module ); * * // Perform operation: * zdrot.main( zx.length, zx, 1, zy, 1, 0.8, 0.6 ); -// zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] -// zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] +* // zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] +* // zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] */ setReadOnly( Routine.prototype, 'main', function zdrot( N, zx, strideX, zy, strideY, c, s ) { return this.ndarray( N, zx, strideX, stride2offset( N, strideX ), zy, strideY, stride2offset( N, strideY ), c, s ); // eslint-disable-line max-len @@ -161,8 +161,8 @@ setReadOnly( Routine.prototype, 'main', function zdrot( N, zx, strideX, zy, stri * * // Perform operation: * zdrot.ndarray( zx.length, zx, 1, 0, zy, 1, 0, 0.8, 0.6 ); -// zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] -// zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] +* // zx => [ ~-0.2, ~-0.4, ~-0.6, ~-0.8, -1.0, ~-1.2 ] +* // zy => [ 1.4, 2.8, 4.2, 5.6, 7.0, 8.4 ] */ setReadOnly( Routine.prototype, 'ndarray', function zdrot( N, zx, strideX, offsetX, zy, strideY, offsetY, c, s ) { var ptrs; diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/src/Makefile index c6976e9d0f03..33e623af65b8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/module.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/module.js index 90a34a16c59e..8a739be8fd20 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/module.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/module.js @@ -127,7 +127,7 @@ inherits( Module, WasmModule ); * @param {PositiveInteger} N - number of indexed elements * @param {NonNegativeInteger} aptr - scalar constant pointer (i.e., byte offset) * @param {NonNegativeInteger} xptr - input array pointer (i.e., byte offset) -* @param {integer} strideX - stride length for `x` +* @param {integer} strideX - `x` stride length * @returns {NonNegativeInteger} input array pointer (i.e., byte offset) * * @example @@ -202,7 +202,7 @@ setReadOnly( Module.prototype, 'main', function zscal( N, aptr, xptr, strideX ) * @param {PositiveInteger} N - number of indexed elements * @param {NonNegativeInteger} aptr - scalar constant pointer (i.e., byte offset) * @param {NonNegativeInteger} xptr - input array pointer (i.e., byte offset) -* @param {integer} strideX - stride length for `x` +* @param {integer} strideX - `x` stride length * @param {NonNegativeInteger} offsetX - starting `x` index * @returns {NonNegativeInteger} input array pointer (i.e., byte offset) * diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/routine.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/routine.js index a56e0396d971..fbb9db587ab1 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/routine.js +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/routine.js @@ -105,7 +105,7 @@ inherits( Routine, Module ); * @param {PositiveInteger} N - number of indexed elements * @param {Complex128} alpha - scalar constant * @param {Complex128Array} x - input array -* @param {integer} strideX - stride length for `x` +* @param {integer} strideX - `x` stride length * @returns {Complex128Array} input array * * @example @@ -142,7 +142,7 @@ setReadOnly( Routine.prototype, 'main', function zscal( N, alpha, x, strideX ) { * @param {PositiveInteger} N - number of indexed elements * @param {Complex128} alpha - scalar constant * @param {Complex128Array} x - input array -* @param {integer} strideX - stride length for `x` +* @param {integer} strideX - `x` stride length * @param {NonNegativeInteger} offsetX - starting index for `x` * @returns {Complex128Array} input array * diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/zscal/src/Makefile index c6976e9d0f03..33e623af65b8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/src/Makefile b/lib/node_modules/@stdlib/blas/base/wasm/zswap/src/Makefile index c6976e9d0f03..33e623af65b8 100644 --- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/src/Makefile +++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/src/Makefile @@ -194,6 +194,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/docs/types/index.d.ts index a42dcddbafb6..ccebeeb547de 100644 --- a/lib/node_modules/@stdlib/blas/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/docs/types/index.d.ts @@ -20,12 +20,14 @@ /* eslint-disable max-lines */ +import asum = require( '@stdlib/blas/asum' ); import base = require( '@stdlib/blas/base' ); import ddot = require( '@stdlib/blas/ddot' ); import dswap = require( '@stdlib/blas/dswap' ); import ext = require( '@stdlib/blas/ext' ); import gdot = require( '@stdlib/blas/gdot' ); import gswap = require( '@stdlib/blas/gswap' ); +import nrm2 = require( '@stdlib/blas/nrm2' ); import sdot = require( '@stdlib/blas/sdot' ); import sswap = require( '@stdlib/blas/sswap' ); @@ -33,6 +35,36 @@ import sswap = require( '@stdlib/blas/sswap' ); * Interface describing the `blas` namespace. */ interface Namespace { + /** + * Computes the sum of absolute values (L1 norm) along one or more ndarray dimensions. + * + * @param x - input ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * + * var y = ns.asum( x ); + * // returns [ 5.0 ] + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * var zeros = require( '@stdlib/ndarray/zeros' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * var y = zeros( [] ); + * + * var out = ns.asum.assign( x, y ); + * // returns [ 5.0 ] + * + * var bool = ( out === y ); + * // returns true + */ + asum: typeof asum; + /** * Base (i.e., lower-level) basic linear algebra subprograms (BLAS). */ @@ -158,6 +190,36 @@ interface Namespace { */ gswap: typeof gswap; + /** + * Computes the L2-norm along one or more ndarray dimensions. + * + * @param x - input ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * + * var y = ns.nrm2( x ); + * // returns [ 3.0 ] + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * var zeros = require( '@stdlib/ndarray/zeros' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * var y = zeros( [] ); + * + * var out = ns.nrm2.assign( x, y ); + * // returns [ 3.0 ] + * + * var bool = ( out === y ); + * // returns true + */ + nrm2: typeof nrm2; + /** * Computes the dot product of two single-precision floating-point vectors. * diff --git a/lib/node_modules/@stdlib/blas/ext/base/README.md b/lib/node_modules/@stdlib/blas/ext/base/README.md index b489f61c66ec..f9db3347aab1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/README.md @@ -53,12 +53,15 @@ var o = ns; - [`cindexOf( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/cindex-of]: return the first index of a specified search element in a single-precision complex floating-point strided array. - [`clastIndexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/clast-index-of-row]: return the index of the last row in a single-precision complex floating-point input matrix which has the same elements as a provided search vector. - [`coneTo( N, x, strideX )`][@stdlib/blas/ext/base/cone-to]: fill a single-precision complex floating-point strided array with linearly spaced numeric elements which increment by `1` starting from one. +- [`creplicate( N, k, x, strideX, out, strideOut )`][@stdlib/blas/ext/base/creplicate]: replicate each element in a single-precision complex floating-point strided array a specified number of times. - [`csum( N, x, strideX )`][@stdlib/blas/ext/base/csum]: calculate the sum of single-precision complex floating-point strided array elements. - [`csumkbn( N, x, strideX )`][@stdlib/blas/ext/base/csumkbn]: calculate the sum of single-precision complex floating-point strided array elements using an improved Kahan–Babuška algorithm. - [`cunitspace( N, start, x, strideX )`][@stdlib/blas/ext/base/cunitspace]: fill a single-precision complex floating-point strided array with linearly spaced numeric elements which increment by `1` starting from a specified value. - [`cwapx( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/cwapx]: add a scalar constant to each element in a single-precision complex floating-point strided array `x` and assign the results to elements in a single-precision complex floating-point strided array `w`. +- [`cwax( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/cwax]: multiply each element in a single-precision complex floating-point strided array `x` by a scalar constant and assign the results to elements in a single-precision complex floating-point strided array `w`. - [`cwhere( N, condition, strideC, x, strideX, y, strideY, out, strideOut )`][@stdlib/blas/ext/base/cwhere]: take elements from one of two single-precision complex floating-point strided arrays depending on a condition. - [`cwxsa( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/cwxsa]: subtract a scalar constant from each element in a single-precision complex floating-point strided array `x` and assign the results to elements in a single-precision complex floating-point strided array `w`. +- [`cxmy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/cxmy]: multiply elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assign the results to `y`. - [`cxpy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/cxpy]: add elements of a single-precision complex floating-point strided array `x` to the corresponding elements of a single-precision complex floating-point strided array `y` and assign the results to `y`. - [`cxsa( N, alpha, x, strideX )`][@stdlib/blas/ext/base/cxsa]: subtract a scalar constant from each element in a single-precision complex floating-point strided array. - [`cxsy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/cxsy]: subtract elements of a single-precision complex floating-point strided array `y` from the corresponding elements of a single-precision complex floating-point strided array `x` and assign the results to `y`. @@ -88,9 +91,15 @@ var o = ns; - [`dcusumpw( N, sum, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dcusumpw]: calculate the cumulative sum of double-precision floating-point strided array elements using pairwise summation. - [`ddiff( N, k, x, strideX, N1, prepend, strideP, N2, append, strideA, out, strideOut, workspace, strideW )`][@stdlib/blas/ext/base/ddiff]: calculate the k-th discrete forward difference of a double-precision floating-point strided array. - [`dediff( N, x, strideX, N1, prepend, strideP, N2, append, strideA, out, strideOut )`][@stdlib/blas/ext/base/dediff]: calculate the differences between consecutive elements of a double-precision floating-point strided array. +- [`dfillEqual( N, searchElement, alpha, x, strideX )`][@stdlib/blas/ext/base/dfill-equal]: replace double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +- [`dfillNaN( N, alpha, x, strideX )`][@stdlib/blas/ext/base/dfill-nan]: replace double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +- [`dfillNotEqual( N, searchElement, alpha, x, strideX )`][@stdlib/blas/ext/base/dfill-not-equal]: replace double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. - [`dfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/dfill]: fill a double-precision floating-point strided array with a specified scalar constant. +- [`dfirstIndexEqual( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dfirst-index-equal]: return the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. +- [`dfirstIndexLessThan( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dfirst-index-less-than]: return the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. - [`dindexOfColumn( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/dindex-of-column]: return the index of the first column in a double-precision floating-point input matrix which has the same elements as a provided search vector. - [`dindexOfFalsy( N, x, strideX )`][@stdlib/blas/ext/base/dindex-of-falsy]: return the index of the first falsy element in a double-precision floating-point strided array. +- [`dindexOfNotEqual( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/dindex-of-not-equal]: return the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. - [`dindexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/dindex-of-row]: return the index of the first row in a double-precision floating-point input matrix which has the same elements as a provided search vector. - [`dindexOfTruthy( N, x, strideX )`][@stdlib/blas/ext/base/dindex-of-truthy]: return the index of the first truthy element in a double-precision floating-point strided array. - [`dindexOf( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/dindex-of]: return the first index of a specified search element in a double-precision floating-point strided array. @@ -119,6 +128,7 @@ var o = ns; - [`dnone( N, x, strideX )`][@stdlib/blas/ext/base/dnone]: test whether every element in a double-precision floating-point strided array is falsy. - [`doneTo( N, x, strideX )`][@stdlib/blas/ext/base/done-to]: fill a double-precision floating-point strided array with linearly spaced numeric elements which increment by `1` starting from one. - [`dones( N, x, strideX )`][@stdlib/blas/ext/base/dones]: fill a double-precision floating-point strided array with ones. +- [`dreplicate( N, k, x, strideX, out, strideOut )`][@stdlib/blas/ext/base/dreplicate]: replicate each element in a double-precision floating-point strided array a specified number of times. - [`drev( N, x, strideX )`][@stdlib/blas/ext/base/drev]: reverse a double-precision floating-point strided array in-place. - [`drrss( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/drrss]: calculate the square root of the residual sum of squares of two double-precision floating-point strided arrays. - [`drss( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/drss]: calculate the residual sum of squares of two double-precision floating-point strided arrays. @@ -149,8 +159,10 @@ var o = ns; - [`dunitspace( N, start, x, strideX )`][@stdlib/blas/ext/base/dunitspace]: fill a double-precision floating-point strided array with linearly spaced numeric elements which increment by `1` starting from a specified value. - [`dvander( order, mode, M, N, x, strideX, out, ldo )`][@stdlib/blas/ext/base/dvander]: generate a double-precision floating-point Vandermonde matrix. - [`dwapx( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/dwapx]: add a scalar constant to each element in a double-precision floating-point strided array `x` and assign the results to elements in a double-precision floating-point strided array `w`. +- [`dwax( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/dwax]: multiply each element in a double-precision floating-point strided array `x` by a scalar constant and assign the results to elements in a double-precision floating-point strided array `w`. - [`dwhere( N, condition, strideC, x, strideX, y, strideY, out, strideOut )`][@stdlib/blas/ext/base/dwhere]: take elements from one of two double-precision floating-point strided arrays depending on a condition. - [`dwxsa( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/dwxsa]: subtract a scalar constant from each element in a double-precision floating-point strided array `x` and assign the results to elements in a double-precision floating-point strided array `w`. +- [`dxdy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dxdy]: divide elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assign the results to `y`. - [`dxmy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dxmy]: multiply elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assign the results to `y`. - [`dxpy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/dxpy]: add elements of a double-precision floating-point strided array `x` to the corresponding elements of a double-precision floating-point strided array `y` and assign the results to `y`. - [`dxsa( N, alpha, x, strideX )`][@stdlib/blas/ext/base/dxsa]: subtract a scalar constant from each element in a double-precision floating-point strided array. @@ -185,16 +197,27 @@ var o = ns; - [`gediff( N, x, strideX, N1, prepend, strideP, N2, append, strideA, out, strideOut )`][@stdlib/blas/ext/base/gediff]: calculate the differences between consecutive elements of a strided array. - [`gevery( N, x, strideX )`][@stdlib/blas/ext/base/gevery]: test whether every element in a strided array is truthy. - [`gfillBy( N, x, strideX, clbk[, thisArg] )`][@stdlib/blas/ext/base/gfill-by]: fill a strided array according to a provided callback function. +- [`gfillEqual( N, searchElement, alpha, x, strideX )`][@stdlib/blas/ext/base/gfill-equal]: replace strided array elements equal to a provided search element with a specified scalar constant. +- [`gfillLessThan( N, searchElement, alpha, x, strideX )`][@stdlib/blas/ext/base/gfill-less-than]: replace strided array elements less than a provided search element with a specified scalar constant. +- [`gfillNaN( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gfill-nan]: replace strided array elements equal to `NaN` with a specified scalar constant. +- [`gfillNotEqual( N, searchElement, alpha, x, strideX )`][@stdlib/blas/ext/base/gfill-not-equal]: replace strided array elements not equal to a provided search element with a specified scalar constant. - [`gfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gfill]: fill a strided array with a specified scalar constant. - [`gfindIndex( N, x, strideX, clbk[, thisArg] )`][@stdlib/blas/ext/base/gfind-index]: return the index of the first element which passes a test implemented by a predicate function. - [`gfindLastIndex( N, x, strideX, clbk[, thisArg] )`][@stdlib/blas/ext/base/gfind-last-index]: return the index of the last element which passes a test implemented by a predicate function. +- [`gfirstIndexEqual( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gfirst-index-equal]: return the index of the first element in a strided array equal to a corresponding element in another strided array. +- [`gfirstIndexGreaterThan( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gfirst-index-greater-than]: return the index of the first element in a strided array which is greater than a corresponding element in another strided array. +- [`gfirstIndexLessThan( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gfirst-index-less-than]: return the index of the first element in a strided array which is less than a corresponding element in another strided array. +- [`gfirstIndexNotEqual( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gfirst-index-not-equal]: return the index of the first element in a strided array which is not equal to the corresponding element in another strided array. - [`gindexOfColumn( order, M, N, A, LDA, x, strideX )`][@stdlib/blas/ext/base/gindex-of-column]: return the index of the first column in an input matrix which has the same elements as a provided search vector. - [`gindexOfFalsy( N, x, strideX )`][@stdlib/blas/ext/base/gindex-of-falsy]: return the index of the first falsy element in a strided array. +- [`gindexOfNotEqual( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/gindex-of-not-equal]: return the first index of an element in a strided array which is not equal to a specified search element. - [`gindexOfRow( order, M, N, A, LDA, x, strideX )`][@stdlib/blas/ext/base/gindex-of-row]: return the index of the first row in an input matrix which has the same elements as a provided search vector. +- [`gindexOfSameValue( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/gindex-of-same-value]: return the index of the first element in a strided array which has the same value as a provided search element. - [`gindexOfTruthy( N, x, strideX )`][@stdlib/blas/ext/base/gindex-of-truthy]: return the index of the first truthy element in a strided array. - [`gindexOf( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/gindex-of]: return the first index of a specified search element in a strided array. - [`gjoinBetween( N, prefix, suffix, x, strideX, separators, strideS )`][@stdlib/blas/ext/base/gjoin-between]: return a string by joining strided array elements using a specified separator for each pair of consecutive elements. - [`gjoin( N, separator, x, strideX )`][@stdlib/blas/ext/base/gjoin]: return a string created by joining strided array elements using a specified separator. +- [`glastIndexEqual( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/glast-index-equal]: return the index of the last element in a strided array equal to a corresponding element in another strided array. - [`glastIndexOfFalsy( N, x, strideX )`][@stdlib/blas/ext/base/glast-index-of-falsy]: return the index of the last falsy element in a strided array. - [`glastIndexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/glast-index-of-row]: return the index of the last row in an input matrix which has the same elements as a provided search vector. - [`glastIndexOfTruthy( N, x, strideX )`][@stdlib/blas/ext/base/glast-index-of-truthy]: return the index of the last truthy element in a strided array. @@ -238,6 +261,7 @@ var o = ns; - [`gwxpy( N, x, strideX, y, strideY, w, strideW )`][@stdlib/blas/ext/base/gwxpy]: add elements of a strided array `x` to the corresponding elements of a strided array `y` and assign the results to elements in a strided array `w`. - [`gwxsa( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/gwxsa]: subtract a scalar constant from each element in a strided array `x` and assign the results to elements in a strided array `w`. - [`gwxsy( N, x, strideX, y, strideY, w, strideW )`][@stdlib/blas/ext/base/gwxsy]: subtract elements of a strided array `y` from the corresponding elements of a strided array `x` and assign the results to elements in a strided array `w`. +- [`gxdy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gxdy]: divide elements of a strided array `x` by the corresponding elements of a strided array `y` and assign the results to `y`. - [`gxmy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gxmy]: multiply elements of a strided array `x` by the corresponding elements of a strided array `y` and assign the results to `y`. - [`gxpy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/gxpy]: add elements of a strided array `x` to the corresponding elements of a strided array `y` and assign the results to `y`. - [`gxsa( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gxsa]: subtract a scalar constant from each element in a strided array. @@ -275,7 +299,12 @@ var o = ns; - [`sdssum( N, x, strideX )`][@stdlib/blas/ext/base/sdssum]: calculate the sum of single-precision floating-point strided array elements using extended accumulation. - [`sdssumpw( N, x, strideX )`][@stdlib/blas/ext/base/sdssumpw]: calculate the sum of single-precision floating-point strided array elements using pairwise summation with extended accumulation. - [`sediff( N, x, strideX, N1, prepend, strideP, N2, append, strideA, out, strideOut )`][@stdlib/blas/ext/base/sediff]: calculate the differences between consecutive elements of a single-precision floating-point strided array. +- [`sfillEqual( N, searchElement, alpha, x, strideX )`][@stdlib/blas/ext/base/sfill-equal]: replace single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +- [`sfillNaN( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sfill-nan]: replace single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +- [`sfillNotEqual( N, searchElement, alpha, x, strideX )`][@stdlib/blas/ext/base/sfill-not-equal]: replace single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. - [`sfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sfill]: fill a single-precision floating-point strided array with a specified scalar constant. +- [`sfirstIndexEqual( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/sfirst-index-equal]: return the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. +- [`sfirstIndexLessThan( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/sfirst-index-less-than]: return the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. - [`sindexOfColumn( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/sindex-of-column]: return the index of the first column in a single-precision floating-point input matrix which has the same elements as a provided search vector. - [`sindexOfFalsy( N, x, strideX )`][@stdlib/blas/ext/base/sindex-of-falsy]: return the index of the first falsy element in a single-precision floating-point strided array. - [`sindexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/sindex-of-row]: return the index of the first row in a single-precision floating-point input matrix which has the same elements as a provided search vector. @@ -298,6 +327,7 @@ var o = ns; - [`snone( N, x, strideX )`][@stdlib/blas/ext/base/snone]: test whether every element in a single-precision floating-point strided array is falsy. - [`soneTo( N, x, strideX )`][@stdlib/blas/ext/base/sone-to]: fill a single-precision floating-point strided array with linearly spaced numeric elements which increment by `1` starting from one. - [`sones( N, x, strideX )`][@stdlib/blas/ext/base/sones]: fill a single-precision floating-point strided array with ones. +- [`sreplicate( N, k, x, strideX, out, strideOut )`][@stdlib/blas/ext/base/sreplicate]: replicate each single-precision floating-point strided array element a specified number of times. - [`srev( N, x, strideX )`][@stdlib/blas/ext/base/srev]: reverse a single-precision floating-point strided array in-place. - [`ssome( N, k, x, strideX )`][@stdlib/blas/ext/base/ssome]: test whether a single-precision floating-point strided array contains at least `k` truthy elements. - [`ssort( N, order, x, strideX )`][@stdlib/blas/ext/base/ssort]: sort a single-precision floating-point strided array. @@ -315,8 +345,10 @@ var o = ns; - [`sunitspace( N, start, x, strideX )`][@stdlib/blas/ext/base/sunitspace]: fill a single-precision floating-point strided array with linearly spaced numeric elements which increment by `1` starting from a specified value. - [`svander( order, mode, M, N, x, strideX, out, ldo )`][@stdlib/blas/ext/base/svander]: generate a single-precision floating-point Vandermonde matrix. - [`swapx( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/swapx]: add a scalar constant to each element in a single-precision floating-point strided array `x` and assign the results to elements in a single-precision floating-point strided array `w`. +- [`swax( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/swax]: multiply each element in a single-precision floating-point strided array `x` by a scalar constant and assign the results to elements in a single-precision floating-point strided array `w`. - [`swhere( N, condition, strideC, x, strideX, y, strideY, out, strideOut )`][@stdlib/blas/ext/base/swhere]: take elements from one of two single-precision floating-point strided arrays depending on a condition. - [`swxsa( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/swxsa]: subtract a scalar constant from each element in a single-precision floating-point strided array `x` and assign the results to elements in a single-precision floating-point strided array `w`. +- [`sxdy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/sxdy]: divide elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assign the results to `y`. - [`sxmy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/sxmy]: multiply elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assign the results to `y`. - [`sxpy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/sxpy]: add elements of a single-precision floating-point strided array `x` to the corresponding elements of a single-precision floating-point strided array `y` and assign the results to `y`. - [`sxsa( N, alpha, x, strideX )`][@stdlib/blas/ext/base/sxsa]: subtract a scalar constant from each element in a single-precision floating-point strided array. @@ -331,16 +363,21 @@ var o = ns; - [`zfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/zfill]: fill a double-precision complex floating-point strided array with a specified scalar constant. - [`zindexOfColumn( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/zindex-of-column]: return the index of the first column in a double-precision complex floating-point input matrix which has the same elements as a provided search vector. - [`zindexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/zindex-of-row]: return the index of the first row in a double-precision complex floating-point input matrix which has the same elements as a provided search vector. +- [`zindexOfTruthy( N, x, strideX )`][@stdlib/blas/ext/base/zindex-of-truthy]: return the index of the first truthy element in a double-precision complex floating-point strided array. - [`zindexOf( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/zindex-of]: return the first index of a specified search element in a double-precision complex floating-point strided array. - [`zlastIndexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/zlast-index-of-row]: return the index of the last row in a double-precision complex floating-point input matrix which has the same elements as a provided search vector. - [`znancount( N, x, strideX )`][@stdlib/blas/ext/base/znancount]: calculate the number of non-`NaN` elements in a double-precision complex floating-point strided array. - [`zoneTo( N, x, strideX )`][@stdlib/blas/ext/base/zone-to]: fill a double-precision complex floating-point strided array with linearly spaced numeric elements which increment by `1` starting from one. +- [`zreplicate( N, k, x, strideX, out, strideOut )`][@stdlib/blas/ext/base/zreplicate]: replicate each element in a double-precision complex floating-point strided array a specified number of times. - [`zsum( N, x, strideX )`][@stdlib/blas/ext/base/zsum]: calculate the sum of double-precision complex floating-point strided array elements. - [`zsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/zsumkbn]: calculate the sum of double-precision complex floating-point strided array elements using an improved Kahan–Babuška algorithm. - [`zunitspace( N, start, x, strideX )`][@stdlib/blas/ext/base/zunitspace]: fill a double-precision complex floating-point strided array with linearly spaced numeric elements which increment by `1` starting from a specified value. - [`zwapx( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/zwapx]: add a scalar constant to each element in a double-precision complex floating-point strided array `x` and assign the results to elements in a double-precision complex floating-point strided array `w`. +- [`zwax( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/zwax]: multiply each element in a double-precision complex floating-point strided array `x` by a scalar constant and assign the results to elements in a double-precision complex floating-point strided array `w`. - [`zwhere( N, condition, strideC, x, strideX, y, strideY, out, strideOut )`][@stdlib/blas/ext/base/zwhere]: take elements from one of two double-precision complex floating-point strided arrays depending on a condition. - [`zwxsa( N, alpha, x, strideX, w, strideW )`][@stdlib/blas/ext/base/zwxsa]: subtract a scalar constant from each element in a double-precision complex floating-point strided array `x` and assign the results to elements in a double-precision complex floating-point strided array `w`. +- [`zxdy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/zxdy]: divide elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assign the results to `y`. +- [`zxmy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/zxmy]: multiply elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assign the results to `y`. - [`zxpy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/zxpy]: add elements of a double-precision complex floating-point strided array `x` to the corresponding elements of a double-precision complex floating-point strided array `y` and assign the results to `y`. - [`zxsa( N, alpha, x, strideX )`][@stdlib/blas/ext/base/zxsa]: subtract a scalar constant from each element in a double-precision complex floating-point strided array. - [`zxsy( N, x, strideX, y, strideY )`][@stdlib/blas/ext/base/zxsy]: subtract elements of a double-precision complex floating-point strided array `y` from the corresponding elements of a double-precision complex floating-point strided array `x` and assign the results to `y`. @@ -415,6 +452,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/cone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cone-to +[@stdlib/blas/ext/base/creplicate]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/creplicate + [@stdlib/blas/ext/base/csum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/csum [@stdlib/blas/ext/base/csumkbn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/csumkbn @@ -423,10 +462,14 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/cwapx]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cwapx +[@stdlib/blas/ext/base/cwax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cwax + [@stdlib/blas/ext/base/cwhere]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cwhere [@stdlib/blas/ext/base/cwxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cwxsa +[@stdlib/blas/ext/base/cxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cxmy + [@stdlib/blas/ext/base/cxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cxpy [@stdlib/blas/ext/base/cxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/cxsa @@ -485,12 +528,24 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/dediff]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dediff +[@stdlib/blas/ext/base/dfill-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfill-equal + +[@stdlib/blas/ext/base/dfill-nan]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfill-nan + +[@stdlib/blas/ext/base/dfill-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfill-not-equal + [@stdlib/blas/ext/base/dfill]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfill +[@stdlib/blas/ext/base/dfirst-index-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfirst-index-equal + +[@stdlib/blas/ext/base/dfirst-index-less-than]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfirst-index-less-than + [@stdlib/blas/ext/base/dindex-of-column]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dindex-of-column [@stdlib/blas/ext/base/dindex-of-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dindex-of-falsy +[@stdlib/blas/ext/base/dindex-of-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dindex-of-not-equal + [@stdlib/blas/ext/base/dindex-of-row]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dindex-of-row [@stdlib/blas/ext/base/dindex-of-truthy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dindex-of-truthy @@ -547,6 +602,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/dones]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dones +[@stdlib/blas/ext/base/dreplicate]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dreplicate + [@stdlib/blas/ext/base/drev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/drev [@stdlib/blas/ext/base/drrss]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/drrss @@ -607,10 +664,14 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/dwapx]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dwapx +[@stdlib/blas/ext/base/dwax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dwax + [@stdlib/blas/ext/base/dwhere]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dwhere [@stdlib/blas/ext/base/dwxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dwxsa +[@stdlib/blas/ext/base/dxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dxdy + [@stdlib/blas/ext/base/dxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dxmy [@stdlib/blas/ext/base/dxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dxpy @@ -679,18 +740,38 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/gfill-by]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill-by +[@stdlib/blas/ext/base/gfill-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill-equal + +[@stdlib/blas/ext/base/gfill-less-than]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill-less-than + +[@stdlib/blas/ext/base/gfill-nan]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill-nan + +[@stdlib/blas/ext/base/gfill-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill-not-equal + [@stdlib/blas/ext/base/gfill]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill [@stdlib/blas/ext/base/gfind-index]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfind-index [@stdlib/blas/ext/base/gfind-last-index]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfind-last-index +[@stdlib/blas/ext/base/gfirst-index-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfirst-index-equal + +[@stdlib/blas/ext/base/gfirst-index-greater-than]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfirst-index-greater-than + +[@stdlib/blas/ext/base/gfirst-index-less-than]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfirst-index-less-than + +[@stdlib/blas/ext/base/gfirst-index-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfirst-index-not-equal + [@stdlib/blas/ext/base/gindex-of-column]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gindex-of-column [@stdlib/blas/ext/base/gindex-of-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gindex-of-falsy +[@stdlib/blas/ext/base/gindex-of-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gindex-of-not-equal + [@stdlib/blas/ext/base/gindex-of-row]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gindex-of-row +[@stdlib/blas/ext/base/gindex-of-same-value]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gindex-of-same-value + [@stdlib/blas/ext/base/gindex-of-truthy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gindex-of-truthy [@stdlib/blas/ext/base/gindex-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gindex-of @@ -699,6 +780,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/gjoin]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gjoin +[@stdlib/blas/ext/base/glast-index-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/glast-index-equal + [@stdlib/blas/ext/base/glast-index-of-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/glast-index-of-falsy [@stdlib/blas/ext/base/glast-index-of-row]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/glast-index-of-row @@ -785,6 +868,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/gwxsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gwxsy +[@stdlib/blas/ext/base/gxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gxdy + [@stdlib/blas/ext/base/gxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gxmy [@stdlib/blas/ext/base/gxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gxpy @@ -859,8 +944,18 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/sediff]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sediff +[@stdlib/blas/ext/base/sfill-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sfill-equal + +[@stdlib/blas/ext/base/sfill-nan]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sfill-nan + +[@stdlib/blas/ext/base/sfill-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sfill-not-equal + [@stdlib/blas/ext/base/sfill]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sfill +[@stdlib/blas/ext/base/sfirst-index-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sfirst-index-equal + +[@stdlib/blas/ext/base/sfirst-index-less-than]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sfirst-index-less-than + [@stdlib/blas/ext/base/sindex-of-column]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sindex-of-column [@stdlib/blas/ext/base/sindex-of-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sindex-of-falsy @@ -905,6 +1000,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/sones]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sones +[@stdlib/blas/ext/base/sreplicate]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sreplicate + [@stdlib/blas/ext/base/srev]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/srev [@stdlib/blas/ext/base/ssome]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ssome @@ -939,10 +1036,14 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/swapx]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/swapx +[@stdlib/blas/ext/base/swax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/swax + [@stdlib/blas/ext/base/swhere]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/swhere [@stdlib/blas/ext/base/swxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/swxsa +[@stdlib/blas/ext/base/sxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sxdy + [@stdlib/blas/ext/base/sxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sxmy [@stdlib/blas/ext/base/sxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sxpy @@ -971,6 +1072,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/zindex-of-row]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zindex-of-row +[@stdlib/blas/ext/base/zindex-of-truthy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zindex-of-truthy + [@stdlib/blas/ext/base/zindex-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zindex-of [@stdlib/blas/ext/base/zlast-index-of-row]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zlast-index-of-row @@ -979,6 +1082,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/zone-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zone-to +[@stdlib/blas/ext/base/zreplicate]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zreplicate + [@stdlib/blas/ext/base/zsum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zsum [@stdlib/blas/ext/base/zsumkbn]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zsumkbn @@ -987,10 +1092,16 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/zwapx]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zwapx +[@stdlib/blas/ext/base/zwax]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zwax + [@stdlib/blas/ext/base/zwhere]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zwhere [@stdlib/blas/ext/base/zwxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zwxsa +[@stdlib/blas/ext/base/zxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zxdy + +[@stdlib/blas/ext/base/zxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zxmy + [@stdlib/blas/ext/base/zxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zxpy [@stdlib/blas/ext/base/zxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/zxsa diff --git a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.js b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.js index 25e74c89a92c..4eaa52ffbdff 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.js @@ -82,7 +82,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.native.js b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.native.js index 6f15c71f970e..9dce9436b253 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.cindex_of.native.js @@ -91,7 +91,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.js index 2ab40706a516..8ee27573db63 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.js @@ -82,7 +82,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.native.js index 9c5a1bd2c013..341e3cd9da8f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/cindex-of/test/test.ndarray.native.js @@ -91,7 +91,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/README.md b/lib/node_modules/@stdlib/blas/ext/base/creplicate/README.md new file mode 100644 index 000000000000..6238b1f67486 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/README.md @@ -0,0 +1,327 @@ + + +# creplicate + +> Replicate each element in a single-precision complex floating-point strided array a specified number of times. + +
+ +
+ + + +
+ +## Usage + +```javascript +var creplicate = require( '@stdlib/blas/ext/base/creplicate' ); +``` + +#### creplicate( N, k, x, strideX, out, strideOut ) + +Replicates each element in a single-precision complex floating-point strided array a specified number of times. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var out = new Complex64Array( 4 ); + +creplicate( x.length, 2, x, 1, out, 1 ); +// out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **k**: number of times to replicate each element. +- **x**: input [`Complex64Array`][@stdlib/array/complex64]. +- **strideX**: stride length for `x`. +- **out**: output [`Complex64Array`][@stdlib/array/complex64]. +- **strideOut**: stride length for `out`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to replicate every other element: + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out = new Complex64Array( 4 ); + +creplicate( 2, 2, x, 2, out, 1 ); +// out => [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +// Initial arrays... +var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out0 = new Complex64Array( 3 ); + +// Create offset views... +var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Complex64Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +creplicate( 1, 2, x1, 2, out1, 1 ); +// out0 => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0 ] +``` + +#### creplicate.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + +Replicates each element in a single-precision complex floating-point strided array a specified number of times using alternative indexing semantics. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var out = new Complex64Array( 4 ); + +creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +// out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetOut**: starting index for `out`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to replicate every element starting from the second element and to store in the last `N*k` elements of the output array starting from the last element: + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var out = new Complex64Array( 2 ); + +creplicate.ndarray( 1, 2, x, 1, 1, out, 1, 0 ); +// out => [ 3.0, 4.0, 3.0, 4.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0` or `k <= 0`, both functions return `out` unchanged. +- Both functions assume that the output array supports `N*k` indexed elements. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var creplicate = require( '@stdlib/blas/ext/base/creplicate' ); + +var xbuf = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +var x = new Complex64Array( xbuf.buffer ); +console.log( x ); + +var out = new Complex64Array( x.length * 5 ); +console.log( out ); + +creplicate( x.length, 5, x, 1, out, 1 ); +console.log( out ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/creplicate.h" +``` + +#### stdlib_strided_creplicate( N, k, \*X, strideX, \*Out, strideOut ) + +Replicates each element in a single-precision complex floating-point strided array a specified number of times. + +```c +#include "stdlib/complex/float32/ctor.h" + +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_creplicate( 2, 2, (stdlib_complex64_t *)x, 1, (stdlib_complex64_t *)out, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] stdlib_complex64_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Out**: `[out] stdlib_complex64_t*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. + +```c +void stdlib_strided_creplicate( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex64_t *X, const CBLAS_INT strideX, stdlib_complex64_t *Out, const CBLAS_INT strideOut ); +``` + + + +#### stdlib_strided_creplicate_ndarray( N, k, \*X, strideX, offsetX, \*Out, strideOut, offsetOut ) + + + +Replicates each element in a single-precision complex floating-point strided array a specified number of times using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_creplicate_ndarray( 2, 2, (stdlib_complex64_t *)x, 1, 0, (stdlib_complex64_t *)out, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] stdlib_complex64_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Out**: `[out] stdlib_complex64_t*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. +- **offsetOut**: `[in] CBLAS_INT` starting index for `Out`. + +```c +void stdlib_strided_creplicate_ndarray( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex64_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex64_t *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/creplicate.h" +#include "stdlib/complex/float32/ctor.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of indexed elements: + const int N = 2; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify strides: + const int strideX = 1; + const int strideOut = 1; + + // Replicate each element: + stdlib_strided_creplicate( N, k, (stdlib_complex64_t *)x, strideX, (stdlib_complex64_t *)out, strideOut ); + + // Print the results: + for ( int i = 0; i < 8; i++ ) { + printf( "out[ %i ] = %f\n", i, out[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.js new file mode 100644 index 000000000000..6aa6748672c4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var creplicate = require( './../lib/creplicate.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float32Array( len * 4 ); + x = new Complex64Array( xbuf.buffer ); + out = new Complex64Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + creplicate( x.length, 2, x, 1, out, 1 ); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.native.js new file mode 100644 index 000000000000..d9e567b5ef9c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.native.js @@ -0,0 +1,119 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var creplicate = tryRequire( resolve( __dirname, './../lib/creplicate.native.js' ) ); +var opts = { + 'skip': ( creplicate instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float32Array( len * 4 ); + x = new Complex64Array( xbuf.buffer ); + out = new Complex64Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + creplicate( x.length, 2, x, 1, out, 1 ); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..84b236ca7d8a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.ndarray.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var creplicate = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float32Array( len * 4 ); + x = new Complex64Array( xbuf.buffer ); + out = new Complex64Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + creplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..61d69509cbf6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,119 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float32Array = require( '@stdlib/array/float32' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var creplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( creplicate instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float32Array( len * 4 ); + x = new Complex64Array( xbuf.buffer ); + out = new Complex64Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + creplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..1f664aac213f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/benchmark/c/benchmark.length.c @@ -0,0 +1,206 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/creplicate.h" +#include "stdlib/complex/float32/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "creplicate" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length (number of complex elements) +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *out; + float *x; + double t; + int i; + + x = (float *) malloc( len * 2 * sizeof( float ) ); + out = (float *) malloc( len * 4 * sizeof( float ) ); + for ( i = 0; i < len * 2; i++ ) { + x[ i ] = ( rand_float()*99.0f ) + 1.0f; + } + for ( i = 0; i < len * 4; i++ ) { + out[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_creplicate( len, 2, (stdlib_complex64_t *)x, 1, (stdlib_complex64_t *)out, 1 ); + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length (number of complex elements) +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *out; + float *x; + double t; + int i; + + x = (float *) malloc( len * 2 * sizeof( float ) ); + out = (float *) malloc( len * 4 * sizeof( float ) ); + for ( i = 0; i < len * 2; i++ ) { + x[ i ] = ( rand_float()*99.0f ) + 1.0f; + } + for ( i = 0; i < len * 4; i++ ) { + out[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_creplicate_ndarray( len, 2, (stdlib_complex64_t *)x, 1, 0, (stdlib_complex64_t *)out, 1, 0 ); + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/creplicate/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/repl.txt new file mode 100644 index 000000000000..d65688b256e3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/repl.txt @@ -0,0 +1,118 @@ + +{{alias}}( N, k, x, strideX, out, strideOut ) + Replicates each element in a single-precision complex floating-point strided + array a specified number of times. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0` or `k <= 0`, the function returns `out` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Complex64Array + Input array. + + strideX: integer + Stride length for `x`. + + out: Complex64Array + Output array. + + strideOut: integer + Stride length for `out`. + + Returns + ------- + out: Complex64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var out = new {{alias:@stdlib/array/complex64}}( 4 ); + > {{alias}}( x.length, 2, x, 1, out, 1 ) + [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > out = new {{alias:@stdlib/array/complex64}}( 4 ); + > {{alias}}( 2, 2, x, 2, out, 1 ) + [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var out0 = new {{alias:@stdlib/array/complex64}}( 3 ); + > var x1 = new {{alias:@stdlib/array/complex64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var out1 = new {{alias:@stdlib/array/complex64}}( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 1, 2, x1, 2, out1, 1 ) + [ 3.0, 4.0, 3.0, 4.0 ] + > out0 + [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0 ] + + +{{alias}}.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + Replicates each element in a single-precision complex floating-point strided + array a specified number of times using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Complex64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + out: Complex64Array + Output array. + + strideOut: integer + Stride length for `out`. + + offsetOut: integer + Starting index for `out`. + + Returns + ------- + out: Complex64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var out = new {{alias:@stdlib/array/complex64}}( 4 ); + > {{alias}}.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ) + [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] + + // Advanced indexing: + > x = new {{alias:@stdlib/array/complex64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > out = new {{alias:@stdlib/array/complex64}}( 2 ); + > {{alias}}.ndarray( 1, 2, x, 1, 1, out, 1, 0 ) + [ 3.0, 4.0, 3.0, 4.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/types/index.d.ts new file mode 100644 index 000000000000..25bd9de1f9eb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/types/index.d.ts @@ -0,0 +1,110 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/// + +// TypeScript Version: 4.1 + +import { Complex64Array } from '@stdlib/types/array'; + +/** +* Interface describing `creplicate`. +*/ +interface Routine { + /** + * Replicates each element in a single-precision complex floating-point strided array a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex64Array( 6 ); + * + * creplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + */ + ( N: number, k: number, x: Complex64Array, strideX: number, out: Complex64Array, strideOut: number ): Complex64Array; + + /** + * Replicates each element in a single-precision complex floating-point strided array a specified number of times using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` + * @returns output array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex64Array( 6 ); + * + * creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + */ + ndarray( N: number, k: number, x: Complex64Array, strideX: number, offsetX: number, out: Complex64Array, strideOut: number, offsetOut: number ): Complex64Array; +} + +/** +* Replicates each element in a single-precision complex floating-point strided array a specified number of times. +* +* @param N - number of indexed elements +* @param k - number of times to replicate each element +* @param x - input array +* @param strideX - stride length for `x` +* @param out - output array +* @param strideOut - stride length for `out` +* @returns output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex64Array( 6 ); +* +* creplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex64Array( 6 ); +* +* creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +declare var creplicate: Routine; + + +// EXPORTS // + +export = creplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/types/test.ts new file mode 100644 index 000000000000..2b3cd2bb5ed0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/docs/types/test.ts @@ -0,0 +1,281 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex64Array = require( '@stdlib/array/complex64' ); +import creplicate = require( './index' ); + + +// TESTS // + +// The function returns a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate( x.length, 2, x, 1, out, 1 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate( '10', 2, x, 1, out, 1 ); // $ExpectError + creplicate( true, 2, x, 1, out, 1 ); // $ExpectError + creplicate( false, 2, x, 1, out, 1 ); // $ExpectError + creplicate( null, 2, x, 1, out, 1 ); // $ExpectError + creplicate( undefined, 2, x, 1, out, 1 ); // $ExpectError + creplicate( [], 2, x, 1, out, 1 ); // $ExpectError + creplicate( {}, 2, x, 1, out, 1 ); // $ExpectError + creplicate( ( x: number ): number => x, 2, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate( x.length, '10', x, 1, out, 1 ); // $ExpectError + creplicate( x.length, true, x, 1, out, 1 ); // $ExpectError + creplicate( x.length, false, x, 1, out, 1 ); // $ExpectError + creplicate( x.length, null, x, 1, out, 1 ); // $ExpectError + creplicate( x.length, undefined, x, 1, out, 1 ); // $ExpectError + creplicate( x.length, [], x, 1, out, 1 ); // $ExpectError + creplicate( x.length, {}, x, 1, out, 1 ); // $ExpectError + creplicate( x.length, ( x: number ): number => x, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate( x.length, 2, 10, 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, '10', 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, true, 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, false, 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, null, 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, undefined, 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, [ '1' ], 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, {}, 1, out, 1 ); // $ExpectError + creplicate( x.length, 2, ( x: number ): number => x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate( x.length, 2, x, '10', out, 1 ); // $ExpectError + creplicate( x.length, 2, x, true, out, 1 ); // $ExpectError + creplicate( x.length, 2, x, false, out, 1 ); // $ExpectError + creplicate( x.length, 2, x, null, out, 1 ); // $ExpectError + creplicate( x.length, 2, x, undefined, out, 1 ); // $ExpectError + creplicate( x.length, 2, x, [], out, 1 ); // $ExpectError + creplicate( x.length, 2, x, {}, out, 1 ); // $ExpectError + creplicate( x.length, 2, x, ( x: number ): number => x, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + + creplicate( x.length, 2, x, 1, 10, 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, '10', 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, true, 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, false, 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, null, 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, undefined, 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, [ '1' ], 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, {}, 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate( x.length, 2, x, 1, out, '10' ); // $ExpectError + creplicate( x.length, 2, x, 1, out, true ); // $ExpectError + creplicate( x.length, 2, x, 1, out, false ); // $ExpectError + creplicate( x.length, 2, x, 1, out, null ); // $ExpectError + creplicate( x.length, 2, x, 1, out, undefined ); // $ExpectError + creplicate( x.length, 2, x, 1, out, [] ); // $ExpectError + creplicate( x.length, 2, x, 1, out, {} ); // $ExpectError + creplicate( x.length, 2, x, 1, out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate(); // $ExpectError + creplicate( x.length ); // $ExpectError + creplicate( x.length, 2 ); // $ExpectError + creplicate( x.length, 2, x ); // $ExpectError + creplicate( x.length, 2, x, 1 ); // $ExpectError + creplicate( x.length, 2, x, 1, out ); // $ExpectError + creplicate( x.length, 2, x, 1, out, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( '10', 2, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( true, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( false, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( null, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( undefined, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( [], 2, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( {}, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( ( x: number ): number => x, 2, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( x.length, '10', x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, true, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, false, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, null, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, undefined, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, [], x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, {}, x, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, ( x: number ): number => x, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( x.length, 2, 10, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, '10', 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, true, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, false, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, null, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, undefined, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, [ '1' ], 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, {}, 1, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( x.length, 2, x, '10', 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, true, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, false, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, null, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, undefined, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, [], 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, {}, 0, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( x.length, 2, x, 1, '10', out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, true, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, false, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, null, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, undefined, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, [], out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, {}, out, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + + creplicate.ndarray( x.length, 2, x, 1, 0, 10, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, '10', 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, true, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, false, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, null, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, undefined, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, {}, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( x.length, 2, x, 1, 0, out, '10', 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, true, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, false, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, null, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, undefined, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, [], 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, {}, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, '10' ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, true ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, false ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, null ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, undefined ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, [] ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, {} ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Complex64Array( 10 ); + const out = new Complex64Array( 20 ); + + creplicate.ndarray(); // $ExpectError + creplicate.ndarray( x.length ); // $ExpectError + creplicate.ndarray( x.length, 2 ); // $ExpectError + creplicate.ndarray( x.length, 2, x ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1 ); // $ExpectError + creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/c/example.c new file mode 100644 index 000000000000..de5195e8b32d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/c/example.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/creplicate.h" +#include "stdlib/complex/float32/ctor.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; + float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of indexed elements: + const int N = 2; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify strides: + const int strideX = 1; + const int strideOut = 1; + + // Replicate each element: + stdlib_strided_creplicate( N, k, (stdlib_complex64_t *)x, strideX, (stdlib_complex64_t *)out, strideOut ); + + // Print the results: + for ( int i = 0; i < 8; i++ ) { + printf( "out[ %i ] = %f\n", i, out[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/index.js new file mode 100644 index 000000000000..4366db3b08ff --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var creplicate = require( './../lib' ); + +var xbuf = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +var x = new Complex64Array( xbuf.buffer ); +console.log( x ); + +var out = new Complex64Array( x.length * 5 ); +console.log( out ); + +creplicate( x.length, 5, x, 1, out, 1 ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/creplicate/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function creplicate( N, k, x, strideX, out, strideOut ) { + var ox = stride2offset( N, strideX ); + var oo = stride2offset( N * k, strideOut ); + return ndarray( N, k, x, strideX, ox, out, strideOut, oo ); +} + + +// EXPORTS // + +module.exports = creplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/creplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/creplicate.native.js new file mode 100644 index 000000000000..f233a058189e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/creplicate.native.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each element in a single-precision complex floating-point strided array a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Complex64Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {Complex64Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex64Array( 6 ); +* +* creplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function creplicate( N, k, x, strideX, out, strideOut ) { + var viewOut; + var viewX; + + viewX = reinterpret( x, 0 ); + viewOut = reinterpret( out, 0 ); + addon( N, k, viewX, strideX, viewOut, strideOut ); + return out; +} + + +// EXPORTS // + +module.exports = creplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/index.js new file mode 100644 index 000000000000..e4b688c3419c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/index.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replicate each element in a single-precision complex floating-point strided array a specified number of times. +* +* @module @stdlib/blas/ext/base/creplicate +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var creplicate = require( '@stdlib/blas/ext/base/creplicate' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex64Array( 6 ); +* +* creplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var creplicate = require( '@stdlib/blas/ext/base/creplicate' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex64Array( 6 ); +* +* creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var creplicate; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + creplicate = main; +} else { + creplicate = tmp; +} + + +// EXPORTS // + +module.exports = creplicate; + +// exports: { "ndarray": "creplicate.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/main.js new file mode 100644 index 000000000000..af3ffb36e18e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var creplicate = require( './creplicate.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( creplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = creplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/native.js new file mode 100644 index 000000000000..bc58eaa44c07 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var creplicate = require( './creplicate.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( creplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = creplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/ndarray.js new file mode 100644 index 000000000000..ce1b37a1ad5b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/ndarray.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); + + +// MAIN // + +/** +* Replicates each element in a single-precision complex floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Complex64Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Complex64Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex64Array( 6 ); +* +* creplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function creplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var viewX; + var viewO; + var re; + var im; + var ix; + var io; + var i; + var j; + + if ( N <= 0 || k <= 0 ) { + return out; + } + viewX = reinterpret( x, 0 ); + viewO = reinterpret( out, 0 ); + ix = offsetX * 2; + io = offsetOut * 2; + strideX *= 2; + strideOut *= 2; + for ( i = 0; i < N; i++ ) { + re = viewX[ ix ]; + im = viewX[ ix+1 ]; + for ( j = 0; j < k; j++ ) { + viewO[ io ] = re; + viewO[ io+1 ] = im; + io += strideOut; + } + ix += strideX; + } + return out; +} + + +// EXPORTS // + +module.exports = creplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/ndarray.native.js new file mode 100644 index 000000000000..597dedacc3f0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/lib/ndarray.native.js @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each element in a single-precision complex floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Complex64Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Complex64Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex64Array( 6 ); +* +* creplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function creplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var viewOut; + var viewX; + + viewX = reinterpret( x, 0 ); + viewOut = reinterpret( out, 0 ); + addon.ndarray( N, k, viewX, strideX, offsetX, viewOut, strideOut, offsetOut ); + return out; +} + + +// EXPORTS // + +module.exports = creplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/creplicate/manifest.json new file mode 100644 index 000000000000..a659b6360e05 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/manifest.json @@ -0,0 +1,81 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-complex64array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/package.json b/lib/node_modules/@stdlib/blas/ext/base/creplicate/package.json new file mode 100644 index 000000000000..28abc3507129 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/package.json @@ -0,0 +1,77 @@ +{ + "name": "@stdlib/blas/ext/base/creplicate", + "version": "0.0.0", + "description": "Replicate each element in a single-precision complex floating-point strided array a specified number of times.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "replicate", + "repeat", + "copy", + "strided", + "array", + "ndarray", + "complex", + "complex64", + "complex64array", + "single-precision", + "creplicate" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/addon.c new file mode 100644 index 000000000000..a14c2c9b6ec7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/addon.c @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/creplicate.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, Out, N * k, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_creplicate)( N, k, (stdlib_complex64_t *)X, strideX, (stdlib_complex64_t *)Out, strideOut ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetOut, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, Out, N * k, strideOut, argv, 5 ); + API_SUFFIX(stdlib_strided_creplicate_ndarray)( N, k, (stdlib_complex64_t *)X, strideX, offsetX, (stdlib_complex64_t *)Out, strideOut, offsetOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/main.c new file mode 100644 index 000000000000..ef478e50cf12 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/src/main.c @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/creplicate.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Replicates each element in a single-precision complex floating-point strided array a specified number of times. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param Out output array +* @param strideOut stride length for Out +*/ +void API_SUFFIX(stdlib_strided_creplicate)( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex64_t *X, const CBLAS_INT strideX, stdlib_complex64_t *Out, const CBLAS_INT strideOut ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oo = stdlib_strided_stride2offset( N * k, strideOut ); + API_SUFFIX(stdlib_strided_creplicate_ndarray)( N, k, X, strideX, ox, Out, strideOut, oo ); +} + +/** +* Replicates each element in a single-precision complex floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Out output array +* @param strideOut stride length for Out +* @param offsetOut starting index for Out +*/ +void API_SUFFIX(stdlib_strided_creplicate_ndarray)( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex64_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex64_t *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ) { + stdlib_complex64_t v; + CBLAS_INT ix; + CBLAS_INT io; + CBLAS_INT i; + CBLAS_INT j; + + if ( N <= 0 || k <= 0 ) { + return; + } + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + for ( j = 0; j < k; j++ ) { + Out[ io ] = v; + io += strideOut; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.creplicate.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.creplicate.js new file mode 100644 index 000000000000..981222d602bd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.creplicate.js @@ -0,0 +1,501 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var creplicate = require( './../lib/creplicate.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof creplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( creplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + creplicate( x.length, 2, x, 1, out, 1 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( x.length, 3, x, 1, out, 1 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 3 ); + + creplicate( x.length, 1, x, 1, out, 1 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 5.0, 6.0 ] ); + out = new Complex64Array( 3 ); + + creplicate( 1, 3, x, 1, out, 1 ); + expected = new Complex64Array( [ 5.0, 6.0, 5.0, 6.0, 5.0, 6.0 ] ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + v = creplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( -1, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( 0, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( x.length, -1, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( x.length, 0, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, 2, out, 1 ); + + expected = new Complex64Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, 1, out, 2 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, -2, out, -1 ); + + expected = new Complex64Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, 2, out, -1 ); + + expected = new Complex64Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0 + ]); + out0 = new Complex64Array( 9 ); + + // Create offset views... + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Complex64Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + creplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 3.0, + 4.0, + 3.0, + 4.0, + 7.0, + 8.0, + 7.0, + 8.0, + 11.0, + 12.0, + 11.0, + 12.0 + ]); + + t.strictEqual( isSameComplex64Array( out0, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.creplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.creplicate.native.js new file mode 100644 index 000000000000..85ab17118630 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.creplicate.native.js @@ -0,0 +1,497 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); + + +// VARIABLES // + +var creplicate = tryRequire( resolve( __dirname, './../lib/creplicate.native.js' ) ); +var opts = { + 'skip': ( creplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof creplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( creplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + creplicate( x.length, 2, x, 1, out, 1 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( x.length, 3, x, 1, out, 1 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 3 ); + + creplicate( x.length, 1, x, 1, out, 1 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 5.0, 6.0 ] ); + out = new Complex64Array( 3 ); + + creplicate( 1, 3, x, 1, out, 1 ); + expected = new Complex64Array( [ 5.0, 6.0, 5.0, 6.0, 5.0, 6.0 ] ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + v = creplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( -1, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( 0, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( x.length, -1, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( x.length, 0, x, 1, out, 1 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, 2, out, 1 ); + + expected = new Complex64Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, 1, out, 2 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, -2, out, -1 ); + + expected = new Complex64Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + creplicate( 3, 2, x, 2, out, -1 ); + + expected = new Complex64Array( [ 9.0, 10.0, 9.0, 10.0, 5.0, 6.0, 5.0, 6.0, 1.0, 2.0, 1.0, 2.0 ] ); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0 + ]); + out0 = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + // Create offset views... + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Complex64Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + creplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 7.0, 8.0, 7.0, 8.0, 11.0, 12.0, 11.0, 12.0 ] ); + + t.strictEqual( isSameComplex64Array( out0, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.js new file mode 100644 index 000000000000..790f2915ec92 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var creplicate = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof creplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof creplicate.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var creplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( creplicate, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var creplicate; + var main; + + main = require( './../lib/creplicate.js' ); + + creplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( creplicate, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.ndarray.js new file mode 100644 index 000000000000..097260207283 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.ndarray.js @@ -0,0 +1,542 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var creplicate = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof creplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( creplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + creplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 3 ); + + creplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 5.0, 6.0 ] ); + out = new Complex64Array( 3 ); + + creplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 5.0, + 6.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + v = creplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 5.0, + 6.0, + 5.0, + 6.0, + 9.0, + 10.0, + 9.0, + 10.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 12 ); + + creplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, -2, 4, out, 1, 0 ); + + expected = new Complex64Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 7.0, + 8.0 + ]); + out = new Complex64Array( 8 ); + + creplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0, + 7.0, + 8.0, + 7.0, + 8.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 8 ); + + creplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Complex64Array([ + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Complex64Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.ndarray.native.js new file mode 100644 index 000000000000..7723ed53b811 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/creplicate/test/test.ndarray.native.js @@ -0,0 +1,551 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); + + +// VARIABLES // + +var creplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( creplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof creplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( creplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + creplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 3 ); + + creplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 5.0, 6.0 ] ); + out = new Complex64Array( 3 ); + + creplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex64Array([ + 5.0, + 6.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array( 6 ); + + v = creplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex64Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + creplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + creplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 5.0, + 6.0, + 5.0, + 6.0, + 9.0, + 10.0, + 9.0, + 10.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 12 ); + + creplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, -2, 4, out, 1, 0 ); + + expected = new Complex64Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 7.0, + 8.0 + ]); + out = new Complex64Array( 8 ); + + creplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Complex64Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0, + 7.0, + 8.0, + 7.0, + 8.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 8 ); + + creplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Complex64Array([ + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex64Array( 6 ); + + creplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Complex64Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex64Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/README.md b/lib/node_modules/@stdlib/blas/ext/base/cwax/README.md new file mode 100644 index 000000000000..d6bf9bdee73a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/README.md @@ -0,0 +1,374 @@ + + +# cwax + +> Multiply each element in a single-precision complex floating-point strided array `x` by a scalar constant and assign the results to elements in a single-precision complex floating-point strided array `w`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{w} = \alpha \cdot \mathbf{x} +``` + + + +This API is complementary to the package [`@stdlib/blas/base/cscal`][@stdlib/blas/base/cscal], which performs an in-place update. + +
+ + + +
+ +## Usage + +```javascript +var cwax = require( '@stdlib/blas/ext/base/cwax' ); +``` + +#### cwax( N, alpha, x, strideX, w, strideW ) + +Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w`. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var alpha = new Complex64( 5.0, 3.0 ); + +cwax( x.length, alpha, x, 1, w, 1 ); +// w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **alpha**: scalar constant. +- **x**: input [`Complex64Array`][@stdlib/array/complex64]. +- **strideX**: stride length for `x`. +- **w**: output [`Complex64Array`][@stdlib/array/complex64]. +- **strideW**: stride length for `w`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other element in `x` by `alpha` and assign the results to every other element in `w`: + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +var alpha = new Complex64( 5.0, 3.0 ); + +cwax( 2, alpha, x, 2, w, 2 ); +// w => [ -1.0, 13.0, 0.0, 0.0, 7.0, 45.0, 0.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); + +// Initial arrays... +var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var w0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var w1 = new Complex64Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +var alpha = new Complex64( 5.0, 3.0 ); + +cwax( 3, alpha, x1, 1, w1, 1 ); +// w0 => [ 0.0, 0.0, 0.0, 0.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +``` + +#### cwax.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + +Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w` using alternative indexing semantics. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var alpha = new Complex64( 5.0, 3.0 ); + +cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); +// w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetW**: starting index for `w`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to multiply the last three elements of `x` by `alpha` and assign the results to the last three elements of `w`: + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +var alpha = new Complex64( 5.0, 3.0 ); + +cwax.ndarray( 3, alpha, x, 1, x.length-3, w, 1, w.length-3 ); +// w => [ 0.0, 0.0, 0.0, 0.0, 7.0, 45.0, 11.0, 61.0, 15.0, 77.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `w` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var logEach = require( '@stdlib/console/log-each' ); +var cwax = require( '@stdlib/blas/ext/base/cwax' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var wbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var x = new Complex64Array( xbuf.buffer ); +var w = new Complex64Array( wbuf.buffer ); +var alpha = new Complex64( 5.0, 3.0 ); + +cwax( x.length, alpha, x, 1, w, 1 ); +logEach( '%s', w ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/cwax.h" +``` + +#### stdlib_strided_cwax( N, alpha, \*X, strideX, \*W, strideW ) + +Multiplies each element in a single-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `W`. + +```c +#include "stdlib/complex/float32/ctor.h" + +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; +float w[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; +const stdlib_complex64_t alpha = stdlib_complex64( 5.0f, 3.0f ); + +stdlib_strided_cwax( 4, alpha, (const stdlib_complex64_t *)x, 1, (stdlib_complex64_t *)w, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] stdlib_complex64_t` scalar constant. +- **X**: `[in] stdlib_complex64_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **W**: `[out] stdlib_complex64_t*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. + +```c +void stdlib_strided_cwax( const CBLAS_INT N, const stdlib_complex64_t alpha, const stdlib_complex64_t *X, const CBLAS_INT strideX, stdlib_complex64_t *W, const CBLAS_INT strideW ); +``` + + + +#### stdlib_strided_cwax_ndarray( N, alpha, \*X, strideX, offsetX, \*W, strideW, offsetW ) + + + +Multiplies each element in a single-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `W` using alternative indexing semantics. + +```c +#include "stdlib/complex/float32/ctor.h" + +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; +float w[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; +const stdlib_complex64_t alpha = stdlib_complex64( 5.0f, 3.0f ); + +stdlib_strided_cwax_ndarray( 4, alpha, (const stdlib_complex64_t *)x, 1, 0, (stdlib_complex64_t *)w, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] stdlib_complex64_t` scalar constant. +- **X**: `[in] stdlib_complex64_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **W**: `[out] stdlib_complex64_t*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. +- **offsetW**: `[in] CBLAS_INT` starting index for `W`. + +```c +void stdlib_strided_cwax_ndarray( const CBLAS_INT N, const stdlib_complex64_t alpha, const stdlib_complex64_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex64_t *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/cwax.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex64_t x[] = { + stdlib_complex64( 1.0f, 2.0f ), + stdlib_complex64( 3.0f, 4.0f ), + stdlib_complex64( 5.0f, 6.0f ), + stdlib_complex64( 7.0f, 8.0f ) + }; + stdlib_complex64_t w[] = { + stdlib_complex64( 0.0f, 0.0f ), + stdlib_complex64( 0.0f, 0.0f ), + stdlib_complex64( 0.0f, 0.0f ), + stdlib_complex64( 0.0f, 0.0f ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Define a scalar constant: + stdlib_complex64_t alpha = stdlib_complex64( 5.0f, 3.0f ); + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_cwax( N, alpha, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "w[ %i ] = %f + %fi\n", i, stdlib_complex64_real( w[ i ] ), stdlib_complex64_imag( w[ i ] ) ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64 + +[@stdlib/blas/base/cscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/cscal + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.js new file mode 100644 index 000000000000..45af8a63661e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.js @@ -0,0 +1,116 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cwax = require( './../lib/cwax.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex64Array( xbuf.buffer ); + w = new Complex64Array( wbuf.buffer ); + + alpha = new Complex64( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cwax( x.length, alpha, x, 1, w, 1 ); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.native.js new file mode 100644 index 000000000000..14bbf6740060 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.native.js @@ -0,0 +1,121 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cwax = tryRequire( resolve( __dirname, './../lib/cwax.native.js' ) ); +var opts = { + 'skip': ( cwax instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex64Array( xbuf.buffer ); + w = new Complex64Array( wbuf.buffer ); + + alpha = new Complex64( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cwax( x.length, alpha, x, 1, w, 1 ); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..f8e355375d55 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.ndarray.js @@ -0,0 +1,116 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cwax = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex64Array( xbuf.buffer ); + w = new Complex64Array( wbuf.buffer ); + + alpha = new Complex64( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..9e1197e7ddf3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,121 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cwax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( cwax instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex64Array( xbuf.buffer ); + w = new Complex64Array( wbuf.buffer ); + + alpha = new Complex64( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..c971a0844aea --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/benchmark/c/benchmark.length.c @@ -0,0 +1,214 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cwax.h" +#include "stdlib/complex/float32/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "cwax" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static float random_uniform( const float min, const float max ) { + float v = (float)rand() / ( (float)RAND_MAX + 1.0f ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + stdlib_complex64_t alpha; + double elapsed; + double t; + float *x; + float *w; + int i; + + x = (float *)malloc( len * 2 * sizeof( float ) ); + w = (float *)malloc( len * 2 * sizeof( float ) ); + + alpha = stdlib_complex64( 5.0f, 3.0f ); + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -100.0f, 100.0f ); + w[ i ] = random_uniform( -100.0f, 100.0f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_cwax( len, alpha, (const stdlib_complex64_t *)x, 1, (stdlib_complex64_t *)w, 1 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + stdlib_complex64_t alpha; + double elapsed; + double t; + float *x; + float *w; + int i; + + x = (float *)malloc( len * 2 * sizeof( float ) ); + w = (float *)malloc( len * 2 * sizeof( float ) ); + + alpha = stdlib_complex64( 5.0f, 3.0f ); + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -100.0f, 100.0f ); + w[ i ] = random_uniform( -100.0f, 100.0f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_cwax_ndarray( len, alpha, (const stdlib_complex64_t *)x, 1, 0, (stdlib_complex64_t *)w, 1, 0 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/cwax/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/repl.txt new file mode 100644 index 000000000000..20c3ce378d9f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/repl.txt @@ -0,0 +1,138 @@ + +{{alias}}( N, alpha, x, strideX, w, strideW ) + Multiplies each element in a single-precision complex floating-point strided + array `x` by a scalar constant and assigns the results to elements in a + single-precision complex floating-point strided array `w`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `w` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: Complex64 + Scalar constant. + + x: Complex64Array + Input array. + + strideX: integer + Stride length for `x`. + + w: Complex64Array + Output array. + + strideW: integer + Stride length for `w`. + + Returns + ------- + w: Complex64Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/complex64}}( bufX ); + > var w = new {{alias:@stdlib/array/complex64}}( bufW ); + > var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 5.0, 3.0 ); + > {{alias}}( x.length, alpha, x, 1, w, 1 ) + [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] + + // Using `N` and stride parameters: + > bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]; + > x = new {{alias:@stdlib/array/complex64}}( bufX ); + > bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > w = new {{alias:@stdlib/array/complex64}}( bufW ); + > alpha = new {{alias:@stdlib/complex/float32/ctor}}( 5.0, 3.0 ); + > {{alias}}( 2, alpha, x, 2, w, 2 ) + [ -1.0, 13.0, 0.0, 0.0, 7.0, 45.0, 0.0, 0.0 ] + + // Using view offsets: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x0 = new {{alias:@stdlib/array/complex64}}( bufX ); + > var w0 = new {{alias:@stdlib/array/complex64}}( bufW ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetW = w0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/complex64}}( x0.buffer, offsetX ); + > var w1 = new {{alias:@stdlib/array/complex64}}( w0.buffer, offsetW ); + > alpha = new {{alias:@stdlib/complex/float32/ctor}}( 5.0, 3.0 ); + > {{alias}}( 3, alpha, x1, 1, w1, 1 ) + [ 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + > w0 + [ 0.0, 0.0, 0.0, 0.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + Multiplies each element in a single-precision complex floating-point strided + array `x` by a scalar constant and assigns the results to elements in a + single-precision complex floating-point strided array `w` using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: Complex64 + Scalar constant. + + x: Complex64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + w: Complex64Array + Output array. + + strideW: integer + Stride length for `w`. + + offsetW: integer + Starting index for `w`. + + Returns + ------- + w: Complex64Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/complex64}}( bufX ); + > var w = new {{alias:@stdlib/array/complex64}}( bufW ); + > var alpha = new {{alias:@stdlib/complex/float32/ctor}}( 5.0, 3.0 ); + > {{alias}}.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ) + [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] + + // Using index offsets: + > bufX = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 4.0, 0.0, 5.0, 0.0 ]; + > x = new {{alias:@stdlib/array/complex64}}( bufX ); + > bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > w = new {{alias:@stdlib/array/complex64}}( bufW ); + > alpha = new {{alias:@stdlib/complex/float32/ctor}}( 2.0, 1.0 ); + > {{alias}}.ndarray( 3, alpha, x, 1, x.length-3, w, 1, w.length-3 ) + [ 0.0, 0.0, 0.0, 0.0, 6.0, 3.0, 8.0, 4.0, 10.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/types/index.d.ts new file mode 100644 index 000000000000..7f6ec1758966 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/types/index.d.ts @@ -0,0 +1,123 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex64Array } from '@stdlib/types/array'; +import { Complex64 } from '@stdlib/types/complex'; + +/** +* Interface describing `cwax`. +*/ +interface Routine { + /** + * Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w`. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32/ctor' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex64( 5.0, 3.0 ); + * + * cwax( x.length, alpha, x, 1, w, 1 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + */ + ( N: number, alpha: Complex64, x: Complex64Array, strideX: number, w: Complex64Array, strideW: number ): Complex64Array; + + /** + * Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting index for `x` + * @param w - output array + * @param strideW - `w` stride length + * @param offsetW - starting index for `w` + * @returns `w` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32/ctor' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex64( 5.0, 3.0 ); + * + * cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + */ + ndarray( N: number, alpha: Complex64, x: Complex64Array, strideX: number, offsetX: number, w: Complex64Array, strideW: number, offsetW: number ): Complex64Array; +} + +/** +* Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w`. +* +* @param N - number of indexed elements +* @param alpha - scalar constant +* @param x - input array +* @param strideX - `x` stride length +* @param w - output array +* @param strideW - `w` stride length +* @returns `w` +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* var alpha = new Complex64( 5.0, 3.0 ); +* +* cwax( x.length, alpha, x, 1, w, 1 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* var alpha = new Complex64( 5.0, 3.0 ); +* +* cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +*/ +declare var cwax: Routine; + + +// EXPORTS // + +export = cwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/types/test.ts new file mode 100644 index 000000000000..f610e9f180e6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/docs/types/test.ts @@ -0,0 +1,298 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex64Array = require( '@stdlib/array/complex64' ); +import Complex64 = require( '@stdlib/complex/float32/ctor' ); +import cwax = require( './index' ); + + +// TESTS // + +// The function returns a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax( x.length, alpha, x, 1, w, 1 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax( '10', alpha, x, 1, w, 1 ); // $ExpectError + cwax( true, alpha, x, 1, w, 1 ); // $ExpectError + cwax( false, alpha, x, 1, w, 1 ); // $ExpectError + cwax( null, alpha, x, 1, w, 1 ); // $ExpectError + cwax( undefined, alpha, x, 1, w, 1 ); // $ExpectError + cwax( [], alpha, x, 1, w, 1 ); // $ExpectError + cwax( {}, alpha, x, 1, w, 1 ); // $ExpectError + cwax( ( x: number ): number => x, alpha, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a complex-like... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + + cwax( x.length, 10, x, 1, w, 1 ); // $ExpectError + cwax( x.length, '10', x, 1, w, 1 ); // $ExpectError + cwax( x.length, true, x, 1, w, 1 ); // $ExpectError + cwax( x.length, false, x, 1, w, 1 ); // $ExpectError + cwax( x.length, null, x, 1, w, 1 ); // $ExpectError + cwax( x.length, undefined, x, 1, w, 1 ); // $ExpectError + cwax( x.length, [], x, 1, w, 1 ); // $ExpectError + cwax( x.length, {}, x, 1, w, 1 ); // $ExpectError + cwax( x.length, ( x: number ): number => x, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Complex64Array... +{ + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax( 10, alpha, 10, 1, w, 1 ); // $ExpectError + cwax( 10, alpha, '10', 1, w, 1 ); // $ExpectError + cwax( 10, alpha, true, 1, w, 1 ); // $ExpectError + cwax( 10, alpha, false, 1, w, 1 ); // $ExpectError + cwax( 10, alpha, null, 1, w, 1 ); // $ExpectError + cwax( 10, alpha, undefined, 1, w, 1 ); // $ExpectError + cwax( 10, alpha, [ '1' ], 1, w, 1 ); // $ExpectError + cwax( 10, alpha, {}, 1, w, 1 ); // $ExpectError + cwax( 10, alpha, ( x: number ): number => x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax( x.length, alpha, x, '10', w, 1 ); // $ExpectError + cwax( x.length, alpha, x, true, w, 1 ); // $ExpectError + cwax( x.length, alpha, x, false, w, 1 ); // $ExpectError + cwax( x.length, alpha, x, null, w, 1 ); // $ExpectError + cwax( x.length, alpha, x, undefined, w, 1 ); // $ExpectError + cwax( x.length, alpha, x, [], w, 1 ); // $ExpectError + cwax( x.length, alpha, x, {}, w, 1 ); // $ExpectError + cwax( x.length, alpha, x, ( x: number ): number => x, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax( x.length, alpha, x, 1, 10, 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, '10', 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, true, 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, false, 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, null, 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, undefined, 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, [ '1' ], 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, {}, 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax( x.length, alpha, x, 1, w, '10' ); // $ExpectError + cwax( x.length, alpha, x, 1, w, true ); // $ExpectError + cwax( x.length, alpha, x, 1, w, false ); // $ExpectError + cwax( x.length, alpha, x, 1, w, null ); // $ExpectError + cwax( x.length, alpha, x, 1, w, undefined ); // $ExpectError + cwax( x.length, alpha, x, 1, w, [] ); // $ExpectError + cwax( x.length, alpha, x, 1, w, {} ); // $ExpectError + cwax( x.length, alpha, x, 1, w, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax(); // $ExpectError + cwax( x.length ); // $ExpectError + cwax( x.length, alpha ); // $ExpectError + cwax( x.length, alpha, x ); // $ExpectError + cwax( x.length, alpha, x, 1 ); // $ExpectError + cwax( x.length, alpha, x, 1, w ); // $ExpectError + cwax( x.length, alpha, x, 1, w, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( '10', alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( true, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( false, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( null, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( undefined, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( [], alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( {}, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( ( x: number ): number => x, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a complex-like... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + + cwax.ndarray( x.length, 10, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, '10', x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, true, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, false, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, null, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, undefined, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, [], x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, {}, x, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, ( x: number ): number => x, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Complex64Array... +{ + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( 10, alpha, 10, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, '10', 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, true, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, false, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, null, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, undefined, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, [ '1' ], 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, {}, 1, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( 10, alpha, ( x: number ): number => x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( x.length, alpha, x, '10', 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, true, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, false, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, null, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, undefined, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, [], 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, {}, 0, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, ( x: number ): number => x, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( x.length, alpha, x, 1, '10', w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, true, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, false, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, null, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, undefined, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, [], w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, {}, w, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, ( x: number ): number => x, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( x.length, alpha, x, 1, 0, 10, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, '10', 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, true, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, false, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, null, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, undefined, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, {}, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( x.length, alpha, x, 1, 0, w, '10', 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, true, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, false, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, null, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, undefined, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, [], 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, {}, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, '10' ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, true ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, false ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, null ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, undefined ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, [] ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, {} ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Complex64Array( 10 ); + const w = new Complex64Array( 10 ); + const alpha = new Complex64( 5.0, 3.0 ); + + cwax.ndarray(); // $ExpectError + cwax.ndarray( x.length ); // $ExpectError + cwax.ndarray( x.length, alpha ); // $ExpectError + cwax.ndarray( x.length, alpha, x ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1 ); // $ExpectError + cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/c/example.c new file mode 100644 index 000000000000..3a1ff9c797d1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/c/example.c @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cwax.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex64_t x[] = { + stdlib_complex64( 1.0f, 2.0f ), + stdlib_complex64( 3.0f, 4.0f ), + stdlib_complex64( 5.0f, 6.0f ), + stdlib_complex64( 7.0f, 8.0f ) + }; + stdlib_complex64_t w[] = { + stdlib_complex64( 0.0f, 0.0f ), + stdlib_complex64( 0.0f, 0.0f ), + stdlib_complex64( 0.0f, 0.0f ), + stdlib_complex64( 0.0f, 0.0f ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Define a scalar constant: + stdlib_complex64_t alpha = stdlib_complex64( 5.0f, 3.0f ); + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_cwax( N, alpha, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "w[ %i ] = %f + %fi\n", i, stdlib_complex64_real( w[ i ] ), stdlib_complex64_imag( w[ i ] ) ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/index.js new file mode 100644 index 000000000000..687048696d31 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var logEach = require( '@stdlib/console/log-each' ); +var cwax = require( './../lib' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var wbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var x = new Complex64Array( xbuf.buffer ); +var w = new Complex64Array( wbuf.buffer ); +var alpha = new Complex64( 5.0, 3.0 ); + +cwax( x.length, alpha, x, 1, w, 1 ); +logEach( '%s', w ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/cwax/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function cwax( N, alpha, x, strideX, w, strideW ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ), w, strideW, stride2offset( N, strideW ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = cwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/cwax.native.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/cwax.native.js new file mode 100644 index 000000000000..09b90f51d4aa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/cwax.native.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64} alpha - scalar constant +* @param {Complex64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex64Array} w - output array +* @param {integer} strideW - `w` stride length +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex64( 5.0, 3.0 ); +* +* cwax( x.length, alpha, x, 1, w, 1 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function cwax( N, alpha, x, strideX, w, strideW ) { + var viewX = reinterpret( x, 0 ); + var viewW = reinterpret( w, 0 ); + addon( N, alpha, viewX, strideX, viewW, strideW ); + return w; +} + + +// EXPORTS // + +module.exports = cwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/index.js new file mode 100644 index 000000000000..3fb65ed7f334 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/index.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply each element in a single-precision complex floating-point strided array `x` by a scalar constant and assign the results to elements in a single-precision complex floating-point strided array `w`. +* +* @module @stdlib/blas/ext/base/cwax +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var cwax = require( '@stdlib/blas/ext/base/cwax' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex64( 2.0, 2.0 ); +* +* cwax( x.length, alpha, x, 1, w, 1 ); +* // w => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0, -2.0, 30.0 ] +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* var cwax = require( '@stdlib/blas/ext/base/cwax' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex64( 2.0, 2.0 ); +* +* cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0, -2.0, 30.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var cwax; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + cwax = main; +} else { + cwax = tmp; +} + + +// EXPORTS // + +module.exports = cwax; + +// exports: { "ndarray": "cwax.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/main.js new file mode 100644 index 000000000000..be559cc128d6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var cwax = require( './cwax.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( cwax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = cwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/native.js new file mode 100644 index 000000000000..04fd20da89fd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var cwax = require( './cwax.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( cwax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = cwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/ndarray.js new file mode 100644 index 000000000000..b34e3ecf566a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/ndarray.js @@ -0,0 +1,133 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var realf = require( '@stdlib/complex/float32/real' ); +var imagf = require( '@stdlib/complex/float32/imag' ); +var ccopy = require( '@stdlib/blas/base/ccopy' ).ndarray; +var cmulf = require( '@stdlib/complex/float32/base/mul' ).assign; + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64} alpha - scalar constant +* @param {Complex64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex64Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex64( 5.0, 3.0 ); +* +* cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function cwax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + var xview; + var wview; + var are; + var aim; + var ix; + var iw; + var sx; + var sw; + var m; + var i; + + if ( N <= 0 ) { + return w; + } + + // Decompose the constant into its real and imaginary components: + are = realf( alpha ); + aim = imagf( alpha ); + + // Fast path: when alpha = 1+0i, delegate to ccopy (w = x) + if ( are === 1.0 && aim === 0.0 ) { + return ccopy( N, x, strideX, offsetX, w, strideW, offsetW ); + } + + // Reinterpret the complex input arrays as real-valued arrays: + xview = reinterpret( x, 0 ); + wview = reinterpret( w, 0 ); + + // Adjust the strides and offsets according to the real-valued arrays: + ix = offsetX * 2; + iw = offsetW * 2; + sx = strideX * 2; + sw = strideW * 2; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideW === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + cmulf( are, aim, xview[ ix ], xview[ ix+1 ], wview, 1, iw ); + ix += sx; + iw += sw; + } + } + if ( N < M ) { + return w; + } + for ( i = m; i < N; i += M ) { + cmulf( are, aim, xview[ ix ], xview[ ix+1 ], wview, 1, iw ); + cmulf( are, aim, xview[ ix+2 ], xview[ ix+3 ], wview, 1, iw+2 ); + cmulf( are, aim, xview[ ix+4 ], xview[ ix+5 ], wview, 1, iw+4 ); + cmulf( are, aim, xview[ ix+6 ], xview[ ix+7 ], wview, 1, iw+6 ); + cmulf( are, aim, xview[ ix+8 ], xview[ ix+9 ], wview, 1, iw+8 ); + ix += M * 2; + iw += M * 2; + } + return w; + } + for ( i = 0; i < N; i++ ) { + cmulf( are, aim, xview[ ix ], xview[ ix+1 ], wview, 1, iw ); + ix += sx; + iw += sw; + } + return w; +} + + +// EXPORTS // + +module.exports = cwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/ndarray.native.js new file mode 100644 index 000000000000..4c87acdf9505 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/lib/ndarray.native.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64} alpha - scalar constant +* @param {Complex64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex64Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var Complex64 = require( '@stdlib/complex/float32/ctor' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex64( 5.0, 3.0 ); +* +* cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function cwax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + var viewX = reinterpret( x, 0 ); + var viewW = reinterpret( w, 0 ); + addon.ndarray( N, alpha, viewX, strideX, offsetX, viewW, strideW, offsetW ); + return w; +} + + +// EXPORTS // + +module.exports = cwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/cwax/manifest.json new file mode 100644 index 000000000000..df4fbe38c349 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/manifest.json @@ -0,0 +1,94 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/base/ccopy", + "@stdlib/complex/float32/base/mul", + "@stdlib/complex/float32/real", + "@stdlib/complex/float32/imag", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-complex64", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-complex64array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/base/ccopy", + "@stdlib/complex/float32/base/mul", + "@stdlib/complex/float32/real", + "@stdlib/complex/float32/imag", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/base/ccopy", + "@stdlib/complex/float32/base/mul", + "@stdlib/complex/float32/real", + "@stdlib/complex/float32/imag", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/package.json b/lib/node_modules/@stdlib/blas/ext/base/cwax/package.json new file mode 100644 index 000000000000..e33579b08638 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/cwax", + "version": "0.0.0", + "description": "Multiply each element in a single-precision complex floating-point strided array `x` by a scalar constant and assign the results to elements in a single-precision complex floating-point strided array `w`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "multiply", + "multiplication", + "scale", + "scaling", + "strided", + "array", + "ndarray", + "cwax", + "complex", + "complex64", + "complex64array", + "float32" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/cwax/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/cwax/src/addon.c new file mode 100644 index 000000000000..08e31ec27f51 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/src/addon.c @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cwax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_complex64.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex64array.h" +#include "stdlib/complex/float32/ctor.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_COMPLEX64( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, W, N, strideW, argv, 4 ); + API_SUFFIX(stdlib_strided_cwax)( N, alpha, (const stdlib_complex64_t *)X, strideX, (stdlib_complex64_t *)W, strideW ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_COMPLEX64( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetW, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, W, N, strideW, argv, 5 ); + API_SUFFIX(stdlib_strided_cwax_ndarray)( N, alpha, (const stdlib_complex64_t *)X, strideX, offsetX, (stdlib_complex64_t *)W, strideW, offsetW ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/cwax/src/main.c new file mode 100644 index 000000000000..e11edba46ac2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/src/main.c @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cwax.h" +#include "stdlib/blas/base/ccopy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include "stdlib/complex/float32/base/mul.h" +#include "stdlib/strided/base/stride2offset.h" + +static const CBLAS_INT M = 5; + +/** +* Multiplies each element in a single-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `W`. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param W output array +* @param strideW stride length for `W` +*/ +void API_SUFFIX(stdlib_strided_cwax)( const CBLAS_INT N, const stdlib_complex64_t alpha, const stdlib_complex64_t *X, const CBLAS_INT strideX, stdlib_complex64_t *W, const CBLAS_INT strideW ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT ow = stdlib_strided_stride2offset( N, strideW ); + API_SUFFIX(stdlib_strided_cwax_ndarray)( N, alpha, X, strideX, ox, W, strideW, ow ); +} + +/** +* Multiplies each element in a single-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `W` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param W output array +* @param strideW stride length for `W` +* @param offsetW starting index for `W` +*/ +void API_SUFFIX(stdlib_strided_cwax_ndarray)( const CBLAS_INT N, const stdlib_complex64_t alpha, const stdlib_complex64_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex64_t *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ) { + CBLAS_INT ix; + CBLAS_INT iw; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + // Fast path: when alpha = 1+0i, delegate to ccopy (w = x) + if ( stdlib_complex64_real( alpha ) == 1.0f && stdlib_complex64_imag( alpha ) == 0.0f ) { + API_SUFFIX(c_ccopy_ndarray)( N, X, strideX, offsetX, W, strideW, offsetW ); + return; + } + ix = offsetX; + iw = offsetW; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideW == 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + W[ iw ] = stdlib_base_complex64_mul( alpha, X[ ix ] ); + ix += strideX; + iw += strideW; + } + } + if ( N < M ) { + return; + } + for ( i = m; i < N; i += M ) { + W[ iw ] = stdlib_base_complex64_mul( alpha, X[ ix ] ); + W[ iw+1 ] = stdlib_base_complex64_mul( alpha, X[ ix+1 ] ); + W[ iw+2 ] = stdlib_base_complex64_mul( alpha, X[ ix+2 ] ); + W[ iw+3 ] = stdlib_base_complex64_mul( alpha, X[ ix+3 ] ); + W[ iw+4 ] = stdlib_base_complex64_mul( alpha, X[ ix+4 ] ); + ix += M; + iw += M; + } + return; + } + for ( i = 0; i < N; i++ ) { + W[ iw ] = stdlib_base_complex64_mul( alpha, X[ ix ] ); + ix += strideX; + iw += strideW; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.cwax.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.cwax.js new file mode 100644 index 000000000000..65c1559ae29f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.cwax.js @@ -0,0 +1,372 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var mul = require( '@stdlib/complex/float32/base/mul' ); +var cwax = require( './../lib/cwax.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( cwax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex64( 3.0, 2.0 ); + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex64Array( x.length ); + out = cwax( x.length, alpha, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + cwax( 0, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + cwax( -4, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 1.0, 0.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex64Array( 3 ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + cwax( 3, alpha, x, 2, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex64Array([ + 0.0, // 0 + 0.0, // 0 + 30.0, + 40.0, + 0.0, // 1 + 0.0, // 1 + 10.0, + 20.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 30.0, + 40.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 10.0, + 20.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 1, w, 2 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex64Array( 5 ); + expected = new Complex64Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + 0.0, + 0.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + 0.0, + 0.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + cwax( 3, alpha, x, -2, w, -2 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var alpha; + var x0; + var w0; + var x1; + var w1; + + alpha = new Complex64( 5.0, 3.0 ); + + x0 = new Complex64Array([ + 1.0, + 2.0, + 3.0, // 0 + 4.0, // 0 + 5.0, // 1 + 6.0, // 1 + 7.0, // 2 + 8.0, // 2 + 9.0, + 10.0 + ]); + w0 = new Complex64Array([ + 10.0, + 11.0, + 12.0, + 13.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Complex64Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex64Array([ + 10.0, + 11.0, + 12.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (7.0+8.0i) + 11.0, + 61.0 + ]); + + cwax( 3, alpha, x1, 1, w1, 1 ); + t.strictEqual( isSameComplex64Array( w0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array( 100 ); + w = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + w = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.cwax.native.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.cwax.native.js new file mode 100644 index 000000000000..328d6e6e2dcd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.cwax.native.js @@ -0,0 +1,381 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var mul = require( '@stdlib/complex/float32/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var cwax = tryRequire( resolve( __dirname, './../lib/cwax.native.js' ) ); +var opts = { + 'skip': ( cwax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( cwax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex64( 3.0, 2.0 ); + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex64Array( x.length ); + out = cwax( x.length, alpha, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + cwax( 0, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + cwax( -4, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 1.0, 0.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex64Array( 3 ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + cwax( 3, alpha, x, 2, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex64Array([ + 0.0, // 0 + 0.0, // 0 + 30.0, + 40.0, + 0.0, // 1 + 0.0, // 1 + 10.0, + 20.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 30.0, + 40.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 10.0, + 20.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 1, w, 2 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex64Array( 5 ); + expected = new Complex64Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + 0.0, + 0.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + 0.0, + 0.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + cwax( 3, alpha, x, -2, w, -2 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var alpha; + var x0; + var w0; + var x1; + var w1; + + alpha = new Complex64( 5.0, 3.0 ); + + x0 = new Complex64Array([ + 1.0, + 2.0, + 3.0, // 0 + 4.0, // 0 + 5.0, // 1 + 6.0, // 1 + 7.0, // 2 + 8.0, // 2 + 9.0, + 10.0 + ]); + w0 = new Complex64Array([ + 10.0, + 11.0, + 12.0, + 13.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Complex64Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex64Array([ + 10.0, + 11.0, + 12.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (7.0+8.0i) + 11.0, + 61.0 + ]); + + cwax( 3, alpha, x1, 1, w1, 1 ); + t.strictEqual( isSameComplex64Array( w0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array( 100 ); + w = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + w = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.js new file mode 100644 index 000000000000..a6849f482959 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var cwax = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof cwax.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var cwax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( cwax, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var cwax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( cwax, require( './../lib/main.js' ), 'returns JS implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.ndarray.js new file mode 100644 index 000000000000..e776f087d5f0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.ndarray.js @@ -0,0 +1,462 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var mul = require( '@stdlib/complex/float32/base/mul' ); +var cwax = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( cwax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex64( 3.0, 2.0 ); + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex64Array( x.length ); + out = cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + cwax( 0, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + cwax( -4, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 1.0, 0.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + cwax( 3, alpha, x, 2, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 0.0, + 0.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 0.0, + 0.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 1, 0, w, 2, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + cwax( 3, alpha, x, -2, x.length-1, w, -1, w.length-1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0 // 2 + ]); + w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 2, 1, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + w = new Complex64Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex64Array([ + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 1, 0, w, 1, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0, // 2 + 0.0, + 0.0 + ]); + w = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + expected = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + 0.0, + 0.0 + ]); + + cwax( 3, alpha, x, 2, 1, w, 1, 2 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array( 100 ); + w = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + w = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.ndarray.native.js new file mode 100644 index 000000000000..ce7570eb47d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cwax/test/test.ndarray.native.js @@ -0,0 +1,471 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var mul = require( '@stdlib/complex/float32/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var cwax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( cwax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( cwax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex64( 3.0, 2.0 ); + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex64Array( x.length ); + out = cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + cwax( 0, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + cwax( -4, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 1.0, 0.0 ); + x = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex64Array( x.length ); + expected = new Complex64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + cwax( 3, alpha, x, 2, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 0.0, + 0.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 0.0, + 0.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 1, 0, w, 2, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + expected = new Complex64Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + cwax( 3, alpha, x, -2, x.length-1, w, -1, w.length-1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0 // 2 + ]); + w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex64Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 2, 1, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + w = new Complex64Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex64Array([ + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + cwax( 3, alpha, x, 1, 0, w, 1, 1 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0, // 2 + 0.0, + 0.0 + ]); + w = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + expected = new Complex64Array([ + 0.0, + 0.0, + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + 0.0, + 0.0 + ]); + + cwax( 3, alpha, x, 2, 1, w, 1, 2 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex64( 5.0, 3.0 ); + + x = new Complex64Array( 100 ); + w = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + w = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex64( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + cwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex64Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/README.md b/lib/node_modules/@stdlib/blas/ext/base/cxmy/README.md new file mode 100644 index 000000000000..d2298098f91c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/README.md @@ -0,0 +1,347 @@ + + +# cxmy + +> Multiply elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assign the results to `y`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \odot \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var cxmy = require( '@stdlib/blas/ext/base/cxmy' ); +``` + +#### cxmy( N, x, strideX, y, strideY ) + +Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + +cxmy( x.length, x, 1, y, 1 ); +// y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Complex64Array`][@stdlib/array/complex64]. +- **strideX**: stride length for `x`. +- **y**: output [`Complex64Array`][@stdlib/array/complex64]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other element of `x` by every other element of `y`: + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var y = new Complex64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 ] ); + +cxmy( 2, x, 2, y, 2 ); +// y => [ -9.0, 22.0, 9.0, 10.0, -17.0, 126.0, 13.0, 14.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +// Initial arrays... +var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var y0 = new Complex64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); + +// Create offset views... +var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +cxmy( 3, x1, 1, y1, 1 ); +// y0 => [ 7.0, 8.0, 9.0, 10.0, -15.0, 80.0, -19.0, 148.0, -23.0, 232.0 ] +``` + +#### cxmy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + +cxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to multiply the last three elements of `x` by the last three elements of `y`: + + + +```javascript +var Complex64Array = require( '@stdlib/array/complex64' ); + +var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var y = new Complex64Array( [ 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0 ] ); + +cxmy.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// y => [ 11.0, 12.0, 13.0, 14.0, -21.0, 170.0, -25.0, 262.0, -29.0, 370.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var logEach = require( '@stdlib/console/log-each' ); +var cxmy = require( '@stdlib/blas/ext/base/cxmy' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var ybuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var x = new Complex64Array( xbuf.buffer ); +var y = new Complex64Array( ybuf.buffer ); + +cxmy( x.length, x, 1, y, 1 ); +logEach( '%s', y ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/cxmy.h" +``` + +#### stdlib_strided_cxmy( N, \*X, strideX, \*Y, strideY ) + +Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. + +```c +#include "stdlib/complex/float32/ctor.h" + +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }; +float y[] = { 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f }; + +stdlib_strided_cxmy( 3, (stdlib_complex64_t *)x, 1, (stdlib_complex64_t *)y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex64_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[inout] stdlib_complex64_t*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_cxmy( const CBLAS_INT N, const stdlib_complex64_t *X, const CBLAS_INT strideX, stdlib_complex64_t *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_cxmy_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```c +#include "stdlib/complex/float32/ctor.h" + +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f }; +float y[] = { 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f }; + +stdlib_strided_cxmy_ndarray( 3, (stdlib_complex64_t *)x, 1, 0, (stdlib_complex64_t *)y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex64_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[inout] stdlib_complex64_t*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_cxmy_ndarray( const CBLAS_INT N, const stdlib_complex64_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex64_t *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/cxmy.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex64_t x[] = { + stdlib_complex64( 1.0f, 2.0f ), + stdlib_complex64( 3.0f, 4.0f ), + stdlib_complex64( 5.0f, 6.0f ), + stdlib_complex64( 7.0f, 8.0f ) + }; + stdlib_complex64_t y[] = { + stdlib_complex64( 2.0f, 3.0f ), + stdlib_complex64( 4.0f, 5.0f ), + stdlib_complex64( 6.0f, 7.0f ), + stdlib_complex64( 8.0f, 9.0f ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Multiply `x` by `y` and assign the results to `y`: + stdlib_strided_cxmy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "y[ %i ] = %f + %fi\n", i, stdlib_complex64_real( y[ i ] ), stdlib_complex64_imag( y[ i ] ) ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.js new file mode 100644 index 000000000000..21645ebe0f56 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cxmy = require( './../lib/cxmy.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex64Array( xbuf.buffer ); + y = new Complex64Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cxmy( x.length, x, 1, y, 1 ); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..80992590210e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.native.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cxmy = tryRequire( resolve( __dirname, './../lib/cxmy.native.js' ) ); +var opts = { + 'skip': ( cxmy instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex64Array( xbuf.buffer ); + y = new Complex64Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cxmy( x.length, x, 1, y, 1 ); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..216df00b388b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.ndarray.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cxmy = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex64Array( xbuf.buffer ); + y = new Complex64Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cxmy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..5b59008034f2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cxmy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( cxmy instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex64Array( xbuf.buffer ); + y = new Complex64Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + cxmy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..f9351b652dff --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/benchmark/c/benchmark.length.c @@ -0,0 +1,210 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cxmy.h" +#include "stdlib/complex/float32/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "cxmy" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static float random_uniform( const float min, const float max ) { + float v = (float)rand() / ( (float)RAND_MAX + 1.0f ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double t; + float *x; + float *y; + int i; + + x = (float *)malloc( len * 2 * sizeof( float ) ); + y = (float *)malloc( len * 2 * sizeof( float ) ); + + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -0.5f, 0.5f ); + y[ i ] = random_uniform( -0.5f, 0.5f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_cxmy( len, (stdlib_complex64_t *)x, 1, (stdlib_complex64_t *)y, 1 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double t; + float *x; + float *y; + int i; + + x = (float *)malloc( len * 2 * sizeof( float ) ); + y = (float *)malloc( len * 2 * sizeof( float ) ); + + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -0.5f, 0.5f ); + y[ i ] = random_uniform( -0.5f, 0.5f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_cxmy_ndarray( len, (stdlib_complex64_t *)x, 1, 0, (stdlib_complex64_t *)y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/cxmy/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/repl.txt new file mode 100644 index 000000000000..748d7d7ef7d1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/repl.txt @@ -0,0 +1,127 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Multiplies elements of a single-precision complex floating-point strided + array `x` by the corresponding elements of a single-precision complex + floating-point strided array `y` and assigns the results to `y`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex64Array + Input array. + + strideX: integer + Stride length for `x`. + + y: Complex64Array + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + y: Complex64Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufY = [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + > var x = new {{alias:@stdlib/array/complex64}}( bufX ); + > var y = new {{alias:@stdlib/array/complex64}}( bufY ); + > {{alias}}( x.length, x, 1, y, 1 ) + [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + + // Using `N` and stride parameters: + > bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]; + > x = new {{alias:@stdlib/array/complex64}}( bufX ); + > bufY = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 ]; + > y = new {{alias:@stdlib/array/complex64}}( bufY ); + > {{alias}}( 2, x, 2, y, 2 ) + [ -9.0, 22.0, 9.0, 10.0, -17.0, 126.0, 13.0, 14.0 ] + + // Using view offsets: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]; + > var bufY = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ]; + > var x0 = new {{alias:@stdlib/array/complex64}}( bufX ); + > var y0 = new {{alias:@stdlib/array/complex64}}( bufY ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetY = y0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/complex64}}( x0.buffer, offsetX ); + > var y1 = new {{alias:@stdlib/array/complex64}}( y0.buffer, offsetY ); + > {{alias}}( 3, x1, 1, y1, 1 ) + [ -15.0, 80.0, -19.0, 148.0, -23.0, 232.0 ] + > y0 + [ 7, 8, 9, 10, -15, 80, -19, 148, -23, 232 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Multiplies elements of a single-precision complex floating-point strided + array `x` by the corresponding elements of a single-precision complex + floating-point strided array `y` and assigns the results to `y` using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Complex64Array + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + y: Complex64Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufY = [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + > var x = new {{alias:@stdlib/array/complex64}}( bufX ); + > var y = new {{alias:@stdlib/array/complex64}}( bufY ); + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + + // Using index offsets: + > bufX = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 4.0, 0.0, 5.0, 0.0 ]; + > x = new {{alias:@stdlib/array/complex64}}( bufX ); + > bufY = [ 6.0, 0.0, 7.0, 0.0, 8.0, 0.0, 9.0, 0.0, 10.0, 0.0 ]; + > y = new {{alias:@stdlib/array/complex64}}( bufY ); + > {{alias}}.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ) + [ 6.0, 0.0, 7.0, 0.0, 24.0, 0.0, 36.0, 0.0, 50.0, 0.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/types/index.d.ts new file mode 100644 index 000000000000..ee4a2b943d4b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/types/index.d.ts @@ -0,0 +1,107 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex64Array } from '@stdlib/types/array'; + +/** +* Interface describing `cxmy`. +*/ +interface Routine { + /** + * Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * cxmy( x.length, x, 1, y, 1 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + */ + ( N: number, x: Complex64Array, strideX: number, y: Complex64Array, strideY: number ): Complex64Array; + + /** + * Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting `x` index + * @param y - output array + * @param strideY - `y` stride length + * @param offsetY - starting `y` index + * @returns output array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * cxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + */ + ndarray( N: number, x: Complex64Array, strideX: number, offsetX: number, y: Complex64Array, strideY: number, offsetY: number ): Complex64Array; +} + +/** +* Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - `x` stride length +* @param y - output array +* @param strideY - `y` stride length +* @returns output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* cxmy( x.length, x, 1, y, 1 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* cxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +declare var cxmy: Routine; + + +// EXPORTS // + +export = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/types/test.ts new file mode 100644 index 000000000000..8d45e0d87b12 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/docs/types/test.ts @@ -0,0 +1,247 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex64Array = require( '@stdlib/array/complex64' ); +import cxmy = require( './index' ); + + +// TESTS // + +// The function returns a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy( x.length, x, 1, y, 1 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy( '10', x, 1, y, 1 ); // $ExpectError + cxmy( true, x, 1, y, 1 ); // $ExpectError + cxmy( false, x, 1, y, 1 ); // $ExpectError + cxmy( null, x, 1, y, 1 ); // $ExpectError + cxmy( undefined, x, 1, y, 1 ); // $ExpectError + cxmy( [], x, 1, y, 1 ); // $ExpectError + cxmy( {}, x, 1, y, 1 ); // $ExpectError + cxmy( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex64Array... +{ + const y = new Complex64Array( 10 ); + + cxmy( 10, 10, 1, y, 1 ); // $ExpectError + cxmy( 10, '10', 1, y, 1 ); // $ExpectError + cxmy( 10, true, 1, y, 1 ); // $ExpectError + cxmy( 10, false, 1, y, 1 ); // $ExpectError + cxmy( 10, null, 1, y, 1 ); // $ExpectError + cxmy( 10, undefined, 1, y, 1 ); // $ExpectError + cxmy( 10, [ '1' ], 1, y, 1 ); // $ExpectError + cxmy( 10, {}, 1, y, 1 ); // $ExpectError + cxmy( 10, ( x: number ): number => x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy( x.length, x, '10', y, 1 ); // $ExpectError + cxmy( x.length, x, true, y, 1 ); // $ExpectError + cxmy( x.length, x, false, y, 1 ); // $ExpectError + cxmy( x.length, x, null, y, 1 ); // $ExpectError + cxmy( x.length, x, undefined, y, 1 ); // $ExpectError + cxmy( x.length, x, [], y, 1 ); // $ExpectError + cxmy( x.length, x, {}, y, 1 ); // $ExpectError + cxmy( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + + cxmy( 10, x, 1, 10, 1 ); // $ExpectError + cxmy( 10, x, 1, '10', 1 ); // $ExpectError + cxmy( 10, x, 1, true, 1 ); // $ExpectError + cxmy( 10, x, 1, false, 1 ); // $ExpectError + cxmy( 10, x, 1, null, 1 ); // $ExpectError + cxmy( 10, x, 1, undefined, 1 ); // $ExpectError + cxmy( 10, x, 1, [ '1' ], 1 ); // $ExpectError + cxmy( 10, x, 1, {}, 1 ); // $ExpectError + cxmy( 10, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy( x.length, x, 1, y, '10' ); // $ExpectError + cxmy( x.length, x, 1, y, true ); // $ExpectError + cxmy( x.length, x, 1, y, false ); // $ExpectError + cxmy( x.length, x, 1, y, null ); // $ExpectError + cxmy( x.length, x, 1, y, undefined ); // $ExpectError + cxmy( x.length, x, 1, y, [] ); // $ExpectError + cxmy( x.length, x, 1, y, {} ); // $ExpectError + cxmy( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy(); // $ExpectError + cxmy( x.length ); // $ExpectError + cxmy( x.length, x ); // $ExpectError + cxmy( x.length, x, 1 ); // $ExpectError + cxmy( x.length, x, 1, y ); // $ExpectError + cxmy( x.length, x, 1, y, 1, 10 ); // $ExpectError +} + +// Attached to the main export is an `ndarray` method which returns a Complex64Array... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType Complex64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex64Array... +{ + const y = new Complex64Array( 10 ); + + cxmy.ndarray( 10, 10, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, '10', 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, true, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, false, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, null, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, undefined, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, [ '1' ], 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, {}, 1, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Complex64Array... +{ + const x = new Complex64Array( 10 ); + + cxmy.ndarray( 10, x, 1, 0, 10, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, '10', 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, true, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, false, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, null, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, undefined, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, {}, 1, 0 ); // $ExpectError + cxmy.ndarray( 10, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Complex64Array( 10 ); + const y = new Complex64Array( 10 ); + + cxmy.ndarray(); // $ExpectError + cxmy.ndarray( x.length ); // $ExpectError + cxmy.ndarray( x.length, x ); // $ExpectError + cxmy.ndarray( x.length, x, 1 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + cxmy.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/c/example.c new file mode 100644 index 000000000000..c9ec95c71ce9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/c/example.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cxmy.h" +#include "stdlib/complex/float32/ctor.h" +#include "stdlib/complex/float32/real.h" +#include "stdlib/complex/float32/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex64_t x[] = { + stdlib_complex64( 1.0f, 2.0f ), + stdlib_complex64( 3.0f, 4.0f ), + stdlib_complex64( 5.0f, 6.0f ), + stdlib_complex64( 7.0f, 8.0f ) + }; + stdlib_complex64_t y[] = { + stdlib_complex64( 2.0f, 3.0f ), + stdlib_complex64( 4.0f, 5.0f ), + stdlib_complex64( 6.0f, 7.0f ), + stdlib_complex64( 8.0f, 9.0f ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Multiply `x` by `y` and assign the results to `y`: + stdlib_strided_cxmy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "y[ %i ] = %f + %fi\n", i, stdlib_complex64_real( y[ i ] ), stdlib_complex64_imag( y[ i ] ) ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/index.js new file mode 100644 index 000000000000..32112d2d4720 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var logEach = require( '@stdlib/console/log-each' ); +var cxmy = require( './../lib' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var ybuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float32' +}); +var x = new Complex64Array( xbuf.buffer ); +var y = new Complex64Array( ybuf.buffer ); + +cxmy( x.length, x, 1, y, 1 ); +logEach( '%s', y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/cxmy/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function cxmy( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/cxmy.native.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/cxmy.native.js new file mode 100644 index 000000000000..dd502f11fb3b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/cxmy.native.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex64Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* cxmy( x.length, x, 1, y, 1 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function cxmy( N, x, strideX, y, strideY ) { + var viewX = reinterpret( x, 0 ); + var viewY = reinterpret( y, 0 ); + addon( N, viewX, strideX, viewY, strideY ); + return y; +} + + +// EXPORTS // + +module.exports = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/index.js new file mode 100644 index 000000000000..125633acb3a3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/index.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assign the results to `y`. +* +* @module @stdlib/blas/ext/base/cxmy +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var cxmy = require( '@stdlib/blas/ext/base/cxmy' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* cxmy( x.length, x, 1, y, 1 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* var cxmy = require( '@stdlib/blas/ext/base/cxmy' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* cxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var cxmy; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + cxmy = main; +} else { + cxmy = tmp; +} + + +// EXPORTS // + +module.exports = cxmy; + +// exports: { "ndarray": "cxmy.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/main.js new file mode 100644 index 000000000000..657c2064b997 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var cxmy = require( './cxmy.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( cxmy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/native.js new file mode 100644 index 000000000000..24a219fbef6b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var cxmy = require( './cxmy.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( cxmy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/ndarray.js new file mode 100644 index 000000000000..9709892e4f45 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/ndarray.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var cmulf = require( '@stdlib/complex/float32/base/mul' ).assign; + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex64Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* cxmy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function cxmy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xview; + var yview; + var ix; + var iy; + var sx; + var sy; + var m; + var i; + + if ( N <= 0 ) { + return y; + } + + // Reinterpret the complex input arrays as real-valued arrays: + xview = reinterpret( x, 0 ); + yview = reinterpret( y, 0 ); + + // Adjust the strides and offsets according to the real-valued arrays: + ix = offsetX * 2; + iy = offsetY * 2; + sx = strideX * 2; + sy = strideY * 2; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideY === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + cmulf( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + ix += sx; + iy += sy; + } + } + if ( N < M ) { + return y; + } + for ( i = m; i < N; i += M ) { + cmulf( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + cmulf( xview[ ix+2 ], xview[ ix+3 ], yview[ iy+2 ], yview[ iy+3 ], yview, 1, iy+2 ); + cmulf( xview[ ix+4 ], xview[ ix+5 ], yview[ iy+4 ], yview[ iy+5 ], yview, 1, iy+4 ); + cmulf( xview[ ix+6 ], xview[ ix+7 ], yview[ iy+6 ], yview[ iy+7 ], yview, 1, iy+6 ); + cmulf( xview[ ix+8 ], xview[ ix+9 ], yview[ iy+8 ], yview[ iy+9 ], yview, 1, iy+8 ); + ix += M * 2; + iy += M * 2; + } + return y; + } + for ( i = 0; i < N; i++ ) { + cmulf( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + ix += sx; + iy += sy; + } + return y; +} + + +// EXPORTS // + +module.exports = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/ndarray.native.js new file mode 100644 index 000000000000..dc48457aa6ed --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/lib/ndarray.native.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex64Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Complex64Array} output array +* +* @example +* var Complex64Array = require( '@stdlib/array/complex64' ); +* +* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* cxmy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function cxmy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var viewX = reinterpret( x, 0 ); + var viewY = reinterpret( y, 0 ); + addon.ndarray( N, viewX, strideX, offsetX, viewY, strideY, offsetY ); + return y; +} + + +// EXPORTS // + +module.exports = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/cxmy/manifest.json new file mode 100644 index 000000000000..8f6292546164 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/manifest.json @@ -0,0 +1,108 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float32/base/mul", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-complex64array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float32/base/mul", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float32/base/mul", + "@stdlib/complex/float32/real", + "@stdlib/complex/float32/imag", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "build", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float32/base/mul", + "@stdlib/complex/float32/ctor", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/package.json b/lib/node_modules/@stdlib/blas/ext/base/cxmy/package.json new file mode 100644 index 000000000000..0af9260528b2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/package.json @@ -0,0 +1,82 @@ +{ + "name": "@stdlib/blas/ext/base/cxmy", + "version": "0.0.0", + "description": "Multiply elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assign the results to `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "linear", + "algebra", + "subroutines", + "multiply", + "transform", + "strided", + "array", + "ndarray", + "vector", + "xmy", + "cxmy", + "complex", + "complex64", + "complex64array", + "float32", + "single" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/addon.c new file mode 100644 index 000000000000..7ff628896864 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cxmy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_cxmy)( N, (stdlib_complex64_t *)X, strideX, (stdlib_complex64_t *)Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX64ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_cxmy_ndarray)( N, (stdlib_complex64_t *)X, strideX, offsetX, (stdlib_complex64_t *)Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/main.c new file mode 100644 index 000000000000..9fc2c08cba00 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/src/main.c @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/cxmy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/complex/float32/base/mul.h" +#include "stdlib/strided/base/stride2offset.h" + +static const CBLAS_INT M = 5; + +/** +* Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param Y output array +* @param strideY stride length for `Y` +*/ +void API_SUFFIX(stdlib_strided_cxmy)( const CBLAS_INT N, const stdlib_complex64_t *X, const CBLAS_INT strideX, stdlib_complex64_t *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_cxmy_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param Y output array +* @param strideY stride length for `Y` +* @param offsetY starting index for `Y` +*/ +void API_SUFFIX(stdlib_strided_cxmy_ndarray)( const CBLAS_INT N, const stdlib_complex64_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex64_t *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideY == 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + Y[ iy ] = stdlib_base_complex64_mul( X[ ix ], Y[ iy ] ); + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return; + } + for ( i = m; i < N; i += M ) { + Y[ iy ] = stdlib_base_complex64_mul( X[ ix ], Y[ iy ] ); + Y[ iy+1 ] = stdlib_base_complex64_mul( X[ ix+1 ], Y[ iy+1 ] ); + Y[ iy+2 ] = stdlib_base_complex64_mul( X[ ix+2 ], Y[ iy+2 ] ); + Y[ iy+3 ] = stdlib_base_complex64_mul( X[ ix+3 ], Y[ iy+3 ] ); + Y[ iy+4 ] = stdlib_base_complex64_mul( X[ ix+4 ], Y[ iy+4 ] ); + ix += M; + iy += M; + } + return; + } + for ( i = 0; i < N; i++ ) { + Y[ iy ] = stdlib_base_complex64_mul( X[ ix ], Y[ iy ] ); + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.cxmy.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.cxmy.js new file mode 100644 index 000000000000..803d5bc09c86 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.cxmy.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var cmulf = require( '@stdlib/complex/float32/base/mul' ); +var cxmy = require( './../lib/cxmy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( cxmy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex64Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = cxmy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + cxmy( 0, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + cxmy( -4, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + cxmy( 3, x, 2, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + cxmy( 3, x, 1, y, 2 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex64Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex64Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + cxmy( 3, x, -2, y, -1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex64Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( 3, x1, 1, y1, 1 ); + t.strictEqual( isSameComplex64Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex64Array( 100 ); + y = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + y = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.cxmy.native.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.cxmy.native.js new file mode 100644 index 000000000000..07fc3f969852 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.cxmy.native.js @@ -0,0 +1,330 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var cmulf = require( '@stdlib/complex/float32/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var cxmy = tryRequire( resolve( __dirname, './../lib/cxmy.native.js' ) ); +var opts = { + 'skip': ( cxmy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( cxmy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex64Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = cxmy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + cxmy( 0, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + cxmy( -4, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + cxmy( 3, x, 2, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + cxmy( 3, x, 1, y, 2 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex64Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex64Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + cxmy( 3, x, -2, y, -1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex64Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( 3, x1, 1, y1, 1 ); + t.strictEqual( isSameComplex64Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex64Array( 100 ); + y = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + y = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.js new file mode 100644 index 000000000000..172868a9a2fb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var cxmy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof cxmy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var cxmy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( cxmy, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var cxmy; + var main; + + main = require( './../lib/cxmy.js' ); + + cxmy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( cxmy, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.ndarray.js new file mode 100644 index 000000000000..336080015e82 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.ndarray.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var cmulf = require( '@stdlib/complex/float32/base/mul' ); +var cxmy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( cxmy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex64Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = cxmy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + cxmy( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + cxmy( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + cxmy( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + cxmy( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex64Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex64Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + cxmy( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex64Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( 3, x1, 1, 0, y1, 1, 0 ); + t.strictEqual( isSameComplex64Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex64Array( 100 ); + y = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + y = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.ndarray.native.js new file mode 100644 index 000000000000..20acca59aa89 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/cxmy/test/test.ndarray.native.js @@ -0,0 +1,330 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var Complex64 = require( '@stdlib/complex/float32/ctor' ); +var cmulf = require( '@stdlib/complex/float32/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var cxmy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( cxmy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( cxmy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex64Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = cxmy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + cxmy( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + cxmy( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + cxmy( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex64Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex64Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + cxmy( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex64Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex64Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex64Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + cxmy( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex64Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex64Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + cxmy( 3, x1, 1, 0, y1, 1, 0 ); + t.strictEqual( isSameComplex64Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex64Array( 100 ); + y = new Complex64Array( 100 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + x = new Complex64Array( 240 ); + y = new Complex64Array( 240 ); + expected = new Complex64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex64( i, 0.0 ); + yv = new Complex64( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmulf( xv, yv ), i ); + } + cxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex64Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dcartesian-power/README.md b/lib/node_modules/@stdlib/blas/ext/base/dcartesian-power/README.md index 5ffba9146ba6..375e6c5a5b81 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dcartesian-power/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dcartesian-power/README.md @@ -110,8 +110,8 @@ The function has the following parameters: - **strideX**: stride length for `x`. - **offsetX**: starting index for `x`. - **out**: output [`Float64Array`][@stdlib/array/float64]. -- **strideOut1**: stride length of the first dimension of `out`. -- **strideOut2**: stride length of the second dimension of `out`. +- **strideOut1**: stride length for the first dimension of `out`. +- **strideOut2**: stride length for the second dimension of `out`. - **offsetOut**: starting index for `out`. While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last two elements: @@ -247,8 +247,8 @@ The function accepts the following arguments: - **strideX**: `[in] CBLAS_INT` stride length for `X`. - **offsetX**: `[in] CBLAS_INT` starting index for `X`. - **Out**: `[out] double*` output array. -- **strideOut1**: `[in] CBLAS_INT` stride length of the first dimension of `Out`. -- **strideOut2**: `[in] CBLAS_INT` stride length of the second dimension of `Out`. +- **strideOut1**: `[in] CBLAS_INT` stride length for the first dimension of `Out`. +- **strideOut2**: `[in] CBLAS_INT` stride length for the second dimension of `Out`. - **offsetOut**: `[in] CBLAS_INT` starting index for `Out`. ```c diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/README.md new file mode 100644 index 000000000000..3df4eb351194 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/README.md @@ -0,0 +1,294 @@ + + +# dfillEqual + +> Replace double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + +
+ +## Usage + +```javascript +var dfillEqual = require( '@stdlib/blas/ext/base/dfill-equal' ); +``` + +#### dfillEqual( N, searchElement, alpha, x, strideX ) + +Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] ); + +dfillEqual( x.length, 0.0, 5.0, x, 1 ); +// x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **alpha**: scalar constant. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 0.0, 1.0, 0.0, -5.0, 4.0, 0.0, -1.0, 0.0 ] ); + +dfillEqual( 4, 0.0, 5.0, x, 2 ); +// x => [ 5.0, 1.0, 5.0, -5.0, 4.0, 0.0, -1.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array: +var x0 = new Float64Array( [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0 ] ); + +// Create an offset view: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +dfillEqual( 3, 0.0, 5.0, x1, 2 ); +// x0 => [ 1.0, 5.0, 3.0, 5.0, -5.0, 5.0 ] +``` + +#### dfillEqual.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + +Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] ); + +dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +// x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] ); + +dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, x.length-3 ); +// x => [ -2.0, 0.0, 3.0, 0.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- When comparing elements, both functions check for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct, and `-0` and `+0` are considered the same. To replace `NaN` values, use [`@stdlib/blas/ext/base/dfill-nan`][@stdlib/blas/ext/base/dfill-nan]. + +
+ + + +
+ +## Examples + + + +```javascript +var zeros = require( '@stdlib/array/zeros' ); +var dfillEqual = require( '@stdlib/blas/ext/base/dfill-equal' ); + +var x = zeros( 10, 'float64' ); +console.log( x ); + +dfillEqual( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dfill_equal.h" +``` + +#### stdlib_strided_dfill_equal( N, searchElement, alpha, \*X, strideX ) + +Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + +```c +double x[] = { -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 }; + +stdlib_strided_dfill_equal( 8, 0.0, 5.0, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] double` search element. +- **alpha**: `[in] double` scalar constant. +- **X**: `[inout] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_dfill_equal( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX ); +``` + + + +#### stdlib_strided_dfill_equal_ndarray( N, searchElement, alpha, \*X, strideX, offsetX ) + + + +Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```c +double x[] = { -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 }; + +stdlib_strided_dfill_equal_ndarray( 8, 0.0, 5.0, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] double` search element. +- **alpha**: `[in] double` scalar constant. +- **X**: `[inout] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_dfill_equal_ndarray( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dfill_equal.h" +#include + +int main( void ) { + // Create a strided array: + double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace equal elements: + stdlib_strided_dfill_equal( N, 5.0, 10.0, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %lf\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/blas/ext/base/dfill-nan]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/dfill-nan + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..0037ef0bbb98 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillEqual = require( './../lib/dfill_equal.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillEqual( x.length, i, i+1, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.native.js new file mode 100644 index 000000000000..ef13b653bea1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfillEqual = tryRequire( resolve( __dirname, './../lib/dfill_equal.native.js' ) ); +var opts = { + 'skip': ( dfillEqual instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillEqual( x.length, i, i+1, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..97dc4fe12052 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillEqual = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..b8eea7279610 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfillEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfillEqual instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..a9ce7bcb5e74 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/benchmark/c/benchmark.length.c @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_equal.h" +#include +#include +#include +#include +#include + +#define NAME "dfill-equal" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0; + } else { + x[ i ] = ( rand_double()*200.0 ) - 100.0; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_dfill_equal( len, (double)i, (double)(i+1), x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0; + } else { + x[ i ] = ( rand_double()*200.0 ) - 100.0; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_dfill_equal_ndarray( len, (double)i, (double)(i+1), x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/repl.txt new file mode 100644 index 000000000000..736a3bd1fd70 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/repl.txt @@ -0,0 +1,104 @@ + +{{alias}}( N, searchElement, alpha, x, strideX ) + Replaces double-precision floating-point strided array elements equal to a + provided search element with a specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: Float64Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}( x.length, 0.0, 5.0, x, 1 ) + [ 5.0, 5.0, 1.0, 5.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}( 2, 0.0, 5.0, x, 2 ) + [ 5.0, 0.0, 1.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 0.0, 5.0, x1, 2 ) + [ 5.0, 1.0, 5.0 ] + > x0 + [ 0.0, 5.0, 1.0, 5.0 ] + + +{{alias}}.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + Replaces double-precision floating-point strided array elements equal to a + provided search element with a specified scalar constant using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: Float64Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}.ndarray( x.length, 0.0, 5.0, x, 1, 0 ) + [ 5.0, 5.0, 1.0, 5.0 ] + + // Using an index offset: + > var x = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}.ndarray( 2, 0.0, 5.0, x, 2, 1 ) + [ 0.0, 5.0, 1.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..66a4a4f8437e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/types/index.d.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dfillEqual`. +*/ +interface Routine { + /** + * Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * dfillEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + ( N: number, searchElement: number, alpha: number, x: Float64Array, strideX: number ): Float64Array; + + /** + * Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + ndarray( N: number, searchElement: number, alpha: number, x: Float64Array, strideX: number, offsetX: number ): Float64Array; +} + +/** +* Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* dfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +declare var dfillEqual: Routine; + + +// EXPORTS // + +export = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/types/test.ts new file mode 100644 index 000000000000..4a6c75ccbab8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/docs/types/test.ts @@ -0,0 +1,217 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dfillEqual = require( './index' ); + + +// TESTS // + +// The function returns a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillEqual( x.length, 0.0, 5.0, x, 1 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual( '10', 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual( true, 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual( false, 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual( null, 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual( undefined, 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual( [], 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual( {}, 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual( ( x: number ): number => x, 0.0, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual( x.length, '10', 5.0, x, 1 ); // $ExpectError + dfillEqual( x.length, true, 5.0, x, 1 ); // $ExpectError + dfillEqual( x.length, false, 5.0, x, 1 ); // $ExpectError + dfillEqual( x.length, null, 5.0, x, 1 ); // $ExpectError + dfillEqual( x.length, undefined, 5.0, x, 1 ); // $ExpectError + dfillEqual( x.length, [], 5.0, x, 1 ); // $ExpectError + dfillEqual( x.length, {}, 5.0, x, 1 ); // $ExpectError + dfillEqual( x.length, ( x: number ): number => x, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual( x.length, 0.0, '10', x, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, true, x, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, false, x, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, null, x, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, undefined, x, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, [], x, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, {}, x, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillEqual( x.length, 0.0, 5.0, 10, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, '10', 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, true, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, false, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, null, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, undefined, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, [], 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, {}, 1 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual( x.length, 0.0, 5.0, x, '10' ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, true ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, false ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, null ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, undefined ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, [] ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, {} ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dfillEqual(); // $ExpectError + dfillEqual( x.length ); // $ExpectError + dfillEqual( x.length, 0.0 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0 ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x ); // $ExpectError + dfillEqual( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray( '10', 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( true, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( false, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( null, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( undefined, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( [], 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( {}, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( ( x: number ): number => x, 0.0, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray( x.length, '10', 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, true, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, false, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, null, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, undefined, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, [], 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, {}, 5.0, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, ( x: number ): number => x, x, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray( x.length, 0.0, '10', x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, true, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, false, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, null, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, undefined, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, [], x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, {}, x, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray( x.length, 0.0, 5.0, 10, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, '10', 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, true, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, false, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, null, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, undefined, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, [], 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, {}, 1, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray( x.length, 0.0, 5.0, x, '10', 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, true, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, false, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, null, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, undefined, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, [], 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, {}, 0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, ( x: number ): number => x, x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, '10' ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, true ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, false ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, null ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, undefined ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, [] ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dfillEqual.ndarray(); // $ExpectError + dfillEqual.ndarray( x.length ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, x ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1 ); // $ExpectError + dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/c/example.c new file mode 100644 index 000000000000..f42bf684529d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_equal.h" +#include + +int main( void ) { + // Create a strided array: + double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace equal elements: + stdlib_strided_dfill_equal( N, 5.0, 10.0, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %lf\n", i, x[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/index.js new file mode 100644 index 000000000000..3133e56bd8ca --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/examples/index.js @@ -0,0 +1,28 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var zeros = require( '@stdlib/array/zeros' ); +var dfillEqual = require( './../lib' ); + +var x = zeros( 10, 'float64' ); +console.log( x ); + +dfillEqual( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function dfillEqual( N, searchElement, alpha, x, strideX ) { + return ndarray( N, searchElement, alpha, x, strideX, stride2offset( N, strideX ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/dfill_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/dfill_equal.native.js new file mode 100644 index 000000000000..88ba9c690617 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/dfill_equal.native.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* dfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function dfillEqual( N, searchElement, alpha, x, strideX ) { + addon( N, searchElement, alpha, x, strideX ); + return x; +} + + +// EXPORTS // + +module.exports = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/index.js new file mode 100644 index 000000000000..c48e39392547 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/index.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/dfill-equal +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dfillEqual = require( '@stdlib/blas/ext/base/dfill-equal' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* dfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dfillEqual = require( '@stdlib/blas/ext/base/dfill-equal' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dfillEqual; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dfillEqual = main; +} else { + dfillEqual = tmp; +} + + +// EXPORTS // + +module.exports = dfillEqual; + +// exports: { "ndarray": "dfillEqual.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/main.js new file mode 100644 index 000000000000..3ef5f189d4da --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dfillEqual = require( './dfill_equal.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( dfillEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/native.js new file mode 100644 index 000000000000..568899122f11 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dfillEqual = require( './dfill_equal.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( dfillEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/ndarray.js new file mode 100644 index 000000000000..25a25e9f5f6e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/ndarray.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @param {integer} offsetX - starting index +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* dfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function dfillEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var ix; + var i; + + if ( N <= 0 ) { + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] === searchElement ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/ndarray.native.js new file mode 100644 index 000000000000..3feaed5b57c4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/lib/ndarray.native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @param {integer} offsetX - starting index +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* dfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function dfillEqual( N, searchElement, alpha, x, strideX, offsetX ) { + addon.ndarray( N, searchElement, alpha, x, strideX, offsetX ); + return x; +} + + +// EXPORTS // + +module.exports = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/manifest.json new file mode 100644 index 000000000000..13cc0c24361f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/manifest.json @@ -0,0 +1,79 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/package.json new file mode 100644 index 000000000000..7b950b945b96 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/dfill-equal", + "version": "0.0.0", + "description": "Replace double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "equal", + "same", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float64", + "double", + "float64array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/addon.c new file mode 100644 index 000000000000..f081a7ed24a1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_dfill_equal)( N, searchElement, alpha, X, strideX ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_dfill_equal_ndarray)( N, searchElement, alpha, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/main.c new file mode 100644 index 000000000000..4da679d84f04 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/src/main.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_dfill_equal)( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_dfill_equal_ndarray)( N, searchElement, alpha, X, strideX, ox ); +} + +/** +* Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_dfill_equal_ndarray)( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] == searchElement ) { + X[ ix ] = alpha; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.dfill_equal.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.dfill_equal.js new file mode 100644 index 000000000000..9ac246a0531f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.dfill_equal.js @@ -0,0 +1,183 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfillEqual = require( './../lib/dfill_equal.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dfillEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + dfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float64Array( [ 0.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = dfillEqual( x.length, 1.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + + out = dfillEqual( 0, 1.0, 5.0, x, 1 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + dfillEqual( 3, 1.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float64Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + dfillEqual( 3, 1.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + dfillEqual( 3, 1.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.dfill_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.dfill_equal.native.js new file mode 100644 index 000000000000..ced017ead037 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.dfill_equal.native.js @@ -0,0 +1,192 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfillEqual = tryRequire( resolve( __dirname, './../lib/dfill_equal.native.js' ) ); +var opts = { + 'skip': ( dfillEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dfillEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + dfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float64Array( [ 0.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = dfillEqual( x.length, 1.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + + out = dfillEqual( 0, 1.0, 5.0, x, 1 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + dfillEqual( 3, 1.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float64Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + dfillEqual( 3, 1.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + dfillEqual( 3, 1.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.js new file mode 100644 index 000000000000..356ee46e7bf1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dfillEqual = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dfillEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dfillEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfillEqual, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dfillEqual; + var main; + + main = require( './../lib/dfill_equal.js' ); + + dfillEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfillEqual, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.ndarray.js new file mode 100644 index 000000000000..dc0cf8b1a8c6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.ndarray.js @@ -0,0 +1,179 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfillEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( dfillEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + dfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = dfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + + out = dfillEqual( 0, 1.0, 5.0, x, 1, 0 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + dfillEqual( 3, 1.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float64Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + dfillEqual( 3, 1.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + dfillEqual( 3, 1.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.ndarray.native.js new file mode 100644 index 000000000000..ef2c317587cc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-equal/test/test.ndarray.native.js @@ -0,0 +1,188 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfillEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfillEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( dfillEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + dfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = dfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 1.0, -4.0, 1.0 ] ); + + out = dfillEqual( 0, 1.0, 5.0, x, 1, 0 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + dfillEqual( 3, 1.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float64Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + dfillEqual( 3, 1.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + dfillEqual( 3, 1.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/README.md b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/README.md new file mode 100644 index 000000000000..9679fe77d7c4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/README.md @@ -0,0 +1,284 @@ + + +# dfillNaN + +> Replace double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + +
+ +## Usage + +```javascript +var dfillNaN = require( '@stdlib/blas/ext/base/dfill-nan' ); +``` + +#### dfillNaN( N, alpha, x, strideX ) + +Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + +dfillNaN( x.length, 0.0, x, 1 ); +// x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **alpha**: scalar constant. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ NaN, 1.0, NaN, -5.0, NaN, 0.0, -1.0, -3.0 ] ); + +dfillNaN( 4, 0.0, x, 2 ); +// x => [ 0.0, 1.0, 0.0, -5.0, 0.0, 0.0, -1.0, -3.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array: +var x0 = new Float64Array( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + +// Create an offset view: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +dfillNaN( 3, 0.0, x1, 2 ); +// x0 => [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] +``` + +#### dfillNaN.ndarray( N, alpha, x, strideX, offsetX ) + +Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + +dfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +// x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + +dfillNaN.ndarray( 3, 0.0, x, 1, x.length-3 ); +// x => [ 1.0, NaN, 3.0, 0.0, 5.0, -6.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var nans = require( '@stdlib/array/nans' ); +var dfillNaN = require( '@stdlib/blas/ext/base/dfill-nan' ); + +var x = nans( 10, 'float64' ); +console.log( x ); + +dfillNaN( x.length, 0.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dfill_nan.h" +``` + +#### stdlib_strided_dfill_nan( N, alpha, \*X, strideX ) + +Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + +```c +double x[] = { 1.0, 0.0/0.0, 3.0, 0.0/0.0 }; + +stdlib_strided_dfill_nan( 4, 0.0, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] double` scalar constant. +- **X**: `[inout] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_dfill_nan( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_dfill_nan_ndarray( N, alpha, \*X, strideX, offsetX ) + +Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + +```c +double x[] = { 1.0, 0.0/0.0, 3.0, 0.0/0.0 }; + +stdlib_strided_dfill_nan_ndarray( 4, 0.0, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] double` scalar constant. +- **X**: `[inout] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_dfill_nan_ndarray( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dfill_nan.h" +#include + +int main( void ) { + // Create a strided array: + double x[] = { 1.0, 0.0/0.0, 3.0, 0.0/0.0, 5.0, -6.0, 7.0, 0.0/0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements equal to `NaN`: + stdlib_strided_dfill_nan( N, 0.0, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %lf\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.js new file mode 100644 index 000000000000..6f39de7f7eed --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillNaN = require( './../lib/dfill_nan.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNaN( x.length, 0.0, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.native.js new file mode 100644 index 000000000000..71a63405fada --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfillNaN = tryRequire( resolve( __dirname, './../lib/dfill_nan.native.js' ) ); +var opts = { + 'skip': ( dfillNaN instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNaN( x.length, 0.0, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..352f5d62553d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillNaN = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNaN( x.length, 0.0, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..cf6c688bc9bf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfillNaN = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfillNaN instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNaN( x.length, 0.0, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..7ffc683135f9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/benchmark/c/benchmark.length.c @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_nan.h" +#include +#include +#include +#include +#include + +#define NAME "dfill-nan" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0 / 0.0; + } else { + x[ i ] = ( rand_double()*200.0 ) - 100.0; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_dfill_nan( len, 0.0, x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0 / 0.0; + } else { + x[ i ] = ( rand_double()*200.0 ) - 100.0; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_dfill_nan_ndarray( len, 0.0, x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/repl.txt new file mode 100644 index 000000000000..0d9ccb622c0e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/repl.txt @@ -0,0 +1,97 @@ + +{{alias}}( N, alpha, x, strideX ) + Replaces double-precision floating-point strided array elements equal to + `NaN` with a specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: Float64Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ NaN, 1.0, 3.0, NaN ] ); + > {{alias}}( x.length, 0.0, x, 1 ) + [ 0.0, 1.0, 3.0, 0.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ NaN, 1.0, NaN, -5.0, NaN ] ); + > {{alias}}( 3, 0.0, x, 2 ) + [ 0.0, 1.0, 0.0, -5.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 0.0, x1, 2 ) + [ 0.0, 3.0, 0.0, 5.0, -6.0 ] + > x0 + [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] + + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Replaces double-precision floating-point strided array elements equal to + `NaN` with a specified scalar constant using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: Float64Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ NaN, 1.0, 3.0, NaN ] ); + > {{alias}}.ndarray( x.length, 0.0, x, 1, 0 ) + [ 0.0, 1.0, 3.0, 0.0 ] + + // Using an index offset: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + > {{alias}}.ndarray( 3, 0.0, x, 2, 1 ) + [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/types/index.d.ts new file mode 100644 index 000000000000..a59e21fee9ca --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/types/index.d.ts @@ -0,0 +1,95 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dfillNaN`. +*/ +interface Routine { + /** + * Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * dfillNaN( x.length, 0.0, x, 1 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + ( N: number, alpha: number, x: Float64Array, strideX: number ): Float64Array; + + /** + * Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * dfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + ndarray( N: number, alpha: number, x: Float64Array, strideX: number, offsetX: number ): Float64Array; +} + +/** +* Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param N - number of indexed elements +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); +* +* dfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); +* +* dfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +* // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +*/ +declare var dfillNaN: Routine; + + +// EXPORTS // + +export = dfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/types/test.ts new file mode 100644 index 000000000000..cfbfd2fbf806 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/docs/types/test.ts @@ -0,0 +1,187 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dfillNaN = require( './index' ); + + +// TESTS // + +// The function returns a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNaN( x.length, 0.0, x, 1 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNaN( '10', 0.0, x, 1 ); // $ExpectError + dfillNaN( true, 0.0, x, 1 ); // $ExpectError + dfillNaN( false, 0.0, x, 1 ); // $ExpectError + dfillNaN( null, 0.0, x, 1 ); // $ExpectError + dfillNaN( undefined, 0.0, x, 1 ); // $ExpectError + dfillNaN( [], 0.0, x, 1 ); // $ExpectError + dfillNaN( {}, 0.0, x, 1 ); // $ExpectError + dfillNaN( ( x: number ): number => x, 0.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNaN( x.length, '10', x, 1 ); // $ExpectError + dfillNaN( x.length, true, x, 1 ); // $ExpectError + dfillNaN( x.length, false, x, 1 ); // $ExpectError + dfillNaN( x.length, null, x, 1 ); // $ExpectError + dfillNaN( x.length, undefined, x, 1 ); // $ExpectError + dfillNaN( x.length, [], x, 1 ); // $ExpectError + dfillNaN( x.length, {}, x, 1 ); // $ExpectError + dfillNaN( x.length, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNaN( x.length, 0.0, 10, 1 ); // $ExpectError + dfillNaN( x.length, 0.0, '10', 1 ); // $ExpectError + dfillNaN( x.length, 0.0, true, 1 ); // $ExpectError + dfillNaN( x.length, 0.0, false, 1 ); // $ExpectError + dfillNaN( x.length, 0.0, null, 1 ); // $ExpectError + dfillNaN( x.length, 0.0, undefined, 1 ); // $ExpectError + dfillNaN( x.length, 0.0, [], 1 ); // $ExpectError + dfillNaN( x.length, 0.0, {}, 1 ); // $ExpectError + dfillNaN( x.length, 0.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNaN( x.length, 0.0, x, '10' ); // $ExpectError + dfillNaN( x.length, 0.0, x, true ); // $ExpectError + dfillNaN( x.length, 0.0, x, false ); // $ExpectError + dfillNaN( x.length, 0.0, x, null ); // $ExpectError + dfillNaN( x.length, 0.0, x, undefined ); // $ExpectError + dfillNaN( x.length, 0.0, x, [] ); // $ExpectError + dfillNaN( x.length, 0.0, x, {} ); // $ExpectError + dfillNaN( x.length, 0.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dfillNaN(); // $ExpectError + dfillNaN( x.length ); // $ExpectError + dfillNaN( x.length, 0.0 ); // $ExpectError + dfillNaN( x.length, 0.0, x ); // $ExpectError + dfillNaN( x.length, 0.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNaN.ndarray( '10', 0.0, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( true, 0.0, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( false, 0.0, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( null, 0.0, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( undefined, 0.0, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( [], 0.0, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( {}, 0.0, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( ( x: number ): number => x, 0.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNaN.ndarray( x.length, '10', x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, true, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, false, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, null, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, undefined, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, [], x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, {}, x, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNaN.ndarray( x.length, 0.0, 10, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, '10', 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, true, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, false, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, null, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, undefined, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, [], 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, {}, 1, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNaN.ndarray( x.length, 0.0, x, '10', 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, true, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, false, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, null, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, undefined, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, [], 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, {}, 0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNaN.ndarray( x.length, 0.0, x, 1, '10' ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, true ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, false ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, null ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, undefined ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, [] ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, {} ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dfillNaN.ndarray(); // $ExpectError + dfillNaN.ndarray( x.length ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1 ); // $ExpectError + dfillNaN.ndarray( x.length, 0.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/c/example.c new file mode 100644 index 000000000000..05ddcc8f558b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_nan.h" +#include + +int main( void ) { + // Create a strided array: + double x[] = { 1.0, 0.0/0.0, 3.0, 0.0/0.0, 5.0, -6.0, 7.0, 0.0/0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements equal to `NaN`: + stdlib_strided_dfill_nan( N, 0.0, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %lf\n", i, x[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/index.js new file mode 100644 index 000000000000..429af0997221 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/examples/index.js @@ -0,0 +1,28 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var nans = require( '@stdlib/array/nans' ); +var dfillNaN = require( './../lib' ); + +var x = nans( 10, 'float64' ); +console.log( x ); + +dfillNaN( x.length, 0.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 0.0, 0.0, 1.0, 0.0 ] +*/ +function dfillNaN( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = dfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/dfill_nan.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/dfill_nan.native.js new file mode 100644 index 000000000000..7ca4b8933c8d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/dfill_nan.native.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ NaN, NaN, 1.0, NaN ] ); +* +* dfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +*/ +function dfillNaN( N, alpha, x, strideX ) { + addon( N, alpha, x, strideX ); + return x; +} + + +// EXPORTS // + +module.exports = dfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/index.js new file mode 100644 index 000000000000..7bc29a8a1475 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/index.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/dfill-nan +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dfillNaN = require( '@stdlib/blas/ext/base/dfill-nan' ); +* +* var x = new Float64Array( [ NaN, NaN, 1.0, NaN ] ); +* +* dfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dfillNaN = require( '@stdlib/blas/ext/base/dfill-nan' ); +* +* var x = new Float64Array( [ NaN, NaN, 1.0, NaN ] ); +* +* dfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dfillNaN; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dfillNaN = main; +} else { + dfillNaN = tmp; +} + + +// EXPORTS // + +module.exports = dfillNaN; + +// exports: { "ndarray": "dfillNaN.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/main.js new file mode 100644 index 000000000000..fafb181de993 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dfillNaN = require( './dfill_nan.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( dfillNaN, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/native.js new file mode 100644 index 000000000000..a1fb5ef5791d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dfillNaN = require( './dfill_nan.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( dfillNaN, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/ndarray.js new file mode 100644 index 000000000000..90ffad419d7b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/ndarray.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ NaN, -2.0, 3.0, NaN, 5.0, -6.0 ] ); +* +* dfillNaN( 6, 0.0, x, 1, 0 ); +* // x => [ 0.0, -2.0, 3.0, 0.0, 5.0, -6.0 ] +*/ +function dfillNaN( N, alpha, x, strideX, offsetX ) { + var ix; + var i; + + if ( N <= 0 ) { + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( isnan( x[ ix ] ) ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = dfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/ndarray.native.js new file mode 100644 index 000000000000..becdb80c65da --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/lib/ndarray.native.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ NaN, -2.0, 3.0, NaN, 5.0, -6.0 ] ); +* +* dfillNaN( 6, 0.0, x, 1, 0 ); +* // x => [ 0.0, -2.0, 3.0, 0.0, 5.0, -6.0 ] +*/ +function dfillNaN( N, alpha, x, strideX, offsetX ) { + addon.ndarray( N, alpha, x, strideX, offsetX ); + return x; +} + + +// EXPORTS // + +module.exports = dfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/manifest.json new file mode 100644 index 000000000000..ec2b36570dcc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/manifest.json @@ -0,0 +1,82 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nan" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/package.json b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/package.json new file mode 100644 index 000000000000..d29e910d4ba5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/dfill-nan", + "version": "0.0.0", + "description": "Replace double-precision floating-point strided array elements equal to NaN with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "nan", + "not-a-number", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float64", + "double", + "float64array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/addon.c new file mode 100644 index 000000000000..bbe891ab4c25 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/addon.c @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_nan.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_dfill_nan)( N, alpha, X, strideX ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_dfill_nan_ndarray)( N, alpha, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/main.c new file mode 100644 index 000000000000..4414d1aa596c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/src/main.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_nan.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/math/base/assert/is_nan.h" + +/** +* Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_dfill_nan)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_dfill_nan_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_dfill_nan_ndarray)( const CBLAS_INT N, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( stdlib_base_is_nan( X[ ix ] ) ) { + X[ ix ] = alpha; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.dfill_nan.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.dfill_nan.js new file mode 100644 index 000000000000..59bde9581a7d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.dfill_nan.js @@ -0,0 +1,184 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfillNaN = require( './../lib/dfill_nan.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( dfillNaN.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + dfillNaN( x.length, 0.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillNaN( x.length, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = dfillNaN( x.length, 0.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var x; + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + + dfillNaN( 0, 0.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + dfillNaN( -4, 0.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float64Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + dfillNaN( 3, 0.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + dfillNaN( 3, 0.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + dfillNaN( 3, 0.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.dfill_nan.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.dfill_nan.native.js new file mode 100644 index 000000000000..13c7f26c5508 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.dfill_nan.native.js @@ -0,0 +1,193 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfillNaN = tryRequire( resolve( __dirname, './../lib/dfill_nan.native.js' ) ); +var opts = { + 'skip': ( dfillNaN instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', opts, function test( t ) { + t.strictEqual( dfillNaN.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + dfillNaN( x.length, 0.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillNaN( x.length, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = dfillNaN( x.length, 0.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var x; + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + + dfillNaN( 0, 0.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + dfillNaN( -4, 0.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float64Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + dfillNaN( 3, 0.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + dfillNaN( 3, 0.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + dfillNaN( 3, 0.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.js new file mode 100644 index 000000000000..f07d28c31d1e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dfillNaN = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dfillNaN.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dfillNaN = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfillNaN, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dfillNaN; + var main; + + main = require( './../lib/dfill_nan.js' ); + + dfillNaN = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfillNaN, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.ndarray.js new file mode 100644 index 000000000000..6885e196b4f4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.ndarray.js @@ -0,0 +1,181 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfillNaN = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dfillNaN.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + dfillNaN( x.length, 0.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillNaN( x.length, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = dfillNaN( x.length, 0.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var x; + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + + dfillNaN( 0, 0.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + dfillNaN( -4, 0.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float64Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + dfillNaN( 3, 0.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + dfillNaN( 3, 0.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + dfillNaN( 3, 0.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.ndarray.native.js new file mode 100644 index 000000000000..b7fe79b5a36a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-nan/test/test.ndarray.native.js @@ -0,0 +1,190 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfillNaN = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfillNaN instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dfillNaN.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + dfillNaN( x.length, 0.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ NaN, 2.0 ] ); + expected = new Float64Array( [ 5.0, 2.0 ] ); + + dfillNaN( x.length, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = dfillNaN( x.length, 0.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var x; + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + + dfillNaN( 0, 0.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float64Array( [ NaN, -4.0, 1.0 ] ); + dfillNaN( -4, 0.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float64Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + dfillNaN( 3, 0.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + dfillNaN( 3, 0.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + dfillNaN( 3, 0.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/README.md new file mode 100644 index 000000000000..0ad9822aeb9a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/README.md @@ -0,0 +1,294 @@ + + +# dfillNotEqual + +> Replace double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + +
+ +## Usage + +```javascript +var dfillNotEqual = require( '@stdlib/blas/ext/base/dfill-not-equal' ); +``` + +#### dfillNotEqual( N, searchElement, alpha, x, strideX ) + +Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **alpha**: scalar constant. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +dfillNotEqual( 3, 0.0, 5.0, x, 2 ); +// x => [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array: +var x0 = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +// Create an offset view: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +dfillNotEqual( 3, 0.0, 5.0, x1, 2 ); +// x0 => [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] +``` + +#### dfillNotEqual.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + +Replaces strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +dfillNotEqual.ndarray( 3, 0.0, 5.0, x, 1, x.length-3 ); +// x => [ 0.0, -2.0, 3.0, 0.0, 5.0, 5.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- When comparing elements, both functions check for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dfillNotEqual = require( '@stdlib/blas/ext/base/dfill-not-equal' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'float64' +}); +console.log( x ); + +dfillNotEqual( x.length, 1, 5, x, 1 ); +console.log( x ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dfill_not_equal.h" +``` + +#### stdlib_strided_dfill_not_equal( N, searchElement, alpha, \*X, strideX ) + +Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + +```c +double x[] = { 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 }; + +stdlib_strided_dfill_not_equal( 6, 0.0, 5.0, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] double` search element. +- **alpha**: `[in] double` scalar constant. +- **X**: `[inout] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_dfill_not_equal( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX ); +``` + + + +#### stdlib_strided_dfill_not_equal_ndarray( N, searchElement, alpha, \*X, strideX, offsetX ) + + + +Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```c +double x[] = { 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 }; + +stdlib_strided_dfill_not_equal_ndarray( 6, 0.0, 5.0, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] double` search element. +- **alpha**: `[in] double` scalar constant. +- **X**: `[inout] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_dfill_not_equal_ndarray( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dfill_not_equal.h" +#include + +int main( void ) { + // Create a strided array: + double x[] = { 0.0, -2.0, 3.0, 0.0, 4.0, -6.0, 0.0, 8.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements not equal to `0.0`: + stdlib_strided_dfill_not_equal( N, 0.0, 5.0, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %lf\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..5439b2f2e3e0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillNotEqual = require( './../lib/dfill_not_equal.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNotEqual( x.length, i, i+1, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.native.js new file mode 100644 index 000000000000..63cd9dd0f391 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfillNotEqual = tryRequire( resolve( __dirname, './../lib/dfill_not_equal.native.js' ) ); +var opts = { + 'skip': ( dfillNotEqual instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNotEqual( x.length, i, i+1, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..1ef6cf599634 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillNotEqual = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNotEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..76236384fd88 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfillNotEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfillNotEqual instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = dfillNotEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..1e8dac240ca7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/benchmark/c/benchmark.length.c @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_not_equal.h" +#include +#include +#include +#include +#include + +#define NAME "dfill-not-equal" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0; + } else { + x[ i ] = ( rand_double()*200.0 ) - 100.0; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_dfill_not_equal( len, (double)i, (double)(i+1), x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0; + } else { + x[ i ] = ( rand_double()*200.0 ) - 100.0; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_dfill_not_equal_ndarray( len, (double)i, (double)(i+1), x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/repl.txt new file mode 100644 index 000000000000..3607ac581d5d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/repl.txt @@ -0,0 +1,104 @@ + +{{alias}}( N, searchElement, alpha, x, strideX ) + Replaces double-precision floating-point strided array elements not equal to + a provided search element with a specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: Float64Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}( x.length, 0.0, 5.0, x, 1 ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}( 3, 0.0, 5.0, x, 2 ) + [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, 0.0, 5.0, x1, 2 ) + [ 5.0, 3.0, 0.0, 4.0, 5.0 ] + > x0 + [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] + + +{{alias}}.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + Replaces double-precision floating-point strided array elements not equal to + a provided search element with a specified scalar constant using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: Float64Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}.ndarray( x.length, 0.0, 5.0, x, 1, 0 ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + // Using an index offset: + > x = new {{alias:@stdlib/array/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}.ndarray( 3, 0.0, 5.0, x, 2, 1 ) + [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..e97d8f9c4ade --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/types/index.d.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dfillNotEqual`. +*/ +interface Routine { + /** + * Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * dfillNotEqual( 6, 0.0, 5.0, x, 1 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + ( N: number, searchElement: number, alpha: number, x: Float64Array, strideX: number ): Float64Array; + + /** + * Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * dfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + ndarray( N: number, searchElement: number, alpha: number, x: Float64Array, strideX: number, offsetX: number ): Float64Array; +} + +/** +* Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* dfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* dfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +declare var dfillNotEqual: Routine; + + +// EXPORTS // + +export = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..7f399f4f6fa8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/docs/types/test.ts @@ -0,0 +1,214 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dfillNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual( '10', 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( true, 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( false, 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( null, 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( undefined, 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( [], 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( {}, 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( ( x: number ): number => x, 0.0, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual( x.length, '10', 5.0, x, 1 ); // $ExpectError + dfillNotEqual( x.length, true, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( x.length, false, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( x.length, null, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( x.length, undefined, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( x.length, [], 5.0, x, 1 ); // $ExpectError + dfillNotEqual( x.length, {}, 5.0, x, 1 ); // $ExpectError + dfillNotEqual( x.length, ( x: number ): number => x, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual( x.length, 0.0, '10', x, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, true, x, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, false, x, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, null, x, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, undefined, x, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, [], x, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, {}, x, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual( x.length, 0.0, 5.0, '10', 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, true, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, false, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, null, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, undefined, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, [], 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, {}, 1 ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual( x.length, 0.0, 5.0, x, '10' ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, true ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, false ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, null ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, undefined ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, [] ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, {} ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual(); // $ExpectError + dfillNotEqual( x.length ); // $ExpectError + dfillNotEqual( x.length, 0.0 ); // $ExpectError + dfillNotEqual( x.length, 0.0, x ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x ); // $ExpectError + dfillNotEqual( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray( '10', 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( true, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( false, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( null, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( undefined, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( [], 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( {}, 0.0, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( ( x: number ): number => x, 0.0, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray( x.length, '10', 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, true, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, false, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, null, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, undefined, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, [], 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, {}, 5.0, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, ( x: number ): number => x, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray( x.length, 0.0, '10', x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, true, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, false, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, null, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, undefined, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, [], x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, {}, x, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray( x.length, 0.0, 5.0, '10', 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, true, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, false, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, null, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, undefined, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, [], 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, {}, 1, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, '10', 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, true, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, false, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, null, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, undefined, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, [], 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, {}, 0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, '10' ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, true ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, false ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, null ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, undefined ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, [] ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dfillNotEqual.ndarray(); // $ExpectError + dfillNotEqual.ndarray( x.length ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1 ); // $ExpectError + dfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/c/example.c new file mode 100644 index 000000000000..aa6593941534 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_not_equal.h" +#include + +int main( void ) { + // Create a strided array: + double x[] = { 0.0, -2.0, 3.0, 0.0, 4.0, -6.0, 0.0, 8.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements not equal to `0.0`: + stdlib_strided_dfill_not_equal( N, 0.0, 5.0, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %lf\n", i, x[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/index.js new file mode 100644 index 000000000000..8e601073ee34 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dfillNotEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'float64' +}); +console.log( x ); + +dfillNotEqual( x.length, 1, 5, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function dfillNotEqual( N, searchElement, alpha, x, strideX ) { + return ndarray( N, searchElement, alpha, x, strideX, stride2offset( N, strideX ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/dfill_not_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/dfill_not_equal.native.js new file mode 100644 index 000000000000..26fe2ca06de4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/dfill_not_equal.native.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* dfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function dfillNotEqual( N, searchElement, alpha, x, strideX ) { + addon( N, searchElement, alpha, x, strideX ); + return x; +} + + +// EXPORTS // + +module.exports = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/index.js new file mode 100644 index 000000000000..dbdd8996eaa5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/index.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/dfill-not-equal +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dfillNotEqual = require( '@stdlib/blas/ext/base/dfill-not-equal' ); +* +* var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* dfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dfillNotEqual = require( '@stdlib/blas/ext/base/dfill-not-equal' ); +* +* var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* dfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dfillNotEqual; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dfillNotEqual = main; +} else { + dfillNotEqual = tmp; +} + + +// EXPORTS // + +module.exports = dfillNotEqual; + +// exports: { "ndarray": "dfillNotEqual.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/main.js new file mode 100644 index 000000000000..6adbed472d75 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dfillNotEqual = require( './dfill_not_equal.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( dfillNotEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/native.js new file mode 100644 index 000000000000..cf082487bd8a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dfillNotEqual = require( './dfill_not_equal.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( dfillNotEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/ndarray.js new file mode 100644 index 000000000000..4a41975c8528 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/ndarray.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* dfillNotEqual( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function dfillNotEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var ix; + var i; + + if ( N <= 0 ) { + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] !== searchElement ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/ndarray.native.js new file mode 100644 index 000000000000..6a3a43de3a35 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/lib/ndarray.native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float64Array} input array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* dfillNotEqual( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function dfillNotEqual( N, searchElement, alpha, x, strideX, offsetX ) { + addon.ndarray( N, searchElement, alpha, x, strideX, offsetX ); + return x; +} + + +// EXPORTS // + +module.exports = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/manifest.json new file mode 100644 index 000000000000..13cc0c24361f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/manifest.json @@ -0,0 +1,79 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/package.json new file mode 100644 index 000000000000..d58fdad4cce1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/dfill-not-equal", + "version": "0.0.0", + "description": "Replace double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "not equal", + "unequal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float64", + "double", + "float64array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/addon.c new file mode 100644 index 000000000000..f9c4166f4a33 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_not_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_dfill_not_equal)( N, searchElement, alpha, X, strideX ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_dfill_not_equal_ndarray)( N, searchElement, alpha, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/main.c new file mode 100644 index 000000000000..6bca64b44f14 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/src/main.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfill_not_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_dfill_not_equal)( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_dfill_not_equal_ndarray)( N, searchElement, alpha, X, strideX, ox ); +} + +/** +* Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_dfill_not_equal_ndarray)( const CBLAS_INT N, const double searchElement, const double alpha, double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] != searchElement ) { + X[ ix ] = alpha; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.dfill_not_equal.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.dfill_not_equal.js new file mode 100644 index 000000000000..13f6ada29a73 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.dfill_not_equal.js @@ -0,0 +1,247 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfillNotEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dfillNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, 2.0 ] ); + expected = new Float64Array( [ 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + + dfillNotEqual( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 1.0, NaN ] ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + + dfillNotEqual( x.length, NaN, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 0.0, NaN ] ); + expected = new Float64Array( [ 5.0, 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + + dfillNotEqual( 0, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + dfillNotEqual( -4, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, -0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + dfillNotEqual( 3, 0.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.dfill_not_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.dfill_not_equal.native.js new file mode 100644 index 000000000000..d09c559f5f64 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.dfill_not_equal.native.js @@ -0,0 +1,256 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfillNotEqual = tryRequire( resolve( __dirname, './../lib/dfill_not_equal.native.js' ) ); +var opts = { + 'skip': ( dfillNotEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dfillNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, 2.0 ] ); + expected = new Float64Array( [ 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + + dfillNotEqual( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 1.0, NaN ] ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + + dfillNotEqual( x.length, NaN, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 0.0, NaN ] ); + expected = new Float64Array( [ 5.0, 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + + dfillNotEqual( 0, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + dfillNotEqual( -4, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, -0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + dfillNotEqual( 3, 0.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.js new file mode 100644 index 000000000000..b86895d1a9c8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dfillNotEqual = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dfillNotEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dfillNotEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfillNotEqual, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dfillNotEqual; + var main; + + main = require( './../lib/dfill_not_equal.js' ); + + dfillNotEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfillNotEqual, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.ndarray.js new file mode 100644 index 000000000000..65ff7bb5df2e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.ndarray.js @@ -0,0 +1,241 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfillNotEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( dfillNotEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, 2.0 ] ); + expected = new Float64Array( [ 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + + dfillNotEqual( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 1.0, NaN ] ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + + dfillNotEqual( x.length, NaN, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 0.0, NaN ] ); + expected = new Float64Array( [ 5.0, 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, -0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + + dfillNotEqual( 0, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + dfillNotEqual( -4, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.ndarray.native.js new file mode 100644 index 000000000000..bf330de084ec --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfill-not-equal/test/test.ndarray.native.js @@ -0,0 +1,250 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfillNotEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfillNotEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( dfillNotEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float64Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, 2.0 ] ); + expected = new Float64Array( [ 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float64Array( [ 4.0, 4.0, 4.0 ] ); + + dfillNotEqual( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 1.0, NaN ] ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + + dfillNotEqual( x.length, NaN, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ NaN, 0.0, NaN ] ); + expected = new Float64Array( [ 5.0, 0.0, 5.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + x = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + dfillNotEqual( x.length, -0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat64Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + + dfillNotEqual( 0, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float64Array( [ 0.0, -4.0, 1.0 ] ); + dfillNotEqual( -4, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float64Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', opts, function test( t ) { + var expected; + var x; + + x = new Float64Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + dfillNotEqual( 3, 0.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/README.md new file mode 100644 index 000000000000..bd4969f05811 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/README.md @@ -0,0 +1,341 @@ + + +# dfirstIndexEqual + +> Return the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var dfirstIndexEqual = require( '@stdlib/blas/ext/base/dfirst-index-equal' ); +``` + +#### dfirstIndexEqual( N, x, strideX, y, strideY ) + +Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +var idx = dfirstIndexEqual( 4, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **y**: second input [`Float64Array`][@stdlib/array/float64]. +- **strideY**: stride length for `y`. + +If the function is unable to find a match, the function returns `-1`. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y = new Float64Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + +var idx = dfirstIndexEqual( 4, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to search every other element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 5.0, 0.0 ] ); + +var idx = dfirstIndexEqual( 3, x, 2, y, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = dfirstIndexEqual( 2, x1, 1, y1, 1 ); +// returns 1 +``` + +#### dfirstIndexEqual.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +var idx = dfirstIndexEqual.ndarray( 4, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting index. For example, to access only the last three elements of the strided arrays: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 6.0 ] ); + +var idx = dfirstIndexEqual.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 2 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct, and `-0` and `+0` are considered the same. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dfirstIndexEqual = require( '@stdlib/blas/ext/base/dfirst-index-equal' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( y ); + +var idx = dfirstIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); + +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dfirst_index_equal.h" +``` + +#### stdlib_strided_dfirst_index_equal( N, \*X, strideX, \*Y, strideY ) + +Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. + +```c +double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double y[] = { 0.0, 0.0, 3.0, 0.0 }; + +int idx = stdlib_strided_dfirst_index_equal( 4, x, 1, y, 1 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[in] double*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +CBLAS_INT stdlib_strided_dfirst_index_equal( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_dfirst_index_equal_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. + +```c +double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double y[] = { 0.0, 0.0, 3.0, 0.0 }; + +int idx = stdlib_strided_dfirst_index_equal_ndarray( 4, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[in] double*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +CBLAS_INT stdlib_strided_dfirst_index_equal_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dfirst_index_equal.h" +#include + +int main( void ) { + // Create strided arrays: + double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + double y[] = { 0.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Find the first index of a match: + int idx = stdlib_strided_dfirst_index_equal( N, x, strideX, y, strideY ); + + // Print the result: + printf( "first index: %d\n", idx ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..924080c11b54 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfirstIndexEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexEqual( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.native.js new file mode 100644 index 000000000000..479fe234279d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.native.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/dfirst_index_equal.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexEqual instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexEqual( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..f91dc1a281e6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfirstIndexEqual = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..91e9d73b8e32 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexEqual instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..c13362dc8c14 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/benchmark/c/benchmark.length.c @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_equal.h" +#include +#include +#include +#include +#include + +#define NAME "dfirst_index_equal" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int idx; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + y = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double()*20000.0 ) - 10000.0; + y[ i ] = -10001.0; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_dfirst_index_equal( len, x, 1, y, 1 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int idx; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + y = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double()*20000.0 ) - 10000.0; + y[ i ] = -10001.0; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_dfirst_index_equal_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/repl.txt new file mode 100644 index 000000000000..649441ce9b41 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/repl.txt @@ -0,0 +1,112 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a double-precision floating-point + strided array equal to a corresponding element in another double-precision + floating-point strided array. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + First input array. + + strideX: integer + Stride length for `x`. + + y: Float64Array + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 3.0, 0.0 ] ); + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0, 5.0, 0.0 ] ); + > idx = {{alias}}( 3, x, 2, y, 2 ) + 2 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var y0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 3.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); + > idx = {{alias}}( 2, x1, 1, y1, 1 ) + 1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a double-precision floating-point + strided array equal to a corresponding element in another double-precision + floating-point strided array using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float64Array + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 3.0, 0.0 ] ); + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using offsets: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0 ] ); + > idx = {{alias}}.ndarray( 3, x, 2, 1, y, 2, 2 ) + -1 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..834ebef251fa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/types/index.d.ts @@ -0,0 +1,111 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dfirstIndexEqual`. +*/ +interface Routine { + /** + * Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. + * + * ## Notes + * + * - If the function is unable to find a match, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + * + * var idx = dfirstIndexEqual( 4, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: Float64Array, strideX: number, y: Float64Array, strideY: number ): number; + + /** + * Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find a match, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + * + * var idx = dfirstIndexEqual.ndarray( 4, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number, y: Float64Array, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); +* +* var idx = dfirstIndexEqual( 4, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); +* +* var idx = dfirstIndexEqual.ndarray( 4, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var dfirstIndexEqual: Routine; + + +// EXPORTS // + +export = dfirstIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/types/test.ts new file mode 100644 index 000000000000..b16ef3584fa3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/docs/types/test.ts @@ -0,0 +1,206 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dfirstIndexEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual( x.length, x, 1, y, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual( '1', x, 1, y, 1 ); // $ExpectError + dfirstIndexEqual( true, x, 1, y, 1 ); // $ExpectError + dfirstIndexEqual( false, x, 1, y, 1 ); // $ExpectError + dfirstIndexEqual( null, x, 1, y, 1 ); // $ExpectError + dfirstIndexEqual( {}, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float64Array... +{ + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual( 3, '1', 1, y, 1 ); // $ExpectError + dfirstIndexEqual( 3, true, 1, y, 1 ); // $ExpectError + dfirstIndexEqual( 3, false, 1, y, 1 ); // $ExpectError + dfirstIndexEqual( 3, null, 1, y, 1 ); // $ExpectError + dfirstIndexEqual( 3, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual( x.length, x, '1', y, 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, true, y, 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, false, y, 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, null, y, 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, {}, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexEqual( x.length, x, 1, '1', 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, true, 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, false, 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, null, 1 ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual( x.length, x, 1, y, '1' ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, y, true ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, y, false ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, y, null ); // $ExpectError + dfirstIndexEqual( x.length, x, 1, y, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual(); // $ExpectError + dfirstIndexEqual( 3 ); // $ExpectError + dfirstIndexEqual( 3, x ); // $ExpectError + dfirstIndexEqual( 3, x, 1 ); // $ExpectError + dfirstIndexEqual( 3, x, 1, y ); // $ExpectError + dfirstIndexEqual( 3, x, 1, y, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array... +{ + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray( 3, '1', 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, true, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, false, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, null, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float64Array... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexEqual.ndarray( x.length, x, 1, 0, '1', 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + dfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 0.0, 2.0, 0.0 ] ); + + dfirstIndexEqual.ndarray(); // $ExpectError + dfirstIndexEqual.ndarray( 3 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, x ); // $ExpectError + dfirstIndexEqual.ndarray( 3, x, 1 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, x, 1, 0 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, x, 1, 0, y ); // $ExpectError + dfirstIndexEqual.ndarray( 3, x, 1, 0, y, 1 ); // $ExpectError + dfirstIndexEqual.ndarray( 3, x, 1, 0, y, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/c/example.c new file mode 100644 index 000000000000..ddc5695e011f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_equal.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + const double y[] = { 0.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Find the first index of a match: + int idx = stdlib_strided_dfirst_index_equal( N, x, strideX, y, strideY ); + + // Print the result: + printf( "first index: %d\n", idx ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/index.js new file mode 100644 index 000000000000..c092f2d9ff82 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dfirstIndexEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( y ); + +var idx = dfirstIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "find", + "index", + "search", + "element", + "equal", + "compare", + "array", + "ndarray", + "strided", + "double", + "float", + "float64", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/addon.c new file mode 100644 index 000000000000..787a6d7760e8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/addon.c @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_int32.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dfirst_index_equal)( N, X, strideX, Y, strideY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dfirst_index_equal_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/main.c new file mode 100644 index 000000000000..5371749d4e3d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/src/main.c @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_equal.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param Y second input array +* @param strideY stride length for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dfirst_index_equal)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + return API_SUFFIX(stdlib_strided_dfirst_index_equal_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Y second input array +* @param strideY stride length for Y +* @param offsetY starting index for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dfirst_index_equal_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + + if ( N <= 0 ) { + return -1; + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] == Y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.dfirst_index_equal.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.dfirst_index_equal.js new file mode 100644 index 000000000000..2c0353416ab5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.dfirst_index_equal.js @@ -0,0 +1,239 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfirstIndexEqual = require( './../lib/dfirst_index_equal.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dfirstIndexEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = dfirstIndexEqual( 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexEqual( -1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided elements equal to `NaN`', function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ NaN ] ), 1, new Float64Array( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ -0.0 ] ), 1, new Float64Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = dfirstIndexEqual( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.dfirst_index_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.dfirst_index_equal.native.js new file mode 100644 index 000000000000..6b1e78b9a70e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.dfirst_index_equal.native.js @@ -0,0 +1,248 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/dfirst_index_equal.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dfirstIndexEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { + var actual; + + actual = dfirstIndexEqual( 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexEqual( -1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided elements equal to `NaN`', opts, function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ NaN ] ), 1, new Float64Array( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', opts, function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ -0.0 ] ), 1, new Float64Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = dfirstIndexEqual( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.js new file mode 100644 index 000000000000..d67398f06c27 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dfirstIndexEqual = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dfirstIndexEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dfirstIndexEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfirstIndexEqual, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dfirstIndexEqual; + var main; + + main = require( './../lib/dfirst_index_equal.js' ); + + dfirstIndexEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfirstIndexEqual, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.ndarray.js new file mode 100644 index 000000000000..f236de9a4f42 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.ndarray.js @@ -0,0 +1,239 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfirstIndexEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( dfirstIndexEqual.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = dfirstIndexEqual( 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexEqual( -1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided elements equal to `NaN`', function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ NaN ] ), 1, 0, new Float64Array( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ -0.0 ] ), 1, 0, new Float64Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = dfirstIndexEqual( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.ndarray.native.js new file mode 100644 index 000000000000..3d08120524fb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-equal/test/test.ndarray.native.js @@ -0,0 +1,248 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( dfirstIndexEqual.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = dfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { + var actual; + + actual = dfirstIndexEqual( 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexEqual( -1, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided elements equal to `NaN`', opts, function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ NaN ] ), 1, 0, new Float64Array( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', opts, function test( t ) { + var actual; + + actual = dfirstIndexEqual( 1, new Float64Array( [ -0.0 ] ), 1, 0, new Float64Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = dfirstIndexEqual( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexEqual( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/README.md b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/README.md new file mode 100644 index 000000000000..6f18d1a15e71 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/README.md @@ -0,0 +1,344 @@ + + +# dfirstIndexLessThan + +> Return the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var dfirstIndexLessThan = require( '@stdlib/blas/ext/base/dfirst-index-less-than' ); +``` + +#### dfirstIndexLessThan( N, x, strideX, y, strideY ) + +Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + +var idx = dfirstIndexLessThan( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **y**: second input [`Float64Array`][@stdlib/array/float64]. +- **strideY**: stride length for `y`. + +If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 5.0, 6.0, 7.0, 8.0 ] ); +var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + +var idx = dfirstIndexLessThan( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compare every other element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Float64Array( [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + +var idx = dfirstIndexLessThan( 3, x, 2, y, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( [ 9.0, 0.0, 9.0, 9.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = dfirstIndexLessThan( 2, x1, 1, y1, 1 ); +// returns 1 +``` + + + +#### dfirstIndexLessThan.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + + + +Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + +var idx = dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last three elements of each strided array: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Float64Array( [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0 ] ); + +var idx = dfirstIndexLessThan.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 1 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks whether an element in `x` is less than a corresponding element in `y` using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dfirstIndexLessThan = require( '@stdlib/blas/ext/base/dfirst-index-less-than' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( y ); + +var idx = dfirstIndexLessThan( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dfirst_index_less_than.h" +``` + +#### stdlib_strided_dfirst_index_less_than( N, \*X, strideX, \*Y, strideY ) + +Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. + +```c +double x[] = { 0.0, 0.0, 0.0, 0.0 }; +double y[] = { 0.0, 0.0, 1.0, 0.0 }; + +int idx = stdlib_strided_dfirst_index_less_than( 4, x, 1, y, 1 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **Y**: `[in] double*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length. + +```c +CBLAS_INT stdlib_strided_dfirst_index_less_than( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_dfirst_index_less_than_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. + +```c +double x[] = { 0.0, 0.0, 0.0, 0.0 }; +double y[] = { 0.0, 0.0, 1.0, 0.0 }; + +int idx = stdlib_strided_dfirst_index_less_than_ndarray( 4, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. +- **Y**: `[in] double*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length. +- **offsetY**: `[in] CBLAS_INT` starting index. + +```c +CBLAS_INT stdlib_strided_dfirst_index_less_than_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dfirst_index_less_than.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0 }; + const double y[] = { 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify stride lengths: + const int strideX = 1; + const int strideY = 1; + + // Perform a search: + int idx = stdlib_strided_dfirst_index_less_than( N, x, strideX, y, strideY ); + + // Print the result: + printf( "index value: %d\n", idx ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.js new file mode 100644 index 000000000000..06ba9bf937ac --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfirstIndexLessThan = require( './../lib/dfirst_index_less_than.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexLessThan( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.native.js new file mode 100644 index 000000000000..f448a1da535c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.native.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/dfirst_index_less_than.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexLessThan instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexLessThan( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..ba3bdc717810 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.ndarray.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfirstIndexLessThan = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..15b342711c79 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexLessThan instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..49231c9f7f74 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/benchmark/c/benchmark.length.c @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_less_than.h" +#include +#include +#include +#include +#include + +#define NAME "dfirst_index_less_than" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int idx; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + y = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double()*20000.0 ) - 10000.0; + y[ i ] = -10001.0; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_dfirst_index_less_than( len, x, 1, y, 1 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int idx; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + y = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double()*20000.0 ) - 10000.0; + y[ i ] = -10001.0; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_dfirst_index_less_than_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/repl.txt new file mode 100644 index 000000000000..4f8e1407a594 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/repl.txt @@ -0,0 +1,118 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a double-precision floating-point + strided array which is less than a corresponding element in another double- + precision floating-point strided array. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + First input array. + + strideX: integer + Stride length for `x`. + + y: Float64Array + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + > idx = {{alias}}( 3, x, 2, y, 2 ) + 2 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y0 = new {{alias:@stdlib/array/float64}}( [ 9.0, 0.0, 9.0, 9.0 ] ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); + > var idx = {{alias}}( 2, x1, 1, y1, 1 ) + 1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a double-precision floating-point + strided array which is less than a corresponding element in another double- + precision floating-point strided array using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on + starting indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float64Array + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var y = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + > idx = {{alias}}.ndarray( 3, x, 2, 0, y, 2, 0 ) + 2 + + // Using an index offset: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 9.0, 2.0, 9.0, 9.0 ] ); + > idx = {{alias}}.ndarray( 2, x, 1, 1, y, 1, 1 ) + 1 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/types/index.d.ts new file mode 100644 index 000000000000..c9e459927f55 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/types/index.d.ts @@ -0,0 +1,115 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dfirstIndexLessThan`. +*/ +interface Routine { + /** + * Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * var idx = dfirstIndexLessThan( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: Float64Array, strideX: number, y: Float64Array, strideY: number ): number; + + /** + * Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * var idx = dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number, y: Float64Array, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. +* +* ## Notes +* +* - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +* var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* var idx = dfirstIndexLessThan( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +* var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* var idx = dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var dfirstIndexLessThan: Routine; + + +// EXPORTS // + +export = dfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/types/test.ts new file mode 100644 index 000000000000..2d3f8236839b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/docs/types/test.ts @@ -0,0 +1,207 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dfirstIndexLessThan = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan( x.length, x, 1, y, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan( '1', x, 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( true, x, 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( false, x, 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( null, x, 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( {}, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float64Array... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan( x.length, '1', 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, true, 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, false, 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, null, 1, y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan( x.length, x, '1', y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, true, y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, false, y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, null, y, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, {}, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan( x.length, x, 1, '1', 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, true, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, false, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, null, 1 ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan( x.length, x, 1, y, '1' ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, y, true ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, y, false ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, y, null ); // $ExpectError + dfirstIndexLessThan( x.length, x, 1, y, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan(); // $ExpectError + dfirstIndexLessThan( 3, x ); // $ExpectError + dfirstIndexLessThan( 3, x, 1 ); // $ExpectError + dfirstIndexLessThan( 3, x, 1, y ); // $ExpectError + dfirstIndexLessThan( 3, x, 1, y, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( x.length, '1', 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, true, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, false, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, null, 1, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float64Array... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, '1', 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError +} + + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dfirstIndexLessThan.ndarray(); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/c/example.c new file mode 100644 index 000000000000..73c81b87173c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_less_than.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0 }; + const double y[] = { 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify stride lengths: + const int strideX = 1; + const int strideY = 1; + + // Perform a search: + int idx = stdlib_strided_dfirst_index_less_than( N, x, strideX, y, strideY ); + + // Print the result: + printf( "index value: %d\n", idx ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/index.js new file mode 100644 index 000000000000..c909a8aeb0a6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dfirstIndexLessThan = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float64' +}); +console.log( y ); + +var idx = dfirstIndexLessThan( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "find", + "index", + "search", + "element", + "array", + "ndarray", + "strided", + "double", + "float", + "float64", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/addon.c new file mode 100644 index 000000000000..f36dbdb54446 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/addon.c @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_less_than.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_int32.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dfirst_index_less_than)( N, X, strideX, Y, strideY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dfirst_index_less_than_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/main.c new file mode 100644 index 000000000000..a0232c3da79e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/src/main.c @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dfirst_index_less_than.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param Y second input array +* @param strideY stride length for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dfirst_index_less_than)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + return API_SUFFIX(stdlib_strided_dfirst_index_less_than_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Y second input array +* @param strideY stride length for Y +* @param offsetY starting index for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dfirst_index_less_than_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + + if ( N <= 0 ) { + return -1; + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] < Y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.dfirst_index_less_than.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.dfirst_index_less_than.js new file mode 100644 index 000000000000..7c95a2a21eb7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.dfirst_index_less_than.js @@ -0,0 +1,270 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfirstIndexLessThan = require( './../lib/dfirst_index_less_than.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexLessThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 1, y, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = dfirstIndexLessThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float64Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -1, y, -2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, y, -2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dfirstIndexLessThan( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ NaN ] ), 1, new Float64Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( 1, new Float64Array( [ 0.0 ] ), 1, new Float64Array( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ -0.0 ] ), 1, new Float64Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float64Array([ + 6.0, + 0.0, // 2 + 5.0, + 1.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = dfirstIndexLessThan( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.dfirst_index_less_than.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.dfirst_index_less_than.native.js new file mode 100644 index 000000000000..01af96a0fc89 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.dfirst_index_less_than.native.js @@ -0,0 +1,279 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/dfirst_index_less_than.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexLessThan instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexLessThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 1, y, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = dfirstIndexLessThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float64Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -1, y, -2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, y, -2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dfirstIndexLessThan( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', opts, function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ NaN ] ), 1, new Float64Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( 1, new Float64Array( [ 0.0 ] ), 1, new Float64Array( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', opts, function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ -0.0 ] ), 1, new Float64Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float64Array([ + 6.0, + 0.0, // 2 + 5.0, + 1.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = dfirstIndexLessThan( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.js new file mode 100644 index 000000000000..04cddc54da24 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dfirstIndexLessThan = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dfirstIndexLessThan.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dfirstIndexLessThan = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfirstIndexLessThan, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dfirstIndexLessThan; + var main; + + main = require( './../lib/dfirst_index_less_than.js' ); + + dfirstIndexLessThan = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dfirstIndexLessThan, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.ndarray.js new file mode 100644 index 000000000000..11b1ebdf9046 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.ndarray.js @@ -0,0 +1,284 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfirstIndexLessThan = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = dfirstIndexLessThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float64Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -1, 2, y, -2, 4 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, 4, y, -2, 4 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dfirstIndexLessThan( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( -1, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ NaN ] ), 1, 0, new Float64Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( 1, new Float64Array( [ 0.0 ] ), 1, 0, new Float64Array( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ -0.0 ] ), 1, 0, new Float64Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 5.0, + 5.0, + 5.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float64Array([ + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, 2, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float64Array([ + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, 0, y, 1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.ndarray.native.js new file mode 100644 index 000000000000..0aff544155b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dfirst-index-less-than/test/test.ndarray.native.js @@ -0,0 +1,293 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dfirstIndexLessThan instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = dfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float64Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float64Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float64Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = dfirstIndexLessThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float64Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float64Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -1, 2, y, -2, 4 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float64Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float64Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = dfirstIndexLessThan( 3, x, -2, 4, y, -2, 4 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dfirstIndexLessThan( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( -1, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', opts, function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ NaN ] ), 1, 0, new Float64Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dfirstIndexLessThan( 1, new Float64Array( [ 0.0 ] ), 1, 0, new Float64Array( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', opts, function test( t ) { + var actual; + + actual = dfirstIndexLessThan( 1, new Float64Array( [ -0.0 ] ), 1, 0, new Float64Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float64Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float64Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float64Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 5.0, + 5.0, + 5.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float64Array([ + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, 2, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float64Array([ + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = dfirstIndexLessThan( 3, x, 1, 0, y, 1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float64Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = dfirstIndexLessThan( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/README.md new file mode 100644 index 000000000000..62662a531dbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/README.md @@ -0,0 +1,319 @@ + + +# dindexOfNotEqual + +> Return the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var dindexOfNotEqual = require( '@stdlib/blas/ext/base/dindex-of-not-equal' ); +``` + +#### dindexOfNotEqual( N, searchElement, x, strideX ) + +Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); + +var idx = dindexOfNotEqual( x.length, 1.0, x, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length. + +If all elements in the array are equal to the search element, the function returns `-1`. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 1.0, 1.0, 1.0 ] ); + +var idx = dindexOfNotEqual( x.length, 1.0, x, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to search every other element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 9.0, 0.0, 9.0, 1.0, 9.0 ] ); + +var idx = dindexOfNotEqual( 3, 1.0, x, 2 ); +// returns 1 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +// Create an offset view... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = dindexOfNotEqual( 3, 2.0, x1, 2 ); +// returns 1 +``` + +#### dindexOfNotEqual.ndarray( N, searchElement, x, strideX, offsetX ) + +Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); + +var idx = dindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); + +var idx = dindexOfNotEqual.ndarray( 3, 1.0, x, 1, 1 ); +// returns 1 +``` + +
+ + + + + +
+ +## Notes + +- When searching for a search element, the function checks for inequality using the strict inequality operator `!==`. As a consequence, `NaN` values are considered distinct from all values (including other `NaN` values), and `-0` and `+0` are considered the same. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dindexOfNotEqual = require( '@stdlib/blas/ext/base/dindex-of-not-equal' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'float64' +}); +console.log( x ); + +var idx = dindexOfNotEqual( x.length, 0.0, x, 1 ); +console.log( idx ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dindex_of_not_equal.h" +``` + +#### stdlib_strided_dindex_of_not_equal( N, searchElement, \*X, strideX ) + +Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. + +```c +double x[] = { 1.0, 1.0, 0.0, 1.0 }; + +int idx = stdlib_strided_dindex_of_not_equal( 4, 1.0, x, 1 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] double` search element. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +CBLAS_INT stdlib_strided_dindex_of_not_equal( const CBLAS_INT N, const double searchElement, const double *X, const CBLAS_INT strideX ); +``` + + + +#### stdlib_strided_dindex_of_not_equal_ndarray( N, searchElement, \*X, strideX, offsetX ) + + + +Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element using alternative indexing semantics. + +```c +double x[] = { 1.0, 1.0, 0.0, 1.0 }; + +int idx = stdlib_strided_dindex_of_not_equal_ndarray( 4, 1.0, x, 1, 0 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] double` search element. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +CBLAS_INT stdlib_strided_dindex_of_not_equal_ndarray( const CBLAS_INT N, const double searchElement, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dindex_of_not_equal.h" +#include + +int main( void ) { + // Create a strided array: + double x[] = { 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 0.0, 1.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Perform a search: + int idx = stdlib_strided_dindex_of_not_equal( N, 1.0, x, strideX ); + + // Print the result: + printf( "index value: %d\n", idx ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..86f59748f1a2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dindexOfNotEqual = require( './../lib/dindex_of_not_equal.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dindexOfNotEqual( x.length, 0.0, x, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.native.js new file mode 100644 index 000000000000..89a3d4c89204 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.native.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dindexOfNotEqual = tryRequire( resolve( __dirname, './../lib/dindex_of_not_equal.native.js' ) ); +var opts = { + 'skip': ( dindexOfNotEqual instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dindexOfNotEqual( x.length, 0.0, x, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..9b7c17a3766b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dindexOfNotEqual = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dindexOfNotEqual( x.length, 0.0, x, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..41d6b462c33a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dindexOfNotEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dindexOfNotEqual instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dindexOfNotEqual( x.length, 0.0, x, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..7824ed0490c8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/benchmark/c/benchmark.length.c @@ -0,0 +1,197 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dindex_of_not_equal.h" +#include +#include +#include +#include +#include + +#define NAME "dindex_of_not_equal" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double t; + int idx; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = 0.0; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_dindex_of_not_equal( len, 0.0, x, 1 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double t; + int idx; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = 0.0; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_dindex_of_not_equal_ndarray( len, 0.0, x, 1, 0 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/repl.txt new file mode 100644 index 000000000000..25a5b034fb96 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/repl.txt @@ -0,0 +1,96 @@ + +{{alias}}( N, searchElement, x, strideX ) + Returns the first index of an element in a double-precision floating-point + strided array which is not equal to a specified search element. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 0.0, 1.0 ] ); + > var idx = {{alias}}( x.length, 1.0, x, 1 ) + 2 + + // Using `N` and stride parameters: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 9.0, 0.0, 9.0, 1.0, 9.0 ] ); + > var idx = {{alias}}( 3, 1.0, x, 2 ) + 1 + + // View offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 1.0, 1.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var idx = {{alias}}( 2, 1.0, x1, 1 ) + 0 + + +{{alias}}.ndarray( N, searchElement, x, strideX, offsetX ) + Returns the first index of an element in a double-precision floating-point + strided array which is not equal to a specified search element using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a + starting index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + x: Float64Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, 0.0, 1.0 ] ); + > var idx = {{alias}}.ndarray( x.length, 1.0, x, 1, 0 ) + 2 + + // Advanced indexing: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 1.0, 3.0, 1.0, 4.0 ] ); + > var idx = {{alias}}.ndarray( 3, 1.0, x, 2, 1 ) + 0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..ac700a017a3e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/types/index.d.ts @@ -0,0 +1,107 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dindexOfNotEqual`. +*/ +interface Routine { + /** + * Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. + * + * ## Notes + * + * - If all elements are equal to the search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); + * + * var idx = dindexOfNotEqual( x.length, 1.0, x, 1 ); + * // returns 2 + */ + ( N: number, searchElement: number, x: Float64Array, strideX: number ): number; + + /** + * Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element using alternative indexing semantics. + * + * ## Notes + * + * - If all elements are equal to the search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); + * + * var idx = dindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, searchElement: number, x: Float64Array, strideX: number, offsetX: number ): number; +} + +/** +* Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. +* +* ## Notes +* +* - If all elements are equal to the search element, the function returns `-1`. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param x - input array +* @param strideX - stride length +* @returns index +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); +* +* var idx = dindexOfNotEqual( x.length, 1.0, x, 1 ); +* // returns 2 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); +* +* var idx = dindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); +* // returns 2 +*/ +declare var dindexOfNotEqual: Routine; + + +// EXPORTS // + +export = dindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..fff8d364263d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/docs/types/test.ts @@ -0,0 +1,148 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dindexOfNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual( x.length, 2.0, x, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual( '1', 2.0, x, 1 ); // $ExpectError + dindexOfNotEqual( true, 2.0, x, 1 ); // $ExpectError + dindexOfNotEqual( false, 2.0, x, 1 ); // $ExpectError + dindexOfNotEqual( null, 2.0, x, 1 ); // $ExpectError + dindexOfNotEqual( {}, 2.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual( x.length, '1', x, 1 ); // $ExpectError + dindexOfNotEqual( x.length, true, x, 1 ); // $ExpectError + dindexOfNotEqual( x.length, false, x, 1 ); // $ExpectError + dindexOfNotEqual( x.length, null, x, 1 ); // $ExpectError + dindexOfNotEqual( x.length, {}, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float64Array... +{ + dindexOfNotEqual( x.length, 1.0, '1', 1 ); // $ExpectError + dindexOfNotEqual( x.length, 1.0, true, 1 ); // $ExpectError + dindexOfNotEqual( x.length, 1.0, false, 1 ); // $ExpectError + dindexOfNotEqual( x.length, 1.0, null, 1 ); // $ExpectError + dindexOfNotEqual( x.length, 1.0, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual( x.length, 2.0, x, '1' ); // $ExpectError + dindexOfNotEqual( x.length, 2.0, x, true ); // $ExpectError + dindexOfNotEqual( x.length, 2.0, x, false ); // $ExpectError + dindexOfNotEqual( x.length, 2.0, x, null ); // $ExpectError + dindexOfNotEqual( x.length, 2.0, x, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + dindexOfNotEqual(); // $ExpectError + dindexOfNotEqual( 3, 2.0 ); // $ExpectError + dindexOfNotEqual( 3, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ) ); // $ExpectError + dindexOfNotEqual( 3, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual.ndarray( x.length, 2.0, x, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual.ndarray( '1', 2.0, x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( true, 2.0, x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( false, 2.0, x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( null, 2.0, x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( {}, 2.0, x, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual.ndarray( x.length, '1', x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, true, x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, false, x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, null, x, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, {}, x, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float64Array... +{ + dindexOfNotEqual.ndarray( x.length, 1.0, '1', 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 1.0, true, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 1.0, false, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 1.0, null, 1, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 1.0, {}, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual.ndarray( x.length, 2.0, x, '1', 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, true, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, false, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, null, 1 ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + dindexOfNotEqual.ndarray( x.length, 2.0, x, 1, '1' ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, 1, true ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, 1, false ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, 1, null ); // $ExpectError + dindexOfNotEqual.ndarray( x.length, 2.0, x, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + dindexOfNotEqual.ndarray(); // $ExpectError + dindexOfNotEqual.ndarray( 3, 2.0 ); // $ExpectError + dindexOfNotEqual.ndarray( 3, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ) ); // $ExpectError + dindexOfNotEqual.ndarray( 3, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); // $ExpectError + dindexOfNotEqual.ndarray( 3, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/c/example.c new file mode 100644 index 000000000000..eb2e1cb1bec4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/c/example.c @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dindex_of_not_equal.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 0.0, 1.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Perform a search: + int idx = stdlib_strided_dindex_of_not_equal( N, 1.0, x, strideX ); + + // Print the result: + printf( "index value: %d\n", idx ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/index.js new file mode 100644 index 000000000000..c8d106292fa1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dindexOfNotEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'float64' +}); +console.log( x ); + +var idx = dindexOfNotEqual( x.length, 0.0, x, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "find", + "index", + "search", + "element", + "array", + "ndarray", + "strided", + "double", + "float", + "float64", + "float64array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/addon.c new file mode 100644 index 000000000000..3233b34bdedb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/addon.c @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dindex_of_not_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include "stdlib/napi/create_int32.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dindex_of_not_equal)( N, searchElement, X, strideX ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_dindex_of_not_equal_ndarray)( N, searchElement, X, strideX, offsetX ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/main.c new file mode 100644 index 000000000000..3e20e3be1e43 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/src/main.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dindex_of_not_equal.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. +* +* @param N number of indexed elements +* @param searchElement search element +* @param X input array +* @param strideX stride length +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dindex_of_not_equal)( const CBLAS_INT N, const double searchElement, const double *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_dindex_of_not_equal_ndarray)( N, searchElement, X, strideX, ox ); +} + +/** +* Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element using alternative indexing semantics. +* +* @param N number of indexed elements +* @param searchElement search element +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_dindex_of_not_equal_ndarray)( const CBLAS_INT N, const double searchElement, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return -1; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] != searchElement ) { + return i; + } + ix += strideX; + } + return -1; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.dindex_of_not_equal.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.dindex_of_not_equal.js new file mode 100644 index 000000000000..031bcd089736 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.dindex_of_not_equal.js @@ -0,0 +1,176 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dindexOfNotEqual = require( './../lib/dindex_of_not_equal.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( dindexOfNotEqual.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = dindexOfNotEqual( x.length, 1.0, x, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + actual = dindexOfNotEqual( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 2.0, 2.0, 2.0 ] ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dindexOfNotEqual( 0, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dindexOfNotEqual( -1, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN`', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ NaN, 1.0 ] ); + + actual = dindexOfNotEqual( 2, NaN, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 1.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 1.0, x, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 0.0, 1.0 ] ); + + actual = dindexOfNotEqual( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 1.0, // 0 + 9.0, + 1.0, // 1 + 9.0, + 0.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 1.0, x, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var x1; + + x0 = new Float64Array( [ 9.0, 0.0, 1.0, 0.0, 0.0 ] ); + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + actual = dindexOfNotEqual( 3, 0.0, x1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.dindex_of_not_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.dindex_of_not_equal.native.js new file mode 100644 index 000000000000..7b5ee6595253 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.dindex_of_not_equal.native.js @@ -0,0 +1,185 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dindexOfNotEqual = tryRequire( resolve( __dirname, './../lib/dindex_of_not_equal.native.js' ) ); +var opts = { + 'skip': ( dindexOfNotEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', opts, function test( t ) { + t.strictEqual( dindexOfNotEqual.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = dindexOfNotEqual( x.length, 1.0, x, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + actual = dindexOfNotEqual( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 2.0, 2.0, 2.0 ] ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dindexOfNotEqual( 0, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dindexOfNotEqual( -1, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN`', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ NaN, 1.0 ] ); + + actual = dindexOfNotEqual( 2, NaN, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 1.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 1.0, x, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 0.0, 1.0 ] ); + + actual = dindexOfNotEqual( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 1.0, // 0 + 9.0, + 1.0, // 1 + 9.0, + 0.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 1.0, x, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var actual; + var x0; + var x1; + + x0 = new Float64Array( [ 9.0, 0.0, 1.0, 0.0, 0.0 ] ); + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + actual = dindexOfNotEqual( 3, 0.0, x1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.js new file mode 100644 index 000000000000..c81c9a7c4bd3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dindexOfNotEqual = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dindexOfNotEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dindexOfNotEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dindexOfNotEqual, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dindexOfNotEqual; + var main; + + main = require( './../lib/dindex_of_not_equal.js' ); + + dindexOfNotEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dindexOfNotEqual, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.ndarray.js new file mode 100644 index 000000000000..ecd2cdab08aa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.ndarray.js @@ -0,0 +1,182 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dindexOfNotEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dindexOfNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = dindexOfNotEqual( x.length, 1.0, x, 1, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + actual = dindexOfNotEqual( x.length, 1.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, -1, x.length-1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 2.0, 2.0, 2.0 ] ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dindexOfNotEqual( 0, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dindexOfNotEqual( -1, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN`', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ NaN, 1.0 ] ); + + actual = dindexOfNotEqual( 2, NaN, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 0.0, x, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 0.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ] ); + + actual = dindexOfNotEqual( x.length, 0.0, x, -1, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 0.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.ndarray.native.js new file mode 100644 index 000000000000..2d2cfb19eaa6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of-not-equal/test/test.ndarray.native.js @@ -0,0 +1,191 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dindexOfNotEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dindexOfNotEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dindexOfNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = dindexOfNotEqual( x.length, 1.0, x, 1, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + actual = dindexOfNotEqual( x.length, 1.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 2.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 3.0, x, -1, x.length-1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = dindexOfNotEqual( x.length, 4.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 2.0, 2.0, 2.0 ] ); + + actual = dindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + + actual = dindexOfNotEqual( 0, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = dindexOfNotEqual( -1, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN`', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ NaN, 1.0 ] ); + + actual = dindexOfNotEqual( 2, NaN, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 0.0, x, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 0.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array( [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ] ); + + actual = dindexOfNotEqual( x.length, 0.0, x, -1, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + + x = new Float64Array([ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]); + + actual = dindexOfNotEqual( 3, 0.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/docs/repl.txt index aba41e1e989f..524a31cce7dc 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/docs/repl.txt @@ -37,7 +37,7 @@ 1 -{{alias}}( N, searchElement, x, strideX, offsetX ) +{{alias}}.ndarray( N, searchElement, x, strideX, offsetX ) Returns the first index of a specified search element in a double-precision floating-point strided array using alternative indexing semantics. diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.js index 2918d8060815..5d0238a31de1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.js @@ -68,7 +68,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; actual = dindexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.native.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.native.js index 2053cd306916..581e8806dc6c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.dindex_of.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = dindexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.js index 53afe4bfc888..839d9b94f244 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.js @@ -68,7 +68,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; actual = dindexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.native.js index f4679eae5f3d..fc8274101c79 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dindex-of/test/test.ndarray.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = dindexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/lib/ndarray.js index 82bdac9c0131..c56004585907 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/lib/ndarray.js @@ -58,8 +58,7 @@ function dlastIndexOf( N, searchElement, x, strideX, offsetX ) { return idx; } // Convert the index from reversed "view" to an index in the original "view": - idx = N - 1 - idx; - return idx; + return N - 1 - idx; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.js b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.js index a97f3c8354a3..ab7675d06166 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.js @@ -68,7 +68,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; actual = dlastIndexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.native.js b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.native.js index bc4dda495805..40294f80972c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.dlast_index_of.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = dlastIndexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.js index 6d843ef4f5e4..e057f6d6ddd1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.js @@ -68,7 +68,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; actual = dlastIndexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.native.js index 8e6a168ecb1c..0113dae2e25e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/dlast-index-of/test/test.ndarray.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = dlastIndexOf( 0, 2.0, new Float64Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts index dcd3eb30cfd0..5e874001469f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts @@ -30,12 +30,15 @@ import cindexOfColumn = require( '@stdlib/blas/ext/base/cindex-of-column' ); import cindexOfRow = require( '@stdlib/blas/ext/base/cindex-of-row' ); import clastIndexOfRow = require( '@stdlib/blas/ext/base/clast-index-of-row' ); import coneTo = require( '@stdlib/blas/ext/base/cone-to' ); +import creplicate = require( '@stdlib/blas/ext/base/creplicate' ); import csum = require( '@stdlib/blas/ext/base/csum' ); import csumkbn = require( '@stdlib/blas/ext/base/csumkbn' ); import cunitspace = require( '@stdlib/blas/ext/base/cunitspace' ); import cwapx = require( '@stdlib/blas/ext/base/cwapx' ); +import cwax = require( '@stdlib/blas/ext/base/cwax' ); import cwhere = require( '@stdlib/blas/ext/base/cwhere' ); import cwxsa = require( '@stdlib/blas/ext/base/cwxsa' ); +import cxmy = require( '@stdlib/blas/ext/base/cxmy' ); import cxpy = require( '@stdlib/blas/ext/base/cxpy' ); import cxsa = require( '@stdlib/blas/ext/base/cxsa' ); import cxsy = require( '@stdlib/blas/ext/base/cxsy' ); @@ -66,9 +69,15 @@ import dcusumpw = require( '@stdlib/blas/ext/base/dcusumpw' ); import ddiff = require( '@stdlib/blas/ext/base/ddiff' ); import dediff = require( '@stdlib/blas/ext/base/dediff' ); import dfill = require( '@stdlib/blas/ext/base/dfill' ); +import dfillEqual = require( '@stdlib/blas/ext/base/dfill-equal' ); +import dfillNaN = require( '@stdlib/blas/ext/base/dfill-nan' ); +import dfillNotEqual = require( '@stdlib/blas/ext/base/dfill-not-equal' ); +import dfirstIndexEqual = require( '@stdlib/blas/ext/base/dfirst-index-equal' ); +import dfirstIndexLessThan = require( '@stdlib/blas/ext/base/dfirst-index-less-than' ); import dindexOf = require( '@stdlib/blas/ext/base/dindex-of' ); import dindexOfColumn = require( '@stdlib/blas/ext/base/dindex-of-column' ); import dindexOfFalsy = require( '@stdlib/blas/ext/base/dindex-of-falsy' ); +import dindexOfNotEqual = require( '@stdlib/blas/ext/base/dindex-of-not-equal' ); import dindexOfRow = require( '@stdlib/blas/ext/base/dindex-of-row' ); import dindexOfTruthy = require( '@stdlib/blas/ext/base/dindex-of-truthy' ); import dlastIndexOf = require( '@stdlib/blas/ext/base/dlast-index-of' ); @@ -96,6 +105,7 @@ import dnansumpw = require( '@stdlib/blas/ext/base/dnansumpw' ); import dnone = require( '@stdlib/blas/ext/base/dnone' ); import doneTo = require( '@stdlib/blas/ext/base/done-to' ); import dones = require( '@stdlib/blas/ext/base/dones' ); +import dreplicate = require( '@stdlib/blas/ext/base/dreplicate' ); import drev = require( '@stdlib/blas/ext/base/drev' ); import drrss = require( '@stdlib/blas/ext/base/drrss' ); import drss = require( '@stdlib/blas/ext/base/drss' ); @@ -126,8 +136,10 @@ import dsumpw = require( '@stdlib/blas/ext/base/dsumpw' ); import dunitspace = require( '@stdlib/blas/ext/base/dunitspace' ); import dvander = require( '@stdlib/blas/ext/base/dvander' ); import dwapx = require( '@stdlib/blas/ext/base/dwapx' ); +import dwax = require( '@stdlib/blas/ext/base/dwax' ); import dwhere = require( '@stdlib/blas/ext/base/dwhere' ); import dwxsa = require( '@stdlib/blas/ext/base/dwxsa' ); +import dxdy = require( '@stdlib/blas/ext/base/dxdy' ); import dxmy = require( '@stdlib/blas/ext/base/dxmy' ); import dxpy = require( '@stdlib/blas/ext/base/dxpy' ); import dxsa = require( '@stdlib/blas/ext/base/dxsa' ); @@ -163,15 +175,26 @@ import gediff = require( '@stdlib/blas/ext/base/gediff' ); import gevery = require( '@stdlib/blas/ext/base/gevery' ); import gfill = require( '@stdlib/blas/ext/base/gfill' ); import gfillBy = require( '@stdlib/blas/ext/base/gfill-by' ); +import gfillEqual = require( '@stdlib/blas/ext/base/gfill-equal' ); +import gfillLessThan = require( '@stdlib/blas/ext/base/gfill-less-than' ); +import gfillNaN = require( '@stdlib/blas/ext/base/gfill-nan' ); +import gfillNotEqual = require( '@stdlib/blas/ext/base/gfill-not-equal' ); import gfindIndex = require( '@stdlib/blas/ext/base/gfind-index' ); import gfindLastIndex = require( '@stdlib/blas/ext/base/gfind-last-index' ); +import gfirstIndexEqual = require( '@stdlib/blas/ext/base/gfirst-index-equal' ); +import gfirstIndexGreaterThan = require( '@stdlib/blas/ext/base/gfirst-index-greater-than' ); +import gfirstIndexLessThan = require( '@stdlib/blas/ext/base/gfirst-index-less-than' ); +import gfirstIndexNotEqual = require( '@stdlib/blas/ext/base/gfirst-index-not-equal' ); import gindexOf = require( '@stdlib/blas/ext/base/gindex-of' ); import gindexOfColumn = require( '@stdlib/blas/ext/base/gindex-of-column' ); import gindexOfFalsy = require( '@stdlib/blas/ext/base/gindex-of-falsy' ); +import gindexOfNotEqual = require( '@stdlib/blas/ext/base/gindex-of-not-equal' ); import gindexOfRow = require( '@stdlib/blas/ext/base/gindex-of-row' ); +import gindexOfSameValue = require( '@stdlib/blas/ext/base/gindex-of-same-value' ); import gindexOfTruthy = require( '@stdlib/blas/ext/base/gindex-of-truthy' ); import gjoin = require( '@stdlib/blas/ext/base/gjoin' ); import gjoinBetween = require( '@stdlib/blas/ext/base/gjoin-between' ); +import glastIndexEqual = require( '@stdlib/blas/ext/base/glast-index-equal' ); import glastIndexOf = require( '@stdlib/blas/ext/base/glast-index-of' ); import glastIndexOfFalsy = require( '@stdlib/blas/ext/base/glast-index-of-falsy' ); import glastIndexOfRow = require( '@stdlib/blas/ext/base/glast-index-of-row' ); @@ -215,6 +238,7 @@ import gwhere = require( '@stdlib/blas/ext/base/gwhere' ); import gwxpy = require( '@stdlib/blas/ext/base/gwxpy' ); import gwxsa = require( '@stdlib/blas/ext/base/gwxsa' ); import gwxsy = require( '@stdlib/blas/ext/base/gwxsy' ); +import gxdy = require( '@stdlib/blas/ext/base/gxdy' ); import gxmy = require( '@stdlib/blas/ext/base/gxmy' ); import gxpy = require( '@stdlib/blas/ext/base/gxpy' ); import gxsa = require( '@stdlib/blas/ext/base/gxsa' ); @@ -253,6 +277,11 @@ import sdssum = require( '@stdlib/blas/ext/base/sdssum' ); import sdssumpw = require( '@stdlib/blas/ext/base/sdssumpw' ); import sediff = require( '@stdlib/blas/ext/base/sediff' ); import sfill = require( '@stdlib/blas/ext/base/sfill' ); +import sfillEqual = require( '@stdlib/blas/ext/base/sfill-equal' ); +import sfillNaN = require( '@stdlib/blas/ext/base/sfill-nan' ); +import sfillNotEqual = require( '@stdlib/blas/ext/base/sfill-not-equal' ); +import sfirstIndexEqual = require( '@stdlib/blas/ext/base/sfirst-index-equal' ); +import sfirstIndexLessThan = require( '@stdlib/blas/ext/base/sfirst-index-less-than' ); import sindexOf = require( '@stdlib/blas/ext/base/sindex-of' ); import sindexOfColumn = require( '@stdlib/blas/ext/base/sindex-of-column' ); import sindexOfFalsy = require( '@stdlib/blas/ext/base/sindex-of-falsy' ); @@ -275,6 +304,7 @@ import snansumpw = require( '@stdlib/blas/ext/base/snansumpw' ); import snone = require( '@stdlib/blas/ext/base/snone' ); import soneTo = require( '@stdlib/blas/ext/base/sone-to' ); import sones = require( '@stdlib/blas/ext/base/sones' ); +import sreplicate = require( '@stdlib/blas/ext/base/sreplicate' ); import srev = require( '@stdlib/blas/ext/base/srev' ); import ssome = require( '@stdlib/blas/ext/base/ssome' ); import ssort = require( '@stdlib/blas/ext/base/ssort' ); @@ -292,8 +322,10 @@ import ssumpw = require( '@stdlib/blas/ext/base/ssumpw' ); import sunitspace = require( '@stdlib/blas/ext/base/sunitspace' ); import svander = require( '@stdlib/blas/ext/base/svander' ); import swapx = require( '@stdlib/blas/ext/base/swapx' ); +import swax = require( '@stdlib/blas/ext/base/swax' ); import swhere = require( '@stdlib/blas/ext/base/swhere' ); import swxsa = require( '@stdlib/blas/ext/base/swxsa' ); +import sxdy = require( '@stdlib/blas/ext/base/sxdy' ); import sxmy = require( '@stdlib/blas/ext/base/sxmy' ); import sxpy = require( '@stdlib/blas/ext/base/sxpy' ); import sxsa = require( '@stdlib/blas/ext/base/sxsa' ); @@ -309,15 +341,20 @@ import zfill = require( '@stdlib/blas/ext/base/zfill' ); import zindexOf = require( '@stdlib/blas/ext/base/zindex-of' ); import zindexOfColumn = require( '@stdlib/blas/ext/base/zindex-of-column' ); import zindexOfRow = require( '@stdlib/blas/ext/base/zindex-of-row' ); +import zindexOfTruthy = require( '@stdlib/blas/ext/base/zindex-of-truthy' ); import zlastIndexOfRow = require( '@stdlib/blas/ext/base/zlast-index-of-row' ); import znancount = require( '@stdlib/blas/ext/base/znancount' ); import zoneTo = require( '@stdlib/blas/ext/base/zone-to' ); +import zreplicate = require( '@stdlib/blas/ext/base/zreplicate' ); import zsum = require( '@stdlib/blas/ext/base/zsum' ); import zsumkbn = require( '@stdlib/blas/ext/base/zsumkbn' ); import zunitspace = require( '@stdlib/blas/ext/base/zunitspace' ); import zwapx = require( '@stdlib/blas/ext/base/zwapx' ); +import zwax = require( '@stdlib/blas/ext/base/zwax' ); import zwhere = require( '@stdlib/blas/ext/base/zwhere' ); import zwxsa = require( '@stdlib/blas/ext/base/zwxsa' ); +import zxdy = require( '@stdlib/blas/ext/base/zxdy' ); +import zxmy = require( '@stdlib/blas/ext/base/zxmy' ); import zxpy = require( '@stdlib/blas/ext/base/zxpy' ); import zxsa = require( '@stdlib/blas/ext/base/zxsa' ); import zxsy = require( '@stdlib/blas/ext/base/zxsy' ); @@ -709,6 +746,37 @@ interface Namespace { */ coneTo: typeof coneTo; + /** + * Replicates each element in a single-precision complex floating-point strided array a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex64Array( 6 ); + * + * ns.creplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex64Array( 6 ); + * + * ns.creplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + */ + creplicate: typeof creplicate; + /** * Computes the sum of single-precision complex floating-point strided array elements. * @@ -827,6 +895,43 @@ interface Namespace { */ cwapx: typeof cwapx; + /** + * Multiplies each element in a single-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision complex floating-point strided array `w`. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32/ctor' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex64( 5.0, 3.0 ); + * + * ns.cwax( x.length, alpha, x, 1, w, 1 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * var Complex64 = require( '@stdlib/complex/float32/ctor' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex64( 5.0, 3.0 ); + * + * ns.cwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + */ + cwax: typeof cwax; + /** * Takes elements from one of two single-precision complex floating-point strided arrays depending on a condition. * @@ -904,6 +1009,36 @@ interface Namespace { */ cwxsa: typeof cwxsa; + /** + * Multiplies elements of a single-precision complex floating-point strided array `x` by the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * ns.cxmy( x.length, x, 1, y, 1 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + * + * @example + * var Complex64Array = require( '@stdlib/array/complex64' ); + * + * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * ns.cxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + */ + cxmy: typeof cxmy; + /** * Adds elements of a single-precision complex floating-point strided array `x` to the corresponding elements of a single-precision complex floating-point strided array `y` and assigns the results to `y`. * @@ -1836,6 +1971,153 @@ interface Namespace { */ dfill: typeof dfill; + /** + * Replaces double-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * ns.dfillEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * ns.dfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + dfillEqual: typeof dfillEqual; + + /** + * Replaces double-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * ns.dfillNaN( x.length, 0.0, x, 1 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * ns.dfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + dfillNaN: typeof dfillNaN; + + /** + * Replaces double-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * ns.dfillNotEqual( 6, 0.0, 5.0, x, 1 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * ns.dfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + dfillNotEqual: typeof dfillNotEqual; + + /** + * Returns the index of the first element in a double-precision floating-point strided array equal to a corresponding element in another double-precision floating-point strided array. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + * + * var idx = ns.dfirstIndexEqual( 4, x, 1, y, 1 ); + * // returns 2 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + * + * var idx = ns.dfirstIndexEqual.ndarray( 4, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + dfirstIndexEqual: typeof dfirstIndexEqual; + + /** + * Returns the index of the first element in a double-precision floating-point strided array which is less than a corresponding element in another double-precision floating-point strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * var idx = ns.dfirstIndexLessThan( x.length, x, 1, y, 1 ); + * // returns 2 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float64Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * var idx = ns.dfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + dfirstIndexLessThan: typeof dfirstIndexLessThan; + /** * Returns the first index of a specified search element in a double-precision floating-point strided array. * @@ -1941,6 +2223,37 @@ interface Namespace { */ dindexOfFalsy: typeof dindexOfFalsy; + /** + * Returns the first index of an element in a double-precision floating-point strided array which is not equal to a specified search element. + * + * ## Notes + * + * - If all elements are equal to the search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); + * + * var idx = ns.dindexOfNotEqual( x.length, 1.0, x, 1 ); + * // returns 2 + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 1.0, 0.0, 1.0 ] ); + * + * var idx = ns.dindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); + * // returns 2 + */ + dindexOfNotEqual: typeof dindexOfNotEqual; + /** * Returns the index of the first row in a double-precision floating-point input matrix which has the same elements as a provided search vector. * @@ -2778,6 +3091,37 @@ interface Namespace { */ dones: typeof dones; + /** + * Replicates each element in a double-precision floating-point strided array a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float64Array( 6 ); + * + * ns.dreplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float64Array( 6 ); + * + * ns.dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + dreplicate: typeof dreplicate; + /** * Reverses a double-precision floating-point strided array in-place. * @@ -3646,21 +3990,52 @@ interface Namespace { dwapx: typeof dwapx; /** - * Takes elements from one of two double-precision floating-point strided arrays depending on a condition. + * Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to a double-precision floating-point strided array `w`. * * @param N - number of indexed elements - * @param condition - condition array - * @param strideC - stride length for `condition` - * @param x - first input array - * @param strideX - stride length for `x` - * @param y - second input array - * @param strideY - stride length for `y` - * @param out - output array - * @param strideOut - stride length for `out` - * @returns output array + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` * * @example - * var BooleanArray = require( '@stdlib/array/bool' ); + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * ns.dwax( x.length, 5.0, x, 1, w, 1 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * ns.dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + */ + dwax: typeof dwax; + + /** + * Takes elements from one of two double-precision floating-point strided arrays depending on a condition. + * + * @param N - number of indexed elements + * @param condition - condition array + * @param strideC - stride length for `condition` + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var BooleanArray = require( '@stdlib/array/bool' ); * * var condition = new BooleanArray( [ true, false, true ] ); * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); @@ -3714,6 +4089,36 @@ interface Namespace { */ dwxsa: typeof dwxsa; + /** + * Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + * var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * ns.dxdy( x.length, x, 1, y, 1 ); + * // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + * var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * ns.dxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] + */ + dxdy: typeof dxdy; + /** * Multiplies elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. * @@ -4667,6 +5072,101 @@ interface Namespace { */ gfillBy: typeof gfillBy; + /** + * Replaces strided array elements equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + * + * ns.gfillEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] + * + * @example + * var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + * + * ns.gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] + */ + gfillEqual: typeof gfillEqual; + + /** + * Replaces strided array elements less than a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * ns.gfillLessThan( x.length, 0.5, 5.0, x, 1 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + * + * @example + * var x = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * ns.gfillLessThan.ndarray( x.length, 0.5, 5.0, x, 1, 0 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + gfillLessThan: typeof gfillLessThan; + + /** + * Replaces strided array elements equal to `NaN` with a specified scalar constant. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; + * + * ns.gfillNaN( x.length, 0.0, x, 1 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + * + * @example + * var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; + * + * ns.gfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + gfillNaN: typeof gfillNaN; + + /** + * Replaces strided array elements not equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + * + * ns.gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + * + * @example + * var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + * + * ns.gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + gfillNotEqual: typeof gfillNotEqual; + /** * Returns the index of the first element which passes a test implemented by a predicate function. * @@ -4753,6 +5253,126 @@ interface Namespace { */ gfindLastIndex: typeof gfindLastIndex; + /** + * Returns the index of the first element in a strided array equal to a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find matching elements, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = ns.gfirstIndexEqual( x.length, x, 1, y, 1 ); + * // returns 2 + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = ns.gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + gfirstIndexEqual: typeof gfirstIndexEqual; + + /** + * Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is greater than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 2.0, 2.0, 2.0, 2.0 ]; + * + * var idx = ns.gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + * // returns 2 + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 2.0, 2.0, 2.0, 2.0 ]; + * + * var idx = ns.gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + gfirstIndexGreaterThan: typeof gfirstIndexGreaterThan; + + /** + * Returns the index of the first element in a strided array which is less than a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 0.0, 0.0, 0.0, 0.0 ]; + * var y = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * var idx = ns.gfirstIndexLessThan( x.length, x, 1, y, 1 ); + * // returns 2 + * + * @example + * var x = [ 0.0, 0.0, 0.0, 0.0 ]; + * var y = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * var idx = ns.gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + gfirstIndexLessThan: typeof gfirstIndexLessThan; + + /** + * Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array. + * + * ## Notes + * + * - If unable to find an element in `x` which is not equal to the corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 0, 0, 1, 0 ]; + * var y = [ 0, 0, 0, 0 ]; + * + * var idx = ns.gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + * // returns 2 + * + * @example + * var x = [ 0, 0, 1, 0 ]; + * var y = [ 0, 0, 0, 0 ]; + * + * var idx = ns.gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + gfirstIndexNotEqual: typeof gfirstIndexNotEqual; + /** * Returns the first index of a specified search element in a strided array. * @@ -4838,6 +5458,33 @@ interface Namespace { */ gindexOfFalsy: typeof gindexOfFalsy; + /** + * Returns the first index of an element in a strided array which is not equal to a specified search element. + * + * ## Notes + * + * - If all elements are equal to the search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var x = [ 1.0, 1.0, 0.0, 1.0 ]; + * + * var idx = ns.gindexOfNotEqual( x.length, 1.0, x, 1 ); + * // returns 2 + * + * @example + * var x = [ 1.0, 1.0, 0.0, 1.0 ]; + * + * var idx = ns.gindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); + * // returns 2 + */ + gindexOfNotEqual: typeof gindexOfNotEqual; + /** * Returns the index of the first row in an input matrix which has the same elements as a provided search vector. * @@ -4870,6 +5517,33 @@ interface Namespace { */ gindexOfRow: typeof gindexOfRow; + /** + * Returns the index of the first element in a strided array which has the same value as a provided search element. + * + * ## Notes + * + * - If the function is unable to find a search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * + * var idx = ns.gindexOfSameValue( x.length, 2.0, x, 1 ); + * // returns 1 + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * + * var idx = ns.gindexOfSameValue.ndarray( x.length, 2.0, x, 1, 0 ); + * // returns 1 + */ + gindexOfSameValue: typeof gindexOfSameValue; + /** * Returns the index of the first truthy element in a strided array. * @@ -4947,6 +5621,36 @@ interface Namespace { */ gjoinBetween: typeof gjoinBetween; + /** + * Returns the index of the last element in a strided array equal to a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find matching elements, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = ns.glastIndexEqual( x.length, x, 1, y, 1 ); + * // returns 2 + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = ns.glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + glastIndexEqual: typeof glastIndexEqual; + /** * Returns the last index of a specified search element in a strided array. * @@ -6087,6 +6791,32 @@ interface Namespace { */ gwxsy: typeof gwxsy; + /** + * Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns `y` + * + * @example + * var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + * var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + * + * ns.gxdy( x.length, x, 1, y, 1 ); + * // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] + * + * @example + * var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + * var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + * + * ns.gxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] + */ + gxdy: typeof gxdy; + /** * Multiplies elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y`. * @@ -7120,71 +7850,222 @@ interface Namespace { sdssumpw: typeof sdssumpw; /** - * Calculates the differences between consecutive elements of a single-precision floating-point strided array. + * Calculates the differences between consecutive elements of a single-precision floating-point strided array. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length for `x` + * @param N1 - number of indexed elements to prepend + * @param prepend - prepend array + * @param strideP - stride length for `prepend` + * @param N2 - number of indexed elements to append + * @param append - append array + * @param strideA - stride length for `append` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 2.0, 4.0, 7.0, 11.0, 16.0 ] ); + * var p = new Float32Array( [ 1.0 ] ); + * var a = new Float32Array( [ 22.0 ] ); + * var out = new Float32Array( 6 ); + * + * ns.sediff( x.length, x, 1, 1, p, 1, 1, a, 1, out, 1 ); + * // out => [ 1.0, 2.0, 3.0, 4.0, 5.0, 22.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 2.0, 4.0, 7.0, 11.0, 16.0 ] ); + * var p = new Float32Array( [ 1.0 ] ); + * var a = new Float32Array( [ 22.0 ] ); + * var out = new Float32Array( 6 ); + * + * ns.sediff.ndarray( x.length, x, 1, 0, 1, p, 1, 0, 1, a, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 2.0, 3.0, 4.0, 5.0, 22.0 ] + */ + sediff: typeof sediff; + + /** + * Fills a single-precision floating-point strided array with a specified scalar value. + * + * @param N - number of indexed elements + * @param alpha - constant + * @param x - input array + * @param strideX - stride length + * @returns input array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * + * ns.sfill( x.length, 5.0, x, 1 ); + * // x => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * + * ns.sfill.ndarray( x.length, 5.0, x, 1, 0 ); + * // x => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] + */ + sfill: typeof sfill; + + /** + * Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * ns.sfillEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * ns.sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + sfillEqual: typeof sfillEqual; + + /** + * Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * ns.sfillNaN( x.length, 0.0, x, 1 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * ns.sfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + sfillNaN: typeof sfillNaN; + + /** + * Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * ns.sfillNotEqual( 6, 0.0, 5.0, x, 1 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * ns.sfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + sfillNotEqual: typeof sfillNotEqual; + + /** + * Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. + * + * ## Notes + * + * - If the function is unable to find a match, the function returns `-1`. * * @param N - number of indexed elements - * @param x - input array + * @param x - first input array * @param strideX - stride length for `x` - * @param N1 - number of indexed elements to prepend - * @param prepend - prepend array - * @param strideP - stride length for `prepend` - * @param N2 - number of indexed elements to append - * @param append - append array - * @param strideA - stride length for `append` - * @param out - output array - * @param strideOut - stride length for `out` - * @returns output array + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index * * @example * var Float32Array = require( '@stdlib/array/float32' ); * - * var x = new Float32Array( [ 2.0, 4.0, 7.0, 11.0, 16.0 ] ); - * var p = new Float32Array( [ 1.0 ] ); - * var a = new Float32Array( [ 22.0 ] ); - * var out = new Float32Array( 6 ); + * var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); * - * ns.sediff( x.length, x, 1, 1, p, 1, 1, a, 1, out, 1 ); - * // out => [ 1.0, 2.0, 3.0, 4.0, 5.0, 22.0 ] + * var idx = ns.sfirstIndexEqual( x.length, x, 1, y, 1 ); + * // returns 2 * * @example * var Float32Array = require( '@stdlib/array/float32' ); * - * var x = new Float32Array( [ 2.0, 4.0, 7.0, 11.0, 16.0 ] ); - * var p = new Float32Array( [ 1.0 ] ); - * var a = new Float32Array( [ 22.0 ] ); - * var out = new Float32Array( 6 ); + * var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); * - * ns.sediff.ndarray( x.length, x, 1, 0, 1, p, 1, 0, 1, a, 1, 0, out, 1, 0 ); - * // out => [ 1.0, 2.0, 3.0, 4.0, 5.0, 22.0 ] + * var idx = ns.sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 */ - sediff: typeof sediff; + sfirstIndexEqual: typeof sfirstIndexEqual; /** - * Fills a single-precision floating-point strided array with a specified scalar value. + * Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. * * @param N - number of indexed elements - * @param alpha - constant - * @param x - input array - * @param strideX - stride length - * @returns input array + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index * * @example * var Float32Array = require( '@stdlib/array/float32' ); * - * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); * - * ns.sfill( x.length, 5.0, x, 1 ); - * // x => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] + * var idx = ns.sfirstIndexLessThan( x.length, x, 1, y, 1 ); + * // returns 2 * * @example * var Float32Array = require( '@stdlib/array/float32' ); * - * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); * - * ns.sfill.ndarray( x.length, 5.0, x, 1, 0 ); - * // x => [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] + * var idx = ns.sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 */ - sfill: typeof sfill; + sfirstIndexLessThan: typeof sfirstIndexLessThan; /** * Returns the first index of a specified search element in a single-precision floating-point strided array. @@ -7895,6 +8776,37 @@ interface Namespace { */ sones: typeof sones; + /** + * Replicates each single-precision floating-point strided array element a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float32Array( 6 ); + * + * ns.sreplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float32Array( 6 ); + * + * ns.sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + sreplicate: typeof sreplicate; + /** * Reverses a single-precision floating-point strided array in-place. * @@ -8400,6 +9312,37 @@ interface Namespace { */ swapx: typeof swapx; + /** + * Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to a single-precision floating-point strided array `w`. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * ns.swax( x.length, 5.0, x, 1, w, 1 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * ns.swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + */ + swax: typeof swax; + /** * Takes elements from one of two single-precision floating-point strided arrays depending on a condition. * @@ -8471,6 +9414,36 @@ interface Namespace { */ swxsa: typeof swxsa; + /** + * Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + * var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * ns.sxdy( x.length, x, 1, y, 1 ); + * // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + * var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * ns.sxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] + */ + sxdy: typeof sxdy; + /** * Multiplies elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. * @@ -8945,6 +9918,38 @@ interface Namespace { */ zindexOfRow: typeof zindexOfRow; + /** + * Returns the index of the first truthy element in a double-precision complex floating-point strided array. + * + * ## Notes + * + * - A complex number is truthy when at least one of its real or imaginary components is truthy. + * - If unable to find a truthy element, the function returns `-1`. + * - The function explicitly treats `NaN` values as falsy. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0 ] ); + * + * var idx = ns.zindexOfTruthy( x.length, x, 1 ); + * // returns 1 + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0 ] ); + * + * var idx = ns.zindexOfTruthy.ndarray( x.length, x, 1, 0 ); + * // returns 1 + */ + zindexOfTruthy: typeof zindexOfTruthy; + /** * Returns the index of the last row in a double-precision complex floating-point input matrix which has the same elements as a provided search vector. * @@ -9042,6 +10047,37 @@ interface Namespace { */ zoneTo: typeof zoneTo; + /** + * Replicates each element in a double-precision complex floating-point strided array a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex128Array( 6 ); + * + * ns.zreplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex128Array( 6 ); + * + * ns.zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + */ + zreplicate: typeof zreplicate; + /** * Computes the sum of double-precision complex floating-point strided array elements. * @@ -9160,6 +10196,43 @@ interface Namespace { */ zwapx: typeof zwapx; + /** + * Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w`. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Complex128 = require( '@stdlib/complex/float64/ctor' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex128( 5.0, 3.0 ); + * + * ns.zwax( x.length, alpha, x, 1, w, 1 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Complex128 = require( '@stdlib/complex/float64/ctor' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex128( 5.0, 3.0 ); + * + * ns.zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + */ + zwax: typeof zwax; + /** * Takes elements from one of two double-precision complex floating-point strided arrays depending on a condition. * @@ -9237,6 +10310,66 @@ interface Namespace { */ zwxsa: typeof zwxsa; + /** + * Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + * var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + * + * ns.zxdy( x.length, x, 1, y, 1 ); + * // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + * var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + * + * ns.zxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] + */ + zxdy: typeof zxdy; + + /** + * Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * ns.zxmy( x.length, x, 1, y, 1 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * ns.zxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + */ + zxmy: typeof zxmy; + /** * Adds elements of a double-precision complex floating-point strided array `x` to the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. * diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/README.md b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/README.md new file mode 100644 index 000000000000..f11e4bfd6bf0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/README.md @@ -0,0 +1,323 @@ + + +# dreplicate + +> Replicate each element in a double-precision floating-point strided array a specified number of times. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dreplicate = require( '@stdlib/blas/ext/base/dreplicate' ); +``` + +#### dreplicate( N, k, x, strideX, out, strideOut ) + +Replicates each element in a double-precision floating-point strided array a specified number of times. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +var out = new Float64Array( 6 ); + +dreplicate( x.length, 2, x, 1, out, 1 ); +// out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **k**: number of times to replicate each element. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **out**: output [`Float64Array`][@stdlib/array/float64]. +- **strideOut**: stride length for `out`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to replicate every other element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out = new Float64Array( 6 ); + +dreplicate( 3, 2, x, 2, out, 1 ); +// out => [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +dreplicate( 3, 2, x1, 2, out1, 1 ); +// out0 => [ 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] +``` + +#### dreplicate.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + +Replicates each element in a double-precision floating-point strided array a specified number of times using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +var out = new Float64Array( 6 ); + +dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +// out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetOut**: starting index for `out`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to replicate every other element in the strided input array starting from the second element and to store in the last `N*k` elements of the strided output array starting from the last element: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +dreplicate.ndarray( 3, 2, x, 2, 1, out, -1, out.length-1 ); +// out => [ 0.0, 0.0, 6.0, 6.0, 4.0, 4.0, 2.0, 2.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0` or `k <= 0`, both functions return `out` unchanged. +- Both functions assume that the output array supports `N*k` indexed elements. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dreplicate = require( '@stdlib/blas/ext/base/dreplicate' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var out = new Float64Array( x.length * 3 ); +console.log( out ); + +dreplicate( x.length, 3, x, 1, out, 1 ); +console.log( out ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dreplicate.h" +``` + +#### stdlib_strided_dreplicate( N, k, \*X, strideX, \*Out, strideOut ) + +Replicates each element in a double-precision floating-point strided array a specified number of times. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; +double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dreplicate( 3, 2, x, 1, out, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Out**: `[out] double*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. + +```c +void stdlib_strided_dreplicate( const CBLAS_INT N, const CBLAS_INT k, const double *X, const CBLAS_INT strideX, double *Out, const CBLAS_INT strideOut ); +``` + + + +#### stdlib_strided_dreplicate_ndarray( N, k, \*X, strideX, offsetX, \*Out, strideOut, offsetOut ) + + + +Replicates each element in a double-precision floating-point strided array a specified number of times using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0 }; +double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dreplicate_ndarray( 3, 2, x, 1, 0, out, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Out**: `[out] double*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. +- **offsetOut**: `[in] CBLAS_INT` starting index for `Out`. + +```c +void stdlib_strided_dreplicate_ndarray( const CBLAS_INT N, const CBLAS_INT k, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dreplicate.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify strides: + const int strideX = 1; + const int strideOut = 1; + + // Replicate each element: + stdlib_strided_dreplicate( N, k, x, strideX, out, strideOut ); + + // Print the results: + for ( int i = 0; i < 8; i++ ) { + printf( "Out[ %i ] = %lf\n", i, out[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.js new file mode 100644 index 000000000000..2e417a5ffaab --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dreplicate = require( './../lib/dreplicate.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = dreplicate( x.length, 2, x, 1, out, 1 ); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.native.js new file mode 100644 index 000000000000..8c3828b79575 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.native.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dreplicate = tryRequire( resolve( __dirname, './../lib/dreplicate.native.js' ) ); +var opts = { + 'skip': ( dreplicate instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = dreplicate( x.length, 2, x, 1, out, 1 ); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..254f58e0593c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.ndarray.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dreplicate = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = dreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..e692b15e78b5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dreplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dreplicate instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = dreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..f0cceee3b598 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/benchmark/c/benchmark.length.c @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dreplicate.h" +#include +#include +#include +#include +#include + +#define NAME "dreplicate" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *out; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + out = (double *) malloc( len * 2 * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double()*99.0 ) + 1.0; + } + for ( i = 0; i < len*2; i++ ) { + out[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_dreplicate( len, 2, x, 1, out, 1 ); + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *out; + double *x; + double t; + int i; + + x = (double *) malloc( len * sizeof( double ) ); + out = (double *) malloc( len * 2 * sizeof( double ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_double()*99.0 ) + 1.0; + } + for ( i = 0; i < len*2; i++ ) { + out[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_dreplicate_ndarray( len, 2, x, 1, 0, out, 1, 0 ); + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/repl.txt new file mode 100644 index 000000000000..9258543e18bb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/repl.txt @@ -0,0 +1,118 @@ + +{{alias}}( N, k, x, strideX, out, strideOut ) + Replicates each element in a double-precision floating-point strided array a + specified number of times. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0` or `k <= 0`, the function returns `out` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + out: Float64Array + Output array. + + strideOut: integer + Stride length for `out`. + + Returns + ------- + out: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0 ] ); + > var out = new {{alias:@stdlib/array/float64}}( 6 ); + > {{alias}}( x.length, 2, x, 1, out, 1 ) + [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > out = new {{alias:@stdlib/array/float64}}( 6 ); + > {{alias}}( 3, 2, x, 2, out, 1 ) + [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var out0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var out1 = new {{alias:@stdlib/array/float64}}( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); + > {{alias}}( 3, 2, x1, 2, out1, 1 ) + [ 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] + > out0 + [ 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] + + +{{alias}}.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + Replicates each element in a double-precision floating-point strided array a + specified number of times using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + out: Float64Array + Output array. + + strideOut: integer + Stride length for `out`. + + offsetOut: integer + Starting index for `out`. + + Returns + ------- + out: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0 ] ); + > var out = new {{alias:@stdlib/array/float64}}( 6 ); + > {{alias}}.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ) + [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + + // Advanced indexing: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > out = new {{alias:@stdlib/array/float64}}( 6 ); + > {{alias}}.ndarray( 3, 2, x, 2, 1, out, -1, out.length-1 ) + [ 6.0, 6.0, 4.0, 4.0, 2.0, 2.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/types/index.d.ts new file mode 100644 index 000000000000..38fbe0047921 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/types/index.d.ts @@ -0,0 +1,106 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dreplicate`. +*/ +interface Routine { + /** + * Replicates each element in a double-precision floating-point strided array a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float64Array( 6 ); + * + * dreplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + ( N: number, k: number, x: Float64Array, strideX: number, out: Float64Array, strideOut: number ): Float64Array; + + /** + * Replicates each element in a double-precision floating-point strided array a specified number of times using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float64Array( 6 ); + * + * dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + ndarray( N: number, k: number, x: Float64Array, strideX: number, offsetX: number, out: Float64Array, strideOut: number, offsetOut: number ): Float64Array; +} + +/** +* Replicates each element in a double-precision floating-point strided array a specified number of times. +* +* @param N - number of indexed elements +* @param k - number of times to replicate each element +* @param x - input array +* @param strideX - stride length for `x` +* @param out - output array +* @param strideOut - stride length for `out` +* @returns output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float64Array( 6 ); +* +* dreplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float64Array( 6 ); +* +* dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +declare var dreplicate: Routine; + + +// EXPORTS // + +export = dreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/types/test.ts new file mode 100644 index 000000000000..468086d4ecda --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/docs/types/test.ts @@ -0,0 +1,280 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dreplicate = require( './index' ); + + +// TESTS // + +// The function returns a Float64Array... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate( x.length, 2, x, 1, out, 1 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate( '10', 2, x, 1, out, 1 ); // $ExpectError + dreplicate( true, 2, x, 1, out, 1 ); // $ExpectError + dreplicate( false, 2, x, 1, out, 1 ); // $ExpectError + dreplicate( null, 2, x, 1, out, 1 ); // $ExpectError + dreplicate( undefined, 2, x, 1, out, 1 ); // $ExpectError + dreplicate( [], 2, x, 1, out, 1 ); // $ExpectError + dreplicate( {}, 2, x, 1, out, 1 ); // $ExpectError + dreplicate( ( x: number ): number => x, 2, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate( x.length, '10', x, 1, out, 1 ); // $ExpectError + dreplicate( x.length, true, x, 1, out, 1 ); // $ExpectError + dreplicate( x.length, false, x, 1, out, 1 ); // $ExpectError + dreplicate( x.length, null, x, 1, out, 1 ); // $ExpectError + dreplicate( x.length, undefined, x, 1, out, 1 ); // $ExpectError + dreplicate( x.length, [], x, 1, out, 1 ); // $ExpectError + dreplicate( x.length, {}, x, 1, out, 1 ); // $ExpectError + dreplicate( x.length, ( x: number ): number => x, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate( x.length, 2, 10, 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, '10', 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, true, 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, false, 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, null, 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, undefined, 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, [ '1' ], 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, {}, 1, out, 1 ); // $ExpectError + dreplicate( x.length, 2, ( x: number ): number => x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate( x.length, 2, x, '10', out, 1 ); // $ExpectError + dreplicate( x.length, 2, x, true, out, 1 ); // $ExpectError + dreplicate( x.length, 2, x, false, out, 1 ); // $ExpectError + dreplicate( x.length, 2, x, null, out, 1 ); // $ExpectError + dreplicate( x.length, 2, x, undefined, out, 1 ); // $ExpectError + dreplicate( x.length, 2, x, [], out, 1 ); // $ExpectError + dreplicate( x.length, 2, x, {}, out, 1 ); // $ExpectError + dreplicate( x.length, 2, x, ( x: number ): number => x, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dreplicate( x.length, 2, x, 1, 10, 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, '10', 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, true, 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, false, 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, null, 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, undefined, 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, [ '1' ], 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, {}, 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate( x.length, 2, x, 1, out, '10' ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, true ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, false ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, null ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, undefined ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, [] ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, {} ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate(); // $ExpectError + dreplicate( x.length ); // $ExpectError + dreplicate( x.length, 2 ); // $ExpectError + dreplicate( x.length, 2, x ); // $ExpectError + dreplicate( x.length, 2, x, 1 ); // $ExpectError + dreplicate( x.length, 2, x, 1, out ); // $ExpectError + dreplicate( x.length, 2, x, 1, out, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float64Array... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( '10', 2, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( true, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( false, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( null, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( undefined, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( [], 2, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( {}, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( ( x: number ): number => x, 2, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( x.length, '10', x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, true, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, false, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, null, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, undefined, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, [], x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, {}, x, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, ( x: number ): number => x, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( x.length, 2, 10, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, '10', 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, true, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, false, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, null, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, undefined, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, [ '1' ], 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, {}, 1, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( x.length, 2, x, '10', 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, true, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, false, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, null, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, undefined, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, [], 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, {}, 0, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( x.length, 2, x, 1, '10', out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, true, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, false, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, null, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, undefined, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, [], out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, {}, out, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dreplicate.ndarray( x.length, 2, x, 1, 0, 10, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, '10', 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, true, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, false, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, null, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, undefined, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, {}, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( x.length, 2, x, 1, 0, out, '10', 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, true, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, false, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, null, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, undefined, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, [], 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, {}, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, '10' ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, true ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, false ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, null ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, undefined ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, [] ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, {} ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const out = new Float64Array( 20 ); + + dreplicate.ndarray(); // $ExpectError + dreplicate.ndarray( x.length ); // $ExpectError + dreplicate.ndarray( x.length, 2 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1 ); // $ExpectError + dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/c/example.c new file mode 100644 index 000000000000..ad1d3d0dfa76 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/c/example.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dreplicate.h" +#include + +int main( void ) { + // Create a strided array: + const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify strides: + const int strideX = 1; + const int strideOut = 1; + + // Replicate each element: + stdlib_strided_dreplicate( N, k, x, strideX, out, strideOut ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "Out[ %i ] = %lf\n", i, out[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/index.js new file mode 100644 index 000000000000..8684e1be7f78 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dreplicate = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var out = new Float64Array( x.length * 3 ); +console.log( out ); + +dreplicate( x.length, 3, x, 1, out, 1 ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function dreplicate( N, k, x, strideX, out, strideOut ) { + var ox = stride2offset( N, strideX ); + var oo = stride2offset( N * k, strideOut ); + return ndarray( N, k, x, strideX, ox, out, strideOut, oo ); +} + + +// EXPORTS // + +module.exports = dreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/dreplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/dreplicate.native.js new file mode 100644 index 000000000000..cb4e46a979c0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/dreplicate.native.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each element in a double-precision floating-point strided array a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {Float64Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float64Array( 6 ); +* +* dreplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function dreplicate( N, k, x, strideX, out, strideOut ) { + addon( N, k, x, strideX, out, strideOut ); + return out; +} + + +// EXPORTS // + +module.exports = dreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/index.js new file mode 100644 index 000000000000..e6349ca2eb5e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/index.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replicate each element in a double-precision floating-point strided array a specified number of times. +* +* @module @stdlib/blas/ext/base/dreplicate +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dreplicate = require( '@stdlib/blas/ext/base/dreplicate' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float64Array( 6 ); +* +* dreplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dreplicate = require( '@stdlib/blas/ext/base/dreplicate' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float64Array( 6 ); +* +* dreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dreplicate; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dreplicate = main; +} else { + dreplicate = tmp; +} + + +// EXPORTS // + +module.exports = dreplicate; + +// exports: { "ndarray": "dreplicate.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/main.js new file mode 100644 index 000000000000..fed60ff90a50 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dreplicate = require( './dreplicate.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( dreplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/native.js new file mode 100644 index 000000000000..5fa9d86367e2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dreplicate = require( './dreplicate.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( dreplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/ndarray.js new file mode 100644 index 000000000000..565de29c5095 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/ndarray.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replicates each element in a double-precision floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Float64Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float64Array( 6 ); +* +* dreplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function dreplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var ix; + var io; + var v; + var i; + var j; + + if ( N <= 0 || k <= 0 ) { + return out; + } + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = x[ ix ]; + for ( j = 0; j < k; j++ ) { + out[ io ] = v; + io += strideOut; + } + ix += strideX; + } + return out; +} + + +// EXPORTS // + +module.exports = dreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/ndarray.native.js new file mode 100644 index 000000000000..eb79ed92f5a4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/lib/ndarray.native.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each element in a double-precision floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Float64Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Float64Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float64Array( 6 ); +* +* dreplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function dreplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + addon.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ); + return out; +} + + +// EXPORTS // + +module.exports = dreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/manifest.json new file mode 100644 index 000000000000..fb41f9fb7ad5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/manifest.json @@ -0,0 +1,78 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/package.json b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/package.json new file mode 100644 index 000000000000..d6f0d198aadf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/blas/ext/base/dreplicate", + "version": "0.0.0", + "description": "Replicate each element in a double-precision floating-point strided array a specified number of times.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "replicate", + "repeat", + "copy", + "strided", + "array", + "ndarray", + "float64", + "double", + "float64array", + "dreplicate" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/addon.c new file mode 100644 index 000000000000..08a06acf6a2d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/addon.c @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dreplicate.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Out, N * k, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_dreplicate)( N, k, X, strideX, Out, strideOut ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetOut, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Out, N * k, strideOut, argv, 5 ); + API_SUFFIX(stdlib_strided_dreplicate_ndarray)( N, k, X, strideX, offsetX, Out, strideOut, offsetOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/main.c new file mode 100644 index 000000000000..1b2762b2c190 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/src/main.c @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dreplicate.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Replicates each element in a double-precision floating-point strided array a specified number of times. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param Out output array +* @param strideOut stride length for Out +*/ +void API_SUFFIX(stdlib_strided_dreplicate)( const CBLAS_INT N, const CBLAS_INT k, const double *X, const CBLAS_INT strideX, double *Out, const CBLAS_INT strideOut ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oo = stdlib_strided_stride2offset( N * k, strideOut ); + API_SUFFIX(stdlib_strided_dreplicate_ndarray)( N, k, X, strideX, ox, Out, strideOut, oo ); +} + +/** +* Replicates each element in a double-precision floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Out output array +* @param strideOut stride length for Out +* @param offsetOut starting index for Out +*/ +void API_SUFFIX(stdlib_strided_dreplicate_ndarray)( const CBLAS_INT N, const CBLAS_INT k, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ) { + CBLAS_INT ix; + CBLAS_INT io; + CBLAS_INT i; + CBLAS_INT j; + double v; + + if ( N <= 0 || k <= 0 ) { + return; + } + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + for ( j = 0; j < k; j++ ) { + Out[ io ] = v; + io += strideOut; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.dreplicate.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.dreplicate.js new file mode 100644 index 000000000000..53b69dd74973 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.dreplicate.js @@ -0,0 +1,302 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dreplicate = require( './../lib/dreplicate.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( dreplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + dreplicate( x.length, 2, x, 1, out, 1 ); + expected = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float64Array( 12 ); + + dreplicate( x.length, 3, x, 1, out, 1 ); + expected = new Float64Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( x.length, 1, x, 1, out, 1 ); + expected = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 5.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( 1, 3, x, 1, out, 1 ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + v = dreplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( -1, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( 0, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( x.length, -1, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( x.length, 0, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 2, out, 1 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]); + + dreplicate( 3, 2, x, 1, out, 2 ); + + expected = new Float64Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, -2, out, -1 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, 2, out, -1 ); + + expected = new Float64Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + out0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + dreplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] ); + + t.deepEqual( out0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.dreplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.dreplicate.native.js new file mode 100644 index 000000000000..1749d6328b4d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.dreplicate.native.js @@ -0,0 +1,311 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Float64Array = require( '@stdlib/array/float64' ); + + +// VARIABLES // + +var dreplicate = tryRequire( resolve( __dirname, './../lib/dreplicate.native.js' ) ); +var opts = { + 'skip': ( dreplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( dreplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + dreplicate( x.length, 2, x, 1, out, 1 ); + expected = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float64Array( 12 ); + + dreplicate( x.length, 3, x, 1, out, 1 ); + expected = new Float64Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( x.length, 1, x, 1, out, 1 ); + expected = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 5.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( 1, 3, x, 1, out, 1 ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + v = dreplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( -1, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( 0, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( x.length, -1, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( x.length, 0, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 2, out, 1 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]); + + dreplicate( 3, 2, x, 1, out, 2 ); + + expected = new Float64Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, -2, out, -1 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, 2, out, -1 ); + + expected = new Float64Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + out0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + dreplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] ); + + t.deepEqual( out0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.js new file mode 100644 index 000000000000..72416dba9fa9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dreplicate = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dreplicate.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dreplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dreplicate, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dreplicate; + var main; + + main = require( './../lib/dreplicate.js' ); + + dreplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dreplicate, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.ndarray.js new file mode 100644 index 000000000000..1ddb33146b16 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.ndarray.js @@ -0,0 +1,353 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dreplicate = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( dreplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + dreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float64Array( 12 ); + + dreplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 5.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + v = dreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]); + + dreplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Float64Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, -2, 4, out, -1, 5 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0 // 3 + ]); + + dreplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Float64Array( [ 1.0, 1.0, -2.0, -2.0, 2.0, 2.0, 4.0, 4.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float64Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Float64Array( [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, + 2.0, // 0, 1, 2 + 3.0 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Float64Array( [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Float64Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.ndarray.native.js new file mode 100644 index 000000000000..c7821f94fb99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dreplicate/test/test.ndarray.native.js @@ -0,0 +1,362 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Float64Array = require( '@stdlib/array/float64' ); + + +// VARIABLES // + +var dreplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dreplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( dreplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + dreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float64Array( 12 ); + + dreplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 5.0 ] ); + out = new Float64Array( 3 ); + + dreplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( 6 ); + + v = dreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + dreplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + dreplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]); + + dreplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Float64Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, -2, 4, out, -1, 5 ); + + expected = new Float64Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, // 3 + 0.0 // 3 + ]); + + dreplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Float64Array( [ 1.0, 1.0, -2.0, -2.0, 2.0, 2.0, 4.0, 4.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float64Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Float64Array( [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, + 2.0, // 0, 1, 2 + 3.0 + ]); + out = new Float64Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + dreplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Float64Array( [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float64Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + dreplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Float64Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsome/README.md b/lib/node_modules/@stdlib/blas/ext/base/dsome/README.md index cd7f63b8cd87..158478bba25a 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/dsome/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/dsome/README.md @@ -58,8 +58,6 @@ The function has the following parameters: The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to test every other element: - - ```javascript var Float64Array = require( '@stdlib/array/float64' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/README.md b/lib/node_modules/@stdlib/blas/ext/base/dwax/README.md new file mode 100644 index 000000000000..21a21790184d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/README.md @@ -0,0 +1,332 @@ + + +# dwax + +> Multiply each element in a double-precision floating-point strided array `x` by a scalar constant and assign the results to elements in a double-precision floating-point strided array `w`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{w} = \alpha \cdot \mathbf{x} +``` + + + +This API is complementary to the package [`@stdlib/blas/base/dscal`][@stdlib/blas/base/dscal], which performs an in-place update. + +
+ + + +
+ +## Usage + +```javascript +var dwax = require( '@stdlib/blas/ext/base/dwax' ); +``` + +#### dwax( N, alpha, x, strideX, w, strideW ) + +Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `w`. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +dwax( x.length, 5.0, x, 1, w, 1 ); +// w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **alpha**: scalar constant. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **w**: output [`Float64Array`][@stdlib/array/float64]. +- **strideW**: stride length for `w`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other element in `x` by `alpha` and assign the results to every other element in `w`: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +dwax( 3, 5.0, x, 2, w, 2 ); +// w => [ 5.0, 0.0, 15.0, 0.0, 25.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var w0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var w1 = new Float64Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +dwax( 3, 5.0, x1, 1, w1, 1 ); +// w0 => [ 0.0, 0.0, 10.0, 15.0, 20.0, 0.0 ] +``` + +#### dwax.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + +Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `w` using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); +// w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetW**: starting index for `w`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to multiply the last three elements of `x` by `alpha` and assign the results to the last three elements of `w`: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +dwax.ndarray( 3, 5.0, x, 1, x.length-3, w, 1, w.length-3 ); +// w => [ 0.0, 0.0, 15.0, 20.0, 25.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `w` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dwax = require( '@stdlib/blas/ext/base/dwax' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var w = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( w ); + +dwax( x.length, 5.0, x, 1, w, 1 ); +console.log( w ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dwax.h" +``` + +#### stdlib_strided_dwax( N, alpha, \*X, strideX, \*W, strideW ) + +Multiplies each element in a double-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `W`. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double w[] = { 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dwax( 4, 5.0, x, 1, w, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] double` scalar constant. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **W**: `[out] double*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. + +```c +void stdlib_strided_dwax( const CBLAS_INT N, const double alpha, const double *X, const CBLAS_INT strideX, double *W, const CBLAS_INT strideW ); +``` + + + +#### stdlib_strided_dwax_ndarray( N, alpha, \*X, strideX, offsetX, \*W, strideW, offsetW ) + + + +Multiplies each element in a double-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `W` using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double w[] = { 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_dwax_ndarray( 4, 5.0, x, 1, 0, w, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] double` scalar constant. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **W**: `[out] double*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. +- **offsetW**: `[in] CBLAS_INT` starting index for `W`. + +```c +void stdlib_strided_dwax_ndarray( const CBLAS_INT N, const double alpha, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dwax.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + double w[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_dwax( N, 5.0, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "w[ %i ] = %lf\n", i, w[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + +[@stdlib/blas/base/dscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/dscal + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.js new file mode 100644 index 000000000000..6290f31a5761 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dwax = require( './../lib/dwax.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dwax( x.length, 5.0, x, 1, w, 1 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.native.js new file mode 100644 index 000000000000..41d0c6aaa63d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dwax = tryRequire( resolve( __dirname, './../lib/dwax.native.js' ) ); +var opts = { + 'skip': ( dwax instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dwax( x.length, 5.0, x, 1, w, 1 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..0169c3889090 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.ndarray.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dwax = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..388c4f33c64b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dwax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dwax instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..43dce26b067c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/benchmark/c/benchmark.length.c @@ -0,0 +1,207 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dwax.h" +#include +#include +#include +#include +#include + +#define NAME "dwax" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double *w; + double t; + int i; + + x = (double *)malloc( len * sizeof(double) ); + w = (double *)malloc( len * sizeof(double) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + w[ i ] = random_uniform( -100.0, 100.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_dwax( len, 5.0, x, 1, w, 1 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double *w; + double t; + int i; + + x = (double *)malloc( len * sizeof(double) ); + w = (double *)malloc( len * sizeof(double) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + w[ i ] = random_uniform( -100.0, 100.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_dwax_ndarray( len, 5.0, x, 1, 0, w, 1, 0 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dwax/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/repl.txt new file mode 100644 index 000000000000..baf4ca92c1cc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/repl.txt @@ -0,0 +1,131 @@ + +{{alias}}( N, alpha, x, strideX, w, strideW ) + Multiplies each element in a double-precision floating-point strided array + `x` by a scalar constant and assigns the results to elements in a double- + precision floating-point strided array `w`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `w` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + w: Float64Array + Output array. + + strideW: integer + Stride length for `w`. + + Returns + ------- + w: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/float64}}( bufX ); + > var w = new {{alias:@stdlib/array/float64}}( bufW ); + > {{alias}}( x.length, 5.0, x, 1, w, 1 ) + [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float64}}( bufX ); + > w = new {{alias:@stdlib/array/float64}}( bufW ); + > {{alias}}( 4, 5.0, x, 2, w, 2 ) + [ -10.0, 0.0, 15.0, 0.0, 20.0, 0.0, -5.0, 0.0 ] + + // Using view offsets: + > var bufX0 = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; + > var bufW0 = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x0 = new {{alias:@stdlib/array/float64}}( bufX0 ); + > var w0 = new {{alias:@stdlib/array/float64}}( bufW0 ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetW = w0.BYTES_PER_ELEMENT * 1; + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, offsetX ); + > var w1 = new {{alias:@stdlib/array/float64}}( w0.buffer, offsetW ); + > {{alias}}( 3, 5.0, x1, 2, w1, 2 ) + [ -10.0, 0.0, -20.0, 0.0, -30.0 ] + > w0 + [ 0.0, -10.0, 0.0, -20.0, 0.0, -30.0 ] + + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + Multiplies each element in a double-precision floating-point strided array + `x` by a scalar constant and assigns the results to elements in a double- + precision floating-point strided array `w` using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + w: Float64Array + Output array. + + strideW: integer + Stride length for `w`. + + offsetW: integer + Starting index for `w`. + + Returns + ------- + w: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/float64}}( bufX ); + > var w = new {{alias:@stdlib/array/float64}}( bufW ); + > {{alias}}.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ) + [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + + // Using index offsets: + > bufX = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; + > bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > x = new {{alias:@stdlib/array/float64}}( bufX ); + > w = new {{alias:@stdlib/array/float64}}( bufW ); + > {{alias}}.ndarray( 3, 5.0, x, 1, x.length-3, w, 1, w.length-3 ) + [ 0.0, 0.0, 0.0, -20.0, 25.0, -30.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/types/index.d.ts new file mode 100644 index 000000000000..9c8db318019a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/types/index.d.ts @@ -0,0 +1,106 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dwax`. +*/ +interface Routine { + /** + * Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to a double-precision floating-point strided array `w`. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * dwax( x.length, 5.0, x, 1, w, 1 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + */ + ( N: number, alpha: number, x: Float64Array, strideX: number, w: Float64Array, strideW: number ): Float64Array; + + /** + * Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to a double-precision floating-point strided array `w` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting index for `x` + * @param w - output array + * @param strideW - `w` stride length + * @param offsetW - starting index for `w` + * @returns `w` + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + */ + ndarray( N: number, alpha: number, x: Float64Array, strideX: number, offsetX: number, w: Float64Array, strideW: number, offsetW: number ): Float64Array; +} + +/** +* Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to a double-precision floating-point strided array `w`. +* +* @param N - number of indexed elements +* @param alpha - scalar constant +* @param x - input array +* @param strideX - `x` stride length +* @param w - output array +* @param strideW - `w` stride length +* @returns `w` +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* dwax( x.length, 5.0, x, 1, w, 1 ); +* // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +*/ +declare var dwax: Routine; + + +// EXPORTS // + +export = dwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/types/test.ts new file mode 100644 index 000000000000..c5664936b7e1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/docs/types/test.ts @@ -0,0 +1,278 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dwax = require( './index' ); + + +// TESTS // + +// The function returns a Float64Array... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax( x.length, 5.0, x, 1, w, 1 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax( '10', 5.0, x, 1, w, 1 ); // $ExpectError + dwax( true, 5.0, x, 1, w, 1 ); // $ExpectError + dwax( false, 5.0, x, 1, w, 1 ); // $ExpectError + dwax( null, 5.0, x, 1, w, 1 ); // $ExpectError + dwax( undefined, 5.0, x, 1, w, 1 ); // $ExpectError + dwax( [], 5.0, x, 1, w, 1 ); // $ExpectError + dwax( {}, 5.0, x, 1, w, 1 ); // $ExpectError + dwax( ( x: number ): number => x, 5.0, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax( x.length, '10', x, 1, w, 1 ); // $ExpectError + dwax( x.length, true, x, 1, w, 1 ); // $ExpectError + dwax( x.length, false, x, 1, w, 1 ); // $ExpectError + dwax( x.length, null, x, 1, w, 1 ); // $ExpectError + dwax( x.length, undefined, x, 1, w, 1 ); // $ExpectError + dwax( x.length, [], x, 1, w, 1 ); // $ExpectError + dwax( x.length, {}, x, 1, w, 1 ); // $ExpectError + dwax( x.length, ( x: number ): number => x, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float64Array... +{ + const w = new Float64Array( 10 ); + + dwax( 10, 5.0, 10, 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, '10', 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, true, 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, false, 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, null, 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, undefined, 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, [], 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, {}, 1, w, 1 ); // $ExpectError + dwax( 10, 5.0, ( x: number ): number => x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax( x.length, 5.0, x, '10', w, 1 ); // $ExpectError + dwax( x.length, 5.0, x, true, w, 1 ); // $ExpectError + dwax( x.length, 5.0, x, false, w, 1 ); // $ExpectError + dwax( x.length, 5.0, x, null, w, 1 ); // $ExpectError + dwax( x.length, 5.0, x, undefined, w, 1 ); // $ExpectError + dwax( x.length, 5.0, x, [], w, 1 ); // $ExpectError + dwax( x.length, 5.0, x, {}, w, 1 ); // $ExpectError + dwax( x.length, 5.0, x, ( x: number ): number => x, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dwax( 10, 5.0, x, 1, 10, 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, '10', 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, true, 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, false, 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, null, 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, undefined, 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, [], 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, {}, 1 ); // $ExpectError + dwax( 10, 5.0, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax( x.length, 5.0, x, 1, w, '10' ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, true ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, false ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, null ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, undefined ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, [] ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, {} ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax(); // $ExpectError + dwax( x.length ); // $ExpectError + dwax( x.length, 5.0 ); // $ExpectError + dwax( x.length, 5.0, x ); // $ExpectError + dwax( x.length, 5.0, x, 1 ); // $ExpectError + dwax( x.length, 5.0, x, 1, w ); // $ExpectError + dwax( x.length, 5.0, x, 1, w, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float64Array... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray( '10', 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( true, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( false, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( null, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( undefined, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( [], 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( {}, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( ( x: number ): number => x, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray( x.length, '10', x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, true, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, false, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, null, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, undefined, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, [], x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, {}, x, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, ( x: number ): number => x, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float64Array... +{ + const w = new Float64Array( 10 ); + + dwax.ndarray( 10, 5.0, 10, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, '10', 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, true, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, false, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, null, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, undefined, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, [], 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, {}, 1, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, ( x: number ): number => x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray( x.length, 5.0, x, '10', 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, true, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, false, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, null, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, undefined, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, [], 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, {}, 0, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, ( x: number ): number => x, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray( x.length, 5.0, x, 1, '10', w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, true, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, false, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, null, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, undefined, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, [], w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, {}, w, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, ( x: number ): number => x, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dwax.ndarray( 10, 5.0, x, 1, 0, 10, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, '10', 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, true, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, false, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, null, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, undefined, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, [], 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, {}, 1, 0 ); // $ExpectError + dwax.ndarray( 10, 5.0, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray( x.length, 5.0, x, 1, 0, w, '10', 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, true, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, false, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, null, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, undefined, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, [], 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, {}, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, '10' ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, true ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, false ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, null ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, undefined ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, [] ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, {} ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const w = new Float64Array( 10 ); + + dwax.ndarray(); // $ExpectError + dwax.ndarray( x.length ); // $ExpectError + dwax.ndarray( x.length, 5.0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1 ); // $ExpectError + dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/c/example.c new file mode 100644 index 000000000000..6374ea3d1dd0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dwax.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + double w[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_dwax( N, 5.0, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "w[ %i ] = %lf\n", i, w[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/index.js new file mode 100644 index 000000000000..3be08e5c58fd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dwax = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var w = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( w ); + +dwax( x.length, 5.0, x, 1, w, 1 ); +console.log( w ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dwax/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function dwax( N, alpha, x, strideX, w, strideW ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ), w, strideW, stride2offset( N, strideW ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/dwax.native.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/dwax.native.js new file mode 100644 index 000000000000..c5cbd96e77d9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/dwax.native.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `w`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Float64Array} w - output array +* @param {integer} strideW - `w` stride length +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* dwax( x.length, 5.0, x, 1, w, 1 ); +* // w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function dwax( N, alpha, x, strideX, w, strideW ) { + addon( N, alpha, x, strideX, w, strideW ); + return w; +} + + +// EXPORTS // + +module.exports = dwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/index.js new file mode 100644 index 000000000000..a5337b550a2d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/index.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply each element in a double-precision floating-point strided array `x` by a scalar constant and assign the results to elements in a double-precision floating-point strided array `w`. +* +* @module @stdlib/blas/ext/base/dwax +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dwax = require( '@stdlib/blas/ext/base/dwax' ); +* +* var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* dwax( x.length, 5.0, x, 1, w, 1 ); +* // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dwax = require( '@stdlib/blas/ext/base/dwax' ); +* +* var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* dwax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dwax; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dwax = main; +} else { + dwax = tmp; +} + + +// EXPORTS // + +module.exports = dwax; + +// exports: { "ndarray": "dwax.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/main.js new file mode 100644 index 000000000000..7d2d5c6bb069 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dwax = require( './dwax.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( dwax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/native.js new file mode 100644 index 000000000000..08628b9c888c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dwax = require( './dwax.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( dwax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/ndarray.js new file mode 100644 index 000000000000..77804d3802d3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/ndarray.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var dcopy = require( '@stdlib/blas/base/dcopy' ).ndarray; + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float64Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function dwax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + var ix; + var iw; + var m; + var i; + + if ( N <= 0 ) { + return w; + } + // Fast path: when alpha = 1.0, delegate to dcopy (w = x) + if ( alpha === 1.0 ) { + return dcopy( N, x, strideX, offsetX, w, strideW, offsetW ); + } + ix = offsetX; + iw = offsetW; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideW === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + w[ iw ] = alpha * x[ ix ]; + ix += strideX; + iw += strideW; + } + } + if ( N < M ) { + return w; + } + for ( i = m; i < N; i += M ) { + w[ iw ] = alpha * x[ ix ]; + w[ iw+1 ] = alpha * x[ ix+1 ]; + w[ iw+2 ] = alpha * x[ ix+2 ]; + w[ iw+3 ] = alpha * x[ ix+3 ]; + w[ iw+4 ] = alpha * x[ ix+4 ]; + ix += M; + iw += M; + } + return w; + } + for ( i = 0; i < N; i++ ) { + w[ iw ] = alpha * x[ ix ]; + ix += strideX; + iw += strideW; + } + return w; +} + + +// EXPORTS // + +module.exports = dwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/ndarray.native.js new file mode 100644 index 000000000000..39d0781c0b8d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/lib/ndarray.native.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a double-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float64Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function dwax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + addon.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ); + return w; +} + + +// EXPORTS // + +module.exports = dwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dwax/manifest.json new file mode 100644 index 000000000000..6b7da160198a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/manifest.json @@ -0,0 +1,82 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-strided-float64array", + "@stdlib/blas/base/dcopy", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/dcopy", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/dcopy", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/package.json b/lib/node_modules/@stdlib/blas/ext/base/dwax/package.json new file mode 100644 index 000000000000..5e57cc40d5c5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/package.json @@ -0,0 +1,75 @@ +{ + "name": "@stdlib/blas/ext/base/dwax", + "version": "0.0.0", + "description": "Multiply each element in a double-precision floating-point strided array `x` by a scalar constant and assign the results to elements in a double-precision floating-point strided array `w`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "multiply", + "scale", + "strided", + "array", + "ndarray", + "float64", + "double", + "float64array", + "dwax" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dwax/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dwax/src/addon.c new file mode 100644 index 000000000000..64ce1370fb30 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/src/addon.c @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dwax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, W, N, strideW, argv, 4 ); + API_SUFFIX(stdlib_strided_dwax)( N, alpha, X, strideX, W, strideW ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetW, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, W, N, strideW, argv, 5 ); + API_SUFFIX(stdlib_strided_dwax_ndarray)( N, alpha, X, strideX, offsetX, W, strideW, offsetW ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dwax/src/main.c new file mode 100644 index 000000000000..fcc260eab6b3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/src/main.c @@ -0,0 +1,100 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dwax.h" +#include "stdlib/blas/base/dcopy.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Multiplies each element in a double-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `W`. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param W output array +* @param strideW stride length for `W` +*/ +void API_SUFFIX(stdlib_strided_dwax)( const CBLAS_INT N, const double alpha, const double *X, const CBLAS_INT strideX, double *W, const CBLAS_INT strideW ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT ow = stdlib_strided_stride2offset( N, strideW ); + API_SUFFIX(stdlib_strided_dwax_ndarray)( N, alpha, X, strideX, ox, W, strideW, ow ); +} + +/** +* Multiplies each element in a double-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision floating-point strided array `W` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param W output array +* @param strideW stride length for `W` +* @param offsetW starting index for `W` +*/ +void API_SUFFIX(stdlib_strided_dwax_ndarray)( const CBLAS_INT N, const double alpha, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ) { + CBLAS_INT ix; + CBLAS_INT iw; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + if ( alpha == 1.0 ) { + API_SUFFIX(c_dcopy_ndarray)( N, X, strideX, offsetX, W, strideW, offsetW ); + return; + } + ix = offsetX; + iw = offsetW; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideW == 1 ) { + m = N % 5; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + W[ iw ] = alpha * X[ ix ]; + ix += strideX; + iw += strideW; + } + } + if ( N < 5 ) { + return; + } + for ( i = m; i < N; i += 5 ) { + W[ iw ] = alpha * X[ ix ]; + W[ iw+1 ] = alpha * X[ ix+1 ]; + W[ iw+2 ] = alpha * X[ ix+2 ]; + W[ iw+3 ] = alpha * X[ ix+3 ]; + W[ iw+4 ] = alpha * X[ ix+4 ]; + ix += 5; + iw += 5; + } + return; + } + for ( i = 0; i < N; i++ ) { + W[ iw ] = alpha * X[ ix ]; + ix += strideX; + iw += strideW; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.dwax.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.dwax.js new file mode 100644 index 000000000000..51390852b647 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.dwax.js @@ -0,0 +1,269 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dwax = require( './../lib/dwax.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( dwax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float64Array( x.length ); + expected = new Float64Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 5.0, 10.0 ] ); + + dwax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float64Array( x.length ); + out = dwax( x.length, 3.0, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dwax( 0, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + dwax( -4, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + dwax( x.length, 1.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + w = new Float64Array( 3 ); + expected = new Float64Array([ + 5.0, // 1.0 * 5.0 + 15.0, // 3.0 * 5.0 + 25.0 // 5.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 2, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float64Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 1, w, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float64Array( 5 ); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + 0.0, + -25.0, // -5.0 * 5.0 + 0.0, + 30.0 // 6.0 * 5.0 + ]); + + dwax( 3, 5.0, x, -2, w, -2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var w0; + var x1; + var w1; + + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w0 = new Float64Array([ + 10.0, + 10.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Float64Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Float64Array([ + 10.0, + 10.0, + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0 // 4.0 * 5.0 + ]); + + dwax( 3, 5.0, x1, 1, w1, 1 ); + t.deepEqual( w0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float64Array( 100 ); + w = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + w = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.dwax.native.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.dwax.native.js new file mode 100644 index 000000000000..146b67cf6349 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.dwax.native.js @@ -0,0 +1,278 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dwax = tryRequire( resolve( __dirname, './../lib/dwax.native.js' ) ); +var opts = { + 'skip': ( dwax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( dwax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float64Array( x.length ); + expected = new Float64Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 5.0, 10.0 ] ); + + dwax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float64Array( x.length ); + out = dwax( x.length, 3.0, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dwax( 0, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + dwax( -4, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + dwax( x.length, 1.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + w = new Float64Array( 3 ); + expected = new Float64Array([ + 5.0, // 1.0 * 5.0 + 15.0, // 3.0 * 5.0 + 25.0 // 5.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 2, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float64Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 1, w, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float64Array( 5 ); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + 0.0, + -25.0, // -5.0 * 5.0 + 0.0, + 30.0 // 6.0 * 5.0 + ]); + + dwax( 3, 5.0, x, -2, w, -2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var w0; + var x1; + var w1; + + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w0 = new Float64Array([ + 10.0, + 10.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Float64Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Float64Array([ + 10.0, + 10.0, + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0 // 4.0 * 5.0 + ]); + + dwax( 3, 5.0, x1, 1, w1, 1 ); + t.deepEqual( w0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float64Array( 100 ); + w = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + w = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.js new file mode 100644 index 000000000000..a94697595361 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dwax = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dwax.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dwax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dwax, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dwax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dwax, require( './../lib/main.js' ), 'returns JS implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.ndarray.js new file mode 100644 index 000000000000..4d3adb7eea01 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.ndarray.js @@ -0,0 +1,285 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dwax = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( dwax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float64Array( x.length ); + expected = new Float64Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 5.0, 10.0 ] ); + + dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float64Array( x.length ); + out = dwax( x.length, 3.0, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dwax( 0, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + dwax( -4, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + dwax( x.length, 1.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + w = new Float64Array( 3 ); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 2, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float64Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 1, 0, w, 2, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float64Array([ + 0.0, // 2 + 0.0, // 1 + 0.0 // 0 + ]); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( 3, 5.0, x, -2, x.length-1, w, -1, w.length-1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w = new Float64Array( 5 ); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0, // 4.0 * 5.0 + 0.0, + 0.0 + ]); + + dwax( 3, 5.0, x, 1, 1, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float64Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 0.0, + 5.0, // 1.0 * 5.0 + 10.0, // 2.0 * 5.0 + 15.0 // 3.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 1, 0, w, 1, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float64Array( 100 ); + w = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + w = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.ndarray.native.js new file mode 100644 index 000000000000..32e744f95713 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dwax/test/test.ndarray.native.js @@ -0,0 +1,294 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dwax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dwax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( dwax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float64Array( x.length ); + expected = new Float64Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 2.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 5.0, 10.0 ] ); + + dwax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float64Array( x.length ); + out = dwax( x.length, 3.0, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dwax( 0, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + dwax( -4, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float64Array( x.length ); + expected = new Float64Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + dwax( x.length, 1.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + w = new Float64Array( 3 ); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 2, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float64Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 1, 0, w, 2, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float64Array([ + 0.0, // 2 + 0.0, // 1 + 0.0 // 0 + ]); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + dwax( 3, 5.0, x, -2, x.length-1, w, -1, w.length-1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w = new Float64Array( 5 ); + expected = new Float64Array([ + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0, // 4.0 * 5.0 + 0.0, + 0.0 + ]); + + dwax( 3, 5.0, x, 1, 1, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float64Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 0.0, + 5.0, // 1.0 * 5.0 + 10.0, // 2.0 * 5.0 + 15.0 // 3.0 * 5.0 + ]); + + dwax( 3, 5.0, x, 1, 0, w, 1, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float64Array( 100 ); + w = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + w = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + dwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/dxdy/README.md new file mode 100644 index 000000000000..9acaadaf557b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/README.md @@ -0,0 +1,317 @@ + + +# dxdy + +> Divide elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assign the results to `y`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var dxdy = require( '@stdlib/blas/ext/base/dxdy' ); +``` + +#### dxdy( N, x, strideX, y, strideY ) + +Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +dxdy( x.length, x, 1, y, 1 ); +// y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Float64Array`][@stdlib/array/float64]. +- **strideX**: stride length for `x`. +- **y**: output [`Float64Array`][@stdlib/array/float64]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to divide every other element of `x` by every other element of `y`: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 6.0, 1.0, 20.0, 1.0, 42.0, 1.0 ] ); +var y = new Float64Array( [ 2.0, 1.0, 4.0, 1.0, 6.0, 1.0 ] ); + +dxdy( 3, x, 2, y, 2 ); +// y => [ 3.0, 1.0, 5.0, 1.0, 7.0, 1.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 6.0, 12.0, 20.0, 1.0, 1.0 ] ); +var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 3.0, 4.0, 1.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +dxdy( 3, x1, 1, y1, 1 ); +// y0 => [ 1.0, 1.0, 3.0, 4.0, 5.0, 1.0 ] +``` + +#### dxdy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +dxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to divide the last three elements of `x` by the last three elements of `y`: + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var x = new Float64Array( [ 1.0, 2.0, 6.0, 20.0, 42.0 ] ); +var y = new Float64Array( [ 1.0, 2.0, 2.0, 4.0, 6.0 ] ); + +dxdy.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// y => [ 1.0, 2.0, 3.0, 5.0, 7.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dxdy = require( '@stdlib/blas/ext/base/dxdy' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 1, 100, { + 'dtype': 'float64' +}); +console.log( y ); + +dxdy( x.length, x, 1, y, 1 ); +console.log( y ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + +
+ +
+ + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/dxdy.h" +``` + +#### stdlib_strided_dxdy( N, \*X, strideX, \*Y, strideY ) + +Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. + +```c +const double x[] = { 6.0, 12.0, 20.0, 30.0 }; +double y[] = { 2.0, 3.0, 4.0, 5.0 }; + +stdlib_strided_dxdy( 4, x, 1, y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[inout] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_dxdy( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_dxdy_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```c +const double x[] = { 6.0, 12.0, 20.0, 30.0 }; +double y[] = { 2.0, 3.0, 4.0, 5.0 }; + +stdlib_strided_dxdy_ndarray( 4, x, 1, 0, y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] double*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[inout] double*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_dxdy_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + +
+ +
+ + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/dxdy.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + double y[] = { 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Divide elements of `x` by the corresponding elements of `y`: + stdlib_strided_dxdy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %i ] = %lf\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..f818d458dcc2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dxdy = require( './../lib/dxdy.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dxdy( x.length, x, 1, y, 1 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..ac20bd2104f3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dxdy = tryRequire( resolve( __dirname, './../lib/dxdy.native.js' ) ); +var opts = { + 'skip': ( dxdy instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dxdy( x.length, x, 1, y, 1 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..450f5b71ced6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.ndarray.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dxdy = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dxdy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..e3f0801d9e59 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var dxdy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dxdy instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = dxdy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..d3ab86f989f4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/benchmark/c/benchmark.length.c @@ -0,0 +1,207 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dxdy.h" +#include +#include +#include +#include +#include + +#define NAME "dxdy" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int i; + + x = (double *)malloc( len * sizeof(double) ); + y = (double *)malloc( len * sizeof(double) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + y[ i ] = random_uniform( 1.0, 100.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_dxdy( len, x, 1, y, 1 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int i; + + x = (double *)malloc( len * sizeof(double) ); + y = (double *)malloc( len * sizeof(double) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + y[ i ] = random_uniform( 1.0, 100.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_dxdy_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/dxdy/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/repl.txt new file mode 100644 index 000000000000..3fefaebd8f63 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/repl.txt @@ -0,0 +1,125 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Divides elements of a double-precision floating-point strided array `x` by + the corresponding elements of a double-precision floating-point strided + array `y` and assigns the results to `y`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + y: Float64Array + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + y: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var buf = [ 6.0, 12.0, 20.0, 30.0, 42.0 ]; + > var x = new {{alias:@stdlib/array/float64}}( buf ); + > buf = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var y = new {{alias:@stdlib/array/float64}}( buf ); + > {{alias}}( x.length, x, 1, y, 1 ) + [ 3.0, 4.0, 5.0, 6.0, 7.0 ] + + // Using `N` and stride parameters: + > buf = [ 6.0, 1.0, 20.0, 1.0, 42.0, 1.0 ]; + > x = new {{alias:@stdlib/array/float64}}( buf ); + > buf = [ 2.0, 1.0, 4.0, 1.0, 6.0, 1.0 ]; + > y = new {{alias:@stdlib/array/float64}}( buf ); + > {{alias}}( 3, x, 2, y, 2 ) + [ 3.0, 1.0, 5.0, 1.0, 7.0, 1.0 ] + + // Using view offsets: + > var bufX = [ 1.0, 6.0, 12.0, 20.0, 1.0, 1.0 ]; + > var bufY = [ 1.0, 1.0, 2.0, 3.0, 4.0, 1.0 ]; + > var x0 = new {{alias:@stdlib/array/float64}}( bufX ); + > var y0 = new {{alias:@stdlib/array/float64}}( bufY ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetY = y0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, offsetX ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, offsetY ); + > {{alias}}( 3, x1, 1, y1, 1 ) + [ 3.0, 4.0, 5.0, 1.0 ] + > y0 + [ 1.0, 1.0, 3.0, 4.0, 5.0, 1.0 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Divides elements of a double-precision floating-point strided array `x` by + the corresponding elements of a double-precision floating-point strided + array `y` and assigns the results to `y` using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float64Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float64Array + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + y: Float64Array + Output array. + + Examples + -------- + // Standard Usage: + > var buf = [ 6.0, 12.0, 20.0, 30.0, 42.0 ]; + > var x = new {{alias:@stdlib/array/float64}}( buf ); + > buf = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var y = new {{alias:@stdlib/array/float64}}( buf ); + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ 3.0, 4.0, 5.0, 6.0, 7.0 ] + + // Using index offsets: + > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 6.0, 20.0, 42.0 ] ); + > y = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 2.0, 4.0, 6.0 ] ); + > {{alias}}.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ) + [ 1.0, 2.0, 3.0, 5.0, 7.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..830d0efc748f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/types/index.d.ts @@ -0,0 +1,103 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `dxdy`. +*/ +interface Routine { + /** + * Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + * var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * dxdy( x.length, x, 1, y, 1 ); + * // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] + */ + ( N: number, x: Float64Array, strideX: number, y: Float64Array, strideY: number ): Float64Array; + + /** + * Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting `x` index + * @param y - output array + * @param strideY - `y` stride length + * @param offsetY - starting `y` index + * @returns output array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + * var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * dxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] + */ + ndarray( N: number, x: Float64Array, strideX: number, offsetX: number, y: Float64Array, strideY: number, offsetY: number ): Float64Array; +} + +/** +* Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - `x` stride length +* @param y - output array +* @param strideY - `y` stride length +* @returns output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* dxdy( x.length, x, 1, y, 1 ); +* // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* dxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ +declare var dxdy: Routine; + + +// EXPORTS // + +export = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/types/test.ts new file mode 100644 index 000000000000..5141a44bd42e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/docs/types/test.ts @@ -0,0 +1,250 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dxdy = require( './index' ); + + +// TESTS // + +// The function returns a Float64Array... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy( x.length, x, 1, y, 1 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy( '10', x, 1, y, 1 ); // $ExpectError + dxdy( true, x, 1, y, 1 ); // $ExpectError + dxdy( false, x, 1, y, 1 ); // $ExpectError + dxdy( null, x, 1, y, 1 ); // $ExpectError + dxdy( undefined, x, 1, y, 1 ); // $ExpectError + dxdy( [], x, 1, y, 1 ); // $ExpectError + dxdy( {}, x, 1, y, 1 ); // $ExpectError + dxdy( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float64Array... +{ + const y = new Float64Array( 10 ); + + dxdy( 10, 10, 1, y, 1 ); // $ExpectError + dxdy( 10, '10', 1, y, 1 ); // $ExpectError + dxdy( 10, true, 1, y, 1 ); // $ExpectError + dxdy( 10, false, 1, y, 1 ); // $ExpectError + dxdy( 10, null, 1, y, 1 ); // $ExpectError + dxdy( 10, undefined, 1, y, 1 ); // $ExpectError + dxdy( 10, [ '1' ], 1, y, 1 ); // $ExpectError + dxdy( 10, {}, 1, y, 1 ); // $ExpectError + dxdy( 10, ( x: number ): number => x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy( x.length, x, '10', y, 1 ); // $ExpectError + dxdy( x.length, x, true, y, 1 ); // $ExpectError + dxdy( x.length, x, false, y, 1 ); // $ExpectError + dxdy( x.length, x, null, y, 1 ); // $ExpectError + dxdy( x.length, x, undefined, y, 1 ); // $ExpectError + dxdy( x.length, x, [], y, 1 ); // $ExpectError + dxdy( x.length, x, {}, y, 1 ); // $ExpectError + dxdy( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dxdy( 10, x, 1, 10, 1 ); // $ExpectError + dxdy( 10, x, 1, '10', 1 ); // $ExpectError + dxdy( 10, x, 1, true, 1 ); // $ExpectError + dxdy( 10, x, 1, false, 1 ); // $ExpectError + dxdy( 10, x, 1, null, 1 ); // $ExpectError + dxdy( 10, x, 1, undefined, 1 ); // $ExpectError + dxdy( 10, x, 1, [ '1' ], 1 ); // $ExpectError + dxdy( 10, x, 1, {}, 1 ); // $ExpectError + dxdy( 10, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy( x.length, x, 1, y, '10' ); // $ExpectError + dxdy( x.length, x, 1, y, true ); // $ExpectError + dxdy( x.length, x, 1, y, false ); // $ExpectError + dxdy( x.length, x, 1, y, null ); // $ExpectError + dxdy( x.length, x, 1, y, undefined ); // $ExpectError + dxdy( x.length, x, 1, y, [] ); // $ExpectError + dxdy( x.length, x, 1, y, {} ); // $ExpectError + dxdy( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy(); // $ExpectError + dxdy( x.length ); // $ExpectError + dxdy( x.length ); // $ExpectError + dxdy( x.length, x ); // $ExpectError + dxdy( x.length, x, 1 ); // $ExpectError + dxdy( x.length, x, 1, y ); // $ExpectError + dxdy( x.length, x, 1, y ); // $ExpectError + dxdy( x.length, x, 1, y, 1, 10 ); // $ExpectError +} + +// Attached to the main export is an `ndarray` method which returns a Float64Array... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array... +{ + const y = new Float64Array( 10 ); + + dxdy.ndarray( 10, 10, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, '10', 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, true, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, false, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, null, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, undefined, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, [ '1' ], 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, {}, 1, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dxdy.ndarray( 10, x, 1, 0, 10, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, '10', 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, true, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, false, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, null, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, undefined, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, {}, 1, 0 ); // $ExpectError + dxdy.ndarray( 10, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + dxdy.ndarray(); // $ExpectError + dxdy.ndarray( x.length ); // $ExpectError + dxdy.ndarray( x.length ); // $ExpectError + dxdy.ndarray( x.length, x ); // $ExpectError + dxdy.ndarray( x.length, x, 1 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + dxdy.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/c/example.c new file mode 100644 index 000000000000..e81cd4c9dfd7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dxdy.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 }; + double y[] = { 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Divide elements of `x` by the corresponding elements of `y`: + stdlib_strided_dxdy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %i ] = %lf\n", i, y[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/index.js new file mode 100644 index 000000000000..92e4f38a79fe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var dxdy = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 1, 100, { + 'dtype': 'float64' +}); +console.log( y ); + +dxdy( x.length, x, 1, y, 1 ); +console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/dxdy/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ +function dxdy( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/dxdy.native.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/dxdy.native.js new file mode 100644 index 000000000000..2a879d1426d2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/dxdy.native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Float64Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* dxdy( x.length, x, 1, y, 1 ); +* // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ +function dxdy( N, x, strideX, y, strideY ) { + addon( N, x, strideX, y, strideY ); + return y; +} + + +// EXPORTS // + +module.exports = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/index.js new file mode 100644 index 000000000000..ca82cd20f87e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/index.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Divide elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assign the results to `y`. +* +* @module @stdlib/blas/ext/base/dxdy +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dxdy = require( '@stdlib/blas/ext/base/dxdy' ); +* +* var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* dxdy( x.length, x, 1, y, 1 ); +* // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var dxdy = require( '@stdlib/blas/ext/base/dxdy' ); +* +* var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* dxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var dxdy; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + dxdy = main; +} else { + dxdy = tmp; +} + + +// EXPORTS // + +module.exports = dxdy; + +// exports: { "ndarray": "dxdy.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/main.js new file mode 100644 index 000000000000..6beafc839b54 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dxdy = require( './dxdy.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( dxdy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/native.js new file mode 100644 index 000000000000..39f6eb41b341 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var dxdy = require( './dxdy.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( dxdy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/ndarray.js new file mode 100644 index 000000000000..fd525ff2d0ef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/ndarray.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float64Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* dxdy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ +function dxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var ix; + var iy; + var m; + var i; + + if ( N <= 0 ) { + return y; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideY === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + y[ iy ] = x[ ix ] / y[ iy ]; + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return y; + } + for ( i = m; i < N; i += M ) { + y[ iy ] = x[ ix ] / y[ iy ]; + y[ iy+1 ] = x[ ix+1 ] / y[ iy+1 ]; + y[ iy+2 ] = x[ ix+2 ] / y[ iy+2 ]; + y[ iy+3 ] = x[ ix+3 ] / y[ iy+3 ]; + y[ iy+4 ] = x[ ix+4 ] / y[ iy+4 ]; + ix += M; + iy += M; + } + return y; + } + for ( i = 0; i < N; i++ ) { + y[ iy ] = x[ ix ] / y[ iy ]; + ix += strideX; + iy += strideY; + } + return y; +} + + +// EXPORTS // + +module.exports = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/ndarray.native.js new file mode 100644 index 000000000000..b37ca3b14c9e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/lib/ndarray.native.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float64Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float64Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Float64Array} output array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* dxdy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ +function dxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); + return y; +} + + +// EXPORTS // + +module.exports = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dxdy/manifest.json new file mode 100644 index 000000000000..6070dc50b80c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/manifest.json @@ -0,0 +1,98 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float64array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "build", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/dxdy/package.json new file mode 100644 index 000000000000..7b1e0b347909 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/package.json @@ -0,0 +1,80 @@ +{ + "name": "@stdlib/blas/ext/base/dxdy", + "version": "0.0.0", + "description": "Divide elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assign the results to `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "linear", + "algebra", + "subroutines", + "divide", + "division", + "quotient", + "transform", + "strided", + "array", + "ndarray", + "vector", + "xdy", + "dxdy", + "float64", + "double", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/addon.c new file mode 100644 index 000000000000..5c190fb057c4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dxdy.h" +#include "stdlib/napi/export.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float64array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_dxdy)( N, X, strideX, Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_dxdy_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/main.c new file mode 100644 index 000000000000..d8fa9d756936 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/src/main.c @@ -0,0 +1,95 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/dxdy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +static const CBLAS_INT M = 5; + +/** +* Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y`. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param Y output array +* @param strideY stride length for `Y` +*/ +void API_SUFFIX(stdlib_strided_dxdy)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_dxdy_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Divides elements of a double-precision floating-point strided array `x` by the corresponding elements of a double-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param Y output array +* @param strideY stride length for `Y` +* @param offsetY starting index for `Y` +*/ +void API_SUFFIX(stdlib_strided_dxdy_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideY == 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + Y[ iy ] = X[ ix ] / Y[ iy ]; + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return; + } + for ( i = m; i < N; i += M ) { + Y[ iy ] = X[ ix ] / Y[ iy ]; + Y[ iy+1 ] = X[ ix+1 ] / Y[ iy+1 ]; + Y[ iy+2 ] = X[ ix+2 ] / Y[ iy+2 ]; + Y[ iy+3 ] = X[ ix+3 ] / Y[ iy+3 ]; + Y[ iy+4 ] = X[ ix+4 ] / Y[ iy+4 ]; + ix += M; + iy += M; + } + return; + } + for ( i = 0; i < N; i++ ) { + Y[ iy ] = X[ ix ] / Y[ iy ]; + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.dxdy.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.dxdy.js new file mode 100644 index 000000000000..a63ef7df97b2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.dxdy.js @@ -0,0 +1,245 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dxdy = require( './../lib/dxdy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( dxdy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0, // 20.0 / 4.0 + 6.0, // 30.0 / 5.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( [ 10.0, 24.0 ] ); + y = new Float64Array( [ 5.0, 6.0 ] ); + expected = new Float64Array( [ 2.0, 4.0 ] ); + + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = dxdy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dxdy( 0, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + dxdy( -4, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, + 20.0, // 1 + 1.0, + 42.0 // 2 + ]); + y = new Float64Array( [ 2.0, 4.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 5.0, // 20.0 / 4.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( 3, x, 2, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 10.0, 15.0, 20.0 ] ); + y = new Float64Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 10.0 / 2.0 + 30.0, + 5.0, // 15.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, 1, y, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 1.0, + 12.0, // 1 + 1.0, + 20.0 // 0 + ]); + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, -2, y, -1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Float64Array([ + 1.0, + 6.0, // 0 + 12.0, // 1 + 20.0, // 2 + 1.0 + ]); + y0 = new Float64Array([ + 1.0, + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Float64Array([ + 1.0, + 1.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x1, 1, y1, 1 ); + t.deepEqual( y0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float64Array( 100 ); + y = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + y = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.dxdy.native.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.dxdy.native.js new file mode 100644 index 000000000000..27151ee04b56 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.dxdy.native.js @@ -0,0 +1,254 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dxdy = tryRequire( resolve( __dirname, './../lib/dxdy.native.js' ) ); +var opts = { + 'skip': ( dxdy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( dxdy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0, // 20.0 / 4.0 + 6.0, // 30.0 / 5.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( [ 10.0, 24.0 ] ); + y = new Float64Array( [ 5.0, 6.0 ] ); + expected = new Float64Array( [ 2.0, 4.0 ] ); + + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = dxdy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dxdy( 0, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + dxdy( -4, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, + 20.0, // 1 + 1.0, + 42.0 // 2 + ]); + y = new Float64Array( [ 2.0, 4.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 5.0, // 20.0 / 4.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( 3, x, 2, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ 10.0, 15.0, 20.0 ]); + y = new Float64Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 10.0 / 2.0 + 30.0, + 5.0, // 15.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, 1, y, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 1.0, + 12.0, // 1 + 1.0, + 20.0 // 0 + ]); + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, -2, y, -1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Float64Array([ + 1.0, + 6.0, // 0 + 12.0, // 1 + 20.0, // 2 + 1.0 + ]); + y0 = new Float64Array([ + 1.0, + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Float64Array([ + 1.0, + 1.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x1, 1, y1, 1 ); + t.deepEqual( y0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float64Array( 100 ); + y = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + y = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.js new file mode 100644 index 000000000000..2565cc9df497 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var dxdy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof dxdy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var dxdy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dxdy, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var dxdy; + var main; + + main = require( './../lib/main.js' ); + + dxdy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( dxdy, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.ndarray.js new file mode 100644 index 000000000000..9e8ebe8a48e5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.ndarray.js @@ -0,0 +1,291 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dxdy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( dxdy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0, // 20.0 / 4.0 + 6.0, // 30.0 / 5.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( [ 10.0, 24.0 ] ); + y = new Float64Array( [ 5.0, 6.0 ] ); + expected = new Float64Array( [ 2.0, 4.0 ] ); + + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = dxdy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dxdy( 0, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + dxdy( -4, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, + 20.0, // 1 + 1.0, + 42.0 // 2 + ]); + y = new Float64Array( [ 2.0, 4.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 5.0, // 20.0 / 4.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( 3, x, 2, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 10.0, 15.0, 20.0 ] ); + y = new Float64Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 10.0 / 2.0 + 30.0, + 5.0, // 15.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, 1, 0, y, 2, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 1.0, + 12.0, // 1 + 1.0, + 20.0 // 0 + ]); + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, -2, x.length-1, y, -1, y.length-1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 0.0, + 6.0, // 0 + 1.0, + 20.0, // 1 + 1.0, + 42.0 // 2 + ]); + y = new Float64Array( [ 2.0, 4.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 5.0, // 20.0 / 4.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( 3, x, 2, 1, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0 ] ); + y = new Float64Array([ + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, 1, 0, y, 1, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 0.0, + 6.0, // 0 + 0.0, + 12.0, // 1 + 0.0, + 20.0 // 2 + ]); + y = new Float64Array([ + 0.0, + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 0.0 + ]); + expected = new Float64Array([ + 0.0, + 0.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0, // 20.0 / 4.0 + 0.0 + ]); + + dxdy( 3, x, 2, 1, y, 1, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float64Array( 100 ); + y = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + y = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.ndarray.native.js new file mode 100644 index 000000000000..249a7c6150af --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/dxdy/test/test.ndarray.native.js @@ -0,0 +1,300 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var dxdy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( dxdy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( dxdy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0, // 20.0 / 4.0 + 6.0, // 30.0 / 5.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( [ 10.0, 24.0 ] ); + y = new Float64Array( [ 5.0, 6.0 ] ); + expected = new Float64Array( [ 2.0, 4.0 ] ); + + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + y = new Float64Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = dxdy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float64Array( [ 4.0, 5.0, 6.0 ] ); + + dxdy( 0, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + dxdy( -4, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 0 + 1.0, + 20.0, // 1 + 1.0, + 42.0 // 2 + ]); + y = new Float64Array( [ 2.0, 4.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 5.0, // 20.0 / 4.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( 3, x, 2, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 10.0, 15.0, 20.0 ] ); + y = new Float64Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float64Array([ + 5.0, // 10.0 / 2.0 + 30.0, + 5.0, // 15.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, 1, 0, y, 2, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 1.0, + 12.0, // 1 + 1.0, + 20.0 // 0 + ]); + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, -2, x.length-1, y, -1, y.length-1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 0.0, + 6.0, // 0 + 1.0, + 20.0, // 1 + 1.0, + 42.0 // 2 + ]); + y = new Float64Array( [ 2.0, 4.0, 6.0 ] ); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 5.0, // 20.0 / 4.0 + 7.0 // 42.0 / 6.0 + ]); + + dxdy( 3, x, 2, 1, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array( [ 6.0, 12.0, 20.0 ] ); + y = new Float64Array([ + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + dxdy( 3, x, 1, 0, y, 1, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 0.0, + 6.0, // 0 + 0.0, + 12.0, // 1 + 0.0, + 20.0 // 2 + ]); + y = new Float64Array([ + 0.0, + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 0.0 + ]); + expected = new Float64Array([ + 0.0, + 0.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0, // 20.0 / 4.0 + 0.0 + ]); + + dxdy( 3, x, 2, 1, y, 1, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float64Array( 100 ); + y = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + y = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + dxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gcartesian-power/README.md b/lib/node_modules/@stdlib/blas/ext/base/gcartesian-power/README.md index d89ace2acf77..40b2b3d5f485 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gcartesian-power/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/gcartesian-power/README.md @@ -104,8 +104,8 @@ The function has the following parameters: - **strideX**: stride length for `x`. - **offsetX**: starting index for `x`. - **out**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. -- **strideOut1**: stride length of the first dimension of `out`. -- **strideOut2**: stride length of the second dimension of `out`. +- **strideOut1**: stride length for the first dimension of `out`. +- **strideOut2**: stride length for the second dimension of `out`. - **offsetOut**: starting index for `out`. While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last two elements: diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/README.md new file mode 100644 index 000000000000..596dc7707fa0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/README.md @@ -0,0 +1,162 @@ + + +# gfillEqual + +> Replace strided array elements equal to a provided search element with a specified scalar constant. + +
+ +## Usage + +```javascript +var gfillEqual = require( '@stdlib/blas/ext/base/gfill-equal' ); +``` + +#### gfillEqual( N, searchElement, alpha, x, strideX ) + +Replaces strided array elements equal to a provided search element with a specified scalar constant. + +```javascript +var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + +gfillEqual( x.length, 0.0, 5.0, x, 1 ); +// x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **alpha**: scalar constant. +- **x**: input array. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var x = [ 0.0, 1.0, 0.0, -5.0, 4.0, 0.0, -1.0, 0.0 ]; + +gfillEqual( 4, 0.0, 5.0, x, 2 ); +// x => [ 5.0, 1.0, 5.0, -5.0, 4.0, 0.0, -1.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array: +var x0 = new Float64Array( [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0 ] ); + +// Create an offset view: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +gfillEqual( 3, 0.0, 5.0, x1, 2 ); +// x0 => [ 1.0, 5.0, 3.0, 5.0, -5.0, 5.0 ] +``` + +#### gfillEqual.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + +Replaces strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```javascript +var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + +gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +// x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var x = [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0 ]; + +gfillEqual.ndarray( 3, 0.0, 5.0, x, 1, x.length-3 ); +// x => [ 1.0, 0.0, 3.0, 5.0, -5.0, 5.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- When comparing elements, both functions check for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct, and `-0` and `+0` are considered the same. To replace `NaN` values, use [`@stdlib/blas/ext/base/gfill-nan`][@stdlib/blas/ext/base/gfill-nan]. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var zeros = require( '@stdlib/array/zeros' ); +var gfillEqual = require( '@stdlib/blas/ext/base/gfill-equal' ); + +var x = zeros( 10, 'generic' ); +console.log( x ); + +gfillEqual( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +[@stdlib/blas/ext/base/gfill-nan]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill-nan + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..e7192d34e1b4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillEqual = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillEqual( x.length, i, i+1, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..26f9c9b6b2b1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillEqual = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/repl.txt new file mode 100644 index 000000000000..5b0873a0bafb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/repl.txt @@ -0,0 +1,103 @@ + +{{alias}}( N, searchElement, alpha, x, strideX ) + Replaces strided array elements equal to a provided search element with a + specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + > {{alias}}( x.length, 0.0, 5.0, x, 1 ) + [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] + + // Using `N` and stride parameters: + > x = [ 0.0, 1.0, 0.0, -5.0, 4.0, 0.0, -1.0, 0.0 ]; + > {{alias}}( 4, 0.0, 5.0, x, 2 ) + [ 5.0, 1.0, 5.0, -5.0, 4.0, 0.0, -1.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, 0.0, 5.0, x1, 2 ) + [ 5.0, 3.0, 5.0, -5.0, 5.0 ] + > x0 + [ 1.0, 5.0, 3.0, 5.0, -5.0, 5.0 ] + + +{{alias}}.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + Replaces strided array elements equal to a provided search element with a + specified scalar constant using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + > {{alias}}.ndarray( x.length, 0.0, 5.0, x, 1, 0 ) + [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] + + // Using an index offset: + > x = [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0 ]; + > {{alias}}.ndarray( 3, 0.0, 5.0, x, 2, 1 ) + [ 1.0, 5.0, 3.0, 5.0, -5.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..6d8d66158255 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/types/index.d.ts @@ -0,0 +1,99 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfillEqual`. +*/ +interface Routine { + /** + * Replaces strided array elements equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + * + * gfillEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] + */ + = InputArray>( N: number, searchElement: T, alpha: U, x: V, strideX: number ): V; + + /** + * Replaces strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; + * + * gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] + */ + ndarray = InputArray>( N: number, searchElement: T, alpha: U, x: V, strideX: number, offsetX: number ): V; +} + +/** +* Replaces strided array elements equal to a provided search element with a specified scalar constant. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; +* +* gfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +* +* @example +* var x = [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; +* +* gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +*/ +declare var gfillEqual: Routine; + + +// EXPORTS // + +export = gfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/types/test.ts new file mode 100644 index 000000000000..019908c283b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/docs/types/test.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfillEqual = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillEqual( x.length, 0.0, 5.0, x, 1 ); // $ExpectType Float64Array + gfillEqual( x.length, 0.0, 5.0, new AccessorArray( x ), 1 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillEqual( '10', 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual( true, 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual( false, 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual( null, 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual( undefined, 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual( [], 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual( {}, 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual( ( x: number ): number => x, 0.0, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillEqual( x.length, 0.0, 5.0, 10, 1 ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, true, 1 ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, false, 1 ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, null, 1 ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, undefined, 1 ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillEqual( x.length, 0.0, 5.0, x, '10' ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, true ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, false ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, null ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, undefined ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, [] ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, {} ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillEqual(); // $ExpectError + gfillEqual( x.length ); // $ExpectError + gfillEqual( x.length, 0.0 ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0 ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x ); // $ExpectError + gfillEqual( x.length, 0.0, 5.0, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); // $ExpectType Float64Array + gfillEqual.ndarray( x.length, 0.0, 5.0, new AccessorArray( x ), 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillEqual.ndarray( '10', 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillEqual.ndarray( true, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillEqual.ndarray( false, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillEqual.ndarray( null, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillEqual.ndarray( undefined, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillEqual.ndarray( [], 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillEqual.ndarray( {}, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillEqual.ndarray( ( x: number ): number => x, 0.0, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillEqual.ndarray( x.length, 0.0, 5.0, 10, 1, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, true, 1, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, false, 1, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, null, 1, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, undefined, 1, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillEqual.ndarray( x.length, 0.0, 5.0, x, '10', 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, true, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, false, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, null, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, undefined, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, [], 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, {}, 0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, '10' ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, true ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, false ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, null ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, undefined ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, [] ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillEqual.ndarray(); // $ExpectError + gfillEqual.ndarray( x.length ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1 ); // $ExpectError + gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/examples/index.js new file mode 100644 index 000000000000..73dacbce7e81 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/examples/index.js @@ -0,0 +1,28 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var zeros = require( '@stdlib/array/zeros' ); +var gfillEqual = require( './../lib' ); + +var x = zeros( 10, 'generic' ); +console.log( x ); + +gfillEqual( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/accessors.js new file mode 100644 index 000000000000..a48004123a09 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/accessors.js @@ -0,0 +1,75 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replaces strided array elements equal to a provided search element with a specified scalar constant. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Object} input array object +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ]; +* +* gfillEqual( x.length, 0.0, 5.0, arraylike2object( toAccessorArray( x ) ), 1, 0 ); +* // x => [ 5.0, 1.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +*/ +function gfillEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var xbuf; + var get; + var set; + var ix; + var i; + var v; + + // Cache reference to array data: + xbuf = x.data; + + // Cache references to the element accessors: + get = x.accessors[ 0 ]; + set = x.accessors[ 1 ]; + + ix = offsetX; + for ( i = 0; i < N; i++ ) { + v = get( xbuf, ix ); + if ( v === searchElement ) { + set( xbuf, ix, alpha ); + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/index.js new file mode 100644 index 000000000000..982389697a3f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace strided array elements equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/gfill-equal +* +* @example +* var gfillEqual = require( '@stdlib/blas/ext/base/gfill-equal' ); +* +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +* +* @example +* var gfillEqual = require( '@stdlib/blas/ext/base/gfill-equal' ); +* +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/main.js new file mode 100644 index 000000000000..9f081bce52e4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/main.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replaces strided array elements equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @returns {Collection} input array +* +* @example +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function gfillEqual( N, searchElement, alpha, x, strideX ) { + return ndarray( N, searchElement, alpha, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = gfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/ndarray.js new file mode 100644 index 000000000000..61f1604c4de9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/lib/ndarray.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Replaces strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Collection} input array +* +* @example +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillEqual( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] +*/ +function gfillEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var ix; + var o; + var i; + + if ( N <= 0 ) { + return x; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + accessors( N, searchElement, alpha, o, strideX, offsetX ); + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] === searchElement ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/package.json new file mode 100644 index 000000000000..5f126d86d69f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/blas/ext/base/gfill-equal", + "version": "0.0.0", + "description": "Replace strided array elements equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "equal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.js new file mode 100644 index 000000000000..790cf31a6201 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfillEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfillEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.main.js new file mode 100644 index 000000000000..1582e719b17a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.main.js @@ -0,0 +1,379 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfillEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements equal to a provided search element', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 2.0, + 5.0, + 4.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]; + + gfillEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 2.0 ]; + + gfillEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces strided array elements equal to a provided search element (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 2.0, + 5.0, + 4.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]; + + gfillEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 2.0 ]; + + gfillEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillEqual( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are equal to a provided search element, the function returns `x` unchanged (accessors)', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillEqual( x.length, 4.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillEqual( x.length, NaN, 5.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged (accessors)', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillEqual( x.length, NaN, 5.0, toAccessorArray( x ), 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, -0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value (accessors)', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, -0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0, 5.0 ]; + out = gfillEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array (accessors)', function test( t ) { + var out; + var x; + + x = toAccessorArray( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = gfillEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 0.0, -4.0, 1.0 ]; + expected = [ 0.0, -4.0, 1.0 ]; + + gfillEqual( 0, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, -4.0, 1.0 ]; + gfillEqual( -4, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]; + expected = [ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]; + + gfillEqual( 3, 0.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + 2.0, + -3.0, + 4.0, + 0.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 0 + 2.0, + -3.0, + 4.0, + 5.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + + gfillEqual( 2, 0.0, 5.0, toAccessorArray( x ), 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]; + expected = [ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]; + + gfillEqual( 3, 0.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 1 + 2.0, + -3.0, + 4.0, + 0.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 1 + 2.0, + -3.0, + 4.0, + 5.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + + gfillEqual( 2, 0.0, 5.0, toAccessorArray( x ), -4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 4.0, + 6.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + gfillEqual( 3, 0.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.ndarray.js new file mode 100644 index 000000000000..f01bbac786a3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-equal/test/test.ndarray.js @@ -0,0 +1,401 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( gfillEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements equal to a provided search element', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 2.0, + 5.0, + 4.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]; + + gfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 2.0 ]; + + gfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces strided array elements equal to a provided search element (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 2.0, + 5.0, + 4.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]; + + gfillEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 2.0 ]; + + gfillEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillEqual( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are equal to a provided search element, the function returns `x` unchanged (accessors)', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillEqual( x.length, 4.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillEqual( x.length, NaN, 5.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged (accessors)', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillEqual( x.length, NaN, 5.0, toAccessorArray( x ), 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, -0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value (accessors)', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ 5.0, 1.0, 5.0, 5.0 ]; + + gfillEqual( x.length, -0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0, 5.0 ]; + out = gfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array (accessors)', function test( t ) { + var out; + var x; + + x = toAccessorArray( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = gfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 0.0, -4.0, 1.0 ]; + expected = [ 0.0, -4.0, 1.0 ]; + + gfillEqual( 0, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, -4.0, 1.0 ]; + gfillEqual( -4, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]; + expected = [ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]; + + gfillEqual( 3, 0.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + 2.0, + -3.0, + 4.0, + 0.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 0 + 2.0, + -3.0, + 4.0, + 5.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + + gfillEqual( 2, 0.0, 5.0, toAccessorArray( x ), 4, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]; + expected = [ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]; + + gfillEqual( 3, 0.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 1 + 2.0, + -3.0, + 4.0, + 0.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 1 + 2.0, + -3.0, + 4.0, + 5.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + + gfillEqual( 2, 0.0, 5.0, toAccessorArray( x ), -4, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = [ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 6.0 // 2 + ]; + expected = [ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 4.0, + 6.0 // 2 + ]; + + gfillEqual( 3, 0.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 6.0 // 2 + ]; + expected = [ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 4.0, + 6.0 // 2 + ]; + + gfillEqual( 3, 0.0, 5.0, toAccessorArray( x ), 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/README.md new file mode 100644 index 000000000000..dc07e89b8ff6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/README.md @@ -0,0 +1,164 @@ + + +# gfillLessThan + +> Replace strided array elements less than a provided search element with a specified scalar constant. + +
+ +## Usage + +```javascript +var gfillLessThan = require( '@stdlib/blas/ext/base/gfill-less-than' ); +``` + +#### gfillLessThan( N, searchElement, alpha, x, strideX ) + +Replaces strided array elements less than a provided search element with a specified scalar constant. + +```javascript +var x = [ 0.0, 0.0, 1.0, 0.0 ]; + +gfillLessThan( x.length, 0.5, 5.0, x, 1 ); +// x => [ 5.0, 5.0, 1.0, 5.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **alpha**: scalar constant. +- **x**: input array. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var x = [ 0.0, 0.0, 1.0, 0.0 ]; + +gfillLessThan( 2, 0.5, 5.0, x, 2 ); +// x => [ 5.0, 0.0, 1.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array: +var x0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 1.0, 0.0 ] ); + +// Create an offset view: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +gfillLessThan( 3, 0.5, 5.0, x1, 2 ); +// x0 => [ 0.0, 5.0, 0.0, 5.0, 1.0, 5.0 ] +``` + +#### gfillLessThan.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + +Replaces strided array elements less than a provided search element with a specified scalar constant using alternative indexing semantics. + +```javascript +var x = [ 0.0, 0.0, 1.0, 0.0 ]; + +gfillLessThan.ndarray( x.length, 0.5, 5.0, x, 1, 0 ); +// x => [ 5.0, 5.0, 1.0, 5.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var x = [ 0.0, 0.0, 1.0, 0.0 ]; + +gfillLessThan.ndarray( 3, 0.5, 5.0, x, 1, x.length-3 ); +// x => [ 0.0, 5.0, 1.0, 5.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- When comparing elements, both functions use the less-than operator `<`. As a consequence, `NaN` values are never less than any value, and `-0` and `+0` are considered equal. To replace `NaN` values, use [`@stdlib/blas/ext/base/gfill-nan`][@stdlib/blas/ext/base/gfill-nan]. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfillLessThan = require( '@stdlib/blas/ext/base/gfill-less-than' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +gfillLessThan( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +[@stdlib/blas/ext/base/gfill-nan]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/gfill-nan + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/benchmark/benchmark.js new file mode 100644 index 000000000000..9c998dd4f0a8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/benchmark/benchmark.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillLessThan = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, 0.0, 100.0, options ); + gfill( x.length, -1.0, x, 3 ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillLessThan( x.length, i, i+1, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..b95fec25f3eb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/benchmark/benchmark.ndarray.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var gfill = require( '@stdlib/blas/ext/base/gfill' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillLessThan = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, 0.0, 100.0, options ); + gfill( x.length, -1.0, x, 3 ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillLessThan( x.length, i, i+1, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/repl.txt new file mode 100644 index 000000000000..ad07cdc1a8ab --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/repl.txt @@ -0,0 +1,103 @@ + +{{alias}}( N, searchElement, alpha, x, strideX ) + Replaces strided array elements less than a provided search element with a + specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ 0.0, 0.0, 1.0, 0.0 ]; + > {{alias}}( x.length, 0.5, 5.0, x, 1 ) + [ 5.0, 5.0, 1.0, 5.0 ] + + // Using `N` and stride parameters: + > x = [ 0.0, 0.0, 1.0, 0.0 ]; + > {{alias}}( 2, 0.5, 5.0, x, 2 ) + [ 5.0, 0.0, 1.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 0.0, 0.0, 1.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, 0.5, 5.0, x1, 2 ) + [ 5.0, 0.0, 5.0, 1.0, 5.0 ] + > x0 + [ 0.0, 5.0, 0.0, 5.0, 1.0, 5.0 ] + + +{{alias}}.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + Replaces strided array elements less than a provided search element with a + specified scalar constant using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ 0.0, 0.0, 1.0, 0.0 ]; + > {{alias}}.ndarray( x.length, 0.5, 5.0, x, 1, 0 ) + [ 5.0, 5.0, 1.0, 5.0 ] + + // Using an index offset: + > x = [ 0.0, 0.0, 1.0, 0.0 ]; + > {{alias}}.ndarray( 2, 0.5, 5.0, x, 2, 1 ) + [ 0.0, 5.0, 1.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/types/index.d.ts new file mode 100644 index 000000000000..804ea96fa3c5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/types/index.d.ts @@ -0,0 +1,99 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfillLessThan`. +*/ +interface Routine { + /** + * Replaces strided array elements less than a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * gfillLessThan( x.length, 0.5, 5.0, x, 1 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + = InputArray>( N: number, searchElement: T, alpha: U, x: V, strideX: number ): V; + + /** + * Replaces strided array elements less than a provided search element with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var x = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * gfillLessThan.ndarray( x.length, 0.5, 5.0, x, 1, 0 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + ndarray = InputArray>( N: number, searchElement: T, alpha: U, x: V, strideX: number, offsetX: number ): V; +} + +/** +* Replaces strided array elements less than a provided search element with a specified scalar constant. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillLessThan( x.length, 0.5, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +* +* @example +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillLessThan.ndarray( x.length, 0.5, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +declare var gfillLessThan: Routine; + + +// EXPORTS // + +export = gfillLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/types/test.ts new file mode 100644 index 000000000000..b9e99611912f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/docs/types/test.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfillLessThan = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillLessThan( x.length, 0.0, 5.0, x, 1 ); // $ExpectType Float64Array + gfillLessThan( x.length, 0.0, 5.0, new AccessorArray( x ), 1 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillLessThan( '10', 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan( true, 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan( false, 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan( null, 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan( undefined, 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan( [], 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan( {}, 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan( ( x: number ): number => x, 0.0, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillLessThan( x.length, 0.0, 5.0, 10, 1 ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, true, 1 ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, false, 1 ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, null, 1 ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, undefined, 1 ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillLessThan( x.length, 0.0, 5.0, x, '10' ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, true ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, false ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, null ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, undefined ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, [] ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, {} ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillLessThan(); // $ExpectError + gfillLessThan( x.length ); // $ExpectError + gfillLessThan( x.length, 0.0 ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0 ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x ); // $ExpectError + gfillLessThan( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); // $ExpectType Float64Array + gfillLessThan.ndarray( x.length, 0.0, 5.0, new AccessorArray( x ), 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillLessThan.ndarray( '10', 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( true, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( false, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( null, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( undefined, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( [], 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( {}, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( ( x: number ): number => x, 0.0, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillLessThan.ndarray( x.length, 0.0, 5.0, 10, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, true, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, false, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, null, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, undefined, 1, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, '10', 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, true, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, false, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, null, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, undefined, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, [], 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, {}, 0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, '10' ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, true ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, false ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, null ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, undefined ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, [] ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillLessThan.ndarray(); // $ExpectError + gfillLessThan.ndarray( x.length ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1 ); // $ExpectError + gfillLessThan.ndarray( x.length, 0.0, 5.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/examples/index.js new file mode 100644 index 000000000000..31992a0ff7f8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfillLessThan = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +gfillLessThan( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/accessors.js new file mode 100644 index 000000000000..a41b506dcc1e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/accessors.js @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replaces strided array elements less than a provided search element with a specified scalar constant. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Object} input array object +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillLessThan( x.length, 0.5, 5.0, arraylike2object( toAccessorArray( x ) ), 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function gfillLessThan( N, searchElement, alpha, x, strideX, offsetX ) { + var xbuf; + var get; + var set; + var ix; + var i; + + // Cache reference to array data: + xbuf = x.data; + + // Cache references to the element accessors: + get = x.accessors[ 0 ]; + set = x.accessors[ 1 ]; + + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( get( xbuf, ix ) < searchElement ) { + set( xbuf, ix, alpha ); + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/index.js new file mode 100644 index 000000000000..f6e77feef919 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace strided array elements less than a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/gfill-less-than +* +* @example +* var gfillLessThan = require( '@stdlib/blas/ext/base/gfill-less-than' ); +* +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillLessThan( x.length, 0.5, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +* +* @example +* var gfillLessThan = require( '@stdlib/blas/ext/base/gfill-less-than' ); +* +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillLessThan.ndarray( x.length, 0.5, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/main.js new file mode 100644 index 000000000000..9e06ee3d63a1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/main.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replaces strided array elements less than a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @returns {Collection} input array +* +* @example +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillLessThan( x.length, 0.5, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function gfillLessThan( N, searchElement, alpha, x, strideX ) { + return ndarray( N, searchElement, alpha, x, strideX, stride2offset( N, strideX ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gfillLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/ndarray.js new file mode 100644 index 000000000000..dacb25b1d166 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/lib/ndarray.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Replaces strided array elements less than a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Collection} input array +* +* @example +* var x = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* gfillLessThan( x.length, 0.5, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function gfillLessThan( N, searchElement, alpha, x, strideX, offsetX ) { + var ix; + var o; + var i; + + if ( N <= 0 ) { + return x; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + accessors( N, searchElement, alpha, o, strideX, offsetX ); + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] < searchElement ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/package.json new file mode 100644 index 000000000000..3b659df5dc0b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/blas/ext/base/gfill-less-than", + "version": "0.0.0", + "description": "Replace strided array elements less than a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "less-than", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.js new file mode 100644 index 000000000000..cfa46997fed4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfillLessThan = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfillLessThan.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.main.js new file mode 100644 index 000000000000..a39a6237aeba --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.main.js @@ -0,0 +1,379 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillLessThan = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfillLessThan.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements less than a provided search element', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 5.0, + 5.0, + 4.0, + 5.0, + 5.0, + 5.0, + 6.0 + ]; + + gfillLessThan( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 5.0 ]; + + gfillLessThan( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces strided array elements less than a provided search element (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 5.0, + 5.0, + 4.0, + 5.0, + 5.0, + 5.0, + 6.0 + ]; + + gfillLessThan( x.length, 4.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 5.0 ]; + + gfillLessThan( x.length, 4.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are less than a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillLessThan( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are less than a provided search element, the function returns `x` unchanged (accessors)', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillLessThan( x.length, 1.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillLessThan( x.length, NaN, 5.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged (accessors)', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillLessThan( x.length, NaN, 5.0, toAccessorArray( x ), 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, -0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value (accessors)', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, -0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0, 5.0 ]; + out = gfillLessThan( x.length, 4.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array (accessors)', function test( t ) { + var out; + var x; + + x = toAccessorArray( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = gfillLessThan( x.length, 4.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 0.0, -4.0, 1.0 ]; + expected = [ 0.0, -4.0, 1.0 ]; + + gfillLessThan( 0, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, -4.0, 1.0 ]; + gfillLessThan( -4, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]; + expected = [ + 5.0, // 0 + -3.0, + 5.0, // 1 + 7.0, + 5.0 // 2 + ]; + + gfillLessThan( 3, 4.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + 2.0, + -3.0, + 4.0, + 0.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 0 + 2.0, + -3.0, + 4.0, + 5.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + + gfillLessThan( 2, 4.0, 5.0, toAccessorArray( x ), 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]; + expected = [ + 5.0, // 2 + -3.0, + 5.0, // 1 + 7.0, + 5.0 // 0 + ]; + + gfillLessThan( 3, 4.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 1 + 2.0, + -3.0, + 4.0, + 0.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 1 + 2.0, + -3.0, + 4.0, + 5.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + + gfillLessThan( 2, 4.0, 5.0, toAccessorArray( x ), -4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 4.0, + 6.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + gfillLessThan( 3, 4.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.ndarray.js new file mode 100644 index 000000000000..e8bccc5515c4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-less-than/test/test.ndarray.js @@ -0,0 +1,401 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillLessThan = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( gfillLessThan.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements less than a provided search element', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 5.0, + 5.0, + 4.0, + 5.0, + 5.0, + 5.0, + 6.0 + ]; + + gfillLessThan( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 5.0 ]; + + gfillLessThan( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces strided array elements less than a provided search element (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, + 5.0, + 5.0, + 4.0, + 5.0, + 5.0, + 5.0, + 6.0 + ]; + + gfillLessThan( x.length, 4.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 5.0, 5.0 ]; + + gfillLessThan( x.length, 4.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are less than a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillLessThan( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if no elements are less than a provided search element, the function returns `x` unchanged (accessors)', function test( t ) { + var expected; + var x; + + x = [ 1.0, 2.0, 3.0 ]; + expected = [ 1.0, 2.0, 3.0 ]; + + gfillLessThan( x.length, 1.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillLessThan( x.length, NaN, 5.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns `x` unchanged (accessors)', function test( t ) { + var x = [ NaN, 1.0, NaN ]; + + gfillLessThan( x.length, NaN, 5.0, toAccessorArray( x ), 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], 1.0, 'returns expected value' ); + t.ok( isnan( x[ 2 ] ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, -0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value (accessors)', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 1.0, 0.0, -0.0 ]; + + gfillLessThan( x.length, -0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0, 5.0 ]; + out = gfillLessThan( x.length, 4.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array (accessors)', function test( t ) { + var out; + var x; + + x = toAccessorArray( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = gfillLessThan( x.length, 4.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 0.0, -4.0, 1.0 ]; + expected = [ 0.0, -4.0, 1.0 ]; + + gfillLessThan( 0, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, -4.0, 1.0 ]; + gfillLessThan( -4, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]; + expected = [ + 5.0, // 0 + -3.0, + 5.0, // 1 + 7.0, + 5.0 // 2 + ]; + + gfillLessThan( 3, 4.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + 2.0, + -3.0, + 4.0, + 0.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 0 + 2.0, + -3.0, + 4.0, + 5.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + + gfillLessThan( 2, 4.0, 5.0, toAccessorArray( x ), 4, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]; + expected = [ + 5.0, // 2 + -3.0, + 5.0, // 1 + 7.0, + 5.0 // 0 + ]; + + gfillLessThan( 3, 4.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 1 + 2.0, + -3.0, + 4.0, + 0.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 5.0, // 1 + 2.0, + -3.0, + 4.0, + 5.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + + gfillLessThan( 2, 4.0, 5.0, toAccessorArray( x ), -4, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = [ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 6.0 // 2 + ]; + expected = [ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 4.0, + 6.0 // 2 + ]; + + gfillLessThan( 3, 4.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 6.0 // 2 + ]; + expected = [ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 4.0, + 6.0 // 2 + ]; + + gfillLessThan( 3, 4.0, 5.0, toAccessorArray( x ), 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/README.md new file mode 100644 index 000000000000..d75078a511b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/README.md @@ -0,0 +1,158 @@ + + +# gfillNaN + +> Replace strided array elements equal to `NaN` with a specified scalar constant. + +
+ +## Usage + +```javascript +var gfillNaN = require( '@stdlib/blas/ext/base/gfill-nan' ); +``` + +#### gfillNaN( N, alpha, x, strideX ) + +Replaces strided array elements equal to `NaN` with a specified scalar constant. + +```javascript +var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; + +gfillNaN( x.length, 0.0, x, 1 ); +// x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **alpha**: scalar constant. +- **x**: input array. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var x = [ NaN, 1.0, NaN, -5.0, NaN, 0.0, -1.0, -3.0 ]; + +gfillNaN( 4, 0.0, x, 2 ); +// x => [ 0.0, 1.0, 0.0, -5.0, 0.0, 0.0, -1.0, -3.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array: +var x0 = new Float64Array( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + +// Create an offset view: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +gfillNaN( 3, 0.0, x1, 2 ); +// x0 => [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] +``` + +#### gfillNaN.ndarray( N, alpha, x, strideX, offsetX ) + +Replaces strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + +```javascript +var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; + +gfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +// x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var x = [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ]; + +gfillNaN.ndarray( 3, 0.0, x, 1, x.length-3 ); +// x => [ 1.0, NaN, 3.0, 0.0, 5.0, -6.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var nans = require( '@stdlib/array/nans' ); +var gfillNaN = require( '@stdlib/blas/ext/base/gfill-nan' ); + +var x = nans( 10 ); +console.log( x ); + +gfillNaN( x.length, 0.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/benchmark/benchmark.js new file mode 100644 index 000000000000..0bdef7edd7d5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillNaN = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillNaN( x.length, 0.0, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..7b08b9301892 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillNaN = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillNaN( x.length, 0.0, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/repl.txt new file mode 100644 index 000000000000..72f5446a9ea0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/repl.txt @@ -0,0 +1,97 @@ + +{{alias}}( N, alpha, x, strideX ) + Replaces strided array elements equal to `NaN` with a specified scalar + constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ NaN, 1.0, 3.0, NaN, 4.0, -1.0, -3.0 ]; + > {{alias}}( x.length, 0.0, x, 1 ) + [ 0.0, 1.0, 3.0, 0.0, 4.0, -1.0, -3.0 ] + + // Using `N` and stride parameters: + > x = [ NaN, 1.0, NaN, -5.0, NaN, -1.0, -3.0 ]; + > {{alias}}( 4, 0.0, x, 2 ) + [ 0.0, 1.0, 0.0, -5.0, 0.0, -1.0, -3.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 0.0, x1, 2 ) + [ 0.0, 3.0, 0.0, 5.0, -6.0 ] + > x0 + [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] + + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Replaces strided array elements equal to `NaN` with a specified scalar + constant using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ NaN, 1.0, 3.0, NaN, 4.0, -1.0, -3.0 ]; + > {{alias}}.ndarray( x.length, 0.0, x, 1, 0 ) + [ 0.0, 1.0, 3.0, 0.0, 4.0, -1.0, -3.0 ] + + // Using an index offset: + > x = [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ]; + > {{alias}}.ndarray( 3, 0.0, x, 2, 1 ) + [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/types/index.d.ts new file mode 100644 index 000000000000..74bb0cb060c6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/types/index.d.ts @@ -0,0 +1,96 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfillNaN`. +*/ +interface Routine { + /** + * Replaces strided array elements equal to `NaN` with a specified scalar constant. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; + * + * gfillNaN( x.length, 0.0, x, 1 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + = InputArray>( N: number, alpha: T, x: V, strideX: number ): V; + + /** + * Replaces strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; + * + * gfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + ndarray = InputArray>( N: number, alpha: T, x: V, strideX: number, offsetX: number ): V; +} + +/** +* Replaces strided array elements equal to `NaN` with a specified scalar constant. +* +* @param N - number of indexed elements +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; +* +* gfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +* +* @example +* var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; +* +* gfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +* // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +*/ +declare var gfillNaN: Routine; + + +// EXPORTS // + +export = gfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/types/test.ts new file mode 100644 index 000000000000..5ac16e8f4683 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/docs/types/test.ts @@ -0,0 +1,156 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfillNaN = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillNaN( x.length, 0.0, x, 1 ); // $ExpectType Float64Array + gfillNaN( x.length, 0.0, new AccessorArray( x ), 1 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNaN( '10', 0.0, x, 1 ); // $ExpectError + gfillNaN( true, 0.0, x, 1 ); // $ExpectError + gfillNaN( false, 0.0, x, 1 ); // $ExpectError + gfillNaN( null, 0.0, x, 1 ); // $ExpectError + gfillNaN( undefined, 0.0, x, 1 ); // $ExpectError + gfillNaN( [], 0.0, x, 1 ); // $ExpectError + gfillNaN( {}, 0.0, x, 1 ); // $ExpectError + gfillNaN( ( x: number ): number => x, 0.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillNaN( x.length, 0.0, 10, 1 ); // $ExpectError + gfillNaN( x.length, 0.0, true, 1 ); // $ExpectError + gfillNaN( x.length, 0.0, false, 1 ); // $ExpectError + gfillNaN( x.length, 0.0, null, 1 ); // $ExpectError + gfillNaN( x.length, 0.0, undefined, 1 ); // $ExpectError + gfillNaN( x.length, 0.0, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNaN( x.length, 0.0, x, '10' ); // $ExpectError + gfillNaN( x.length, 0.0, x, true ); // $ExpectError + gfillNaN( x.length, 0.0, x, false ); // $ExpectError + gfillNaN( x.length, 0.0, x, null ); // $ExpectError + gfillNaN( x.length, 0.0, x, undefined ); // $ExpectError + gfillNaN( x.length, 0.0, x, [] ); // $ExpectError + gfillNaN( x.length, 0.0, x, {} ); // $ExpectError + gfillNaN( x.length, 0.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillNaN(); // $ExpectError + gfillNaN( x.length ); // $ExpectError + gfillNaN( x.length, 0.0 ); // $ExpectError + gfillNaN( x.length, 0.0, x ); // $ExpectError + gfillNaN( x.length, 0.0, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); // $ExpectType Float64Array + gfillNaN.ndarray( x.length, 0.0, new AccessorArray( x ), 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNaN.ndarray( '10', 0.0, x, 1, 0 ); // $ExpectError + gfillNaN.ndarray( true, 0.0, x, 1, 0 ); // $ExpectError + gfillNaN.ndarray( false, 0.0, x, 1, 0 ); // $ExpectError + gfillNaN.ndarray( null, 0.0, x, 1, 0 ); // $ExpectError + gfillNaN.ndarray( undefined, 0.0, x, 1, 0 ); // $ExpectError + gfillNaN.ndarray( [], 0.0, x, 1, 0 ); // $ExpectError + gfillNaN.ndarray( {}, 0.0, x, 1, 0 ); // $ExpectError + gfillNaN.ndarray( ( x: number ): number => x, 0.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillNaN.ndarray( x.length, 0.0, 10, 1, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, true, 1, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, false, 1, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, null, 1, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, undefined, 1, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNaN.ndarray( x.length, 0.0, x, '10', 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, true, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, false, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, null, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, undefined, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, [], 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, {}, 0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNaN.ndarray( x.length, 0.0, x, 1, '10' ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, true ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, false ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, null ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, undefined ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, [] ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, {} ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillNaN.ndarray(); // $ExpectError + gfillNaN.ndarray( x.length ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1 ); // $ExpectError + gfillNaN.ndarray( x.length, 0.0, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/examples/index.js new file mode 100644 index 000000000000..6b1653475ba6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/examples/index.js @@ -0,0 +1,28 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var nans = require( '@stdlib/array/nans' ); +var gfillNaN = require( './../lib' ); + +var x = nans( 10 ); +console.log( x ); + +gfillNaN( x.length, 0.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/accessors.js new file mode 100644 index 000000000000..6151dcbb4846 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/accessors.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Replaces strided array elements equal to `NaN` with a specified scalar constant. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {*} alpha - scalar constant +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Object} input array object +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ]; +* +* gfillNaN( x.length, 0.0, arraylike2object( toAccessorArray( x ) ), 1, 0 ); +* // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +*/ +function gfillNaN( N, alpha, x, strideX, offsetX ) { + var xbuf; + var get; + var set; + var ix; + var i; + var v; + + // Cache reference to array data: + xbuf = x.data; + + // Cache references to the element accessors: + get = x.accessors[ 0 ]; + set = x.accessors[ 1 ]; + + ix = offsetX; + for ( i = 0; i < N; i++ ) { + v = get( xbuf, ix ); + if ( isnan( v ) ) { + set( xbuf, ix, alpha ); + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/index.js new file mode 100644 index 000000000000..9d232d20da65 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace strided array elements equal to `NaN` with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/gfill-nan +* +* @example +* var gfillNaN = require( '@stdlib/blas/ext/base/gfill-nan' ); +* +* var x = [ NaN, NaN, 1.0, NaN ]; +* +* gfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +* +* @example +* var gfillNaN = require( '@stdlib/blas/ext/base/gfill-nan' ); +* +* var x = [ NaN, NaN, 1.0, NaN ]; +* +* gfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/main.js new file mode 100644 index 000000000000..2fc31ba152cb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/main.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replaces strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @returns {Collection} input array +* +* @example +* var x = [ NaN, NaN, 1.0, NaN ]; +* +* gfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +*/ +function gfillNaN( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = gfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/ndarray.js new file mode 100644 index 000000000000..8ac52887d65f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/lib/ndarray.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Replaces strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Collection} input array +* +* @example +* var x = [ NaN, -2.0, 3.0, NaN, 5.0, -6.0 ]; +* +* gfillNaN( 6, 0.0, x, 1, 0 ); +* // x => [ 0.0, -2.0, 3.0, 0.0, 5.0, -6.0 ] +*/ +function gfillNaN( N, alpha, x, strideX, offsetX ) { + var ix; + var o; + var i; + + if ( N <= 0 ) { + return x; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + accessors( N, alpha, o, strideX, offsetX ); + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( isnan( x[ ix ] ) ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/package.json new file mode 100644 index 000000000000..4b82c89a1ac0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/blas/ext/base/gfill-nan", + "version": "0.0.0", + "description": "Replace strided array elements equal to NaN with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "nan", + "not-a-number", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.js new file mode 100644 index 000000000000..496b0b764a7f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfillNaN = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfillNaN.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.main.js new file mode 100644 index 000000000000..addf10f3af8c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.main.js @@ -0,0 +1,278 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillNaN = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( gfillNaN.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', function test( t ) { + var expected; + var x; + + x = [ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + + gfillNaN( x.length, 0.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ NaN, 2.0 ]; + expected = [ 5.0, 2.0 ]; + + gfillNaN( x.length, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array (accessors)', function test( t ) { + var expected; + var x; + + x = [ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + + gfillNaN( x.length, 0.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, NaN, 3.0, NaN, 5.0 ]; + out = gfillNaN( x.length, 0.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var x; + + x = [ NaN, -4.0, 1.0 ]; + + gfillNaN( 0, 0.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = [ NaN, -4.0, 1.0 ]; + gfillNaN( -4, 0.0, x, 1 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]; + expected = [ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]; + + gfillNaN( 3, 0.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 0 + 2.0, + -3.0, + 5.0, + NaN, // 1 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, // 0 + 2.0, + -3.0, + 5.0, + 0.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + + gfillNaN( 2, 0.0, toAccessorArray( x ), 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]; + expected = [ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]; + + gfillNaN( 3, 0.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 1 + 2.0, + -3.0, + 5.0, + NaN, // 0 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, // 1 + 2.0, + -3.0, + 5.0, + 0.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + + gfillNaN( 2, 0.0, toAccessorArray( x ), -4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float64Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + gfillNaN( 3, 0.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.ndarray.js new file mode 100644 index 000000000000..197b6e28d00e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-nan/test/test.ndarray.js @@ -0,0 +1,300 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillNaN = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfillNaN.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', function test( t ) { + var expected; + var x; + + x = [ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + + gfillNaN( x.length, 0.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ NaN, 2.0 ]; + expected = [ 5.0, 2.0 ]; + + gfillNaN( x.length, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array (accessors)', function test( t ) { + var expected; + var x; + + x = [ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + + gfillNaN( x.length, 0.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, NaN, 3.0, NaN, 5.0 ]; + out = gfillNaN( x.length, 0.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var x; + + x = [ NaN, -4.0, 1.0 ]; + + gfillNaN( 0, 0.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = [ NaN, -4.0, 1.0 ]; + gfillNaN( -4, 0.0, x, 1, 0 ); + t.ok( isnan( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]; + expected = [ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]; + + gfillNaN( 3, 0.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 0 + 2.0, + -3.0, + 5.0, + NaN, // 1 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, // 0 + 2.0, + -3.0, + 5.0, + 0.0, // 1 + 2.0, + -5.0, + 6.0 + ]; + + gfillNaN( 2, 0.0, toAccessorArray( x ), 4, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]; + expected = [ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]; + + gfillNaN( 3, 0.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + NaN, // 1 + 2.0, + -3.0, + 5.0, + NaN, // 0 + 2.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, // 1 + 2.0, + -3.0, + 5.0, + 0.0, // 0 + 2.0, + -5.0, + 6.0 + ]; + + gfillNaN( 2, 0.0, toAccessorArray( x ), -4, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = [ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]; + expected = [ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]; + + gfillNaN( 3, 0.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]; + expected = [ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]; + + gfillNaN( 3, 0.0, toAccessorArray( x ), 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/README.md new file mode 100644 index 000000000000..31b43dc81f6b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/README.md @@ -0,0 +1,162 @@ + + +# gfillNotEqual + +> Replace strided array elements not equal to a provided search element with a specified scalar constant. + +
+ +## Usage + +```javascript +var gfillNotEqual = require( '@stdlib/blas/ext/base/gfill-not-equal' ); +``` + +#### gfillNotEqual( N, searchElement, alpha, x, strideX ) + +Replaces strided array elements not equal to a provided search element with a specified scalar constant. + +```javascript +var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + +gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **alpha**: scalar constant. +- **x**: input array. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + +gfillNotEqual( 3, 0.0, 5.0, x, 2 ); +// x => [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array: +var x0 = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +// Create an offset view: +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +gfillNotEqual( 3, 0.0, 5.0, x1, 2 ); +// x0 => [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] +``` + +#### gfillNotEqual.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + +Replaces strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```javascript +var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + +gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + +gfillNotEqual.ndarray( 3, 0.0, 5.0, x, 1, x.length-3 ); +// x => [ 0.0, -2.0, 3.0, 0.0, 5.0, 5.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- When comparing elements, both functions check for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfillNotEqual = require( '@stdlib/blas/ext/base/gfill-not-equal' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'generic' +}); +console.log( x ); + +gfillNotEqual( x.length, 1, 5, x, 1 ); +console.log( x ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..214426315e32 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillNotEqual = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillNotEqual( x.length, i, i+1, x, 1 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..8195a6c5acfb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillNotEqual = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = gfillNotEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/repl.txt new file mode 100644 index 000000000000..2b29e4de922a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/repl.txt @@ -0,0 +1,103 @@ + +{{alias}}( N, searchElement, alpha, x, strideX ) + Replaces strided array elements not equal to a provided search element with + a specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + > {{alias}}( x.length, 0.0, 5.0, x, 1 ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + // Using `N` and stride parameters: + > x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + > {{alias}}( 3, 0.0, 5.0, x, 2 ) + [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, 0.0, 5.0, x1, 2 ) + [ 5.0, 3.0, 0.0, 4.0, 5.0 ] + > x0 + [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] + + +{{alias}}.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + Replaces strided array elements not equal to a provided search element with + a specified scalar constant using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + alpha: any + Scalar constant. + + x: ArrayLikeObject + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: ArrayLikeObject + Input array. + + Examples + -------- + // Standard Usage: + > var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + > {{alias}}.ndarray( x.length, 0.0, 5.0, x, 1, 0 ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + // Using an index offset: + > x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + > {{alias}}.ndarray( 3, 0.0, 5.0, x, 2, 1 ) + [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..0fe5a22f5141 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/types/index.d.ts @@ -0,0 +1,99 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfillNotEqual`. +*/ +interface Routine { + /** + * Replaces strided array elements not equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + * + * gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + = InputArray>( N: number, searchElement: T, alpha: U, x: V, strideX: number ): V; + + /** + * Replaces strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + * + * gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + ndarray = InputArray>( N: number, searchElement: T, alpha: U, x: V, strideX: number, offsetX: number ): V; +} + +/** +* Replaces strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +* +* @example +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +declare var gfillNotEqual: Routine; + + +// EXPORTS // + +export = gfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..376097285cee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/docs/types/test.ts @@ -0,0 +1,158 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfillNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); // $ExpectType Float64Array + gfillNotEqual( x.length, 0.0, 5.0, new AccessorArray( x ), 1 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual( '10', 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual( true, 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual( false, 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual( null, 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual( undefined, 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual( [], 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual( {}, 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual( ( x: number ): number => x, 0.0, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual( x.length, 0.0, 5.0, 10, 1 ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, true, 1 ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, false, 1 ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, null, 1 ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, undefined, 1 ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual( x.length, 0.0, 5.0, x, '10' ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, true ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, false ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, null ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, undefined ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, [] ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, {} ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual(); // $ExpectError + gfillNotEqual( x.length ); // $ExpectError + gfillNotEqual( x.length, 0.0 ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0 ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x ); // $ExpectError + gfillNotEqual( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a collection... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); // $ExpectType Float64Array + gfillNotEqual.ndarray( x.length, 0.0, 5.0, new AccessorArray( x ), 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual.ndarray( '10', 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( true, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( false, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( null, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( undefined, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( [], 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( {}, 0.0, 5.0, x, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( ( x: number ): number => x, 0.0, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a collection... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual.ndarray( x.length, 0.0, 5.0, 10, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, true, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, false, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, null, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, undefined, 1, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, '10', 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, true, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, false, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, null, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, undefined, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, [], 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, {}, 0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, '10' ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, true ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, false ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, null ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, undefined ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, [] ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + gfillNotEqual.ndarray(); // $ExpectError + gfillNotEqual.ndarray( x.length ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1 ); // $ExpectError + gfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/examples/index.js new file mode 100644 index 000000000000..8e94b4c9960b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfillNotEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'generic' +}); +console.log( x ); + +gfillNotEqual( x.length, 1, 5, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/accessors.js new file mode 100644 index 000000000000..d84b5e46e96d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/accessors.js @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replaces strided array elements not equal to a provided search element with a specified scalar constant. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Object} input array object +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillNotEqual( 6, 0.0, 5.0, arraylike2object( toAccessorArray( x ) ), 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function gfillNotEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var xbuf; + var get; + var set; + var ix; + var i; + + // Cache reference to array data: + xbuf = x.data; + + // Cache references to the element accessors: + get = x.accessors[ 0 ]; + set = x.accessors[ 1 ]; + + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( get( xbuf, ix ) !== searchElement ) { + set( xbuf, ix, alpha ); + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/index.js new file mode 100644 index 000000000000..0f54d104454b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace strided array elements not equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/gfill-not-equal +* +* @example +* var gfillNotEqual = require( '@stdlib/blas/ext/base/gfill-not-equal' ); +* +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +* +* @example +* var gfillNotEqual = require( '@stdlib/blas/ext/base/gfill-not-equal' ); +* +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/main.js new file mode 100644 index 000000000000..cff23e157471 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/main.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replaces strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @returns {Collection} input array +* +* @example +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function gfillNotEqual( N, searchElement, alpha, x, strideX ) { + return ndarray( N, searchElement, alpha, x, strideX, stride2offset( N, strideX ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/ndarray.js new file mode 100644 index 000000000000..4ae7578ddced --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/lib/ndarray.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Replaces strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {*} alpha - scalar constant +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Collection} input array +* +* @example +* var x = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; +* +* gfillNotEqual( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function gfillNotEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var ix; + var o; + var i; + + if ( N <= 0 ) { + return x; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + accessors( N, searchElement, alpha, o, strideX, offsetX ); + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] !== searchElement ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = gfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/package.json new file mode 100644 index 000000000000..c29fa94db92d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/blas/ext/base/gfill-not-equal", + "version": "0.0.0", + "description": "Replace strided array elements not equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "not equal", + "unequal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.js new file mode 100644 index 000000000000..b649b48022be --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfillNotEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfillNotEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.main.js new file mode 100644 index 000000000000..8ae585edc092 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.main.js @@ -0,0 +1,405 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillNotEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfillNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 4.0, 4.0, 4.0 ]; + expected = [ 4.0, 4.0, 4.0 ]; + + gfillNotEqual( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged (accessors)', function test( t ) { + var expected; + var x; + + x = [ 4.0, 4.0, 4.0 ]; + expected = [ 4.0, 4.0, 4.0 ]; + + gfillNotEqual( x.length, 4.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var expected; + var x; + + x = [ NaN, 1.0, NaN ]; + expected = [ 5.0, 5.0, 5.0 ]; + + gfillNotEqual( x.length, NaN, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements (accessors)', function test( t ) { + var expected; + var x; + + x = [ NaN, 1.0, NaN ]; + expected = [ 5.0, 5.0, 5.0 ]; + + gfillNotEqual( x.length, NaN, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var expected; + var x; + + x = [ NaN, 0.0, NaN ]; + expected = [ 5.0, 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements (accessors)', function test( t ) { + var expected; + var x; + + x = [ NaN, 0.0, NaN ]; + expected = [ 5.0, 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, -0.0, 5.0, x, 1 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value (accessors)', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, -0.0, 5.0, toAccessorArray( x ), 1 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0, 5.0 ]; + out = gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array (accessors)', function test( t ) { + var out; + var x; + + x = toAccessorArray( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = gfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 0.0, -4.0, 1.0 ]; + expected = [ 0.0, -4.0, 1.0 ]; + + gfillNotEqual( 0, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, -4.0, 1.0 ]; + gfillNotEqual( -4, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]; + expected = [ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]; + expected = [ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, toAccessorArray( x ), 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]; + expected = [ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]; + expected = [ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, toAccessorArray( x ), -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float64Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float64Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + gfillNotEqual( 3, 0.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.ndarray.js new file mode 100644 index 000000000000..222088d8e0e0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfill-not-equal/test/test.ndarray.js @@ -0,0 +1,427 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfillNotEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( gfillNotEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]; + expected = [ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, 2.0 ]; + expected = [ 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 4.0, 4.0, 4.0 ]; + expected = [ 4.0, 4.0, 4.0 ]; + + gfillNotEqual( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged (accessors)', function test( t ) { + var expected; + var x; + + x = [ 4.0, 4.0, 4.0 ]; + expected = [ 4.0, 4.0, 4.0 ]; + + gfillNotEqual( x.length, 4.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var expected; + var x; + + x = [ NaN, 1.0, NaN ]; + expected = [ 5.0, 5.0, 5.0 ]; + + gfillNotEqual( x.length, NaN, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements (accessors)', function test( t ) { + var expected; + var x; + + x = [ NaN, 1.0, NaN ]; + expected = [ 5.0, 5.0, 5.0 ]; + + gfillNotEqual( x.length, NaN, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var expected; + var x; + + x = [ NaN, 0.0, NaN ]; + expected = [ 5.0, 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements (accessors)', function test( t ) { + var expected; + var x; + + x = [ NaN, 0.0, NaN ]; + expected = [ 5.0, 0.0, 5.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, -0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value (accessors)', function test( t ) { + var expected; + var x; + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, 0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + x = [ -0.0, 1.0, 0.0, -0.0 ]; + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + + gfillNotEqual( x.length, -0.0, 5.0, toAccessorArray( x ), 1, 0 ); + t.strictEqual( isSameArray( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = [ 1.0, 0.0, 3.0, 0.0, 5.0 ]; + out = gfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'the function returns a reference to the input array (accessors)', function test( t ) { + var out; + var x; + + x = toAccessorArray( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = gfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = [ 0.0, -4.0, 1.0 ]; + expected = [ 0.0, -4.0, 1.0 ]; + + gfillNotEqual( 0, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = [ 0.0, -4.0, 1.0 ]; + gfillNotEqual( -4, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]; + expected = [ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]; + expected = [ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, toAccessorArray( x ), 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]; + expected = [ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]; + expected = [ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]; + + gfillNotEqual( 3, 0.0, 5.0, toAccessorArray( x ), -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]; + expected = [ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]; + + gfillNotEqual( 3, 0.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter (accessors)', function test( t ) { + var expected; + var x; + + x = [ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]; + expected = [ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]; + + gfillNotEqual( 3, 0.0, 5.0, toAccessorArray( x ), 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/lib/ndarray.js index 8ebf19af4e9e..ddd30561008d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gfind-last-index/lib/ndarray.js @@ -62,8 +62,7 @@ function gfindLastIndex( N, x, strideX, offsetX, clbk, thisArg ) { return idx; } // Convert the index from the reversed "view" to an index in the original "view": - idx = N - 1 - idx; - return idx; + return N - 1 - idx; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/README.md new file mode 100644 index 000000000000..e3e72fdbac37 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/README.md @@ -0,0 +1,201 @@ + + +# gfirstIndexEqual + +> Return the index of the first element in a strided array equal to a corresponding element in another strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var gfirstIndexEqual = require( '@stdlib/blas/ext/base/gfirst-index-equal' ); +``` + +#### gfirstIndexEqual( N, x, strideX, y, strideY ) + +Returns the index of the first element in a strided array equal to a corresponding element in another strided array. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 0.0, 0.0, 3.0, 0.0 ]; + +var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input array. +- **strideX**: stride length for `x`. +- **y**: second input array. +- **strideY**: stride length for `y`. + +If the function is unable to find matching elements, the function returns `-1`. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 5.0, 6.0, 7.0, 8.0 ]; + +var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compare every other element: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + +var idx = gfirstIndexEqual( 3, x, 2, y, 2 ); +// returns 1 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = gfirstIndexEqual( 2, x1, 1, y1, 1 ); +// returns 1 +``` + +#### gfirstIndexEqual.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Returns the index of the first element in a strided array equal to a corresponding element in another strided array using alternative indexing semantics. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 0.0, 0.0, 3.0, 0.0 ]; + +var idx = gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last three elements of each strided array: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 0.0, 0.0, 0.0, 4.0, 5.0, 6.0 ]; + +var idx = gfirstIndexEqual.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 0 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct, and `-0` and `+0` are considered the same. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexEqual = require( '@stdlib/blas/ext/base/gfirst-index-equal' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..7bdb57c00288 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/benchmark/benchmark.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexEqual( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..62c17322655f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexEqual = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/repl.txt new file mode 100644 index 000000000000..8af16549ed83 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/repl.txt @@ -0,0 +1,111 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a strided array equal to a + corresponding element in another strided array. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 2.0, 3.0, 4.0 ]; + > var y = [ 0.0, 0.0, 3.0, 0.0 ]; + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + > idx = {{alias}}( 3, x, 2, y, 2 ) + 1 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var y0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + > idx = {{alias}}( 3, x1, 2, y1, 2 ) + -1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a strided array equal to a + corresponding element in another strided array using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on + starting indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 2.0, 3.0, 4.0 ]; + > var y = [ 0.0, 0.0, 3.0, 0.0 ]; + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using offsets: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + > idx = {{alias}}.ndarray( 3, x, 2, 1, y, 2, 2 ) + -1 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..39894631667c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/types/index.d.ts @@ -0,0 +1,116 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfirstIndexEqual`. +*/ +interface Routine { + /** + * Returns the index of the first element in a strided array equal to a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find matching elements, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: InputArray, strideX: number, y: InputArray, strideY: number ): number; + + /** + * Returns the index of the first element in a strided array equal to a corresponding element in another strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find matching elements, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number, y: InputArray, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a strided array equal to a corresponding element in another strided array. +* +* ## Notes +* +* - If the function is unable to find matching elements, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var gfirstIndexEqual: Routine; + + +// EXPORTS // + +export = gfirstIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/types/test.ts new file mode 100644 index 000000000000..cb544495117f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/docs/types/test.ts @@ -0,0 +1,237 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfirstIndexEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual( x.length, x, 1, y, 1 ); // $ExpectType number + gfirstIndexEqual( x.length, new AccessorArray( x ), 1, new AccessorArray( y ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual( '1', x, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( true, x, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( false, x, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( null, x, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( undefined, x, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( [], x, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( {}, x, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual( 3, 10, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( 3, true, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( 3, false, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( 3, null, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( 3, undefined, 1, y, 1 ); // $ExpectError + gfirstIndexEqual( 3, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual( x.length, x, '1', y, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, true, y, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, false, y, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, null, y, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, undefined, y, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, [], y, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, {}, y, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + const x = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual( x.length, x, 1, 10, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, true, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, false, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, null, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, undefined, 1 ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual( x.length, x, 1, y, '1' ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, y, true ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, y, false ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, y, null ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, y, undefined ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, y, [] ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, y, {} ); // $ExpectError + gfirstIndexEqual( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual(); // $ExpectError + gfirstIndexEqual( 3 ); // $ExpectError + gfirstIndexEqual( 3, x ); // $ExpectError + gfirstIndexEqual( 3, x, 1 ); // $ExpectError + gfirstIndexEqual( 3, x, 1, y ); // $ExpectError + gfirstIndexEqual( 3, x, 1, y, 1, 0 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number + gfirstIndexEqual.ndarray( x.length, new AccessorArray( x ), 1, 0, new AccessorArray( y ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a collection... +{ + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( 3, 10, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, true, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, false, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, null, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, undefined, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a collection... +{ + const x = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( x.length, x, 1, 0, 10, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexEqual.ndarray(); // $ExpectError + gfirstIndexEqual.ndarray( 3 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, x ); // $ExpectError + gfirstIndexEqual.ndarray( 3, x, 1 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, x, 1, 0 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, x, 1, 0, y ); // $ExpectError + gfirstIndexEqual.ndarray( 3, x, 1, 0, y, 1 ); // $ExpectError + gfirstIndexEqual.ndarray( 3, x, 1, 0, y, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/examples/index.js new file mode 100644 index 000000000000..a6d1d1dec38c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/accessors.js new file mode 100644 index 000000000000..e9b7d1895c24 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/accessors.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns the index of the first element in a strided array equal to a corresponding element in another strided array. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - first input array object +* @param {Collection} x.data - first input array data +* @param {Array} x.accessors - first array element accessors +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Object} y - second input array object +* @param {Collection} y.data - second input array data +* @param {Array} y.accessors - second array element accessors +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = gfirstIndexEqual( x.length, arraylike2object( toAccessorArray( x ) ), 1, 0, arraylike2object( toAccessorArray( y ) ), 1, 0 ); +* // returns 2 +*/ +function gfirstIndexEqual( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xbuf; + var ybuf; + var xget; + var yget; + var ix; + var iy; + var i; + + // Cache reference to array data: + xbuf = x.data; + ybuf = y.data; + + // Cache a reference to the element accessors: + xget = x.accessors[ 0 ]; + yget = y.accessors[ 0 ]; + + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( xget( xbuf, ix ) === yget( ybuf, iy ) ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/index.js new file mode 100644 index 000000000000..2cd4f1690a06 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the first element in a strided array equal to a corresponding element in another strided array. +* +* @module @stdlib/blas/ext/base/gfirst-index-equal +* +* @example +* var gfirstIndexEqual = require( '@stdlib/blas/ext/base/gfirst-index-equal' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +* var y = [ 5.0, 4.0, 3.0, 2.0, 1.0 ]; +* +* var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var gfirstIndexEqual = require( '@stdlib/blas/ext/base/gfirst-index-equal' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +* var y = [ 5.0, 4.0, 3.0, 2.0, 1.0 ]; +* +* var idx = gfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/main.js new file mode 100644 index 000000000000..6880c0cef142 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array equal to a corresponding element in another strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @returns {integer} index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = gfirstIndexEqual( x.length, x, 1, y, 1 ); +* // returns 2 +*/ +function gfirstIndexEqual( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gfirstIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/ndarray.js new file mode 100644 index 000000000000..d835f9601dbb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/lib/ndarray.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array equal to a corresponding element in another strided array using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = gfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +function gfirstIndexEqual( N, x, strideX, offsetX, y, strideY, offsetY ) { + var ix; + var iy; + var ox; + var oy; + var i; + + if ( N <= 0 ) { + return -1; + } + ox = arraylike2object( x ); + oy = arraylike2object( y ); + if ( ox.accessorProtocol || oy.accessorProtocol ) { + return accessors( N, ox, strideX, offsetX, oy, strideY, offsetY ); + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] === y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/package.json new file mode 100644 index 000000000000..3dbcb361165c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/gfirst-index-equal", + "version": "0.0.0", + "description": "Return the index of the first element in a strided array equal to a corresponding element in another strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "equal", + "index", + "compare", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.js new file mode 100644 index 000000000000..39d2e573b87a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfirstIndexEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfirstIndexEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.main.js new file mode 100644 index 000000000000..e8f8c989ce8d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.main.js @@ -0,0 +1,440 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfirstIndexEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + // Nonnegative stride... + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ]; + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ] ); + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 0, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexEqual( -1, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexEqual( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, [ NaN ], 1, [ NaN ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN` (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, toAccessorArray( [ NaN ] ), 1, toAccessorArray( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, [ -0.0 ], 1, [ 0.0 ], 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, toAccessorArray( [ -0.0 ] ), 1, toAccessorArray( [ 0.0 ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, toAccessorArray( x ), 2, toAccessorArray( y ), 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = gfirstIndexEqual( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = gfirstIndexEqual( 3, toAccessorArray( x ), 1, toAccessorArray( y ), 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, toAccessorArray( x ), -2, toAccessorArray( y ), -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float64Array([ + 1.0, + 2.0, // 2 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 4.0, // 1 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = gfirstIndexEqual( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.ndarray.js new file mode 100644 index 000000000000..654f26045608 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-equal/test/test.ndarray.js @@ -0,0 +1,405 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( gfirstIndexEqual.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + // Nonnegative stride... + actual = gfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = gfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = gfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = gfirstIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = toAccessorArray( [ 5.0, 6.0, 7.0, 8.0 ] ); + + actual = gfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 0, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexEqual( -1, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexEqual( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, [ NaN ], 1, 0, [ NaN ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN` (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, toAccessorArray( [ NaN ] ), 1, 0, toAccessorArray( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, [ -0.0 ], 1, 0, [ 0.0 ], 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexEqual( 1, toAccessorArray( [ -0.0 ] ), 1, 0, toAccessorArray( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = gfirstIndexEqual( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = gfirstIndexEqual( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, toAccessorArray( x ), -2, 4, toAccessorArray( y ), -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = gfirstIndexEqual( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/README.md new file mode 100644 index 000000000000..87b03420cbdf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/README.md @@ -0,0 +1,207 @@ + + +# gfirstIndexGreaterThan + +> Return the index of the first element in a strided array which is greater than a corresponding element in another strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var gfirstIndexGreaterThan = require( '@stdlib/blas/ext/base/gfirst-index-greater-than' ); +``` + +#### gfirstIndexGreaterThan( N, x, strideX, y, strideY ) + +Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 2.0, 2.0, 2.0, 2.0 ]; + +var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input array. +- **strideX**: stride length for `x`. +- **y**: second input array. +- **strideY**: stride length for `y`. + +If the function is unable to find an element in `x` which is greater than a corresponding element in `y`, the function returns `-1`. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 5.0, 6.0, 7.0, 8.0 ]; + +var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compare every other element: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + +var idx = gfirstIndexGreaterThan( 3, x, 2, y, 2 ); +// returns 1 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( [ 9.0, 9.0, 0.0, 9.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = gfirstIndexGreaterThan( 2, x1, 1, y1, 1 ); +// returns 1 +``` + + + +#### gfirstIndexGreaterThan.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + + + +Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array using alternative indexing semantics. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 2.0, 2.0, 2.0, 2.0 ]; + +var idx = gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last three elements of each strided array: + + + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0 ]; + +var idx = gfirstIndexGreaterThan.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 0 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks whether an element in `x` is greater than a corresponding element in `y` using the greater-than operator `>`. As a consequence, comparisons involving `NaN` always evaluate to `false`. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexGreaterThan = require( '@stdlib/blas/ext/base/gfirst-index-greater-than' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/benchmark/benchmark.js new file mode 100644 index 000000000000..851f28a2ceff --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/benchmark/benchmark.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexGreaterThan = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..25bda681442c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/benchmark/benchmark.ndarray.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexGreaterThan = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexGreaterThan( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/repl.txt new file mode 100644 index 000000000000..2786a7cb1ccb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/repl.txt @@ -0,0 +1,111 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a strided array which is greater + than a corresponding element in another strided array. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 2.0, 3.0, 4.0 ]; + > var y = [ 2.0, 2.0, 2.0, 2.0 ]; + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + > idx = {{alias}}( 3, x, 2, y, 2 ) + 1 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 0.0 ] ); + > var y0 = new {{alias:@stdlib/array/float64}}( [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + > idx = {{alias}}( 3, x1, 2, y1, 2 ) + -1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a strided array which is greater + than a corresponding element in another strided array using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on + starting indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 2.0, 3.0, 4.0 ]; + > var y = [ 2.0, 2.0, 2.0, 2.0 ]; + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using offsets: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 0.0 ]; + > y = [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0, 0.0 ]; + > idx = {{alias}}.ndarray( 3, x, 2, 1, y, 2, 2 ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/types/index.d.ts new file mode 100644 index 000000000000..60eeba2e4494 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/types/index.d.ts @@ -0,0 +1,116 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfirstIndexGreaterThan`. +*/ +interface Routine { + /** + * Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is greater than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 2.0, 2.0, 2.0, 2.0 ]; + * + * var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: InputArray, strideX: number, y: InputArray, strideY: number ): number; + + /** + * Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is greater than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 2.0, 2.0, 2.0, 2.0 ]; + * + * var idx = gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number, y: InputArray, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array. +* +* ## Notes +* +* - If the function is unable to find an element in `x` which is greater than a corresponding element in `y`, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 2.0, 2.0, 2.0, 2.0 ]; +* +* var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 2.0, 2.0, 2.0, 2.0 ]; +* +* var idx = gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var gfirstIndexGreaterThan: Routine; + + +// EXPORTS // + +export = gfirstIndexGreaterThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/types/test.ts new file mode 100644 index 000000000000..fa8e84b4573d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/docs/types/test.ts @@ -0,0 +1,237 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfirstIndexGreaterThan = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); // $ExpectType number + gfirstIndexGreaterThan( x.length, new AccessorArray( x ), 1, new AccessorArray( y ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan( '1', x, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( true, x, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( false, x, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( null, x, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( undefined, x, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( [], x, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( {}, x, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan( 3, 10, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( 3, true, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( 3, false, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( 3, null, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( 3, undefined, 1, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( 3, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan( x.length, x, '1', y, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, true, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, false, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, null, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, undefined, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, [], y, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, {}, y, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan( x.length, x, 1, 10, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, true, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, false, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, null, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, undefined, 1 ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan( x.length, x, 1, y, '1' ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, y, true ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, y, false ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, y, null ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, y, undefined ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, y, [] ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, y, {} ); // $ExpectError + gfirstIndexGreaterThan( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan(); // $ExpectError + gfirstIndexGreaterThan( 3 ); // $ExpectError + gfirstIndexGreaterThan( 3, x ); // $ExpectError + gfirstIndexGreaterThan( 3, x, 1 ); // $ExpectError + gfirstIndexGreaterThan( 3, x, 1, y ); // $ExpectError + gfirstIndexGreaterThan( 3, x, 1, y, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number + gfirstIndexGreaterThan.ndarray( x.length, new AccessorArray( x ), 1, 0, new AccessorArray( y ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a collection... +{ + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( 3, 10, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, true, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, false, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, null, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, undefined, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a collection... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, 10, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexGreaterThan.ndarray(); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, x ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, x, 1 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, x, 1, 0 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, x, 1, 0, y ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, x, 1, 0, y, 1 ); // $ExpectError + gfirstIndexGreaterThan.ndarray( 3, x, 1, 0, y, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/examples/index.js new file mode 100644 index 000000000000..556a22e391ee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexGreaterThan = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/accessors.js new file mode 100644 index 000000000000..869c4f71aa53 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/accessors.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - first input array object +* @param {Collection} x.data - first input array data +* @param {Array} x.accessors - first array element accessors +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Object} y - second input array object +* @param {Collection} y.data - second input array data +* @param {Array} y.accessors - second array element accessors +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 2.0, 2.0, 2.0, 2.0 ]; +* +* var idx = gfirstIndexGreaterThan( x.length, arraylike2object( toAccessorArray( x ) ), 1, 0, arraylike2object( toAccessorArray( y ) ), 1, 0 ); +* // returns 2 +*/ +function gfirstIndexGreaterThan( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xbuf; + var ybuf; + var xget; + var yget; + var ix; + var iy; + var i; + + // Cache reference to array data: + xbuf = x.data; + ybuf = y.data; + + // Cache a reference to the element accessors: + xget = x.accessors[ 0 ]; + yget = y.accessors[ 0 ]; + + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( xget( xbuf, ix ) > yget( ybuf, iy ) ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexGreaterThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/index.js new file mode 100644 index 000000000000..52cb30ee9d25 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the first element in a strided array which is greater than a corresponding element in another strided array. +* +* @module @stdlib/blas/ext/base/gfirst-index-greater-than +* +* @example +* var gfirstIndexGreaterThan = require( '@stdlib/blas/ext/base/gfirst-index-greater-than' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 2.0, 2.0, 2.0, 2.0 ]; +* +* var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var gfirstIndexGreaterThan = require( '@stdlib/blas/ext/base/gfirst-index-greater-than' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 2.0, 2.0, 2.0, 2.0 ]; +* +* var idx = gfirstIndexGreaterThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/main.js new file mode 100644 index 000000000000..a993d370c91b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @returns {integer} index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 2.0, 2.0, 2.0, 2.0 ]; +* +* var idx = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); +* // returns 2 +*/ +function gfirstIndexGreaterThan( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gfirstIndexGreaterThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/ndarray.js new file mode 100644 index 000000000000..a0432966ab91 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/lib/ndarray.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is greater than a corresponding element in another strided array using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 2.0, 2.0, 2.0, 2.0 ]; +* +* var idx = gfirstIndexGreaterThan( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +function gfirstIndexGreaterThan( N, x, strideX, offsetX, y, strideY, offsetY ) { + var ix; + var iy; + var ox; + var oy; + var i; + + if ( N <= 0 ) { + return -1; + } + ox = arraylike2object( x ); + oy = arraylike2object( y ); + if ( ox.accessorProtocol || oy.accessorProtocol ) { + return accessors( N, ox, strideX, offsetX, oy, strideY, offsetY ); + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] > y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexGreaterThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/package.json new file mode 100644 index 000000000000..55556bed35e3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/gfirst-index-greater-than", + "version": "0.0.0", + "description": "Return the index of the first element in a strided array which is greater than a corresponding element in another strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "greater", + "index", + "compare", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.js new file mode 100644 index 000000000000..86b2d869257e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfirstIndexGreaterThan = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexGreaterThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfirstIndexGreaterThan.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.main.js new file mode 100644 index 000000000000..4289f03ef0ec --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.main.js @@ -0,0 +1,452 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexGreaterThan = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexGreaterThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfirstIndexGreaterThan.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is greater than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 9.0, 9.0, 9.0, 9.0, 9.0 ]; + + // Nonnegative stride... + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 9.0, 0.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + y = [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 0.0, 9.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 9.0, 9.0, 0.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which is greater than a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 9.0, 9.0, 9.0, 9.0, 9.0 ] ); + + // Nonnegative stride... + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 9.0, 0.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 0.0, 9.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 9.0, 9.0, 0.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 0, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( -1, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, [ NaN ], 1, [ 0.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( 1, [ 0.0 ], 1, [ NaN ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, toAccessorArray( [ NaN ] ), 1, toAccessorArray( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( 1, toAccessorArray( [ 0.0 ] ), 1, toAccessorArray( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, [ 0.0 ], 1, [ -0.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, toAccessorArray( [ 0.0 ] ), 1, toAccessorArray( [ -0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 9.0, // 0 + 0.0, // 1 + 9.0, // 2 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 9.0, // 0 + 0.0, // 1 + 9.0, // 2 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, toAccessorArray( x ), 2, toAccessorArray( y ), 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 9.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 9.0 // 2 + ]; + + actual = gfirstIndexGreaterThan( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 9.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 9.0 // 2 + ]; + + actual = gfirstIndexGreaterThan( 3, toAccessorArray( x ), 1, toAccessorArray( y ), 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 9.0, // 2 + 0.0, // 1 + 9.0, // 0 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 9.0, // 2 + 0.0, // 1 + 9.0, // 0 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, toAccessorArray( x ), -2, toAccessorArray( y ), -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + y = [ + 0.0, // 2 + 9.0, // 1 + 9.0, // 0 + 9.0, + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float64Array([ + 1.0, + 2.0, // 2 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float64Array([ + 9.0, + 9.0, + 9.0, + 9.0, // 0 + 0.0, // 1 + 9.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = gfirstIndexGreaterThan( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.ndarray.js new file mode 100644 index 000000000000..07e155ed20a9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-greater-than/test/test.ndarray.js @@ -0,0 +1,539 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexGreaterThan = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexGreaterThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( gfirstIndexGreaterThan.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is greater than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 9.0, 9.0, 9.0, 9.0, 9.0 ]; + + // Nonnegative stride... + actual = gfirstIndexGreaterThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 9.0, 0.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + y = [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 0.0, 9.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 9.0, 9.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 9.0, 9.0, 9.0, 9.0, 9.0, 9.0 ]; + + actual = gfirstIndexGreaterThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which is greater than a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 9.0, 9.0, 9.0, 9.0, 9.0 ] ); + + // Nonnegative stride... + actual = gfirstIndexGreaterThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 9.0, 0.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 0.0, 9.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 9.0, 9.0, 9.0, 9.0, 9.0 ] ); + + actual = gfirstIndexGreaterThan( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = toAccessorArray( [ 5.0, 6.0, 7.0, 8.0 ] ); + + actual = gfirstIndexGreaterThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 0, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( -1, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, [ NaN ], 1, 0, [ 0.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( 1, [ 0.0 ], 1, 0, [ NaN ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, toAccessorArray( [ NaN ] ), 1, 0, toAccessorArray( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexGreaterThan( 1, toAccessorArray( [ 0.0 ] ), 1, 0, toAccessorArray( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, [ 0.0 ], 1, 0, [ -0.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexGreaterThan( 1, toAccessorArray( [ 0.0 ] ), 1, 0, toAccessorArray( [ -0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 9.0, // 0 + 0.0, // 1 + 9.0, // 2 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 9.0, // 0 + 0.0, // 1 + 9.0, // 2 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 9.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 9.0 // 2 + ]; + + actual = gfirstIndexGreaterThan( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 9.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 9.0 // 2 + ]; + + actual = gfirstIndexGreaterThan( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 9.0, // 2 + 0.0, // 1 + 9.0, // 0 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 9.0, // 2 + 0.0, // 1 + 9.0, // 0 + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, toAccessorArray( x ), -2, 4, toAccessorArray( y ), -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var actual; + var x; + var y; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + y = [ + 9.0, // 0 + 9.0, // 1 + 0.0, // 2 + 9.0, // 3 + 9.0, + 9.0, + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 4, x, 2, 1, y, 1, 0 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + y = [ + 9.0, // 0 + 9.0, // 1 + 0.0, // 2 + 9.0, // 3 + 9.0, + 9.0, + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 4, toAccessorArray( x ), 2, 1, toAccessorArray( y ), 1, 0 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var actual; + var x; + var y; + + x = [ + 2.0, // 0 + 1.0, // 1 + 2.0, // 2 + -2.0, // 3 + -2.0, + 2.0, + 3.0, + 4.0 + ]; + y = [ + 9.0, + 9.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 9.0, // 2 + 9.0, + 9.0 // 3 + ]; + + actual = gfirstIndexGreaterThan( 4, x, 1, 0, y, 2, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 2.0, // 0 + 1.0, // 1 + 2.0, // 2 + -2.0, // 3 + -2.0, + 2.0, + 3.0, + 4.0 + ]; + y = [ + 9.0, + 9.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 9.0, // 2 + 9.0, + 9.0 // 3 + ]; + + actual = gfirstIndexGreaterThan( 4, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + y = [ + 0.0, // 2 + 9.0, // 1 + 9.0, // 0 + 9.0, + 9.0, + 9.0 + ]; + + actual = gfirstIndexGreaterThan( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/README.md new file mode 100644 index 000000000000..faa848dfae6e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/README.md @@ -0,0 +1,201 @@ + + +# gfirstIndexLessThan + +> Return the index of the first element in a strided array which is less than a corresponding element in another strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var gfirstIndexLessThan = require( '@stdlib/blas/ext/base/gfirst-index-less-than' ); +``` + +#### gfirstIndexLessThan( N, x, strideX, y, strideY ) + +Returns the index of the first element in a strided array which is less than a corresponding element in another strided array. + +```javascript +var x = [ 0.0, 0.0, 0.0, 0.0 ]; +var y = [ 0.0, 0.0, 1.0, 0.0 ]; + +var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input array. +- **strideX**: stride length for `x`. +- **y**: second input array. +- **strideY**: stride length for `y`. + +If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + +```javascript +var x = [ 5.0, 6.0, 7.0, 8.0 ]; +var y = [ 1.0, 2.0, 3.0, 4.0 ]; + +var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compare every other element: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + +var idx = gfirstIndexLessThan( 3, x, 2, y, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( [ 9.0, 0.0, 9.0, 9.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = gfirstIndexLessThan( 2, x1, 1, y1, 1 ); +// returns 1 +``` + +#### gfirstIndexLessThan.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Returns the index of the first element in a strided array which is less than a corresponding element in another strided array using alternative indexing semantics. + +```javascript +var x = [ 0.0, 0.0, 0.0, 0.0 ]; +var y = [ 0.0, 0.0, 1.0, 0.0 ]; + +var idx = gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last three elements of each strided array: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 9.0, 9.0, 9.0, 0.0, 9.0, 9.0 ]; + +var idx = gfirstIndexLessThan.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 1 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks whether an element in `x` is less than a corresponding element in `y` using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexLessThan = require( '@stdlib/blas/ext/base/gfirst-index-less-than' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/benchmark/benchmark.js new file mode 100644 index 000000000000..8096c58932a0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/benchmark/benchmark.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexLessThan = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexLessThan( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..9931a025082b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/benchmark/benchmark.ndarray.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexLessThan = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float64' ); + var y = ones( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/repl.txt new file mode 100644 index 000000000000..ea57498c005d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/repl.txt @@ -0,0 +1,117 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a strided array which is less than + a corresponding element in another strided array. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 0.0, 0.0, 0.0, 0.0 ]; + > var y = [ 0.0, 0.0, 1.0, 0.0 ]; + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + > idx = {{alias}}( 3, x, 2, y, 2 ) + 2 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y0 = new {{alias:@stdlib/array/float64}}( [ 9.0, 0.0, 9.0, 9.0 ] ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); + > var idx = {{alias}}( 2, x1, 1, y1, 1 ) + 1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a strided array which is less than + a corresponding element in another strided array using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on + starting indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 0.0, 0.0, 0.0, 0.0 ]; + > var y = [ 0.0, 0.0, 1.0, 0.0 ]; + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using `N` and stride parameters: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ]; + > idx = {{alias}}.ndarray( 3, x, 2, 0, y, 2, 0 ) + 2 + + // Using an index offset: + > x = [ 1.0, 2.0, 3.0, 4.0 ]; + > y = [ 9.0, 2.0, 9.0, 9.0 ]; + > idx = {{alias}}.ndarray( 2, x, 1, 1, y, 1, 1 ) + 1 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/types/index.d.ts new file mode 100644 index 000000000000..4b3fdd72c449 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/types/index.d.ts @@ -0,0 +1,116 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfirstIndexLessThan`. +*/ +interface Routine { + /** + * Returns the index of the first element in a strided array which is less than a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 0.0, 0.0, 0.0, 0.0 ]; + * var y = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: InputArray, strideX: number, y: InputArray, strideY: number ): number; + + /** + * Returns the index of the first element in a strided array which is less than a corresponding element in another strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var x = [ 0.0, 0.0, 0.0, 0.0 ]; + * var y = [ 0.0, 0.0, 1.0, 0.0 ]; + * + * var idx = gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number, y: InputArray, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a strided array which is less than a corresponding element in another strided array. +* +* ## Notes +* +* - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var x = [ 0.0, 0.0, 0.0, 0.0 ]; +* var y = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var x = [ 0.0, 0.0, 0.0, 0.0 ]; +* var y = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* var idx = gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var gfirstIndexLessThan: Routine; + + +// EXPORTS // + +export = gfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/types/test.ts new file mode 100644 index 000000000000..2c961c05495e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/docs/types/test.ts @@ -0,0 +1,237 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfirstIndexLessThan = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan( x.length, x, 1, y, 1 ); // $ExpectType number + gfirstIndexLessThan( x.length, new AccessorArray( x ), 1, new AccessorArray( y ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan( '10', x, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( true, x, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( false, x, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( null, x, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( undefined, x, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( [], x, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( {}, x, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan( 3, 10, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( 3, true, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( 3, false, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( 3, null, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( 3, undefined, 1, y, 1 ); // $ExpectError + gfirstIndexLessThan( 3, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan( x.length, x, '10', y, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, true, y, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, false, y, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, null, y, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, undefined, y, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, [], y, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, {}, y, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + const x = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexLessThan( x.length, x, 1, 10, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, true, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, false, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, null, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, undefined, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan( x.length, x, 1, y, '10' ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, true ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, false ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, null ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, undefined ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, [] ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, {} ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan(); // $ExpectError + gfirstIndexLessThan( x.length ); // $ExpectError + gfirstIndexLessThan( x.length, x ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1 ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y ); // $ExpectError + gfirstIndexLessThan( x.length, x, 1, y, 1, 0 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number + gfirstIndexLessThan.ndarray( x.length, new AccessorArray( x ), 1, 0, new AccessorArray( y ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a collection... +{ + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray( 3, 10, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( 3, true, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( 3, false, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( 3, null, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( 3, undefined, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( 3, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a collection... +{ + const x = [ 1.0, 2.0, 3.0 ]; + + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, 10, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = [ 1.0, 2.0, 3.0 ]; + const y = [ 2.0, 1.0, 2.0 ]; + + gfirstIndexLessThan.ndarray(); // $ExpectError + gfirstIndexLessThan.ndarray( x.length ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0, 0 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/examples/index.js new file mode 100644 index 000000000000..b8835146b4ee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexLessThan = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/accessors.js new file mode 100644 index 000000000000..534eddd017b7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/accessors.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is less than a corresponding element in another strided array. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - first input array object +* @param {Collection} x.data - first input array data +* @param {Array} x.accessors - first array element accessors +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Object} y - second input array object +* @param {Collection} y.data - second input array data +* @param {Array} y.accessors - second array element accessors +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 0.0, 0.0, 0.0, 0.0 ]; +* var y = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* var idx = gfirstIndexLessThan( x.length, arraylike2object( toAccessorArray( x ) ), 1, 0, arraylike2object( toAccessorArray( y ) ), 1, 0 ); +* // returns 2 +*/ +function gfirstIndexLessThan( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xbuf; + var ybuf; + var xget; + var yget; + var ix; + var iy; + var i; + + // Cache reference to array data: + xbuf = x.data; + ybuf = y.data; + + // Cache a reference to the element accessors: + xget = x.accessors[ 0 ]; + yget = y.accessors[ 0 ]; + + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( xget( xbuf, ix ) < yget( ybuf, iy ) ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/index.js new file mode 100644 index 000000000000..e9020155fbad --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the first element in a strided array which is less than a corresponding element in another strided array. +* +* @module @stdlib/blas/ext/base/gfirst-index-less-than +* +* @example +* var gfirstIndexLessThan = require( '@stdlib/blas/ext/base/gfirst-index-less-than' ); +* +* var x = [ 0.0, 0.0, 0.0, 0.0 ]; +* var y = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var gfirstIndexLessThan = require( '@stdlib/blas/ext/base/gfirst-index-less-than' ); +* +* var x = [ 0.0, 0.0, 0.0, 0.0 ]; +* var y = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* var idx = gfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/main.js new file mode 100644 index 000000000000..9f57a4e6cfdc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is less than a corresponding element in another strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @returns {integer} index +* +* @example +* var x = [ 0.0, 0.0, 0.0, 0.0 ]; +* var y = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* var idx = gfirstIndexLessThan( x.length, x, 1, y, 1 ); +* // returns 2 +*/ +function gfirstIndexLessThan( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/ndarray.js new file mode 100644 index 000000000000..f93b5755d738 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/lib/ndarray.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is less than a corresponding element in another strided array using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var x = [ 0.0, 0.0, 0.0, 0.0 ]; +* var y = [ 0.0, 0.0, 1.0, 0.0 ]; +* +* var idx = gfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +function gfirstIndexLessThan( N, x, strideX, offsetX, y, strideY, offsetY ) { + var ix; + var iy; + var ox; + var oy; + var i; + + if ( N <= 0 ) { + return -1; + } + ox = arraylike2object( x ); + oy = arraylike2object( y ); + if ( ox.accessorProtocol || oy.accessorProtocol ) { + return accessors( N, ox, strideX, offsetX, oy, strideY, offsetY ); + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] < y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/package.json new file mode 100644 index 000000000000..22bb4cc4a2bc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/gfirst-index-less-than", + "version": "0.0.0", + "description": "Return the index of the first element in a strided array which is less than a corresponding element in another strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "less", + "index", + "compare", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.js new file mode 100644 index 000000000000..bcb63f4120b1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfirstIndexLessThan = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfirstIndexLessThan.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.main.js new file mode 100644 index 000000000000..45e02ab563ea --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.main.js @@ -0,0 +1,468 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexLessThan = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfirstIndexLessThan.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ]; + y = [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ]; + + // Nonnegative stride... + actual = gfirstIndexLessThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ]; + y = [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ]; + y = [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, 1, y, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ]; + y = [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ]; + y = [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ]; + + actual = gfirstIndexLessThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ]; + y = [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ]; + + actual = gfirstIndexLessThan( 3, x, -2, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ]; + y = [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, -1, y, -2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]; + y = [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, -2, y, -2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = gfirstIndexLessThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, 1, y, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = toAccessorArray( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = toAccessorArray( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = gfirstIndexLessThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = toAccessorArray( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = gfirstIndexLessThan( 3, x, -2, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = toAccessorArray( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, -1, y, -2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = toAccessorArray( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, -2, y, -2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 0, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( -1, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, [ NaN ], 1, [ 0.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( 1, [ 0.0 ], 1, [ NaN ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, toAccessorArray( [ NaN ] ), 1, toAccessorArray( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( 1, toAccessorArray( [ 0.0 ] ), 1, toAccessorArray( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, [ 0.0 ], 1, [ -0.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, toAccessorArray( [ 0.0 ] ), 1, toAccessorArray( [ -0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), 2, toAccessorArray( y ), 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]; + + actual = gfirstIndexLessThan( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), 1, toAccessorArray( y ), 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), -2, toAccessorArray( y ), -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), 2, toAccessorArray( y ), -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float64Array([ + 6.0, + 0.0, // 2 + 5.0, + 1.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = gfirstIndexLessThan( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.ndarray.js new file mode 100644 index 000000000000..cb4f429eaf73 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-less-than/test/test.ndarray.js @@ -0,0 +1,433 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexLessThan = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( gfirstIndexLessThan.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ]; + y = [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ]; + + // Nonnegative stride... + actual = gfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ]; + y = [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ]; + y = [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ]; + y = [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ]; + y = [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ]; + + actual = gfirstIndexLessThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ]; + y = [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ]; + + actual = gfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ]; + y = [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, -1, 2, y, -2, 4 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]; + y = [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ]; + + actual = gfirstIndexLessThan( 3, x, -2, 4, y, -2, 4 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = gfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = toAccessorArray( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = toAccessorArray( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = toAccessorArray( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = gfirstIndexLessThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = toAccessorArray( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = gfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = toAccessorArray( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, -1, 2, y, -2, 4 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = toAccessorArray( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = gfirstIndexLessThan( 3, x, -2, 4, y, -2, 4 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 0, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( -1, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, [ NaN ], 1, 0, [ 0.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( 1, [ 0.0 ], 1, 0, [ NaN ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, toAccessorArray( [ NaN ] ), 1, 0, toAccessorArray( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexLessThan( 1, toAccessorArray( [ 0.0 ] ), 1, 0, toAccessorArray( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, [ 0.0 ], 1, 0, [ -0.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexLessThan( 1, toAccessorArray( [ 0.0 ] ), 1, 0, toAccessorArray( [ -0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]; + + actual = gfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), -2, 4, toAccessorArray( y ), -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = gfirstIndexLessThan( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/README.md new file mode 100644 index 000000000000..134951d415aa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/README.md @@ -0,0 +1,187 @@ + + +# gfirstIndexNotEqual + +> Return the index of the first element in a strided array which is not equal to the corresponding element in another strided array. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gfirstIndexNotEqual = require( '@stdlib/blas/ext/base/gfirst-index-not-equal' ); +``` + +#### gfirstIndexNotEqual( N, x, strideX, y, strideY ) + +Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array. + +```javascript +var x = [ 0, 0, 1, 0 ]; +var y = [ 0, 0, 0, 0 ]; + +var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideX**: stride length for `x`. +- **y**: second input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideY**: stride length for `y`. + +If unable to find an element in `x` which is not equal to the corresponding element in `y`, the function returns `-1`. + +```javascript +var x = [ 0, 0, 0, 0 ]; +var y = [ 0, 0, 0, 0 ]; + +var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compare every other element in `x` to every other element in `y`: + +```javascript +var x = [ 0, 0, 1, 0, 0, 0 ]; +var y = [ 0, 0, 1, 0, 9, 0 ]; + +var idx = gfirstIndexNotEqual( 3, x, 2, y, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 0, 0, 0, 1, 0, 0 ] ); +var y0 = new Float64Array( [ 0, 0, 0, 0, 0, 0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +var idx = gfirstIndexNotEqual( x1.length, x1, 1, y1, 1 ); +// returns 2 +``` + +#### gfirstIndexNotEqual.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array using alternative indexing semantics. + +```javascript +var x = [ 0, 0, 1, 0 ]; +var y = [ 0, 0, 0, 0 ]; + +var idx = gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to compare the last three elements of `x` to the last three elements of `y`: + +```javascript +var x = [ 0, 0, 0, 1 ]; +var y = [ 1, 0, 0, 0 ]; + +var idx = gfirstIndexNotEqual.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 2 +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `-1`. +- Both functions determine whether corresponding elements are equal using strict equality (i.e., the `===` operator). As a consequence, corresponding `NaN` elements are considered unequal (as `NaN !== NaN` always evaluates to `true`), while `-0` and `+0` are considered equal. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexNotEqual = require( '@stdlib/blas/ext/base/gfirst-index-not-equal' ); + +var x = discreteUniform( 10, -5, 5, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, -5, 5, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..e12dde8c4f68 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/benchmark/benchmark.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexNotEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = oneTo( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..6bcddbd9e06e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexNotEqual = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = oneTo( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/repl.txt new file mode 100644 index 000000000000..fb1b3586817c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/repl.txt @@ -0,0 +1,112 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a strided array which is not + equal to the corresponding element in another strided array. + + The `N` and stride parameters determine which elements in the strided + arrays are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use + typed array views. + + If `N <= 0` or if unable to find an element in `x` which is not equal to + the corresponding element in `y`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 0, 0, 1, 0 ]; + > var y = [ 0, 0, 0, 0 ]; + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > var x = [ 2, 4, 6, 8, 10 ]; + > var y = [ 2, 3, 4, 5, 6 ]; + > var idx = {{alias}}( 3, x, 2, y, 1 ) + 1 + + // View offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 0, 0, 1, 0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y = [ 0, 0, 0 ]; + > var idx = {{alias}}( x1.length, x1, 1, y, 1 ) + 1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a strided array which is not + equal to the corresponding element in another strided array using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on + starting indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 0, 0, 1, 0 ]; + > var y = [ 0, 0, 0, 0 ]; + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Advanced indexing: + > var x = [ 2, 4, 6, 8, 10 ]; + > var y = [ 2, 3, 4, 5, 6 ]; + > var idx = {{alias}}.ndarray( 3, x, 2, 0, y, 1, 0 ) + 1 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..d2912c974a27 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/types/index.d.ts @@ -0,0 +1,116 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gfirstIndexNotEqual`. +*/ +interface Routine { + /** + * Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array. + * + * ## Notes + * + * - If unable to find an element in `x` which is not equal to the corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 0, 0, 1, 0 ]; + * var y = [ 0, 0, 0, 0 ]; + * + * var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: InputArray, strideX: number, y: InputArray, strideY: number ): number; + + /** + * Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array using alternative indexing semantics. + * + * ## Notes + * + * - If unable to find an element in `x` which is not equal to the corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var x = [ 0, 0, 1, 0 ]; + * var y = [ 0, 0, 0, 0 ]; + * + * var idx = gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number, y: InputArray, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array. +* +* ## Notes +* +* - If unable to find an element in `x` which is not equal to the corresponding element in `y`, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var x = [ 0, 0, 1, 0 ]; +* var y = [ 0, 0, 0, 0 ]; +* +* var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var x = [ 0, 0, 1, 0 ]; +* var y = [ 0, 0, 0, 0 ]; +* +* var idx = gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var gfirstIndexNotEqual: Routine; + + +// EXPORTS // + +export = gfirstIndexNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..16ab0fbf3ed9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/docs/types/test.ts @@ -0,0 +1,215 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gfirstIndexNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual( x.length, x, 1, y, 1 ); // $ExpectType number + gfirstIndexNotEqual( x.length, new AccessorArray( x ), 1, new AccessorArray( y ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual( '1', x, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( true, x, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( false, x, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( null, x, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( {}, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual( x.length, 5, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, true, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, false, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, null, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, undefined, 1, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual( x.length, x, '1', y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, true, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, false, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, null, y, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, {}, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + const x = [ 0, 0, 1, 0 ]; + + gfirstIndexNotEqual( x.length, x, 1, 5, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, true, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, false, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, null, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, undefined, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual( x.length, x, 1, y, '1' ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, y, true ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, y, false ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, y, null ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, y, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual(); // $ExpectError + gfirstIndexNotEqual( x.length ); // $ExpectError + gfirstIndexNotEqual( x.length, x ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1 ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, y ); // $ExpectError + gfirstIndexNotEqual( x.length, x, 1, y, 1, {} ); // $ExpectError +} + +// Attached to the main export is an `ndarray` method which returns a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number + gfirstIndexNotEqual.ndarray( x.length, new AccessorArray( x ), 1, 0, new AccessorArray( y ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a collection... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray( x.length, 5, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, true, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, false, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, null, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, undefined, 1, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a collection... +{ + const x = [ 0, 0, 1, 0 ]; + + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, 5, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = [ 0, 0, 1, 0 ]; + const y = [ 0, 0, 0, 0 ]; + + gfirstIndexNotEqual.ndarray(); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/examples/index.js new file mode 100644 index 000000000000..0126c17a60b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gfirstIndexNotEqual = require( './../lib' ); + +var x = discreteUniform( 10, -5, 5, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, -5, 5, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/accessors.js new file mode 100644 index 000000000000..bdecb9046ac9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/accessors.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - first input array object +* @param {Collection} x.data - first input array data +* @param {Array} x.accessors - first array element accessors +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Object} y - second input array object +* @param {Collection} y.data - second input array data +* @param {Array} y.accessors - second array element accessors +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 0, 0, 1, 0 ]; +* var y = [ 0, 0, 0, 0 ]; +* +* var idx = gfirstIndexNotEqual( x.length, arraylike2object( toAccessorArray( x ) ), 1, 0, arraylike2object( toAccessorArray( y ) ), 1, 0 ); +* // returns 2 +*/ +function gfirstIndexNotEqual( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xbuf; + var ybuf; + var xget; + var yget; + var ix; + var iy; + var i; + + xbuf = x.data; + ybuf = y.data; + xget = x.accessors[ 0 ]; + yget = y.accessors[ 0 ]; + + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( xget( xbuf, ix ) !== yget( ybuf, iy ) ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/index.js new file mode 100644 index 000000000000..566db2a17318 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the first element in a strided array which is not equal to the corresponding element in another strided array. +* +* @module @stdlib/blas/ext/base/gfirst-index-not-equal +* +* @example +* var gfirstIndexNotEqual = require( '@stdlib/blas/ext/base/gfirst-index-not-equal' ); +* +* var x = [ 0, 0, 1, 0 ]; +* var y = [ 0, 0, 0, 0 ]; +* +* var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var gfirstIndexNotEqual = require( '@stdlib/blas/ext/base/gfirst-index-not-equal' ); +* +* var x = [ 0, 0, 1, 0 ]; +* var y = [ 0, 0, 0, 0 ]; +* +* var idx = gfirstIndexNotEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/main.js new file mode 100644 index 000000000000..4e4574936111 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @returns {integer} index +* +* @example +* var x = [ 0, 0, 1, 0 ]; +* var y = [ 0, 0, 0, 0 ]; +* +* var idx = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); +* // returns 2 +*/ +function gfirstIndexNotEqual( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gfirstIndexNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/ndarray.js new file mode 100644 index 000000000000..e8c244bbc23c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/lib/ndarray.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which is not equal to the corresponding element in another strided array using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var x = [ 0, 0, 1, 0 ]; +* var y = [ 0, 0, 0, 0 ]; +* +* var idx = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +function gfirstIndexNotEqual( N, x, strideX, offsetX, y, strideY, offsetY ) { + var ix; + var iy; + var ox; + var oy; + var i; + + if ( N <= 0 ) { + return -1; + } + ox = arraylike2object( x ); + oy = arraylike2object( y ); + if ( ox.accessorProtocol || oy.accessorProtocol ) { + return accessors( N, ox, strideX, offsetX, oy, strideY, offsetY ); + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] !== y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} + + +// EXPORTS // + +module.exports = gfirstIndexNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/package.json new file mode 100644 index 000000000000..60594a62cec3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/ext/base/gfirst-index-not-equal", + "version": "0.0.0", + "description": "Return the index of the first element in a strided array which is not equal to the corresponding element in another strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "search", + "index", + "first", + "compare", + "comparison", + "equal", + "equality", + "not equal", + "unequal", + "mismatch", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.js new file mode 100644 index 000000000000..d107b9dcd33d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gfirstIndexNotEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gfirstIndexNotEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.main.js new file mode 100644 index 000000000000..1c040bfd9cb9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.main.js @@ -0,0 +1,339 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexNotEqual = require( './../lib/main.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gfirstIndexNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in `x` which is not equal to the corresponding element in `y`', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 1.0, 2.0, 5.0, 3.0, 3.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + x = [ 9.0, 1.0, 2.0 ]; + y = [ 1.0, 1.0, 2.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element in `x` which is not equal to the corresponding element in `y` (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 1.0, 2.0, 5.0, 3.0, 3.0 ] ); + + actual = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + x = toAccessorArray( [ 9.0, 1.0, 2.0 ] ); + y = toAccessorArray( [ 1.0, 1.0, 2.0 ] ); + + actual = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in `x` is equal to the corresponding element in `y`', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 2.0, 3.0 ]; + y = [ 1.0, 2.0, 3.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in `x` is equal to the corresponding element in `y` (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + + actual = gfirstIndexNotEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter less than or equal to zero', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + + actual = gfirstIndexNotEqual( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexNotEqual( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter less than or equal to zero (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + y = toAccessorArray( [ 4.0, 5.0, 6.0 ] ); + + actual = gfirstIndexNotEqual( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexNotEqual( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats corresponding `NaN` elements as unequal', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, [ NaN ], 1, [ NaN ], 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats corresponding `NaN` elements as unequal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, toAccessorArray( [ NaN ] ), 1, toAccessorArray( [ NaN ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, [ -0.0 ], 1, [ 0.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, toAccessorArray( [ -0.0 ] ), 1, toAccessorArray( [ 0.0 ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, x, 2, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, toAccessorArray( x ), 2, toAccessorArray( y ), 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ 0.0, 0.0, 1.0 ]; + y = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, x, 1, y, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ 0.0, 0.0, 1.0 ]; + y = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, toAccessorArray( x ), 1, toAccessorArray( y ), 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ]; + y = [ 5.0, 4.0, 3.0, 9.0, 1.0, 0.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ]; + y = [ 5.0, 4.0, 3.0, 9.0, 1.0, 0.0 ]; + + actual = gfirstIndexNotEqual( x.length, toAccessorArray( x ), -1, toAccessorArray( y ), -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 2 + 0.0, // 1 + 0.0, // 0 + 9.0, + 9.0 + ]; + + actual = gfirstIndexNotEqual( 3, x, 2, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + x0 = new Float64Array( [ 9.0, 0.0, 1.0, 0.0, 0.0 ] ); + y0 = new Float64Array( [ 9.0, 9.0, 0.0, 0.0, 0.0 ] ); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + actual = gfirstIndexNotEqual( 3, x1, 1, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.ndarray.js new file mode 100644 index 000000000000..d93e337a660b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gfirst-index-not-equal/test/test.ndarray.js @@ -0,0 +1,437 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gfirstIndexNotEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( gfirstIndexNotEqual.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in `x` which is not equal to the corresponding element in `y`', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 1.0, 2.0, 5.0, 3.0, 3.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + x = [ 9.0, 1.0, 2.0 ]; + y = [ 1.0, 1.0, 2.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element in `x` which is not equal to the corresponding element in `y` (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 1.0, 2.0, 5.0, 3.0, 3.0 ] ); + + actual = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + x = toAccessorArray( [ 9.0, 1.0, 2.0 ] ); + y = toAccessorArray( [ 1.0, 1.0, 2.0 ] ); + + actual = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in `x` is equal to the corresponding element in `y`', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 2.0, 3.0 ]; + y = [ 1.0, 2.0, 3.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in `x` is equal to the corresponding element in `y` (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + + actual = gfirstIndexNotEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter less than or equal to zero', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + + actual = gfirstIndexNotEqual( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexNotEqual( -1, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter less than or equal to zero (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + y = toAccessorArray( [ 4.0, 5.0, 6.0 ] ); + + actual = gfirstIndexNotEqual( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gfirstIndexNotEqual( -1, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats corresponding `NaN` elements as unequal', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, [ NaN ], 1, 0, [ NaN ], 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats corresponding `NaN` elements as unequal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, toAccessorArray( [ NaN ] ), 1, 0, toAccessorArray( [ NaN ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, [ -0.0 ], 1, 0, [ 0.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal (accessors)', function test( t ) { + var actual; + + actual = gfirstIndexNotEqual( 1, toAccessorArray( [ -0.0 ] ), 1, 0, toAccessorArray( [ 0.0 ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var actual; + var x; + var y; + + x = [ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, x, 2, 1, y, 1, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, toAccessorArray( x ), 2, 1, toAccessorArray( y ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ 0.0, 0.0, 1.0 ]; + y = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ 0.0, 0.0, 1.0 ]; + y = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var actual; + var x; + var y; + + x = [ 0.0, 0.0, 1.0 ]; + y = [ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, x, 1, 0, y, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` offset (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ 0.0, 0.0, 1.0 ]; + y = [ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gfirstIndexNotEqual( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 1 ); // eslint-disable-line max-len + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ]; + y = [ 5.0, 4.0, 3.0, 9.0, 1.0, 0.0 ]; + + actual = gfirstIndexNotEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); // eslint-disable-line max-len + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ]; + y = [ 5.0, 4.0, 3.0, 9.0, 1.0, 0.0 ]; + + actual = gfirstIndexNotEqual( x.length, toAccessorArray( x ), -1, x.length-1, toAccessorArray( y ), -1, y.length-1 ); // eslint-disable-line max-len + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 2 + 0.0, // 1 + 0.0, // 0 + 9.0, + 9.0 + ]; + + actual = gfirstIndexNotEqual( 3, x, 2, 0, y, -1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + y = [ + 0.0, // 2 + 0.0, // 1 + 0.0, // 0 + 9.0, + 9.0 + ]; + + actual = gfirstIndexNotEqual( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), -1, 2 ); // eslint-disable-line max-len + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/README.md new file mode 100644 index 000000000000..06ca7496d2af --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/README.md @@ -0,0 +1,187 @@ + + +# gindexOfNotEqual + +> Return the first index of an element in a strided array which is not equal to a specified search element. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var gindexOfNotEqual = require( '@stdlib/blas/ext/base/gindex-of-not-equal' ); +``` + +#### gindexOfNotEqual( N, searchElement, x, strideX ) + +Returns the first index of an element in a strided array which is not equal to a specified search element. + +```javascript +var x = [ 1.0, 1.0, 0.0, 1.0 ]; + +var idx = gindexOfNotEqual( x.length, 1.0, x, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **x**: input array. +- **strideX**: stride length. + +If all elements in the array are equal to the search element, the function returns `-1`. + +```javascript +var x = [ 1.0, 1.0, 1.0, 1.0 ]; + +var idx = gindexOfNotEqual( x.length, 1.0, x, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to search every other element: + +```javascript +var x = [ 1.0, 9.0, 0.0, 9.0, 1.0, 9.0 ]; + +var idx = gindexOfNotEqual( 3, 1.0, x, 2 ); +// returns 1 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +// Create an offset view... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = gindexOfNotEqual( 3, 2.0, x1, 2 ); +// returns 1 +``` + +#### gindexOfNotEqual.ndarray( N, searchElement, x, strideX, offsetX ) + +Returns the first index of an element in a strided array which is not equal to a specified search element using alternative indexing semantics. + +```javascript +var x = [ 1.0, 1.0, 0.0, 1.0 ]; + +var idx = gindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array: + +```javascript +var x = [ 1.0, 1.0, 0.0, 1.0 ]; + +var idx = gindexOfNotEqual.ndarray( 3, 1.0, x, 1, 1 ); +// returns 1 +``` + +
+ + + + + +
+ +## Notes + +- When searching for a search element, the function checks for inequality using the strict inequality operator `!==`. As a consequence, `NaN` values are considered distinct from all values (including other `NaN` values), and `-0` and `+0` are considered the same. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gindexOfNotEqual = require( '@stdlib/blas/ext/base/gindex-of-not-equal' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'generic' +}); +console.log( x ); + +var idx = gindexOfNotEqual( x.length, 0.0, x, 1 ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..6c3748fcd92a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/benchmark/benchmark.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gindexOfNotEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gindexOfNotEqual( x.length, 0.0, x, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..116220a44b01 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gindexOfNotEqual = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gindexOfNotEqual( x.length, 0.0, x, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/repl.txt new file mode 100644 index 000000000000..5bed55ccbb29 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/repl.txt @@ -0,0 +1,95 @@ + +{{alias}}( N, searchElement, x, strideX ) + Returns the first index of an element in a strided array which is not equal + to a specified search element. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 1.0, 0.0, 1.0 ]; + > var idx = {{alias}}( x.length, 1.0, x, 1 ) + 2 + + // Using `N` and stride parameters: + > var x = [ 1.0, 9.0, 0.0, 9.0, 1.0, 9.0 ]; + > var idx = {{alias}}( 3, 1.0, x, 2 ) + 1 + + // View offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 1.0, 1.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var idx = {{alias}}( 2, 1.0, x1, 1 ) + 0 + + +{{alias}}.ndarray( N, searchElement, x, strideX, offsetX ) + Returns the first index of an element in a strided array which is not equal + to a specified search element using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a + starting index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 1.0, 0.0, 1.0 ]; + > var idx = {{alias}}.ndarray( x.length, 1.0, x, 1, 0 ) + 2 + + // Advanced indexing: + > var x = [ 1.0, 2.0, 1.0, 3.0, 1.0, 4.0 ]; + > var idx = {{alias}}.ndarray( 3, 1.0, x, 2, 1 ) + 0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..2eef2727379f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/types/index.d.ts @@ -0,0 +1,108 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gindexOfNotEqual`. +*/ +interface Routine { + /** + * Returns the first index of an element in a strided array which is not equal to a specified search element. + * + * ## Notes + * + * - If all elements are equal to the search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var x = [ 1.0, 1.0, 0.0, 1.0 ]; + * + * var idx = gindexOfNotEqual( x.length, 1.0, x, 1 ); + * // returns 2 + */ + ( N: number, searchElement: unknown, x: InputArray, strideX: number ): number; + + /** + * Returns the first index of an element in a strided array which is not equal to a specified search element using alternative indexing semantics. + * + * ## Notes + * + * - If all elements are equal to the search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns index + * + * @example + * var x = [ 1.0, 1.0, 0.0, 1.0 ]; + * + * var idx = gindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, searchElement: unknown, x: InputArray, strideX: number, offsetX: number ): number; +} + +/** +* Returns the first index of an element in a strided array which is not equal to a specified search element. +* +* ## Notes +* +* - If all elements are equal to the search element, the function returns `-1`. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param x - input array +* @param strideX - stride length +* @returns index +* +* @example +* var x = [ 1.0, 1.0, 0.0, 1.0 ]; +* +* var idx = gindexOfNotEqual( x.length, 1.0, x, 1 ); +* // returns 2 +* +* @example +* var x = [ 1.0, 1.0, 0.0, 1.0 ]; +* +* var idx = gindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); +* // returns 2 +*/ +declare var gindexOfNotEqual: Routine; + + +// EXPORTS // + +export = gindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..d58b9cf76888 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/docs/types/test.ts @@ -0,0 +1,129 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gindexOfNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfNotEqual( x.length, 2.0, x, 1 ); // $ExpectType number + gindexOfNotEqual( x.length, 2.0, new AccessorArray( x ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfNotEqual( '1', 2.0, x, 1 ); // $ExpectError + gindexOfNotEqual( true, 2.0, x, 1 ); // $ExpectError + gindexOfNotEqual( false, 2.0, x, 1 ); // $ExpectError + gindexOfNotEqual( null, 2.0, x, 1 ); // $ExpectError + gindexOfNotEqual( {}, 2.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a collection... +{ + gindexOfNotEqual( x.length, 1.0, 1, 1 ); // $ExpectError + gindexOfNotEqual( x.length, 1.0, true, 1 ); // $ExpectError + gindexOfNotEqual( x.length, 1.0, false, 1 ); // $ExpectError + gindexOfNotEqual( x.length, 1.0, null, 1 ); // $ExpectError + gindexOfNotEqual( x.length, 1.0, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfNotEqual( x.length, 2.0, x, '1' ); // $ExpectError + gindexOfNotEqual( x.length, 2.0, x, true ); // $ExpectError + gindexOfNotEqual( x.length, 2.0, x, false ); // $ExpectError + gindexOfNotEqual( x.length, 2.0, x, null ); // $ExpectError + gindexOfNotEqual( x.length, 2.0, x, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + gindexOfNotEqual(); // $ExpectError + gindexOfNotEqual( 3, 2.0 ); // $ExpectError + gindexOfNotEqual( 3, 2.0, [ 1.0, 2.0, 3.0 ] ); // $ExpectError + gindexOfNotEqual( 3, 2.0, [ 1.0, 2.0, 3.0 ], 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfNotEqual.ndarray( x.length, 2.0, x, 1, 0 ); // $ExpectType number + gindexOfNotEqual.ndarray( x.length, 2.0, new AccessorArray( x ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfNotEqual.ndarray( '1', 2.0, x, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( true, 2.0, x, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( false, 2.0, x, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( null, 2.0, x, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( {}, 2.0, x, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a collection... +{ + gindexOfNotEqual.ndarray( x.length, 1.0, 1, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 1.0, true, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 1.0, false, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 1.0, null, 1, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 1.0, {}, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfNotEqual.ndarray( x.length, 2.0, x, '1', 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, true, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, false, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, null, 1 ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfNotEqual.ndarray( x.length, 2.0, x, 1, '1' ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, 1, true ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, 1, false ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, 1, null ); // $ExpectError + gindexOfNotEqual.ndarray( x.length, 2.0, x, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + gindexOfNotEqual.ndarray(); // $ExpectError + gindexOfNotEqual.ndarray( 3, 2.0 ); // $ExpectError + gindexOfNotEqual.ndarray( 3, 2.0, [ 1.0, 2.0, 3.0 ] ); // $ExpectError + gindexOfNotEqual.ndarray( 3, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); // $ExpectError + gindexOfNotEqual.ndarray( 3, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/examples/index.js new file mode 100644 index 000000000000..a35dd53376d6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gindexOfNotEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'generic' +}); +console.log( x ); + +var idx = gindexOfNotEqual( x.length, 0.0, x, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/accessors.js new file mode 100644 index 000000000000..fe79423c9fe7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/accessors.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns the first index of an element in a strided array which is not equal to a specified search element. +* +* ## Notes +* +* - If all elements are equal to the search element, the function returns `-1`. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {integer} index +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 1.0, 1.0, 0.0, 1.0 ]; +* +* var idx = gindexOfNotEqual( x.length, 1.0, arraylike2object( toAccessorArray( x ) ), 1, 0 ); +* // returns 2 +*/ +function gindexOfNotEqual( N, searchElement, x, strideX, offsetX ) { + var xbuf; + var get; + var ix; + var i; + + // Cache a reference to array data: + xbuf = x.data; + + // Cache a reference to the element accessor: + get = x.accessors[ 0 ]; + + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( get( xbuf, ix ) !== searchElement ) { + return i; + } + ix += strideX; + } + return -1; +} + + +// EXPORTS // + +module.exports = gindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/index.js new file mode 100644 index 000000000000..f02ee44c3f9b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the first index of an element in a strided array which is not equal to a specified search element. +* +* @module @stdlib/blas/ext/base/gindex-of-not-equal +* +* @example +* var gindexOfNotEqual = require( '@stdlib/blas/ext/base/gindex-of-not-equal' ); +* +* var x = [ 1.0, 1.0, 0.0, 1.0 ]; +* +* var idx = gindexOfNotEqual( x.length, 1.0, x, 1 ); +* // returns 2 +* +* @example +* var gindexOfNotEqual = require( '@stdlib/blas/ext/base/gindex-of-not-equal' ); +* +* var x = [ 1.0, 1.0, 0.0, 1.0 ]; +* +* var idx = gindexOfNotEqual.ndarray( x.length, 1.0, x, 1, 0 ); +* // returns 2 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/main.js new file mode 100644 index 000000000000..d7fae19502cd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/main.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Returns the first index of an element in a strided array which is not equal to a specified search element. +* +* ## Notes +* +* - If all elements are equal to the search element, the function returns `-1`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @returns {integer} index +* +* @example +* var x = [ 1.0, 1.0, 0.0, 1.0 ]; +* +* var idx = gindexOfNotEqual( x.length, 1.0, x, 1 ); +* // returns 2 +*/ +function gindexOfNotEqual( N, searchElement, x, strideX ) { + return ndarray( N, searchElement, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = gindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/ndarray.js new file mode 100644 index 000000000000..4b5d2e295180 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/lib/ndarray.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Returns the first index of an element in a strided array which is not equal to a specified search element using alternative indexing semantics. +* +* ## Notes +* +* - If all elements are equal to the search element, the function returns `-1`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {integer} index +* +* @example +* var x = [ 1.0, 1.0, 0.0, 1.0 ]; +* +* var idx = gindexOfNotEqual( x.length, 1.0, x, 1, 0 ); +* // returns 2 +*/ +function gindexOfNotEqual( N, searchElement, x, strideX, offsetX ) { + var ix; + var o; + var i; + + if ( N <= 0 ) { + return -1; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + return accessors( N, searchElement, o, strideX, offsetX ); + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] !== searchElement ) { + return i; + } + ix += strideX; + } + return -1; +} + + +// EXPORTS // + +module.exports = gindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/package.json new file mode 100644 index 000000000000..af543d7033e6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/gindex-of-not-equal", + "version": "0.0.0", + "description": "Return the first index of an element in a strided array which is not equal to a specified search element.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "search", + "index", + "get", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.js new file mode 100644 index 000000000000..e6b4186ea0ba --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gindexOfNotEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gindexOfNotEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.main.js new file mode 100644 index 000000000000..2601cf099fd8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.main.js @@ -0,0 +1,288 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gindexOfNotEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( gindexOfNotEqual.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element', function test( t ) { + var actual; + var x; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + + // Nonnegative stride... + actual = gindexOfNotEqual( x.length, 1.0, x, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + actual = gindexOfNotEqual( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = gindexOfNotEqual( x.length, 1.0, x, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + actual = gindexOfNotEqual( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element', function test( t ) { + var actual; + var x; + + x = [ 2.0, 2.0, 2.0 ]; + + actual = gindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray( [ 2.0, 2.0, 2.0 ] ); + + actual = gindexOfNotEqual( x.length, 2.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfNotEqual( -1, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 0, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfNotEqual( -1, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN`', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 2, NaN, [ NaN, 1.0 ], 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN` (accessors)', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 2, NaN, toAccessorArray( [ NaN, 1.0 ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 1.0, x, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 1.0, toAccessorArray( x ), 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + + x = [ 1.0, 1.0, 1.0, 1.0, 0.0, 1.0 ]; + + actual = gindexOfNotEqual( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + + x = [ 1.0, 1.0, 1.0, 1.0, 0.0, 1.0 ]; + + actual = gindexOfNotEqual( x.length, 1.0, toAccessorArray( x ), -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 9.0, + 1.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 1.0, x, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns (accessors)', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 9.0, + 1.0, // 1 + 9.0, + 0.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 1.0, toAccessorArray( x ), 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var x1; + + x0 = new Float64Array( [ 9.0, 0.0, 1.0, 0.0, 0.0 ] ); + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + actual = gindexOfNotEqual( 3, 0.0, x1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.ndarray.js new file mode 100644 index 000000000000..2b80a3a06bcb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-not-equal/test/test.ndarray.js @@ -0,0 +1,294 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gindexOfNotEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gindexOfNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element', function test( t ) { + var actual; + var x; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + + // Nonnegative stride... + actual = gindexOfNotEqual( x.length, 1.0, x, 1, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + actual = gindexOfNotEqual( x.length, 1.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, -1, x.length-1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element in a strided array which is not equal to a provided search element (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = gindexOfNotEqual( x.length, 1.0, x, 1, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + actual = gindexOfNotEqual( x.length, 1.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 2.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 3.0, x, -1, x.length-1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfNotEqual( x.length, 4.0, x, -1, x.length-1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element', function test( t ) { + var actual; + var x; + + x = [ 2.0, 2.0, 2.0 ]; + + actual = gindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every indexed element in the array is equal to the search element (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray( [ 2.0, 2.0, 2.0 ] ); + + actual = gindexOfNotEqual( x.length, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfNotEqual( -1, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 0, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfNotEqual( -1, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN`', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 2, NaN, [ NaN, 1.0 ], 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided `searchElement` is `NaN` (accessors)', function test( t ) { + var actual; + + actual = gindexOfNotEqual( 2, NaN, toAccessorArray( [ NaN, 1.0 ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 0.0, x, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + + x = [ + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 0.0, toAccessorArray( x ), 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var actual; + var x; + + x = [ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 0.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var actual; + var x; + + x = [ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 0.0, toAccessorArray( x ), 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + + x = [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ]; + + actual = gindexOfNotEqual( x.length, 0.0, x, -1, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + + x = [ 5.0, 4.0, 3.0, 2.0, 1.0, 0.0 ]; + + actual = gindexOfNotEqual( x.length, 0.0, toAccessorArray( x ), -1, x.length-1 ); // eslint-disable-line max-len + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + + x = [ + 9.0, + 0.0, // 0 + 9.0, + 0.0, // 1 + 9.0, + 1.0 // 2 + ]; + + actual = gindexOfNotEqual( 3, 0.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/README.md b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/README.md new file mode 100644 index 000000000000..845fa63a226a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/README.md @@ -0,0 +1,187 @@ + + +# gindexOfSameValue + +> Return the index of the first element in a strided array which has the same value as a provided search element. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var gindexOfSameValue = require( '@stdlib/blas/ext/base/gindex-of-same-value' ); +``` + +#### gindexOfSameValue( N, searchElement, x, strideX ) + +Returns the index of the first element in a strided array which has the same value as a provided search element. + +```javascript +var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; + +var idx = gindexOfSameValue( x.length, 3.0, x, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **x**: input array. +- **strideX**: stride length. + +If the function is unable to find a search element, the function returns `-1`. + +```javascript +var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; + +var idx = gindexOfSameValue( x.length, 8.0, x, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to search every other element: + +```javascript +var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; + +var idx = gindexOfSameValue( 4, -1.0, x, 2 ); +// returns 3 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial array... +var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] ); + +// Create an offset view... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = gindexOfSameValue( 3, -6.0, x1, 2 ); +// returns 2 +``` + +#### gindexOfSameValue.ndarray( N, searchElement, x, strideX, offsetX ) + +Returns the index of the first element in a strided array which has the same value as a provided search element using alternative indexing semantics. + +```javascript +var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; + +var idx = gindexOfSameValue.ndarray( x.length, 3.0, x, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array: + +```javascript +var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; + +var idx = gindexOfSameValue.ndarray( 3, 3.0, x, 1, x.length-3 ); +// returns 2 +``` + +
+ + + + + +
+ +## Notes + +- When searching for a search element, the function checks for equality using the same value algorithm. As a consequence, `NaN` values are considered equal, and `-0` and `+0` are considered distinct. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gindexOfSameValue = require( '@stdlib/blas/ext/base/gindex-of-same-value' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'generic' +}); +console.log( x ); + +var idx = gindexOfSameValue( x.length, 80.0, x, 1 ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/benchmark/benchmark.js new file mode 100644 index 000000000000..4b482710e337 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/benchmark/benchmark.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gindexOfSameValue = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gindexOfSameValue( x.length, len+1, x, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..5d79117799b8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/benchmark/benchmark.ndarray.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gindexOfSameValue = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gindexOfSameValue( x.length, len+1, x, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/repl.txt new file mode 100644 index 000000000000..5de6c917b347 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/repl.txt @@ -0,0 +1,95 @@ + +{{alias}}( N, searchElement, x, strideX ) + Returns the index of the first element in a strided array which has the same + value as a provided search element. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; + > var idx = {{alias}}( x.length, 1.0, x, 1 ) + 1 + + // Using `N` and stride parameters: + > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; + > var idx = {{alias}}( 3, 4.0, x, 2 ) + 2 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var idx = {{alias}}( 3, -1.0, x1, 2 ) + 2 + + +{{alias}}.ndarray( N, searchElement, x, strideX, offsetX ) + Returns the index of the first element in a strided array which has the same + value as a provided search element using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: any + Search element. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; + > var idx = {{alias}}.ndarray( x.length, 1.0, x, 1, 0 ) + 1 + + // Advanced indexing: + > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ]; + > var idx = {{alias}}.ndarray( 3, -1.0, x, 2, 1 ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/types/index.d.ts new file mode 100644 index 000000000000..bd82c8151ece --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/types/index.d.ts @@ -0,0 +1,108 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `gindexOfSameValue`. +*/ +interface Routine { + /** + * Returns the index of the first element in a strided array which has the same value as a provided search element. + * + * ## Notes + * + * - If the function is unable to find a search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * + * var idx = gindexOfSameValue( x.length, 2.0, x, 1 ); + * // returns 1 + */ + ( N: number, searchElement: unknown, x: InputArray, strideX: number ): number; + + /** + * Returns the index of the first element in a strided array which has the same value as a provided search element using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find a search element, the function returns `-1`. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * + * var idx = gindexOfSameValue.ndarray( x.length, 2.0, x, 1, 0 ); + * // returns 1 + */ + ndarray( N: number, searchElement: unknown, x: InputArray, strideX: number, offsetX: number ): number; +} + +/** +* Returns the index of the first element in a strided array which has the same value as a provided search element. +* +* ## Notes +* +* - If the function is unable to find a search element, the function returns `-1`. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param x - input array +* @param strideX - stride length +* @returns index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* +* var idx = gindexOfSameValue( x.length, 2.0, x, 1 ); +* // returns 1 +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* +* var idx = gindexOfSameValue.ndarray( x.length, 2.0, x, 1, 0 ); +* // returns 1 +*/ +declare var gindexOfSameValue: Routine; + + +// EXPORTS // + +export = gindexOfSameValue; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/types/test.ts new file mode 100644 index 000000000000..45303172e20f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/docs/types/test.ts @@ -0,0 +1,129 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gindexOfSameValue = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfSameValue( x.length, 2.0, x, 1 ); // $ExpectType number + gindexOfSameValue( x.length, 2.0, new AccessorArray( x ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfSameValue( '1', 2.0, x, 1 ); // $ExpectError + gindexOfSameValue( true, 2.0, x, 1 ); // $ExpectError + gindexOfSameValue( false, 2.0, x, 1 ); // $ExpectError + gindexOfSameValue( null, 2.0, x, 1 ); // $ExpectError + gindexOfSameValue( {}, 2.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a collection... +{ + gindexOfSameValue( x.length, 1.0, 1, 1 ); // $ExpectError + gindexOfSameValue( x.length, 1.0, true, 1 ); // $ExpectError + gindexOfSameValue( x.length, 1.0, false, 1 ); // $ExpectError + gindexOfSameValue( x.length, 1.0, null, 1 ); // $ExpectError + gindexOfSameValue( x.length, 1.0, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfSameValue( x.length, 2.0, x, '1' ); // $ExpectError + gindexOfSameValue( x.length, 2.0, x, true ); // $ExpectError + gindexOfSameValue( x.length, 2.0, x, false ); // $ExpectError + gindexOfSameValue( x.length, 2.0, x, null ); // $ExpectError + gindexOfSameValue( x.length, 2.0, x, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + gindexOfSameValue(); // $ExpectError + gindexOfSameValue( 3, 2.0 ); // $ExpectError + gindexOfSameValue( 3, 2.0, [ 1.0, 2.0, 3.0 ] ); // $ExpectError + gindexOfSameValue( 3, 2.0, [ 1.0, 2.0, 3.0 ], 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfSameValue.ndarray( x.length, 2.0, x, 1, 0 ); // $ExpectType number + gindexOfSameValue.ndarray( x.length, 2.0, new AccessorArray( x ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfSameValue.ndarray( '1', 2.0, x, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( true, 2.0, x, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( false, 2.0, x, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( null, 2.0, x, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( {}, 2.0, x, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a collection... +{ + gindexOfSameValue.ndarray( x.length, 1.0, 1, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 1.0, true, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 1.0, false, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 1.0, null, 1, 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 1.0, {}, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfSameValue.ndarray( x.length, 2.0, x, '1', 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, true, 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, false, 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, null, 1 ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + gindexOfSameValue.ndarray( x.length, 2.0, x, 1, '1' ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, 1, true ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, 1, false ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, 1, null ); // $ExpectError + gindexOfSameValue.ndarray( x.length, 2.0, x, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + gindexOfSameValue.ndarray(); // $ExpectError + gindexOfSameValue.ndarray( 3, 2.0 ); // $ExpectError + gindexOfSameValue.ndarray( 3, 2.0, [ 1.0, 2.0, 3.0 ] ); // $ExpectError + gindexOfSameValue.ndarray( 3, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); // $ExpectError + gindexOfSameValue.ndarray( 3, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/examples/index.js new file mode 100644 index 000000000000..da15251b0f09 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gindexOfSameValue = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'generic' +}); +console.log( x ); + +var idx = gindexOfSameValue( x.length, 80.0, x, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/accessors.js new file mode 100644 index 000000000000..67aec8c59246 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/accessors.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isSameValue = require( '@stdlib/assert/is-same-value' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which has the same value as a provided search element. +* +* ## Notes +* +* - If the function is unable to find a search element, the function returns `-1`. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {integer} index +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; +* +* var idx = gindexOfSameValue( x.length, 3.0, arraylike2object( toAccessorArray( x ) ), 1, 0 ); +* // returns 2 +*/ +function gindexOfSameValue( N, searchElement, x, strideX, offsetX ) { + var xbuf; + var get; + var ix; + var i; + + // Cache a reference to array data: + xbuf = x.data; + + // Cache a reference to the element accessor: + get = x.accessors[ 0 ]; + + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( isSameValue( searchElement, get( xbuf, ix ) ) ) { + return i; + } + ix += strideX; + } + return -1; +} + + +// EXPORTS // + +module.exports = gindexOfSameValue; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/index.js new file mode 100644 index 000000000000..c33ba5acd785 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the first element in a strided array which has the same value as a provided search element. +* +* @module @stdlib/blas/ext/base/gindex-of-same-value +* +* @example +* var gindexOfSameValue = require( '@stdlib/blas/ext/base/gindex-of-same-value' ); +* +* var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; +* +* var idx = gindexOfSameValue( x.length, 3.0, x, 1 ); +* // returns 2 +* +* @example +* var gindexOfSameValue = require( '@stdlib/blas/ext/base/gindex-of-same-value' ); +* +* var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; +* +* var idx = gindexOfSameValue.ndarray( x.length, 3.0, x, 1, 0 ); +* // returns 2 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/main.js new file mode 100644 index 000000000000..3152e658afef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/main.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which has the same value as a provided search element. +* +* ## Notes +* +* - If the function is unable to find a search element, the function returns `-1`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @returns {integer} index +* +* @example +* var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; +* +* var idx = gindexOfSameValue( x.length, 3.0, x, 1 ); +* // returns 2 +*/ +function gindexOfSameValue( N, searchElement, x, strideX ) { + return ndarray( N, searchElement, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = gindexOfSameValue; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/ndarray.js new file mode 100644 index 000000000000..498194cb040c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/lib/ndarray.js @@ -0,0 +1,75 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var isSameValue = require( '@stdlib/assert/is-same-value' ); +var accessors = require( './accessors.js' ); + + +// MAIN // + +/** +* Returns the index of the first element in a strided array which has the same value as a provided search element using alternative indexing semantics. +* +* ## Notes +* +* - If the function is unable to find a search element, the function returns `-1`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {*} searchElement - search element +* @param {Collection} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {integer} index +* +* @example +* var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, 3.0 ]; +* +* var idx = gindexOfSameValue( x.length, 3.0, x, 1, 0 ); +* // returns 2 +*/ +function gindexOfSameValue( N, searchElement, x, strideX, offsetX ) { + var ix; + var o; + var i; + + if ( N <= 0 ) { + return -1; + } + o = arraylike2object( x ); + if ( o.accessorProtocol ) { + return accessors( N, searchElement, o, strideX, offsetX ); + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( isSameValue( searchElement, x[ ix ] ) ) { + return i; + } + ix += strideX; + } + return -1; +} + + +// EXPORTS // + +module.exports = gindexOfSameValue; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/package.json b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/package.json new file mode 100644 index 000000000000..1e2b154954bd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/gindex-of-same-value", + "version": "0.0.0", + "description": "Return the index of the first element in a strided array which has the same value as a provided search element.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "search", + "index", + "get", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.js new file mode 100644 index 000000000000..f4eeb3d43302 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gindexOfSameValue = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gindexOfSameValue, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gindexOfSameValue.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.main.js new file mode 100644 index 000000000000..be9e03d4951a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.main.js @@ -0,0 +1,303 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gindexOfSameValue = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gindexOfSameValue, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( gindexOfSameValue.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which has the same value as a provided search element', function test( t ) { + var actual; + var x; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + + // Nonnegative stride... + actual = gindexOfSameValue( x.length, 1.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 2.0, x, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 3.0, x, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 4.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + actual = gindexOfSameValue( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 2.0, x, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 3.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 4.0, x, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which has the same value as a provided search element (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = gindexOfSameValue( x.length, 1.0, x, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 2.0, x, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 3.0, x, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 4.0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + actual = gindexOfSameValue( x.length, 1.0, x, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 2.0, x, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 3.0, x, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 4.0, x, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = gindexOfSameValue( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( -1, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = gindexOfSameValue( 0, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( -1, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index when searching for `NaN`', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, NaN, [ NaN ], 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index when searching for `NaN` (accessors)', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, NaN, toAccessorArray( [ NaN ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function distinguishes between -0 and +0', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, 0.0, [ -0.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, [ 0.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, 0.0, [ 0.0 ], 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, [ -0.0 ], 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function distinguishes between -0 and +0 (accessors)', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, 0.0, toAccessorArray( [ -0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, toAccessorArray( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, 0.0, toAccessorArray( [ 0.0 ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, toAccessorArray( [ -0.0 ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + + actual = gindexOfSameValue( 3, 3.0, x, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + + actual = gindexOfSameValue( 3, 3.0, x, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + + actual = gindexOfSameValue( 3, 3.0, x, -2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + + actual = gindexOfSameValue( 3, 3.0, x, -2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + + actual = gindexOfSameValue( 3, 3.0, x, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var x1; + + // Initial array... + x0 = new Float64Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + + // Create offset view... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + + actual = gindexOfSameValue( 3, 4.0, x1, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.ndarray.js new file mode 100644 index 000000000000..0a9db7c83df4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of-same-value/test/test.ndarray.js @@ -0,0 +1,323 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gindexOfSameValue = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gindexOfSameValue, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gindexOfSameValue.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which has the same value as a provided search element', function test( t ) { + var actual; + var x; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + + // Nonnegative stride... + actual = gindexOfSameValue( x.length, 1.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( x.length-1, 2.0, x, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = gindexOfSameValue( x.length-2, 3.0, x, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length-2, 4.0, x, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + actual = gindexOfSameValue( x.length, 1.0, x, -1, x.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + actual = gindexOfSameValue( 3, 2.0, x, -2, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = gindexOfSameValue( 3, 1.0, x, -2, x.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 4.0, x, -1, x.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index of an element which has the same value as a provided search element (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + // Nonnegative stride... + actual = gindexOfSameValue( x.length, 1.0, x, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( x.length-1, 2.0, x, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = gindexOfSameValue( x.length-2, 3.0, x, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length-2, 4.0, x, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + actual = gindexOfSameValue( x.length, 1.0, x, -1, x.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + actual = gindexOfSameValue( 3, 2.0, x, -2, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = gindexOfSameValue( 3, 1.0, x, -2, x.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + actual = gindexOfSameValue( x.length, 4.0, x, -1, x.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = gindexOfSameValue( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( -1, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray( [ 1.0, 2.0, 3.0 ] ); + + actual = gindexOfSameValue( 0, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( -1, 2.0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index when searching for `NaN`', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, NaN, [ NaN ], 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the first index when searching for `NaN` (accessors)', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, NaN, toAccessorArray( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function distinguishes between -0 and +0', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, 0.0, [ -0.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, [ 0.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, 0.0, [ 0.0 ], 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, [ -0.0 ], 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function distinguishes between -0 and +0 (accessors)', function test( t ) { + var actual; + + actual = gindexOfSameValue( 1, 0.0, toAccessorArray( [ -0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, toAccessorArray( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = gindexOfSameValue( 1, 0.0, toAccessorArray( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = gindexOfSameValue( 1, -0.0, toAccessorArray( [ -0.0 ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + + actual = gindexOfSameValue( 3, 3.0, x, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + + actual = gindexOfSameValue( 3, 3.0, x, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + + actual = gindexOfSameValue( 3, 3.0, x, -2, 4 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + + actual = gindexOfSameValue( 3, 3.0, x, -2, 4 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var actual; + var x; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]; + + actual = gindexOfSameValue( 4, 2.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var actual; + var x; + + x = toAccessorArray([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + + actual = gindexOfSameValue( 4, 2.0, x, 2, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + + actual = gindexOfSameValue( 3, 3.0, x, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/docs/repl.txt index 1c55282b286d..64fd6f8de899 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/docs/repl.txt @@ -36,7 +36,7 @@ 1 -{{alias}}( N, searchElement, x, strideX, offsetX ) +{{alias}}.ndarray( N, searchElement, x, strideX, offsetX ) Returns the first index of a specified search element in a strided array using alternative indexing semantics. diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.main.js index 3ced0ed6d992..56a6cd5d8aac 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.main.js @@ -108,7 +108,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; actual = gindexOf( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); @@ -120,7 +120,7 @@ tape( 'the function returns `-1` if provided `N` parameter is less than or equal t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { var actual; actual = gindexOf( 0, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.ndarray.js index 681a34ae8878..4d1b4a570710 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/gindex-of/test/test.ndarray.js @@ -108,7 +108,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; actual = gindexOf( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0 ); @@ -120,7 +120,7 @@ tape( 'the function returns `-1` if provided an `N` parameter is less than or eq t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero (accessors)', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero (accessors)', function test( t ) { var actual; actual = gindexOf( 0, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/README.md new file mode 100644 index 000000000000..24722730328c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/README.md @@ -0,0 +1,201 @@ + + +# glastIndexEqual + +> Return the index of the last element in a strided array equal to a corresponding element in another strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var glastIndexEqual = require( '@stdlib/blas/ext/base/glast-index-equal' ); +``` + +#### glastIndexEqual( N, x, strideX, y, strideY ) + +Returns the index of the last element in a strided array equal to a corresponding element in another strided array. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 0.0, 0.0, 3.0, 0.0 ]; + +var idx = glastIndexEqual( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input array. +- **strideX**: stride length for `x`. +- **y**: second input array. +- **strideY**: stride length for `y`. + +If the function is unable to find matching elements, the function returns `-1`. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 5.0, 6.0, 7.0, 8.0 ]; + +var idx = glastIndexEqual( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compare every other element: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + +var idx = glastIndexEqual( 3, x, 2, y, 2 ); +// returns 1 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float64Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = glastIndexEqual( 2, x1, 1, y1, 1 ); +// returns 1 +``` + +#### glastIndexEqual.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Returns the index of the last element in a strided array equal to a corresponding element in another strided array using alternative indexing semantics. + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0 ]; +var y = [ 0.0, 0.0, 3.0, 0.0 ]; + +var idx = glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last three elements of each strided array: + +```javascript +var x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; +var y = [ 0.0, 0.0, 0.0, 4.0, 5.0, 6.0 ]; + +var idx = glastIndexEqual.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 2 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct, and `-0` and `+0` are considered the same. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var glastIndexEqual = require( '@stdlib/blas/ext/base/glast-index-equal' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = glastIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..cd6d0397b75a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/benchmark/benchmark.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var glastIndexEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = glastIndexEqual( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..406963bda924 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var glastIndexEqual = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float64' ); + var y = zeros( len, 'float64' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = glastIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/repl.txt new file mode 100644 index 000000000000..4ea27fa169e5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/repl.txt @@ -0,0 +1,111 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the last element in a strided array equal to a + corresponding element in another strided array. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 2.0, 3.0, 4.0 ]; + > var y = [ 0.0, 0.0, 3.0, 0.0 ]; + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + > idx = {{alias}}( 3, x, 2, y, 2 ) + 1 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var y0 = new {{alias:@stdlib/array/float64}}( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + > idx = {{alias}}( 3, x1, 2, y1, 2 ) + -1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the last element in a strided array equal to a + corresponding element in another strided array using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on + starting indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Array|TypedArray + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = [ 1.0, 2.0, 3.0, 4.0 ]; + > var y = [ 0.0, 0.0, 3.0, 0.0 ]; + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using offsets: + > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + > idx = {{alias}}.ndarray( 3, x, 2, 1, y, 2, 2 ) + -1 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..d6819d0cf3c9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/types/index.d.ts @@ -0,0 +1,116 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = Collection | AccessorArrayLike; + +/** +* Interface describing `glastIndexEqual`. +*/ +interface Routine { + /** + * Returns the index of the last element in a strided array equal to a corresponding element in another strided array. + * + * ## Notes + * + * - If the function is unable to find matching elements, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = glastIndexEqual( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: InputArray, strideX: number, y: InputArray, strideY: number ): number; + + /** + * Returns the index of the last element in a strided array equal to a corresponding element in another strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find matching elements, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var x = [ 1.0, 2.0, 3.0, 4.0 ]; + * var y = [ 0.0, 0.0, 3.0, 0.0 ]; + * + * var idx = glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number, y: InputArray, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the last element in a strided array equal to a corresponding element in another strided array. +* +* ## Notes +* +* - If the function is unable to find matching elements, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = glastIndexEqual( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var glastIndexEqual: Routine; + + +// EXPORTS // + +export = glastIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/types/test.ts new file mode 100644 index 000000000000..e9d804868a30 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/docs/types/test.ts @@ -0,0 +1,237 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import glastIndexEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual( x.length, x, 1, y, 1 ); // $ExpectType number + glastIndexEqual( x.length, new AccessorArray( x ), 1, new AccessorArray( y ), 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual( '1', x, 1, y, 1 ); // $ExpectError + glastIndexEqual( true, x, 1, y, 1 ); // $ExpectError + glastIndexEqual( false, x, 1, y, 1 ); // $ExpectError + glastIndexEqual( null, x, 1, y, 1 ); // $ExpectError + glastIndexEqual( undefined, x, 1, y, 1 ); // $ExpectError + glastIndexEqual( [], x, 1, y, 1 ); // $ExpectError + glastIndexEqual( {}, x, 1, y, 1 ); // $ExpectError + glastIndexEqual( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual( 3, 10, 1, y, 1 ); // $ExpectError + glastIndexEqual( 3, true, 1, y, 1 ); // $ExpectError + glastIndexEqual( 3, false, 1, y, 1 ); // $ExpectError + glastIndexEqual( 3, null, 1, y, 1 ); // $ExpectError + glastIndexEqual( 3, undefined, 1, y, 1 ); // $ExpectError + glastIndexEqual( 3, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual( x.length, x, '1', y, 1 ); // $ExpectError + glastIndexEqual( x.length, x, true, y, 1 ); // $ExpectError + glastIndexEqual( x.length, x, false, y, 1 ); // $ExpectError + glastIndexEqual( x.length, x, null, y, 1 ); // $ExpectError + glastIndexEqual( x.length, x, undefined, y, 1 ); // $ExpectError + glastIndexEqual( x.length, x, [], y, 1 ); // $ExpectError + glastIndexEqual( x.length, x, {}, y, 1 ); // $ExpectError + glastIndexEqual( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a collection... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual( x.length, x, 1, 10, 1 ); // $ExpectError + glastIndexEqual( x.length, x, 1, true, 1 ); // $ExpectError + glastIndexEqual( x.length, x, 1, false, 1 ); // $ExpectError + glastIndexEqual( x.length, x, 1, null, 1 ); // $ExpectError + glastIndexEqual( x.length, x, 1, undefined, 1 ); // $ExpectError + glastIndexEqual( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual( x.length, x, 1, y, '1' ); // $ExpectError + glastIndexEqual( x.length, x, 1, y, true ); // $ExpectError + glastIndexEqual( x.length, x, 1, y, false ); // $ExpectError + glastIndexEqual( x.length, x, 1, y, null ); // $ExpectError + glastIndexEqual( x.length, x, 1, y, undefined ); // $ExpectError + glastIndexEqual( x.length, x, 1, y, [] ); // $ExpectError + glastIndexEqual( x.length, x, 1, y, {} ); // $ExpectError + glastIndexEqual( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual(); // $ExpectError + glastIndexEqual( 3 ); // $ExpectError + glastIndexEqual( 3, x ); // $ExpectError + glastIndexEqual( 3, x, 1 ); // $ExpectError + glastIndexEqual( 3, x, 1, y ); // $ExpectError + glastIndexEqual( 3, x, 1, y, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number + glastIndexEqual.ndarray( x.length, new AccessorArray( x ), 1, 0, new AccessorArray( y ), 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a collection... +{ + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( 3, 10, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( 3, true, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( 3, false, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( 3, null, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( 3, undefined, 1, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( 3, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a collection... +{ + var x = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( x.length, x, 1, 0, 10, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + var x = [ 1.0, 2.0, 3.0 ]; + var y = [ 1.0, 2.0, 3.0 ]; + + glastIndexEqual.ndarray(); // $ExpectError + glastIndexEqual.ndarray( 3 ); // $ExpectError + glastIndexEqual.ndarray( 3, x ); // $ExpectError + glastIndexEqual.ndarray( 3, x, 1 ); // $ExpectError + glastIndexEqual.ndarray( 3, x, 1, 0 ); // $ExpectError + glastIndexEqual.ndarray( 3, x, 1, 0, y ); // $ExpectError + glastIndexEqual.ndarray( 3, x, 1, 0, y, 1 ); // $ExpectError + glastIndexEqual.ndarray( 3, x, 1, 0, y, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/examples/index.js new file mode 100644 index 000000000000..6c20682c62f2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var glastIndexEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'generic' +}); +console.log( y ); + +var idx = glastIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/index.js new file mode 100644 index 000000000000..24db051ccbe4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the last element in a strided array equal to a corresponding element in another strided array. +* +* @module @stdlib/blas/ext/base/glast-index-equal +* +* @example +* var glastIndexEqual = require( '@stdlib/blas/ext/base/glast-index-equal' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +* var y = [ 5.0, 4.0, 3.0, 2.0, 1.0 ]; +* +* var idx = glastIndexEqual( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var glastIndexEqual = require( '@stdlib/blas/ext/base/glast-index-equal' ); +* +* var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; +* var y = [ 5.0, 4.0, 3.0, 2.0, 1.0 ]; +* +* var idx = glastIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/main.js new file mode 100644 index 000000000000..84c927d2de7a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Returns the index of the last element in a strided array equal to a corresponding element in another strided array. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @returns {integer} index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = glastIndexEqual( x.length, x, 1, y, 1 ); +* // returns 2 +*/ +function glastIndexEqual( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = glastIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/ndarray.js new file mode 100644 index 000000000000..aa20112736b8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/lib/ndarray.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var gfirstIndexEqual = require( '@stdlib/blas/ext/base/gfirst-index-equal' ).ndarray; + + +// MAIN // + +/** +* Returns the index of the last element in a strided array equal to a corresponding element in another strided array using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Collection} x - first input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Collection} y - second input array +* @param {integer} strideY - stride length for `y` +* @param {NonNegativeInteger} offsetY - starting index for `y` +* @returns {integer} index +* +* @example +* var x = [ 1.0, 2.0, 3.0, 4.0 ]; +* var y = [ 0.0, 0.0, 3.0, 0.0 ]; +* +* var idx = glastIndexEqual( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +function glastIndexEqual( N, x, strideX, offsetX, y, strideY, offsetY ) { + var idx; + + if ( N <= 0 ) { + return -1; + } + // Reverse the iteration order by flipping the strides and adjusting the offsets: + offsetX += ( N-1 ) * strideX; + offsetY += ( N-1 ) * strideY; + strideX *= -1; + strideY *= -1; + + // Find the index of the first matching element in the reversed "views": + idx = gfirstIndexEqual( N, x, strideX, offsetX, y, strideY, offsetY ); + if ( idx < 0 ) { + return idx; + } + // Convert the index from the reversed "views" to an index in the original "views": + return N - 1 - idx; +} + + +// EXPORTS // + +module.exports = glastIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/package.json new file mode 100644 index 000000000000..b28526580248 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/blas/ext/base/glast-index-equal", + "version": "0.0.0", + "description": "Return the index of the last element in a strided array equal to a corresponding element in another strided array.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "equal", + "index", + "compare", + "strided", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.js new file mode 100644 index 000000000000..cfe36fba948c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var glastIndexEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof glastIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof glastIndexEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.main.js new file mode 100644 index 000000000000..74f2f1c1a9cd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.main.js @@ -0,0 +1,440 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var glastIndexEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof glastIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( glastIndexEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the last index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + // Nonnegative stride... + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ]; + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the last index of an element which equals a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ] ); + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + + actual = glastIndexEqual( 0, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = glastIndexEqual( -1, [ 1.0, 2.0, 3.0 ], 1, [ 1.0, 2.0, 3.0 ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = glastIndexEqual( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = glastIndexEqual( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, [ NaN ], 1, [ NaN ], 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN` (accessors)', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, toAccessorArray( [ NaN ] ), 1, toAccessorArray( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, [ -0.0 ], 1, [ 0.0 ], 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal (accessors)', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, toAccessorArray( [ -0.0 ] ), 1, toAccessorArray( [ 0.0 ] ), 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, toAccessorArray( x ), 2, toAccessorArray( y ), 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = glastIndexEqual( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = glastIndexEqual( 3, toAccessorArray( x ), 1, toAccessorArray( y ), 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, toAccessorArray( x ), -2, toAccessorArray( y ), -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float64Array([ + 1.0, + 2.0, // 2 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float64Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 4.0, // 1 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = glastIndexEqual( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.ndarray.js new file mode 100644 index 000000000000..5966a6b45af9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-equal/test/test.ndarray.js @@ -0,0 +1,405 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var glastIndexEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof glastIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( glastIndexEqual.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the last index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + // Nonnegative stride... + actual = glastIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ]; + + actual = glastIndexEqual( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ]; + + actual = glastIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + y = [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ]; + y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + + actual = glastIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the last index of an element which equals a corresponding element in another array (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = glastIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = glastIndexEqual( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = glastIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = toAccessorArray( [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = glastIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = toAccessorArray( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = toAccessorArray( [ 5.0, 6.0, 7.0, 8.0 ] ); + + actual = glastIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + + actual = glastIndexEqual( 0, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = glastIndexEqual( -1, [ 1.0, 2.0, 3.0 ], 1, 0, [ 1.0, 2.0, 3.0 ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero (accessors)', function test( t ) { + var actual; + + actual = glastIndexEqual( 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = glastIndexEqual( -1, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, [ NaN ], 1, 0, [ NaN ], 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN` (accessors)', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, toAccessorArray( [ NaN ] ), 1, 0, toAccessorArray( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, [ -0.0 ], 1, 0, [ 0.0 ], 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal (accessors)', function test( t ) { + var actual; + + actual = glastIndexEqual( 1, toAccessorArray( [ -0.0 ] ), 1, 0, toAccessorArray( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]; + y = [ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = glastIndexEqual( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]; + y = [ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]; + + actual = glastIndexEqual( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]; + y = [ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, toAccessorArray( x ), -2, 4, toAccessorArray( y ), -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]; + y = [ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]; + + actual = glastIndexEqual( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/lib/ndarray.js index 1cc55de2dfd6..885da3022418 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/lib/ndarray.js @@ -57,8 +57,7 @@ function glastIndexOf( N, searchElement, x, strideX, offsetX ) { return idx; } // Convert the index from reversed "view" to an index in the original "view": - idx = N - 1 - idx; - return idx; + return N - 1 - idx; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.main.js index c8dcccab256e..8308a0003707 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.main.js +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.main.js @@ -103,7 +103,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; actual = glastIndexOf( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1 ); @@ -115,7 +115,7 @@ tape( 'the function returns `-1` if provided `N` parameter is less than or equal t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero (accessors)', function test( t ) { var actual; actual = glastIndexOf( 0, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.ndarray.js index be2665328d63..abdafdc8aa8f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/glast-index-of/test/test.ndarray.js @@ -103,7 +103,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; actual = glastIndexOf( 0, 2.0, [ 1.0, 2.0, 3.0 ], 1, 0 ); @@ -115,7 +115,7 @@ tape( 'the function returns `-1` if provided an `N` parameter is less than or eq t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero (accessors)', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero (accessors)', function test( t ) { var actual; actual = glastIndexOf( 0, 2.0, toAccessorArray( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gnancount/package.json b/lib/node_modules/@stdlib/blas/ext/base/gnancount/package.json index 4e9c8c3eae14..c1353eea6335 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/gnancount/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/gnancount/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/gnancount", "version": "0.0.0", - "description": "Calculate the number of non-`NaN` elements in a strided array.", + "description": "Calculate the number of non-NaN elements in a strided array.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/gxdy/README.md new file mode 100644 index 000000000000..7612101349b2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/README.md @@ -0,0 +1,190 @@ + + +# gxdy + +> Divide elements of a strided array `x` by the corresponding elements of a strided array `y` and assign the results to `y`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var gxdy = require( '@stdlib/blas/ext/base/gxdy' ); +``` + +#### gxdy( N, x, strideX, y, strideY ) + +Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y`. + +```javascript +var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + +gxdy( x.length, x, 1, y, 1 ); +// y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideX**: stride length for `x`. +- **y**: output [`Array`][mdn-array] or [`typed array`][mdn-typed-array]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to divide every other element of `x` by every other element of `y`: + +```javascript +var x = [ 6.0, 2.0, 20.0, 4.0, 30.0, 6.0 ]; +var y = [ 2.0, 8.0, 4.0, 10.0, 5.0, 12.0 ]; + +gxdy( 3, x, 2, y, 2 ); +// y => [ 3.0, 8.0, 5.0, 10.0, 6.0, 12.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +// Initial arrays... +var x0 = new Float64Array( [ 1.0, 6.0, 12.0, 20.0, 5.0, 6.0 ] ); +var y0 = new Float64Array( [ 7.0, 8.0, 2.0, 3.0, 4.0, 12.0 ] ); + +// Create offset views... +var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +gxdy( 3, x1, 1, y1, 1 ); +// y0 => [ 7.0, 8.0, 3.0, 4.0, 5.0, 12.0 ] +``` + +#### gxdy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```javascript +var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + +gxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to divide the last three elements of `x` by the last three elements of `y`: + +```javascript +var x = [ 1.0, 2.0, 12.0, 20.0, 30.0 ]; +var y = [ 6.0, 7.0, 3.0, 4.0, 5.0 ]; + +gxdy.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// y => [ 6.0, 7.0, 4.0, 5.0, 6.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. +- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gxdy = require( '@stdlib/blas/ext/base/gxdy' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 1, 100, { + 'dtype': 'float64' +}); +console.log( y ); + +gxdy( x.length, x, 1, y, 1 ); +console.log( y ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/base/accessor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/accessor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..6c0e7a658837 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/benchmark/benchmark.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gxdy = require( './../lib/main.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var y = uniform( len, 1, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = gxdy( x.length, x, 1, y, 1 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..d88eb2577b73 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/benchmark/benchmark.ndarray.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gxdy = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var y = uniform( len, 1, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = gxdy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/repl.txt new file mode 100644 index 000000000000..54d50e561ab7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/repl.txt @@ -0,0 +1,118 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Divides elements of a strided array `x` by the corresponding elements of a + strided array `y` and assigns the results to `y`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length for `x`. + + y: Array|TypedArray + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + y: Array|TypedArray + Output array. + + Examples + -------- + // Standard Usage: + > var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + > var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > {{alias}}( x.length, x, 1, y, 1 ) + [ 2.0, 2.0, 3.0, 4.0, 5.0 ] + + // Using `N` and stride parameters: + > x = [ 6.0, 2.0, 20.0, 4.0, 30.0, 6.0 ]; + > y = [ 2.0, 8.0, 4.0, 10.0, 5.0, 12.0 ]; + > {{alias}}( 3, x, 2, y, 2 ) + [ 3.0, 8.0, 5.0, 10.0, 6.0, 12.0 ] + + // Using view offsets: + > var bufX = [ 1.0, 6.0, 12.0, 20.0, 5.0, 6.0 ]; + > var bufY = [ 7.0, 8.0, 2.0, 3.0, 4.0, 12.0 ]; + > var x0 = new {{alias:@stdlib/array/float64}}( bufX ); + > var y0 = new {{alias:@stdlib/array/float64}}( bufY ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetY = y0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, offsetX ); + > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, offsetY ); + > {{alias}}( 3, x1, 1, y1, 1 ) + [ 3.0, 4.0, 5.0, 12.0 ] + > y0 + [ 7.0, 8.0, 3.0, 4.0, 5.0, 12.0 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Divides elements of a strided array `x` by the corresponding elements of a + strided array `y` and assigns the results to `y` using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Array|TypedArray + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Array|TypedArray + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + y: Array|TypedArray + Output array. + + Examples + -------- + // Standard Usage: + > var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + > var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ 2.0, 2.0, 3.0, 4.0, 5.0 ] + + // Using index offsets: + > x = [ 1.0, 2.0, 12.0, 20.0, 30.0 ]; + > y = [ 6.0, 7.0, 3.0, 4.0, 5.0 ]; + > {{alias}}.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ) + [ 6.0, 7.0, 4.0, 5.0, 6.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..c9b803b5d23f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/types/index.d.ts @@ -0,0 +1,104 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { NumericArray, Collection, AccessorArrayLike } from '@stdlib/types/array'; + +/** +* Input array. +*/ +type InputArray = NumericArray | Collection | AccessorArrayLike; + +/** +* Interface describing `gxdy`. +*/ +interface Routine { + /** + * Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns `y` + * + * @example + * var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + * var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + * + * gxdy( x.length, x, 1, y, 1 ); + * // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] + */ + ( N: number, x: InputArray, strideX: number, y: T, strideY: number ): T; + + /** + * Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting index for `x` + * @param y - output array + * @param strideY - `y` stride length + * @param offsetY - starting index for `y` + * @returns `y` + * + * @example + * var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + * var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + * + * gxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] + */ + ndarray( N: number, x: InputArray, strideX: number, offsetX: number, y: T, strideY: number, offsetY: number ): T; +} + +/** +* Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y`. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - `x` stride length +* @param y - output array +* @param strideY - `y` stride length +* @returns `y` +* +* @example +* var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; +* +* gxdy( x.length, x, 1, y, 1 ); +* // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +* +* @example +* var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; +* +* gxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +declare var gxdy: Routine; + + +// EXPORTS // + +export = gxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/types/test.ts new file mode 100644 index 000000000000..9d1ee2c7db1c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/docs/types/test.ts @@ -0,0 +1,249 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import AccessorArray = require( '@stdlib/array/base/accessor' ); +import gxdy = require( './index' ); + + +// TESTS // + +// The function returns a numeric array... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy( x.length, x, 1, y, 1 ); // $ExpectType Float64Array + gxdy( x.length, new AccessorArray( x ), 1, new AccessorArray( y ), 1 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy( '10', x, 1, y, 1 ); // $ExpectError + gxdy( true, x, 1, y, 1 ); // $ExpectError + gxdy( false, x, 1, y, 1 ); // $ExpectError + gxdy( null, x, 1, y, 1 ); // $ExpectError + gxdy( undefined, x, 1, y, 1 ); // $ExpectError + gxdy( [], x, 1, y, 1 ); // $ExpectError + gxdy( {}, x, 1, y, 1 ); // $ExpectError + gxdy( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a numeric array... +{ + const y = new Float64Array( 10 ); + + gxdy( 10, 10, 1, y, 1 ); // $ExpectError + gxdy( 10, '10', 1, y, 1 ); // $ExpectError + gxdy( 10, true, 1, y, 1 ); // $ExpectError + gxdy( 10, false, 1, y, 1 ); // $ExpectError + gxdy( 10, null, 1, y, 1 ); // $ExpectError + gxdy( 10, undefined, 1, y, 1 ); // $ExpectError + gxdy( 10, [ '1' ], 1, y, 1 ); // $ExpectError + gxdy( 10, {}, 1, y, 1 ); // $ExpectError + gxdy( 10, ( x: number ): number => x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy( x.length, x, '10', y, 1 ); // $ExpectError + gxdy( x.length, x, true, y, 1 ); // $ExpectError + gxdy( x.length, x, false, y, 1 ); // $ExpectError + gxdy( x.length, x, null, y, 1 ); // $ExpectError + gxdy( x.length, x, undefined, y, 1 ); // $ExpectError + gxdy( x.length, x, [], y, 1 ); // $ExpectError + gxdy( x.length, x, {}, y, 1 ); // $ExpectError + gxdy( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + gxdy( 10, x, 1, 10, 1 ); // $ExpectError + gxdy( 10, x, 1, '10', 1 ); // $ExpectError + gxdy( 10, x, 1, true, 1 ); // $ExpectError + gxdy( 10, x, 1, false, 1 ); // $ExpectError + gxdy( 10, x, 1, null, 1 ); // $ExpectError + gxdy( 10, x, 1, undefined, 1 ); // $ExpectError + gxdy( 10, x, 1, [ '1' ], 1 ); // $ExpectError + gxdy( 10, x, 1, {}, 1 ); // $ExpectError + gxdy( 10, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy( x.length, x, 1, y, '10' ); // $ExpectError + gxdy( x.length, x, 1, y, true ); // $ExpectError + gxdy( x.length, x, 1, y, false ); // $ExpectError + gxdy( x.length, x, 1, y, null ); // $ExpectError + gxdy( x.length, x, 1, y, undefined ); // $ExpectError + gxdy( x.length, x, 1, y, [] ); // $ExpectError + gxdy( x.length, x, 1, y, {} ); // $ExpectError + gxdy( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy(); // $ExpectError + gxdy( x.length ); // $ExpectError + gxdy( x.length, x ); // $ExpectError + gxdy( x.length, x, 1 ); // $ExpectError + gxdy( x.length, x, 1, y ); // $ExpectError + gxdy( x.length, x, 1, y, 1, 10 ); // $ExpectError +} + +// Attached to the main export is an `ndarray` method which returns a numeric array... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType Float64Array + gxdy.ndarray( x.length, new AccessorArray( x ), 1, 0, new AccessorArray( y ), 1, 0 ); // $ExpectType AccessorArray +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a numeric array... +{ + const y = new Float64Array( 10 ); + + gxdy.ndarray( 10, 10, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, '10', 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, true, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, false, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, null, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, undefined, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, [ '1' ], 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, {}, 1, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a numeric array... +{ + const x = new Float64Array( 10 ); + + gxdy.ndarray( 10, x, 1, 0, 10, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, '10', 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, true, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, false, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, null, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, undefined, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, {}, 1, 0 ); // $ExpectError + gxdy.ndarray( 10, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + const y = new Float64Array( 10 ); + + gxdy.ndarray(); // $ExpectError + gxdy.ndarray( x.length ); // $ExpectError + gxdy.ndarray( x.length, x ); // $ExpectError + gxdy.ndarray( x.length, x, 1 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + gxdy.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/examples/index.js new file mode 100644 index 000000000000..6f54ffbaa32f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var gxdy = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +console.log( x ); + +var y = discreteUniform( 10, 1, 100, { + 'dtype': 'float64' +}); +console.log( y ); + +gxdy( x.length, x, 1, y, 1 ); +console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/accessors.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/accessors.js new file mode 100644 index 000000000000..9a46fe276999 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/accessors.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y`. +* +* @private +* @param {PositiveInteger} N - number of indexed elements +* @param {Object} x - input array object +* @param {Collection} x.data - input array data +* @param {Array} x.accessors - array element accessors +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Object} y - output array object +* @param {Collection} y.data - output array data +* @param {Array} y.accessors - array element accessors +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Object} output array object +* +* @example +* var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +* var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +* +* var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; +* +* gxdy( x.length, arraylike2object( toAccessorArray( x ) ), 1, 0, arraylike2object( toAccessorArray( y ) ), 1, 0 ); +* // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function gxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xbuf; + var ybuf; + var xget; + var yset; + var yget; + var ix; + var iy; + var i; + + // Cache references to array data: + xbuf = x.data; + ybuf = y.data; + + // Cache references to element accessors: + xget = x.accessors[ 0 ]; + yget = y.accessors[ 0 ]; + yset = y.accessors[ 1 ]; + + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + yset( ybuf, iy, xget( xbuf, ix ) / yget( ybuf, iy ) ); + ix += strideX; + iy += strideY; + } + return y; +} + + +// EXPORTS // + +module.exports = gxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/index.js new file mode 100644 index 000000000000..218b600f4534 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/index.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Divide elements of a strided array `x` by the corresponding elements of a strided array `y` and assign the results to `y`. +* +* @module @stdlib/blas/ext/base/gxdy +* +* @example +* var gxdy = require( '@stdlib/blas/ext/base/gxdy' ); +* +* var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; +* +* gxdy( x.length, x, 1, y, 1 ); +* // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +* +* @example +* var gxdy = require( '@stdlib/blas/ext/base/gxdy' ); +* +* var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; +* +* gxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( main, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/main.js new file mode 100644 index 000000000000..b5174100cf65 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {NumericArray} x - input array +* @param {integer} strideX - `x` stride length +* @param {NumericArray} y - output array +* @param {integer} strideY - `y` stride length +* @returns {NumericArray} output array +* +* @example +* var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; +* +* gxdy( x.length, x, 1, y, 1 ); +* // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function gxdy( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/ndarray.js new file mode 100644 index 000000000000..bdbeea7a3652 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/lib/ndarray.js @@ -0,0 +1,110 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var arraylike2object = require( '@stdlib/array/base/arraylike2object' ); +var accessors = require( './accessors.js' ); + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Divides elements of a strided array `x` by the corresponding elements of a strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {NumericArray} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {NumericArray} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {NumericArray} output array +* +* @example +* var x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; +* var y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; +* +* gxdy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function gxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var ix; + var iy; + var ox; + var oy; + var m; + var i; + + if ( N <= 0 ) { + return y; + } + ox = arraylike2object( x ); + oy = arraylike2object( y ); + if ( ox.accessorProtocol || oy.accessorProtocol ) { + accessors( N, ox, strideX, offsetX, oy, strideY, offsetY ); + return y; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideY === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + y[ iy ] = x[ ix ] / y[ iy ]; + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return y; + } + for ( i = m; i < N; i += M ) { + y[ iy ] = x[ ix ] / y[ iy ]; + y[ iy+1 ] = x[ ix+1 ] / y[ iy+1 ]; + y[ iy+2 ] = x[ ix+2 ] / y[ iy+2 ]; + y[ iy+3 ] = x[ ix+3 ] / y[ iy+3 ]; + y[ iy+4 ] = x[ ix+4 ] / y[ iy+4 ]; + ix += M; + iy += M; + } + return y; + } + for ( i = 0; i < N; i++ ) { + y[ iy ] = x[ ix ] / y[ iy ]; + ix += strideX; + iy += strideY; + } + return y; +} + + +// EXPORTS // + +module.exports = gxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/gxdy/package.json new file mode 100644 index 000000000000..5b4d4f258e9b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/ext/base/gxdy", + "version": "0.0.0", + "description": "Divide elements of a strided array `x` by the corresponding elements of a strided array `y` and assign the results to `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "linear", + "algebra", + "subroutines", + "divide", + "division", + "quotient", + "strided", + "array", + "ndarray", + "vector", + "xdy", + "gxdy" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.js new file mode 100644 index 000000000000..2eb639d8c6c5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var gxdy = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof gxdy.ndarray, 'function', 'method is a function' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.main.js new file mode 100644 index 000000000000..20aeb7cc8c20 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.main.js @@ -0,0 +1,352 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gxdy = require( './../lib/main.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( gxdy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + expected = [ + 2.0, // 4.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]; + + gxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = [ 10.0, 24.0 ]; + y = [ 5.0, 6.0 ]; + expected = [ 2.0, 4.0 ]; + + gxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y` (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + expected = [ + 2.0, // 4.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]; + + gxdy( x.length, toAccessorArray( x ), 1, toAccessorArray( y ), 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = [ 10.0, 24.0 ]; + y = [ 5.0, 6.0 ]; + expected = [ 2.0, 4.0 ]; + + gxdy( x.length, toAccessorArray( x ), 1, toAccessorArray( y ), 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + y = [ 5.0, 6.0, 7.0, 8.0, 9.0 ]; + out = gxdy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + expected = [ 4.0, 5.0, 6.0 ]; + + gxdy( 0, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + gxdy( -4, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 2 + ]; + y = [ 2.0, 3.0, 4.0 ]; + expected = [ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, x, 2, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 2 + ]; + y = [ 2.0, 3.0, 4.0 ]; + expected = [ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, toAccessorArray( x ), 2, toAccessorArray( y ), 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = [ 6.0, 12.0, 20.0 ]; + y = [ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]; + expected = [ + 3.0, // 6.0 / 2.0 + 30.0, + 4.0, // 12.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, x, 1, y, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ 6.0, 12.0, 20.0 ]; + y = [ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]; + expected = [ + 3.0, // 6.0 / 2.0 + 30.0, + 4.0, // 12.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, toAccessorArray( x ), 1, toAccessorArray( y ), 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 0 + ]); + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + gxdy( 3, x, -2, y, -1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ + 6.0, // 2 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 0 + ]; + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + gxdy( 3, toAccessorArray( x ), -2, toAccessorArray( y ), -1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Float64Array([ + 10.0, + 6.0, // 0 + 12.0, // 1 + 20.0, // 2 + 4.0 + ]); + y0 = new Float64Array([ + 10.0, + 10.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + + x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Float64Array([ + 10.0, + 10.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + gxdy( 3, x1, 1, y1, 1 ); + t.deepEqual( y0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float64Array( 100 ); + y = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + gxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + y = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + gxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.ndarray.js new file mode 100644 index 000000000000..afd3bb41bc06 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/gxdy/test/test.ndarray.js @@ -0,0 +1,447 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' ); +var gxdy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( gxdy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + expected = [ + 2.0, // 4.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]; + + gxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = [ 10.0, 24.0 ]; + y = [ 5.0, 6.0 ]; + expected = [ 2.0, 4.0 ]; + + gxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y` (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ 4.0, 6.0, 12.0, 20.0, 30.0 ]; + y = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + expected = [ + 2.0, // 4.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]; + + gxdy( x.length, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = [ 10.0, 24.0 ]; + y = [ 5.0, 6.0 ]; + expected = [ 2.0, 4.0 ]; + + gxdy( x.length, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ]; + y = [ 5.0, 6.0, 7.0, 8.0, 9.0 ]; + out = gxdy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = [ 1.0, 2.0, 3.0 ]; + y = [ 4.0, 5.0, 6.0 ]; + expected = [ 4.0, 5.0, 6.0 ]; + + gxdy( 0, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + gxdy( -4, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 2 + ]; + y = [ 2.0, 3.0, 4.0 ]; + expected = [ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, x, 2, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ + 6.0, // 0 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 2 + ]; + y = [ 2.0, 3.0, 4.0 ]; + expected = [ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, toAccessorArray( x ), 2, 0, toAccessorArray( y ), 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = [ 6.0, 12.0, 20.0 ]; + y = [ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]; + expected = [ + 3.0, // 6.0 / 2.0 + 30.0, + 4.0, // 12.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, x, 1, 0, y, 2, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ 6.0, 12.0, 20.0 ]; + y = [ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]; + expected = [ + 3.0, // 6.0 / 2.0 + 30.0, + 4.0, // 12.0 / 3.0 + 10.0, + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 2, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Float64Array([ + 6.0, // 2 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 0 + ]); + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + gxdy( 3, x, -2, x.length-1, y, -1, y.length-1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ + 6.0, // 2 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 0 + ]; + y = new Float64Array([ + 2.0, // 2 + 3.0, // 1 + 4.0 // 0 + ]); + expected = new Float64Array([ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + gxdy( 3, toAccessorArray( x ), -2, x.length-1, toAccessorArray( y ), -1, y.length-1 ); // eslint-disable-line max-len + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var x; + var y; + + x = [ + 0.0, + 6.0, // 0 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 2 + ]; + y = [ 2.0, 3.0, 4.0 ]; + expected = [ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, x, 2, 1, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ + 0.0, + 6.0, // 0 + 2.0, + 12.0, // 1 + 4.0, + 20.0 // 2 + ]; + y = [ 2.0, 3.0, 4.0 ]; + expected = [ + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, toAccessorArray( x ), 2, 1, toAccessorArray( y ), 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var expected; + var x; + var y; + + x = [ 6.0, 12.0, 20.0 ]; + y = [ + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]; + expected = [ + 0.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, x, 1, 0, y, 1, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset (accessors)', function test( t ) { + var expected; + var x; + var y; + + x = [ 6.0, 12.0, 20.0 ]; + y = [ + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]; + expected = [ + 0.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]; + + gxdy( 3, toAccessorArray( x ), 1, 0, toAccessorArray( y ), 1, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var x; + var y; + + x = [ + 0.0, + 6.0, // 0 + 0.0, + 12.0, // 1 + 0.0, + 20.0 // 2 + ]; + y = [ + 0.0, + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 0.0 + ]; + expected = [ + 0.0, + 0.0, + 3.0, // 6.0 / 2.0 + 4.0, // 12.0 / 3.0 + 5.0, // 20.0 / 4.0 + 0.0 + ]; + + gxdy( 3, x, 2, 1, y, 1, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float64Array( 100 ); + y = new Float64Array( 100 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + gxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float64Array( 240 ); + y = new Float64Array( 240 ); + expected = new Float64Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + gxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/lib/index.js index f4df6bd45877..79db4b549957 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/lib/index.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable max-lines */ + 'use strict'; /* @@ -126,6 +128,15 @@ setReadOnly( ns, 'clastIndexOfRow', require( '@stdlib/blas/ext/base/clast-index- */ setReadOnly( ns, 'coneTo', require( '@stdlib/blas/ext/base/cone-to' ) ); +/** +* @name creplicate +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/creplicate} +*/ +setReadOnly( ns, 'creplicate', require( '@stdlib/blas/ext/base/creplicate' ) ); + /** * @name csum * @memberof ns @@ -162,6 +173,15 @@ setReadOnly( ns, 'cunitspace', require( '@stdlib/blas/ext/base/cunitspace' ) ); */ setReadOnly( ns, 'cwapx', require( '@stdlib/blas/ext/base/cwapx' ) ); +/** +* @name cwax +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/cwax} +*/ +setReadOnly( ns, 'cwax', require( '@stdlib/blas/ext/base/cwax' ) ); + /** * @name cwhere * @memberof ns @@ -180,6 +200,15 @@ setReadOnly( ns, 'cwhere', require( '@stdlib/blas/ext/base/cwhere' ) ); */ setReadOnly( ns, 'cwxsa', require( '@stdlib/blas/ext/base/cwxsa' ) ); +/** +* @name cxmy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/cxmy} +*/ +setReadOnly( ns, 'cxmy', require( '@stdlib/blas/ext/base/cxmy' ) ); + /** * @name cxpy * @memberof ns @@ -450,6 +479,51 @@ setReadOnly( ns, 'dediff', require( '@stdlib/blas/ext/base/dediff' ) ); */ setReadOnly( ns, 'dfill', require( '@stdlib/blas/ext/base/dfill' ) ); +/** +* @name dfillEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dfill-equal} +*/ +setReadOnly( ns, 'dfillEqual', require( '@stdlib/blas/ext/base/dfill-equal' ) ); + +/** +* @name dfillNaN +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dfill-nan} +*/ +setReadOnly( ns, 'dfillNaN', require( '@stdlib/blas/ext/base/dfill-nan' ) ); + +/** +* @name dfillNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dfill-not-equal} +*/ +setReadOnly( ns, 'dfillNotEqual', require( '@stdlib/blas/ext/base/dfill-not-equal' ) ); + +/** +* @name dfirstIndexEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dfirst-index-equal} +*/ +setReadOnly( ns, 'dfirstIndexEqual', require( '@stdlib/blas/ext/base/dfirst-index-equal' ) ); + +/** +* @name dfirstIndexLessThan +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dfirst-index-less-than} +*/ +setReadOnly( ns, 'dfirstIndexLessThan', require( '@stdlib/blas/ext/base/dfirst-index-less-than' ) ); + /** * @name dindexOf * @memberof ns @@ -477,6 +551,15 @@ setReadOnly( ns, 'dindexOfColumn', require( '@stdlib/blas/ext/base/dindex-of-col */ setReadOnly( ns, 'dindexOfFalsy', require( '@stdlib/blas/ext/base/dindex-of-falsy' ) ); +/** +* @name dindexOfNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dindex-of-not-equal} +*/ +setReadOnly( ns, 'dindexOfNotEqual', require( '@stdlib/blas/ext/base/dindex-of-not-equal' ) ); + /** * @name dindexOfRow * @memberof ns @@ -720,6 +803,15 @@ setReadOnly( ns, 'doneTo', require( '@stdlib/blas/ext/base/done-to' ) ); */ setReadOnly( ns, 'dones', require( '@stdlib/blas/ext/base/dones' ) ); +/** +* @name dreplicate +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dreplicate} +*/ +setReadOnly( ns, 'dreplicate', require( '@stdlib/blas/ext/base/dreplicate' ) ); + /** * @name drev * @memberof ns @@ -990,6 +1082,15 @@ setReadOnly( ns, 'dvander', require( '@stdlib/blas/ext/base/dvander' ) ); */ setReadOnly( ns, 'dwapx', require( '@stdlib/blas/ext/base/dwapx' ) ); +/** +* @name dwax +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dwax} +*/ +setReadOnly( ns, 'dwax', require( '@stdlib/blas/ext/base/dwax' ) ); + /** * @name dwhere * @memberof ns @@ -1008,6 +1109,15 @@ setReadOnly( ns, 'dwhere', require( '@stdlib/blas/ext/base/dwhere' ) ); */ setReadOnly( ns, 'dwxsa', require( '@stdlib/blas/ext/base/dwxsa' ) ); +/** +* @name dxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/dxdy} +*/ +setReadOnly( ns, 'dxdy', require( '@stdlib/blas/ext/base/dxdy' ) ); + /** * @name dxmy * @memberof ns @@ -1323,6 +1433,42 @@ setReadOnly( ns, 'gfill', require( '@stdlib/blas/ext/base/gfill' ) ); */ setReadOnly( ns, 'gfillBy', require( '@stdlib/blas/ext/base/gfill-by' ) ); +/** +* @name gfillEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfill-equal} +*/ +setReadOnly( ns, 'gfillEqual', require( '@stdlib/blas/ext/base/gfill-equal' ) ); + +/** +* @name gfillLessThan +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfill-less-than} +*/ +setReadOnly( ns, 'gfillLessThan', require( '@stdlib/blas/ext/base/gfill-less-than' ) ); + +/** +* @name gfillNaN +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfill-nan} +*/ +setReadOnly( ns, 'gfillNaN', require( '@stdlib/blas/ext/base/gfill-nan' ) ); + +/** +* @name gfillNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfill-not-equal} +*/ +setReadOnly( ns, 'gfillNotEqual', require( '@stdlib/blas/ext/base/gfill-not-equal' ) ); + /** * @name gfindIndex * @memberof ns @@ -1341,6 +1487,42 @@ setReadOnly( ns, 'gfindIndex', require( '@stdlib/blas/ext/base/gfind-index' ) ); */ setReadOnly( ns, 'gfindLastIndex', require( '@stdlib/blas/ext/base/gfind-last-index' ) ); +/** +* @name gfirstIndexEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfirst-index-equal} +*/ +setReadOnly( ns, 'gfirstIndexEqual', require( '@stdlib/blas/ext/base/gfirst-index-equal' ) ); + +/** +* @name gfirstIndexGreaterThan +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfirst-index-greater-than} +*/ +setReadOnly( ns, 'gfirstIndexGreaterThan', require( '@stdlib/blas/ext/base/gfirst-index-greater-than' ) ); + +/** +* @name gfirstIndexLessThan +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfirst-index-less-than} +*/ +setReadOnly( ns, 'gfirstIndexLessThan', require( '@stdlib/blas/ext/base/gfirst-index-less-than' ) ); + +/** +* @name gfirstIndexNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gfirst-index-not-equal} +*/ +setReadOnly( ns, 'gfirstIndexNotEqual', require( '@stdlib/blas/ext/base/gfirst-index-not-equal' ) ); + /** * @name gindexOf * @memberof ns @@ -1368,6 +1550,15 @@ setReadOnly( ns, 'gindexOfColumn', require( '@stdlib/blas/ext/base/gindex-of-col */ setReadOnly( ns, 'gindexOfFalsy', require( '@stdlib/blas/ext/base/gindex-of-falsy' ) ); +/** +* @name gindexOfNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gindex-of-not-equal} +*/ +setReadOnly( ns, 'gindexOfNotEqual', require( '@stdlib/blas/ext/base/gindex-of-not-equal' ) ); + /** * @name gindexOfRow * @memberof ns @@ -1377,6 +1568,15 @@ setReadOnly( ns, 'gindexOfFalsy', require( '@stdlib/blas/ext/base/gindex-of-fals */ setReadOnly( ns, 'gindexOfRow', require( '@stdlib/blas/ext/base/gindex-of-row' ) ); +/** +* @name gindexOfSameValue +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gindex-of-same-value} +*/ +setReadOnly( ns, 'gindexOfSameValue', require( '@stdlib/blas/ext/base/gindex-of-same-value' ) ); + /** * @name gindexOfTruthy * @memberof ns @@ -1404,6 +1604,15 @@ setReadOnly( ns, 'gjoin', require( '@stdlib/blas/ext/base/gjoin' ) ); */ setReadOnly( ns, 'gjoinBetween', require( '@stdlib/blas/ext/base/gjoin-between' ) ); +/** +* @name glastIndexEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/glast-index-equal} +*/ +setReadOnly( ns, 'glastIndexEqual', require( '@stdlib/blas/ext/base/glast-index-equal' ) ); + /** * @name glastIndexOf * @memberof ns @@ -1791,6 +2000,15 @@ setReadOnly( ns, 'gwxsa', require( '@stdlib/blas/ext/base/gwxsa' ) ); */ setReadOnly( ns, 'gwxsy', require( '@stdlib/blas/ext/base/gwxsy' ) ); +/** +* @name gxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/gxdy} +*/ +setReadOnly( ns, 'gxdy', require( '@stdlib/blas/ext/base/gxdy' ) ); + /** * @name gxmy * @memberof ns @@ -2133,6 +2351,51 @@ setReadOnly( ns, 'sediff', require( '@stdlib/blas/ext/base/sediff' ) ); */ setReadOnly( ns, 'sfill', require( '@stdlib/blas/ext/base/sfill' ) ); +/** +* @name sfillEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/sfill-equal} +*/ +setReadOnly( ns, 'sfillEqual', require( '@stdlib/blas/ext/base/sfill-equal' ) ); + +/** +* @name sfillNaN +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/sfill-nan} +*/ +setReadOnly( ns, 'sfillNaN', require( '@stdlib/blas/ext/base/sfill-nan' ) ); + +/** +* @name sfillNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/sfill-not-equal} +*/ +setReadOnly( ns, 'sfillNotEqual', require( '@stdlib/blas/ext/base/sfill-not-equal' ) ); + +/** +* @name sfirstIndexEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/sfirst-index-equal} +*/ +setReadOnly( ns, 'sfirstIndexEqual', require( '@stdlib/blas/ext/base/sfirst-index-equal' ) ); + +/** +* @name sfirstIndexLessThan +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/sfirst-index-less-than} +*/ +setReadOnly( ns, 'sfirstIndexLessThan', require( '@stdlib/blas/ext/base/sfirst-index-less-than' ) ); + /** * @name sindexOf * @memberof ns @@ -2331,6 +2594,15 @@ setReadOnly( ns, 'soneTo', require( '@stdlib/blas/ext/base/sone-to' ) ); */ setReadOnly( ns, 'sones', require( '@stdlib/blas/ext/base/sones' ) ); +/** +* @name sreplicate +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/sreplicate} +*/ +setReadOnly( ns, 'sreplicate', require( '@stdlib/blas/ext/base/sreplicate' ) ); + /** * @name srev * @memberof ns @@ -2484,6 +2756,15 @@ setReadOnly( ns, 'svander', require( '@stdlib/blas/ext/base/svander' ) ); */ setReadOnly( ns, 'swapx', require( '@stdlib/blas/ext/base/swapx' ) ); +/** +* @name swax +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/swax} +*/ +setReadOnly( ns, 'swax', require( '@stdlib/blas/ext/base/swax' ) ); + /** * @name swhere * @memberof ns @@ -2502,6 +2783,15 @@ setReadOnly( ns, 'swhere', require( '@stdlib/blas/ext/base/swhere' ) ); */ setReadOnly( ns, 'swxsa', require( '@stdlib/blas/ext/base/swxsa' ) ); +/** +* @name sxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/sxdy} +*/ +setReadOnly( ns, 'sxdy', require( '@stdlib/blas/ext/base/sxdy' ) ); + /** * @name sxmy * @memberof ns @@ -2637,6 +2927,15 @@ setReadOnly( ns, 'zindexOfColumn', require( '@stdlib/blas/ext/base/zindex-of-col */ setReadOnly( ns, 'zindexOfRow', require( '@stdlib/blas/ext/base/zindex-of-row' ) ); +/** +* @name zindexOfTruthy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/zindex-of-truthy} +*/ +setReadOnly( ns, 'zindexOfTruthy', require( '@stdlib/blas/ext/base/zindex-of-truthy' ) ); + /** * @name zlastIndexOfRow * @memberof ns @@ -2664,6 +2963,15 @@ setReadOnly( ns, 'znancount', require( '@stdlib/blas/ext/base/znancount' ) ); */ setReadOnly( ns, 'zoneTo', require( '@stdlib/blas/ext/base/zone-to' ) ); +/** +* @name zreplicate +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/zreplicate} +*/ +setReadOnly( ns, 'zreplicate', require( '@stdlib/blas/ext/base/zreplicate' ) ); + /** * @name zsum * @memberof ns @@ -2700,6 +3008,15 @@ setReadOnly( ns, 'zunitspace', require( '@stdlib/blas/ext/base/zunitspace' ) ); */ setReadOnly( ns, 'zwapx', require( '@stdlib/blas/ext/base/zwapx' ) ); +/** +* @name zwax +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/zwax} +*/ +setReadOnly( ns, 'zwax', require( '@stdlib/blas/ext/base/zwax' ) ); + /** * @name zwhere * @memberof ns @@ -2718,6 +3035,24 @@ setReadOnly( ns, 'zwhere', require( '@stdlib/blas/ext/base/zwhere' ) ); */ setReadOnly( ns, 'zwxsa', require( '@stdlib/blas/ext/base/zwxsa' ) ); +/** +* @name zxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/zxdy} +*/ +setReadOnly( ns, 'zxdy', require( '@stdlib/blas/ext/base/zxdy' ) ); + +/** +* @name zxmy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/zxmy} +*/ +setReadOnly( ns, 'zxmy', require( '@stdlib/blas/ext/base/zxmy' ) ); + /** * @name zxpy * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md index bf14e6d39a2b..80e1b13e4500 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md @@ -52,10 +52,12 @@ The namespace exposes the following APIs: - [`csum( arrays )`][@stdlib/blas/ext/base/ndarray/csum]: compute the sum of all elements in a one-dimensional single-precision complex floating-point ndarray. - [`csumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/csumkbn]: compute the sum of all elements in a one-dimensional single-precision complex floating-point ndarray using an improved Kahan–Babuška algorithm. - [`cunitspace( arrays )`][@stdlib/blas/ext/base/ndarray/cunitspace]: fill a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from a specified value. +- [`cxmy( arrays )`][@stdlib/blas/ext/base/ndarray/cxmy]: multiply elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assign the results to the second ndarray. - [`cxpy( arrays )`][@stdlib/blas/ext/base/ndarray/cxpy]: add elements of a one-dimensional single-precision complex floating-point ndarray to the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assign the results to the second ndarray. - [`cxsa( arrays )`][@stdlib/blas/ext/base/ndarray/cxsa]: subtract a scalar constant from each element in a one-dimensional single-precision complex floating-point ndarray. - [`cxsy( arrays )`][@stdlib/blas/ext/base/ndarray/cxsy]: subtract the elements of an output one-dimensional single-precision complex floating-point ndarray from the corresponding elements in an input one-dimensional single-precision complex floating-point ndarray and assign the results to the output ndarray. - [`czeroTo( arrays )`][@stdlib/blas/ext/base/ndarray/czero-to]: fill a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from zero. +- [`dany( arrays )`][@stdlib/blas/ext/base/ndarray/dany]: test whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy. - [`daxpb( arrays )`][@stdlib/blas/ext/base/ndarray/daxpb]: multiply each element in a one-dimensional double-precision floating-point ndarray by a scalar constant and add a scalar constant to each result. - [`daxpby( arrays )`][@stdlib/blas/ext/base/ndarray/daxpby]: multiply a one-dimensional double-precision floating-point ndarray by a scalar constant and add the result to a second one-dimensional double-precision floating-point ndarray multiplied by a scalar constant. - [`dcircshift( arrays )`][@stdlib/blas/ext/base/ndarray/dcircshift]: circularly shift the elements of a one-dimensional double-precision floating-point ndarray by a specified number of positions. @@ -65,6 +67,8 @@ The namespace exposes the following APIs: - [`dcusumors( arrays )`][@stdlib/blas/ext/base/ndarray/dcusumors]: compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation. - [`dcusumpw( arrays )`][@stdlib/blas/ext/base/ndarray/dcusumpw]: compute the cumulative sum of a one-dimensional double-precision floating-point ndarray using pairwise summation. - [`ddiff( arrays )`][@stdlib/blas/ext/base/ndarray/ddiff]: calculate the k-th discrete forward difference of a one-dimensional double-precision floating-point ndarray. +- [`dfillEqual( arrays )`][@stdlib/blas/ext/base/ndarray/dfill-equal]: replace elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant. +- [`dfillNotEqual( arrays )`][@stdlib/blas/ext/base/ndarray/dfill-not-equal]: replace elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. - [`dindexOfFalsy( arrays )`][@stdlib/blas/ext/base/ndarray/dindex-of-falsy]: return the index of the first falsy element in a one-dimensional double-precision floating-point ndarray. - [`dindexOf( arrays )`][@stdlib/blas/ext/base/ndarray/dindex-of]: return the first index of a search element in a one-dimensional double-precision floating-point ndarray. - [`dlastIndexOf( arrays )`][@stdlib/blas/ext/base/ndarray/dlast-index-of]: return the last index of a search element in a one-dimensional double-precision floating-point ndarray. @@ -82,13 +86,16 @@ The namespace exposes the following APIs: - [`dsum( arrays )`][@stdlib/blas/ext/base/ndarray/dsum]: compute the sum of all elements in a one-dimensional double-precision floating-point ndarray. - [`dsumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/dsumkbn]: compute the sum of all elements in a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm. - [`dsumkbn2( arrays )`][@stdlib/blas/ext/base/ndarray/dsumkbn2]: compute the sum of all elements in a one-dimensional double-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm. -- [`dsumors( arrays )`][@stdlib/blas/ext/base/ndarray/dsumors]: compute the sum of a one-dimensional double-precision floating-point ndarray using ordinary recursive summation. -- [`dsumpw( arrays )`][@stdlib/blas/ext/base/ndarray/dsumpw]: compute the sum of a one-dimensional double-precision floating-point ndarray using pairwise summation. +- [`dsumors( arrays )`][@stdlib/blas/ext/base/ndarray/dsumors]: compute the sum of all elements in a one-dimensional double-precision floating-point ndarray using ordinary recursive summation. +- [`dsumpw( arrays )`][@stdlib/blas/ext/base/ndarray/dsumpw]: compute the sum of all elements in a one-dimensional double-precision floating-point ndarray using pairwise summation. - [`dunitspace( arrays )`][@stdlib/blas/ext/base/ndarray/dunitspace]: fill a one-dimensional double-precision floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from a specified value. +- [`dxdy( arrays )`][@stdlib/blas/ext/base/ndarray/dxdy]: divide elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray. +- [`dxmy( arrays )`][@stdlib/blas/ext/base/ndarray/dxmy]: multiply elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray. - [`dxpy( arrays )`][@stdlib/blas/ext/base/ndarray/dxpy]: add elements of a one-dimensional double-precision floating-point ndarray to the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray. - [`dxsa( arrays )`][@stdlib/blas/ext/base/ndarray/dxsa]: subtract a scalar constant from each element in a one-dimensional double-precision floating-point ndarray. - [`dxsy( arrays )`][@stdlib/blas/ext/base/ndarray/dxsy]: subtract the elements of an output one-dimensional double-precision floating-point ndarray from the corresponding elements in an input one-dimensional double-precision floating-point ndarray and assign the results to the output ndarray. - [`dzeroTo( arrays )`][@stdlib/blas/ext/base/ndarray/dzero-to]: fill a one-dimensional double-precision floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from zero. +- [`gany( arrays )`][@stdlib/blas/ext/base/ndarray/gany]: test whether at least one element in a one-dimensional ndarray is truthy. - [`gaxpb( arrays )`][@stdlib/blas/ext/base/ndarray/gaxpb]: multiply each element in a one-dimensional ndarray by a scalar constant and add a scalar constant to each result. - [`gaxpby( arrays )`][@stdlib/blas/ext/base/ndarray/gaxpby]: multiply a one-dimensional ndarray by a scalar constant and add the result to a second one-dimensional ndarray multiplied by a scalar constant. - [`gcircshift( arrays )`][@stdlib/blas/ext/base/ndarray/gcircshift]: circularly shift the elements of a one-dimensional ndarray by a specified number of positions. @@ -97,9 +104,11 @@ The namespace exposes the following APIs: - [`gcusumkbn2( arrays )`][@stdlib/blas/ext/base/ndarray/gcusumkbn2]: compute the cumulative sum of a one-dimensional ndarray using a second-order iterative Kahan–Babuška algorithm. - [`gcusumors( arrays )`][@stdlib/blas/ext/base/ndarray/gcusumors]: compute the cumulative sum of a one-dimensional ndarray using ordinary recursive summation. - [`gcusumpw( arrays )`][@stdlib/blas/ext/base/ndarray/gcusumpw]: compute the cumulative sum of a one-dimensional ndarray using pairwise summation. +- [`gfillNotEqual( arrays )`][@stdlib/blas/ext/base/ndarray/gfill-not-equal]: replace elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant. - [`gfindIndex( arrays, clbk[, thisArg] )`][@stdlib/blas/ext/base/ndarray/gfind-index]: return the index of the first element in a one-dimensional ndarray which passes a test implemented by a predicate function. - [`gfindLastIndex( arrays, clbk[, thisArg] )`][@stdlib/blas/ext/base/ndarray/gfind-last-index]: return the index of the last element in a one-dimensional ndarray which passes a test implemented by a predicate function. - [`gindexOfFalsy( arrays )`][@stdlib/blas/ext/base/ndarray/gindex-of-falsy]: return the index of the first falsy element in a one-dimensional ndarray. +- [`gindexOfNotEqual( arrays )`][@stdlib/blas/ext/base/ndarray/gindex-of-not-equal]: return the first index of an element in a one-dimensional ndarray which is not equal to a specified search element. - [`gindexOfTruthy( arrays )`][@stdlib/blas/ext/base/ndarray/gindex-of-truthy]: return the index of the first truthy element in a one-dimensional ndarray. - [`gindexOf( arrays )`][@stdlib/blas/ext/base/ndarray/gindex-of]: return the first index of a search element in a one-dimensional ndarray. - [`gjoinBetween( arrays )`][@stdlib/blas/ext/base/ndarray/gjoin-between]: return a string by joining one-dimensional ndarray elements using a specified separator for each pair of consecutive elements. @@ -120,10 +129,13 @@ The namespace exposes the following APIs: - [`gsumors( arrays )`][@stdlib/blas/ext/base/ndarray/gsumors]: compute the sum of all elements in a one-dimensional ndarray using ordinary recursive summation. - [`gsumpw( arrays )`][@stdlib/blas/ext/base/ndarray/gsumpw]: compute the sum of all elements in a one-dimensional ndarray using pairwise summation. - [`gunitspace( arrays )`][@stdlib/blas/ext/base/ndarray/gunitspace]: fill a one-dimensional ndarray with linearly spaced numeric elements which increment by `1` starting from a specified value. +- [`gxdy( arrays )`][@stdlib/blas/ext/base/ndarray/gxdy]: divide elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray. +- [`gxmy( arrays )`][@stdlib/blas/ext/base/ndarray/gxmy]: multiply elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray. - [`gxpy( arrays )`][@stdlib/blas/ext/base/ndarray/gxpy]: add elements of a one-dimensional ndarray to the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray. - [`gxsa( arrays )`][@stdlib/blas/ext/base/ndarray/gxsa]: subtract a scalar constant from each element in a one-dimensional ndarray. - [`gxsy( arrays )`][@stdlib/blas/ext/base/ndarray/gxsy]: subtract the elements of an output one-dimensional ndarray from the corresponding elements in an input one-dimensional ndarray and assign the results to the output ndarray. - [`gzeroTo( arrays )`][@stdlib/blas/ext/base/ndarray/gzero-to]: fill a one-dimensional ndarray with linearly spaced numeric elements which increment by `1` starting from zero. +- [`sany( arrays )`][@stdlib/blas/ext/base/ndarray/sany]: test whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy. - [`saxpb( arrays )`][@stdlib/blas/ext/base/ndarray/saxpb]: multiply each element in a one-dimensional single-precision floating-point ndarray by a scalar constant and add a scalar constant to each result. - [`saxpby( arrays )`][@stdlib/blas/ext/base/ndarray/saxpby]: multiply a one-dimensional single-precision floating-point ndarray by a scalar constant and add the result to a second one-dimensional single-precision floating-point ndarray multiplied by a scalar constant. - [`scircshift( arrays )`][@stdlib/blas/ext/base/ndarray/scircshift]: circularly shift the elements of a one-dimensional single-precision floating-point ndarray by a specified number of positions. @@ -132,6 +144,7 @@ The namespace exposes the following APIs: - [`scusumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/scusumkbn]: compute the cumulative sum of a one-dimensional single-precision floating-point ndarray using an improved Kahan–Babuška algorithm. - [`scusumkbn2( arrays )`][@stdlib/blas/ext/base/ndarray/scusumkbn2]: compute the cumulative sum of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm. - [`scusumors( arrays )`][@stdlib/blas/ext/base/ndarray/scusumors]: compute the cumulative sum of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation. +- [`sfillNotEqual( arrays )`][@stdlib/blas/ext/base/ndarray/sfill-not-equal]: replace elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. - [`sindexOf( arrays )`][@stdlib/blas/ext/base/ndarray/sindex-of]: return the first index of a search element in a one-dimensional single-precision floating-point ndarray. - [`slastIndexOf( arrays )`][@stdlib/blas/ext/base/ndarray/slast-index-of]: return the last index of a search element in a one-dimensional single-precision floating-point ndarray. - [`slinspace( arrays )`][@stdlib/blas/ext/base/ndarray/slinspace]: fill a one-dimensional single-precision floating-point ndarray with linearly spaced values over a specified interval. @@ -146,9 +159,11 @@ The namespace exposes the following APIs: - [`ssum( arrays )`][@stdlib/blas/ext/base/ndarray/ssum]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray. - [`ssumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/ssumkbn]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using an improved Kahan–Babuška algorithm. - [`ssumkbn2( arrays )`][@stdlib/blas/ext/base/ndarray/ssumkbn2]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm. -- [`ssumors( arrays )`][@stdlib/blas/ext/base/ndarray/ssumors]: compute the sum of a one-dimensional single-precision floating-point ndarray using ordinary recursive summation. +- [`ssumors( arrays )`][@stdlib/blas/ext/base/ndarray/ssumors]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using ordinary recursive summation. - [`ssumpw( arrays )`][@stdlib/blas/ext/base/ndarray/ssumpw]: compute the sum of all elements in a one-dimensional single-precision floating-point ndarray using pairwise summation. - [`sunitspace( arrays )`][@stdlib/blas/ext/base/ndarray/sunitspace]: fill a one-dimensional single-precision floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from a specified value. +- [`sxdy( arrays )`][@stdlib/blas/ext/base/ndarray/sxdy]: divide elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray. +- [`sxmy( arrays )`][@stdlib/blas/ext/base/ndarray/sxmy]: multiply elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray. - [`sxpy( arrays )`][@stdlib/blas/ext/base/ndarray/sxpy]: add elements of a one-dimensional single-precision floating-point ndarray to the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray. - [`sxsa( arrays )`][@stdlib/blas/ext/base/ndarray/sxsa]: subtract a scalar constant from each element in a one-dimensional single-precision floating-point ndarray. - [`sxsy( arrays )`][@stdlib/blas/ext/base/ndarray/sxsy]: subtract the elements of an output one-dimensional single-precision floating-point ndarray from the corresponding elements in an input one-dimensional single-precision floating-point ndarray and assign the results to the output ndarray. @@ -160,6 +175,8 @@ The namespace exposes the following APIs: - [`zsum( arrays )`][@stdlib/blas/ext/base/ndarray/zsum]: compute the sum of all elements in a one-dimensional double-precision complex floating-point ndarray. - [`zsumkbn( arrays )`][@stdlib/blas/ext/base/ndarray/zsumkbn]: compute the sum of all elements in a one-dimensional double-precision complex floating-point ndarray using an improved Kahan–Babuška algorithm. - [`zunitspace( arrays )`][@stdlib/blas/ext/base/ndarray/zunitspace]: fill a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from a specified value. +- [`zxdy( arrays )`][@stdlib/blas/ext/base/ndarray/zxdy]: divide elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray. +- [`zxmy( arrays )`][@stdlib/blas/ext/base/ndarray/zxmy]: multiply elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray. - [`zxpy( arrays )`][@stdlib/blas/ext/base/ndarray/zxpy]: add elements of a one-dimensional double-precision complex floating-point ndarray to the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray. - [`zxsa( arrays )`][@stdlib/blas/ext/base/ndarray/zxsa]: subtract a scalar constant from each element in a one-dimensional double-precision complex floating-point ndarray. - [`zxsy( arrays )`][@stdlib/blas/ext/base/ndarray/zxsy]: subtract the elements of an output one-dimensional double-precision complex floating-point ndarray from the corresponding elements in an input one-dimensional double-precision complex floating-point ndarray and assign the results to the output ndarray. @@ -220,6 +237,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/cunitspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/cunitspace +[@stdlib/blas/ext/base/ndarray/cxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/cxmy + [@stdlib/blas/ext/base/ndarray/cxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/cxpy [@stdlib/blas/ext/base/ndarray/cxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/cxsa @@ -228,6 +247,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/czero-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/czero-to +[@stdlib/blas/ext/base/ndarray/dany]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dany + [@stdlib/blas/ext/base/ndarray/daxpb]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/daxpb [@stdlib/blas/ext/base/ndarray/daxpby]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/daxpby @@ -246,6 +267,10 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/ddiff]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/ddiff +[@stdlib/blas/ext/base/ndarray/dfill-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dfill-equal + +[@stdlib/blas/ext/base/ndarray/dfill-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dfill-not-equal + [@stdlib/blas/ext/base/ndarray/dindex-of-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dindex-of-falsy [@stdlib/blas/ext/base/ndarray/dindex-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dindex-of @@ -286,6 +311,10 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/dunitspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dunitspace +[@stdlib/blas/ext/base/ndarray/dxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dxdy + +[@stdlib/blas/ext/base/ndarray/dxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dxmy + [@stdlib/blas/ext/base/ndarray/dxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dxpy [@stdlib/blas/ext/base/ndarray/dxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dxsa @@ -294,6 +323,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/dzero-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dzero-to +[@stdlib/blas/ext/base/ndarray/gany]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gany + [@stdlib/blas/ext/base/ndarray/gaxpb]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gaxpb [@stdlib/blas/ext/base/ndarray/gaxpby]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gaxpby @@ -310,12 +341,16 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/gcusumpw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gcusumpw +[@stdlib/blas/ext/base/ndarray/gfill-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gfill-not-equal + [@stdlib/blas/ext/base/ndarray/gfind-index]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gfind-index [@stdlib/blas/ext/base/ndarray/gfind-last-index]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gfind-last-index [@stdlib/blas/ext/base/ndarray/gindex-of-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gindex-of-falsy +[@stdlib/blas/ext/base/ndarray/gindex-of-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gindex-of-not-equal + [@stdlib/blas/ext/base/ndarray/gindex-of-truthy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gindex-of-truthy [@stdlib/blas/ext/base/ndarray/gindex-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gindex-of @@ -356,6 +391,10 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/gunitspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gunitspace +[@stdlib/blas/ext/base/ndarray/gxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gxdy + +[@stdlib/blas/ext/base/ndarray/gxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gxmy + [@stdlib/blas/ext/base/ndarray/gxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gxpy [@stdlib/blas/ext/base/ndarray/gxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gxsa @@ -364,6 +403,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/gzero-to]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gzero-to +[@stdlib/blas/ext/base/ndarray/sany]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sany + [@stdlib/blas/ext/base/ndarray/saxpb]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/saxpb [@stdlib/blas/ext/base/ndarray/saxpby]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/saxpby @@ -380,6 +421,8 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/scusumors]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/scusumors +[@stdlib/blas/ext/base/ndarray/sfill-not-equal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sfill-not-equal + [@stdlib/blas/ext/base/ndarray/sindex-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sindex-of [@stdlib/blas/ext/base/ndarray/slast-index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/slast-index-of @@ -414,6 +457,10 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/sunitspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sunitspace +[@stdlib/blas/ext/base/ndarray/sxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sxdy + +[@stdlib/blas/ext/base/ndarray/sxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sxmy + [@stdlib/blas/ext/base/ndarray/sxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sxpy [@stdlib/blas/ext/base/ndarray/sxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/sxsa @@ -436,6 +483,10 @@ console.log( objectKeys( ns ) ); [@stdlib/blas/ext/base/ndarray/zunitspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zunitspace +[@stdlib/blas/ext/base/ndarray/zxdy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zxdy + +[@stdlib/blas/ext/base/ndarray/zxmy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zxmy + [@stdlib/blas/ext/base/ndarray/zxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zxpy [@stdlib/blas/ext/base/ndarray/zxsa]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/zxsa diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cunitspace/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cunitspace/README.md index 4e3453922ec9..a41a785544f0 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cunitspace/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cunitspace/README.md @@ -40,8 +40,6 @@ var cunitspace = require( '@stdlib/blas/ext/base/ndarray/cunitspace' ); Fills a one-dimensional single-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from a specified value. - - ```javascript var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/README.md new file mode 100644 index 000000000000..ed5206d0b522 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/README.md @@ -0,0 +1,128 @@ + + +# cxmy + +> Multiply elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \odot \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var cxmy = require( '@stdlib/blas/ext/base/ndarray/cxmy' ); +``` + +#### cxmy( arrays ) + +Multiplies elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assigns the results to the second ndarray. + +```javascript +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); + +var x = new Complex64Vector( [ 1.0, 2.0, 3.0, -1.0, 0.0, 1.0 ] ); +var y = new Complex64Vector( [ 2.0, 1.0, -1.0, 3.0, 4.0, 0.0 ] ); + +cxmy( [ x, y ] ); +// y => [ [ 0.0, 5.0 ], [ 0.0, 10.0 ], [ 0.0, 4.0 ] ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var cxmy = require( '@stdlib/blas/ext/base/ndarray/cxmy' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = new Complex64Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( x ) ); + +var y = new Complex64Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( y ) ); + +cxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/benchmark/benchmark.js new file mode 100644 index 000000000000..44f5766b70b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/benchmark/benchmark.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cxmy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -100.0, 100.0, { + 'dtype': 'float32' + }); + ybuf = uniform( len*2, -100.0, 100.0, { + 'dtype': 'float32' + }); + x = new Complex64Vector( xbuf.buffer ); + y = new Complex64Vector( ybuf.buffer ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = cxmy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/repl.txt new file mode 100644 index 000000000000..3a82ba382f03 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}( arrays ) + Multiplies elements of a one-dimensional single-precision complex floating- + point ndarray by the corresponding elements of a second one-dimensional + single-precision complex floating-point ndarray and assigns the results to + the second ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var bufX = [ 1.0, 2.0, 3.0, -1.0, 0.0, 1.0 ]; + > var bufY = [ 2.0, 1.0, -1.0, 3.0, 4.0, 0.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/complex64}}( bufX ); + > var y = new {{alias:@stdlib/ndarray/vector/complex64}}( bufY ); + > {{alias}}( [ x, y ] ) + [ [ 0, 5 ], [ 0, 10 ], [ 0, 4 ] ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/types/index.d.ts new file mode 100644 index 000000000000..deb04b522769 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { complex64ndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +* +* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, -1.0, 0.0, 1.0 ] ); +* var y = new Complex64Vector( [ 2.0, 1.0, -1.0, 3.0, 4.0, 0.0 ] ); +* +* var out = cxmy( [ x, y ] ); +* // returns [ [ 0.0, 5.0 ], [ 0.0, 10.0 ], [ 0.0, 4.0 ] ] +*/ +declare function cxmy( arrays: [ complex64ndarray, complex64ndarray ] ): complex64ndarray; + + +// EXPORTS // + +export = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/types/test.ts new file mode 100644 index 000000000000..06db8e13af42 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import cxmy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'complex64' + }); + + cxmy( [ x, y ] ); // $ExpectType complex64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + cxmy( '10' ); // $ExpectError + cxmy( 5 ); // $ExpectError + cxmy( true ); // $ExpectError + cxmy( false ); // $ExpectError + cxmy( null ); // $ExpectError + cxmy( undefined ); // $ExpectError + cxmy( [] ); // $ExpectError + cxmy( {} ); // $ExpectError + cxmy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'complex64' + }); + + cxmy(); // $ExpectError + cxmy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/examples/index.js new file mode 100644 index 000000000000..4c27866fcbaa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var cxmy = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = new Complex64Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( x ) ); + +var y = new Complex64Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( y ) ); + +cxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/lib/index.js new file mode 100644 index 000000000000..f582a4f68fd1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/cxmy +* +* @example +* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +* var cxmy = require( '@stdlib/blas/ext/base/ndarray/cxmy' ); +* +* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, -1.0, 0.0, 1.0 ] ); +* var y = new Complex64Vector( [ 2.0, 1.0, -1.0, 3.0, 4.0, 0.0 ] ); +* +* var out = cxmy( [ x, y ] ); +* // returns [ [ 0.0, 5.0 ], [ 0.0, 10.0 ], [ 0.0, 4.0 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/lib/main.js new file mode 100644 index 000000000000..67eaa72a7b50 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/cxmy' ).ndarray; + + +// MAIN // + +/** +* Multiplies elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); +* +* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, -1.0, 0.0, 1.0 ] ); +* var y = new Complex64Vector( [ 2.0, 1.0, -1.0, 3.0, 4.0, 0.0 ] ); +* +* var out = cxmy( [ x, y ] ); +* // returns [ [ 0.0, 5.0 ], [ 0.0, 10.0 ], [ 0.0, 4.0 ] ] +*/ +function cxmy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = cxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/package.json new file mode 100644 index 000000000000..7fed957eeef4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/cxmy", + "version": "0.0.0", + "description": "Multiply elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "cxmy", + "xmy", + "multiply", + "multiplication", + "hadamard", + "strided", + "array", + "ndarray", + "complex64", + "complex", + "single", + "single-precision", + "float32" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/test/test.js new file mode 100644 index 000000000000..fba33a99ecac --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/cxmy/test/test.js @@ -0,0 +1,333 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex64Array = require( '@stdlib/assert/is-same-complex64array' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var cxmy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( cxmy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, -1.0, 0.0, 1.0 ] ); + ybuf = new Complex64Array( [ 2.0, 1.0, -1.0, 3.0, 4.0, 0.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + + actual = cxmy( [ x, y ] ); + expected = new Complex64Array([ + // (1.0+2.0i) * (2.0+1.0i) + 0.0, + 5.0, + // (3.0-1.0i) * (-1.0+3.0i) + 0.0, + 10.0, + // (0.0+1.0i) * (4.0+0.0i) + 0.0, + 4.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + xbuf = new Complex64Array( [ 1.0, 0.0, 2.0, 1.0 ] ); + ybuf = new Complex64Array( [ 3.0, -1.0, 4.0, 2.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + + actual = cxmy( [ x, y ] ); + expected = new Complex64Array([ + // (1.0+0.0i) * (3.0-1.0i) + 3.0, + -1.0, + // (2.0+1.0i) * (4.0+2.0i) + 6.0, + 8.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + -1.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 1.0 // 2 + ]); + ybuf = new Complex64Array([ + 2.0, // 0 + 1.0, // 0 + -1.0, // 1 + 3.0, // 1 + 4.0, // 2 + 0.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + y = vector( ybuf, 3, 1, 0 ); + + actual = cxmy( [ x, y ] ); + expected = new Complex64Array([ + // (1.0+2.0i) * (2.0+1.0i) + 0.0, + 5.0, + // (3.0-1.0i) * (-1.0+3.0i) + 0.0, + 10.0, + // (0.0+1.0i) * (4.0+0.0i) + 0.0, + 4.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex64Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + -1.0, // 1 + 0.0, // 2 + 1.0 // 2 + ]); + ybuf = new Complex64Array([ + 2.0, // 0 + 1.0, // 0 + 0.0, + 0.0, + -1.0, // 1 + 3.0, // 1 + 0.0, + 0.0, + 4.0, // 2 + 0.0 // 2 + ]); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 2, 0 ); + + actual = cxmy( [ x, y ] ); + expected = new Complex64Array([ + // (1.0+2.0i) * (2.0+1.0i) + 0.0, + 5.0, + 0.0, + 0.0, + // (3.0-1.0i) * (-1.0+3.0i) + 0.0, + 10.0, + 0.0, + 0.0, + // (0.0+1.0i) * (4.0+0.0i) + 0.0, + 4.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex64Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + -1.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + ybuf = new Complex64Array([ + 4.0, // 2 + 0.0, // 2 + 3.0, // 1 + -1.0, // 1 + 2.0, // 0 + 1.0 // 0 + ]); + x = vector( xbuf, 3, -2, 4 ); + y = vector( ybuf, 3, -1, 2 ); + + actual = cxmy( [ x, y ] ); + expected = new Complex64Array([ + // (1.0+2.0i) * (4.0+0.0i) + 4.0, + 8.0, + // (3.0-1.0i) * (3.0-1.0i) + 8.0, + -6.0, + // (5.0+6.0i) * (2.0+1.0i) + 4.0, + 17.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex64Array([ + 0.0, + 0.0, + 1.0, // 0 + 0.0, // 0 + 0.0, + 0.0, + 2.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 3.0, // 2 + 0.0 // 2 + ]); + ybuf = new Complex64Array([ + 0.0, + 0.0, + 2.0, // 0 + 0.0, // 0 + 3.0, // 1 + 0.0, // 1 + 4.0, // 2 + 0.0 // 2 + ]); + x = vector( xbuf, 3, 2, 1 ); + y = vector( ybuf, 3, 1, 1 ); + + actual = cxmy( [ x, y ] ); + + expected = new Complex64Array([ + 0.0, + 0.0, + // (1.0+0.0i) * (2.0+0.0i) + 2.0, + 0.0, + // (2.0+0.0i) * (3.0+0.0i) + 6.0, + 0.0, + // (3.0+0.0i) * (4.0+0.0i) + 12.0, + 0.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided empty ndarrays, the function returns the output ndarray unchanged', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex64Array( [] ); + ybuf = new Complex64Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + + actual = cxmy( [ x, y ] ); + expected = new Complex64Array( [] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex64Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/README.md new file mode 100644 index 000000000000..449886207062 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/README.md @@ -0,0 +1,109 @@ + + +# dany + +> Test whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dany = require( '@stdlib/blas/ext/base/ndarray/dany' ); +``` + +#### dany( arrays ) + +Tests whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + +var x = new Float64Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); + +var v = dany( [ x ] ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray. + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `false`. +- The function explicitly treats `NaN` values as falsy. + +
+ + + +
+ +## Examples + + + +```javascript +var bernoulli = require( '@stdlib/random/bernoulli' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dany = require( '@stdlib/blas/ext/base/ndarray/dany' ); + +var x = bernoulli( [ 10 ], 0.2, { + 'dtype': 'float64' +}); +console.log( ndarray2array( x ) ); + +var v = dany( [ x ] ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/benchmark/benchmark.js new file mode 100644 index 000000000000..e7ebcc7d6c25 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/benchmark/benchmark.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dany = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( [ len ], options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dany( [ x ] ); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/repl.txt new file mode 100644 index 000000000000..91f47c30b07c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( arrays ) + Tests whether at least one element in a one-dimensional double-precision + floating-point ndarray is truthy. + + If provided an empty ndarray, the function returns `false`. + + The function explicitly treats `NaN` values as falsy. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray. + + Returns + ------- + bool: boolean + Boolean indicating whether at least one element is truthy. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 0.0, 0.0, 1.0 ] ); + > {{alias}}( [ x ] ) + true + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/types/index.d.ts new file mode 100644 index 000000000000..d438344c2e83 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray } from '@stdlib/types/ndarray'; + +/** +* Tests whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* +* - The function explicitly treats `NaN` values as falsy. +* +* @param arrays - array-like object containing ndarrays +* @returns boolean indicating whether at least one element is truthy +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); +* +* var v = dany( [ x ] ); +* // returns true +*/ +declare function dany( arrays: [ float64ndarray ] ): boolean; + + +// EXPORTS // + +export = dany; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/types/test.ts new file mode 100644 index 000000000000..4639fba07a14 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dany = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dany( [ x ] ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dany( '10' ); // $ExpectError + dany( 10 ); // $ExpectError + dany( true ); // $ExpectError + dany( false ); // $ExpectError + dany( null ); // $ExpectError + dany( undefined ); // $ExpectError + dany( [] ); // $ExpectError + dany( {} ); // $ExpectError + dany( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dany(); // $ExpectError + dany( [ x ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/examples/index.js new file mode 100644 index 000000000000..5b8903aa8ab1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var bernoulli = require( '@stdlib/random/bernoulli' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dany = require( './../lib' ); + +var x = bernoulli( [ 10 ], 0.2, { + 'dtype': 'float64' +}); +console.log( ndarray2array( x ) ); + +var v = dany( [ x ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/lib/index.js new file mode 100644 index 000000000000..2a02a502d07d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy. +* +* @module @stdlib/blas/ext/base/ndarray/dany +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var dany = require( '@stdlib/blas/ext/base/ndarray/dany' ); +* +* var x = new Float64Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); +* +* var v = dany( [ x ] ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/lib/main.js new file mode 100644 index 000000000000..32a0b74a2e0a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/lib/main.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/dany' ).ndarray; + + +// MAIN // + +/** +* Tests whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* +* - The function explicitly treats `NaN` values as falsy. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {boolean} boolean indicating whether at least one element is truthy +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); +* +* var v = dany( [ x ] ); +* // returns true +*/ +function dany( arrays ) { + var x = arrays[ 0 ]; + return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dany; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/package.json new file mode 100644 index 000000000000..f0bb98a40ace --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dany", + "version": "0.0.0", + "description": "Test whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "any", + "dany", + "truthy", + "test", + "boolean", + "ndarray", + "float64", + "double-precision", + "float64array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/test/test.js new file mode 100644 index 000000000000..e09d33374cec --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dany/test/test.js @@ -0,0 +1,178 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dany = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dany, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dany.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function tests whether at least one element in a one-dimensional ndarray is truthy', function test( t ) { + var x; + var v; + + x = new Float64Array( [ 0.0, 0.0, 1.0, 1.0 ] ); + v = dany( [ vector( x, 4, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + x = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + v = dany( [ vector( x, 5, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float64Array( [ 1.0, 0.0, 0.0 ] ); + v = dany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + x = new Float64Array( [ -0.0, 0.0, -0.0 ] ); + v = dany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float64Array( [ -1.0, 0.0, 0.0 ] ); + v = dany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `NaN` values as falsy', function test( t ) { + var x; + var v; + + x = new Float64Array( [ NaN, 0.0, 0.0 ] ); + v = dany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float64Array( [ NaN, NaN, NaN ] ); + v = dany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float64Array( [ NaN, 0.0, 1.0 ] ); + v = dany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `false`', function test( t ) { + var x; + var v; + + x = new Float64Array( [] ); + + v = dany( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 0.0, // 0 + 1.0, + 0.0, // 1 + 1.0, + 0.0, // 2 + 1.0, + 0.0, // 3 + 1.0 + ]); + + v = dany( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, false, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, // 3 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 0 + 0.0 + ]); + + v = dany( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Float64Array([ + 1.0, + 0.0, // 0 + 1.0, + 0.0, // 1 + 1.0, + 0.0, // 2 + 1.0, + 0.0 // 3 + ]); + + v = dany( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/README.md new file mode 100644 index 000000000000..48b0acbf5e00 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/README.md @@ -0,0 +1,132 @@ + + +# dfillEqual + +> Replace elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dfillEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-equal' ); +``` + +#### dfillEqual( arrays ) + +Replaces elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +var searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' +}); + +var alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' +}); + +dfillEqual( [ x, searchElement, alpha ] ); +// x => [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + +
+ + + +
+ +## Notes + +- The input ndarray is modified **in-place** (i.e., the input ndarray is **mutated**). +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var dfillEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-equal' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1.0, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +dfillEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..de290d93c07e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var dfill = require( '@stdlib/blas/ext/base/dfill' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillEqual = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var searchElement; + var alpha; + var xbuf; + var x; + + xbuf = uniform( len, -100.0, 100.0, options ); + dfill( len, 0.0, xbuf, 3 ); + x = vector( xbuf, options.dtype ); + searchElement = scalar2ndarray( 0.0, options ); + alpha = scalar2ndarray( 5.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfillEqual( [ x, searchElement, alpha ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/repl.txt new file mode 100644 index 000000000000..d8ee49a8c7b1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( arrays ) + Replaces elements in a one-dimensional double-precision floating-point + ndarray equal to a provided search element with a specified scalar + constant. + + The input ndarray is modified *in-place* (i.e., the input ndarray is + *mutated*). + + When comparing elements, the function checks for equality using the strict + equality operator `===`. As a consequence, `NaN` values are considered + distinct and `-0` and `+0` are considered the same. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > var v = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, { 'dtype': 'float64' } ); + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'float64' } ); + > {{alias}}( [ x, v, alpha ] ) + [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..e70899dfa18d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Replaces elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct and `-0` and `+0` are considered the same. +* +* @param arrays - array-like object containing ndarrays +* @returns input ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float64' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float64' +* }); +* +* var out = dfillEqual( [ x, searchElement, alpha ] ); +* // returns [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] +*/ +declare function dfillEqual( arrays: [ float64ndarray, typedndarray, typedndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/types/test.ts new file mode 100644 index 000000000000..f0ea40eae8e8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/docs/types/test.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import dfillEqual = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + dfillEqual( [ x, searchElement, alpha ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dfillEqual( '10' ); // $ExpectError + dfillEqual( 5 ); // $ExpectError + dfillEqual( true ); // $ExpectError + dfillEqual( false ); // $ExpectError + dfillEqual( null ); // $ExpectError + dfillEqual( undefined ); // $ExpectError + dfillEqual( [] ); // $ExpectError + dfillEqual( {} ); // $ExpectError + dfillEqual( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + dfillEqual(); // $ExpectError + dfillEqual( [ x, searchElement, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/examples/index.js new file mode 100644 index 000000000000..6463300da794 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var dfillEqual = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1.0, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +dfillEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/lib/index.js new file mode 100644 index 000000000000..85e8bb18ad34 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/lib/index.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/ndarray/dfill-equal +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dfillEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-equal' ); +* +* var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float64' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float64' +* }); +* +* var out = dfillEqual( [ x, searchElement, alpha ] ); +* // returns [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/lib/main.js new file mode 100644 index 000000000000..cf9e9e1671c2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/lib/main.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/dfill-equal' ).ndarray; +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); + + +// MAIN // + +/** +* Replaces elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct and `-0` and `+0` are considered the same. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} input ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float64' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float64' +* }); +* +* var out = dfillEqual( [ x, searchElement, alpha ] ); +* // returns [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] +*/ +function dfillEqual( arrays ) { + var searchElement; + var alpha; + var x; + + x = arrays[ 0 ]; + searchElement = ndarraylike2scalar( arrays[ 1 ] ); + alpha = ndarraylike2scalar( arrays[ 2 ] ); + strided( numelDimension( x, 0 ), searchElement, alpha, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = dfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/package.json new file mode 100644 index 000000000000..7ad0e4828f3a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dfill-equal", + "version": "0.0.0", + "description": "Replace elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "fill", + "equal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float64", + "double" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/test/test.js new file mode 100644 index 000000000000..1a5aaf4a4b30 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-equal/test/test.js @@ -0,0 +1,301 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dfillEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function replaces elements equal to a provided search element', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 6, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, 2, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 5.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, -2, 4 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 5.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-zero offset', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, 1, 3 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 0.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are not equal to a provided search element, the function returns the input ndarray unchanged', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function returns the input ndarray unchanged', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ NaN, 1.0, NaN ] ); + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( NaN, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ NaN, 1.0, NaN ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function does not replace `NaN` elements', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ NaN, 0.0, NaN ] ); + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ NaN, 5.0, NaN ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 5.0, 1.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( -0.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 5.0, 1.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the input ndarray unchanged when the input ndarray is empty', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/README.md new file mode 100644 index 000000000000..27d06cbe4566 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/README.md @@ -0,0 +1,132 @@ + + +# dfillNotEqual + +> Replace elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-not-equal' ); +``` + +#### dfillNotEqual( arrays ) + +Replaces elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +var searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' +}); + +var alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' +}); + +dfillNotEqual( [ x, searchElement, alpha ] ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + +
+ + + +
+ +## Notes + +- The input ndarray is modified **in-place** (i.e., the input ndarray is **mutated**). +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var dfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-not-equal' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1.0, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +dfillNotEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..8de3cf5ad3e5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfillNotEqual = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var searchElement; + var alpha; + var x; + + x = uniform( [ len ], -100.0, 100.0, options ); + searchElement = scalar2ndarray( 0.0, options ); + alpha = scalar2ndarray( 5.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfillNotEqual( [ x, searchElement, alpha ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/repl.txt new file mode 100644 index 000000000000..3216cb60a9bf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/repl.txt @@ -0,0 +1,39 @@ + +{{alias}}( arrays ) + Replaces elements in a one-dimensional double-precision floating-point + ndarray not equal to a provided search element with a specified scalar + constant. + + The input ndarray is modified *in-place* (i.e., the input ndarray is + *mutated*). + + When comparing elements, the function checks for equality using the strict + equality operator `===`. As a consequence, `NaN` values are considered + distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements + are always replaced), and `-0` and `+0` are considered the same. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > var v = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, { 'dtype': 'float64' } ); + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'float64' } ); + > {{alias}}( [ x, v, alpha ] ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..118b1c624a9f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Replaces elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. +* +* @param arrays - array-like object containing ndarrays +* @returns input ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float64' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float64' +* }); +* +* var out = dfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +declare function dfillNotEqual( arrays: [ float64ndarray, typedndarray, typedndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..56572c894c26 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/docs/types/test.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import dfillNotEqual = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + dfillNotEqual( [ x, searchElement, alpha ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dfillNotEqual( '10' ); // $ExpectError + dfillNotEqual( 5 ); // $ExpectError + dfillNotEqual( true ); // $ExpectError + dfillNotEqual( false ); // $ExpectError + dfillNotEqual( null ); // $ExpectError + dfillNotEqual( undefined ); // $ExpectError + dfillNotEqual( [] ); // $ExpectError + dfillNotEqual( {} ); // $ExpectError + dfillNotEqual( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + dfillNotEqual(); // $ExpectError + dfillNotEqual( [ x, searchElement, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/examples/index.js new file mode 100644 index 000000000000..1647130cd216 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var dfillNotEqual = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1.0, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +dfillNotEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/lib/index.js new file mode 100644 index 000000000000..be540fb01568 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/lib/index.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/ndarray/dfill-not-equal +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-not-equal' ); +* +* var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float64' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float64' +* }); +* +* var out = dfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/lib/main.js new file mode 100644 index 000000000000..a7735034cdb6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/lib/main.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/dfill-not-equal' ).ndarray; +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); + + +// MAIN // + +/** +* Replaces elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} input ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float64' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float64' +* }); +* +* var out = dfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function dfillNotEqual( arrays ) { + var searchElement; + var alpha; + var x; + + x = arrays[ 0 ]; + searchElement = ndarraylike2scalar( arrays[ 1 ] ); + alpha = ndarraylike2scalar( arrays[ 2 ] ); + strided( numelDimension( x, 0 ), searchElement, alpha, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = dfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/package.json new file mode 100644 index 000000000000..6b418fe8e57c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dfill-not-equal", + "version": "0.0.0", + "description": "Replace elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "fill", + "not equal", + "unequal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float64", + "double" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/test/test.js new file mode 100644 index 000000000000..06a6b4b78809 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfill-not-equal/test/test.js @@ -0,0 +1,301 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat64Array = require( '@stdlib/assert/is-same-float64array' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var dfillNotEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function replaces elements not equal to a provided search element', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 6, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, 2, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, -2, 4 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-zero offset', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, 1, 3 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 0.0, -2.0, 3.0, 0.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns the input ndarray unchanged', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ NaN, 1.0, NaN ] ); + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( NaN, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 5.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ NaN, 0.0, NaN ] ); + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ 5.0, 0.0, 5.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + xbuf = new Float64Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( -0.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the input ndarray unchanged when the input ndarray is empty', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float64Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float64' + }); + + actual = dfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float64Array( [] ); + t.strictEqual( isSameFloat64Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/README.md new file mode 100644 index 000000000000..ffcdab1d53e5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/README.md @@ -0,0 +1,128 @@ + + +# dfirstIndexLessThan + +> Return the index of the first element in a one-dimensional double-precision floating-point ndarray which is less than a corresponding element in another one-dimensional double-precision floating-point ndarray. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dfirstIndexLessThan = require( '@stdlib/blas/ext/base/ndarray/dfirst-index-less-than' ); +``` + +#### dfirstIndexLessThan( arrays ) + +Returns the index of the first element in a one-dimensional double-precision floating-point ndarray which is less than a corresponding element in another one-dimensional double-precision floating-point ndarray. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + +var x = new Float64Vector( [ 0.0, 0.0, 0.0, 0.0 ] ); +var y = new Float64Vector( [ 0.0, 0.0, 1.0, 0.0 ] ); + +var idx = dfirstIndexLessThan( [ x, y ] ); +// returns 2 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - first one-dimensional input ndarray. + - second one-dimensional input ndarray. + +If the function is unable to find an element in the first one-dimensional input ndarray which is less than a corresponding element in the second one-dimensional input ndarray, the function returns `-1`. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + +var x = new Float64Vector( [ 5.0, 6.0, 7.0, 8.0 ] ); +var y = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0 ] ); + +var idx = dfirstIndexLessThan( [ x, y ] ); +// returns -1 +``` + +
+ + + +
+ +## Notes + +- When comparing elements, the function checks whether an element in the first one-dimensional input ndarray is less than a corresponding element in the second one-dimensional input ndarray using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dfirstIndexLessThan = require( '@stdlib/blas/ext/base/ndarray/dfirst-index-less-than' ); + +var opts = { + 'dtype': 'float64' +}; +var x = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( y ) ); + +var idx = dfirstIndexLessThan( [ x, y ] ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/benchmark/benchmark.js new file mode 100644 index 000000000000..176490c3079e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/benchmark/benchmark.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dfirstIndexLessThan = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = new Float64Vector( ones( len, options.dtype ) ); + var y = new Float64Vector( ones( len, options.dtype ) ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dfirstIndexLessThan( [ x, y ] ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/repl.txt new file mode 100644 index 000000000000..e6886c7faa75 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/repl.txt @@ -0,0 +1,33 @@ + +{{alias}}( arrays ) + Returns the index of the first element in a one-dimensional double- + precision floating-point ndarray which is less than a corresponding element + in another one-dimensional double-precision floating-point ndarray. + + When comparing elements, the function checks whether an element in the first + one-dimensional input ndarray is less than a corresponding element in the + second one-dimensional input ndarray using the less-than operator `<`. As a + consequence, comparisons involving `NaN` always evaluate to `false`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - first one-dimensional input ndarray. + - second one-dimensional input ndarray. + + Returns + ------- + out: integer + Index. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var y = new {{alias:@stdlib/ndarray/vector/float64}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}( [ x, y ] ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/types/index.d.ts new file mode 100644 index 000000000000..98180c960525 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/types/index.d.ts @@ -0,0 +1,54 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray } from '@stdlib/types/ndarray'; + +/** +* Returns the index of the first element in a one-dimensional double-precision floating-point ndarray which is less than a corresponding element in another one-dimensional double-precision floating-point ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - first one-dimensional input ndarray. +* - second one-dimensional input ndarray. +* +* - When comparing elements, the function checks whether an element in the first one-dimensional input ndarray is less than a corresponding element in the second one-dimensional input ndarray using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. +* +* @param arrays - array-like object containing ndarrays +* @returns index +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 0.0, 0.0, 0.0, 0.0 ] ); +* var y = new Float64Vector( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* var idx = dfirstIndexLessThan( [ x, y ] ); +* // returns 2 +*/ +declare function dfirstIndexLessThan( arrays: [ float64ndarray, float64ndarray ] ): number; + + +// EXPORTS // + +export = dfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/types/test.ts new file mode 100644 index 000000000000..ada378446f94 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dfirstIndexLessThan = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dfirstIndexLessThan( [ x, y ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dfirstIndexLessThan( '10' ); // $ExpectError + dfirstIndexLessThan( 10 ); // $ExpectError + dfirstIndexLessThan( true ); // $ExpectError + dfirstIndexLessThan( false ); // $ExpectError + dfirstIndexLessThan( null ); // $ExpectError + dfirstIndexLessThan( undefined ); // $ExpectError + dfirstIndexLessThan( [] ); // $ExpectError + dfirstIndexLessThan( {} ); // $ExpectError + dfirstIndexLessThan( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dfirstIndexLessThan(); // $ExpectError + dfirstIndexLessThan( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/examples/index.js new file mode 100644 index 000000000000..7c3ab47e7f69 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dfirstIndexLessThan = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var x = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( y ) ); + +var idx = dfirstIndexLessThan( [ x, y ] ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/lib/index.js new file mode 100644 index 000000000000..b4fee2b37824 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the first element in a one-dimensional double-precision floating-point ndarray which is less than a corresponding element in another one-dimensional double-precision floating-point ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/dfirst-index-less-than +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var dfirstIndexLessThan = require( '@stdlib/blas/ext/base/ndarray/dfirst-index-less-than' ); +* +* var x = new Float64Vector( [ 0.0, 0.0, 0.0, 0.0 ] ); +* var y = new Float64Vector( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* var idx = dfirstIndexLessThan( [ x, y ] ); +* // returns 2 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/lib/main.js new file mode 100644 index 000000000000..b203c92d4c3e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/lib/main.js @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/dfirst-index-less-than' ).ndarray; + + +// MAIN // + +/** +* Returns the index of the first element in a one-dimensional double-precision floating-point ndarray which is less than a corresponding element in another one-dimensional double-precision floating-point ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - first one-dimensional input ndarray. +* - second one-dimensional input ndarray. +* +* - When comparing elements, the function checks whether an element in the first one-dimensional input ndarray is less than a corresponding element in the second one-dimensional input ndarray using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {integer} index +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 0.0, 0.0, 0.0, 0.0 ] ); +* var y = new Float64Vector( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* var idx = dfirstIndexLessThan( [ x, y ] ); +* // returns 2 +*/ +function dfirstIndexLessThan( arrays ) { + var x = arrays[ 0 ]; + var y = arrays[ 1 ]; + return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/package.json new file mode 100644 index 000000000000..bae2b524a0de --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dfirst-index-less-than", + "version": "0.0.0", + "description": "Return the index of the first element in a one-dimensional double-precision floating-point ndarray which is less than a corresponding element in another one-dimensional double-precision floating-point ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "array", + "index", + "search", + "find", + "less", + "compare", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/test/test.js new file mode 100644 index 000000000000..d29e09798be8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dfirst-index-less-than/test/test.js @@ -0,0 +1,194 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var Float64Array = require( '@stdlib/array/float64' ); +var dfirstIndexLessThan = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray', function test( t ) { + var actual; + var x; + var y; + + x = vector( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ), 6, 1, 0 ); + y = vector( new Float64Array( [ 2.0, 2.0, 2.0, 3.0, 4.0, 5.0 ] ), 6, 1, 0 ); + + actual = dfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = vector( new Float64Array( [ 2.0, 1.0, 3.0, 4.0, 5.0, 6.0 ] ), 6, 1, 0 ); + y = vector( new Float64Array( [ 1.0, 2.0, 2.0, 3.0, 4.0, 5.0 ] ), 6, 1, 0 ); + + actual = dfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = vector( new Float64Array( [ 2.0, 2.0, 2.0, 4.0, 5.0, 6.0 ] ), 6, 1, 0 ); + y = vector( new Float64Array( [ 1.0, 2.0, 3.0, 5.0, 4.0, 5.0 ] ), 6, 1, 0 ); + + actual = dfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = vector( new Float64Array( [ 2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ), 6, 1, 0 ); + y = vector( new Float64Array( [ 1.0, 2.0, 2.0, 3.0, 4.0, 5.0 ] ), 6, 1, 0 ); + + actual = dfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if unable to find an element in the first one-dimensional input ndarray which is less than a corresponding element in the second one-dimensional input ndarray', function test( t ) { + var actual; + var x; + var y; + + x = vector( new Float64Array( [ 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ), 6, 1, 0 ); + y = vector( new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ), 6, 1, 0 ); + + actual = dfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 2.0, // 0 + 2.0, + 2.0, // 1 + -4.0, + 3.0, // 2 + 3.0, + 5.0, // 3 + 2.0 + ]); + y = new Float64Array([ + 1.0, // 0 + 2.0, + 1.0, // 1 + -4.0, + 4.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]); + + actual = dfirstIndexLessThan( [ vector( x, 4, 2, 0 ), vector( y, 4, 2, 0 ) ] ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 1.0, // 3 + 2.0, + 2.0, // 2 + -2.0, + 3.0, // 1 + 4.0, + 5.0, // 0 + 2.0 + ]); + y = new Float64Array([ + 4.0, // 3 + 2.0, + 3.0, // 2 + -2.0, + 4.0, // 1 + 4.0, + 4.0, // 0 + 2.0 + ]); + + actual = dfirstIndexLessThan( [ vector( x, 4, -2, 6 ), vector( y, 4, -2, 6 ) ] ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var actual; + var x; + var y; + + x = new Float64Array([ + 2.0, + 1.0, // 0 + 2.0, + 2.0, // 1 + -2.0, + 3.0, // 2 + 3.0, + 4.0 // 3 + ]); + y = new Float64Array([ + 2.0, + 2.0, // 0 + 2.0, + 3.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 5.0 // 3 + ]); + + actual = dfirstIndexLessThan( [ vector( x, 4, 2, 1 ), vector( y, 4, 2, 1 ) ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-falsy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-falsy/README.md index 6dd9ff3da3bb..87682c4e81d1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-falsy/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-falsy/README.md @@ -51,9 +51,7 @@ var idx = dindexOfFalsy( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. If the function is unable to find a falsy element, the function returns `-1`. diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/README.md new file mode 100644 index 000000000000..c65caf575761 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/README.md @@ -0,0 +1,139 @@ + + +# dindexOfNotEqual + +> Return the first index of an element in a one-dimensional double-precision floating-point ndarray which is not equal to a specified search element. + +
+ +
+ + + +
+ +## Usage + +```javascript +var dindexOfNotEqual = require( '@stdlib/blas/ext/base/ndarray/dindex-of-not-equal' ); +``` + +#### dindexOfNotEqual( arrays ) + +Returns the first index of an element in a one-dimensional double-precision floating-point ndarray which is not equal to a specified search element. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = new Float64Vector( [ 1.0, 1.0, 3.0 ] ); + +var searchElement = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); + +var idx = dindexOfNotEqual( [ x, searchElement ] ); +// returns 2 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + +If the function is unable to find an element which is not equal to a specified search element, the function returns `-1`. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = new Float64Vector( [ 1.0, 1.0, 1.0 ] ); + +var searchElement = scalar2ndarray( 1.0, { + 'dtype': 'float64' +}); + +var idx = dindexOfNotEqual( [ x, searchElement ] ); +// returns -1 +``` + +
+ + + +
+ +## Notes + +- When searching for a search element, the function checks for inequality using the strict inequality operator `!==`. As a consequence, `NaN` values are considered distinct from all values (including other `NaN` values), and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var dindexOfNotEqual = require( '@stdlib/blas/ext/base/ndarray/dindex-of-not-equal' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 0, 2, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 0, opts ); +console.log( 'Search Element:', ndarraylike2scalar( searchElement ) ); + +var idx = dindexOfNotEqual( [ x, searchElement ] ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..28913ccee710 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dindexOfNotEqual = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var searchElement; + var x; + + x = zeros( [ len ], options ); + searchElement = scalar2ndarray( 0.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dindexOfNotEqual( [ x, searchElement ] ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/repl.txt new file mode 100644 index 000000000000..c1b0cf95e56c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/repl.txt @@ -0,0 +1,35 @@ + +{{alias}}( arrays ) + Returns the first index of an element in a one-dimensional double-precision + floating-point ndarray which is not equal to a specified search element. + + When searching for a search element, the function checks for inequality + using the strict inequality operator `!==`. As a consequence, `NaN` values + are considered distinct from all values (including other `NaN` values), and + `-0` and `+0` are considered the same. + + If unable to find an element which is not equal to a specified search + element, the function returns `-1`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + + Returns + ------- + out: integer + Index. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 1.0, 1.0, 3.0 ] ); + > var v = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, { 'dtype': 'float64' } ); + > {{alias}}( [ x, v ] ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..b8a73d6fc028 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/types/index.d.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Returns the first index of an element in a one-dimensional double-precision floating-point ndarray which is not equal to a specified search element. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* +* @param arrays - array-like object containing ndarrays +* @returns index +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 1.0, 1.0, 3.0 ] ); +* +* var searchElement = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var v = dindexOfNotEqual( [ x, searchElement ] ); +* // returns 2 +*/ +declare function dindexOfNotEqual( arrays: [ float64ndarray, typedndarray ] ): number; + + +// EXPORTS // + +export = dindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..762ef435b2e5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/docs/types/test.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import dindexOfNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + + dindexOfNotEqual( [ x, searchElement ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dindexOfNotEqual( '10' ); // $ExpectError + dindexOfNotEqual( 10 ); // $ExpectError + dindexOfNotEqual( true ); // $ExpectError + dindexOfNotEqual( false ); // $ExpectError + dindexOfNotEqual( null ); // $ExpectError + dindexOfNotEqual( undefined ); // $ExpectError + dindexOfNotEqual( [] ); // $ExpectError + dindexOfNotEqual( {} ); // $ExpectError + dindexOfNotEqual( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + + dindexOfNotEqual(); // $ExpectError + dindexOfNotEqual( [ x, searchElement ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/examples/index.js new file mode 100644 index 000000000000..c2c2f793c424 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var dindexOfNotEqual = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 0, 2, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 0, opts ); +console.log( 'Search Element:', ndarraylike2scalar( searchElement ) ); + +var idx = dindexOfNotEqual( [ x, searchElement ] ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/lib/index.js new file mode 100644 index 000000000000..0c1cba106c48 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/lib/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the first index of an element in a one-dimensional double-precision floating-point ndarray which is not equal to a specified search element. +* +* @module @stdlib/blas/ext/base/ndarray/dindex-of-not-equal +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var dindexOfNotEqual = require( '@stdlib/blas/ext/base/ndarray/dindex-of-not-equal' ); +* +* var x = new Float64Vector( [ 1.0, 1.0, 3.0 ] ); +* +* var searchElement = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var v = dindexOfNotEqual( [ x, searchElement ] ); +* // returns 2 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/lib/main.js new file mode 100644 index 000000000000..ab4dae461cdb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); +var strided = require( '@stdlib/blas/ext/base/dindex-of-not-equal' ).ndarray; + + +// MAIN // + +/** +* Returns the first index of an element in a one-dimensional double-precision floating-point ndarray which is not equal to a specified search element. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {integer} index +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float64Vector( [ 1.0, 1.0, 3.0 ] ); +* +* var searchElement = scalar2ndarray( 1.0, { +* 'dtype': 'float64' +* }); +* +* var v = dindexOfNotEqual( [ x, searchElement ] ); +* // returns 2 +*/ +function dindexOfNotEqual( arrays ) { + var x = arrays[ 0 ]; + return strided( numelDimension( x, 0 ), ndarraylike2scalar( arrays[ 1 ] ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = dindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/package.json new file mode 100644 index 000000000000..a722eb7d655f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dindex-of-not-equal", + "version": "0.0.0", + "description": "Return the first index of an element in a one-dimensional double-precision floating-point ndarray which is not equal to a specified search element.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "array", + "index", + "search", + "find", + "equal", + "unequal", + "float64", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/test/test.js new file mode 100644 index 000000000000..37ffcc7b8f96 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dindex-of-not-equal/test/test.js @@ -0,0 +1,227 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dindexOfNotEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a one-dimensional ndarray which is not equal to a provided search element', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ), 6, 1, 0 ); + + searchElement = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + searchElement = scalar2ndarray( 3.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + searchElement = scalar2ndarray( 4.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every element in a one-dimensional ndarray is equal to a provided search element', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ 2.0, 2.0, 2.0 ] ), 3, 1, 0 ); + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `NaN` elements to be not equal to a provided search element', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ 1.0, NaN, 1.0 ] ), 3, 1, 0 ); + searchElement = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided search element is `NaN`', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ NaN, 1.0 ] ), 2, 1, 0 ); + searchElement = scalar2ndarray( NaN, { + 'dtype': 'float64' + }); + + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be equal', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ -0.0, 0.0 ] ), 2, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float64' + }); + + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ 2.0, 9.0, 2.0, 9.0, 3.0, 9.0 ] ), 3, 2, 0 ); + + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + searchElement = scalar2ndarray( 9.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ), 6, -1, 5 ); + + searchElement = scalar2ndarray( 3.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + searchElement = scalar2ndarray( 1.0, { + 'dtype': 'float64' + }); + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ), 3, 1, 3 ); + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an empty one-dimensional ndarray', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( new Float64Array( [] ), 0, 1, 0 ); + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'float64' + }); + + actual = dindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json index 32b27be4577a..0a439cfa7053 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansum/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/dnansum", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/package.json index ea2dd45b7e7e..55c32b1ae93b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/dnansumkbn", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.", + "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using an improved Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/package.json index 23499e315635..2680da766088 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumkbn2/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/dnansumkbn2", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.", + "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/package.json index 845185426018..f587935b9f2e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/dnansumors", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using ordinary recursive summation.", + "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/package.json index 0bff39b073ad..d07fd4cd6642 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dnansumpw/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/dnansumpw", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using pairwise summation.", + "description": "Compute the sum of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using pairwise summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts index b29eda953ebd..bea90f192fc1 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/docs/types/index.d.ts @@ -27,10 +27,12 @@ import coneTo = require( '@stdlib/blas/ext/base/ndarray/cone-to' ); import csum = require( '@stdlib/blas/ext/base/ndarray/csum' ); import csumkbn = require( '@stdlib/blas/ext/base/ndarray/csumkbn' ); import cunitspace = require( '@stdlib/blas/ext/base/ndarray/cunitspace' ); +import cxmy = require( '@stdlib/blas/ext/base/ndarray/cxmy' ); import cxpy = require( '@stdlib/blas/ext/base/ndarray/cxpy' ); import cxsa = require( '@stdlib/blas/ext/base/ndarray/cxsa' ); import cxsy = require( '@stdlib/blas/ext/base/ndarray/cxsy' ); import czeroTo = require( '@stdlib/blas/ext/base/ndarray/czero-to' ); +import dany = require( '@stdlib/blas/ext/base/ndarray/dany' ); import daxpb = require( '@stdlib/blas/ext/base/ndarray/daxpb' ); import daxpby = require( '@stdlib/blas/ext/base/ndarray/daxpby' ); import dcircshift = require( '@stdlib/blas/ext/base/ndarray/dcircshift' ); @@ -40,6 +42,8 @@ import dcusumkbn2 = require( '@stdlib/blas/ext/base/ndarray/dcusumkbn2' ); import dcusumors = require( '@stdlib/blas/ext/base/ndarray/dcusumors' ); import dcusumpw = require( '@stdlib/blas/ext/base/ndarray/dcusumpw' ); import ddiff = require( '@stdlib/blas/ext/base/ndarray/ddiff' ); +import dfillEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-equal' ); +import dfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/dfill-not-equal' ); import dindexOf = require( '@stdlib/blas/ext/base/ndarray/dindex-of' ); import dindexOfFalsy = require( '@stdlib/blas/ext/base/ndarray/dindex-of-falsy' ); import dlastIndexOf = require( '@stdlib/blas/ext/base/ndarray/dlast-index-of' ); @@ -60,10 +64,13 @@ import dsumkbn2 = require( '@stdlib/blas/ext/base/ndarray/dsumkbn2' ); import dsumors = require( '@stdlib/blas/ext/base/ndarray/dsumors' ); import dsumpw = require( '@stdlib/blas/ext/base/ndarray/dsumpw' ); import dunitspace = require( '@stdlib/blas/ext/base/ndarray/dunitspace' ); +import dxdy = require( '@stdlib/blas/ext/base/ndarray/dxdy' ); +import dxmy = require( '@stdlib/blas/ext/base/ndarray/dxmy' ); import dxpy = require( '@stdlib/blas/ext/base/ndarray/dxpy' ); import dxsa = require( '@stdlib/blas/ext/base/ndarray/dxsa' ); import dxsy = require( '@stdlib/blas/ext/base/ndarray/dxsy' ); import dzeroTo = require( '@stdlib/blas/ext/base/ndarray/dzero-to' ); +import gany = require( '@stdlib/blas/ext/base/ndarray/gany' ); import gaxpb = require( '@stdlib/blas/ext/base/ndarray/gaxpb' ); import gaxpby = require( '@stdlib/blas/ext/base/ndarray/gaxpby' ); import gcircshift = require( '@stdlib/blas/ext/base/ndarray/gcircshift' ); @@ -72,10 +79,12 @@ import gcusumkbn = require( '@stdlib/blas/ext/base/ndarray/gcusumkbn' ); import gcusumkbn2 = require( '@stdlib/blas/ext/base/ndarray/gcusumkbn2' ); import gcusumors = require( '@stdlib/blas/ext/base/ndarray/gcusumors' ); import gcusumpw = require( '@stdlib/blas/ext/base/ndarray/gcusumpw' ); +import gfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/gfill-not-equal' ); import gfindIndex = require( '@stdlib/blas/ext/base/ndarray/gfind-index' ); import gfindLastIndex = require( '@stdlib/blas/ext/base/ndarray/gfind-last-index' ); import gindexOf = require( '@stdlib/blas/ext/base/ndarray/gindex-of' ); import gindexOfFalsy = require( '@stdlib/blas/ext/base/ndarray/gindex-of-falsy' ); +import gindexOfNotEqual = require( '@stdlib/blas/ext/base/ndarray/gindex-of-not-equal' ); import gindexOfTruthy = require( '@stdlib/blas/ext/base/ndarray/gindex-of-truthy' ); import gjoin = require( '@stdlib/blas/ext/base/ndarray/gjoin' ); import gjoinBetween = require( '@stdlib/blas/ext/base/ndarray/gjoin-between' ); @@ -95,10 +104,13 @@ import gsumkbn2 = require( '@stdlib/blas/ext/base/ndarray/gsumkbn2' ); import gsumors = require( '@stdlib/blas/ext/base/ndarray/gsumors' ); import gsumpw = require( '@stdlib/blas/ext/base/ndarray/gsumpw' ); import gunitspace = require( '@stdlib/blas/ext/base/ndarray/gunitspace' ); +import gxdy = require( '@stdlib/blas/ext/base/ndarray/gxdy' ); +import gxmy = require( '@stdlib/blas/ext/base/ndarray/gxmy' ); import gxpy = require( '@stdlib/blas/ext/base/ndarray/gxpy' ); import gxsa = require( '@stdlib/blas/ext/base/ndarray/gxsa' ); import gxsy = require( '@stdlib/blas/ext/base/ndarray/gxsy' ); import gzeroTo = require( '@stdlib/blas/ext/base/ndarray/gzero-to' ); +import sany = require( '@stdlib/blas/ext/base/ndarray/sany' ); import saxpb = require( '@stdlib/blas/ext/base/ndarray/saxpb' ); import saxpby = require( '@stdlib/blas/ext/base/ndarray/saxpby' ); import scircshift = require( '@stdlib/blas/ext/base/ndarray/scircshift' ); @@ -107,6 +119,7 @@ import scusum = require( '@stdlib/blas/ext/base/ndarray/scusum' ); import scusumkbn = require( '@stdlib/blas/ext/base/ndarray/scusumkbn' ); import scusumkbn2 = require( '@stdlib/blas/ext/base/ndarray/scusumkbn2' ); import scusumors = require( '@stdlib/blas/ext/base/ndarray/scusumors' ); +import sfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/sfill-not-equal' ); import sindexOf = require( '@stdlib/blas/ext/base/ndarray/sindex-of' ); import slastIndexOf = require( '@stdlib/blas/ext/base/ndarray/slast-index-of' ); import slinspace = require( '@stdlib/blas/ext/base/ndarray/slinspace' ); @@ -124,6 +137,8 @@ import ssumkbn2 = require( '@stdlib/blas/ext/base/ndarray/ssumkbn2' ); import ssumors = require( '@stdlib/blas/ext/base/ndarray/ssumors' ); import ssumpw = require( '@stdlib/blas/ext/base/ndarray/ssumpw' ); import sunitspace = require( '@stdlib/blas/ext/base/ndarray/sunitspace' ); +import sxdy = require( '@stdlib/blas/ext/base/ndarray/sxdy' ); +import sxmy = require( '@stdlib/blas/ext/base/ndarray/sxmy' ); import sxpy = require( '@stdlib/blas/ext/base/ndarray/sxpy' ); import sxsa = require( '@stdlib/blas/ext/base/ndarray/sxsa' ); import sxsy = require( '@stdlib/blas/ext/base/ndarray/sxsy' ); @@ -135,6 +150,8 @@ import zoneTo = require( '@stdlib/blas/ext/base/ndarray/zone-to' ); import zsum = require( '@stdlib/blas/ext/base/ndarray/zsum' ); import zsumkbn = require( '@stdlib/blas/ext/base/ndarray/zsumkbn' ); import zunitspace = require( '@stdlib/blas/ext/base/ndarray/zunitspace' ); +import zxdy = require( '@stdlib/blas/ext/base/ndarray/zxdy' ); +import zxmy = require( '@stdlib/blas/ext/base/ndarray/zxmy' ); import zxpy = require( '@stdlib/blas/ext/base/ndarray/zxpy' ); import zxsa = require( '@stdlib/blas/ext/base/ndarray/zxsa' ); import zxsy = require( '@stdlib/blas/ext/base/ndarray/zxsy' ); @@ -343,6 +360,30 @@ interface Namespace { */ cunitspace: typeof cunitspace; + /** + * Multiplies elements of a one-dimensional single-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' ); + * + * var x = new Complex64Vector( [ 1.0, 2.0, 3.0, -1.0, 0.0, 1.0 ] ); + * var y = new Complex64Vector( [ 2.0, 1.0, -1.0, 3.0, 4.0, 0.0 ] ); + * + * var out = ns.cxmy( [ x, y ] ); + * // returns [ [ 0.0, 5.0 ], [ 0.0, 10.0 ], [ 0.0, 4.0 ] ] + */ + cxmy: typeof cxmy; + /** * Adds elements of a one-dimensional single-precision complex floating-point ndarray to the corresponding elements of a second one-dimensional single-precision complex floating-point ndarray and assigns the results to the second ndarray. * @@ -442,6 +483,30 @@ interface Namespace { */ czeroTo: typeof czeroTo; + /** + * Tests whether at least one element in a one-dimensional double-precision floating-point ndarray is truthy. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * + * - The function explicitly treats `NaN` values as falsy. + * + * @param arrays - array-like object containing ndarrays + * @returns boolean indicating whether at least one element is truthy + * + * @example + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * + * var x = new Float64Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); + * + * var v = ns.dany( [ x ] ); + * // returns true + */ + dany: typeof dany; + /** * Multiplies each element in a one-dimensional double-precision floating-point ndarray by a scalar constant and adds a scalar constant to each result. * @@ -738,6 +803,76 @@ interface Namespace { */ ddiff: typeof ddiff; + /** + * Replaces elements in a one-dimensional double-precision floating-point ndarray equal to a provided search element with a specified scalar constant. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a zero-dimensional ndarray containing the search element. + * - a zero-dimensional ndarray containing the scalar constant. + * + * - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct and `-0` and `+0` are considered the same. + * + * @param arrays - array-like object containing ndarrays + * @returns input ndarray + * + * @example + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * var searchElement = scalar2ndarray( 0.0, { + * 'dtype': 'float64' + * }); + * + * var alpha = scalar2ndarray( 5.0, { + * 'dtype': 'float64' + * }); + * + * var out = ns.dfillEqual( [ x, searchElement, alpha ] ); + * // returns [ 5.0, -2.0, 3.0, 5.0, 4.0, -6.0 ] + */ + dfillEqual: typeof dfillEqual; + + /** + * Replaces elements in a one-dimensional double-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a zero-dimensional ndarray containing the search element. + * - a zero-dimensional ndarray containing the scalar constant. + * + * - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + * + * @param arrays - array-like object containing ndarrays + * @returns input ndarray + * + * @example + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = new Float64Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * var searchElement = scalar2ndarray( 0.0, { + * 'dtype': 'float64' + * }); + * + * var alpha = scalar2ndarray( 5.0, { + * 'dtype': 'float64' + * }); + * + * var out = ns.dfillNotEqual( [ x, searchElement, alpha ] ); + * // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + dfillNotEqual: typeof dfillNotEqual; + /** * Returns the first index of a search element in a one-dimensional double-precision floating-point ndarray. * @@ -1251,6 +1386,54 @@ interface Namespace { */ dunitspace: typeof dunitspace; + /** + * Divides elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * + * var x = new Float64Vector( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); + * var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * var out = ns.dxdy( [ x, y ] ); + * // returns [ 3.0, 4.0, 5.0, 6.0, 7.0 ] + */ + dxdy: typeof dxdy; + + /** + * Multiplies elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + * + * var x = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * var out = ns.dxmy( [ x, y ] ); + * // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] + */ + dxmy: typeof dxmy; + /** * Adds elements of a one-dimensional double-precision floating-point ndarray to the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. * @@ -1350,6 +1533,30 @@ interface Namespace { */ dzeroTo: typeof dzeroTo; + /** + * Tests whether at least one element in a one-dimensional ndarray is truthy. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * + * - The function explicitly treats `NaN` values as falsy. + * + * @param arrays - array-like object containing ndarrays + * @returns boolean indicating whether at least one element is truthy + * + * @example + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * + * var x = vector( [ 0.0, 0.0, 1.0, 1.0 ], 'generic' ); + * + * var v = ns.gany( [ x ] ); + * // returns true + */ + gany: typeof gany; + /** * Multiplies each element in a one-dimensional ndarray by a scalar constant and adds a scalar constant to each result. * @@ -1611,6 +1818,41 @@ interface Namespace { */ gcusumpw: typeof gcusumpw; + /** + * Replaces elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a zero-dimensional ndarray containing the search element. + * - a zero-dimensional ndarray containing the scalar constant. + * + * - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + * + * @param arrays - array-like object containing ndarrays + * @returns input ndarray + * + * @example + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ], 'generic' ); + * + * var searchElement = scalar2ndarray( 0.0, { + * 'dtype': 'generic' + * }); + * + * var alpha = scalar2ndarray( 5.0, { + * 'dtype': 'generic' + * }); + * + * var out = ns.gfillNotEqual( [ x, searchElement, alpha ] ); + * // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + gfillNotEqual: typeof gfillNotEqual; + /** * Returns the index of the first element in a one-dimensional ndarray which passes a test implemented by a predicate function. * @@ -1726,6 +1968,34 @@ interface Namespace { */ gindexOfFalsy: typeof gindexOfFalsy; + /** + * Returns the first index of an element in a one-dimensional ndarray which is not equal to a specified search element. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a zero-dimensional ndarray containing the search element. + * + * @param arrays - array-like object containing ndarrays + * @returns index + * + * @example + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = vector( [ 1.0, 1.0, 3.0 ], 'generic' ); + * + * var searchElement = scalar2ndarray( 1.0, { + * 'dtype': 'generic' + * }); + * + * var v = ns.gindexOfNotEqual( [ x, searchElement ] ); + * // returns 2 + */ + gindexOfNotEqual: typeof gindexOfNotEqual; + /** * Returns the index of the first truthy element in a one-dimensional ndarray. * @@ -2209,6 +2479,54 @@ interface Namespace { */ gunitspace: typeof gunitspace; + /** + * Divides elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * + * var x = vector( [ 4.0, 6.0, 12.0, 20.0, 30.0 ], 'generic' ); + * var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); + * + * var out = ns.gxdy( [ x, y ] ); + * // returns [ 2.0, 2.0, 3.0, 4.0, 5.0 ] + */ + gxdy: typeof gxdy; + + /** + * Multiplies elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var vector = require( '@stdlib/ndarray/vector/ctor' ); + * + * var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' ); + * var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); + * + * var out = ns.gxmy( [ x, y ] ); + * // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] + */ + gxmy: typeof gxmy; + /** * Adds elements of a one-dimensional ndarray to the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. * @@ -2308,6 +2626,30 @@ interface Namespace { */ gzeroTo: typeof gzeroTo; + /** + * Tests whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * + * - The function explicitly treats `NaN` values as falsy. + * + * @param arrays - array-like object containing ndarrays + * @returns boolean indicating whether at least one element is truthy + * + * @example + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * + * var x = new Float32Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); + * + * var v = ns.sany( [ x ] ); + * // returns true + */ + sany: typeof sany; + /** * Multiplies each element in a one-dimensional single-precision floating-point ndarray by a scalar constant and adds a scalar constant to each result. * @@ -2564,6 +2906,41 @@ interface Namespace { */ scusumors: typeof scusumors; + /** + * Replaces elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a zero-dimensional ndarray containing the search element. + * - a zero-dimensional ndarray containing the scalar constant. + * + * - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + * + * @param arrays - array-like object containing ndarrays + * @returns input ndarray + * + * @example + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + * + * var x = new Float32Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * var searchElement = scalar2ndarray( 0.0, { + * 'dtype': 'float32' + * }); + * + * var alpha = scalar2ndarray( 5.0, { + * 'dtype': 'float32' + * }); + * + * var out = ns.sfillNotEqual( [ x, searchElement, alpha ] ); + * // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + sfillNotEqual: typeof sfillNotEqual; + /** * Returns the first index of a search element in a one-dimensional single-precision floating-point ndarray. * @@ -3003,6 +3380,54 @@ interface Namespace { */ sunitspace: typeof sunitspace; + /** + * Divides elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * + * var x = new Float32Vector( [ 10.0, 12.0, 6.0, -4.0, 8.0 ] ); + * var y = new Float32Vector( [ 2.0, 3.0, 2.0, -2.0, 4.0 ] ); + * + * var out = ns.sxdy( [ x, y ] ); + * // returns [ 5.0, 4.0, 3.0, 2.0, 2.0 ] + */ + sxdy: typeof sxdy; + + /** + * Multiplies elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + * + * var x = new Float32Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + * var y = new Float32Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * var out = ns.sxmy( [ x, y ] ); + * // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] + */ + sxmy: typeof sxmy; + /** * Adds elements of a one-dimensional single-precision floating-point ndarray to the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. * @@ -3301,6 +3726,54 @@ interface Namespace { */ zunitspace: typeof zunitspace; + /** + * Divides elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); + * + * var x = new Complex128Vector( [ -1.0, 3.0, -2.0, 14.0, -4.0, 44.0 ] ); + * var y = new Complex128Vector( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + * + * var out = ns.zxdy( [ x, y ] ); + * // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ] + */ + zxdy: typeof zxdy; + + /** + * Multiplies elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. + * + * ## Notes + * + * - The function expects the following ndarrays: + * + * - a one-dimensional input ndarray. + * - a one-dimensional output ndarray. + * + * @param arrays - array-like object containing ndarrays + * @returns output ndarray + * + * @example + * var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); + * + * var x = new Complex128Vector( [ 1.0, 1.0, 2.0, -1.0, 3.0, 0.0 ] ); + * var y = new Complex128Vector( [ 2.0, 1.0, 1.0, 2.0, 2.0, -2.0 ] ); + * + * var out = ns.zxmy( [ x, y ] ); + * // returns [ [ 1.0, 3.0 ], [ 4.0, 3.0 ], [ 6.0, -6.0 ] ] + */ + zxmy: typeof zxmy; + /** * Adds elements of a one-dimensional double-precision complex floating-point ndarray to the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. * diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/README.md new file mode 100644 index 000000000000..49ffe28222fd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/README.md @@ -0,0 +1,132 @@ + + +# dxdy + +> Divide elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var dxdy = require( '@stdlib/blas/ext/base/ndarray/dxdy' ); +``` + +#### dxdy( arrays ) + +Divides elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + +var x = new Float64Vector( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +dxdy( [ x, y ] ); +// y => [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dxdy = require( '@stdlib/blas/ext/base/ndarray/dxdy' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( y ) ); + +dxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..40413474122c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dxdy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -100.0, 100.0, options ); + var y = uniform( [ len ], 1.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dxdy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/img/equation_xdy.svg b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/img/equation_xdy.svg new file mode 100644 index 000000000000..1b0e60ad95cf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/img/equation_xdy.svg @@ -0,0 +1,16 @@ + +bold y equals bold x circled-division-slash bold y + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/repl.txt new file mode 100644 index 000000000000..90cb76ad819f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/repl.txt @@ -0,0 +1,35 @@ + +{{alias}}( arrays ) + Divides elements of a one-dimensional double-precision floating-point + ndarray by the corresponding elements of a second one-dimensional double- + precision floating-point ndarray and assigns the results to the second + ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 6.0, 12.0, 20.0, 30.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf ); + > var ybuf = [ 2.0, 3.0, 4.0, 5.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float64}}( ybuf ); + > {{alias}}( [ x, y ] ) + [ 3.0, 4.0, 5.0, 6.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..4177bbeda47c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray } from '@stdlib/types/ndarray'; + +/** +* Divides elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = dxdy( [ x, y ] ); +* // returns [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ +declare function dxdy( arrays: [ float64ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/types/test.ts new file mode 100644 index 000000000000..3007f4485335 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dxdy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dxdy( [ x, y ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dxdy( '10' ); // $ExpectError + dxdy( 5 ); // $ExpectError + dxdy( true ); // $ExpectError + dxdy( false ); // $ExpectError + dxdy( null ); // $ExpectError + dxdy( undefined ); // $ExpectError + dxdy( [] ); // $ExpectError + dxdy( {} ); // $ExpectError + dxdy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dxdy(); // $ExpectError + dxdy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/examples/index.js new file mode 100644 index 000000000000..9323ff136a47 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dxdy = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( y ) ); + +dxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/lib/index.js new file mode 100644 index 000000000000..0292b7e5d543 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Divide elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/dxdy +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var dxdy = require( '@stdlib/blas/ext/base/ndarray/dxdy' ); +* +* var x = new Float64Vector( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = dxdy( [ x, y ] ); +* // returns [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/lib/main.js new file mode 100644 index 000000000000..643e65dcbf7f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/dxdy' ).ndarray; + + +// MAIN // + +/** +* Divides elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 6.0, 12.0, 20.0, 30.0, 42.0 ] ); +* var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = dxdy( [ x, y ] ); +* // returns [ 3.0, 4.0, 5.0, 6.0, 7.0 ] +*/ +function dxdy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = dxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/package.json new file mode 100644 index 000000000000..23f3e58ec14c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dxdy", + "version": "0.0.0", + "description": "Divide elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "dxdy", + "xdy", + "divide", + "division", + "quotient", + "vector", + "strided", + "array", + "ndarray", + "float64", + "double", + "double-precision" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/test/test.js new file mode 100644 index 000000000000..1189096b5463 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxdy/test/test.js @@ -0,0 +1,234 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dxdy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dxdy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0 ] ); + ybuf = new Float64Array( [ 1.0, 2.0, -3.0, 4.0, -1.0 ] ); + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + expected = new Float64Array([ + -2.0, // -2.0 / 1.0 + 0.5, // 1.0 / 2.0 + -1.0, // 3.0 / (-3.0) + -1.25, // -5.0 / 4.0 + -4.0 // 4.0 / (-1.0) + ]); + + actual = dxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-unit strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array([ + -2.0, // 0 + 1.0, + 3.0, // 1 + -5.0, + 4.0, // 2 + 0.0, + 6.0, // 3 + -3.0 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0, + -3.0, // 1 + 4.0, + -1.0, // 2 + 0.0, + 2.0, // 3 + 2.0 + ]); + x = vector( xbuf, 4, 2, 0 ); + y = vector( ybuf, 4, 2, 0 ); + expected = new Float64Array([ + -2.0, // -2.0 / 1.0 + 2.0, + -1.0, // 3.0 / (-3.0) + 4.0, + -4.0, // 4.0 / (-1.0) + 0.0, + 3.0, // 6.0 / 2.0 + 2.0 + ]); + + actual = dxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array([ + -2.0, // 4 + 1.0, // 3 + 3.0, // 2 + -5.0, // 1 + 4.0 // 0 + ]); + ybuf = new Float64Array([ + 1.0, // 4 + 2.0, // 3 + -3.0, // 2 + 4.0, // 1 + -1.0 // 0 + ]); + x = vector( xbuf, 5, -1, 4 ); + y = vector( ybuf, 5, -1, 4 ); + expected = new Float64Array([ + -2.0, // -2.0 / 1.0 + 0.5, // 1.0 / 2.0 + -1.0, // 3.0 / (-3.0) + -1.25, // -5.0 / 4.0 + -4.0 // 4.0 / (-1.0) + ]); + + actual = dxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array([ + 1.0, + -2.0, + 3.0, // 0 + -5.0, // 1 + 4.0, // 2 + 0.0 + ]); + ybuf = new Float64Array([ + 1.0, + -2.0, + 1.0, // 0 + 4.0, // 1 + -1.0, // 2 + 0.0 + ]); + x = vector( xbuf, 3, 1, 2 ); + y = vector( ybuf, 3, 1, 2 ); + expected = new Float64Array([ + 1.0, + -2.0, + 3.0, // 3.0 / 1.0 + -1.25, // -5.0 / 4.0 + -4.0, // 4.0 / (-1.0) + 0.0 + ]); + + actual = dxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the output ndarray unchanged when the input ndarrays are empty', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array( [] ); + ybuf = new Float64Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + expected = new Float64Array( [] ); + + actual = dxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/README.md new file mode 100644 index 000000000000..376802e09891 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/README.md @@ -0,0 +1,127 @@ + + +# dxmy + +> Multiply elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \odot \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var dxmy = require( '@stdlib/blas/ext/base/ndarray/dxmy' ); +``` + +#### dxmy( arrays ) + +Multiplies elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. + +```javascript +var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); + +var x = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +dxmy( [ x, y ] ); +// y => [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dxmy = require( '@stdlib/blas/ext/base/ndarray/dxmy' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( y ) ); + +dxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/benchmark/benchmark.js new file mode 100644 index 000000000000..a8d2f826b5f6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var dxmy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -100.0, 100.0, options ); + var y = uniform( [ len ], -100.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = dxmy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/repl.txt new file mode 100644 index 000000000000..06dce2d4325f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/repl.txt @@ -0,0 +1,35 @@ + +{{alias}}( arrays ) + Multiplies elements of a one-dimensional double-precision floating-point + ndarray by the corresponding elements of a second one-dimensional double- + precision floating-point ndarray and assigns the results to the second + ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0, 4.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float64}}( xbuf ); + > var ybuf = [ 2.0, 3.0, 4.0, 5.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float64}}( ybuf ); + > {{alias}}( [ x, y ] ) + [ 2.0, 6.0, 12.0, 20.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/types/index.d.ts new file mode 100644 index 000000000000..dab6c2fbf2d1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float64ndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = dxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ +declare function dxmy( arrays: [ float64ndarray, float64ndarray ] ): float64ndarray; + + +// EXPORTS // + +export = dxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/types/test.ts new file mode 100644 index 000000000000..cabafe35dee2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import dxmy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dxmy( [ x, y ] ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + dxmy( '10' ); // $ExpectError + dxmy( 5 ); // $ExpectError + dxmy( true ); // $ExpectError + dxmy( false ); // $ExpectError + dxmy( null ); // $ExpectError + dxmy( undefined ); // $ExpectError + dxmy( [] ); // $ExpectError + dxmy( {} ); // $ExpectError + dxmy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float64' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float64' + }); + + dxmy(); // $ExpectError + dxmy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/examples/index.js new file mode 100644 index 000000000000..467e2f8e168e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var dxmy = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( y ) ); + +dxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/lib/index.js new file mode 100644 index 000000000000..2ef1ac8d8775 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/dxmy +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* var dxmy = require( '@stdlib/blas/ext/base/ndarray/dxmy' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = dxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/lib/main.js new file mode 100644 index 000000000000..e79dce150e4c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/dxmy' ).ndarray; + + +// MAIN // + +/** +* Multiplies elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var Float64Vector = require( '@stdlib/ndarray/vector/float64' ); +* +* var x = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var y = new Float64Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = dxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ +function dxmy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = dxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/package.json new file mode 100644 index 000000000000..23db04d61100 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/dxmy", + "version": "0.0.0", + "description": "Multiply elements of a one-dimensional double-precision floating-point ndarray by the corresponding elements of a second one-dimensional double-precision floating-point ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "dxmy", + "xmy", + "multiply", + "multiplication", + "product", + "vector", + "strided", + "array", + "ndarray", + "float64", + "double", + "double-precision" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/test/test.js new file mode 100644 index 000000000000..9808017488b2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/dxmy/test/test.js @@ -0,0 +1,234 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var dxmy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float64Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof dxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( dxmy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0 ] ); + ybuf = new Float64Array( [ 1.0, 2.0, -3.0, 4.0, -1.0 ] ); + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + expected = new Float64Array([ + -2.0, // -2.0 * 1.0 + 2.0, // 1.0 * 2.0 + -9.0, // 3.0 * (-3.0) + -20.0, // -5.0 * 4.0 + -4.0 // 4.0 * (-1.0) + ]); + + actual = dxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-unit strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array([ + -2.0, // 0 + 1.0, + 3.0, // 1 + -5.0, + 4.0, // 2 + 0.0, + -1.0, // 3 + -3.0 + ]); + ybuf = new Float64Array([ + 1.0, // 0 + 2.0, + -3.0, // 1 + 4.0, + -1.0, // 2 + 0.0, + 3.0, // 3 + 2.0 + ]); + x = vector( xbuf, 4, 2, 0 ); + y = vector( ybuf, 4, 2, 0 ); + expected = new Float64Array([ + -2.0, // -2.0 * 1.0 + 2.0, + -9.0, // 3.0 * (-3.0) + 4.0, + -4.0, // 4.0 * (-1.0) + 0.0, + -3.0, // -1.0 * 3.0 + 2.0 + ]); + + actual = dxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array([ + -2.0, // 4 + 1.0, // 3 + 3.0, // 2 + -5.0, // 1 + 4.0 // 0 + ]); + ybuf = new Float64Array([ + 1.0, // 4 + 2.0, // 3 + -3.0, // 2 + 4.0, // 1 + -1.0 // 0 + ]); + x = vector( xbuf, 5, -1, 4 ); + y = vector( ybuf, 5, -1, 4 ); + expected = new Float64Array([ + -2.0, // -2.0 * 1.0 + 2.0, // 1.0 * 2.0 + -9.0, // 3.0 * (-3.0) + -20.0, // -5.0 * 4.0 + -4.0 // 4.0 * (-1.0) + ]); + + actual = dxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array([ + 1.0, + -2.0, + 3.0, // 0 + -5.0, // 1 + 4.0, // 2 + 0.0 + ]); + ybuf = new Float64Array([ + 1.0, + -2.0, + 0.0, // 0 + 4.0, // 1 + -1.0, // 2 + 0.0 + ]); + x = vector( xbuf, 3, 1, 2 ); + y = vector( ybuf, 3, 1, 2 ); + expected = new Float64Array([ + 1.0, + -2.0, + 0.0, // 3.0 * 0.0 + -20.0, // -5.0 * 4.0 + -4.0, // 4.0 * (-1.0) + 0.0 + ]); + + actual = dxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the output ndarray unchanged when the input ndarrays are empty', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float64Array( [] ); + ybuf = new Float64Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + expected = new Float64Array( [] ); + + actual = dxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/README.md new file mode 100644 index 000000000000..efac896ae8b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/README.md @@ -0,0 +1,109 @@ + + +# gany + +> Test whether at least one element in a one-dimensional ndarray is truthy. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gany = require( '@stdlib/blas/ext/base/ndarray/gany' ); +``` + +#### gany( arrays ) + +Tests whether at least one element in a one-dimensional ndarray is truthy. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); + +var x = vector( [ 0.0, 0.0, 1.0, 1.0 ], 'generic' ); + +var v = gany( [ x ] ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray. + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `false`. +- The function explicitly treats `NaN` values as falsy. + +
+ + + +
+ +## Examples + + + +```javascript +var bernoulli = require( '@stdlib/random/bernoulli' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gany = require( '@stdlib/blas/ext/base/ndarray/gany' ); + +var x = bernoulli( [ 10 ], 0.2, { + 'dtype': 'generic' +}); +console.log( ndarray2array( x ) ); + +var v = gany( [ x ] ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/benchmark/benchmark.js new file mode 100644 index 000000000000..5b64c82805c8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/benchmark/benchmark.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gany = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( [ len ], options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gany( [ x ] ); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/repl.txt new file mode 100644 index 000000000000..3ca50a62fb9d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/repl.txt @@ -0,0 +1,26 @@ + +{{alias}}( arrays ) + Tests whether at least one element in a one-dimensional ndarray is truthy. + + If provided an empty one-dimensional ndarray, the function returns `false`. + + The function explicitly treats `NaN` values as falsy. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray. + + Returns + ------- + bool: boolean + Boolean indicating whether at least one element is truthy. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 0.0, 0.0, 1.0, 1.0 ], 'generic' ); + > {{alias}}( [ x ] ) + true + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/types/index.d.ts new file mode 100644 index 000000000000..f7fdba5b75bc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Tests whether at least one element in a one-dimensional ndarray is truthy. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* +* - The function explicitly treats `NaN` values as falsy. +* +* @param arrays - array-like object containing ndarrays +* @returns boolean indicating whether at least one element is truthy +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 0.0, 0.0, 1.0, 1.0 ], 'generic' ); +* +* var v = gany( [ x ] ); +* // returns true +*/ +declare function gany( arrays: [ typedndarray ] ): boolean; + + +// EXPORTS // + +export = gany; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/types/test.ts new file mode 100644 index 000000000000..316d7155e415 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import gany = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gany( [ x ] ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gany( '10' ); // $ExpectError + gany( 10 ); // $ExpectError + gany( true ); // $ExpectError + gany( false ); // $ExpectError + gany( null ); // $ExpectError + gany( undefined ); // $ExpectError + gany( [] ); // $ExpectError + gany( {} ); // $ExpectError + gany( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gany(); // $ExpectError + gany( [ x ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/examples/index.js new file mode 100644 index 000000000000..3e13b180d746 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var bernoulli = require( '@stdlib/random/bernoulli' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gany = require( './../lib' ); + +var x = bernoulli( [ 10 ], 0.2, { + 'dtype': 'generic' +}); +console.log( ndarray2array( x ) ); + +var v = gany( [ x ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/lib/index.js new file mode 100644 index 000000000000..e6db1fbd3aff --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test whether at least one element in a one-dimensional ndarray is truthy. +* +* @module @stdlib/blas/ext/base/ndarray/gany +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var gany = require( '@stdlib/blas/ext/base/ndarray/gany' ); +* +* var x = vector( [ 0.0, 0.0, 1.0, 1.0 ], 'generic' ); +* +* var v = gany( [ x ] ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/lib/main.js new file mode 100644 index 000000000000..8a57813a8ab9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/lib/main.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/gany' ).ndarray; + + +// MAIN // + +/** +* Tests whether at least one element in a one-dimensional ndarray is truthy. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* +* - The function explicitly treats `NaN` values as falsy. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {boolean} boolean indicating whether at least one element is truthy +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 0.0, 0.0, 1.0, 1.0 ], 'generic' ); +* +* var v = gany( [ x ] ); +* // returns true +*/ +function gany( arrays ) { + var x = arrays[ 0 ]; + return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gany; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/package.json new file mode 100644 index 000000000000..7935ede3d12d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/gany", + "version": "0.0.0", + "description": "Test whether at least one element in a one-dimensional ndarray is truthy.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "any", + "gany", + "truthy", + "boolean", + "strided", + "ndarray", + "generic" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/test/test.js new file mode 100644 index 000000000000..2612996acc0f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gany/test/test.js @@ -0,0 +1,155 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var gany = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gany, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( gany.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function tests whether at least one element in a one-dimensional ndarray is truthy', function test( t ) { + var x; + var v; + + x = [ 0, 0, 1, 1 ]; + v = gany( [ vector( x, 4, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + x = [ 0, 0, 0, 0, 0 ]; + v = gany( [ vector( x, 5, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = [ 1, 0, 0 ]; + v = gany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + x = [ -0, 0, -0 ]; + v = gany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = [ -1, 0, 0 ]; + v = gany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `false`', function test( t ) { + var x; + var v; + + x = []; + + v = gany( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = [ + 0, // 0 + 1, + 0, // 1 + 1, + 0, // 2 + 1, + 0, // 3 + 1 + ]; + v = gany( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, false, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = [ + 1, // 3 + 0, + 0, // 2 + 0, + 0, // 1 + 0, + 0, // 0 + 0 + ]; + v = gany( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = [ + 1, + 0, // 0 + 1, + 0, // 1 + 1, + 0, // 2 + 1, + 0 // 3 + ]; + v = gany( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/README.md new file mode 100644 index 000000000000..4e2337bb1b2e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/README.md @@ -0,0 +1,132 @@ + + +# gfillNotEqual + +> Replace elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/gfill-not-equal' ); +``` + +#### gfillNotEqual( arrays ) + +Replaces elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ], 'generic' ); + +var searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' +}); + +var alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' +}); + +gfillNotEqual( [ x, searchElement, alpha ] ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + +
+ + + +
+ +## Notes + +- The input ndarray is modified **in-place** (i.e., the input ndarray is **mutated**). +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var gfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/gfill-not-equal' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +gfillNotEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..4a4fdca081f9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfillNotEqual = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var searchElement; + var alpha; + var x; + + x = uniform( [ len ], -100.0, 100.0, options ); + searchElement = scalar2ndarray( 0.0, options ); + alpha = scalar2ndarray( 5.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfillNotEqual( [ x, searchElement, alpha ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/repl.txt new file mode 100644 index 000000000000..d563c6f0a4f0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/repl.txt @@ -0,0 +1,40 @@ + +{{alias}}( arrays ) + Replaces elements in a one-dimensional ndarray not equal to a provided + search element with a specified scalar constant. + + The input ndarray is modified *in-place* (i.e., the input ndarray is + *mutated*). + + When comparing elements, the function checks for equality using the strict + equality operator `===`. As a consequence, `NaN` values are considered + distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements + are always replaced), and `-0` and `+0` are considered the same. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var buf = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( buf, 'generic' ); + > var opts = { 'dtype': 'generic' }; + > var v = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, opts ); + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, opts ); + > {{alias}}( [ x, v, alpha ] ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..258a99187659 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Replaces elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. +* +* @param arrays - array-like object containing ndarrays +* @returns input ndarray +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ], 'generic' ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'generic' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'generic' +* }); +* +* var out = gfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +declare function gfillNotEqual = typedndarray>( arrays: [ T, typedndarray, typedndarray ] ): T; + + +// EXPORTS // + +export = gfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..61a1cce5cc88 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/docs/types/test.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import gfillNotEqual = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + gfillNotEqual( [ x, searchElement, alpha ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gfillNotEqual( '10' ); // $ExpectError + gfillNotEqual( 5 ); // $ExpectError + gfillNotEqual( true ); // $ExpectError + gfillNotEqual( false ); // $ExpectError + gfillNotEqual( null ); // $ExpectError + gfillNotEqual( undefined ); // $ExpectError + gfillNotEqual( [] ); // $ExpectError + gfillNotEqual( {} ); // $ExpectError + gfillNotEqual( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + gfillNotEqual(); // $ExpectError + gfillNotEqual( [ x, searchElement, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/examples/index.js new file mode 100644 index 000000000000..5341cb4b9c75 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var gfillNotEqual = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +gfillNotEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/lib/index.js new file mode 100644 index 000000000000..c5a52876a70d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/lib/index.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/ndarray/gfill-not-equal +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var gfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/gfill-not-equal' ); +* +* var x = vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ], 'generic' ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'generic' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'generic' +* }); +* +* var out = gfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/lib/main.js new file mode 100644 index 000000000000..58bc94c25612 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/lib/main.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/gfill-not-equal' ).ndarray; +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); + + +// MAIN // + +/** +* Replaces elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} input ndarray +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ], 'generic' ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'generic' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'generic' +* }); +* +* var out = gfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function gfillNotEqual( arrays ) { + var searchElement; + var alpha; + var x; + + x = arrays[ 0 ]; + searchElement = ndarraylike2scalar( arrays[ 1 ] ); + alpha = ndarraylike2scalar( arrays[ 2 ] ); + strided( numelDimension( x, 0 ), searchElement, alpha, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = gfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/package.json new file mode 100644 index 000000000000..e682b543fa90 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/gfill-not-equal", + "version": "0.0.0", + "description": "Replace elements in a one-dimensional ndarray not equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "fill", + "not equal", + "unequal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "generic" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/test/test.js new file mode 100644 index 000000000000..3e8af1d0ac30 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfill-not-equal/test/test.js @@ -0,0 +1,299 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameArray = require( '@stdlib/assert/is-same-array' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var gfillNotEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function replaces elements not equal to a provided search element', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + x = vector( xbuf, 6, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ]; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + x = vector( xbuf, 3, 2, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ]; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + x = vector( xbuf, 3, -2, 4 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ]; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-zero offset', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ]; + x = vector( xbuf, 3, 1, 3 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ 0.0, -2.0, 3.0, 0.0, 5.0, 5.0 ]; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns the input ndarray unchanged', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ 0.0, 0.0, 0.0, 0.0 ]; + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ 0.0, 0.0, 0.0, 0.0 ]; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ NaN, 1.0, NaN ]; + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( NaN, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ 5.0, 5.0, 5.0 ]; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ NaN, 0.0, NaN ]; + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ 5.0, 0.0, 5.0 ]; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = [ -0.0, 1.0, 0.0, -0.0 ]; + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + t.strictEqual( isSameArray( xbuf, expected ), true, 'returns expected value' ); + + xbuf = [ -0.0, 1.0, 0.0, -0.0 ]; + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( -0.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = [ -0.0, 5.0, 0.0, -0.0 ]; + t.strictEqual( isSameArray( xbuf, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the input ndarray unchanged when the input ndarray is empty', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = []; + x = vector( xbuf, 0, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'generic' + }); + + actual = gfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = []; + t.deepEqual( xbuf, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/README.md new file mode 100644 index 000000000000..3849f8561ece --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/README.md @@ -0,0 +1,128 @@ + + +# gfirstIndexLessThan + +> Return the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gfirstIndexLessThan = require( '@stdlib/blas/ext/base/ndarray/gfirst-index-less-than' ); +``` + +#### gfirstIndexLessThan( arrays ) + +Returns the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); + +var x = vector( [ 0.0, 0.0, 0.0, 0.0 ], 'generic' ); +var y = vector( [ 0.0, 0.0, 1.0, 0.0 ], 'generic' ); + +var idx = gfirstIndexLessThan( [ x, y ] ); +// returns 2 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - first one-dimensional input ndarray. + - second one-dimensional input ndarray. + +If the function is unable to find an element in the first one-dimensional input ndarray which is less than a corresponding element in the second one-dimensional input ndarray, the function returns `-1`. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); + +var x = vector( [ 5.0, 6.0, 7.0, 8.0 ], 'generic' ); +var y = vector( [ 1.0, 2.0, 3.0, 4.0 ], 'generic' ); + +var idx = gfirstIndexLessThan( [ x, y ] ); +// returns -1 +``` + +
+ + + +
+ +## Notes + +- When comparing elements, the function checks whether an element in the first one-dimensional input ndarray is less than a corresponding element in the second one-dimensional input ndarray using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gfirstIndexLessThan = require( '@stdlib/blas/ext/base/ndarray/gfirst-index-less-than' ); + +var opts = { + 'dtype': 'generic' +}; +var x = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( y ) ); + +var idx = gfirstIndexLessThan( [ x, y ] ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/benchmark/benchmark.js new file mode 100644 index 000000000000..b9570f0d2cbf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/benchmark/benchmark.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var pow = require( '@stdlib/math/base/special/pow' ); +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gfirstIndexLessThan = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = vector( ones( len, options.dtype ), options.dtype ); + var y = vector( ones( len, options.dtype ), options.dtype ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gfirstIndexLessThan( [ x, y ] ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/repl.txt new file mode 100644 index 000000000000..2b3d1c70f718 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/repl.txt @@ -0,0 +1,32 @@ + +{{alias}}( arrays ) + Returns the index of the first element in a one-dimensional ndarray which is + less than a corresponding element in another one-dimensional ndarray. + + When comparing elements, the function checks whether an element in the first + one-dimensional input ndarray is less than a corresponding element in the + second one-dimensional input ndarray using the less-than operator `<`. As a + consequence, comparisons involving `NaN` always evaluate to `false`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - first one-dimensional input ndarray. + - second one-dimensional input ndarray. + + Returns + ------- + out: integer + Index. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 0.0, 0.0, 0.0, 0.0 ], 'generic' ); + > var y = {{alias:@stdlib/ndarray/vector/ctor}}( [ 0.0, 0.0, 1.0, 0.0 ], 'generic' ); + > {{alias}}( [ x, y ] ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/types/index.d.ts new file mode 100644 index 000000000000..56144c2690bf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/types/index.d.ts @@ -0,0 +1,54 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Returns the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - first one-dimensional input ndarray. +* - second one-dimensional input ndarray. +* +* - When comparing elements, the function checks whether an element in the first one-dimensional input ndarray is less than a corresponding element in the second one-dimensional input ndarray using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. +* +* @param arrays - array-like object containing ndarrays +* @returns index +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 0.0, 0.0, 0.0, 0.0 ], 'generic' ); +* var y = vector( [ 0.0, 0.0, 1.0, 0.0 ], 'generic' ); +* +* var idx = gfirstIndexLessThan( [ x, y ] ); +* // returns 2 +*/ +declare function gfirstIndexLessThan( arrays: [ typedndarray, typedndarray ] ): number; + + +// EXPORTS // + +export = gfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/types/test.ts new file mode 100644 index 000000000000..4c1fc8b25eea --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import gfirstIndexLessThan = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gfirstIndexLessThan( [ x, y ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gfirstIndexLessThan( '10' ); // $ExpectError + gfirstIndexLessThan( 10 ); // $ExpectError + gfirstIndexLessThan( true ); // $ExpectError + gfirstIndexLessThan( false ); // $ExpectError + gfirstIndexLessThan( null ); // $ExpectError + gfirstIndexLessThan( undefined ); // $ExpectError + gfirstIndexLessThan( [] ); // $ExpectError + gfirstIndexLessThan( {} ); // $ExpectError + gfirstIndexLessThan( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gfirstIndexLessThan(); // $ExpectError + gfirstIndexLessThan( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/examples/index.js new file mode 100644 index 000000000000..35c2479426f2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gfirstIndexLessThan = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; +var x = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 0, 10, opts ); +console.log( ndarray2array( y ) ); + +var idx = gfirstIndexLessThan( [ x, y ] ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/lib/index.js new file mode 100644 index 000000000000..f8e50426a29c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/gfirst-index-less-than +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var gfirstIndexLessThan = require( '@stdlib/blas/ext/base/ndarray/gfirst-index-less-than' ); +* +* var x = vector( [ 0.0, 0.0, 0.0, 0.0 ], 'generic' ); +* var y = vector( [ 0.0, 0.0, 1.0, 0.0 ], 'generic' ); +* +* var idx = gfirstIndexLessThan( [ x, y ] ); +* // returns 2 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/lib/main.js new file mode 100644 index 000000000000..d76ea8ec3554 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/lib/main.js @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/gfirst-index-less-than' ).ndarray; + + +// MAIN // + +/** +* Returns the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - first one-dimensional input ndarray. +* - second one-dimensional input ndarray. +* +* - When comparing elements, the function checks whether an element in the first one-dimensional input ndarray is less than a corresponding element in the second one-dimensional input ndarray using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {integer} index +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 0.0, 0.0, 0.0, 0.0 ], 'generic' ); +* var y = vector( [ 0.0, 0.0, 1.0, 0.0 ], 'generic' ); +* +* var idx = gfirstIndexLessThan( [ x, y ] ); +* // returns 2 +*/ +function gfirstIndexLessThan( arrays ) { + var x = arrays[ 0 ]; + var y = arrays[ 1 ]; + return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/package.json new file mode 100644 index 000000000000..2f39b41ca260 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/gfirst-index-less-than", + "version": "0.0.0", + "description": "Return the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "array", + "index", + "search", + "find", + "less", + "compare", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/test/test.js new file mode 100644 index 000000000000..c3e984da4741 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gfirst-index-less-than/test/test.js @@ -0,0 +1,193 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var gfirstIndexLessThan = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a one-dimensional ndarray which is less than a corresponding element in another one-dimensional ndarray', function test( t ) { + var actual; + var x; + var y; + + x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], 6, 1, 0 ); + y = vector( [ 2.0, 2.0, 2.0, 3.0, 4.0, 5.0 ], 6, 1, 0 ); + + actual = gfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = vector( [ 2.0, 1.0, 3.0, 4.0, 5.0, 6.0 ], 6, 1, 0 ); + y = vector( [ 1.0, 2.0, 2.0, 3.0, 4.0, 5.0 ], 6, 1, 0 ); + + actual = gfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = vector( [ 2.0, 2.0, 2.0, 4.0, 5.0, 6.0 ], 6, 1, 0 ); + y = vector( [ 1.0, 2.0, 3.0, 5.0, 4.0, 5.0 ], 6, 1, 0 ); + + actual = gfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = vector( [ 2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], 6, 1, 0 ); + y = vector( [ 1.0, 2.0, 2.0, 3.0, 4.0, 5.0 ], 6, 1, 0 ); + + actual = gfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if unable to find an element in the first one-dimensional input ndarray which is less than a corresponding element in the second one-dimensional input ndarray', function test( t ) { + var actual; + var x; + var y; + + x = vector( [ 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ], 6, 1, 0 ); + y = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ], 6, 1, 0 ); + + actual = gfirstIndexLessThan( [ x, y ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 2.0, // 0 + 2.0, + 2.0, // 1 + -4.0, + 3.0, // 2 + 3.0, + 5.0, // 3 + 2.0 + ]; + y = [ + 1.0, // 0 + 2.0, + 1.0, // 1 + -4.0, + 4.0, // 2 + 3.0, + 4.0, // 3 + 2.0 + ]; + + actual = gfirstIndexLessThan( [ vector( x, 4, 2, 0 ), vector( y, 4, 2, 0 ) ] ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var actual; + var x; + var y; + + x = [ + 1.0, // 3 + 2.0, + 2.0, // 2 + -2.0, + 3.0, // 1 + 4.0, + 5.0, // 0 + 2.0 + ]; + y = [ + 4.0, // 3 + 2.0, + 3.0, // 2 + -2.0, + 4.0, // 1 + 4.0, + 4.0, // 0 + 2.0 + ]; + + actual = gfirstIndexLessThan( [ vector( x, 4, -2, 6 ), vector( y, 4, -2, 6 ) ] ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var actual; + var x; + var y; + + x = [ + 2.0, + 1.0, // 0 + 2.0, + 2.0, // 1 + -2.0, + 3.0, // 2 + 3.0, + 4.0 // 3 + ]; + y = [ + 2.0, + 2.0, // 0 + 2.0, + 3.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 5.0 // 3 + ]; + + actual = gfirstIndexLessThan( [ vector( x, 4, 2, 1 ), vector( y, 4, 2, 1 ) ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-falsy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-falsy/README.md index 5fdffdc55614..657227c61cf3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-falsy/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-falsy/README.md @@ -51,9 +51,7 @@ var idx = gindexOfFalsy( [ x ] ); The function has the following parameters: -- **arrays**: array-like object containing the following ndarrays: - - - a one-dimensional input ndarray. +- **arrays**: array-like object containing a one-dimensional input ndarray. If the function is unable to find a falsy element, the function returns `-1`. diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/README.md new file mode 100644 index 000000000000..1b097db1311f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/README.md @@ -0,0 +1,139 @@ + + +# gindexOfNotEqual + +> Return the first index of an element in a one-dimensional ndarray which is not equal to a specified search element. + +
+ +
+ + + +
+ +## Usage + +```javascript +var gindexOfNotEqual = require( '@stdlib/blas/ext/base/ndarray/gindex-of-not-equal' ); +``` + +#### gindexOfNotEqual( arrays ) + +Returns the first index of an element in a one-dimensional ndarray which is not equal to a specified search element. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = vector( [ 1.0, 1.0, 3.0 ], 'generic' ); + +var searchElement = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +var idx = gindexOfNotEqual( [ x, searchElement ] ); +// returns 2 +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + +If the function is unable to find an element which is not equal to a specified search element, the function returns `-1`. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = vector( [ 1.0, 1.0, 1.0 ], 'generic' ); + +var searchElement = scalar2ndarray( 1.0, { + 'dtype': 'generic' +}); + +var idx = gindexOfNotEqual( [ x, searchElement ] ); +// returns -1 +``` + +
+ + + +
+ +## Notes + +- When searching for a search element, the function checks for inequality using the strict inequality operator `!==`. As a consequence, `NaN` values are considered distinct from all values (including other `NaN` values), and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var gindexOfNotEqual = require( '@stdlib/blas/ext/base/ndarray/gindex-of-not-equal' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], 0, 2, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 0, opts ); +console.log( 'Search Element:', ndarraylike2scalar( searchElement ) ); + +var idx = gindexOfNotEqual( [ x, searchElement ] ); +console.log( idx ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..5409d6e5a284 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var pow = require( '@stdlib/math/base/special/pow' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gindexOfNotEqual = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var searchElement; + var x; + + x = zeros( [ len ], options ); + searchElement = scalar2ndarray( 0.0, options ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gindexOfNotEqual( [ x, searchElement ] ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/repl.txt new file mode 100644 index 000000000000..bba8a7c46b76 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/repl.txt @@ -0,0 +1,35 @@ + +{{alias}}( arrays ) + Returns the first index of an element in a one-dimensional ndarray which is + not equal to a specified search element. + + When searching for a search element, the function checks for inequality + using the strict inequality operator `!==`. As a consequence, `NaN` values + are considered distinct from all values (including other `NaN` values), and + `-0` and `+0` are considered the same. + + If unable to find an element which is not equal to a specified search + element, the function returns `-1`. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + + Returns + ------- + out: integer + Index. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 1.0, 1.0, 3.0 ], 'generic' ); + > var v = {{alias:@stdlib/ndarray/from-scalar}}( 1.0, { 'dtype': 'generic' } ); + > {{alias}}( [ x, v ] ) + 2 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..baa3e589cb15 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/types/index.d.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Returns the first index of an element in a one-dimensional ndarray which is not equal to a specified search element. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* +* @param arrays - array-like object containing ndarrays +* @returns index +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = vector( [ 1.0, 1.0, 3.0 ], 'generic' ); +* +* var searchElement = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var v = gindexOfNotEqual( [ x, searchElement ] ); +* // returns 2 +*/ +declare function gindexOfNotEqual( arrays: [ typedndarray, typedndarray ] ): number; + + +// EXPORTS // + +export = gindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..0bfe0dadd7ef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/docs/types/test.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import gindexOfNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + + gindexOfNotEqual( [ x, searchElement ] ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gindexOfNotEqual( '10' ); // $ExpectError + gindexOfNotEqual( 10 ); // $ExpectError + gindexOfNotEqual( true ); // $ExpectError + gindexOfNotEqual( false ); // $ExpectError + gindexOfNotEqual( null ); // $ExpectError + gindexOfNotEqual( undefined ); // $ExpectError + gindexOfNotEqual( [] ); // $ExpectError + gindexOfNotEqual( {} ); // $ExpectError + gindexOfNotEqual( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + + gindexOfNotEqual(); // $ExpectError + gindexOfNotEqual( [ x, searchElement ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/examples/index.js new file mode 100644 index 000000000000..253390c037c3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var gindexOfNotEqual = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], 0, 2, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 0, opts ); +console.log( 'Search Element:', ndarraylike2scalar( searchElement ) ); + +var idx = gindexOfNotEqual( [ x, searchElement ] ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/lib/index.js new file mode 100644 index 000000000000..cd48bc5152c3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/lib/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the first index of an element in a one-dimensional ndarray which is not equal to a specified search element. +* +* @module @stdlib/blas/ext/base/ndarray/gindex-of-not-equal +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var gindexOfNotEqual = require( '@stdlib/blas/ext/base/ndarray/gindex-of-not-equal' ); +* +* var x = vector( [ 1.0, 1.0, 3.0 ], 'generic' ); +* +* var searchElement = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var v = gindexOfNotEqual( [ x, searchElement ] ); +* // returns 2 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/lib/main.js new file mode 100644 index 000000000000..6134b4461d72 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/gindex-of-not-equal' ).ndarray; +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); + + +// MAIN // + +/** +* Returns the first index of an element in a one-dimensional ndarray which is not equal to a specified search element. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {integer} index +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = vector( [ 1.0, 1.0, 3.0 ], 'generic' ); +* +* var searchElement = scalar2ndarray( 1.0, { +* 'dtype': 'generic' +* }); +* +* var v = gindexOfNotEqual( [ x, searchElement ] ); +* // returns 2 +*/ +function gindexOfNotEqual( arrays ) { + var x = arrays[ 0 ]; + return strided( numelDimension( x, 0 ), ndarraylike2scalar( arrays[ 1 ] ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = gindexOfNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/package.json new file mode 100644 index 000000000000..d50fa060053c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/gindex-of-not-equal", + "version": "0.0.0", + "description": "Return the first index of an element in a one-dimensional ndarray which is not equal to a specified search element.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "array", + "index", + "search", + "get", + "not equal", + "unequal", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/test/test.js new file mode 100644 index 000000000000..4a610e224cbc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gindex-of-not-equal/test/test.js @@ -0,0 +1,226 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var gindexOfNotEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gindexOfNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first element in a one-dimensional ndarray which is not equal to a provided search element', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ], 6, 1, 0 ); + + searchElement = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + searchElement = scalar2ndarray( 3.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + searchElement = scalar2ndarray( 4.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if every element in a one-dimensional ndarray is equal to a provided search element', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ 2.0, 2.0, 2.0 ], 3, 1, 0 ); + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `NaN` elements to be not equal to a provided search element', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ 1.0, NaN, 1.0 ], 3, 1, 0 ); + searchElement = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the index of the first element if a provided search element is `NaN`', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ NaN, 1.0 ], 2, 1, 0 ); + searchElement = scalar2ndarray( NaN, { + 'dtype': 'generic' + }); + + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be equal', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ -0.0, 0.0 ], 2, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'generic' + }); + + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ 2.0, 9.0, 2.0, 9.0, 3.0, 9.0 ], 3, 2, 0 ); + + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + searchElement = scalar2ndarray( 9.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ 2.0, 1.0, 2.0, 2.0, 3.0, 3.0 ], 6, -1, 5 ); + + searchElement = scalar2ndarray( 3.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 2, 'returns expected value' ); + + searchElement = scalar2ndarray( 1.0, { + 'dtype': 'generic' + }); + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ], 3, 1, 3 ); + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an empty one-dimensional ndarray', function test( t ) { + var searchElement; + var actual; + var x; + + x = vector( [], 0, 1, 0 ); + searchElement = scalar2ndarray( 2.0, { + 'dtype': 'generic' + }); + + actual = gindexOfNotEqual( [ x, searchElement ] ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/package.json index b55c20e6e1ad..651a8686d5e8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansum/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/gnansum", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional ndarray, ignoring `NaN` values.", + "description": "Compute the sum of a one-dimensional ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/package.json index 3205f819e46b..c059879e9beb 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/gnansumkbn", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional ndarray, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.", + "description": "Compute the sum of a one-dimensional ndarray, ignoring NaN values and using an improved Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/package.json index 171e3fd5f59b..6c1fc183ce43 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumkbn2/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/gnansumkbn2", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional ndarray, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.", + "description": "Compute the sum of a one-dimensional ndarray, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/package.json index 5c8e3b05aede..eace71f78e3c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/gnansumors", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional ndarray, ignoring `NaN` values and using ordinary recursive summation.", + "description": "Compute the sum of a one-dimensional ndarray, ignoring NaN values and using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/package.json index e93a8404a471..0867bab3bbcd 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gnansumpw/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/gnansumpw", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional ndarray, ignoring `NaN` values and using pairwise summation.", + "description": "Compute the sum of a one-dimensional ndarray, ignoring NaN values and using pairwise summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/README.md new file mode 100644 index 000000000000..92588f4e75bd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/README.md @@ -0,0 +1,132 @@ + + +# gxdy + +> Divide elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var gxdy = require( '@stdlib/blas/ext/base/ndarray/gxdy' ); +``` + +#### gxdy( arrays ) + +Divides elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); + +var x = vector( [ 4.0, 6.0, 12.0, 20.0, 30.0 ], 'generic' ); +var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); + +gxdy( [ x, y ] ); +// y => [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gxdy = require( '@stdlib/blas/ext/base/ndarray/gxdy' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( y ) ); + +gxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..dba5b4cb3cb7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gxdy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -100.0, 100.0, options ); + var y = uniform( [ len ], 1.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gxdy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/img/equation_xdy.svg b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/img/equation_xdy.svg new file mode 100644 index 000000000000..1b0e60ad95cf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/img/equation_xdy.svg @@ -0,0 +1,16 @@ + +bold y equals bold x circled-division-slash bold y + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/repl.txt new file mode 100644 index 000000000000..579425a834c9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/repl.txt @@ -0,0 +1,33 @@ + +{{alias}}( arrays ) + Divides elements of a one-dimensional ndarray by the corresponding elements + of a second one-dimensional ndarray and assigns the results to the second + ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 4.0, 6.0, 12.0, 20.0 ]; + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( xbuf, 'generic' ); + > var ybuf = [ 2.0, 3.0, 4.0, 5.0 ]; + > var y = {{alias:@stdlib/ndarray/vector/ctor}}( ybuf, 'generic' ); + > {{alias}}( [ x, y ] ) + [ 2.0, 2.0, 3.0, 4.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..c14ef1b550f7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Divides elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 4.0, 6.0, 12.0, 20.0, 30.0 ], 'generic' ); +* var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); +* +* var out = gxdy( [ x, y ] ); +* // returns [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +declare function gxdy = typedndarray>( arrays: [ typedndarray, T ] ): T; + + +// EXPORTS // + +export = gxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/types/test.ts new file mode 100644 index 000000000000..4b2567bf5a45 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import gxdy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gxdy( [ x, y ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gxdy( '10' ); // $ExpectError + gxdy( 5 ); // $ExpectError + gxdy( true ); // $ExpectError + gxdy( false ); // $ExpectError + gxdy( null ); // $ExpectError + gxdy( undefined ); // $ExpectError + gxdy( [] ); // $ExpectError + gxdy( {} ); // $ExpectError + gxdy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gxdy(); // $ExpectError + gxdy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/examples/index.js new file mode 100644 index 000000000000..3e9b8835db70 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gxdy = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( y ) ); + +gxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/lib/index.js new file mode 100644 index 000000000000..cc3a5e8208d3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Divide elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/gxdy +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var gxdy = require( '@stdlib/blas/ext/base/ndarray/gxdy' ); +* +* var x = vector( [ 4.0, 6.0, 12.0, 20.0, 30.0 ], 'generic' ); +* var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); +* +* var out = gxdy( [ x, y ] ); +* // returns [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/lib/main.js new file mode 100644 index 000000000000..e91d9101e056 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/gxdy' ).ndarray; + + +// MAIN // + +/** +* Divides elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 4.0, 6.0, 12.0, 20.0, 30.0 ], 'generic' ); +* var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); +* +* var out = gxdy( [ x, y ] ); +* // returns [ 2.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function gxdy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = gxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/package.json new file mode 100644 index 000000000000..b66d8efe4789 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/gxdy", + "version": "0.0.0", + "description": "Divide elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "gxdy", + "xdy", + "divide", + "division", + "vector", + "strided", + "array", + "ndarray", + "generic" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/test/test.js new file mode 100644 index 000000000000..4b1d0ecf19b3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxdy/test/test.js @@ -0,0 +1,233 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var gxdy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( gxdy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ -2.0, 1.0, 3.0, -5.0, 4.0 ]; + ybuf = [ 1.0, 2.0, -3.0, 5.0, -1.0 ]; + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + expected = [ + -2.0, // -2.0 / 1.0 + 0.5, // 1.0 / 2.0 + -1.0, // 3.0 / (-3.0) + -1.0, // -5.0 / 5.0 + -4.0 // 4.0 / (-1.0) + ]; + + actual = gxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-unit strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ + -2.0, // 0 + 1.0, + 3.0, // 1 + -5.0, + 4.0, // 2 + 0.0, + -1.0, // 3 + -3.0 + ]; + ybuf = [ + 1.0, // 0 + 2.0, + -3.0, // 1 + 4.0, + -1.0, // 2 + 0.0, + 2.0, // 3 + 2.0 + ]; + x = vector( xbuf, 4, 2, 0 ); + y = vector( ybuf, 4, 2, 0 ); + expected = [ + -2.0, // -2.0 / 1.0 + 2.0, + -1.0, // 3.0 / (-3.0) + 4.0, + -4.0, // 4.0 / (-1.0) + 0.0, + -0.5, // -1.0 / 2.0 + 2.0 + ]; + + actual = gxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ + -2.0, // 4 + 1.0, // 3 + 3.0, // 2 + -5.0, // 1 + 4.0 // 0 + ]; + ybuf = [ + 1.0, // 4 + 2.0, // 3 + -3.0, // 2 + 5.0, // 1 + -1.0 // 0 + ]; + x = vector( xbuf, 5, -1, 4 ); + y = vector( ybuf, 5, -1, 4 ); + expected = [ + -2.0, // -2.0 / 1.0 + 0.5, // 1.0 / 2.0 + -1.0, // 3.0 / (-3.0) + -1.0, // -5.0 / 5.0 + -4.0 // 4.0 / (-1.0) + ]; + + actual = gxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ + 1.0, + -2.0, + 3.0, // 0 + -5.0, // 1 + 4.0, // 2 + 0.0 + ]; + ybuf = [ + 1.0, + -2.0, + 1.0, // 0 + 5.0, // 1 + -1.0, // 2 + 0.0 + ]; + x = vector( xbuf, 3, 1, 2 ); + y = vector( ybuf, 3, 1, 2 ); + expected = [ + 1.0, + -2.0, + 3.0, // 3.0 / 1.0 + -1.0, // -5.0 / 5.0 + -4.0, // 4.0 / (-1.0) + 0.0 + ]; + + actual = gxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the output ndarray unchanged when the input ndarrays are empty', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = []; + ybuf = []; + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + expected = []; + + actual = gxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/README.md new file mode 100644 index 000000000000..494b50f4ad8f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/README.md @@ -0,0 +1,127 @@ + + +# gxmy + +> Multiply elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \odot \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var gxmy = require( '@stdlib/blas/ext/base/ndarray/gxmy' ); +``` + +#### gxmy( arrays ) + +Multiplies elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. + +```javascript +var vector = require( '@stdlib/ndarray/vector/ctor' ); + +var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' ); +var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); + +gxmy( [ x, y ] ); +// y => [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gxmy = require( '@stdlib/blas/ext/base/ndarray/gxmy' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( y ) ); + +gxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/benchmark/benchmark.js new file mode 100644 index 000000000000..1678646438c6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var gxmy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'generic' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -100.0, 100.0, options ); + var y = uniform( [ len ], -100.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = gxmy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/repl.txt new file mode 100644 index 000000000000..01778591ce58 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/repl.txt @@ -0,0 +1,33 @@ + +{{alias}}( arrays ) + Multiplies elements of a one-dimensional ndarray by the corresponding + elements of a second one-dimensional ndarray and assigns the results to the + second ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0, 4.0 ]; + > var x = {{alias:@stdlib/ndarray/vector/ctor}}( xbuf, 'generic' ); + > var ybuf = [ 2.0, 3.0, 4.0, 5.0 ]; + > var y = {{alias:@stdlib/ndarray/vector/ctor}}( ybuf, 'generic' ); + > {{alias}}( [ x, y ] ) + [ 2.0, 6.0, 12.0, 20.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/types/index.d.ts new file mode 100644 index 000000000000..54a275f65e27 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { typedndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' ); +* var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); +* +* var out = gxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ +declare function gxmy = typedndarray>( arrays: [ typedndarray, T ] ): T; + + +// EXPORTS // + +export = gxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/types/test.ts new file mode 100644 index 000000000000..c8c026bf57d3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import gxmy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gxmy( [ x, y ] ); // $ExpectType genericndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + gxmy( '10' ); // $ExpectError + gxmy( 5 ); // $ExpectError + gxmy( true ); // $ExpectError + gxmy( false ); // $ExpectError + gxmy( null ); // $ExpectError + gxmy( undefined ); // $ExpectError + gxmy( [] ); // $ExpectError + gxmy( {} ); // $ExpectError + gxmy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'generic' + }); + const y = zeros( [ 10 ], { + 'dtype': 'generic' + }); + + gxmy(); // $ExpectError + gxmy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/examples/index.js new file mode 100644 index 000000000000..74f0b4894561 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var gxmy = require( './../lib' ); + +var opts = { + 'dtype': 'generic' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( y ) ); + +gxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/lib/index.js new file mode 100644 index 000000000000..2cd4aa750a6f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/gxmy +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* var gxmy = require( '@stdlib/blas/ext/base/ndarray/gxmy' ); +* +* var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' ); +* var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); +* +* var out = gxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/lib/main.js new file mode 100644 index 000000000000..5e26540a2f3d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/gxmy' ).ndarray; + + +// MAIN // + +/** +* Multiplies elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var vector = require( '@stdlib/ndarray/vector/ctor' ); +* +* var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' ); +* var y = vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ], 'generic' ); +* +* var out = gxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ +function gxmy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = gxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/package.json new file mode 100644 index 000000000000..7a53deb31b7a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/gxmy", + "version": "0.0.0", + "description": "Multiply elements of a one-dimensional ndarray by the corresponding elements of a second one-dimensional ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "gxmy", + "xmy", + "multiply", + "multiplication", + "vector", + "strided", + "array", + "ndarray", + "generic" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/test/test.js new file mode 100644 index 000000000000..8e02648bd3d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/gxmy/test/test.js @@ -0,0 +1,233 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var gxmy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Collection} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( gxmy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ -2.0, 1.0, 3.0, -5.0, 4.0 ]; + ybuf = [ 1.0, 2.0, -3.0, 4.0, -1.0 ]; + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + expected = [ + -2.0, // -2.0 * 1.0 + 2.0, // 1.0 * 2.0 + -9.0, // 3.0 * (-3.0) + -20.0, // -5.0 * 4.0 + -4.0 // 4.0 * (-1.0) + ]; + + actual = gxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-unit strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ + -2.0, // 0 + 1.0, + 3.0, // 1 + -5.0, + 4.0, // 2 + 0.0, + -1.0, // 3 + -3.0 + ]; + ybuf = [ + 1.0, // 0 + 2.0, + -3.0, // 1 + 4.0, + -1.0, // 2 + 0.0, + 3.0, // 3 + 2.0 + ]; + x = vector( xbuf, 4, 2, 0 ); + y = vector( ybuf, 4, 2, 0 ); + expected = [ + -2.0, // -2.0 * 1.0 + 2.0, + -9.0, // 3.0 * (-3.0) + 4.0, + -4.0, // 4.0 * (-1.0) + 0.0, + -3.0, // -1.0 * 3.0 + 2.0 + ]; + + actual = gxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ + -2.0, // 4 + 1.0, // 3 + 3.0, // 2 + -5.0, // 1 + 4.0 // 0 + ]; + ybuf = [ + 1.0, // 4 + 2.0, // 3 + -3.0, // 2 + 4.0, // 1 + -1.0 // 0 + ]; + x = vector( xbuf, 5, -1, 4 ); + y = vector( ybuf, 5, -1, 4 ); + expected = [ + -2.0, // -2.0 * 1.0 + 2.0, // 1.0 * 2.0 + -9.0, // 3.0 * (-3.0) + -20.0, // -5.0 * 4.0 + -4.0 // 4.0 * (-1.0) + ]; + + actual = gxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = [ + 1.0, + -2.0, + 3.0, // 0 + -5.0, // 1 + 4.0, // 2 + 0.0 + ]; + ybuf = [ + 1.0, + -2.0, + 0.0, // 0 + 4.0, // 1 + -1.0, // 2 + 0.0 + ]; + x = vector( xbuf, 3, 1, 2 ); + y = vector( ybuf, 3, 1, 2 ); + expected = [ + 1.0, + -2.0, + 0.0, // 3.0 * 0.0 + -20.0, // -5.0 * 4.0 + -4.0, // 4.0 * (-1.0) + 0.0 + ]; + + actual = gxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the output ndarray unchanged when the input ndarrays are empty', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = []; + ybuf = []; + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + expected = []; + + actual = gxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js index fb5fc5343a01..be417fbff97e 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/lib/index.js @@ -99,6 +99,15 @@ setReadOnly( ns, 'csumkbn', require( '@stdlib/blas/ext/base/ndarray/csumkbn' ) ) */ setReadOnly( ns, 'cunitspace', require( '@stdlib/blas/ext/base/ndarray/cunitspace' ) ); +/** +* @name cxmy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/cxmy} +*/ +setReadOnly( ns, 'cxmy', require( '@stdlib/blas/ext/base/ndarray/cxmy' ) ); + /** * @name cxpy * @memberof ns @@ -135,6 +144,15 @@ setReadOnly( ns, 'cxsy', require( '@stdlib/blas/ext/base/ndarray/cxsy' ) ); */ setReadOnly( ns, 'czeroTo', require( '@stdlib/blas/ext/base/ndarray/czero-to' ) ); +/** +* @name dany +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/dany} +*/ +setReadOnly( ns, 'dany', require( '@stdlib/blas/ext/base/ndarray/dany' ) ); + /** * @name daxpb * @memberof ns @@ -216,6 +234,24 @@ setReadOnly( ns, 'dcusumpw', require( '@stdlib/blas/ext/base/ndarray/dcusumpw' ) */ setReadOnly( ns, 'ddiff', require( '@stdlib/blas/ext/base/ndarray/ddiff' ) ); +/** +* @name dfillEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/dfill-equal} +*/ +setReadOnly( ns, 'dfillEqual', require( '@stdlib/blas/ext/base/ndarray/dfill-equal' ) ); + +/** +* @name dfillNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/dfill-not-equal} +*/ +setReadOnly( ns, 'dfillNotEqual', require( '@stdlib/blas/ext/base/ndarray/dfill-not-equal' ) ); + /** * @name dindexOf * @memberof ns @@ -396,6 +432,24 @@ setReadOnly( ns, 'dsumpw', require( '@stdlib/blas/ext/base/ndarray/dsumpw' ) ); */ setReadOnly( ns, 'dunitspace', require( '@stdlib/blas/ext/base/ndarray/dunitspace' ) ); +/** +* @name dxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/dxdy} +*/ +setReadOnly( ns, 'dxdy', require( '@stdlib/blas/ext/base/ndarray/dxdy' ) ); + +/** +* @name dxmy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/dxmy} +*/ +setReadOnly( ns, 'dxmy', require( '@stdlib/blas/ext/base/ndarray/dxmy' ) ); + /** * @name dxpy * @memberof ns @@ -432,6 +486,15 @@ setReadOnly( ns, 'dxsy', require( '@stdlib/blas/ext/base/ndarray/dxsy' ) ); */ setReadOnly( ns, 'dzeroTo', require( '@stdlib/blas/ext/base/ndarray/dzero-to' ) ); +/** +* @name gany +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/gany} +*/ +setReadOnly( ns, 'gany', require( '@stdlib/blas/ext/base/ndarray/gany' ) ); + /** * @name gaxpb * @memberof ns @@ -504,6 +567,15 @@ setReadOnly( ns, 'gcusumors', require( '@stdlib/blas/ext/base/ndarray/gcusumors' */ setReadOnly( ns, 'gcusumpw', require( '@stdlib/blas/ext/base/ndarray/gcusumpw' ) ); +/** +* @name gfillNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/gfill-not-equal} +*/ +setReadOnly( ns, 'gfillNotEqual', require( '@stdlib/blas/ext/base/ndarray/gfill-not-equal' ) ); + /** * @name gfindIndex * @memberof ns @@ -540,6 +612,15 @@ setReadOnly( ns, 'gindexOf', require( '@stdlib/blas/ext/base/ndarray/gindex-of' */ setReadOnly( ns, 'gindexOfFalsy', require( '@stdlib/blas/ext/base/ndarray/gindex-of-falsy' ) ); +/** +* @name gindexOfNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/gindex-of-not-equal} +*/ +setReadOnly( ns, 'gindexOfNotEqual', require( '@stdlib/blas/ext/base/ndarray/gindex-of-not-equal' ) ); + /** * @name gindexOfTruthy * @memberof ns @@ -711,6 +792,24 @@ setReadOnly( ns, 'gsumpw', require( '@stdlib/blas/ext/base/ndarray/gsumpw' ) ); */ setReadOnly( ns, 'gunitspace', require( '@stdlib/blas/ext/base/ndarray/gunitspace' ) ); +/** +* @name gxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/gxdy} +*/ +setReadOnly( ns, 'gxdy', require( '@stdlib/blas/ext/base/ndarray/gxdy' ) ); + +/** +* @name gxmy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/gxmy} +*/ +setReadOnly( ns, 'gxmy', require( '@stdlib/blas/ext/base/ndarray/gxmy' ) ); + /** * @name gxpy * @memberof ns @@ -747,6 +846,15 @@ setReadOnly( ns, 'gxsy', require( '@stdlib/blas/ext/base/ndarray/gxsy' ) ); */ setReadOnly( ns, 'gzeroTo', require( '@stdlib/blas/ext/base/ndarray/gzero-to' ) ); +/** +* @name sany +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/sany} +*/ +setReadOnly( ns, 'sany', require( '@stdlib/blas/ext/base/ndarray/sany' ) ); + /** * @name saxpb * @memberof ns @@ -819,6 +927,15 @@ setReadOnly( ns, 'scusumkbn2', require( '@stdlib/blas/ext/base/ndarray/scusumkbn */ setReadOnly( ns, 'scusumors', require( '@stdlib/blas/ext/base/ndarray/scusumors' ) ); +/** +* @name sfillNotEqual +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/sfill-not-equal} +*/ +setReadOnly( ns, 'sfillNotEqual', require( '@stdlib/blas/ext/base/ndarray/sfill-not-equal' ) ); + /** * @name sindexOf * @memberof ns @@ -972,6 +1089,24 @@ setReadOnly( ns, 'ssumpw', require( '@stdlib/blas/ext/base/ndarray/ssumpw' ) ); */ setReadOnly( ns, 'sunitspace', require( '@stdlib/blas/ext/base/ndarray/sunitspace' ) ); +/** +* @name sxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/sxdy} +*/ +setReadOnly( ns, 'sxdy', require( '@stdlib/blas/ext/base/ndarray/sxdy' ) ); + +/** +* @name sxmy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/sxmy} +*/ +setReadOnly( ns, 'sxmy', require( '@stdlib/blas/ext/base/ndarray/sxmy' ) ); + /** * @name sxpy * @memberof ns @@ -1071,6 +1206,24 @@ setReadOnly( ns, 'zsumkbn', require( '@stdlib/blas/ext/base/ndarray/zsumkbn' ) ) */ setReadOnly( ns, 'zunitspace', require( '@stdlib/blas/ext/base/ndarray/zunitspace' ) ); +/** +* @name zxdy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/zxdy} +*/ +setReadOnly( ns, 'zxdy', require( '@stdlib/blas/ext/base/ndarray/zxdy' ) ); + +/** +* @name zxmy +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/ext/base/ndarray/zxmy} +*/ +setReadOnly( ns, 'zxmy', require( '@stdlib/blas/ext/base/ndarray/zxmy' ) ); + /** * @name zxpy * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/README.md new file mode 100644 index 000000000000..1dcb71e4bb30 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/README.md @@ -0,0 +1,109 @@ + + +# sany + +> Test whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy. + +
+ +
+ + + +
+ +## Usage + +```javascript +var sany = require( '@stdlib/blas/ext/base/ndarray/sany' ); +``` + +#### sany( arrays ) + +Tests whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy. + +```javascript +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + +var x = new Float32Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); + +var v = sany( [ x ] ); +// returns true +``` + +The function has the following parameters: + +- **arrays**: array-like object containing a one-dimensional input ndarray. + +
+ + + +
+ +## Notes + +- If provided an empty one-dimensional ndarray, the function returns `false`. +- The function explicitly treats `NaN` values as falsy. + +
+ + + +
+ +## Examples + + + +```javascript +var bernoulli = require( '@stdlib/random/bernoulli' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sany = require( '@stdlib/blas/ext/base/ndarray/sany' ); + +var x = bernoulli( [ 10 ], 0.2, { + 'dtype': 'float32' +}); +console.log( ndarray2array( x ) ); + +var v = sany( [ x ] ); +console.log( v ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/benchmark/benchmark.js new file mode 100644 index 000000000000..5d7a6b9b5153 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/benchmark/benchmark.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sany = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = zeros( [ len ], options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sany( [ x ] ); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + } + b.toc(); + if ( typeof out !== 'boolean' ) { + b.fail( 'should return a boolean' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/repl.txt new file mode 100644 index 000000000000..deb7a59019f8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/repl.txt @@ -0,0 +1,28 @@ + +{{alias}}( arrays ) + Tests whether at least one element in a one-dimensional single-precision + floating-point ndarray is truthy. + + If provided an empty ndarray, the function returns `false`. + + The function explicitly treats `NaN` values as falsy. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing a one-dimensional input ndarray. + + Returns + ------- + bool: boolean + Boolean indicating whether at least one element is truthy. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( [ 0.0, 0.0, 1.0 ] ); + > {{alias}}( [ x ] ) + true + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/types/index.d.ts new file mode 100644 index 000000000000..b1321a994871 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray } from '@stdlib/types/ndarray'; + +/** +* Tests whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* +* - The function explicitly treats `NaN` values as falsy. +* +* @param arrays - array-like object containing ndarrays +* @returns boolean indicating whether at least one element is truthy +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* +* var x = new Float32Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); +* +* var v = sany( [ x ] ); +* // returns true +*/ +declare function sany( arrays: [ float32ndarray ] ): boolean; + + +// EXPORTS // + +export = sany; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/types/test.ts new file mode 100644 index 000000000000..668a17f03bd7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/docs/types/test.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import sany = require( './index' ); + + +// TESTS // + +// The function returns a boolean... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + + sany( [ x ] ); // $ExpectType boolean +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sany( '10' ); // $ExpectError + sany( 10 ); // $ExpectError + sany( true ); // $ExpectError + sany( false ); // $ExpectError + sany( null ); // $ExpectError + sany( undefined ); // $ExpectError + sany( [] ); // $ExpectError + sany( {} ); // $ExpectError + sany( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + + sany(); // $ExpectError + sany( [ x ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/examples/index.js new file mode 100644 index 000000000000..0a62dc4f8bee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var bernoulli = require( '@stdlib/random/bernoulli' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sany = require( './../lib' ); + +var x = bernoulli( [ 10 ], 0.2, { + 'dtype': 'float32' +}); +console.log( ndarray2array( x ) ); + +var v = sany( [ x ] ); +console.log( v ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/lib/index.js new file mode 100644 index 000000000000..9c64d34d0fca --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/lib/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Test whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy. +* +* @module @stdlib/blas/ext/base/ndarray/sany +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var sany = require( '@stdlib/blas/ext/base/ndarray/sany' ); +* +* var x = new Float32Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); +* +* var v = sany( [ x ] ); +* // returns true +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/lib/main.js new file mode 100644 index 000000000000..fd419edfff6b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/lib/main.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/sany' ).ndarray; + + +// MAIN // + +/** +* Tests whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* +* - The function explicitly treats `NaN` values as falsy. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {boolean} boolean indicating whether at least one element is truthy +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* +* var x = new Float32Vector( [ 0.0, 0.0, 1.0, 1.0 ] ); +* +* var v = sany( [ x ] ); +* // returns true +*/ +function sany( arrays ) { + var x = arrays[ 0 ]; + return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = sany; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/package.json new file mode 100644 index 000000000000..a4b3b1d9896e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/sany", + "version": "0.0.0", + "description": "Test whether at least one element in a one-dimensional single-precision floating-point ndarray is truthy.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "any", + "sany", + "truthy", + "test", + "boolean", + "ndarray", + "float32", + "single-precision", + "float32array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/test/test.js new file mode 100644 index 000000000000..1286e19da836 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sany/test/test.js @@ -0,0 +1,178 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var sany = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sany, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sany.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function tests whether at least one element in a one-dimensional ndarray is truthy', function test( t ) { + var x; + var v; + + x = new Float32Array( [ 0.0, 0.0, 1.0, 1.0 ] ); + v = sany( [ vector( x, 4, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + v = sany( [ vector( x, 5, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 0.0, 0.0 ] ); + v = sany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + x = new Float32Array( [ -0.0, 0.0, -0.0 ] ); + v = sany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float32Array( [ -1.0, 0.0, 0.0 ] ); + v = sany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `NaN` values as falsy', function test( t ) { + var x; + var v; + + x = new Float32Array( [ NaN, 0.0, 0.0 ] ); + v = sany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float32Array( [ NaN, NaN, NaN ] ); + v = sany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + x = new Float32Array( [ NaN, 0.0, 1.0 ] ); + v = sany( [ vector( x, 3, 1, 0 ) ] ); + t.strictEqual( v, true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an empty ndarray, the function returns `false`', function test( t ) { + var x; + var v; + + x = new Float32Array( [] ); + + v = sany( [ vector( x, 0, 1, 0 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 0.0, // 0 + 1.0, + 0.0, // 1 + 1.0, + 0.0, // 2 + 1.0, + 0.0, // 3 + 1.0 + ]); + + v = sany( [ vector( x, 4, 2, 0 ) ] ); + + t.strictEqual( v, false, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, // 3 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 0 + 0.0 + ]); + + v = sany( [ vector( x, 4, -2, 6 ) ] ); + + t.strictEqual( v, true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) { + var x; + var v; + + x = new Float32Array([ + 1.0, + 0.0, // 0 + 1.0, + 0.0, // 1 + 1.0, + 0.0, // 2 + 1.0, + 0.0 // 3 + ]); + + v = sany( [ vector( x, 4, 2, 1 ) ] ); + t.strictEqual( v, false, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/README.md new file mode 100644 index 000000000000..5af933bd5fc8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/README.md @@ -0,0 +1,132 @@ + + +# sfillNotEqual + +> Replace elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. + +
+ +
+ + + +
+ +## Usage + +```javascript +var sfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/sfill-not-equal' ); +``` + +#### sfillNotEqual( arrays ) + +Replaces elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. + +```javascript +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); + +var x = new Float32Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +var searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' +}); + +var alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' +}); + +sfillNotEqual( [ x, searchElement, alpha ] ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + +
+ + + +
+ +## Notes + +- The input ndarray is modified **in-place** (i.e., the input ndarray is **mutated**). +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var sfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/sfill-not-equal' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1.0, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +sfillNotEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..aa384ace23b3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfillNotEqual = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var searchElement; + var alpha; + var x; + + x = uniform( [ len ], -100.0, 100.0, options ); + searchElement = scalar2ndarray( 0.0, options ); + alpha = scalar2ndarray( 5.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfillNotEqual( [ x, searchElement, alpha ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/repl.txt new file mode 100644 index 000000000000..bd2339de7b9a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( arrays ) + Replaces elements in a one-dimensional single-precision floating-point + ndarray not equal to a provided search element with a specified scalar + constant. + + The input ndarray is modified *in-place* (i.e., the input ndarray is + *mutated*). + + When comparing elements, the function checks for equality using the strict + equality operator `===`. As a consequence, `NaN` values are considered + distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements + are always replaced), and `-0` and `+0` are considered the same. + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a zero-dimensional ndarray containing the search element. + - a zero-dimensional ndarray containing the scalar constant. + + Returns + ------- + out: ndarray + Input ndarray. + + Examples + -------- + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > var v = {{alias:@stdlib/ndarray/from-scalar}}( 0.0, { 'dtype': 'float32' } ); + > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'float32' } ); + > {{alias}}( [ x, v, alpha ] ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..5a51cfea6a57 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Replaces elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. +* +* @param arrays - array-like object containing ndarrays +* @returns input ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float32Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float32' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float32' +* }); +* +* var out = sfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +declare function sfillNotEqual( arrays: [ float32ndarray, typedndarray, typedndarray ] ): float32ndarray; + + +// EXPORTS // + +export = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..86417a4f3f1a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/docs/types/test.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +import sfillNotEqual = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + sfillNotEqual( [ x, searchElement, alpha ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sfillNotEqual( '10' ); // $ExpectError + sfillNotEqual( 5 ); // $ExpectError + sfillNotEqual( true ); // $ExpectError + sfillNotEqual( false ); // $ExpectError + sfillNotEqual( null ); // $ExpectError + sfillNotEqual( undefined ); // $ExpectError + sfillNotEqual( [] ); // $ExpectError + sfillNotEqual( {} ); // $ExpectError + sfillNotEqual( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + const alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + sfillNotEqual(); // $ExpectError + sfillNotEqual( [ x, searchElement, alpha ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/examples/index.js new file mode 100644 index 000000000000..8dadc1aef501 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var ndarraylike2scalar = require( '@stdlib/ndarray/ndarraylike2scalar' ); +var sfillNotEqual = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 10 ], 0, 3, opts ); +console.log( ndarray2array( x ) ); + +var searchElement = scalar2ndarray( 1.0, opts ); +console.log( 'Search Element: %d', ndarraylike2scalar( searchElement ) ); + +var alpha = scalar2ndarray( 5.0, opts ); +console.log( 'Alpha: %d', ndarraylike2scalar( alpha ) ); + +sfillNotEqual( [ x, searchElement, alpha ] ); +console.log( ndarray2array( x ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/lib/index.js new file mode 100644 index 000000000000..e521f96a879c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/lib/index.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Replace elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. +* +* @module @stdlib/blas/ext/base/ndarray/sfill-not-equal +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* var sfillNotEqual = require( '@stdlib/blas/ext/base/ndarray/sfill-not-equal' ); +* +* var x = new Float32Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float32' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float32' +* }); +* +* var out = sfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/lib/main.js new file mode 100644 index 000000000000..4e9acf308ef9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/lib/main.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/sfill-not-equal' ).ndarray; +var ndarraylike2scalar = require( '@stdlib/ndarray/base/ndarraylike2scalar' ); + + +// MAIN // + +/** +* Replaces elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a zero-dimensional ndarray containing the search element. +* - a zero-dimensional ndarray containing the scalar constant. +* +* - When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} input ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +* +* var x = new Float32Vector( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* var searchElement = scalar2ndarray( 0.0, { +* 'dtype': 'float32' +* }); +* +* var alpha = scalar2ndarray( 5.0, { +* 'dtype': 'float32' +* }); +* +* var out = sfillNotEqual( [ x, searchElement, alpha ] ); +* // returns [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function sfillNotEqual( arrays ) { + var searchElement; + var alpha; + var x; + + x = arrays[ 0 ]; + searchElement = ndarraylike2scalar( arrays[ 1 ] ); + alpha = ndarraylike2scalar( arrays[ 2 ] ); + strided( numelDimension( x, 0 ), searchElement, alpha, getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len + return x; +} + + +// EXPORTS // + +module.exports = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/package.json new file mode 100644 index 000000000000..eaeab44d09c3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/sfill-not-equal", + "version": "0.0.0", + "description": "Replace elements in a one-dimensional single-precision floating-point ndarray not equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "fill", + "not equal", + "unequal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float32", + "single" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/test/test.js new file mode 100644 index 000000000000..8e23d48c0b53 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sfill-not-equal/test/test.js @@ -0,0 +1,301 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var sfillNotEqual = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function replaces elements not equal to a provided search element', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 6, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, 2, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a negative stride', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, -2, 4 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-zero offset', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + x = vector( xbuf, 3, 1, 3 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns the input ndarray unchanged', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ NaN, 1.0, NaN ] ); + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( NaN, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ NaN, 0.0, NaN ] ); + x = vector( xbuf, 3, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ 5.0, 0.0, 5.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + xbuf = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + x = vector( xbuf, 4, 1, 0 ); + searchElement = scalar2ndarray( -0.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the input ndarray unchanged when the input ndarray is empty', function test( t ) { + var searchElement; + var expected; + var actual; + var alpha; + var xbuf; + var x; + + xbuf = new Float32Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + searchElement = scalar2ndarray( 0.0, { + 'dtype': 'float32' + }); + alpha = scalar2ndarray( 5.0, { + 'dtype': 'float32' + }); + + actual = sfillNotEqual( [ x, searchElement, alpha ] ); + t.strictEqual( actual, x, 'returns expected value' ); + + expected = new Float32Array( [] ); + t.strictEqual( isSameFloat32Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json index a008530fd94d..0d4f54ece7a5 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansum/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/snansum", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/package.json index 642e7040a7b4..15c4fe328f50 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/snansumkbn", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.", + "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using an improved Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/package.json index 456b60db6847..8b80015727ca 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumkbn2/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/snansumkbn2", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.", + "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/package.json index 5c9fb9c66dd1..8c98ab122886 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/snansumors", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using ordinary recursive summation.", + "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/package.json index 789a51c65174..09c3e15a9b80 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/snansumpw/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/ndarray/snansumpw", "version": "0.0.0", - "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using pairwise summation.", + "description": "Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using pairwise summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/README.md new file mode 100644 index 000000000000..0cd587f91bc5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/README.md @@ -0,0 +1,132 @@ + + +# sxdy + +> Divide elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var sxdy = require( '@stdlib/blas/ext/base/ndarray/sxdy' ); +``` + +#### sxdy( arrays ) + +Divides elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. + +```javascript +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + +var x = new Float32Vector( [ 10.0, 12.0, 6.0, -4.0, 8.0 ] ); +var y = new Float32Vector( [ 2.0, 3.0, 2.0, -2.0, 4.0 ] ); + +sxdy( [ x, y ] ); +// y => [ 5.0, 4.0, 3.0, 2.0, 2.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sxdy = require( '@stdlib/blas/ext/base/ndarray/sxdy' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( y ) ); + +sxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..16678db3f9d3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sxdy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -100.0, 100.0, options ); + var y = uniform( [ len ], 1.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sxdy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/img/equation_xdy.svg b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/img/equation_xdy.svg new file mode 100644 index 000000000000..1b0e60ad95cf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/img/equation_xdy.svg @@ -0,0 +1,16 @@ + +bold y equals bold x circled-division-slash bold y + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/repl.txt new file mode 100644 index 000000000000..baaa3b392a78 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}( arrays ) + Divides elements of a one-dimensional single-precision floating-point + ndarray by the corresponding elements of a second one-dimensional single- + precision floating-point ndarray and assigns the results to the second + ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 10.0, 12.0, 6.0, 8.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf ); + > var ybuf = [ 2.0, 3.0, 2.0, 4.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf ); + > {{alias}}( [ x, y ] ) + [ 5.0, 4.0, 3.0, 2.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..d785add5945a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray } from '@stdlib/types/ndarray'; + +/** +* Divides elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* +* var x = new Float32Vector( [ 10.0, 12.0, 6.0, -4.0, 8.0 ] ); +* var y = new Float32Vector( [ 2.0, 3.0, 2.0, -2.0, 4.0 ] ); +* +* var out = sxdy( [ x, y ] ); +* // returns [ 5.0, 4.0, 3.0, 2.0, 2.0 ] +*/ +declare function sxdy( arrays: [ float32ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/types/test.ts new file mode 100644 index 000000000000..9aa111b05f13 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import sxdy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float32' + }); + + sxdy( [ x, y ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sxdy( '10' ); // $ExpectError + sxdy( 5 ); // $ExpectError + sxdy( true ); // $ExpectError + sxdy( false ); // $ExpectError + sxdy( null ); // $ExpectError + sxdy( undefined ); // $ExpectError + sxdy( [] ); // $ExpectError + sxdy( {} ); // $ExpectError + sxdy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float32' + }); + + sxdy(); // $ExpectError + sxdy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/examples/index.js new file mode 100644 index 000000000000..0a340114649b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sxdy = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], 1, 100, opts ); +console.log( ndarray2array( y ) ); + +sxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/lib/index.js new file mode 100644 index 000000000000..a7ea84002c1a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Divide elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/sxdy +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var sxdy = require( '@stdlib/blas/ext/base/ndarray/sxdy' ); +* +* var x = new Float32Vector( [ 10.0, 12.0, 6.0, -4.0, 8.0 ] ); +* var y = new Float32Vector( [ 2.0, 3.0, 2.0, -2.0, 4.0 ] ); +* +* var out = sxdy( [ x, y ] ); +* // returns [ 5.0, 4.0, 3.0, 2.0, 2.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/lib/main.js new file mode 100644 index 000000000000..e439fd2e7963 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/sxdy' ).ndarray; + + +// MAIN // + +/** +* Divides elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* +* var x = new Float32Vector( [ 10.0, 12.0, 6.0, -4.0, 8.0 ] ); +* var y = new Float32Vector( [ 2.0, 3.0, 2.0, -2.0, 4.0 ] ); +* +* var out = sxdy( [ x, y ] ); +* // returns [ 5.0, 4.0, 3.0, 2.0, 2.0 ] +*/ +function sxdy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/package.json new file mode 100644 index 000000000000..ffc119978eb5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/sxdy", + "version": "0.0.0", + "description": "Divide elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "sxdy", + "xdy", + "divide", + "division", + "quotient", + "vector", + "strided", + "array", + "ndarray", + "float32", + "single", + "single-precision" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/test/test.js new file mode 100644 index 000000000000..f34c7b02d3db --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxdy/test/test.js @@ -0,0 +1,234 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var sxdy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sxdy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array( [ -2.0, 4.0, -9.0, -20.0, -4.0 ] ); + ybuf = new Float32Array( [ 1.0, 2.0, -3.0, 4.0, -1.0 ] ); + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + expected = new Float32Array([ + -2.0, // -2.0 / 1.0 + 2.0, // 4.0 / 2.0 + 3.0, // -9.0 / (-3.0) + -5.0, // -20.0 / 4.0 + 4.0 // -4.0 / (-1.0) + ]); + + actual = sxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-unit strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array([ + -2.0, // 0 + 1.0, + -9.0, // 1 + -5.0, + -4.0, // 2 + 0.0, + -3.0, // 3 + -3.0 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0, + -3.0, // 1 + 4.0, + -1.0, // 2 + 0.0, + 3.0, // 3 + 2.0 + ]); + x = vector( xbuf, 4, 2, 0 ); + y = vector( ybuf, 4, 2, 0 ); + expected = new Float32Array([ + -2.0, // -2.0 / 1.0 + 2.0, + 3.0, // -9.0 / (-3.0) + 4.0, + 4.0, // -4.0 / (-1.0) + 0.0, + -1.0, // -3.0 / 3.0 + 2.0 + ]); + + actual = sxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array([ + -2.0, // 4 + 4.0, // 3 + -9.0, // 2 + -20.0, // 1 + -4.0 // 0 + ]); + ybuf = new Float32Array([ + 1.0, // 4 + 2.0, // 3 + -3.0, // 2 + 4.0, // 1 + -1.0 // 0 + ]); + x = vector( xbuf, 5, -1, 4 ); + y = vector( ybuf, 5, -1, 4 ); + expected = new Float32Array([ + -2.0, // -2.0 / 1.0 + 2.0, // 4.0 / 2.0 + 3.0, // -9.0 / (-3.0) + -5.0, // -20.0 / 4.0 + 4.0 // -4.0 / (-1.0) + ]); + + actual = sxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array([ + 1.0, + -2.0, + 0.0, // 0 + -20.0, // 1 + -4.0, // 2 + 0.0 + ]); + ybuf = new Float32Array([ + 1.0, + -2.0, + 3.0, // 0 + 4.0, // 1 + -1.0, // 2 + 0.0 + ]); + x = vector( xbuf, 3, 1, 2 ); + y = vector( ybuf, 3, 1, 2 ); + expected = new Float32Array([ + 1.0, + -2.0, + 0.0, // 0.0 / 3.0 + -5.0, // -20.0 / 4.0 + 4.0, // -4.0 / (-1.0) + 0.0 + ]); + + actual = sxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the output ndarray unchanged when the input ndarrays are empty', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array( [] ); + ybuf = new Float32Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + expected = new Float32Array( [] ); + + actual = sxdy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/README.md new file mode 100644 index 000000000000..a5eabab8e7bf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/README.md @@ -0,0 +1,127 @@ + + +# sxmy + +> Multiply elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \odot \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var sxmy = require( '@stdlib/blas/ext/base/ndarray/sxmy' ); +``` + +#### sxmy( arrays ) + +Multiplies elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. + +```javascript +var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); + +var x = new Float32Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var y = new Float32Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +sxmy( [ x, y ] ); +// y => [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sxmy = require( '@stdlib/blas/ext/base/ndarray/sxmy' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( y ) ); + +sxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/benchmark/benchmark.js new file mode 100644 index 000000000000..3a0becac4dbb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sxmy = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -100.0, 100.0, options ); + var y = uniform( [ len ], -100.0, 100.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sxmy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/repl.txt new file mode 100644 index 000000000000..48e148ddc886 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}( arrays ) + Multiplies elements of a one-dimensional single-precision floating-point + ndarray by the corresponding elements of a second one-dimensional single- + precision floating-point ndarray and assigns the results to the second + ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var xbuf = [ 1.0, 2.0, 3.0, 4.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/float32}}( xbuf ); + > var ybuf = [ 2.0, 3.0, 4.0, 5.0 ]; + > var y = new {{alias:@stdlib/ndarray/vector/float32}}( ybuf ); + > {{alias}}( [ x, y ] ) + [ 2.0, 6.0, 12.0, 20.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/types/index.d.ts new file mode 100644 index 000000000000..364e59d8e6b7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { float32ndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var y = new Float32Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = sxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ +declare function sxmy( arrays: [ float32ndarray, float32ndarray ] ): float32ndarray; + + +// EXPORTS // + +export = sxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/types/test.ts new file mode 100644 index 000000000000..e2b6bd6c644b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import sxmy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float32' + }); + + sxmy( [ x, y ] ); // $ExpectType float32ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + sxmy( '10' ); // $ExpectError + sxmy( 5 ); // $ExpectError + sxmy( true ); // $ExpectError + sxmy( false ); // $ExpectError + sxmy( null ); // $ExpectError + sxmy( undefined ); // $ExpectError + sxmy( [] ); // $ExpectError + sxmy( {} ); // $ExpectError + sxmy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'float32' + }); + const y = zeros( [ 10 ], { + 'dtype': 'float32' + }); + + sxmy(); // $ExpectError + sxmy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/examples/index.js new file mode 100644 index 000000000000..9d56c89ca15e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/discrete-uniform' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var sxmy = require( './../lib' ); + +var opts = { + 'dtype': 'float32' +}; + +var x = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( x ) ); + +var y = discreteUniform( [ 10 ], -100, 100, opts ); +console.log( ndarray2array( y ) ); + +sxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/lib/index.js new file mode 100644 index 000000000000..7bf713925acc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/sxmy +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* var sxmy = require( '@stdlib/blas/ext/base/ndarray/sxmy' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var y = new Float32Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = sxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/lib/main.js new file mode 100644 index 000000000000..fcbd154fe070 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/sxmy' ).ndarray; + + +// MAIN // + +/** +* Multiplies elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var Float32Vector = require( '@stdlib/ndarray/vector/float32' ); +* +* var x = new Float32Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var y = new Float32Vector( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* var out = sxmy( [ x, y ] ); +* // returns [ 2.0, 6.0, 12.0, 20.0, 30.0 ] +*/ +function sxmy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = sxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/package.json new file mode 100644 index 000000000000..41bfd59fdabc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/sxmy", + "version": "0.0.0", + "description": "Multiply elements of a one-dimensional single-precision floating-point ndarray by the corresponding elements of a second one-dimensional single-precision floating-point ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "sxmy", + "xmy", + "multiply", + "multiplication", + "product", + "vector", + "strided", + "array", + "ndarray", + "float32", + "single", + "single-precision" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/test/test.js new file mode 100644 index 000000000000..0d0c1eea2a92 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/sxmy/test/test.js @@ -0,0 +1,234 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var sxmy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Float32Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( sxmy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0 ] ); + ybuf = new Float32Array( [ 1.0, 2.0, -3.0, 4.0, -1.0 ] ); + x = vector( xbuf, 5, 1, 0 ); + y = vector( ybuf, 5, 1, 0 ); + expected = new Float32Array([ + -2.0, // -2.0 * 1.0 + 2.0, // 1.0 * 2.0 + -9.0, // 3.0 * (-3.0) + -20.0, // -5.0 * 4.0 + -4.0 // 4.0 * (-1.0) + ]); + + actual = sxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-unit strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array([ + -2.0, // 0 + 1.0, + 3.0, // 1 + -5.0, + 4.0, // 2 + 0.0, + -1.0, // 3 + -3.0 + ]); + ybuf = new Float32Array([ + 1.0, // 0 + 2.0, + -3.0, // 1 + 4.0, + -1.0, // 2 + 0.0, + 3.0, // 3 + 2.0 + ]); + x = vector( xbuf, 4, 2, 0 ); + y = vector( ybuf, 4, 2, 0 ); + expected = new Float32Array([ + -2.0, // -2.0 * 1.0 + 2.0, + -9.0, // 3.0 * (-3.0) + 4.0, + -4.0, // 4.0 * (-1.0) + 0.0, + -3.0, // -1.0 * 3.0 + 2.0 + ]); + + actual = sxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array([ + -2.0, // 4 + 1.0, // 3 + 3.0, // 2 + -5.0, // 1 + 4.0 // 0 + ]); + ybuf = new Float32Array([ + 1.0, // 4 + 2.0, // 3 + -3.0, // 2 + 4.0, // 1 + -1.0 // 0 + ]); + x = vector( xbuf, 5, -1, 4 ); + y = vector( ybuf, 5, -1, 4 ); + expected = new Float32Array([ + -2.0, // -2.0 * 1.0 + 2.0, // 1.0 * 2.0 + -9.0, // 3.0 * (-3.0) + -20.0, // -5.0 * 4.0 + -4.0 // 4.0 * (-1.0) + ]); + + actual = sxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports input ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array([ + 1.0, + -2.0, + 3.0, // 0 + -5.0, // 1 + 4.0, // 2 + 0.0 + ]); + ybuf = new Float32Array([ + 1.0, + -2.0, + 0.0, // 0 + 4.0, // 1 + -1.0, // 2 + 0.0 + ]); + x = vector( xbuf, 3, 1, 2 ); + y = vector( ybuf, 3, 1, 2 ); + expected = new Float32Array([ + 1.0, + -2.0, + 0.0, // 3.0 * 0.0 + -20.0, // -5.0 * 4.0 + -4.0, // 4.0 * (-1.0) + 0.0 + ]); + + actual = sxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the output ndarray unchanged when the input ndarrays are empty', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Float32Array( [] ); + ybuf = new Float32Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + expected = new Float32Array( [] ); + + actual = sxmy( [ x, y ] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.deepEqual( ybuf, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zunitspace/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zunitspace/README.md index 2cf6fcfd7082..23921225ce2f 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zunitspace/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zunitspace/README.md @@ -40,8 +40,6 @@ var zunitspace = require( '@stdlib/blas/ext/base/ndarray/zunitspace' ); Fills a one-dimensional double-precision complex floating-point ndarray with linearly spaced numeric elements which increment by `1` starting from a specified value. - - ```javascript var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); var Complex128 = require( '@stdlib/complex/float64/ctor' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/README.md new file mode 100644 index 000000000000..a94f1daf45e7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/README.md @@ -0,0 +1,133 @@ + + +# zxdy + +> Divide elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var zxdy = require( '@stdlib/blas/ext/base/ndarray/zxdy' ); +``` + +#### zxdy( arrays ) + +Divides elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. + +```javascript +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); + +var x = new Complex128Vector( [ -1.0, 3.0, -2.0, 14.0, -4.0, 44.0 ] ); +var y = new Complex128Vector( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + +zxdy( [ x, y ] ); +// y => [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zxdy = require( '@stdlib/blas/ext/base/ndarray/zxdy' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = new Complex128Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( x ) ); + +var y = new Complex128Vector( discreteUniform( 20, 1, 100, opts ) ); +console.log( ndarray2array( y ) ); + +zxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..f6d0afdb5691 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/benchmark/benchmark.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zxdy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -100.0, 100.0, { + 'dtype': 'float64' + }); + ybuf = uniform( len*2, 1.0, 100.0, { + 'dtype': 'float64' + }); + x = new Complex128Vector( xbuf.buffer ); + y = new Complex128Vector( ybuf.buffer ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = zxdy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/img/equation_xdy.svg b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/img/equation_xdy.svg new file mode 100644 index 000000000000..1b0e60ad95cf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/img/equation_xdy.svg @@ -0,0 +1,16 @@ + +bold y equals bold x circled-division-slash bold y + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/repl.txt new file mode 100644 index 000000000000..0b3674fbf706 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}( arrays ) + Divides elements of a one-dimensional double-precision complex floating- + point ndarray by the corresponding elements of a second one-dimensional + double-precision complex floating-point ndarray and assigns the results to + the second ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var bufX = [ -1.0, 3.0, -2.0, 14.0, -4.0, 44.0 ]; + > var bufY = [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/complex128}}( bufX ); + > var y = new {{alias:@stdlib/ndarray/vector/complex128}}( bufY ); + > {{alias}}( [ x, y ] ) + [ [ 1,2 ], [ 3,4 ], [ 5,6 ] ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..68187707325c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { complex128ndarray } from '@stdlib/types/ndarray'; + +/** +* Divides elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +* +* var x = new Complex128Vector( [ -1.0, 3.0, -2.0, 14.0, -4.0, 44.0 ] ); +* var y = new Complex128Vector( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* var out = zxdy( [ x, y ] ); +* // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ] +*/ +declare function zxdy( arrays: [ complex128ndarray, complex128ndarray ] ): complex128ndarray; + + +// EXPORTS // + +export = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/types/test.ts new file mode 100644 index 000000000000..2b82c18f15d7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import zxdy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + const y = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + + zxdy( [ x, y ] ); // $ExpectType complex128ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + zxdy( '10' ); // $ExpectError + zxdy( 5 ); // $ExpectError + zxdy( true ); // $ExpectError + zxdy( false ); // $ExpectError + zxdy( null ); // $ExpectError + zxdy( undefined ); // $ExpectError + zxdy( [] ); // $ExpectError + zxdy( {} ); // $ExpectError + zxdy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + const y = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + + zxdy(); // $ExpectError + zxdy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/examples/index.js new file mode 100644 index 000000000000..98e78016cfe9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zxdy = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = new Complex128Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( x ) ); + +var y = new Complex128Vector( discreteUniform( 20, 1, 100, opts ) ); +console.log( ndarray2array( y ) ); + +zxdy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/lib/index.js new file mode 100644 index 000000000000..56effa50f514 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Divide elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/zxdy +* +* @example +* var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +* var zxdy = require( '@stdlib/blas/ext/base/ndarray/zxdy' ); +* +* var x = new Complex128Vector( [ -1.0, 3.0, -2.0, 14.0, -4.0, 44.0 ] ); +* var y = new Complex128Vector( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* var out = zxdy( [ x, y ] ); +* // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/lib/main.js new file mode 100644 index 000000000000..0ee5178c7e22 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/zxdy' ).ndarray; + + +// MAIN // + +/** +* Divides elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +* +* var x = new Complex128Vector( [ -1.0, 3.0, -2.0, 14.0, -4.0, 44.0 ] ); +* var y = new Complex128Vector( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* var out = zxdy( [ x, y ] ); +* // returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ], [ 5.0, 6.0 ] ] +*/ +function zxdy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/package.json new file mode 100644 index 000000000000..8b56b46d7236 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/zxdy", + "version": "0.0.0", + "description": "Divide elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "zxdy", + "xdy", + "divide", + "division", + "strided", + "array", + "ndarray", + "complex128", + "complex", + "double", + "double-precision", + "float64" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/test/test.js new file mode 100644 index 000000000000..74ca632e7391 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxdy/test/test.js @@ -0,0 +1,333 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var zxdy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex128Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex128', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( zxdy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array( [ -1.0, 3.0, -2.0, 14.0, -4.0, 44.0 ] ); + ybuf = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + + actual = zxdy( [ x, y ] ); + expected = new Complex128Array([ + // (-1.0+3.0i) / (1.0+1.0i) + 1.0, + 2.0, + // (-2.0+14.0i) / (2.0+2.0i) + 3.0, + 4.0, + // (-4.0+44.0i) / (4.0+4.0i) + 5.0, + 6.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + xbuf = new Complex128Array( [ 6.0, 2.0, -3.0, 1.0 ] ); + ybuf = new Complex128Array( [ 2.0, 2.0, 1.0, 1.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + + actual = zxdy( [ x, y ] ); + expected = new Complex128Array([ + // (6.0+2.0i) / (2.0+2.0i) + 2.0, + -1.0, + // (-3.0+1.0i) / (1.0+1.0i) + -1.0, + 2.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + -1.0, // 0 + 3.0, // 0 + 0.0, + 0.0, + -2.0, // 1 + 14.0, // 1 + 0.0, + 0.0, + -4.0, // 2 + 44.0 // 2 + ]); + ybuf = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 2.0, // 1 + 2.0, // 1 + 4.0, // 2 + 4.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + y = vector( ybuf, 3, 1, 0 ); + + actual = zxdy( [ x, y ] ); + expected = new Complex128Array([ + // (-1.0+3.0i) / (1.0+1.0i) + 1.0, + 2.0, + // (-2.0+14.0i) / (2.0+2.0i) + 3.0, + 4.0, + // (-4.0+44.0i) / (4.0+4.0i) + 5.0, + 6.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + -1.0, // 0 + 3.0, // 0 + -2.0, // 1 + 14.0, // 1 + -4.0, // 2 + 44.0 // 2 + ]); + ybuf = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 0.0, + 0.0, + 2.0, // 1 + 2.0, // 1 + 0.0, + 0.0, + 4.0, // 2 + 4.0 // 2 + ]); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 2, 0 ); + + actual = zxdy( [ x, y ] ); + expected = new Complex128Array([ + // (-1.0+3.0i) / (1.0+1.0i) + 1.0, + 2.0, + 0.0, + 0.0, + // (-2.0+14.0i) / (2.0+2.0i) + 3.0, + 4.0, + 0.0, + 0.0, + // (-4.0+44.0i) / (4.0+4.0i) + 5.0, + 6.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + -4.0, // 2 + 44.0, // 2 + 0.0, + 0.0, + -2.0, // 1 + 14.0, // 1 + 0.0, + 0.0, + -1.0, // 0 + 3.0 // 0 + ]); + ybuf = new Complex128Array([ + 4.0, // 2 + 4.0, // 2 + 2.0, // 1 + 2.0, // 1 + 1.0, // 0 + 1.0 // 0 + ]); + x = vector( xbuf, 3, -2, 4 ); + y = vector( ybuf, 3, -1, 2 ); + + actual = zxdy( [ x, y ] ); + expected = new Complex128Array([ + // (-4.0+44.0i) / (4.0+4.0i) + 5.0, + 6.0, + // (-2.0+14.0i) / (2.0+2.0i) + 3.0, + 4.0, + // (-1.0+3.0i) / (1.0+1.0i) + 1.0, + 2.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + 0.0, + 0.0, + 6.0, // 0 + 0.0, // 0 + 0.0, + 0.0, + 8.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 12.0, // 2 + 0.0 // 2 + ]); + ybuf = new Complex128Array([ + 0.0, + 0.0, + 2.0, // 0 + 0.0, // 0 + 4.0, // 1 + 0.0, // 1 + 8.0, // 2 + 0.0 // 2 + ]); + x = vector( xbuf, 3, 2, 1 ); + y = vector( ybuf, 3, 1, 1 ); + + actual = zxdy( [ x, y ] ); + + expected = new Complex128Array([ + 0.0, + 0.0, + // (6.0+0.0i) / (2.0+0.0i) + 3.0, + 0.0, + // (8.0+0.0i) / (4.0+0.0i) + 2.0, + 0.0, + // (12.0+0.0i) / (8.0+0.0i) + 1.5, + 0.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided empty ndarrays, the function returns the output ndarray unchanged', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array( [] ); + ybuf = new Complex128Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + + actual = zxdy( [ x, y ] ); + expected = new Complex128Array( [] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/README.md new file mode 100644 index 000000000000..9f9bc6dc1287 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/README.md @@ -0,0 +1,128 @@ + + +# zxmy + +> Multiply elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \odot \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var zxmy = require( '@stdlib/blas/ext/base/ndarray/zxmy' ); +``` + +#### zxmy( arrays ) + +Multiplies elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. + +```javascript +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); + +var x = new Complex128Vector( [ 1.0, 1.0, 2.0, -1.0, 3.0, 0.0 ] ); +var y = new Complex128Vector( [ 2.0, 1.0, 1.0, 2.0, 2.0, -2.0 ] ); + +zxmy( [ x, y ] ); +// y => [ [ 1.0, 3.0 ], [ 4.0, 3.0 ], [ 6.0, -6.0 ] ] +``` + +The function has the following parameters: + +- **arrays**: array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + +
+ + + +
+ +## Notes + +- The output ndarray is modified **in-place** (i.e., the output ndarray is **mutated**). + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zxmy = require( '@stdlib/blas/ext/base/ndarray/zxmy' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = new Complex128Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( x ) ); + +var y = new Complex128Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( y ) ); + +zxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/benchmark/benchmark.js new file mode 100644 index 000000000000..11bc7c162b8a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/benchmark/benchmark.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zxmy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - ndarray length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -100.0, 100.0, { + 'dtype': 'float64' + }); + ybuf = uniform( len*2, -100.0, 100.0, { + 'dtype': 'float64' + }); + x = new Complex128Vector( xbuf.buffer ); + y = new Complex128Vector( ybuf.buffer ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = zxmy( [ x, y ] ); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( typeof out !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/repl.txt new file mode 100644 index 000000000000..f067b48b107e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}( arrays ) + Multiplies elements of a one-dimensional double-precision complex floating- + point ndarray by the corresponding elements of a second one-dimensional + double-precision complex floating-point ndarray and assigns the results to + the second ndarray. + + The output ndarray is modified *in-place* (i.e., the output ndarray is + *mutated*). + + Parameters + ---------- + arrays: ArrayLikeObject + Array-like object containing the following ndarrays: + + - a one-dimensional input ndarray. + - a one-dimensional output ndarray. + + Returns + ------- + out: ndarray + Output ndarray. + + Examples + -------- + > var bufX = [ 1.0, 1.0, 2.0, -1.0, 3.0, 0.0 ]; + > var bufY = [ 2.0, 1.0, 1.0, 2.0, 2.0, -2.0 ]; + > var x = new {{alias:@stdlib/ndarray/vector/complex128}}( bufX ); + > var y = new {{alias:@stdlib/ndarray/vector/complex128}}( bufY ); + > {{alias}}( [ x, y ] ) + [ [ 1,3 ], [ 4,3 ], [ 6,-6 ] ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/types/index.d.ts new file mode 100644 index 000000000000..278ba4f9dee7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/types/index.d.ts @@ -0,0 +1,52 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { complex128ndarray } from '@stdlib/types/ndarray'; + +/** +* Multiplies elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param arrays - array-like object containing ndarrays +* @returns output ndarray +* +* @example +* var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +* +* var x = new Complex128Vector( [ 1.0, 1.0, 2.0, -1.0, 3.0, 0.0 ] ); +* var y = new Complex128Vector( [ 2.0, 1.0, 1.0, 2.0, 2.0, -2.0 ] ); +* +* var out = zxmy( [ x, y ] ); +* // returns [ [ 1.0, 3.0 ], [ 4.0, 3.0 ], [ 6.0, -6.0 ] ] +*/ +declare function zxmy( arrays: [ complex128ndarray, complex128ndarray ] ): complex128ndarray; + + +// EXPORTS // + +export = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/types/test.ts new file mode 100644 index 000000000000..4c620e03b067 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import zxmy = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + const y = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + + zxmy( [ x, y ] ); // $ExpectType complex128ndarray +} + +// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... +{ + zxmy( '10' ); // $ExpectError + zxmy( 5 ); // $ExpectError + zxmy( true ); // $ExpectError + zxmy( false ); // $ExpectError + zxmy( null ); // $ExpectError + zxmy( undefined ); // $ExpectError + zxmy( [] ); // $ExpectError + zxmy( {} ); // $ExpectError + zxmy( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + const y = zeros( [ 10 ], { + 'dtype': 'complex128' + }); + + zxmy(); // $ExpectError + zxmy( [ x, y ], {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/examples/index.js new file mode 100644 index 000000000000..75fd69acb51a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var zxmy = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = new Complex128Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( x ) ); + +var y = new Complex128Vector( discreteUniform( 20, -100, 100, opts ) ); +console.log( ndarray2array( y ) ); + +zxmy( [ x, y ] ); +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/lib/index.js new file mode 100644 index 000000000000..c63f366232ef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Multiply elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray. +* +* @module @stdlib/blas/ext/base/ndarray/zxmy +* +* @example +* var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +* var zxmy = require( '@stdlib/blas/ext/base/ndarray/zxmy' ); +* +* var x = new Complex128Vector( [ 1.0, 1.0, 2.0, -1.0, 3.0, 0.0 ] ); +* var y = new Complex128Vector( [ 2.0, 1.0, 1.0, 2.0, 2.0, -2.0 ] ); +* +* var out = zxmy( [ x, y ] ); +* // returns [ [ 1.0, 3.0 ], [ 4.0, 3.0 ], [ 6.0, -6.0 ] ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/lib/main.js new file mode 100644 index 000000000000..48f2e16ef9bf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/lib/main.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); +var getStride = require( '@stdlib/ndarray/base/stride' ); +var getOffset = require( '@stdlib/ndarray/base/offset' ); +var getData = require( '@stdlib/ndarray/base/data-buffer' ); +var strided = require( '@stdlib/blas/ext/base/zxmy' ).ndarray; + + +// MAIN // + +/** +* Multiplies elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assigns the results to the second ndarray. +* +* ## Notes +* +* - The function expects the following ndarrays: +* +* - a one-dimensional input ndarray. +* - a one-dimensional output ndarray. +* +* @param {ArrayLikeObject} arrays - array-like object containing ndarrays +* @returns {ndarray} output ndarray +* +* @example +* var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' ); +* +* var x = new Complex128Vector( [ 1.0, 1.0, 2.0, -1.0, 3.0, 0.0 ] ); +* var y = new Complex128Vector( [ 2.0, 1.0, 1.0, 2.0, 2.0, -2.0 ] ); +* +* var out = zxmy( [ x, y ] ); +* // returns [ [ 1.0, 3.0 ], [ 4.0, 3.0 ], [ 6.0, -6.0 ] ] +*/ +function zxmy( arrays ) { + var x; + var y; + + x = arrays[ 0 ]; + y = arrays[ 1 ]; + strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len + return y; +} + + +// EXPORTS // + +module.exports = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/package.json b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/package.json new file mode 100644 index 000000000000..5c6d66f6c3e4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/blas/ext/base/ndarray/zxmy", + "version": "0.0.0", + "description": "Multiply elements of a one-dimensional double-precision complex floating-point ndarray by the corresponding elements of a second one-dimensional double-precision complex floating-point ndarray and assign the results to the second ndarray.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "ext", + "zxmy", + "xmy", + "multiply", + "multiplication", + "strided", + "array", + "ndarray", + "complex128", + "complex", + "double", + "double-precision", + "float64" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/test/test.js new file mode 100644 index 000000000000..a203c056dcc4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/zxmy/test/test.js @@ -0,0 +1,333 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var ndarray = require( '@stdlib/ndarray/base/ctor' ); +var getData = require( '@stdlib/ndarray/data-buffer' ); +var zxmy = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Returns a one-dimensional ndarray. +* +* @private +* @param {Complex128Array} buffer - underlying data buffer +* @param {NonNegativeInteger} length - number of indexed elements +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - index offset +* @returns {ndarray} one-dimensional ndarray +*/ +function vector( buffer, length, stride, offset ) { + return new ndarray( 'complex128', buffer, [ length ], [ stride ], offset, 'row-major' ); +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 1', function test( t ) { + t.strictEqual( zxmy.length, 1, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by `y` and assigns the results to `y`', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array( [ 1.0, 1.0, 2.0, -1.0, 3.0, 0.0 ] ); + ybuf = new Complex128Array( [ 2.0, 1.0, 1.0, 2.0, 2.0, -2.0 ] ); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 1, 0 ); + + actual = zxmy( [ x, y ] ); + expected = new Complex128Array([ + // (1.0+1.0i) * (2.0+1.0i) + 1.0, + 3.0, + // (2.0-1.0i) * (1.0+2.0i) + 4.0, + 3.0, + // (3.0+0.0i) * (2.0-2.0i) + 6.0, + -6.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + xbuf = new Complex128Array( [ 1.0, 0.0, 2.0, 1.0 ] ); + ybuf = new Complex128Array( [ 3.0, -1.0, 4.0, 2.0 ] ); + x = vector( xbuf, 2, 1, 0 ); + y = vector( ybuf, 2, 1, 0 ); + + actual = zxmy( [ x, y ] ); + expected = new Complex128Array([ + // (1.0+0.0i) * (3.0-1.0i) + 3.0, + -1.0, + // (2.0+1.0i) * (4.0+2.0i) + 6.0, + 8.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an input ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 0.0, + 0.0, + 2.0, // 1 + -1.0, // 1 + 0.0, + 0.0, + 3.0, // 2 + 0.0 // 2 + ]); + ybuf = new Complex128Array([ + 2.0, // 0 + 1.0, // 0 + 1.0, // 1 + 2.0, // 1 + 2.0, // 2 + -2.0 // 2 + ]); + x = vector( xbuf, 3, 2, 0 ); + y = vector( ybuf, 3, 1, 0 ); + + actual = zxmy( [ x, y ] ); + expected = new Complex128Array([ + // (1.0+1.0i) * (2.0+1.0i) + 1.0, + 3.0, + // (2.0-1.0i) * (1.0+2.0i) + 4.0, + 3.0, + // (3.0+0.0i) * (2.0-2.0i) + 6.0, + -6.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output ndarray having a non-unit stride', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 2.0, // 1 + -1.0, // 1 + 3.0, // 2 + 0.0 // 2 + ]); + ybuf = new Complex128Array([ + 2.0, // 0 + 1.0, // 0 + 0.0, + 0.0, + 1.0, // 1 + 2.0, // 1 + 0.0, + 0.0, + 2.0, // 2 + -2.0 // 2 + ]); + x = vector( xbuf, 3, 1, 0 ); + y = vector( ybuf, 3, 2, 0 ); + + actual = zxmy( [ x, y ] ); + expected = new Complex128Array([ + // (1.0+1.0i) * (2.0+1.0i) + 1.0, + 3.0, + 0.0, + 0.0, + // (2.0-1.0i) * (1.0+2.0i) + 4.0, + 3.0, + 0.0, + 0.0, + // (3.0+0.0i) * (2.0-2.0i) + 6.0, + -6.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports ndarrays having negative strides', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + -1.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + ybuf = new Complex128Array([ + 4.0, // 2 + 0.0, // 2 + 3.0, // 1 + -1.0, // 1 + 2.0, // 0 + 1.0 // 0 + ]); + x = vector( xbuf, 3, -2, 4 ); + y = vector( ybuf, 3, -1, 2 ); + + actual = zxmy( [ x, y ] ); + expected = new Complex128Array([ + // (1.0+2.0i) * (4.0+0.0i) + 4.0, + 8.0, + // (3.0-1.0i) * (3.0-1.0i) + 8.0, + -6.0, + // (5.0+6.0i) * (2.0+1.0i) + 4.0, + 17.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports ndarrays having non-zero offsets', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array([ + 0.0, + 0.0, + 1.0, // 0 + 0.0, // 0 + 0.0, + 0.0, + 2.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 3.0, // 2 + 0.0 // 2 + ]); + ybuf = new Complex128Array([ + 0.0, + 0.0, + 2.0, // 0 + 0.0, // 0 + 3.0, // 1 + 0.0, // 1 + 4.0, // 2 + 0.0 // 2 + ]); + x = vector( xbuf, 3, 2, 1 ); + y = vector( ybuf, 3, 1, 1 ); + + actual = zxmy( [ x, y ] ); + + expected = new Complex128Array([ + 0.0, + 0.0, + // (1.0+0.0i) * (2.0+0.0i) + 2.0, + 0.0, + // (2.0+0.0i) * (3.0+0.0i) + 6.0, + 0.0, + // (3.0+0.0i) * (4.0+0.0i) + 12.0, + 0.0 + ]); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided empty ndarrays, the function returns the output ndarray unchanged', function test( t ) { + var expected; + var actual; + var xbuf; + var ybuf; + var x; + var y; + + xbuf = new Complex128Array( [] ); + ybuf = new Complex128Array( [] ); + x = vector( xbuf, 0, 1, 0 ); + y = vector( ybuf, 0, 1, 0 ); + + actual = zxmy( [ x, y ] ); + expected = new Complex128Array( [] ); + t.strictEqual( actual, y, 'returns expected value' ); + t.strictEqual( isSameComplex128Array( getData( actual ), expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/scartesian-power/README.md b/lib/node_modules/@stdlib/blas/ext/base/scartesian-power/README.md index 46d3d6096702..9404b1498d02 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/scartesian-power/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/scartesian-power/README.md @@ -110,8 +110,8 @@ The function has the following parameters: - **strideX**: stride length for `x`. - **offsetX**: starting index for `x`. - **out**: output [`Float32Array`][@stdlib/array/float32]. -- **strideOut1**: stride length of the first dimension of `out`. -- **strideOut2**: stride length of the second dimension of `out`. +- **strideOut1**: stride length for the first dimension of `out`. +- **strideOut2**: stride length for the second dimension of `out`. - **offsetOut**: starting index for `out`. While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to access only the last two elements: @@ -247,8 +247,8 @@ The function accepts the following arguments: - **strideX**: `[in] CBLAS_INT` stride length for `X`. - **offsetX**: `[in] CBLAS_INT` starting index for `X`. - **Out**: `[out] float*` output array. -- **strideOut1**: `[in] CBLAS_INT` stride length of the first dimension of `Out`. -- **strideOut2**: `[in] CBLAS_INT` stride length of the second dimension of `Out`. +- **strideOut1**: `[in] CBLAS_INT` stride length for the first dimension of `Out`. +- **strideOut2**: `[in] CBLAS_INT` stride length for the second dimension of `Out`. - **offsetOut**: `[in] CBLAS_INT` starting index for `Out`. ```c diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/README.md new file mode 100644 index 000000000000..195219162e7b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/README.md @@ -0,0 +1,294 @@ + + +# sfillEqual + +> Replace single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + +
+ +## Usage + +```javascript +var sfillEqual = require( '@stdlib/blas/ext/base/sfill-equal' ); +``` + +#### sfillEqual( N, searchElement, alpha, x, strideX ) + +Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] ); + +sfillEqual( x.length, 0.0, 5.0, x, 1 ); +// x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **alpha**: scalar constant. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 0.0, 1.0, 0.0, -5.0, 4.0, 0.0, -1.0, 0.0 ] ); + +sfillEqual( 4, 0.0, 5.0, x, 2 ); +// x => [ 5.0, 1.0, 5.0, -5.0, 4.0, 0.0, -1.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial array: +var x0 = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, -5.0, 0.0 ] ); + +// Create an offset view: +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +sfillEqual( 3, 0.0, 5.0, x1, 2 ); +// x0 => [ 1.0, 5.0, 3.0, 5.0, -5.0, 5.0 ] +``` + +#### sfillEqual.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + +Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] ); + +sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +// x => [ -2.0, 5.0, 3.0, 5.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ -2.0, 0.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] ); + +sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, x.length-3 ); +// x => [ -2.0, 0.0, 3.0, 0.0, 4.0, 5.0, -1.0, -3.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- When comparing elements, both functions check for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct, and `-0` and `+0` are considered the same. To replace `NaN` values, use [`@stdlib/blas/ext/base/sfill-nan`][@stdlib/blas/ext/base/sfill-nan]. + +
+ + + +
+ +## Examples + + + +```javascript +var zeros = require( '@stdlib/array/zeros' ); +var sfillEqual = require( '@stdlib/blas/ext/base/sfill-equal' ); + +var x = zeros( 10, 'float32' ); +console.log( x ); + +sfillEqual( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sfill_equal.h" +``` + +#### stdlib_strided_sfill_equal( N, searchElement, alpha, \*X, strideX ) + +Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + +```c +float x[] = { -2.0f, 0.0f, 3.0f, 0.0f, 4.0f, 0.0f, -1.0f, -3.0f }; + +stdlib_strided_sfill_equal( 8, 0.0f, 5.0f, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] float` search element. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_sfill_equal( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX ); +``` + + + +#### stdlib_strided_sfill_equal_ndarray( N, searchElement, alpha, \*X, strideX, offsetX ) + + + +Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```c +float x[] = { -2.0f, 0.0f, 3.0f, 0.0f, 4.0f, 0.0f, -1.0f, -3.0f }; + +stdlib_strided_sfill_equal_ndarray( 8, 0.0f, 5.0f, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] float` search element. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_sfill_equal_ndarray( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sfill_equal.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace equal elements: + stdlib_strided_sfill_equal( N, 5.0f, 10.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/blas/ext/base/sfill-nan]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/sfill-nan + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..3df7a42b5544 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfillEqual = require( './../lib/sfill_equal.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillEqual( x.length, i, i+1, x, 1 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.native.js new file mode 100644 index 000000000000..1f2165d87721 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfillEqual = tryRequire( resolve( __dirname, './../lib/sfill_equal.native.js' ) ); +var opts = { + 'skip': ( sfillEqual instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillEqual( x.length, i, i+1, x, 1 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..ba2885fa5b3b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfillEqual = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..127f5e8799e0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfillEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfillEqual instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..36a8b13f7f5c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/benchmark/c/benchmark.length.c @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_equal.h" +#include +#include +#include +#include +#include + +#define NAME "sfill-equal" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0f; + } else { + x[ i ] = ( rand_float()*200.0f ) - 100.0f; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_sfill_equal( len, (float)i, (float)(i+1), x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0f; + } else { + x[ i ] = ( rand_float()*200.0f ) - 100.0f; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_sfill_equal_ndarray( len, (float)i, (float)(i+1), x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/repl.txt new file mode 100644 index 000000000000..fecdecb540b6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/repl.txt @@ -0,0 +1,104 @@ + +{{alias}}( N, searchElement, alpha, x, strideX ) + Replaces single-precision floating-point strided array elements equal to a + provided search element with a specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}( x.length, 0.0, 5.0, x, 1 ) + [ 5.0, 5.0, 1.0, 5.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}( 2, 0.0, 5.0, x, 2 ) + [ 5.0, 0.0, 1.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 0.0, 5.0, x1, 2 ) + [ 5.0, 1.0, 5.0 ] + > x0 + [ 0.0, 5.0, 1.0, 5.0 ] + + +{{alias}}.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + Replaces single-precision floating-point strided array elements equal to a + provided search element with a specified scalar constant using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}.ndarray( x.length, 0.0, 5.0, x, 1, 0 ) + [ 5.0, 5.0, 1.0, 5.0 ] + + // Using an index offset: + > var x = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > {{alias}}.ndarray( 2, 0.0, 5.0, x, 2, 1 ) + [ 0.0, 5.0, 1.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..77924a34f7dd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/types/index.d.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `sfillEqual`. +*/ +interface Routine { + /** + * Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * sfillEqual( x.length, 0.0, 5.0, x, 1 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + ( N: number, searchElement: number, alpha: number, x: Float32Array, strideX: number ): Float32Array; + + /** + * Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); + * // x => [ 5.0, 5.0, 1.0, 5.0 ] + */ + ndarray( N: number, searchElement: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): Float32Array; +} + +/** +* Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* sfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +declare var sfillEqual: Routine; + + +// EXPORTS // + +export = sfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/types/test.ts new file mode 100644 index 000000000000..dd9870c29ab1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/docs/types/test.ts @@ -0,0 +1,217 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import sfillEqual = require( './index' ); + + +// TESTS // + +// The function returns a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillEqual( x.length, 0.0, 5.0, x, 1 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual( '10', 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual( true, 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual( false, 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual( null, 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual( undefined, 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual( [], 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual( {}, 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual( ( x: number ): number => x, 0.0, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual( x.length, '10', 5.0, x, 1 ); // $ExpectError + sfillEqual( x.length, true, 5.0, x, 1 ); // $ExpectError + sfillEqual( x.length, false, 5.0, x, 1 ); // $ExpectError + sfillEqual( x.length, null, 5.0, x, 1 ); // $ExpectError + sfillEqual( x.length, undefined, 5.0, x, 1 ); // $ExpectError + sfillEqual( x.length, [], 5.0, x, 1 ); // $ExpectError + sfillEqual( x.length, {}, 5.0, x, 1 ); // $ExpectError + sfillEqual( x.length, ( x: number ): number => x, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual( x.length, 0.0, '10', x, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, true, x, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, false, x, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, null, x, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, undefined, x, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, [], x, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, {}, x, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillEqual( x.length, 0.0, 5.0, 10, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, '10', 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, true, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, false, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, null, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, undefined, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, [], 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, {}, 1 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual( x.length, 0.0, 5.0, x, '10' ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, true ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, false ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, null ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, undefined ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, [] ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, {} ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + sfillEqual(); // $ExpectError + sfillEqual( x.length ); // $ExpectError + sfillEqual( x.length, 0.0 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0 ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x ); // $ExpectError + sfillEqual( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray( '10', 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( true, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( false, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( null, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( undefined, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( [], 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( {}, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( ( x: number ): number => x, 0.0, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray( x.length, '10', 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, true, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, false, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, null, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, undefined, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, [], 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, {}, 5.0, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, ( x: number ): number => x, x, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray( x.length, 0.0, '10', x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, true, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, false, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, null, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, undefined, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, [], x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, {}, x, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray( x.length, 0.0, 5.0, 10, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, '10', 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, true, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, false, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, null, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, undefined, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, [], 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, {}, 1, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray( x.length, 0.0, 5.0, x, '10', 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, true, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, false, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, null, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, undefined, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, [], 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, {}, 0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, ( x: number ): number => x, x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, '10' ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, true ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, false ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, null ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, undefined ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, [] ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + sfillEqual.ndarray(); // $ExpectError + sfillEqual.ndarray( x.length ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, x ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1 ); // $ExpectError + sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/c/example.c new file mode 100644 index 000000000000..0d79c7dedb4d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_equal.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace equal elements: + stdlib_strided_sfill_equal( N, 5.0f, 10.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/index.js new file mode 100644 index 000000000000..a4c02fe31f55 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/examples/index.js @@ -0,0 +1,28 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var zeros = require( '@stdlib/array/zeros' ); +var sfillEqual = require( './../lib' ); + +var x = zeros( 10, 'float32' ); +console.log( x ); + +sfillEqual( x.length, 0.0, 5.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 5.0, 5.0, 1.0, 5.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var sfillEqual = require( '@stdlib/blas/ext/base/sfill-equal' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* sfillEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var sfillEqual; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + sfillEqual = main; +} else { + sfillEqual = tmp; +} + + +// EXPORTS // + +module.exports = sfillEqual; + +// exports: { "ndarray": "sfillEqual.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/main.js new file mode 100644 index 000000000000..ee10e83f8239 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sfillEqual = require( './sfill_equal.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( sfillEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/native.js new file mode 100644 index 000000000000..13a92c61080b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sfillEqual = require( './sfill_equal.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( sfillEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/ndarray.js new file mode 100644 index 000000000000..0fafe4c0120a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/ndarray.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {integer} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* sfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function sfillEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var ix; + var i; + + if ( N <= 0 ) { + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] === searchElement ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = sfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/ndarray.native.js new file mode 100644 index 000000000000..2098994a0a32 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/ndarray.native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {integer} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* sfillEqual( x.length, 0.0, 5.0, x, 1, 0 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function sfillEqual( N, searchElement, alpha, x, strideX, offsetX ) { + addon.ndarray( N, searchElement, alpha, x, strideX, offsetX ); + return x; +} + + +// EXPORTS // + +module.exports = sfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/sfill_equal.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/sfill_equal.js new file mode 100644 index 000000000000..896e6298b9ee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/sfill_equal.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* sfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function sfillEqual( N, searchElement, alpha, x, strideX ) { + return ndarray( N, searchElement, alpha, x, strideX, stride2offset( N, strideX ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = sfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/sfill_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/sfill_equal.native.js new file mode 100644 index 000000000000..00e2a568046a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/lib/sfill_equal.native.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* sfillEqual( x.length, 0.0, 5.0, x, 1 ); +* // x => [ 5.0, 5.0, 1.0, 5.0 ] +*/ +function sfillEqual( N, searchElement, alpha, x, strideX ) { + addon( N, searchElement, alpha, x, strideX ); + return x; +} + + +// EXPORTS // + +module.exports = sfillEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/manifest.json new file mode 100644 index 000000000000..9184cfd03771 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/manifest.json @@ -0,0 +1,79 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/package.json new file mode 100644 index 000000000000..d50e342c03c8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/sfill-equal", + "version": "0.0.0", + "description": "Replace single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "equal", + "same", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float32", + "single", + "float32array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/addon.c new file mode 100644 index 000000000000..b1aa44f87999 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_sfill_equal)( N, searchElement, alpha, X, strideX ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_sfill_equal_ndarray)( N, searchElement, alpha, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/main.c new file mode 100644 index 000000000000..55dcce268076 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/src/main.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_sfill_equal)( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_sfill_equal_ndarray)( N, searchElement, alpha, X, strideX, ox ); +} + +/** +* Replaces single-precision floating-point strided array elements equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_sfill_equal_ndarray)( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] == searchElement ) { + X[ ix ] = alpha; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.js new file mode 100644 index 000000000000..d5c37d04bea2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var sfillEqual = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof sfillEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var sfillEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfillEqual, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var sfillEqual; + var main; + + main = require( './../lib/sfill_equal.js' ); + + sfillEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfillEqual, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.ndarray.js new file mode 100644 index 000000000000..82ecaab0a3fa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.ndarray.js @@ -0,0 +1,179 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfillEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( sfillEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + sfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = sfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + + out = sfillEqual( 0, 1.0, 5.0, x, 1, 0 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + sfillEqual( 3, 1.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float32Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + sfillEqual( 3, 1.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + sfillEqual( 3, 1.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.ndarray.native.js new file mode 100644 index 000000000000..fcdfcdb0a17e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.ndarray.native.js @@ -0,0 +1,188 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfillEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfillEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( sfillEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + sfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = sfillEqual( x.length, 1.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + + out = sfillEqual( 0, 1.0, 5.0, x, 1, 0 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + sfillEqual( 3, 1.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float32Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + sfillEqual( 3, 1.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an offset parameter', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + sfillEqual( 3, 1.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.sfill_equal.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.sfill_equal.js new file mode 100644 index 000000000000..2d705e50b4e2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.sfill_equal.js @@ -0,0 +1,183 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfillEqual = require( './../lib/sfill_equal.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( sfillEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + sfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 0.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = sfillEqual( x.length, 1.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + + out = sfillEqual( 0, 1.0, 5.0, x, 1 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + sfillEqual( 3, 1.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float32Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + sfillEqual( 3, 1.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + sfillEqual( 3, 1.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.sfill_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.sfill_equal.native.js new file mode 100644 index 000000000000..ad4f8d7e95d5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-equal/test/test.sfill_equal.native.js @@ -0,0 +1,192 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfillEqual = tryRequire( resolve( __dirname, './../lib/sfill_equal.native.js' ) ); +var opts = { + 'skip': ( sfillEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( sfillEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces values equal to the provided `searchElement` in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + 2.0, + 1.0, + 5.0, + -1.0, + 1.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 5.0, + 2.0, + 5.0, + 5.0, + -1.0, + 5.0, + -5.0, + 6.0 + ]); + + sfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillEqual( x.length, 1.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 0.0, 1.0, 3.0, 1.0, 5.0 ] ); + out = sfillEqual( x.length, 1.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 1.0, -4.0, 1.0 ] ); + + out = sfillEqual( 0, 1.0, 5.0, x, 1 ); + t.strictEqual( out, x, 'returns expected value' ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 2 + ]); + + sfillEqual( 3, 1.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 1.0 // 0 + ]); + expected = new Float32Array([ + 5.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 5.0 // 0 + ]); + + sfillEqual( 3, 1.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + 1.0, // 0 + 3.0, + 1.0, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 5.0, // 0 + 3.0, + 5.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + sfillEqual( 3, 1.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/README.md b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/README.md new file mode 100644 index 000000000000..4db503b933bb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/README.md @@ -0,0 +1,284 @@ + + +# sfillNaN + +> Replace single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + +
+ +## Usage + +```javascript +var sfillNaN = require( '@stdlib/blas/ext/base/sfill-nan' ); +``` + +#### sfillNaN( N, alpha, x, strideX ) + +Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + +sfillNaN( x.length, 0.0, x, 1 ); +// x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **alpha**: scalar constant. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ NaN, 1.0, NaN, -5.0, NaN, 0.0, -1.0, -3.0 ] ); + +sfillNaN( 4, 0.0, x, 2 ); +// x => [ 0.0, 1.0, 0.0, -5.0, 0.0, 0.0, -1.0, -3.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial array: +var x0 = new Float32Array( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + +// Create an offset view: +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +sfillNaN( 3, 0.0, x1, 2 ); +// x0 => [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] +``` + +#### sfillNaN.ndarray( N, alpha, x, strideX, offsetX ) + +Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + +sfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +// x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + +sfillNaN.ndarray( 3, 0.0, x, 1, x.length-3 ); +// x => [ 1.0, NaN, 3.0, 0.0, 5.0, -6.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var nans = require( '@stdlib/array/nans' ); +var sfillNaN = require( '@stdlib/blas/ext/base/sfill-nan' ); + +var x = nans( 10, 'float32' ); +console.log( x ); + +sfillNaN( x.length, 0.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sfill_nan.h" +``` + +#### stdlib_strided_sfill_nan( N, alpha, \*X, strideX ) + +Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + +```c +float x[] = { 1.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f }; + +stdlib_strided_sfill_nan( 4, 0.0f, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_sfill_nan( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_sfill_nan_ndarray( N, alpha, \*X, strideX, offsetX ) + +Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + +```c +float x[] = { 1.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f }; + +stdlib_strided_sfill_nan_ndarray( 4, 0.0f, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_sfill_nan_ndarray( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sfill_nan.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 5.0f, -6.0f, 7.0f, 0.0f/0.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements equal to `NaN`: + stdlib_strided_sfill_nan( N, 0.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.js new file mode 100644 index 000000000000..c1d1888614d9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfillNaN = require( './../lib/sfill_nan.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNaN( x.length, 0.0, x, 1 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.native.js new file mode 100644 index 000000000000..4a3f5e3e0498 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfillNaN = tryRequire( resolve( __dirname, './../lib/sfill_nan.native.js' ) ); +var opts = { + 'skip': ( sfillNaN instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNaN( x.length, 0.0, x, 1 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..2523319913a3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfillNaN = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNaN( x.length, 0.0, x, 1, 0 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..b0d05e053179 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfillNaN = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfillNaN instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = NaN; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNaN( x.length, 0.0, x, 1, 0 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..8940faee39d3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/benchmark/c/benchmark.length.c @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_nan.h" +#include +#include +#include +#include +#include + +#define NAME "sfill-nan" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0f / 0.0f; + } else { + x[ i ] = ( rand_float()*200.0f ) - 100.0f; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_sfill_nan( len, 0.0f, x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0f / 0.0f; + } else { + x[ i ] = ( rand_float()*200.0f ) - 100.0f; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_sfill_nan_ndarray( len, 0.0f, x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/repl.txt new file mode 100644 index 000000000000..7366d753d23f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/repl.txt @@ -0,0 +1,97 @@ + +{{alias}}( N, alpha, x, strideX ) + Replaces single-precision floating-point strided array elements equal to + `NaN` with a specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ NaN, 1.0, 3.0, NaN ] ); + > {{alias}}( x.length, 0.0, x, 1 ) + [ 0.0, 1.0, 3.0, 0.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ NaN, 1.0, NaN, -5.0, NaN ] ); + > {{alias}}( 3, 0.0, x, 2 ) + [ 0.0, 1.0, 0.0, -5.0, 0.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 0.0, x1, 2 ) + [ 0.0, 3.0, 0.0, 5.0, -6.0 ] + > x0 + [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] + + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX ) + Replaces single-precision floating-point strided array elements equal to + `NaN` with a specified scalar constant using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ NaN, 1.0, 3.0, NaN ] ); + > {{alias}}.ndarray( x.length, 0.0, x, 1, 0 ) + [ 0.0, 1.0, 3.0, 0.0 ] + + // Using an index offset: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, NaN, 3.0, NaN, 5.0, -6.0 ] ); + > {{alias}}.ndarray( 3, 0.0, x, 2, 1 ) + [ 1.0, 0.0, 3.0, 0.0, 5.0, -6.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/types/index.d.ts new file mode 100644 index 000000000000..fffef642ffaa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/types/index.d.ts @@ -0,0 +1,95 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `sfillNaN`. +*/ +interface Routine { + /** + * Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * sfillNaN( x.length, 0.0, x, 1 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + ( N: number, alpha: number, x: Float32Array, strideX: number ): Float32Array; + + /** + * Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); + * + * sfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); + * // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] + */ + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): Float32Array; +} + +/** +* Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param N - number of indexed elements +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); +* +* sfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ NaN, 1.0, 3.0, NaN, 4.0, 0.0, -1.0, -3.0 ] ); +* +* sfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +* // x => [ 0.0, 1.0, 3.0, 0.0, 4.0, 0.0, -1.0, -3.0 ] +*/ +declare var sfillNaN: Routine; + + +// EXPORTS // + +export = sfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/types/test.ts new file mode 100644 index 000000000000..8afa2f2ea9cd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/docs/types/test.ts @@ -0,0 +1,187 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import sfillNaN = require( './index' ); + + +// TESTS // + +// The function returns a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNaN( x.length, 0.0, x, 1 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNaN( '10', 0.0, x, 1 ); // $ExpectError + sfillNaN( true, 0.0, x, 1 ); // $ExpectError + sfillNaN( false, 0.0, x, 1 ); // $ExpectError + sfillNaN( null, 0.0, x, 1 ); // $ExpectError + sfillNaN( undefined, 0.0, x, 1 ); // $ExpectError + sfillNaN( [], 0.0, x, 1 ); // $ExpectError + sfillNaN( {}, 0.0, x, 1 ); // $ExpectError + sfillNaN( ( x: number ): number => x, 0.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNaN( x.length, '10', x, 1 ); // $ExpectError + sfillNaN( x.length, true, x, 1 ); // $ExpectError + sfillNaN( x.length, false, x, 1 ); // $ExpectError + sfillNaN( x.length, null, x, 1 ); // $ExpectError + sfillNaN( x.length, undefined, x, 1 ); // $ExpectError + sfillNaN( x.length, [], x, 1 ); // $ExpectError + sfillNaN( x.length, {}, x, 1 ); // $ExpectError + sfillNaN( x.length, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNaN( x.length, 0.0, 10, 1 ); // $ExpectError + sfillNaN( x.length, 0.0, '10', 1 ); // $ExpectError + sfillNaN( x.length, 0.0, true, 1 ); // $ExpectError + sfillNaN( x.length, 0.0, false, 1 ); // $ExpectError + sfillNaN( x.length, 0.0, null, 1 ); // $ExpectError + sfillNaN( x.length, 0.0, undefined, 1 ); // $ExpectError + sfillNaN( x.length, 0.0, [], 1 ); // $ExpectError + sfillNaN( x.length, 0.0, {}, 1 ); // $ExpectError + sfillNaN( x.length, 0.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNaN( x.length, 0.0, x, '10' ); // $ExpectError + sfillNaN( x.length, 0.0, x, true ); // $ExpectError + sfillNaN( x.length, 0.0, x, false ); // $ExpectError + sfillNaN( x.length, 0.0, x, null ); // $ExpectError + sfillNaN( x.length, 0.0, x, undefined ); // $ExpectError + sfillNaN( x.length, 0.0, x, [] ); // $ExpectError + sfillNaN( x.length, 0.0, x, {} ); // $ExpectError + sfillNaN( x.length, 0.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + sfillNaN(); // $ExpectError + sfillNaN( x.length ); // $ExpectError + sfillNaN( x.length, 0.0 ); // $ExpectError + sfillNaN( x.length, 0.0, x ); // $ExpectError + sfillNaN( x.length, 0.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNaN.ndarray( '10', 0.0, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( true, 0.0, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( false, 0.0, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( null, 0.0, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( undefined, 0.0, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( [], 0.0, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( {}, 0.0, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( ( x: number ): number => x, 0.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNaN.ndarray( x.length, '10', x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, true, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, false, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, null, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, undefined, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, [], x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, {}, x, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNaN.ndarray( x.length, 0.0, 10, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, '10', 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, true, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, false, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, null, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, undefined, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, [], 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, {}, 1, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNaN.ndarray( x.length, 0.0, x, '10', 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, true, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, false, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, null, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, undefined, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, [], 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, {}, 0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNaN.ndarray( x.length, 0.0, x, 1, '10' ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, true ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, false ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, null ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, undefined ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, [] ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, {} ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + sfillNaN.ndarray(); // $ExpectError + sfillNaN.ndarray( x.length ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1 ); // $ExpectError + sfillNaN.ndarray( x.length, 0.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/c/example.c new file mode 100644 index 000000000000..18fe1ccedc3f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_nan.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 1.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 5.0f, -6.0f, 7.0f, 0.0f/0.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements equal to `NaN`: + stdlib_strided_sfill_nan( N, 0.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/index.js new file mode 100644 index 000000000000..6e7dc8a972ab --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/examples/index.js @@ -0,0 +1,28 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var nans = require( '@stdlib/array/nans' ); +var sfillNaN = require( './../lib' ); + +var x = nans( 10, 'float32' ); +console.log( x ); + +sfillNaN( x.length, 0.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 0.0, 0.0, 1.0, 0.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var sfillNaN = require( '@stdlib/blas/ext/base/sfill-nan' ); +* +* var x = new Float32Array( [ NaN, NaN, 1.0, NaN ] ); +* +* sfillNaN.ndarray( x.length, 0.0, x, 1, 0 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var sfillNaN; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + sfillNaN = main; +} else { + sfillNaN = tmp; +} + + +// EXPORTS // + +module.exports = sfillNaN; + +// exports: { "ndarray": "sfillNaN.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/main.js new file mode 100644 index 000000000000..f04cefcac3d5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sfillNaN = require( './sfill_nan.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( sfillNaN, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/native.js new file mode 100644 index 000000000000..d656b08bf673 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sfillNaN = require( './sfill_nan.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( sfillNaN, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/ndarray.js new file mode 100644 index 000000000000..a0e614b6df0d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/ndarray.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ NaN, -2.0, 3.0, NaN, 5.0, -6.0 ] ); +* +* sfillNaN( 6, 0.0, x, 1, 0 ); +* // x => [ 0.0, -2.0, 3.0, 0.0, 5.0, -6.0 ] +*/ +function sfillNaN( N, alpha, x, strideX, offsetX ) { + var ix; + var i; + + if ( N <= 0 ) { + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( isnanf( x[ ix ] ) ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = sfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/ndarray.native.js new file mode 100644 index 000000000000..2749c82a36c7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/ndarray.native.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ NaN, -2.0, 3.0, NaN, 5.0, -6.0 ] ); +* +* sfillNaN( 6, 0.0, x, 1, 0 ); +* // x => [ 0.0, -2.0, 3.0, 0.0, 5.0, -6.0 ] +*/ +function sfillNaN( N, alpha, x, strideX, offsetX ) { + addon.ndarray( N, alpha, x, strideX, offsetX ); + return x; +} + + +// EXPORTS // + +module.exports = sfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/sfill_nan.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/sfill_nan.js new file mode 100644 index 000000000000..25492e03712e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/sfill_nan.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ NaN, NaN, 1.0, NaN ] ); +* +* sfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +*/ +function sfillNaN( N, alpha, x, strideX ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ) ); +} + + +// EXPORTS // + +module.exports = sfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/sfill_nan.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/sfill_nan.native.js new file mode 100644 index 000000000000..20cb5d9353f7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/lib/sfill_nan.native.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ NaN, NaN, 1.0, NaN ] ); +* +* sfillNaN( x.length, 0.0, x, 1 ); +* // x => [ 0.0, 0.0, 1.0, 0.0 ] +*/ +function sfillNaN( N, alpha, x, strideX ) { + addon( N, alpha, x, strideX ); + return x; +} + + +// EXPORTS // + +module.exports = sfillNaN; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/manifest.json new file mode 100644 index 000000000000..fea47805d59c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/manifest.json @@ -0,0 +1,82 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/math/base/assert/is-nanf" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/package.json b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/package.json new file mode 100644 index 000000000000..11d432e28504 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/sfill-nan", + "version": "0.0.0", + "description": "Replace single-precision floating-point strided array elements equal to NaN with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "nan", + "not-a-number", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float32", + "single", + "float32array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/addon.c new file mode 100644 index 000000000000..fc02c3da50f2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/addon.c @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_nan.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_sfill_nan)( N, alpha, X, strideX ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + API_SUFFIX(stdlib_strided_sfill_nan_ndarray)( N, alpha, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/main.c new file mode 100644 index 000000000000..a2089996434f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/src/main.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_nan.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/math/base/assert/is_nanf.h" + +/** +* Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_sfill_nan)( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_sfill_nan_ndarray)( N, alpha, X, strideX, ox ); +} + +/** +* Replaces single-precision floating-point strided array elements equal to `NaN` with a specified scalar constant using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_sfill_nan_ndarray)( const CBLAS_INT N, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( stdlib_base_is_nanf( X[ ix ] ) ) { + X[ ix ] = alpha; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.js new file mode 100644 index 000000000000..33038d3b0363 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var sfillNaN = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof sfillNaN.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var sfillNaN = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfillNaN, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var sfillNaN; + var main; + + main = require( './../lib/sfill_nan.js' ); + + sfillNaN = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfillNaN, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.ndarray.js new file mode 100644 index 000000000000..935455720f15 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.ndarray.js @@ -0,0 +1,181 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfillNaN = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( sfillNaN.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + sfillNaN( x.length, 0.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ NaN, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillNaN( x.length, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = sfillNaN( x.length, 0.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var x; + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + + sfillNaN( 0, 0.0, x, 1, 0 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + sfillNaN( -4, 0.0, x, 1, 0 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float32Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + sfillNaN( 3, 0.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + sfillNaN( 3, 0.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + sfillNaN( 3, 0.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.ndarray.native.js new file mode 100644 index 000000000000..9a0394b944f6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.ndarray.native.js @@ -0,0 +1,190 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfillNaN = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfillNaN instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( sfillNaN.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + sfillNaN( x.length, 0.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ NaN, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillNaN( x.length, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = sfillNaN( x.length, 0.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var x; + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + + sfillNaN( 0, 0.0, x, 1, 0 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + sfillNaN( -4, 0.0, x, 1, 0 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float32Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + sfillNaN( 3, 0.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + sfillNaN( 3, 0.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + sfillNaN( 3, 0.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.sfill_nan.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.sfill_nan.js new file mode 100644 index 000000000000..efebd51ec8ca --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.sfill_nan.js @@ -0,0 +1,184 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfillNaN = require( './../lib/sfill_nan.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( sfillNaN.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + sfillNaN( x.length, 0.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ NaN, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillNaN( x.length, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = sfillNaN( x.length, 0.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var x; + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + + sfillNaN( 0, 0.0, x, 1 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + sfillNaN( -4, 0.0, x, 1 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float32Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + sfillNaN( 3, 0.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + sfillNaN( 3, 0.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + sfillNaN( 3, 0.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.sfill_nan.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.sfill_nan.native.js new file mode 100644 index 000000000000..5240a82ac2ad --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-nan/test/test.sfill_nan.native.js @@ -0,0 +1,193 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfillNaN = tryRequire( resolve( __dirname, './../lib/sfill_nan.native.js' ) ); +var opts = { + 'skip': ( sfillNaN instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNaN, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', opts, function test( t ) { + t.strictEqual( sfillNaN.length, 4, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces `NaN` values in a strided array', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, + 2.0, + NaN, + 5.0, + -1.0, + NaN, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 2.0, + 0.0, + 5.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + + sfillNaN( x.length, 0.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ NaN, 2.0 ] ); + expected = new Float32Array( [ 5.0, 2.0 ] ); + + sfillNaN( x.length, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, NaN, 3.0, NaN, 5.0 ] ); + out = sfillNaN( x.length, 0.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var x; + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + + sfillNaN( 0, 0.0, x, 1 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + x = new Float32Array( [ NaN, -4.0, 1.0 ] ); + sfillNaN( -4, 0.0, x, 1 ); + t.ok( isnanf( x[ 0 ] ), 'returns expected value' ); + t.strictEqual( x[ 1 ], -4.0, 'returns expected value' ); + t.strictEqual( x[ 2 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 0 + -3.0, + -5.0, // 1 + 7.0, + NaN // 2 + ]); + expected = new Float32Array([ + 0.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 2 + ]); + + sfillNaN( 3, 0.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + NaN, // 2 + -3.0, + -5.0, // 1 + 7.0, + NaN // 0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 0.0 // 0 + ]); + + sfillNaN( 3, 0.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 1.0, + NaN, // 0 + 3.0, + NaN, // 1 + 5.0, + 6.0 // 2 + ]); + expected = new Float32Array([ + 1.0, + 0.0, // 0 + 3.0, + 0.0, // 1 + 5.0, + 6.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + sfillNaN( 3, 0.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/README.md new file mode 100644 index 000000000000..966ef0bfa67d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/README.md @@ -0,0 +1,294 @@ + + +# sfillNotEqual + +> Replace single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + +
+ +## Usage + +```javascript +var sfillNotEqual = require( '@stdlib/blas/ext/base/sfill-not-equal' ); +``` + +#### sfillNotEqual( N, searchElement, alpha, x, strideX ) + +Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **searchElement**: search element. +- **alpha**: scalar constant. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length. + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to iterate over every other element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +sfillNotEqual( 3, 0.0, 5.0, x, 2 ); +// x => [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial array: +var x0 = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +// Create an offset view: +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Iterate over every other element: +sfillNotEqual( 3, 0.0, 5.0, x1, 2 ); +// x0 => [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] +``` + +#### sfillNotEqual.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + +Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); +// x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + +sfillNotEqual.ndarray( 3, 0.0, 5.0, x, 1, x.length-3 ); +// x => [ 0.0, -2.0, 3.0, 0.0, 5.0, 5.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `x` unchanged. +- When comparing elements, both functions check for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct (i.e., as `NaN !== NaN` always evaluates to `true`, `NaN` elements are always replaced), and `-0` and `+0` are considered the same. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sfillNotEqual = require( '@stdlib/blas/ext/base/sfill-not-equal' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'float32' +}); +console.log( x ); + +sfillNotEqual( x.length, 1.0, 5.0, x, 1 ); +console.log( x ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sfill_not_equal.h" +``` + +#### stdlib_strided_sfill_not_equal( N, searchElement, alpha, \*X, strideX ) + +Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + +```c +float x[] = { 0.0f, -2.0f, 3.0f, 0.0f, 4.0f, -6.0f }; + +stdlib_strided_sfill_not_equal( 6, 0.0f, 5.0f, x, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] float` search element. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +void stdlib_strided_sfill_not_equal( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX ); +``` + + + +#### stdlib_strided_sfill_not_equal_ndarray( N, searchElement, alpha, \*X, strideX, offsetX ) + + + +Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + +```c +float x[] = { 0.0f, -2.0f, 3.0f, 0.0f, 4.0f, -6.0f }; + +stdlib_strided_sfill_not_equal_ndarray( 6, 0.0f, 5.0f, x, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **searchElement**: `[in] float` search element. +- **alpha**: `[in] float` scalar constant. +- **X**: `[inout] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +void stdlib_strided_sfill_not_equal_ndarray( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sfill_not_equal.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 0.0f, -2.0f, 3.0f, 0.0f, 4.0f, -6.0f, 0.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements not equal to `0.0f`: + stdlib_strided_sfill_not_equal( N, 0.0f, 5.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..baf280e044fa --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfillNotEqual = require( './../lib/sfill_not_equal.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNotEqual( x.length, i, i+1, x, 1 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.native.js new file mode 100644 index 000000000000..e41bededb341 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfillNotEqual = tryRequire( resolve( __dirname, './../lib/sfill_not_equal.native.js' ) ); +var opts = { + 'skip': ( sfillNotEqual instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNotEqual( x.length, i, i+1, x, 1 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..9a3d1db3a7a5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfillNotEqual = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNotEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..e076b4097114 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfillNotEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfillNotEqual instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x; + var i; + + x = uniform( len, -100, 100, options ); + for ( i = 0; i < x.length; i += 3 ) { + x[ i ] = 0.0; + } + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var y; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = sfillNotEqual( x.length, i, i+1, x, 1, 0 ); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( y[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..f52ed5937add --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/benchmark/c/benchmark.length.c @@ -0,0 +1,199 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_not_equal.h" +#include +#include +#include +#include +#include + +#define NAME "sfill-not-equal" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0f; + } else { + x[ i ] = ( rand_float()*200.0f ) - 100.0f; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_sfill_not_equal( len, (float)i, (float)(i+1), x, 1 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + double t; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + if ( i%3 == 0 ) { + x[ i ] = 0.0f; + } else { + x[ i ] = ( rand_float()*200.0f ) - 100.0f; + } + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + stdlib_strided_sfill_not_equal_ndarray( len, (float)i, (float)(i+1), x, 1, 0 ); + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( x[ 0 ] != x[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/repl.txt new file mode 100644 index 000000000000..46105fc7b100 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/repl.txt @@ -0,0 +1,104 @@ + +{{alias}}( N, searchElement, alpha, x, strideX ) + Replaces single-precision floating-point strided array elements not equal to + a provided search element with a specified scalar constant. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `x` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}( x.length, 0.0, 5.0, x, 1 ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}( 3, 0.0, 5.0, x, 2 ) + [ 0.0, -2.0, 5.0, 0.0, 5.0, -6.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 3, 0.0, 5.0, x1, 2 ) + [ 5.0, 3.0, 0.0, 4.0, 5.0 ] + > x0 + [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] + + +{{alias}}.ndarray( N, searchElement, alpha, x, strideX, offsetX ) + Replaces single-precision floating-point strided array elements not equal to + a provided search element with a specified scalar constant using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a starting + index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + searchElement: number + Search element. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + x: Float32Array + Input array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}.ndarray( x.length, 0.0, 5.0, x, 1, 0 ) + [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + + // Using an index offset: + > x = new {{alias:@stdlib/array/float32}}( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + > {{alias}}.ndarray( 3, 0.0, 5.0, x, 2, 1 ) + [ 0.0, 5.0, 3.0, 0.0, 4.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..9f1e62530fc9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/types/index.d.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `sfillNotEqual`. +*/ +interface Routine { + /** + * Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * sfillNotEqual( 6, 0.0, 5.0, x, 1 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + ( N: number, searchElement: number, alpha: number, x: Float32Array, strideX: number ): Float32Array; + + /** + * Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param searchElement - search element + * @param alpha - scalar constant + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns `x` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); + * + * sfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); + * // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] + */ + ndarray( N: number, searchElement: number, alpha: number, x: Float32Array, strideX: number, offsetX: number ): Float32Array; +} + +/** +* Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param N - number of indexed elements +* @param searchElement - search element +* @param alpha - scalar constant +* @param x - input array +* @param strideX - stride length +* @returns `x` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* sfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* sfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +declare var sfillNotEqual: Routine; + + +// EXPORTS // + +export = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/types/test.ts new file mode 100644 index 000000000000..85a639ae391a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/docs/types/test.ts @@ -0,0 +1,214 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import sfillNotEqual = require( './index' ); + + +// TESTS // + +// The function returns a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual( '10', 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( true, 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( false, 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( null, 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( undefined, 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( [], 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( {}, 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( ( x: number ): number => x, 0.0, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual( x.length, '10', 5.0, x, 1 ); // $ExpectError + sfillNotEqual( x.length, true, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( x.length, false, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( x.length, null, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( x.length, undefined, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( x.length, [], 5.0, x, 1 ); // $ExpectError + sfillNotEqual( x.length, {}, 5.0, x, 1 ); // $ExpectError + sfillNotEqual( x.length, ( x: number ): number => x, 5.0, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual( x.length, 0.0, '10', x, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, true, x, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, false, x, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, null, x, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, undefined, x, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, [], x, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, {}, x, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual( x.length, 0.0, 5.0, '10', 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, true, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, false, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, null, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, undefined, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, [], 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, {}, 1 ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual( x.length, 0.0, 5.0, x, '10' ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, true ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, false ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, null ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, undefined ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, [] ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, {} ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual(); // $ExpectError + sfillNotEqual( x.length ); // $ExpectError + sfillNotEqual( x.length, 0.0 ); // $ExpectError + sfillNotEqual( x.length, 0.0, x ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x ); // $ExpectError + sfillNotEqual( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray( '10', 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( true, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( false, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( null, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( undefined, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( [], 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( {}, 0.0, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( ( x: number ): number => x, 0.0, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray( x.length, '10', 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, true, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, false, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, null, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, undefined, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, [], 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, {}, 5.0, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, ( x: number ): number => x, 5.0, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray( x.length, 0.0, '10', x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, true, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, false, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, null, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, undefined, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, [], x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, {}, x, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray( x.length, 0.0, 5.0, '10', 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, true, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, false, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, null, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, undefined, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, [], 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, {}, 1, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, '10', 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, true, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, false, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, null, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, undefined, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, [], 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, {}, 0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, '10' ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, true ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, false ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, null ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, undefined ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, [] ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, {} ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + + sfillNotEqual.ndarray(); // $ExpectError + sfillNotEqual.ndarray( x.length ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1 ); // $ExpectError + sfillNotEqual.ndarray( x.length, 0.0, 5.0, x, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/c/example.c new file mode 100644 index 000000000000..da16783f597b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_not_equal.h" +#include + +int main( void ) { + // Create a strided array: + float x[] = { 0.0f, -2.0f, 3.0f, 0.0f, 4.0f, -6.0f, 0.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify a stride: + const int strideX = 1; + + // Replace elements not equal to `0.0f`: + stdlib_strided_sfill_not_equal( N, 0.0f, 5.0f, x, strideX ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "x[ %i ] = %f\n", i, x[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/index.js new file mode 100644 index 000000000000..41594daeefa4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sfillNotEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 3, { + 'dtype': 'float32' +}); +console.log( x ); + +sfillNotEqual( x.length, 1.0, 5.0, x, 1 ); +console.log( x ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var sfillNotEqual = require( '@stdlib/blas/ext/base/sfill-not-equal' ); +* +* var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* sfillNotEqual.ndarray( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var sfillNotEqual; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + sfillNotEqual = main; +} else { + sfillNotEqual = tmp; +} + + +// EXPORTS // + +module.exports = sfillNotEqual; + +// exports: { "ndarray": "sfillNotEqual.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/main.js new file mode 100644 index 000000000000..0eeb81e5758d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sfillNotEqual = require( './sfill_not_equal.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( sfillNotEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/native.js new file mode 100644 index 000000000000..313fab8b03bd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sfillNotEqual = require( './sfill_not_equal.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( sfillNotEqual, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/ndarray.js new file mode 100644 index 000000000000..cb15d8c21847 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/ndarray.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* sfillNotEqual( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function sfillNotEqual( N, searchElement, alpha, x, strideX, offsetX ) { + var ix; + var i; + + if ( N <= 0 ) { + return x; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( x[ ix ] !== searchElement ) { + x[ ix ] = alpha; + } + ix += strideX; + } + return x; +} + + +// EXPORTS // + +module.exports = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/ndarray.native.js new file mode 100644 index 000000000000..776a2be1b647 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/ndarray.native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @param {NonNegativeInteger} offsetX - starting index +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* sfillNotEqual( 6, 0.0, 5.0, x, 1, 0 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function sfillNotEqual( N, searchElement, alpha, x, strideX, offsetX ) { + addon.ndarray( N, searchElement, alpha, x, strideX, offsetX ); + return x; +} + + +// EXPORTS // + +module.exports = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/sfill_not_equal.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/sfill_not_equal.js new file mode 100644 index 000000000000..4590b02a56c6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/sfill_not_equal.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* sfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function sfillNotEqual( N, searchElement, alpha, x, strideX ) { + return ndarray( N, searchElement, alpha, x, strideX, stride2offset( N, strideX ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/sfill_not_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/sfill_not_equal.native.js new file mode 100644 index 000000000000..933df814db3a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/lib/sfill_not_equal.native.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} searchElement - search element +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length +* @returns {Float32Array} input array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, -2.0, 3.0, 0.0, 4.0, -6.0 ] ); +* +* sfillNotEqual( 6, 0.0, 5.0, x, 1 ); +* // x => [ 0.0, 5.0, 5.0, 0.0, 5.0, 5.0 ] +*/ +function sfillNotEqual( N, searchElement, alpha, x, strideX ) { + addon( N, searchElement, alpha, x, strideX ); + return x; +} + + +// EXPORTS // + +module.exports = sfillNotEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/manifest.json new file mode 100644 index 000000000000..9184cfd03771 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/manifest.json @@ -0,0 +1,79 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/package.json b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/package.json new file mode 100644 index 000000000000..3780cb8c5b93 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/sfill-not-equal", + "version": "0.0.0", + "description": "Replace single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "fill", + "not equal", + "unequal", + "replace", + "assign", + "set", + "strided", + "array", + "ndarray", + "float32", + "single", + "float32array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/addon.c new file mode 100644 index 000000000000..32c5e6de8610 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_not_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_sfill_not_equal)( N, searchElement, alpha, X, strideX ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, searchElement, argv, 1 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 3 ); + API_SUFFIX(stdlib_strided_sfill_not_equal_ndarray)( N, searchElement, alpha, X, strideX, offsetX ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/main.c new file mode 100644 index 000000000000..d3706e785f14 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/src/main.c @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfill_not_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +/** +* Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +*/ +void API_SUFFIX(stdlib_strided_sfill_not_equal)( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + API_SUFFIX(stdlib_strided_sfill_not_equal_ndarray)( N, searchElement, alpha, X, strideX, ox ); +} + +/** +* Replaces single-precision floating-point strided array elements not equal to a provided search element with a specified scalar constant using alternative indexing semantics. +* +* @param N number of indexed elements +* @param searchElement search element +* @param alpha scalar constant +* @param X input array +* @param strideX stride length +* @param offsetX starting index +*/ +void API_SUFFIX(stdlib_strided_sfill_not_equal_ndarray)( const CBLAS_INT N, const float searchElement, const float alpha, float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + CBLAS_INT ix; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] != searchElement ) { + X[ ix ] = alpha; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.js new file mode 100644 index 000000000000..bc3fa33f9dbc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var sfillNotEqual = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof sfillNotEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var sfillNotEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfillNotEqual, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var sfillNotEqual; + var main; + + main = require( './../lib/sfill_not_equal.js' ); + + sfillNotEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfillNotEqual, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.ndarray.js new file mode 100644 index 000000000000..c195699e0b8b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.ndarray.js @@ -0,0 +1,241 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfillNotEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( sfillNotEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, 2.0 ] ); + expected = new Float32Array( [ 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + + sfillNotEqual( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 1.0, NaN ] ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + + sfillNotEqual( x.length, NaN, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 0.0, NaN ] ); + expected = new Float32Array( [ 5.0, 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, -0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + + sfillNotEqual( 0, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + sfillNotEqual( -4, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.ndarray.native.js new file mode 100644 index 000000000000..02b86b5086df --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.ndarray.native.js @@ -0,0 +1,250 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfillNotEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfillNotEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( sfillNotEqual.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, 2.0 ] ); + expected = new Float32Array( [ 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + + sfillNotEqual( x.length, 4.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 1.0, NaN ] ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + + sfillNotEqual( x.length, NaN, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 0.0, NaN ] ); + expected = new Float32Array( [ 5.0, 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, -0.0, 5.0, x, 1, 0 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + + sfillNotEqual( 0, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + sfillNotEqual( -4, 0.0, 5.0, x, 1, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, 2, 0 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, -2, 4 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an offset parameter', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, 2, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.sfill_not_equal.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.sfill_not_equal.js new file mode 100644 index 000000000000..5125a30b1fc1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.sfill_not_equal.js @@ -0,0 +1,247 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfillNotEqual = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( sfillNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, 2.0 ] ); + expected = new Float32Array( [ 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + + sfillNotEqual( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 1.0, NaN ] ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + + sfillNotEqual( x.length, NaN, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 0.0, NaN ] ); + expected = new Float32Array( [ 5.0, 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + + sfillNotEqual( 0, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + sfillNotEqual( -4, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', function test( t ) { + var expected; + var x; + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, -0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + sfillNotEqual( 3, 0.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.sfill_not_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.sfill_not_equal.native.js new file mode 100644 index 000000000000..ed5cb4e510b9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfill-not-equal/test/test.sfill_not_equal.native.js @@ -0,0 +1,256 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfillNotEqual = tryRequire( resolve( __dirname, './../lib/sfill_not_equal.native.js' ) ); +var opts = { + 'skip': ( sfillNotEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfillNotEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( sfillNotEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replaces strided array elements not equal to a provided search element', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, + 2.0, + 0.0, + 4.0, + -1.0, + 0.0, + -5.0, + 6.0 + ]); + expected = new Float32Array([ + 0.0, + 5.0, + 0.0, + 5.0, + 5.0, + 0.0, + 5.0, + 5.0 + ]); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, 2.0 ] ); + expected = new Float32Array( [ 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the input array', opts, function test( t ) { + var out; + var x; + + x = new Float32Array( [ 1.0, 0.0, 3.0, 0.0, 5.0 ] ); + out = sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + + t.strictEqual( out, x, 'same reference' ); + t.end(); +}); + +tape( 'if all elements are equal to a provided search element, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + expected = new Float32Array( [ 4.0, 4.0, 4.0 ] ); + + sfillNotEqual( x.length, 4.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a search element equal to `NaN`, the function replaces all elements', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 1.0, NaN ] ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + + sfillNotEqual( x.length, NaN, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replaces `NaN` elements', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ NaN, 0.0, NaN ] ); + expected = new Float32Array( [ 5.0, 0.0, 5.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `x` unchanged', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + expected = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + + sfillNotEqual( 0, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + x = new Float32Array( [ 0.0, -4.0, 1.0 ] ); + sfillNotEqual( -4, 0.0, 5.0, x, 1 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function considers `-0` and `+0` to be the same value', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, 0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + x = new Float32Array( [ -0.0, 1.0, 0.0, -0.0 ] ); + expected = new Float32Array( [ -0.0, 5.0, 0.0, -0.0 ] ); + + sfillNotEqual( x.length, -0.0, 5.0, x, 1 ); + t.strictEqual( isSameFloat32Array( x, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 0 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 2 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 0 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 2 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, 2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a negative stride', opts, function test( t ) { + var expected; + var x; + + x = new Float32Array([ + 0.0, // 2 + -2.0, + 3.0, // 1 + 0.0, + 4.0, // 0 + -6.0 + ]); + expected = new Float32Array([ + 0.0, // 2 + -2.0, + 5.0, // 1 + 0.0, + 5.0, // 0 + -6.0 + ]); + + sfillNotEqual( 3, 0.0, 5.0, x, -2 ); + t.deepEqual( x, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var x1; + + x0 = new Float32Array([ + 0.0, + -2.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + -6.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 5.0, // 0 + 3.0, + 0.0, // 1 + 4.0, + 5.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + + sfillNotEqual( 3, 0.0, 5.0, x1, 2 ); + t.deepEqual( x0, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/README.md b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/README.md new file mode 100644 index 000000000000..a4a2932a4488 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/README.md @@ -0,0 +1,340 @@ + + +# sfirstIndexEqual + +> Return the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var sfirstIndexEqual = require( '@stdlib/blas/ext/base/sfirst-index-equal' ); +``` + +#### sfirstIndexEqual( N, x, strideX, y, strideY ) + +Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +var idx = sfirstIndexEqual( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length for `x`. +- **y**: second input [`Float32Array`][@stdlib/array/float32]. +- **strideY**: stride length for `y`. + +If the function is unable to find matching elements, the function returns `-1`. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y = new Float32Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + +var idx = sfirstIndexEqual( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compare every other element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + +var idx = sfirstIndexEqual( 3, x, 2, y, 2 ); +// returns 1 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial arrays... +var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = sfirstIndexEqual( 2, x1, 1, y1, 1 ); +// returns 1 +``` + +#### sfirstIndexEqual.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + +var idx = sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of each strided array: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Float32Array( [ 0.0, 0.0, 0.0, 4.0, 5.0, 6.0 ] ); + +var idx = sfirstIndexEqual.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 0 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks for equality using the strict equality operator `===`. As a consequence, `NaN` values are considered distinct, and `-0` and `+0` are considered the same. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sfirstIndexEqual = require( '@stdlib/blas/ext/base/sfirst-index-equal' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( y ); + +var idx = sfirstIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sfirst_index_equal.h" +``` + +#### stdlib_strided_sfirst_index_equal( N, \*X, strideX, \*Y, strideY ) + +Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +const float y[] = { 0.0f, 0.0f, 3.0f, 0.0f }; + +int idx = stdlib_strided_sfirst_index_equal( 4, x, 1, y, 1 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[in] float*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +CBLAS_INT stdlib_strided_sfirst_index_equal( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_sfirst_index_equal_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +const float y[] = { 0.0f, 0.0f, 3.0f, 0.0f }; + +int idx = stdlib_strided_sfirst_index_equal_ndarray( 4, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[in] float*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +CBLAS_INT stdlib_strided_sfirst_index_equal_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sfirst_index_equal.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + const float y[] = { 0.0f, -1.0f, -2.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Perform a search: + int idx = stdlib_strided_sfirst_index_equal( N, x, strideX, y, strideY ); + + // Print the result: + printf( "index value: %d\n", idx ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.js new file mode 100644 index 000000000000..d6930a87dfaf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfirstIndexEqual = require( './../lib/sfirst_index_equal.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float32' ); + var y = zeros( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexEqual( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.native.js new file mode 100644 index 000000000000..09bf34993b25 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.native.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/sfirst_index_equal.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexEqual instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float32' ); + var y = zeros( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexEqual( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..44715f5b509d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.ndarray.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfirstIndexEqual = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float32' ); + var y = zeros( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..0ef625044cff --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var oneTo = require( '@stdlib/array/one-to' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexEqual instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = oneTo( len, 'float32' ); + var y = zeros( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..ebf786ebc33f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/benchmark/c/benchmark.length.c @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_equal.h" +#include +#include +#include +#include +#include + +#define NAME "sfirst_index_equal" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + float *y; + double t; + int idx; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + y = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + y[ i ] = -10001.0f; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_sfirst_index_equal( len, x, 1, y, 1 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + float *y; + double t; + int idx; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + y = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + y[ i ] = -10001.0f; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_sfirst_index_equal_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/repl.txt new file mode 100644 index 000000000000..e13b62f90852 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/repl.txt @@ -0,0 +1,112 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a single-precision floating-point + strided array equal to a corresponding element in another single-precision + floating-point strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + First input array. + + strideX: integer + Stride length for `x`. + + y: Float32Array + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var y = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 3.0, 0.0 ] ); + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + > idx = {{alias}}( 3, x, 2, y, 2 ) + 1 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var y0 = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0 ] ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + > idx = {{alias}}( 3, x1, 2, y1, 2 ) + -1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a single-precision floating-point + strided array equal to a corresponding element in another single-precision + floating-point strided array using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float32Array + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var y = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 3.0, 0.0 ] ); + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using offsets: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0 ] ); + > idx = {{alias}}.ndarray( 3, x, 2, 1, y, 2, 2 ) + -1 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/types/index.d.ts new file mode 100644 index 000000000000..af32c7f83e17 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/types/index.d.ts @@ -0,0 +1,115 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `sfirstIndexEqual`. +*/ +interface Routine { + /** + * Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. + * + * ## Notes + * + * - If the function is unable to find a match, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + * + * var idx = sfirstIndexEqual( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: Float32Array, strideX: number, y: Float32Array, strideY: number ): number; + + /** + * Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find a match, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); + * + * var idx = sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number, y: Float32Array, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. +* +* ## Notes +* +* - If the function is unable to find a match, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); +* +* var idx = sfirstIndexEqual( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +* var y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0 ] ); +* +* var idx = sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var sfirstIndexEqual: Routine; + + +// EXPORTS // + +export = sfirstIndexEqual; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/types/test.ts new file mode 100644 index 000000000000..1012afe953cb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/docs/types/test.ts @@ -0,0 +1,208 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import sfirstIndexEqual = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual( x.length, x, 1, y, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual( '1', x, 1, y, 1 ); // $ExpectError + sfirstIndexEqual( true, x, 1, y, 1 ); // $ExpectError + sfirstIndexEqual( false, x, 1, y, 1 ); // $ExpectError + sfirstIndexEqual( null, x, 1, y, 1 ); // $ExpectError + sfirstIndexEqual( {}, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual( x.length, '1', 1, y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, true, 1, y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, false, 1, y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, null, 1, y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual( x.length, x, '1', y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, true, y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, false, y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, null, y, 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, {}, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual( x.length, x, 1, '1', 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, true, 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, false, 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, null, 1 ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual( x.length, x, 1, y, '1' ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, y, true ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, y, false ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, y, null ); // $ExpectError + sfirstIndexEqual( x.length, x, 1, y, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual(); // $ExpectError + sfirstIndexEqual( 3, x ); // $ExpectError + sfirstIndexEqual( 3, x, 1 ); // $ExpectError + sfirstIndexEqual( 3, x, 1, y ); // $ExpectError + sfirstIndexEqual( 3, x, 1, y, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( x.length, '1', 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, true, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, false, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, null, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError +} + + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( x.length, x, 1, 0, '1', 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexEqual.ndarray(); // $ExpectError + sfirstIndexEqual.ndarray( x.length ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + sfirstIndexEqual.ndarray( x.length, x, 1, 0, y, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/c/example.c new file mode 100644 index 000000000000..81679d7d664e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_equal.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + const float y[] = { 0.0f, -1.0f, -2.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Perform a search: + int idx = stdlib_strided_sfirst_index_equal( N, x, strideX, y, strideY ); + + // Print the result: + printf( "index value: %d\n", idx ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/index.js new file mode 100644 index 000000000000..757513811f3b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sfirstIndexEqual = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( y ); + +var idx = sfirstIndexEqual( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "find", + "index", + "search", + "element", + "array", + "ndarray", + "strided", + "float", + "float32", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/addon.c new file mode 100644 index 000000000000..98ae5ba93bd0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/addon.c @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_equal.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 3 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_sfirst_index_equal)( N, X, strideX, Y, strideY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_sfirst_index_equal_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/main.c new file mode 100644 index 000000000000..491bf992ef83 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/src/main.c @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_equal.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param Y second input array +* @param strideY stride length for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_sfirst_index_equal)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const float *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + return API_SUFFIX(stdlib_strided_sfirst_index_equal_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Returns the index of the first element in a single-precision floating-point strided array equal to a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Y second input array +* @param strideY stride length for Y +* @param offsetY starting index for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_sfirst_index_equal_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + + if ( N <= 0 ) { + return -1; + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] == Y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.js new file mode 100644 index 000000000000..5251cd24de5e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var sfirstIndexEqual = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof sfirstIndexEqual.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var sfirstIndexEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfirstIndexEqual, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var sfirstIndexEqual; + var main; + + main = require( './../lib/sfirst_index_equal.js' ); + + sfirstIndexEqual = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfirstIndexEqual, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.ndarray.js new file mode 100644 index 000000000000..e51f28fd3f6f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.ndarray.js @@ -0,0 +1,239 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfirstIndexEqual = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( sfirstIndexEqual.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = sfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + + actual = sfirstIndexEqual( 0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexEqual( -1, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ NaN ] ), 1, 0, new Float32Array( [ NaN ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ -0.0 ] ), 1, 0, new Float32Array( [ 0.0 ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = sfirstIndexEqual( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, 0, y, -1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.ndarray.native.js new file mode 100644 index 000000000000..2ef56b8ad53e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.ndarray.native.js @@ -0,0 +1,248 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( sfirstIndexEqual.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = sfirstIndexEqual( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length-1, x, 1, 1, y, 1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length-2, x, 1, 2, y, 1, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, -2, x.length-1, y, -2, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, -2, x.length-2, y, -2, y.length-2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { + var actual; + + actual = sfirstIndexEqual( 0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexEqual( -1, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', opts, function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ NaN ] ), 1, 0, new Float32Array( [ NaN ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', opts, function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ -0.0 ] ), 1, 0, new Float32Array( [ 0.0 ] ), 1, 0 ); // eslint-disable-line max-len + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = sfirstIndexEqual( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, 0, y, -1, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.sfirst_index_equal.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.sfirst_index_equal.js new file mode 100644 index 000000000000..3d8e115069ef --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.sfirst_index_equal.js @@ -0,0 +1,279 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfirstIndexEqual = require( './../lib/sfirst_index_equal.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( sfirstIndexEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + actual = sfirstIndexEqual( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexEqual( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ NaN ] ), 1, new Float32Array( [ NaN ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ -0.0 ] ), 1, new Float32Array( [ 0.0 ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = sfirstIndexEqual( 3, x, 1, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, -2, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float32Array([ + 1.0, + 2.0, // 2 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float32Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 4.0, // 1 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = sfirstIndexEqual( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.sfirst_index_equal.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.sfirst_index_equal.native.js new file mode 100644 index 000000000000..5dcea9e9048c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-equal/test/test.sfirst_index_equal.native.js @@ -0,0 +1,288 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfirstIndexEqual = tryRequire( resolve( __dirname, './../lib/sfirst_index_equal.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexEqual instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexEqual, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( sfirstIndexEqual.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which equals a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + // Nonnegative stride... + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 2.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 3.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( 3, x, 2, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + // Negative stride... + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 1.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 4, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 2.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 3.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + actual = sfirstIndexEqual( x.length, x, -1, y, -1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + actual = sfirstIndexEqual( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexEqual( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided a search element equal to `NaN`', opts, function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ NaN ] ), 1, new Float32Array( [ NaN ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats -0 and +0 as equal', opts, function test( t ) { + var actual; + + actual = sfirstIndexEqual( 1, new Float32Array( [ -0.0 ] ), 1, new Float32Array( [ 0.0 ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 0.0, // 0 + 3.0, // 1 + 0.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 0.0, // 0 + 0.0, + 2.0, // 1 + 0.0, + 0.0 // 2 + ]); + + actual = sfirstIndexEqual( 3, x, 1, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 0.0, // 2 + 3.0, // 1 + 0.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, -2, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 0.0, // 1 + 0.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexEqual( 3, x, 2, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float32Array([ + 1.0, + 2.0, // 2 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float32Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 4.0, // 1 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = sfirstIndexEqual( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/README.md b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/README.md new file mode 100644 index 000000000000..bd4786bb7d21 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/README.md @@ -0,0 +1,340 @@ + + +# sfirstIndexLessThan + +> Return the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var sfirstIndexLessThan = require( '@stdlib/blas/ext/base/sfirst-index-less-than' ); +``` + +#### sfirstIndexLessThan( N, x, strideX, y, strideY ) + +Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + +var idx = sfirstIndexLessThan( x.length, x, 1, y, 1 ); +// returns 2 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: first input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length for `x`. +- **y**: second input [`Float32Array`][@stdlib/array/float32]. +- **strideY**: stride length for `y`. + +If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 5.0, 6.0, 7.0, 8.0 ] ); +var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + +var idx = sfirstIndexLessThan( x.length, x, 1, y, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compare every other element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Float32Array( [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + +var idx = sfirstIndexLessThan( 3, x, 2, y, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial arrays... +var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var y0 = new Float32Array( [ 9.0, 0.0, 9.0, 9.0 ] ); + +// Create offset views... +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = sfirstIndexLessThan( 2, x1, 1, y1, 1 ); +// returns 1 +``` + +#### sfirstIndexLessThan.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + +var idx = sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of each strided array: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 9.0, 9.0, 9.0, 0.0, 0.0, 0.0 ] ); +var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 1.0 ] ); + +var idx = sfirstIndexLessThan.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// returns 2 +``` + +
+ + + + + +
+ +## Notes + +- When comparing elements, the function checks whether an element in `x` is less than a corresponding element in `y` using the less-than operator `<`. As a consequence, comparisons involving `NaN` always evaluate to `false`. + +
+ + + + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sfirstIndexLessThan = require( '@stdlib/blas/ext/base/sfirst-index-less-than' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( y ); + +var idx = sfirstIndexLessThan( x.length, x, 1, y, 1 ); +console.log( idx ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sfirst_index_less_than.h" +``` + +#### stdlib_strided_sfirst_index_less_than( N, \*X, strideX, \*Y, strideY ) + +Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. + +```c +const float x[] = { 0.0f, 0.0f, 0.0f, 0.0f }; +const float y[] = { 0.0f, 0.0f, 1.0f, 0.0f }; + +int idx = stdlib_strided_sfirst_index_less_than( 4, x, 1, y, 1 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[in] float*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +CBLAS_INT stdlib_strided_sfirst_index_less_than( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_sfirst_index_less_than_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. + +```c +const float x[] = { 0.0f, 0.0f, 0.0f, 0.0f }; +const float y[] = { 0.0f, 0.0f, 1.0f, 0.0f }; + +int idx = stdlib_strided_sfirst_index_less_than_ndarray( 4, x, 1, 0, y, 1, 0 ); +// returns 2 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` first input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[in] float*` second input array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +CBLAS_INT stdlib_strided_sfirst_index_less_than_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sfirst_index_less_than.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + const float y[] = { 0.0f, -1.0f, -2.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Perform a search: + int idx = stdlib_strided_sfirst_index_less_than( N, x, strideX, y, strideY ); + + // Print the result: + printf( "index value: %d\n", idx ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.js new file mode 100644 index 000000000000..760ca3514c08 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfirstIndexLessThan = require( './../lib/sfirst_index_less_than.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float32' ); + var y = ones( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexLessThan( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.native.js new file mode 100644 index 000000000000..aaf2c04f8734 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.native.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/sfirst_index_less_than.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexLessThan instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float32' ); + var y = ones( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexLessThan( x.length, x, 1, y, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..5de536fac403 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.ndarray.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sfirstIndexLessThan = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float32' ); + var y = ones( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..9bfc275172a8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,107 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var ones = require( '@stdlib/array/ones' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexLessThan instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = ones( len, 'float32' ); + var y = ones( len, 'float32' ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = sfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..d07ee8992767 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/benchmark/c/benchmark.length.c @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_less_than.h" +#include +#include +#include +#include +#include + +#define NAME "sfirst_index_less_than" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + float *y; + double t; + int idx; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + y = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + y[ i ] = -10001.0f; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_sfirst_index_less_than( len, x, 1, y, 1 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + float *y; + double t; + int idx; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + y = (float *) malloc( len * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float()*20000.0f ) - 10000.0f; + y[ i ] = -10001.0f; + } + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + idx = stdlib_strided_sfirst_index_less_than_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( idx < -2 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < -2 ) { + printf( "unexpected result\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/repl.txt new file mode 100644 index 000000000000..1d6ff9172673 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/repl.txt @@ -0,0 +1,112 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Returns the index of the first element in a single-precision floating-point + strided array which is less than a corresponding element in another single- + precision floating-point strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + First input array. + + strideX: integer + Stride length for `x`. + + y: Float32Array + Second input array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var y = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > var idx = {{alias}}( x.length, x, 1, y, 1 ) + 2 + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float32}}( [ 0.0, 9.0, 0.0, 9.0, 9.0, 9.0 ] ); + > idx = {{alias}}( 3, x, 2, y, 2 ) + 2 + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var y0 = new {{alias:@stdlib/array/float32}}( [ 9.0, 0.0, 9.0, 9.0 ] ); + > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); + > var idx = {{alias}}( 2, x1, 1, y1, 1 ) + 1 + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Returns the index of the first element in a single-precision floating-point + strided array which is less than a corresponding element in another single- + precision floating-point strided array using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + First input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float32Array + Second input array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + // Standard usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 0.0, 0.0 ] ); + > var y = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 1.0, 0.0 ] ); + > var idx = {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + 2 + + // Using offsets: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > y = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 3.0, 0.0, 0.0, 0.0, 0.0 ] ); + > idx = {{alias}}.ndarray( 3, x, 2, 1, y, 2, 2 ) + 0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/types/index.d.ts new file mode 100644 index 000000000000..494f50cc7b80 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/types/index.d.ts @@ -0,0 +1,115 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `sfirstIndexLessThan`. +*/ +interface Routine { + /** + * Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @returns index + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * var idx = sfirstIndexLessThan( x.length, x, 1, y, 1 ); + * // returns 2 + */ + ( N: number, x: Float32Array, strideX: number, y: Float32Array, strideY: number ): number; + + /** + * Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. + * + * ## Notes + * + * - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. + * + * @param N - number of indexed elements + * @param x - first input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param y - second input array + * @param strideY - stride length for `y` + * @param offsetY - starting index for `y` + * @returns index + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + * var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); + * + * var idx = sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // returns 2 + */ + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number, y: Float32Array, strideY: number, offsetY: number ): number; +} + +/** +* Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. +* +* ## Notes +* +* - If the function is unable to find an element in `x` which is less than a corresponding element in `y`, the function returns `-1`. +* +* @param N - number of indexed elements +* @param x - first input array +* @param strideX - stride length for `x` +* @param y - second input array +* @param strideY - stride length for `y` +* @returns index +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +* var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* var idx = sfirstIndexLessThan( x.length, x, 1, y, 1 ); +* // returns 2 +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] ); +* var y = new Float32Array( [ 0.0, 0.0, 1.0, 0.0 ] ); +* +* var idx = sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // returns 2 +*/ +declare var sfirstIndexLessThan: Routine; + + +// EXPORTS // + +export = sfirstIndexLessThan; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/types/test.ts new file mode 100644 index 000000000000..f170cae22dbb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/docs/types/test.ts @@ -0,0 +1,208 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import sfirstIndexLessThan = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan( x.length, x, 1, y, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan( '1', x, 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( true, x, 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( false, x, 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( null, x, 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( {}, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan( x.length, '1', 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, true, 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, false, 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, null, 1, y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, {}, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan( x.length, x, '1', y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, true, y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, false, y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, null, y, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, {}, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan( x.length, x, 1, '1', 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, true, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, false, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, null, 1 ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan( x.length, x, 1, y, '1' ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, y, true ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, y, false ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, y, null ); // $ExpectError + sfirstIndexLessThan( x.length, x, 1, y, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan(); // $ExpectError + sfirstIndexLessThan( 3, x ); // $ExpectError + sfirstIndexLessThan( 3, x, 1 ); // $ExpectError + sfirstIndexLessThan( 3, x, 1, y ); // $ExpectError + sfirstIndexLessThan( 3, x, 1, y, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( '1', x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( x.length, '1', 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, true, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, false, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, null, 1, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, {}, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( x.length, x, '1', 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError +} + + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( x.length, x, 1, '1', y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float32Array... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, '1', 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, '1', 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, '1' ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + var y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + sfirstIndexLessThan.ndarray(); // $ExpectError + sfirstIndexLessThan.ndarray( x.length ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + sfirstIndexLessThan.ndarray( x.length, x, 1, 0, y, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/c/example.c new file mode 100644 index 000000000000..3372aa5ce299 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/c/example.c @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_less_than.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + const float y[] = { 0.0f, -1.0f, -2.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Perform a search: + int idx = stdlib_strided_sfirst_index_less_than( N, x, strideX, y, strideY ); + + // Print the result: + printf( "index value: %d\n", idx ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/index.js new file mode 100644 index 000000000000..17a74aa96392 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sfirstIndexLessThan = require( './../lib' ); + +var x = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( x ); + +var y = discreteUniform( 10, 0, 10, { + 'dtype': 'float32' +}); +console.log( y ); + +var idx = sfirstIndexLessThan( x.length, x, 1, y, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "find", + "index", + "search", + "element", + "array", + "ndarray", + "strided", + "single", + "float", + "float32", + "float32array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/addon.c new file mode 100644 index 000000000000..25ee6041082d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/addon.c @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_less_than.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include "stdlib/napi/create_int32.h" +#include "stdlib/napi/export.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 3 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_sfirst_index_less_than)( N, X, strideX, Y, strideY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_sfirst_index_less_than_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/main.c new file mode 100644 index 000000000000..4f77233603e3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/src/main.c @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sfirst_index_less_than.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param Y second input array +* @param strideY stride length for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_sfirst_index_less_than)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const float *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + return API_SUFFIX(stdlib_strided_sfirst_index_less_than_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Returns the index of the first element in a single-precision floating-point strided array which is less than a corresponding element in another single-precision floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X first input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Y second input array +* @param strideY stride length for Y +* @param offsetY starting index for Y +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_sfirst_index_less_than_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT i; + + if ( N <= 0 ) { + return -1; + } + ix = offsetX; + iy = offsetY; + for ( i = 0; i < N; i++ ) { + if ( X[ ix ] < Y[ iy ] ) { + return i; + } + ix += strideX; + iy += strideY; + } + return -1; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.js new file mode 100644 index 000000000000..fada99187988 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var sfirstIndexLessThan = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof sfirstIndexLessThan.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var sfirstIndexLessThan = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfirstIndexLessThan, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var sfirstIndexLessThan; + var main; + + main = require( './../lib/sfirst_index_less_than.js' ); + + sfirstIndexLessThan = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sfirstIndexLessThan, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.ndarray.js new file mode 100644 index 000000000000..156732b8ff03 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.ndarray.js @@ -0,0 +1,284 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfirstIndexLessThan = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = sfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = new Float32Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float32Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = sfirstIndexLessThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float32Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -1, 2, y, -2, 4 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, 4, y, -2, 4 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + actual = sfirstIndexLessThan( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( -1, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ NaN ] ), 1, 0, new Float32Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( 1, new Float32Array( [ 0.0 ] ), 1, 0, new Float32Array( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ -0.0 ] ), 1, 0, new Float32Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 5.0, + 5.0, + 5.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float32Array([ + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, 2, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float32Array([ + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, 0, y, 1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.ndarray.native.js new file mode 100644 index 000000000000..2aaf68fb7bee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.ndarray.native.js @@ -0,0 +1,293 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexLessThan instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = sfirstIndexLessThan( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, 2, 0 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = new Float32Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float32Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = sfirstIndexLessThan( x.length, x, -1, x.length-1, y, -1, y.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float32Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -1, 2, y, -2, 4 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, 4, y, -2, 4 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + actual = sfirstIndexLessThan( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( -1, x, 1, 0, y, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', opts, function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ NaN ] ), 1, 0, new Float32Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( 1, new Float32Array( [ 0.0 ] ), 1, 0, new Float32Array( [ NaN ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', opts, function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ -0.0 ] ), 1, 0, new Float32Array( [ 0.0 ] ), 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, 0, y, 2, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, -2, 4, y, -1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 5.0, + 5.0, + 5.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float32Array([ + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, 2, y, 1, 0 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 1.0, // 1 + 5.0 // 2 + ]); + y = new Float32Array([ + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 4.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, 0, y, 1, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, 0, y, -1, 2 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.sfirst_index_less_than.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.sfirst_index_less_than.js new file mode 100644 index 000000000000..f23f0a316404 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.sfirst_index_less_than.js @@ -0,0 +1,274 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sfirstIndexLessThan = require( './../lib/sfirst_index_less_than.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( sfirstIndexLessThan.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 1, y, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float32Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = sfirstIndexLessThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float32Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -1, y, -2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, y, -2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float32Array( [ 2.0, 3.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ NaN ] ), 1, new Float32Array( [ 0.0 ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( 1, new Float32Array( [ 0.0 ] ), 1, new Float32Array( [ NaN ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ -0.0 ] ), 1, new Float32Array( [ 0.0 ] ), 1 ); // eslint-disable-line max-len + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, y, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, -2, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, y, -1 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float32Array([ + 6.0, + 0.0, // 2 + 5.0, + 1.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float32Array([ + 0.0, + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + + // Create offset views... + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = sfirstIndexLessThan( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.sfirst_index_less_than.native.js b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.sfirst_index_less_than.native.js new file mode 100644 index 000000000000..a7fafb965efd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sfirst-index-less-than/test/test.sfirst_index_less_than.native.js @@ -0,0 +1,279 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sfirstIndexLessThan = tryRequire( resolve( __dirname, './../lib/sfirst_index_less_than.native.js' ) ); +var opts = { + 'skip': ( sfirstIndexLessThan instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sfirstIndexLessThan, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the first index of an element which is less than a corresponding element in another array', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 6.0, 1.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 2.0, 4.0, 4.0, 4.0, 4.0 ] ); + + // Nonnegative stride... + actual = sfirstIndexLessThan( x.length, x, 1, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 1.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 2.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, y, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 1, y, 2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + x = new Float32Array( [ 6.0, 5.0, 5.0, 5.0, 1.0, 5.0 ] ); + y = new Float32Array( [ 5.0, 4.0, 4.0, 4.0, 2.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, 2, y, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + x = new Float32Array( [ 1.0, 5.0, 4.0, 3.0, 2.0, 6.0 ] ); + y = new Float32Array( [ 2.0, 6.0, 5.0, 4.0, 3.0, 5.0 ] ); + + actual = sfirstIndexLessThan( x.length, x, -1, y, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + x = new Float32Array( [ 3.0, 5.0, 4.0, 6.0, 2.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 6.0, 5.0, 5.0, 3.0, 6.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, y, -1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 6.0, 3.0, 2.0, 4.0 ] ); + y = new Float32Array( [ 6.0, 6.0, 5.0, 4.0, 3.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -1, y, -2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] ); + y = new Float32Array( [ 4.0, 4.0, 4.0, 4.0, 4.0, 4.0 ] ); + + actual = sfirstIndexLessThan( 3, x, -2, y, -2 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + y = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + + actual = sfirstIndexLessThan( 0, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( -1, x, 1, y, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if comparisons involve `NaN` values', opts, function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ NaN ] ), 1, new Float32Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = sfirstIndexLessThan( 1, new Float32Array( [ 0.0 ] ), 1, new Float32Array( [ NaN ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function treats `-0` and `+0` as equal', opts, function test( t ) { + var actual; + + actual = sfirstIndexLessThan( 1, new Float32Array( [ -0.0 ] ), 1, new Float32Array( [ 0.0 ] ), 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 2 + ]); + y = new Float32Array([ + 5.0, // 0 + 2.0, // 1 + 4.0, // 2 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, y, 1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 1.0, // 1 + 5.0, // 2 + 4.0, + 5.0 + ]); + y = new Float32Array([ + 5.0, // 0 + 0.0, + 4.0, // 1 + 0.0, + 3.0 // 2 + ]); + + actual = sfirstIndexLessThan( 3, x, 1, y, 2 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 2 + 2.0, + 1.0, // 1 + 4.0, + 5.0 // 0 + ]); + y = new Float32Array([ + 3.0, // 2 + 2.0, // 1 + 5.0, // 0 + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, -2, y, -1 ); + + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var actual; + var x; + var y; + + x = new Float32Array([ + 6.0, // 0 + 2.0, + 5.0, // 1 + 4.0, + 0.0, // 2 + 6.0 + ]); + y = new Float32Array([ + 5.0, // 2 + 4.0, // 1 + 5.0, // 0 + 0.0, + 0.0, + 0.0 + ]); + + actual = sfirstIndexLessThan( 3, x, 2, y, -1 ); + + t.strictEqual( actual, 2, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var actual; + var x0; + var y0; + var x1; + var y1; + + // Initial arrays... + x0 = new Float32Array([ + 6.0, + 0.0, // 2 + 5.0, + 1.0, // 1 + 5.0, + 6.0 // 0 + ]); + y0 = new Float32Array([ + 0.0, + 0.0, + 0.0, + 5.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + + // Create offset views... + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + actual = sfirstIndexLessThan( 3, x1, -2, y1, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/docs/repl.txt index 5fbb693f40b9..f02a766a9f0d 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/docs/repl.txt +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/docs/repl.txt @@ -37,7 +37,7 @@ 1 -{{alias}}( N, searchElement, x, strideX, offsetX ) +{{alias}}.ndarray( N, searchElement, x, strideX, offsetX ) Returns the first index of a specified search element in a single-precision floating-point strided array using alternative indexing semantics. diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.js index dd71e13ae2be..8911c6247d71 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.js @@ -68,7 +68,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; actual = sindexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.native.js index d4cb0bbb0dec..95c1cb837798 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.ndarray.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = sindexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.js index 78a023a0a434..6d9be76f62c3 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.js @@ -68,7 +68,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; actual = sindexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.native.js b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.native.js index 2bd8dbdb6faf..7bda2ba1dc31 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/sindex-of/test/test.sindex_of.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = sindexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/lib/ndarray.js index 6821b123f546..af1a3c21adc4 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/lib/ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/lib/ndarray.js @@ -58,8 +58,7 @@ function slastIndexOf( N, searchElement, x, strideX, offsetX ) { return idx; } // Convert the index from reversed "view" to an index in the original "view": - idx = N - 1 - idx; - return idx; + return N - 1 - idx; } diff --git a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.js index 8d938561bb86..29a6a4b31e89 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.js @@ -68,7 +68,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; actual = slastIndexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.native.js index 5a5b57e5d948..3283ccea7c36 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.ndarray.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = slastIndexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1, 0 ); // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.js b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.js index f37f88d6d8b1..8fdd41b42138 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.js +++ b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.js @@ -68,7 +68,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; actual = slastIndexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.native.js b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.native.js index b8e6bbe4cbf3..04d74a842d8b 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/slast-index-of/test/test.slast_index_of.native.js @@ -77,7 +77,7 @@ tape( 'the function returns the last index of an element which equals a provided t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; actual = slastIndexOf( 0, 2.0, new Float32Array( [ 1.0, 2.0, 3.0 ] ), 1 ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/README.md b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/README.md new file mode 100644 index 000000000000..c0e60d997d5e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/README.md @@ -0,0 +1,329 @@ + + +# sreplicate + +> Replicate each single-precision floating-point strided array element a specified number of times. + +
+ +
+ + + +
+ +## Usage + +```javascript +var sreplicate = require( '@stdlib/blas/ext/base/sreplicate' ); +``` + +#### sreplicate( N, k, x, strideX, out, strideOut ) + +Replicates each single-precision floating-point strided array element a specified number of times. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +var out = new Float32Array( 6 ); + +sreplicate( x.length, 2, x, 1, out, 1 ); +// out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **k**: number of times to replicate each element. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length for `x`. +- **out**: output [`Float32Array`][@stdlib/array/float32]. +- **strideOut**: stride length for `out`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to replicate every other element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out = new Float32Array( 6 ); + +sreplicate( 3, 2, x, 2, out, 1 ); +// out => [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial arrays... +var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Float32Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +sreplicate( 3, 2, x1, 2, out1, 1 ); +// out0 => [ 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] +``` + +#### sreplicate.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + +Replicates each single-precision floating-point strided array element a specified number of times using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +var out = new Float32Array( 6 ); + +sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +// out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetOut**: starting index for `out`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to replicate every other element in the strided input array starting from the second element and to store in the last `N*k` elements of the strided output array starting from the last element: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +sreplicate.ndarray( 3, 2, x, 2, 1, out, -1, out.length-1 ); +// out => [ 0.0, 0.0, 6.0, 6.0, 4.0, 4.0, 2.0, 2.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0` or `k <= 0`, both functions return `out` unchanged. +- Both functions assume that the output array supports `N*k` indexed elements. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sreplicate = require( '@stdlib/blas/ext/base/sreplicate' ); + +var x = discreteUniform( 5, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +var out = new Float32Array( x.length * 3 ); +console.log( out ); + +sreplicate( x.length, 3, x, 1, out, 1 ); +console.log( out ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sreplicate.h" +``` + +#### stdlib_strided_sreplicate( N, k, \*X, strideX, \*Out, strideOut ) + +Replicates each single-precision floating-point strided array element a specified number of times. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_sreplicate( 4, 2, x, 1, out, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Out**: `[out] float*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. + +```c +void stdlib_strided_sreplicate( const CBLAS_INT N, const CBLAS_INT k, const float *X, const CBLAS_INT strideX, float *Out, const CBLAS_INT strideOut ); +``` + + + +#### stdlib_strided_sreplicate_ndarray( N, k, \*X, strideX, offsetX, \*Out, strideOut, offsetOut ) + + + +Replicates each single-precision floating-point strided array element a specified number of times using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_sreplicate_ndarray( 4, 2, x, 1, 0, out, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Out**: `[out] float*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. +- **offsetOut**: `[in] CBLAS_INT` starting index for `Out`. + +```c +void stdlib_strided_sreplicate_ndarray( const CBLAS_INT N, const CBLAS_INT k, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sreplicate.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f }; + float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 3; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify stride lengths: + const int strideX = 1; + const int strideOut = 1; + + // Replicate elements: + stdlib_strided_sreplicate( N, k, x, strideX, out, strideOut ); + + // Print the result: + for ( int i = 0; i < 6; i++ ) { + printf( "out[ %d ] = %f\n", i, out[ i ] ); + } +} +``` + +
+ + + +
+ + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.js new file mode 100644 index 000000000000..2f34d577035c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sreplicate = require( './../lib/sreplicate.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = sreplicate( x.length, 2, x, 1, out, 1 ); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.native.js new file mode 100644 index 000000000000..15e074883081 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.native.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sreplicate = tryRequire( resolve( __dirname, './../lib/sreplicate.native.js' ) ); +var opts = { + 'skip': ( sreplicate instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = sreplicate( x.length, 2, x, 1, out, 1 ); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..1dc03b94cefe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.ndarray.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sreplicate = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = sreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..219f0aeb8e14 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var zeros = require( '@stdlib/array/zeros' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sreplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sreplicate instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( len * 2, options.dtype ); + var x = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x[ 0 ] += 1.0; + v = sreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( v[ i % ( len * 2 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..8476b5951b4b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/benchmark/c/benchmark.length.c @@ -0,0 +1,209 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sreplicate.h" +#include +#include +#include +#include +#include + +#define NAME "sreplicate" +#define ITERATIONS 1000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static float rand_float( void ) { + int r = rand(); + return (float)r / ( (float)RAND_MAX + 1.0f ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *out; + double t; + float *x; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + out = (float *) malloc( len * 2 * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + for ( i = 0; i < len*2; i++ ) { + out[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_sreplicate( len, 2, x, 1, out, 1 ); + if ( out[ 0 ] != out[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ (len*2)-1 ] != out[ (len*2)-1 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *out; + double t; + float *x; + int i; + + x = (float *) malloc( len * sizeof( float ) ); + out = (float *) malloc( len * 2 * sizeof( float ) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f; + } + for ( i = 0; i < len*2; i++ ) { + out[ i ] = 0.0f; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0f; + stdlib_strided_sreplicate_ndarray( len, 2, x, 1, 0, out, 1, 0 ); + if ( out[ 0 ] != out[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ (len*2)-1 ] != out[ (len*2)-1 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/repl.txt new file mode 100644 index 000000000000..2303aef2ee89 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/repl.txt @@ -0,0 +1,119 @@ + +{{alias}}( N, k, x, strideX, out, strideOut ) + Replicates each single-precision floating-point strided array element a + specified number of times. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0` or `k <= 0`, the function returns `out` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Float32Array + Input array. + + strideX: integer + Stride length for `x`. + + out: Float32Array + Output array. + + strideOut: integer + Stride length for `out`. + + Returns + ------- + out: Float32Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0 ] ); + > var out = new {{alias:@stdlib/array/float32}}( 6 ); + > {{alias}}( x.length, 2, x, 1, out, 1 ) + [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > out = new {{alias:@stdlib/array/float32}}( 6 ); + > {{alias}}( 3, 2, x, 2, out, 1 ) + [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var out0 = new {{alias:@stdlib/array/float32}}( 6 ); + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var out1 = new {{alias:@stdlib/array/float32}}( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 2, 2, x1, 2, out1, 1 ) + [ 2.0, 2.0, 4.0, 4.0, 0.0 ] + > out0 + [ 0.0, 2.0, 2.0, 4.0, 4.0, 0.0 ] + + +{{alias}}.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + Replicates each single-precision floating-point strided array element a + specified number of times using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Float32Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + out: Float32Array + Output array. + + strideOut: integer + Stride length for `out`. + + offsetOut: integer + Starting index for `out`. + + Returns + ------- + out: Float32Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0 ] ); + > var out = new {{alias:@stdlib/array/float32}}( 6 ); + > {{alias}}.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ) + [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + + // Advanced indexing: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > out = new {{alias:@stdlib/array/float32}}( 6 ); + > {{alias}}.ndarray( 3, 2, x, 2, 1, out, 1, 0 ) + [ 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/types/index.d.ts new file mode 100644 index 000000000000..32b597117b3c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/types/index.d.ts @@ -0,0 +1,106 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `sreplicate`. +*/ +interface Routine { + /** + * Replicates each single-precision floating-point strided array element a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float32Array( 6 ); + * + * sreplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + ( N: number, k: number, x: Float32Array, strideX: number, out: Float32Array, strideOut: number ): Float32Array; + + /** + * Replicates each single-precision floating-point strided array element a specified number of times using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` + * @returns output array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + * var out = new Float32Array( 6 ); + * + * sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] + */ + ndarray( N: number, k: number, x: Float32Array, strideX: number, offsetX: number, out: Float32Array, strideOut: number, offsetOut: number ): Float32Array; +} + +/** +* Replicates each single-precision floating-point strided array element a specified number of times. +* +* @param N - number of indexed elements +* @param k - number of times to replicate each element +* @param x - input array +* @param strideX - stride length for `x` +* @param out - output array +* @param strideOut - stride length for `out` +* @returns output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float32Array( 6 ); +* +* sreplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float32Array( 6 ); +* +* sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +declare var sreplicate: Routine; + + +// EXPORTS // + +export = sreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/types/test.ts new file mode 100644 index 000000000000..01e9f44292b3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/docs/types/test.ts @@ -0,0 +1,282 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import sreplicate = require( './index' ); + + +// TESTS // + +// The function returns a Float32Array... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate( x.length, 2, x, 1, out, 1 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate( '10', 2, x, 1, out, 1 ); // $ExpectError + sreplicate( true, 2, x, 1, out, 1 ); // $ExpectError + sreplicate( false, 2, x, 1, out, 1 ); // $ExpectError + sreplicate( null, 2, x, 1, out, 1 ); // $ExpectError + sreplicate( undefined, 2, x, 1, out, 1 ); // $ExpectError + sreplicate( [], 2, x, 1, out, 1 ); // $ExpectError + sreplicate( {}, 2, x, 1, out, 1 ); // $ExpectError + sreplicate( ( x: number ): number => x, 2, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate( x.length, '10', x, 1, out, 1 ); // $ExpectError + sreplicate( x.length, true, x, 1, out, 1 ); // $ExpectError + sreplicate( x.length, false, x, 1, out, 1 ); // $ExpectError + sreplicate( x.length, null, x, 1, out, 1 ); // $ExpectError + sreplicate( x.length, undefined, x, 1, out, 1 ); // $ExpectError + sreplicate( x.length, [], x, 1, out, 1 ); // $ExpectError + sreplicate( x.length, {}, x, 1, out, 1 ); // $ExpectError + sreplicate( x.length, ( x: number ): number => x, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate( x.length, 2, 10, 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, '10', 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, true, 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, false, 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, null, 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, undefined, 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, [ '1' ], 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, {}, 1, out, 1 ); // $ExpectError + sreplicate( x.length, 2, ( x: number ): number => x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate( x.length, 2, x, '10', out, 1 ); // $ExpectError + sreplicate( x.length, 2, x, true, out, 1 ); // $ExpectError + sreplicate( x.length, 2, x, false, out, 1 ); // $ExpectError + sreplicate( x.length, 2, x, null, out, 1 ); // $ExpectError + sreplicate( x.length, 2, x, undefined, out, 1 ); // $ExpectError + sreplicate( x.length, 2, x, [], out, 1 ); // $ExpectError + sreplicate( x.length, 2, x, {}, out, 1 ); // $ExpectError + sreplicate( x.length, 2, x, ( x: number ): number => x, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sreplicate( x.length, 2, x, 1, 10, 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, '10', 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, true, 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, false, 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, null, 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, undefined, 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, [ '1' ], 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, {}, 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate( x.length, 2, x, 1, out, '10' ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, true ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, false ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, null ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, undefined ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, [] ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, {} ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate(); // $ExpectError + sreplicate( x.length ); // $ExpectError + sreplicate( x.length, 2 ); // $ExpectError + sreplicate( x.length, 2, x ); // $ExpectError + sreplicate( x.length, 2, x, 1 ); // $ExpectError + sreplicate( x.length, 2, x, 1, out ); // $ExpectError + sreplicate( x.length, 2, x, 1, out, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float32Array... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( '10', 2, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( true, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( false, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( null, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( undefined, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( [], 2, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( {}, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( ( x: number ): number => x, 2, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( x.length, '10', x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, true, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, false, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, null, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, undefined, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, [], x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, {}, x, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, ( x: number ): number => x, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( x.length, 2, 10, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, '10', 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, true, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, false, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, null, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, undefined, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, [ '1' ], 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, {}, 1, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( x.length, 2, x, '10', 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, true, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, false, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, null, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, undefined, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, [], 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, {}, 0, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( x.length, 2, x, 1, '10', out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, true, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, false, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, null, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, undefined, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, [], out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, {}, out, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sreplicate.ndarray( x.length, 2, x, 1, 0, 10, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, '10', 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, true, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, false, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, null, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, undefined, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, {}, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( x.length, 2, x, 1, 0, out, '10', 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, true, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, false, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, null, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, undefined, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, [], 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, {}, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, '10' ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, true ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, false ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, null ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, undefined ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, [] ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, {} ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + const out = new Float32Array( 20 ); + + sreplicate.ndarray(); // $ExpectError + sreplicate.ndarray( x.length ); // $ExpectError + sreplicate.ndarray( x.length, 2 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1 ); // $ExpectError + sreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/c/example.c new file mode 100644 index 000000000000..b449b9dee31c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/c/example.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sreplicate.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, 2.0f, 3.0f }; + float out[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of elements: + const int N = 3; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify stride lengths: + const int strideX = 1; + const int strideOut = 1; + + // Replicate elements: + stdlib_strided_sreplicate( N, k, x, strideX, out, strideOut ); + + // Print the result: + for ( int i = 0; i < 6; i++ ) { + printf( "out[ %d ] = %f\n", i, out[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/index.js new file mode 100644 index 000000000000..a9a0a51f47f9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sreplicate = require( './../lib' ); + +var x = discreteUniform( 5, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +var out = new Float32Array( x.length * 3 ); +console.log( out ); + +sreplicate( x.length, 3, x, 1, out, 1 ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var sreplicate = require( '@stdlib/blas/ext/base/sreplicate' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float32Array( 6 ); +* +* sreplicate.ndarray( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var sreplicate; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + sreplicate = main; +} else { + sreplicate = tmp; +} + + +// EXPORTS // + +module.exports = sreplicate; + +// exports: { "ndarray": "sreplicate.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/main.js new file mode 100644 index 000000000000..96f592745652 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sreplicate = require( './sreplicate.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( sreplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/native.js new file mode 100644 index 000000000000..f982ba86ac25 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sreplicate = require( './sreplicate.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( sreplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/ndarray.js new file mode 100644 index 000000000000..22f71c03ba39 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/ndarray.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Replicates each single-precision floating-point strided array element a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Float32Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float32Array( 6 ); +* +* sreplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function sreplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var io; + var ix; + var v; + var i; + var j; + + if ( N <= 0 || k <= 0 ) { + return out; + } + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = x[ ix ]; + for ( j = 0; j < k; j++ ) { + out[ io ] = v; + io += strideOut; + } + ix += strideX; + } + return out; +} + + +// EXPORTS // + +module.exports = sreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/ndarray.native.js new file mode 100644 index 000000000000..7abc7191d5bf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/ndarray.native.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each single-precision floating-point strided array element a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Float32Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float32Array( 6 ); +* +* var v = sreplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // returns [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function sreplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + addon.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ); + return out; +} + + +// EXPORTS // + +module.exports = sreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/sreplicate.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/sreplicate.js new file mode 100644 index 000000000000..71da47c7fc9c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/sreplicate.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replicates each single-precision floating-point strided array element a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {Float32Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float32Array( 6 ); +* +* var v = sreplicate( 3, 2, x, 1, out, 1 ); +* // returns [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function sreplicate( N, k, x, strideX, out, strideOut ) { + var ox = stride2offset( N, strideX ); + var oo = stride2offset( N * k, strideOut ); + return ndarray( N, k, x, strideX, ox, out, strideOut, oo ); +} + + +// EXPORTS // + +module.exports = sreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/sreplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/sreplicate.native.js new file mode 100644 index 000000000000..f290744fe556 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/lib/sreplicate.native.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each single-precision floating-point strided array element a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Float32Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {Float32Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); +* var out = new Float32Array( 6 ); +* +* var v = sreplicate( 3, 2, x, 1, out, 1 ); +* // returns [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] +*/ +function sreplicate( N, k, x, strideX, out, strideOut ) { + addon( N, k, x, strideX, out, strideOut ); + return out; +} + + +// EXPORTS // + +module.exports = sreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/manifest.json new file mode 100644 index 000000000000..db2cfcfefe78 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/manifest.json @@ -0,0 +1,78 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/strided/base/stride2offset", + "@stdlib/blas/base/shared" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/package.json b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/package.json new file mode 100644 index 000000000000..01446ce271ec --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/package.json @@ -0,0 +1,77 @@ +{ + "name": "@stdlib/blas/ext/base/sreplicate", + "version": "0.0.0", + "description": "Replicate each single-precision floating-point strided array element a specified number of times.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "replicate", + "repeat", + "copy", + "strided", + "strided array", + "typed", + "array", + "float32", + "float", + "single", + "float32array" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/addon.c new file mode 100644 index 000000000000..b8cda935968d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/addon.c @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sreplicate.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Out, N*k, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_sreplicate)( N, k, X, strideX, Out, strideOut ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetOut, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Out, N*k, strideOut, argv, 5 ); + API_SUFFIX(stdlib_strided_sreplicate_ndarray)( N, k, X, strideX, offsetX, Out, strideOut, offsetOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/main.c new file mode 100644 index 000000000000..64a3f0fbfff5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/src/main.c @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sreplicate.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Replicates each single-precision floating-point strided array element a specified number of times. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param Out output array +* @param strideOut stride length for Out +*/ +void API_SUFFIX(stdlib_strided_sreplicate)( const CBLAS_INT N, const CBLAS_INT k, const float *X, const CBLAS_INT strideX, float *Out, const CBLAS_INT strideOut ) { + const CBLAS_INT offsetX = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT offsetOut = stdlib_strided_stride2offset( N * k, strideOut ); + API_SUFFIX(stdlib_strided_sreplicate_ndarray)( N, k, X, strideX, offsetX, Out, strideOut, offsetOut ); +} + +/** +* Replicates each single-precision floating-point strided array element a specified number of times using alternative indexing semantics. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Out output array +* @param strideOut stride length for Out +* @param offsetOut starting index for Out +*/ +void API_SUFFIX(stdlib_strided_sreplicate_ndarray)( const CBLAS_INT N, const CBLAS_INT k, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ) { + CBLAS_INT ix; + CBLAS_INT io; + CBLAS_INT i; + CBLAS_INT j; + float v; + + if ( N <= 0 || k <= 0 ) { + return; + } + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + for ( j = 0; j < k; j++ ) { + Out[ io ] = v; + io += strideOut; + } + ix += strideX; + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.js new file mode 100644 index 000000000000..64885229fcfb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var sreplicate = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof sreplicate.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var sreplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sreplicate, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var sreplicate; + var main; + + main = require( './../lib/sreplicate.js' ); + + sreplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sreplicate, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.ndarray.js new file mode 100644 index 000000000000..9e48d9e0a4d6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.ndarray.js @@ -0,0 +1,294 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sreplicate = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( sreplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + sreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float32Array( 12 ); + + sreplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 5.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + v = sreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float32Array( 12 ); + + sreplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, -2, 4, out, -1, 5 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + out = new Float32Array( 8 ); + + sreplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Float32Array( [ 1.0, 1.0, -2.0, -2.0, 2.0, 2.0, 4.0, 4.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float32Array( 8 ); + + sreplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Float32Array( [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, + 2.0, // 0, 1, 2 + 3.0 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Float32Array( [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Float32Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.ndarray.native.js new file mode 100644 index 000000000000..5fa3a77f43b5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.ndarray.native.js @@ -0,0 +1,303 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Float32Array = require( '@stdlib/array/float32' ); + + +// VARIABLES // + +var sreplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sreplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( sreplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + sreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float32Array( 12 ); + + sreplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 5.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + v = sreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float32Array( 12 ); + + sreplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, -2, 4, out, -1, 5 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 2.0, + 1.0, // 0 + 2.0, + -2.0, // 1 + -2.0, + 2.0, // 2 + 3.0, + 4.0 // 3 + ]); + out = new Float32Array( 8 ); + + sreplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Float32Array( [ 1.0, 1.0, -2.0, -2.0, 2.0, 2.0, 4.0, 4.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float32Array( 8 ); + + sreplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Float32Array( [ 0.0, 0.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, + 2.0, // 0, 1, 2 + 3.0 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Float32Array( [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Float32Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.sreplicate.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.sreplicate.js new file mode 100644 index 000000000000..994ffffdb698 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.sreplicate.js @@ -0,0 +1,302 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sreplicate = require( './../lib/sreplicate.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( sreplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + sreplicate( x.length, 2, x, 1, out, 1 ); + expected = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float32Array( 12 ); + + sreplicate( x.length, 3, x, 1, out, 1 ); + expected = new Float32Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( x.length, 1, x, 1, out, 1 ); + expected = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 5.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( 1, 3, x, 1, out, 1 ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + v = sreplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( -1, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( 0, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( x.length, -1, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( x.length, 0, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float32Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + sreplicate( 3, 2, x, 2, out, 1 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, // 1 + 3.0 // 2 + ]); + out = new Float32Array([ + 0.0, // 0 + 0.0, + 0.0, // 0 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 1 + 0.0, + 0.0, // 2 + 0.0, + 0.0, // 2 + 0.0 + ]); + + sreplicate( 3, 2, x, 1, out, 2 ); + + expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 2 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 0 + ]); + out = new Float32Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + sreplicate( 3, 2, x, -2, out, -1 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + out = new Float32Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + + sreplicate( 3, 2, x, 2, out, -1 ); + + expected = new Float32Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Float32Array([ + 1.0, + 2.0, // 0 + 3.0, + 4.0, // 1 + 5.0, + 6.0 // 2 + ]); + out0 = new Float32Array([ + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + // Create offset views... + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Float32Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + sreplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] ); + + t.deepEqual( out0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.sreplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.sreplicate.native.js new file mode 100644 index 000000000000..31d4f4686178 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sreplicate/test/test.sreplicate.native.js @@ -0,0 +1,236 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Float32Array = require( '@stdlib/array/float32' ); + + +// VARIABLES // + +var sreplicate = tryRequire( resolve( __dirname, './../lib/sreplicate.native.js' ) ); +var opts = { + 'skip': ( sreplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( sreplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + sreplicate( x.length, 2, x, 1, out, 1 ); + expected = new Float32Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + out = new Float32Array( 12 ); + + sreplicate( x.length, 3, x, 1, out, 1 ); + expected = new Float32Array( [ 1.0, 1.0, 1.0, 2.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0, 4.0, 4.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( x.length, 1, x, 1, out, 1 ); + expected = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 5.0 ] ); + out = new Float32Array( 3 ); + + sreplicate( 1, 3, x, 1, out, 1 ); + expected = new Float32Array( [ 5.0, 5.0, 5.0 ] ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 6 ); + + v = sreplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( -1, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( 0, 2, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + expected = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 ] ); + + sreplicate( x.length, -1, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + sreplicate( x.length, 0, x, 1, out, 1 ); + t.deepEqual( out, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 2, out, 1 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + out = new Float32Array( 12 ); + + sreplicate( 3, 2, x, 1, out, 2 ); + + expected = new Float32Array( [ 1.0, 0.0, 1.0, 0.0, 2.0, 0.0, 2.0, 0.0, 3.0, 0.0, 3.0, 0.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, -2, out, -1 ); + + expected = new Float32Array( [ 1.0, 1.0, 3.0, 3.0, 5.0, 5.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + out = new Float32Array( 6 ); + + sreplicate( 3, 2, x, 2, out, -1 ); + + expected = new Float32Array( [ 5.0, 5.0, 3.0, 3.0, 1.0, 1.0 ] ); + + t.deepEqual( out, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + out1 = new Float32Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); + + sreplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Float32Array( [ 0.0, 0.0, 0.0, 2.0, 2.0, 4.0, 4.0, 6.0, 6.0 ] ); + + t.deepEqual( out0, expected, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/ssome/README.md b/lib/node_modules/@stdlib/blas/ext/base/ssome/README.md index 2b9f9516dcf1..e0211f43166c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/ssome/README.md +++ b/lib/node_modules/@stdlib/blas/ext/base/ssome/README.md @@ -58,8 +58,6 @@ The function has the following parameters: The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to test every other element: - - ```javascript var Float32Array = require( '@stdlib/array/float32' ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/README.md b/lib/node_modules/@stdlib/blas/ext/base/swax/README.md new file mode 100644 index 000000000000..cf7b4df00883 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/README.md @@ -0,0 +1,332 @@ + + +# swax + +> Multiply each element in a single-precision floating-point strided array `x` by a scalar constant and assign the results to elements in a single-precision floating-point strided array `w`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{w} = \alpha \cdot \mathbf{x} +``` + + + +This API is complementary to the package [`@stdlib/blas/base/sscal`][@stdlib/blas/base/sscal], which performs an in-place update. + +
+ + + +
+ +## Usage + +```javascript +var swax = require( '@stdlib/blas/ext/base/swax' ); +``` + +#### swax( N, alpha, x, strideX, w, strideW ) + +Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `w`. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +swax( x.length, 5.0, x, 1, w, 1 ); +// w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **alpha**: scalar constant. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length for `x`. +- **w**: output [`Float32Array`][@stdlib/array/float32]. +- **strideW**: stride length for `w`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other element in `x` by `alpha` and assign the results to every other element in `w`: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +swax( 3, 5.0, x, 2, w, 2 ); +// w => [ 5.0, 0.0, 15.0, 0.0, 25.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial arrays... +var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var w0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var w1 = new Float32Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +swax( 3, 5.0, x1, 1, w1, 1 ); +// w0 => [ 0.0, 0.0, 10.0, 15.0, 20.0, 0.0 ] +``` + +#### swax.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + +Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `w` using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); +// w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetW**: starting index for `w`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to multiply the last three elements of `x` by `alpha` and assign the results to the last three elements of `w`: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +swax.ndarray( 3, 5.0, x, 1, x.length-3, w, 1, w.length-3 ); +// w => [ 0.0, 0.0, 15.0, 20.0, 25.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `w` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var swax = require( '@stdlib/blas/ext/base/swax' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +var w = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( w ); + +swax( x.length, 5.0, x, 1, w, 1 ); +console.log( w ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/swax.h" +``` + +#### stdlib_strided_swax( N, alpha, \*X, strideX, \*W, strideW ) + +Multiplies each element in a single-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `W`. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float w[] = { 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_swax( 4, 5.0f, x, 1, w, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **W**: `[out] float*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. + +```c +void stdlib_strided_swax( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, float *W, const CBLAS_INT strideW ); +``` + + + +#### stdlib_strided_swax_ndarray( N, alpha, \*X, strideX, offsetX, \*W, strideW, offsetW ) + + + +Multiplies each element in a single-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `W` using alternative indexing semantics. + +```c +const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f }; +float w[] = { 0.0f, 0.0f, 0.0f, 0.0f }; + +stdlib_strided_swax_ndarray( 4, 5.0f, x, 1, 0, w, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] float` scalar constant. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **W**: `[out] float*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. +- **offsetW**: `[in] CBLAS_INT` starting index for `W`. + +```c +void stdlib_strided_swax_ndarray( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/swax.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + float w[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_swax( N, 5.0f, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "w[ %i ] = %f\n", i, w[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + +[@stdlib/blas/base/sscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/sscal + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.js new file mode 100644 index 000000000000..ba791b608b0b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var swax = require( './../lib/swax.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = swax( x.length, 5.0, x, 1, w, 1 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.native.js new file mode 100644 index 000000000000..0e907dcf622a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var swax = tryRequire( resolve( __dirname, './../lib/swax.native.js' ) ); +var opts = { + 'skip': ( swax instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = swax( x.length, 5.0, x, 1, w, 1 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..bdb96421b380 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.ndarray.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var swax = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..20c6b625dcb2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var swax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( swax instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -100, 100, options ); + var w = uniform( len, -100, 100, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..2f6c096dea5a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/benchmark/c/benchmark.length.c @@ -0,0 +1,207 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/swax.h" +#include +#include +#include +#include +#include + +#define NAME "swax" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static float random_uniform( const float min, const float max ) { + float v = (float)rand() / ( (float)RAND_MAX + 1.0f ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + float *w; + double t; + int i; + + x = (float *)malloc( len * sizeof(float) ); + w = (float *)malloc( len * sizeof(float) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0f, 100.0f ); + w[ i ] = random_uniform( -100.0f, 100.0f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_swax( len, 5.0f, x, 1, w, 1 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + float *w; + double t; + int i; + + x = (float *)malloc( len * sizeof(float) ); + w = (float *)malloc( len * sizeof(float) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0f, 100.0f ); + w[ i ] = random_uniform( -100.0f, 100.0f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_swax_ndarray( len, 5.0f, x, 1, 0, w, 1, 0 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/swax/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/swax/docs/repl.txt new file mode 100644 index 000000000000..805852136833 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/docs/repl.txt @@ -0,0 +1,131 @@ + +{{alias}}( N, alpha, x, strideX, w, strideW ) + Multiplies each element in a single-precision floating-point strided array + `x` by a scalar constant and assigns the results to elements in a single- + precision floating-point strided array `w`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `w` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length for `x`. + + w: Float32Array + Output array. + + strideW: integer + Stride length for `w`. + + Returns + ------- + w: Float32Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/float32}}( bufX ); + > var w = new {{alias:@stdlib/array/float32}}( bufW ); + > {{alias}}( x.length, 5.0, x, 1, w, 1 ) + [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/float32}}( bufX ); + > w = new {{alias:@stdlib/array/float32}}( bufW ); + > {{alias}}( 4, 5.0, x, 2, w, 2 ) + [ -10.0, 0.0, 15.0, 0.0, 20.0, 0.0, -5.0, 0.0 ] + + // Using view offsets: + > var bufX0 = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; + > var bufW0 = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x0 = new {{alias:@stdlib/array/float32}}( bufX0 ); + > var w0 = new {{alias:@stdlib/array/float32}}( bufW0 ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetW = w0.BYTES_PER_ELEMENT * 1; + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, offsetX ); + > var w1 = new {{alias:@stdlib/array/float32}}( w0.buffer, offsetW ); + > {{alias}}( 3, 5.0, x1, 2, w1, 2 ) + [ -10.0, 0.0, -20.0, 0.0, -30.0 ] + > w0 + [ 0.0, -10.0, 0.0, -20.0, 0.0, -30.0 ] + + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + Multiplies each element in a single-precision floating-point strided array + `x` by a scalar constant and assigns the results to elements in a single- + precision floating-point strided array `w` using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: number + Scalar constant. + + x: Float32Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + w: Float32Array + Output array. + + strideW: integer + Stride length for `w`. + + offsetW: integer + Starting index for `w`. + + Returns + ------- + w: Float32Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/float32}}( bufX ); + > var w = new {{alias:@stdlib/array/float32}}( bufW ); + > {{alias}}.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ) + [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + + // Using index offsets: + > bufX = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ]; + > bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > x = new {{alias:@stdlib/array/float32}}( bufX ); + > w = new {{alias:@stdlib/array/float32}}( bufW ); + > {{alias}}.ndarray( 3, 5.0, x, 1, x.length-3, w, 1, w.length-3 ) + [ 0.0, 0.0, 0.0, -20.0, 25.0, -30.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/swax/docs/types/index.d.ts new file mode 100644 index 000000000000..dd691175310c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/docs/types/index.d.ts @@ -0,0 +1,106 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `swax`. +*/ +interface Routine { + /** + * Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to a single-precision floating-point strided array `w`. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * swax( x.length, 5.0, x, 1, w, 1 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + */ + ( N: number, alpha: number, x: Float32Array, strideX: number, w: Float32Array, strideW: number ): Float32Array; + + /** + * Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to a single-precision floating-point strided array `w` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting index for `x` + * @param w - output array + * @param strideW - `w` stride length + * @param offsetW - starting index for `w` + * @returns `w` + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); + * var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); + * // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] + */ + ndarray( N: number, alpha: number, x: Float32Array, strideX: number, offsetX: number, w: Float32Array, strideW: number, offsetW: number ): Float32Array; +} + +/** +* Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to a single-precision floating-point strided array `w`. +* +* @param N - number of indexed elements +* @param alpha - scalar constant +* @param x - input array +* @param strideX - `x` stride length +* @param w - output array +* @param strideW - `w` stride length +* @returns `w` +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +* var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* swax( x.length, 5.0, x, 1, w, 1 ); +* // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +* var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +*/ +declare var swax: Routine; + + +// EXPORTS // + +export = swax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/swax/docs/types/test.ts new file mode 100644 index 000000000000..26a71ac96e9b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/docs/types/test.ts @@ -0,0 +1,278 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import swax = require( './index' ); + + +// TESTS // + +// The function returns a Float32Array... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax( x.length, 5.0, x, 1, w, 1 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax( '10', 5.0, x, 1, w, 1 ); // $ExpectError + swax( true, 5.0, x, 1, w, 1 ); // $ExpectError + swax( false, 5.0, x, 1, w, 1 ); // $ExpectError + swax( null, 5.0, x, 1, w, 1 ); // $ExpectError + swax( undefined, 5.0, x, 1, w, 1 ); // $ExpectError + swax( [], 5.0, x, 1, w, 1 ); // $ExpectError + swax( {}, 5.0, x, 1, w, 1 ); // $ExpectError + swax( ( x: number ): number => x, 5.0, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax( x.length, '10', x, 1, w, 1 ); // $ExpectError + swax( x.length, true, x, 1, w, 1 ); // $ExpectError + swax( x.length, false, x, 1, w, 1 ); // $ExpectError + swax( x.length, null, x, 1, w, 1 ); // $ExpectError + swax( x.length, undefined, x, 1, w, 1 ); // $ExpectError + swax( x.length, [], x, 1, w, 1 ); // $ExpectError + swax( x.length, {}, x, 1, w, 1 ); // $ExpectError + swax( x.length, ( x: number ): number => x, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Float32Array... +{ + const w = new Float32Array( 10 ); + + swax( 10, 5.0, 10, 1, w, 1 ); // $ExpectError + swax( 10, 5.0, '10', 1, w, 1 ); // $ExpectError + swax( 10, 5.0, true, 1, w, 1 ); // $ExpectError + swax( 10, 5.0, false, 1, w, 1 ); // $ExpectError + swax( 10, 5.0, null, 1, w, 1 ); // $ExpectError + swax( 10, 5.0, undefined, 1, w, 1 ); // $ExpectError + swax( 10, 5.0, [], 1, w, 1 ); // $ExpectError + swax( 10, 5.0, {}, 1, w, 1 ); // $ExpectError + swax( 10, 5.0, ( x: number ): number => x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax( x.length, 5.0, x, '10', w, 1 ); // $ExpectError + swax( x.length, 5.0, x, true, w, 1 ); // $ExpectError + swax( x.length, 5.0, x, false, w, 1 ); // $ExpectError + swax( x.length, 5.0, x, null, w, 1 ); // $ExpectError + swax( x.length, 5.0, x, undefined, w, 1 ); // $ExpectError + swax( x.length, 5.0, x, [], w, 1 ); // $ExpectError + swax( x.length, 5.0, x, {}, w, 1 ); // $ExpectError + swax( x.length, 5.0, x, ( x: number ): number => x, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + swax( 10, 5.0, x, 1, 10, 1 ); // $ExpectError + swax( 10, 5.0, x, 1, '10', 1 ); // $ExpectError + swax( 10, 5.0, x, 1, true, 1 ); // $ExpectError + swax( 10, 5.0, x, 1, false, 1 ); // $ExpectError + swax( 10, 5.0, x, 1, null, 1 ); // $ExpectError + swax( 10, 5.0, x, 1, undefined, 1 ); // $ExpectError + swax( 10, 5.0, x, 1, [], 1 ); // $ExpectError + swax( 10, 5.0, x, 1, {}, 1 ); // $ExpectError + swax( 10, 5.0, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax( x.length, 5.0, x, 1, w, '10' ); // $ExpectError + swax( x.length, 5.0, x, 1, w, true ); // $ExpectError + swax( x.length, 5.0, x, 1, w, false ); // $ExpectError + swax( x.length, 5.0, x, 1, w, null ); // $ExpectError + swax( x.length, 5.0, x, 1, w, undefined ); // $ExpectError + swax( x.length, 5.0, x, 1, w, [] ); // $ExpectError + swax( x.length, 5.0, x, 1, w, {} ); // $ExpectError + swax( x.length, 5.0, x, 1, w, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax(); // $ExpectError + swax( x.length ); // $ExpectError + swax( x.length, 5.0 ); // $ExpectError + swax( x.length, 5.0, x ); // $ExpectError + swax( x.length, 5.0, x, 1 ); // $ExpectError + swax( x.length, 5.0, x, 1, w ); // $ExpectError + swax( x.length, 5.0, x, 1, w, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Float32Array... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray( '10', 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( true, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( false, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( null, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( undefined, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( [], 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( {}, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( ( x: number ): number => x, 5.0, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray( x.length, '10', x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, true, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, false, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, null, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, undefined, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, [], x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, {}, x, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, ( x: number ): number => x, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Float32Array... +{ + const w = new Float32Array( 10 ); + + swax.ndarray( 10, 5.0, 10, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, '10', 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, true, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, false, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, null, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, undefined, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, [], 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, {}, 1, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, ( x: number ): number => x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray( x.length, 5.0, x, '10', 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, true, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, false, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, null, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, undefined, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, [], 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, {}, 0, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, ( x: number ): number => x, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray( x.length, 5.0, x, 1, '10', w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, true, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, false, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, null, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, undefined, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, [], w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, {}, w, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, ( x: number ): number => x, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + swax.ndarray( 10, 5.0, x, 1, 0, 10, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, '10', 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, true, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, false, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, null, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, undefined, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, [], 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, {}, 1, 0 ); // $ExpectError + swax.ndarray( 10, 5.0, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray( x.length, 5.0, x, 1, 0, w, '10', 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, true, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, false, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, null, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, undefined, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, [], 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, {}, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, '10' ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, true ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, false ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, null ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, undefined ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, [] ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, {} ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + const w = new Float32Array( 10 ); + + swax.ndarray(); // $ExpectError + swax.ndarray( x.length ); // $ExpectError + swax.ndarray( x.length, 5.0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1 ); // $ExpectError + swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/swax/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/swax/examples/c/example.c new file mode 100644 index 000000000000..31c0e8451d55 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/swax.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 1.0f, -2.0f, 3.0f, -4.0f, 5.0f, -6.0f, 7.0f, -8.0f }; + float w[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_swax( N, 5.0f, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "w[ %i ] = %f\n", i, w[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/swax/examples/index.js new file mode 100644 index 000000000000..ce38d6e7c890 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var swax = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +var w = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( w ); + +swax( x.length, 5.0, x, 1, w, 1 ); +console.log( w ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/swax/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var swax = require( '@stdlib/blas/ext/base/swax' ); +* +* var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] ); +* var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* swax.ndarray( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var swax; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + swax = main; +} else { + swax = tmp; +} + + +// EXPORTS // + +module.exports = swax; + +// exports: { "ndarray": "swax.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/main.js new file mode 100644 index 000000000000..498c80bc6443 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var swax = require( './swax.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( swax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = swax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/native.js new file mode 100644 index 000000000000..e051ab36f79a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var swax = require( './swax.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( swax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = swax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/ndarray.js new file mode 100644 index 000000000000..8b7459029d68 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/ndarray.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var scopy = require( '@stdlib/blas/base/scopy' ).ndarray; + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float32Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function swax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + var ix; + var iw; + var m; + var i; + + if ( N <= 0 ) { + return w; + } + // Fast path: when alpha = 1.0, delegate to scopy (w = x) + if ( alpha === 1.0 ) { + return scopy( N, x, strideX, offsetX, w, strideW, offsetW ); + } + ix = offsetX; + iw = offsetW; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideW === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + w[ iw ] = alpha * x[ ix ]; + ix += strideX; + iw += strideW; + } + } + if ( N < M ) { + return w; + } + for ( i = m; i < N; i += M ) { + w[ iw ] = alpha * x[ ix ]; + w[ iw+1 ] = alpha * x[ ix+1 ]; + w[ iw+2 ] = alpha * x[ ix+2 ]; + w[ iw+3 ] = alpha * x[ ix+3 ]; + w[ iw+4 ] = alpha * x[ ix+4 ]; + ix += M; + iw += M; + } + return w; + } + for ( i = 0; i < N; i++ ) { + w[ iw ] = alpha * x[ ix ]; + ix += strideX; + iw += strideW; + } + return w; +} + + +// EXPORTS // + +module.exports = swax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/ndarray.native.js new file mode 100644 index 000000000000..767a0dc4c175 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/ndarray.native.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float32Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); +* // w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function swax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + addon.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ); + return w; +} + + +// EXPORTS // + +module.exports = swax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/lib/swax.js b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/swax.js new file mode 100644 index 000000000000..0674484f814c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/swax.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `w`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Float32Array} w - output array +* @param {integer} strideW - `w` stride length +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* swax( x.length, 5.0, x, 1, w, 1 ); +* // w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function swax( N, alpha, x, strideX, w, strideW ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ), w, strideW, stride2offset( N, strideW ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = swax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/lib/swax.native.js b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/swax.native.js new file mode 100644 index 000000000000..6ba17f921aa9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/lib/swax.native.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a single-precision floating-point strided array `x` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `w`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {number} alpha - scalar constant +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Float32Array} w - output array +* @param {integer} strideW - `w` stride length +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); +* var w = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* swax( x.length, 5.0, x, 1, w, 1 ); +* // w => [ 5.0, 10.0, 15.0, 20.0, 25.0 ] +*/ +function swax( N, alpha, x, strideX, w, strideW ) { + addon( N, alpha, x, strideX, w, strideW ); + return w; +} + + +// EXPORTS // + +module.exports = swax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/swax/manifest.json new file mode 100644 index 000000000000..e351badd1689 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/manifest.json @@ -0,0 +1,82 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-float", + "@stdlib/napi/argv-strided-float32array", + "@stdlib/blas/base/scopy", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/scopy", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/scopy", + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/package.json b/lib/node_modules/@stdlib/blas/ext/base/swax/package.json new file mode 100644 index 000000000000..67adc6b1bb1f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/blas/ext/base/swax", + "version": "0.0.0", + "description": "Multiply each element in a single-precision floating-point strided array `x` by a scalar constant and assign the results to elements in a single-precision floating-point strided array `w`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "multiply", + "scale", + "strided", + "array", + "ndarray", + "float32", + "float", + "single", + "float32array", + "swax" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/swax/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/swax/src/addon.c new file mode 100644 index 000000000000..bbc84602bba3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/src/addon.c @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/swax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_float.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, W, N, strideW, argv, 4 ); + API_SUFFIX(stdlib_strided_swax)( N, alpha, X, strideX, W, strideW ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_FLOAT( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetW, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, W, N, strideW, argv, 5 ); + API_SUFFIX(stdlib_strided_swax_ndarray)( N, alpha, X, strideX, offsetX, W, strideW, offsetW ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/swax/src/main.c new file mode 100644 index 000000000000..636196dc29d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/src/main.c @@ -0,0 +1,100 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/swax.h" +#include "stdlib/blas/base/scopy.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Multiplies each element in a single-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `W`. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param W output array +* @param strideW stride length for `W` +*/ +void API_SUFFIX(stdlib_strided_swax)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, float *W, const CBLAS_INT strideW ) { + const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + const CBLAS_INT ow = stdlib_strided_stride2offset( N, strideW ); + API_SUFFIX(stdlib_strided_swax_ndarray)( N, alpha, X, strideX, ox, W, strideW, ow ); +} + +/** +* Multiplies each element in a single-precision floating-point strided array `X` by a scalar constant and assigns the results to elements in a single-precision floating-point strided array `W` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param W output array +* @param strideW stride length for `W` +* @param offsetW starting index for `W` +*/ +void API_SUFFIX(stdlib_strided_swax_ndarray)( const CBLAS_INT N, const float alpha, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ) { + CBLAS_INT ix; + CBLAS_INT iw; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + if ( alpha == 1.0f ) { + API_SUFFIX(c_scopy_ndarray)( N, X, strideX, offsetX, W, strideW, offsetW ); + return; + } + ix = offsetX; + iw = offsetW; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideW == 1 ) { + m = N % 5; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + W[ iw ] = alpha * X[ ix ]; + ix += strideX; + iw += strideW; + } + } + if ( N < 5 ) { + return; + } + for ( i = m; i < N; i += 5 ) { + W[ iw ] = alpha * X[ ix ]; + W[ iw+1 ] = alpha * X[ ix+1 ]; + W[ iw+2 ] = alpha * X[ ix+2 ]; + W[ iw+3 ] = alpha * X[ ix+3 ]; + W[ iw+4 ] = alpha * X[ ix+4 ]; + ix += 5; + iw += 5; + } + return; + } + for ( i = 0; i < N; i++ ) { + W[ iw ] = alpha * X[ ix ]; + ix += strideX; + iw += strideW; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.js new file mode 100644 index 000000000000..0dfd85efbabd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var swax = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof swax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof swax.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var swax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( swax, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var swax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( swax, require( './../lib/main.js' ), 'returns JS implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.ndarray.js new file mode 100644 index 000000000000..53e9ee52e5be --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.ndarray.js @@ -0,0 +1,285 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var swax = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof swax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( swax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float32Array( x.length ); + expected = new Float32Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 5.0, 10.0 ] ); + + swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float32Array( x.length ); + out = swax( x.length, 3.0, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + swax( 0, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + swax( -4, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + swax( x.length, 1.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + w = new Float32Array( 3 ); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( 3, 5.0, x, 2, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float32Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + swax( 3, 5.0, x, 1, 0, w, 2, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float32Array([ + 0.0, // 2 + 0.0, // 1 + 0.0 // 0 + ]); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( 3, 5.0, x, -2, x.length-1, w, -1, w.length-1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w = new Float32Array( 5 ); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0, // 4.0 * 5.0 + 0.0, + 0.0 + ]); + + swax( 3, 5.0, x, 1, 1, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float32Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 0.0, + 5.0, // 1.0 * 5.0 + 10.0, // 2.0 * 5.0 + 15.0 // 3.0 * 5.0 + ]); + + swax( 3, 5.0, x, 1, 0, w, 1, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float32Array( 100 ); + w = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + w = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.ndarray.native.js new file mode 100644 index 000000000000..9f09646e6752 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.ndarray.native.js @@ -0,0 +1,294 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var swax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( swax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof swax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( swax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float32Array( x.length ); + expected = new Float32Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 5.0, 10.0 ] ); + + swax( x.length, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float32Array( x.length ); + out = swax( x.length, 3.0, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + swax( 0, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + swax( -4, 5.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + swax( x.length, 1.0, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 2.0, // 0 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 2 + ]); + w = new Float32Array( 3 ); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( 3, 5.0, x, 2, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float32Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + swax( 3, 5.0, x, 1, 0, w, 2, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float32Array([ + 0.0, // 2 + 0.0, // 1 + 0.0 // 0 + ]); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( 3, 5.0, x, -2, x.length-1, w, -1, w.length-1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w = new Float32Array( 5 ); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0, // 4.0 * 5.0 + 0.0, + 0.0 + ]); + + swax( 3, 5.0, x, 1, 1, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float32Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 0.0, + 5.0, // 1.0 * 5.0 + 10.0, // 2.0 * 5.0 + 15.0 // 3.0 * 5.0 + ]); + + swax( 3, 5.0, x, 1, 0, w, 1, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float32Array( 100 ); + w = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + w = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.swax.js b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.swax.js new file mode 100644 index 000000000000..49781d923c6d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.swax.js @@ -0,0 +1,269 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var swax = require( './../lib/swax.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof swax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( swax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float32Array( x.length ); + expected = new Float32Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 5.0, 10.0 ] ); + + swax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float32Array( x.length ); + out = swax( x.length, 3.0, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + swax( 0, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + swax( -4, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + swax( x.length, 1.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + w = new Float32Array( 3 ); + expected = new Float32Array([ + 5.0, // 1.0 * 5.0 + 15.0, // 3.0 * 5.0 + 25.0 // 5.0 * 5.0 + ]); + + swax( 3, 5.0, x, 2, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float32Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + swax( 3, 5.0, x, 1, w, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float32Array( 5 ); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + 0.0, + -25.0, // -5.0 * 5.0 + 0.0, + 30.0 // 6.0 * 5.0 + ]); + + swax( 3, 5.0, x, -2, w, -2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var w0; + var x1; + var w1; + + x0 = new Float32Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w0 = new Float32Array([ + 10.0, + 10.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Float32Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Float32Array([ + 10.0, + 10.0, + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0 // 4.0 * 5.0 + ]); + + swax( 3, 5.0, x1, 1, w1, 1 ); + t.deepEqual( w0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float32Array( 100 ); + w = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + w = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.swax.native.js b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.swax.native.js new file mode 100644 index 000000000000..d6fae06ab859 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/swax/test/test.swax.native.js @@ -0,0 +1,278 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var swax = tryRequire( resolve( __dirname, './../lib/swax.native.js' ) ); +var opts = { + 'skip': ( swax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof swax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( swax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Float32Array( x.length ); + expected = new Float32Array([ + 20.0, // 4.0 * 5.0 + 10.0, // 2.0 * 5.0 + -15.0, // -3.0 * 5.0 + 25.0, // 5.0 * 5.0 + -5.0, // -1.0 * 5.0 + 10.0, // 2.0 * 5.0 + -25.0, // -5.0 * 5.0 + 30.0 // 6.0 * 5.0 + ]); + + swax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( [ 1.0, 2.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 5.0, 10.0 ] ); + + swax( x.length, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + w = new Float32Array( x.length ); + out = swax( x.length, 3.0, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0 ] ); + w = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + swax( 0, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + swax( -4, 5.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Float32Array( x.length ); + expected = new Float32Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + swax( x.length, 1.0, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 1.0, // 0 + 2.0, + 3.0, // 1 + 4.0, + 5.0 // 2 + ]); + w = new Float32Array( 3 ); + expected = new Float32Array([ + 5.0, // 1.0 * 5.0 + 15.0, // 3.0 * 5.0 + 25.0 // 5.0 * 5.0 + ]); + + swax( 3, 5.0, x, 2, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array( [ 1.0, 2.0, 3.0 ] ); + w = new Float32Array([ + 0.0, // 0 + 30.0, + 0.0, // 1 + 10.0, + 0.0 // 2 + ]); + expected = new Float32Array([ + 5.0, // 1.0 * 5.0 + 30.0, + 10.0, // 2.0 * 5.0 + 10.0, + 15.0 // 3.0 * 5.0 + ]); + + swax( 3, 5.0, x, 1, w, 2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var w; + + x = new Float32Array([ + 2.0, // 2 + -3.0, + -5.0, // 1 + 7.0, + 6.0 // 0 + ]); + w = new Float32Array( 5 ); + expected = new Float32Array([ + 10.0, // 2.0 * 5.0 + 0.0, + -25.0, // -5.0 * 5.0 + 0.0, + 30.0 // 6.0 * 5.0 + ]); + + swax( 3, 5.0, x, -2, w, -2 ); + t.deepEqual( w, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var w0; + var x1; + var w1; + + x0 = new Float32Array([ + 1.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 5.0 + ]); + w0 = new Float32Array([ + 10.0, + 10.0, + 0.0, // 0 + 0.0, // 1 + 0.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Float32Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Float32Array([ + 10.0, + 10.0, + 10.0, // 2.0 * 5.0 + 15.0, // 3.0 * 5.0 + 20.0 // 4.0 * 5.0 + ]); + + swax( 3, 5.0, x1, 1, w1, 1 ); + t.deepEqual( w0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var i; + + alpha = 3.0; + x = new Float32Array( 100 ); + w = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + w = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + expected[ i ] = alpha * x[ i ]; + } + swax( x.length, alpha, x, 1, w, 1 ); + t.deepEqual( w, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/sxdy/README.md new file mode 100644 index 000000000000..117cf909895a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/README.md @@ -0,0 +1,317 @@ + + +# sxdy + +> Divide elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assign the results to `y`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var sxdy = require( '@stdlib/blas/ext/base/sxdy' ); +``` + +#### sxdy( N, x, strideX, y, strideY ) + +Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +sxdy( x.length, x, 1, y, 1 ); +// y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Float32Array`][@stdlib/array/float32]. +- **strideX**: stride length for `x`. +- **y**: output [`Float32Array`][@stdlib/array/float32]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to divide every other element of `x` by every other element of `y`: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 14.0, 2.0, 27.0, 4.0, 33.0, 6.0 ] ); +var y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + +sxdy( 3, x, 2, y, 2 ); +// y => [ 2.0, 8.0, 3.0, 10.0, 3.0, 12.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +// Initial arrays... +var x0 = new Float32Array( [ 1.0, 18.0, 30.0, 44.0, 5.0, 6.0 ] ); +var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); + +// Create offset views... +var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +sxdy( 3, x1, 1, y1, 1 ); +// y0 => [ 7.0, 8.0, 2.0, 3.0, 4.0, 12.0 ] +``` + +#### sxdy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + +sxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to divide the last three elements of `x` by the last three elements of `y`: + +```javascript +var Float32Array = require( '@stdlib/array/float32' ); + +var x = new Float32Array( [ 1.0, 2.0, 24.0, 36.0, 50.0 ] ); +var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); + +sxdy.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// y => [ 6.0, 7.0, 3.0, 4.0, 5.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sxdy = require( '@stdlib/blas/ext/base/sxdy' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +var y = discreteUniform( 10, 1, 100, { + 'dtype': 'float32' +}); +console.log( y ); + +sxdy( x.length, x, 1, y, 1 ); +console.log( y ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + +
+ +
+ + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/sxdy.h" +``` + +#### stdlib_strided_sxdy( N, \*X, strideX, \*Y, strideY ) + +Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. + +```c +const float x[] = { 2.0f, 6.0f, 12.0f, 20.0f }; +float y[] = { 2.0f, 3.0f, 4.0f, 5.0f }; + +stdlib_strided_sxdy( 4, x, 1, y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[inout] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_sxdy( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_sxdy_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```c +const float x[] = { 2.0f, 6.0f, 12.0f, 20.0f }; +float y[] = { 2.0f, 3.0f, 4.0f, 5.0f }; + +stdlib_strided_sxdy_ndarray( 4, x, 1, 0, y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] float*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[inout] float*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_sxdy_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + +
+ +
+ + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/sxdy.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 2.0f, -6.0f, 12.0f, -20.0f, 30.0f, -42.0f, 56.0f, -72.0f }; + float y[] = { 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Divide elements of `x` by the corresponding elements of `y`: + stdlib_strided_sxdy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %i ] = %f\n", i, y[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +[@stdlib/array/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float32 + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..da2c3323b82f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sxdy = require( './../lib/sxdy.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sxdy( x.length, x, 1, y, 1 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..ab5579c8e6ff --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sxdy = tryRequire( resolve( __dirname, './../lib/sxdy.native.js' ) ); +var opts = { + 'skip': ( sxdy instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sxdy( x.length, x, 1, y, 1 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..2da1cfe9028b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.ndarray.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var sxdy = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sxdy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..1099e968abb7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,109 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var sxdy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sxdy instanceof Error ) +}; +var options = { + 'dtype': 'float32' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( len, -10.0, 10.0, options ); + var y = uniform( len, 1.0, 10.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var z; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = sxdy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnanf( z[ i%x.length ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..36d7c27be80f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/benchmark/c/benchmark.length.c @@ -0,0 +1,207 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sxdy.h" +#include +#include +#include +#include +#include + +#define NAME "sxdy" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static float random_uniform( const float min, const float max ) { + float v = (float)rand() / ( (float)RAND_MAX + 1.0f ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + float *x; + float *y; + double t; + int i; + + x = (float *)malloc( len * sizeof(float) ); + y = (float *)malloc( len * sizeof(float) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0f, 100.0f ); + y[ i ] = random_uniform( 1.0f, 100.0f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_sxdy( len, x, 1, y, 1 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + float *x; + float *y; + double t; + int i; + + x = (float *)malloc( len * sizeof(float) ); + y = (float *)malloc( len * sizeof(float) ); + for ( i = 0; i < len; i++ ) { + x[ i ] = random_uniform( -100.0f, 100.0f ); + y[ i ] = random_uniform( 1.0f, 100.0f ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_sxdy_ndarray( len, x, 1, 0, y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/sxdy/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/repl.txt new file mode 100644 index 000000000000..e74090fa8947 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/repl.txt @@ -0,0 +1,125 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Divides elements of a single-precision floating-point strided array `x` by + the corresponding elements of a single-precision floating-point strided + array `y` and assigns the results to `y`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + Input array. + + strideX: integer + Stride length for `x`. + + y: Float32Array + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + y: Float32Array + Output array. + + Examples + -------- + // Standard Usage: + > var buf = [ 2.0, 6.0, 12.0, 20.0, 30.0 ]; + > var x = new {{alias:@stdlib/array/float32}}( buf ); + > buf = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var y = new {{alias:@stdlib/array/float32}}( buf ); + > {{alias}}( x.length, x, 1, y, 1 ) + [ 1.0, 2.0, 3.0, 4.0, 5.0 ] + + // Using `N` and stride parameters: + > buf = [ 14.0, 2.0, 27.0, 4.0, 33.0, 6.0 ]; + > x = new {{alias:@stdlib/array/float32}}( buf ); + > buf = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ]; + > y = new {{alias:@stdlib/array/float32}}( buf ); + > {{alias}}( 3, x, 2, y, 2 ) + [ 2.0, 8.0, 3.0, 10.0, 3.0, 12.0 ] + + // Using view offsets: + > var bufX = [ 1.0, 18.0, 30.0, 44.0, 5.0, 6.0 ]; + > var bufY = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ]; + > var x0 = new {{alias:@stdlib/array/float32}}( bufX ); + > var y0 = new {{alias:@stdlib/array/float32}}( bufY ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetY = y0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, offsetX ); + > var y1 = new {{alias:@stdlib/array/float32}}( y0.buffer, offsetY ); + > {{alias}}( 3, x1, 1, y1, 1 ) + [ 2.0, 3.0, 4.0, 12.0 ] + > y0 + [ 7.0, 8.0, 2.0, 3.0, 4.0, 12.0 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Divides elements of a single-precision floating-point strided array `x` by + the corresponding elements of a single-precision floating-point strided + array `y` and assigns the results to `y` using alternative indexing + semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Float32Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Float32Array + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + y: Float32Array + Output array. + + Examples + -------- + // Standard Usage: + > var buf = [ 2.0, 6.0, 12.0, 20.0, 30.0 ]; + > var x = new {{alias:@stdlib/array/float32}}( buf ); + > buf = [ 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var y = new {{alias:@stdlib/array/float32}}( buf ); + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ 1.0, 2.0, 3.0, 4.0, 5.0 ] + + // Using index offsets: + > x = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 24.0, 36.0, 50.0 ] ); + > y = new {{alias:@stdlib/array/float32}}( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] ); + > {{alias}}.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ) + [ 6.0, 7.0, 3.0, 4.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..401498720389 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/types/index.d.ts @@ -0,0 +1,103 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Interface describing `sxdy`. +*/ +interface Routine { + /** + * Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + * var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * sxdy( x.length, x, 1, y, 1 ); + * // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] + */ + ( N: number, x: Float32Array, strideX: number, y: Float32Array, strideY: number ): Float32Array; + + /** + * Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting `x` index + * @param y - output array + * @param strideY - `y` stride length + * @param offsetY - starting `y` index + * @returns output array + * + * @example + * var Float32Array = require( '@stdlib/array/float32' ); + * + * var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + * var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * + * sxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] + */ + ndarray( N: number, x: Float32Array, strideX: number, offsetX: number, y: Float32Array, strideY: number, offsetY: number ): Float32Array; +} + +/** +* Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - `x` stride length +* @param y - output array +* @param strideY - `y` stride length +* @returns output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +* var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* sxdy( x.length, x, 1, y, 1 ); +* // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +* var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* sxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +declare var sxdy: Routine; + + +// EXPORTS // + +export = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/types/test.ts new file mode 100644 index 000000000000..f06df8580dba --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/docs/types/test.ts @@ -0,0 +1,250 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import sxdy = require( './index' ); + + +// TESTS // + +// The function returns a Float32Array... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy( x.length, x, 1, y, 1 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy( '10', x, 1, y, 1 ); // $ExpectError + sxdy( true, x, 1, y, 1 ); // $ExpectError + sxdy( false, x, 1, y, 1 ); // $ExpectError + sxdy( null, x, 1, y, 1 ); // $ExpectError + sxdy( undefined, x, 1, y, 1 ); // $ExpectError + sxdy( [], x, 1, y, 1 ); // $ExpectError + sxdy( {}, x, 1, y, 1 ); // $ExpectError + sxdy( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float32Array... +{ + const y = new Float32Array( 10 ); + + sxdy( 10, 10, 1, y, 1 ); // $ExpectError + sxdy( 10, '10', 1, y, 1 ); // $ExpectError + sxdy( 10, true, 1, y, 1 ); // $ExpectError + sxdy( 10, false, 1, y, 1 ); // $ExpectError + sxdy( 10, null, 1, y, 1 ); // $ExpectError + sxdy( 10, undefined, 1, y, 1 ); // $ExpectError + sxdy( 10, [ '1' ], 1, y, 1 ); // $ExpectError + sxdy( 10, {}, 1, y, 1 ); // $ExpectError + sxdy( 10, ( x: number ): number => x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy( x.length, x, '10', y, 1 ); // $ExpectError + sxdy( x.length, x, true, y, 1 ); // $ExpectError + sxdy( x.length, x, false, y, 1 ); // $ExpectError + sxdy( x.length, x, null, y, 1 ); // $ExpectError + sxdy( x.length, x, undefined, y, 1 ); // $ExpectError + sxdy( x.length, x, [], y, 1 ); // $ExpectError + sxdy( x.length, x, {}, y, 1 ); // $ExpectError + sxdy( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sxdy( 10, x, 1, 10, 1 ); // $ExpectError + sxdy( 10, x, 1, '10', 1 ); // $ExpectError + sxdy( 10, x, 1, true, 1 ); // $ExpectError + sxdy( 10, x, 1, false, 1 ); // $ExpectError + sxdy( 10, x, 1, null, 1 ); // $ExpectError + sxdy( 10, x, 1, undefined, 1 ); // $ExpectError + sxdy( 10, x, 1, [ '1' ], 1 ); // $ExpectError + sxdy( 10, x, 1, {}, 1 ); // $ExpectError + sxdy( 10, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy( x.length, x, 1, y, '10' ); // $ExpectError + sxdy( x.length, x, 1, y, true ); // $ExpectError + sxdy( x.length, x, 1, y, false ); // $ExpectError + sxdy( x.length, x, 1, y, null ); // $ExpectError + sxdy( x.length, x, 1, y, undefined ); // $ExpectError + sxdy( x.length, x, 1, y, [] ); // $ExpectError + sxdy( x.length, x, 1, y, {} ); // $ExpectError + sxdy( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy(); // $ExpectError + sxdy( x.length ); // $ExpectError + sxdy( x.length ); // $ExpectError + sxdy( x.length, x ); // $ExpectError + sxdy( x.length, x, 1 ); // $ExpectError + sxdy( x.length, x, 1, y ); // $ExpectError + sxdy( x.length, x, 1, y ); // $ExpectError + sxdy( x.length, x, 1, y, 1, 10 ); // $ExpectError +} + +// Attached to the main export is an `ndarray` method which returns a Float32Array... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType Float32Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float32Array... +{ + const y = new Float32Array( 10 ); + + sxdy.ndarray( 10, 10, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, '10', 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, true, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, false, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, null, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, undefined, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, [ '1' ], 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, {}, 1, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float32Array... +{ + const x = new Float32Array( 10 ); + + sxdy.ndarray( 10, x, 1, 0, 10, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, '10', 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, true, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, false, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, null, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, undefined, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, {}, 1, 0 ); // $ExpectError + sxdy.ndarray( 10, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float32Array( 10 ); + const y = new Float32Array( 10 ); + + sxdy.ndarray(); // $ExpectError + sxdy.ndarray( x.length ); // $ExpectError + sxdy.ndarray( x.length ); // $ExpectError + sxdy.ndarray( x.length, x ); // $ExpectError + sxdy.ndarray( x.length, x, 1 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + sxdy.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/c/example.c new file mode 100644 index 000000000000..0deaa7dc7817 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sxdy.h" +#include + +int main( void ) { + // Create strided arrays: + const float x[] = { 2.0f, -6.0f, 12.0f, -20.0f, 30.0f, -42.0f, 56.0f, -72.0f }; + float y[] = { 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f }; + + // Specify the number of indexed elements: + const int N = 8; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Divide elements of `x` by the corresponding elements of `y`: + stdlib_strided_sxdy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < 8; i++ ) { + printf( "y[ %i ] = %f\n", i, y[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/index.js new file mode 100644 index 000000000000..00a66515561f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var sxdy = require( './../lib' ); + +var x = discreteUniform( 10, -100, 100, { + 'dtype': 'float32' +}); +console.log( x ); + +var y = discreteUniform( 10, 1, 100, { + 'dtype': 'float32' +}); +console.log( y ); + +sxdy( x.length, x, 1, y, 1 ); +console.log( y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/sxdy/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* var sxdy = require( '@stdlib/blas/ext/base/sxdy' ); +* +* var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +* var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* sxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var sxdy; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + sxdy = main; +} else { + sxdy = tmp; +} + + +// EXPORTS // + +module.exports = sxdy; + +// exports: { "ndarray": "sxdy.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/main.js new file mode 100644 index 000000000000..e6211740b2d8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sxdy = require( './sxdy.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( sxdy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/native.js new file mode 100644 index 000000000000..bea9d15e6b99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var sxdy = require( './sxdy.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( sxdy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/ndarray.js new file mode 100644 index 000000000000..500685fcb399 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/ndarray.js @@ -0,0 +1,98 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float32Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +* var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* sxdy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function sxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var ix; + var iy; + var m; + var i; + + if ( N <= 0 ) { + return y; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideY === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + y[ iy ] = x[ ix ] / y[ iy ]; + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return y; + } + for ( i = m; i < N; i += M ) { + y[ iy ] = x[ ix ] / y[ iy ]; + y[ iy+1 ] = x[ ix+1 ] / y[ iy+1 ]; + y[ iy+2 ] = x[ ix+2 ] / y[ iy+2 ]; + y[ iy+3 ] = x[ ix+3 ] / y[ iy+3 ]; + y[ iy+4 ] = x[ ix+4 ] / y[ iy+4 ]; + ix += M; + iy += M; + } + return y; + } + for ( i = 0; i < N; i++ ) { + y[ iy ] = x[ ix ] / y[ iy ]; + ix += strideX; + iy += strideY; + } + return y; +} + + +// EXPORTS // + +module.exports = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/ndarray.native.js new file mode 100644 index 000000000000..33a0ca4ed772 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/ndarray.native.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Float32Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +* var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* sxdy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function sxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ); + return y; +} + + +// EXPORTS // + +module.exports = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/sxdy.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/sxdy.js new file mode 100644 index 000000000000..8f4d5373b703 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/sxdy.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Float32Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +* var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* sxdy( x.length, x, 1, y, 1 ); +* // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function sxdy( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/sxdy.native.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/sxdy.native.js new file mode 100644 index 000000000000..f40ccc75b125 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/lib/sxdy.native.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Float32Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Float32Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Float32Array} output array +* +* @example +* var Float32Array = require( '@stdlib/array/float32' ); +* +* var x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); +* var y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* +* sxdy( x.length, x, 1, y, 1 ); +* // y => [ 1.0, 2.0, 3.0, 4.0, 5.0 ] +*/ +function sxdy( N, x, strideX, y, strideY ) { + addon( N, x, strideX, y, strideY ); + return y; +} + + +// EXPORTS // + +module.exports = sxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/sxdy/manifest.json new file mode 100644 index 000000000000..0495ff2aab4a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/manifest.json @@ -0,0 +1,98 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-float32array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "build", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/sxdy/package.json new file mode 100644 index 000000000000..697e07cd8c22 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/package.json @@ -0,0 +1,80 @@ +{ + "name": "@stdlib/blas/ext/base/sxdy", + "version": "0.0.0", + "description": "Divide elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assign the results to `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "linear", + "algebra", + "subroutines", + "divide", + "division", + "quotient", + "transform", + "strided", + "array", + "ndarray", + "vector", + "xdy", + "sxdy", + "float32", + "single", + "float32array" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/addon.c new file mode 100644 index 000000000000..c76f0e0ace9f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sxdy.h" +#include "stdlib/napi/export.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_float32array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_sxdy)( N, X, strideX, Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_sxdy_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/main.c new file mode 100644 index 000000000000..351afeb73b62 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/src/main.c @@ -0,0 +1,95 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/sxdy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/strided/base/stride2offset.h" + +static const CBLAS_INT M = 5; + +/** +* Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y`. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param Y output array +* @param strideY stride length for `Y` +*/ +void API_SUFFIX(stdlib_strided_sxdy)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_sxdy_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Divides elements of a single-precision floating-point strided array `x` by the corresponding elements of a single-precision floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param Y output array +* @param strideY stride length for `Y` +* @param offsetY starting index for `Y` +*/ +void API_SUFFIX(stdlib_strided_sxdy_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideY == 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + Y[ iy ] = X[ ix ] / Y[ iy ]; + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return; + } + for ( i = m; i < N; i += M ) { + Y[ iy ] = X[ ix ] / Y[ iy ]; + Y[ iy+1 ] = X[ ix+1 ] / Y[ iy+1 ]; + Y[ iy+2 ] = X[ ix+2 ] / Y[ iy+2 ]; + Y[ iy+3 ] = X[ ix+3 ] / Y[ iy+3 ]; + Y[ iy+4 ] = X[ ix+4 ] / Y[ iy+4 ]; + ix += M; + iy += M; + } + return; + } + for ( i = 0; i < N; i++ ) { + Y[ iy ] = X[ ix ] / Y[ iy ]; + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.js new file mode 100644 index 000000000000..2a25c7fabf2e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var sxdy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof sxdy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var sxdy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sxdy, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var sxdy; + var main; + + main = require( './../lib/main.js' ); + + sxdy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( sxdy, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.ndarray.js new file mode 100644 index 000000000000..8244953dabc8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.ndarray.js @@ -0,0 +1,291 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sxdy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( sxdy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]); + + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 12.0 ] ); + y = new Float32Array( [ 5.0, 6.0 ] ); + expected = new Float32Array( [ 1.0, 2.0 ] ); + + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + out = sxdy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + sxdy( 0, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + sxdy( -4, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 2.0, // 0 + 2.0, + 9.0, // 1 + 4.0, + 20.0 // 2 + ]); + y = new Float32Array( [ 2.0, 3.0, 4.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 3.0, // 9.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + sxdy( 3, x, 2, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 30.0, + 2.0, // 6.0 / 3.0 + 10.0, + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x, 1, 0, y, 2, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 4.0, // 2 + 2.0, + 9.0, // 1 + 4.0, + 10.0 // 0 + ]); + y = new Float32Array([ + 4.0, // 2 + 3.0, // 1 + 2.0 // 0 + ]); + expected = new Float32Array([ + 1.0, // 4.0 / 4.0 + 3.0, // 9.0 / 3.0 + 5.0 // 10.0 / 2.0 + ]); + + sxdy( 3, x, -2, x.length-1, y, -1, y.length-1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 0.0, + 2.0, // 0 + 2.0, + 9.0, // 1 + 4.0, + 20.0 // 2 + ]); + y = new Float32Array( [ 2.0, 3.0, 4.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 3.0, // 9.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + sxdy( 3, x, 2, 1, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array([ + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x, 1, 0, y, 1, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 0.0, + 2.0, // 0 + 0.0, + 6.0, // 1 + 0.0, + 12.0 // 2 + ]); + y = new Float32Array([ + 0.0, + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 0.0 + ]); + expected = new Float32Array([ + 0.0, + 0.0, + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 0.0 + ]); + + sxdy( 3, x, 2, 1, y, 1, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float32Array( 100 ); + y = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + y = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.ndarray.native.js new file mode 100644 index 000000000000..1c2e1cd894e8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.ndarray.native.js @@ -0,0 +1,300 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sxdy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( sxdy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( sxdy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]); + + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 12.0 ] ); + y = new Float32Array( [ 5.0, 6.0 ] ); + expected = new Float32Array( [ 1.0, 2.0 ] ); + + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + out = sxdy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + sxdy( 0, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + sxdy( -4, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 2.0, // 0 + 2.0, + 9.0, // 1 + 4.0, + 20.0 // 2 + ]); + y = new Float32Array( [ 2.0, 3.0, 4.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 3.0, // 9.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + sxdy( 3, x, 2, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 30.0, + 2.0, // 6.0 / 3.0 + 10.0, + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x, 1, 0, y, 2, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 4.0, // 2 + 2.0, + 9.0, // 1 + 4.0, + 10.0 // 0 + ]); + y = new Float32Array([ + 4.0, // 2 + 3.0, // 1 + 2.0 // 0 + ]); + expected = new Float32Array([ + 1.0, // 4.0 / 4.0 + 3.0, // 9.0 / 3.0 + 5.0 // 10.0 / 2.0 + ]); + + sxdy( 3, x, -2, x.length-1, y, -1, y.length-1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 0.0, + 2.0, // 0 + 2.0, + 9.0, // 1 + 4.0, + 20.0 // 2 + ]); + y = new Float32Array( [ 2.0, 3.0, 4.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 3.0, // 9.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + sxdy( 3, x, 2, 1, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` offset', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array([ + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + expected = new Float32Array([ + 0.0, + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x, 1, 0, y, 1, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 0.0, + 2.0, // 0 + 0.0, + 6.0, // 1 + 0.0, + 12.0 // 2 + ]); + y = new Float32Array([ + 0.0, + 0.0, + 2.0, // 0 + 3.0, // 1 + 4.0, // 2 + 0.0 + ]); + expected = new Float32Array([ + 0.0, + 0.0, + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 0.0 + ]); + + sxdy( 3, x, 2, 1, y, 1, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float32Array( 100 ); + y = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + y = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, 0, y, 1, 0 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.sxdy.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.sxdy.js new file mode 100644 index 000000000000..f54a9623e659 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.sxdy.js @@ -0,0 +1,245 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var sxdy = require( './../lib/sxdy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( sxdy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]); + + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 12.0 ] ); + y = new Float32Array( [ 5.0, 6.0 ] ); + expected = new Float32Array( [ 1.0, 2.0 ] ); + + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = sxdy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + sxdy( 0, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + sxdy( -4, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 2.0, // 0 + 2.0, + 9.0, // 1 + 4.0, + 20.0 // 2 + ]); + y = new Float32Array( [ 2.0, 3.0, 4.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 3.0, // 9.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + sxdy( 3, x, 2, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 30.0, + 2.0, // 6.0 / 3.0 + 10.0, + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x, 1, y, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 4.0, // 2 + 2.0, + 9.0, // 1 + 4.0, + 10.0 // 0 + ]); + y = new Float32Array([ + 4.0, // 2 + 3.0, // 1 + 2.0 // 0 + ]); + expected = new Float32Array([ + 1.0, // 4.0 / 4.0 + 3.0, // 9.0 / 3.0 + 5.0 // 10.0 / 2.0 + ]); + + sxdy( 3, x, -2, y, -1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Float32Array([ + 10.0, + 2.0, // 0 + 6.0, // 1 + 12.0, // 2 + 4.0 + ]); + y0 = new Float32Array([ + 10.0, + 10.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Float32Array([ + 10.0, + 10.0, + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x1, 1, y1, 1 ); + t.deepEqual( y0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float32Array( 100 ); + y = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + y = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.sxdy.native.js b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.sxdy.native.js new file mode 100644 index 000000000000..b9022f04b97c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/sxdy/test/test.sxdy.native.js @@ -0,0 +1,254 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Float32Array = require( '@stdlib/array/float32' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var sxdy = tryRequire( resolve( __dirname, './../lib/sxdy.native.js' ) ); +var opts = { + 'skip': ( sxdy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( sxdy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0, // 12.0 / 4.0 + 4.0, // 20.0 / 5.0 + 5.0 // 30.0 / 6.0 + ]); + + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( [ 5.0, 12.0 ] ); + y = new Float32Array( [ 5.0, 6.0 ] ); + expected = new Float32Array( [ 1.0, 2.0 ] ); + + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0, 20.0, 30.0 ] ); + y = new Float32Array( [ 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = sxdy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array( [ 2.0, 6.0, 12.0 ] ); + y = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + expected = new Float32Array( [ 4.0, 5.0, 6.0 ] ); + + sxdy( 0, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + sxdy( -4, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 2.0, // 0 + 2.0, + 9.0, // 1 + 4.0, + 20.0 // 2 + ]); + y = new Float32Array( [ 2.0, 3.0, 4.0 ] ); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 3.0, // 9.0 / 3.0 + 5.0 // 20.0 / 4.0 + ]); + + sxdy( 3, x, 2, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ 2.0, 6.0, 12.0 ]); + y = new Float32Array([ + 2.0, // 0 + 30.0, + 3.0, // 1 + 10.0, + 4.0 // 2 + ]); + expected = new Float32Array([ + 1.0, // 2.0 / 2.0 + 30.0, + 2.0, // 6.0 / 3.0 + 10.0, + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x, 1, y, 2 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Float32Array([ + 4.0, // 2 + 2.0, + 9.0, // 1 + 4.0, + 10.0 // 0 + ]); + y = new Float32Array([ + 4.0, // 2 + 3.0, // 1 + 2.0 // 0 + ]); + expected = new Float32Array([ + 1.0, // 4.0 / 4.0 + 3.0, // 9.0 / 3.0 + 5.0 // 10.0 / 2.0 + ]); + + sxdy( 3, x, -2, y, -1 ); + t.deepEqual( y, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Float32Array([ + 10.0, + 2.0, // 0 + 6.0, // 1 + 12.0, // 2 + 4.0 + ]); + y0 = new Float32Array([ + 10.0, + 10.0, + 2.0, // 0 + 3.0, // 1 + 4.0 // 2 + ]); + + x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Float32Array([ + 10.0, + 10.0, + 1.0, // 2.0 / 2.0 + 2.0, // 6.0 / 3.0 + 3.0 // 12.0 / 4.0 + ]); + + sxdy( 3, x1, 1, y1, 1 ); + t.deepEqual( y0, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + var i; + + x = new Float32Array( 100 ); + y = new Float32Array( 100 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + x = new Float32Array( 240 ); + y = new Float32Array( 240 ); + expected = new Float32Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + x[ i ] = i; + y[ i ] = x.length - i; + expected[ i ] = x[ i ] / y[ i ]; + } + sxdy( x.length, x, 1, y, 1 ); + t.deepEqual( y, expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/scripts/build.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/scripts/build.js index 5f54efd4e40f..66bf9650b6d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/scripts/build.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/scripts/build.js @@ -26,6 +26,7 @@ var resolve = require( 'path' ).resolve; var readFile = require( '@stdlib/fs/read-file' ).sync; var writeFile = require( '@stdlib/fs/write-file' ).sync; var replace = require( '@stdlib/string/replace' ); +var currentYear = require( '@stdlib/time/current-year' ); // VARIABLES // @@ -33,7 +34,6 @@ var replace = require( '@stdlib/string/replace' ); var wpath = resolve( __dirname, '..', 'src', 'main.wasm' ); var tpath = resolve( __dirname, 'template.txt' ); var opath = resolve( __dirname, '..', 'lib', 'binary.browser.js' ); -var currentYear = require( '@stdlib/time/current-year' ); var opts = { 'encoding': 'utf8' diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/src/Makefile index eb51121eec4c..0fbfa072ced8 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/scripts/build.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/scripts/build.js index 5f54efd4e40f..66bf9650b6d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/scripts/build.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/scripts/build.js @@ -26,6 +26,7 @@ var resolve = require( 'path' ).resolve; var readFile = require( '@stdlib/fs/read-file' ).sync; var writeFile = require( '@stdlib/fs/write-file' ).sync; var replace = require( '@stdlib/string/replace' ); +var currentYear = require( '@stdlib/time/current-year' ); // VARIABLES // @@ -33,7 +34,6 @@ var replace = require( '@stdlib/string/replace' ); var wpath = resolve( __dirname, '..', 'src', 'main.wasm' ); var tpath = resolve( __dirname, 'template.txt' ); var opath = resolve( __dirname, '..', 'lib', 'binary.browser.js' ); -var currentYear = require( '@stdlib/time/current-year' ); var opts = { 'encoding': 'utf8' diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/package.json b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/package.json index 9d4c4f937d2f..f7910642ea63 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/package.json +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/blas/ext/base/wasm/dnansumkbn2", "version": "0.0.0", - "description": "Compute the sum of double-precision floating-point strided array elements, ignoring `NaN` values and using a second-order iterative Kahan–Babuška algorithm.", + "description": "Compute the sum of double-precision floating-point strided array elements, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/scripts/build.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/scripts/build.js index 5f54efd4e40f..66bf9650b6d6 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/scripts/build.js +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/scripts/build.js @@ -26,6 +26,7 @@ var resolve = require( 'path' ).resolve; var readFile = require( '@stdlib/fs/read-file' ).sync; var writeFile = require( '@stdlib/fs/write-file' ).sync; var replace = require( '@stdlib/string/replace' ); +var currentYear = require( '@stdlib/time/current-year' ); // VARIABLES // @@ -33,7 +34,6 @@ var replace = require( '@stdlib/string/replace' ); var wpath = resolve( __dirname, '..', 'src', 'main.wasm' ); var tpath = resolve( __dirname, 'template.txt' ); var opath = resolve( __dirname, '..', 'lib', 'binary.browser.js' ); -var currentYear = require( '@stdlib/time/current-year' ); var opts = { 'encoding': 'utf8' diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/src/Makefile +++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/README.md b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/README.md new file mode 100644 index 000000000000..0030cbdf3770 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/README.md @@ -0,0 +1,330 @@ + + +# zindexOfTruthy + +> Return the index of the first truthy element in a double-precision complex floating-point strided array. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var zindexOfTruthy = require( '@stdlib/blas/ext/base/zindex-of-truthy' ); +``` + +#### zindexOfTruthy( N, x, strideX ) + +Returns the index of the first truthy element in a double-precision complex floating-point strided array. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0, 4.0, 5.0 ] ); + +var idx = zindexOfTruthy( x.length, x, 1 ); +// returns 1 +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Complex128Array`][@stdlib/array/complex128]. +- **strideX**: stride length. + +If the function is unable to find a truthy element, the function returns `-1`. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0 ] ); + +var idx = zindexOfTruthy( x.length, x, 1 ); +// returns -1 +``` + +The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element: + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 0.0, 0.0, 3.0, 4.0, 0.0, 0.0, 5.0, 6.0, 7.0, 8.0, 9.0, 1.0, 2.0, 3.0, 4.0, 5.0 ] ); + +var idx = zindexOfTruthy( 4, x, 2 ); +// returns 2 +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +// Initial array... +var x0 = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0, 3.0, 4.0 ] ); + +// Create an offset view... +var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +// Find index... +var idx = zindexOfTruthy( 2, x1, 1 ); +// returns 0 +``` + +#### zindexOfTruthy.ndarray( N, x, strideX, offsetX ) + +Returns the index of the first truthy element in a double-precision complex floating-point strided array using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0, 4.0, 5.0 ] ); + +var idx = zindexOfTruthy.ndarray( x.length, x, 1, 0 ); +// returns 1 +``` + +The function has the following additional parameters: + +- **offsetX**: starting index. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements of the strided array: + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0 ] ); + +var idx = zindexOfTruthy.ndarray( 3, x, 1, x.length-3 ); +// returns 2 +``` + +
+ + + + + +
+ +## Notes + +- A complex number is truthy when at least one of its real or imaginary components is truthy. +- If unable to find a truthy element, both functions return `-1`. +- Both functions explicitly treat `NaN` values as falsy. + +
+ + + + + +
+ +## Examples + + + +```javascript +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var logEach = require( '@stdlib/console/log-each' ); +var zindexOfTruthy = require( '@stdlib/blas/ext/base/zindex-of-truthy' ); + +var buf = bernoulli( 10*2, 0.7, { + 'dtype': 'float64' +}); +var x = new Complex128Array( buf.buffer ); +logEach( '%s', x ); + +var idx = zindexOfTruthy( x.length, x, 1 ); +console.log( idx ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/zindex_of_truthy.h" +``` + +#### stdlib_strided_zindex_of_truthy( N, \*X, strideX ) + +Returns the index of the first truthy element in a double-precision complex floating-point strided array. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 0.0, 0.0, 1.0, 2.0 }; + +int idx = stdlib_strided_zindex_of_truthy( 2, (const stdlib_complex128_t *)x, 1 ); +// returns 1 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. + +```c +CBLAS_INT stdlib_strided_zindex_of_truthy( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX ); +``` + +#### stdlib_strided_zindex_of_truthy_ndarray( N, \*X, strideX, offsetX ) + +Returns the index of the first truthy element in a double-precision complex floating-point strided array using alternative indexing semantics. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 0.0, 0.0, 1.0, 2.0 }; + +int idx = stdlib_strided_zindex_of_truthy_ndarray( 2, (const stdlib_complex128_t *)x, 1, 0 ); +// returns 1 +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length. +- **offsetX**: `[in] CBLAS_INT` starting index. + +```c +CBLAS_INT stdlib_strided_zindex_of_truthy_ndarray( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +``` + +
+ + + + + +
+ +### Notes + +- A complex number is truthy when at least one of its real or imaginary components is truthy. +- If unable to find a truthy element, both functions return `-1`. +- Both functions explicitly treat `NaN` values as falsy. + +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/zindex_of_truthy.h" +#include "stdlib/complex/float64/ctor.h" +#include + +int main( void ) { + // Create a strided array (interleaved real and imaginary components): + const double x[] = { 0.0, 0.0, 1.0, 2.0, 4.0, 5.0, 6.0, 7.0 }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify a stride: + const int strideX = 1; + + // Find the index of the first truthy element: + int idx = stdlib_strided_zindex_of_truthy( N, (const stdlib_complex128_t *)x, strideX ); + + // Print the result: + printf( "index value: %d\n", idx ); +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.js new file mode 100644 index 000000000000..470721aef897 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zindexOfTruthy = require( './../lib/zindex_of_truthy.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = new Complex128Array( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = zindexOfTruthy( x.length, x, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..5b8663b4f431 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.native.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zindexOfTruthy = tryRequire( resolve( __dirname, './../lib/zindex_of_truthy.native.js' ) ); +var opts = { + 'skip': ( zindexOfTruthy instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = new Complex128Array( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = zindexOfTruthy( x.length, x, 1 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..8f7aa5dea810 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.ndarray.js @@ -0,0 +1,97 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zindexOfTruthy = require( './../lib/ndarray.js' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = new Complex128Array( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = zindexOfTruthy( x.length, x, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..b082d5a3e720 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zindexOfTruthy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zindexOfTruthy instanceof Error ) +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = new Complex128Array( len ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = zindexOfTruthy( x.length, x, 1, 0 ); + if ( out !== out ) { + b.fail( 'should return an integer' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..faa1ac640b8c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/benchmark/c/benchmark.length.c @@ -0,0 +1,200 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zindex_of_truthy.h" +#include "stdlib/complex/float64/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "zindex_of_truthy" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double t; + int idx; + int i; + + x = (double *)malloc( (size_t)( len*2 ) * sizeof( double ) ); + for ( i = 0; i < len*2; i++ ) { + x[ i ] = 0.0; + } + x[ (len*2)-1 ] = 1.0; + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ (len*2)-4 ] = (double)( i % 4 ); + idx = stdlib_strided_zindex_of_truthy( len, (const stdlib_complex128_t *)x, 1 ); + if ( idx < 0 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < 0 ) { + printf( "unexpected result\n" ); + } + free( x ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double t; + int idx; + int i; + + x = (double *)malloc( (size_t)( len*2 ) * sizeof( double ) ); + for ( i = 0; i < len*2; i++ ) { + x[ i ] = 0.0; + } + x[ (len*2)-1 ] = 1.0; + idx = -1; + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ (len*2)-4 ] = (double)( i % 4 ); + idx = stdlib_strided_zindex_of_truthy_ndarray( len, (const stdlib_complex128_t *)x, 1, 0 ); + if ( idx < 0 ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( idx < 0 ) { + printf( "unexpected result\n" ); + } + free( x ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/repl.txt new file mode 100644 index 000000000000..b359df93a40f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/repl.txt @@ -0,0 +1,77 @@ + +{{alias}}( N, x, strideX ) + Returns the index of the first truthy element in a double-precision complex + floating-point strided array. + + The `N` and stride parameters determine which elements in the strided array + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0`, the function returns `-1`. + + A complex number is truthy when at least one of its real or imaginary + components is truthy. + + The function treats `NaN` values as falsy. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex128Array + Input array. + + strideX: integer + Stride length. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + > var x = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 1.0, 2.0 ] ); + > var idx = {{alias}}( x.length, x, 1 ) + 1 + + +{{alias}}.ndarray( N, x, strideX, offsetX ) + Returns the index of the first truthy element in a double-precision complex + floating-point strided array using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameter supports indexing semantics based on a + starting index. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex128Array + Input array. + + strideX: integer + Stride length. + + offsetX: integer + Starting index. + + Returns + ------- + idx: integer + Index. + + Examples + -------- + > var x = new {{alias:@stdlib/array/complex128}}( [ 0.0, 0.0, 1.0, 2.0 ] ); + > var idx = {{alias}}.ndarray( x.length, x, 1, 0 ) + 1 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/types/index.d.ts new file mode 100644 index 000000000000..c53c507b3609 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/types/index.d.ts @@ -0,0 +1,112 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +import { Complex128Array } from '@stdlib/types/array'; + +/** +* Interface describing `zindexOfTruthy`. +*/ +interface Routine { + /** + * Returns the index of the first truthy element in a double-precision complex floating-point strided array. + * + * ## Notes + * + * - A complex number is truthy when at least one of its real or imaginary components is truthy. + * - If unable to find a truthy element, the function returns `-1`. + * - The function explicitly treats `NaN` values as falsy. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @returns index + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0 ] ); + * + * var idx = zindexOfTruthy( x.length, x, 1 ); + * // returns 1 + */ + ( N: number, x: Complex128Array, strideX: number ): number; + + /** + * Returns the index of the first truthy element in a double-precision complex floating-point strided array using alternative indexing semantics. + * + * ## Notes + * + * - A complex number is truthy when at least one of its real or imaginary components is truthy. + * - If unable to find a truthy element, the function returns `-1`. + * - The function explicitly treats `NaN` values as falsy. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - stride length + * @param offsetX - starting index + * @returns index + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0 ] ); + * + * var idx = zindexOfTruthy.ndarray( x.length, x, 1, 0 ); + * // returns 1 + */ + ndarray( N: number, x: Complex128Array, strideX: number, offsetX: number ): number; +} + +/** +* Returns the index of the first truthy element in a double-precision complex floating-point strided array. +* +* ## Notes +* +* - A complex number is truthy when at least one of its real or imaginary components is truthy. +* - If unable to find a truthy element, the function returns `-1`. +* - The function explicitly treats `NaN` values as falsy. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - stride length +* @returns index +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0 ] ); +* +* var idx = zindexOfTruthy( x.length, x, 1 ); +* // returns 1 +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 0.0, 0.0, 1.0, 2.0 ] ); +* +* var idx = zindexOfTruthy.ndarray( x.length, x, 1, 0 ); +* // returns 1 +*/ +declare var zindexOfTruthy: Routine; + + +// EXPORTS // + +export = zindexOfTruthy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/types/test.ts new file mode 100644 index 000000000000..78b08a0bd288 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/docs/types/test.ts @@ -0,0 +1,133 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import zindexOfTruthy = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy( x.length, x, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy( '1', x, 1 ); // $ExpectError + zindexOfTruthy( true, x, 1 ); // $ExpectError + zindexOfTruthy( false, x, 1 ); // $ExpectError + zindexOfTruthy( null, x, 1 ); // $ExpectError + zindexOfTruthy( {}, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex128Array... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy( x.length, '1', 1 ); // $ExpectError + zindexOfTruthy( x.length, true, 1 ); // $ExpectError + zindexOfTruthy( x.length, false, 1 ); // $ExpectError + zindexOfTruthy( x.length, null, 1 ); // $ExpectError + zindexOfTruthy( x.length, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy( x.length, x, '1' ); // $ExpectError + zindexOfTruthy( x.length, x, true ); // $ExpectError + zindexOfTruthy( x.length, x, false ); // $ExpectError + zindexOfTruthy( x.length, x, null ); // $ExpectError + zindexOfTruthy( x.length, x, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + zindexOfTruthy(); // $ExpectError + zindexOfTruthy( 3 ); // $ExpectError + zindexOfTruthy( 3, new Complex128Array( [ 1.0, 2.0, 3.0 ] ) ); // $ExpectError + zindexOfTruthy( 3, new Complex128Array( [ 1.0, 2.0, 3.0 ] ), 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy.ndarray( x.length, x, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy.ndarray( '1', x, 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( true, x, 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( false, x, 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( null, x, 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( {}, x, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex128Array... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy.ndarray( x.length, '1', 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, true, 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, false, 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, null, 1, 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, {}, 1, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy.ndarray( x.length, x, '1', 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, true, 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, false, 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, null, 1 ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, {}, 1 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + var x = new Complex128Array( [ 1.0, 2.0, 3.0 ] ); + + zindexOfTruthy.ndarray( x.length, x, 1, '1' ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, 1, true ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, 1, false ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, 1, null ); // $ExpectError + zindexOfTruthy.ndarray( x.length, x, 1, {} ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + zindexOfTruthy.ndarray(); // $ExpectError + zindexOfTruthy.ndarray( 3 ); // $ExpectError + zindexOfTruthy.ndarray( 3, new Complex128Array( [ 1.0, 2.0, 3.0 ] ) ); // $ExpectError + zindexOfTruthy.ndarray( 3, new Complex128Array( [ 1.0, 2.0, 3.0 ] ), 1 ); // $ExpectError + zindexOfTruthy.ndarray( 3, new Complex128Array( [ 1.0, 2.0, 3.0 ] ), 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/c/example.c new file mode 100644 index 000000000000..5616071f22e9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/c/example.c @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zindex_of_truthy.h" +#include "stdlib/complex/float64/ctor.h" +#include + +int main( void ) { + // Create a strided array (interleaved real and imaginary components): + const double x[] = { 0.0, 0.0, 1.0, 2.0, 4.0, 5.0, 6.0, 7.0 }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify a stride: + const int strideX = 1; + + // Find the index of the first truthy element: + int idx = stdlib_strided_zindex_of_truthy( N, (const stdlib_complex128_t *)x, strideX ); + + // Print the result: + printf( "index value: %d\n", idx ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/index.js new file mode 100644 index 000000000000..b78478e8caae --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/examples/index.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var bernoulli = require( '@stdlib/random/array/bernoulli' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var logEach = require( '@stdlib/console/log-each' ); +var zindexOfTruthy = require( './../lib' ); + +var buf = bernoulli( 10*2, 0.7, { + 'dtype': 'float64' +}); +var x = new Complex128Array( buf.buffer ); +logEach( '%s', x ); + +var idx = zindexOfTruthy( x.length, x, 1 ); +console.log( idx ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "blas", + "find", + "index", + "search", + "truthy", + "array", + "ndarray", + "strided", + "complex", + "complex128", + "complex128array" + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/addon.c new file mode 100644 index 000000000000..daf5152cc213 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/addon.c @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zindex_of_truthy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex128array.h" +#include "stdlib/napi/create_int32.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_zindex_of_truthy)( N, (const stdlib_complex128_t *)X, strideX ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 4 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_CREATE_INT32( env, API_SUFFIX(stdlib_strided_zindex_of_truthy_ndarray)( N, (const stdlib_complex128_t *)X, strideX, offsetX ), idx ); // TODO: Need to revisit in order to support int64_t for CBLAS_INT + return idx; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/main.c new file mode 100644 index 000000000000..d8ad62e8c9f5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/src/main.c @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zindex_of_truthy.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Returns the index of the first truthy element in a double-precision complex floating-point strided array. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_zindex_of_truthy)( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + return API_SUFFIX(stdlib_strided_zindex_of_truthy_ndarray)( N, X, strideX, ox ); +} + +/** +* Returns the index of the first truthy element in a double-precision complex floating-point strided array using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length +* @param offsetX starting index +* @return index +*/ +CBLAS_INT API_SUFFIX(stdlib_strided_zindex_of_truthy_ndarray)( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { + stdlib_complex128_t v; + CBLAS_INT ix; + CBLAS_INT i; + double re; + double im; + + if ( N <= 0 ) { + return -1; + } + ix = offsetX; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + re = stdlib_complex128_real( v ); + im = stdlib_complex128_imag( v ); + if ( ( re != 0.0 && !stdlib_base_is_nan( re ) ) || ( im != 0.0 && !stdlib_base_is_nan( im ) ) ) { + return i; + } + ix += strideX; + } + return -1; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.js new file mode 100644 index 000000000000..d36c2610e94d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var zindexOfTruthy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zindexOfTruthy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zindexOfTruthy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zindexOfTruthy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zindexOfTruthy, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zindexOfTruthy; + var main; + + main = require( './../lib/zindex_of_truthy.js' ); + + zindexOfTruthy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zindexOfTruthy, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.ndarray.js new file mode 100644 index 000000000000..17ad7be49605 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.ndarray.js @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zindexOfTruthy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zindexOfTruthy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first truthy element', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0, + 2.0, + 2.0, + 3.0, + 3.0, + 0.0, + 0.0 + ]); + + // Nonnegative stride... + actual = zindexOfTruthy( x.length, x, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( x.length-1, x, 1, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = zindexOfTruthy( x.length-2, x, 1, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 1, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + actual = zindexOfTruthy( x.length, x, -1, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, -2, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, -2, x.length-2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function ignores falsy elements (e.g., `0+0i`, `NaN+NaNi`, `NaN+0i`)', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + NaN, + NaN, + NaN, + 0.0, + 1.0, + 1.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1, 0 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if unable to find a truthy element', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 1.0, + 1.0, + 0.0, + 0.0, + 3.0, + 4.0 + ]); + + actual = zindexOfTruthy( 0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = zindexOfTruthy( -1, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.ndarray.native.js new file mode 100644 index 000000000000..a26a2388aa5b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.ndarray.native.js @@ -0,0 +1,152 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zindexOfTruthy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zindexOfTruthy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zindexOfTruthy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first truthy element', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0, + 2.0, + 2.0, + 3.0, + 3.0, + 0.0, + 0.0 + ]); + + // Nonnegative stride... + actual = zindexOfTruthy( x.length, x, 1, 0 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( x.length-1, x, 1, 1 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + actual = zindexOfTruthy( x.length-2, x, 1, 2 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 1, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + // Negative stride... + actual = zindexOfTruthy( x.length, x, -1, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, -2, x.length-1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, -2, x.length-2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function ignores falsy elements (e.g., `0+0i`, `NaN+NaNi`, `NaN+0i`)', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + NaN, + NaN, + NaN, + 0.0, + 1.0, + 1.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1, 0 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if unable to find a truthy element', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 1.0, + 1.0, + 0.0, + 0.0, + 3.0, + 4.0 + ]); + + actual = zindexOfTruthy( 0, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = zindexOfTruthy( -1, x, 1, 0 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.zindex_of_truthy.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.zindex_of_truthy.js new file mode 100644 index 000000000000..96da7d86b6df --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.zindex_of_truthy.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zindexOfTruthy = require( './../lib/zindex_of_truthy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zindexOfTruthy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first truthy element', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0, + 2.0, + 2.0, + 3.0, + 3.0, + 0.0, + 0.0 + ]); + + // Nonnegative stride... + actual = zindexOfTruthy( x.length, x, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + actual = zindexOfTruthy( x.length, x, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, -2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function ignores falsy elements (e.g., `0+0i`, `NaN+NaNi`, `NaN+0i`)', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + NaN, + NaN, + NaN, + 0.0, + 1.0, + 1.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if unable to find a truthy element', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 1.0, + 1.0, + 0.0, + 0.0, + 3.0, + 4.0 + ]); + + actual = zindexOfTruthy( 0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = zindexOfTruthy( -1, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.zindex_of_truthy.native.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.zindex_of_truthy.native.js new file mode 100644 index 000000000000..09acc9f73e11 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of-truthy/test/test.zindex_of_truthy.native.js @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zindexOfTruthy = tryRequire( resolve( __dirname, './../lib/zindex_of_truthy.native.js' ) ); +var opts = { + 'skip': ( zindexOfTruthy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zindexOfTruthy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the index of the first truthy element', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, + 1.0, + 0.0, + 0.0, + 2.0, + 2.0, + 3.0, + 3.0, + 0.0, + 0.0 + ]); + + // Nonnegative stride... + actual = zindexOfTruthy( x.length, x, 1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, 2 ); + t.strictEqual( actual, 2, 'returns expected value' ); + + // Negative stride... + actual = zindexOfTruthy( x.length, x, -1 ); + t.strictEqual( actual, 1, 'returns expected value' ); + + actual = zindexOfTruthy( 3, x, -2 ); + t.strictEqual( actual, 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function ignores falsy elements (e.g., `0+0i`, `NaN+NaNi`, `NaN+0i`)', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + NaN, + NaN, + NaN, + 0.0, + 1.0, + 1.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1 ); + t.strictEqual( actual, 3, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if unable to find a truthy element', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + actual = zindexOfTruthy( x.length, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { + var actual; + var x; + + x = new Complex128Array([ + 1.0, + 1.0, + 0.0, + 0.0, + 3.0, + 4.0 + ]); + + actual = zindexOfTruthy( 0, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + actual = zindexOfTruthy( -1, x, 1 ); + t.strictEqual( actual, -1, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.js index 0eb5b8ff7ae2..b6f279af74fe 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.js @@ -82,7 +82,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.native.js index 9e22df7a1785..634a3fb84ff9 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.ndarray.native.js @@ -91,7 +91,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided an `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if provided an `N` parameter which is less than or equal to zero', opts, function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.js index 26c9ba3d1192..fe9c74819ec2 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.js +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.js @@ -82,7 +82,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.native.js b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.native.js index b3aaf73c4418..4c63ec4ef34c 100644 --- a/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.native.js +++ b/lib/node_modules/@stdlib/blas/ext/base/zindex-of/test/test.zindex_of.native.js @@ -91,7 +91,7 @@ tape( 'the function returns the first index of an element which equals a provide t.end(); }); -tape( 'the function returns `-1` if provided `N` parameter is less than or equal to zero', opts, function test( t ) { +tape( 'the function returns `-1` if a provided `N` parameter is less than or equal to zero', opts, function test( t ) { var actual; var x; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/README.md b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/README.md new file mode 100644 index 000000000000..85ed30163719 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/README.md @@ -0,0 +1,327 @@ + + +# zreplicate + +> Replicate each element in a double-precision complex floating-point strided array a specified number of times. + +
+ +
+ + + +
+ +## Usage + +```javascript +var zreplicate = require( '@stdlib/blas/ext/base/zreplicate' ); +``` + +#### zreplicate( N, k, x, strideX, out, strideOut ) + +Replicates each element in a double-precision complex floating-point strided array a specified number of times. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var out = new Complex128Array( 4 ); + +zreplicate( x.length, 2, x, 1, out, 1 ); +// out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **k**: number of times to replicate each element. +- **x**: input [`Complex128Array`][@stdlib/array/complex128]. +- **strideX**: stride length for `x`. +- **out**: output [`Complex128Array`][@stdlib/array/complex128]. +- **strideOut**: stride length for `out`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to replicate every other element: + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out = new Complex128Array( 4 ); + +zreplicate( 2, 2, x, 2, out, 1 ); +// out => [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +// Initial arrays... +var x0 = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var out0 = new Complex128Array( 3 ); + +// Create offset views... +var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var out1 = new Complex128Array( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); // start at 2nd element + +zreplicate( 1, 2, x1, 2, out1, 1 ); +// out0 => [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0 ] +``` + +#### zreplicate.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + +Replicates each element in a double-precision complex floating-point strided array a specified number of times using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var out = new Complex128Array( 4 ); + +zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +// out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetOut**: starting index for `out`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to replicate every element starting from the second element and to store in the last `N*k` elements of the output array starting from the last element: + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); +var out = new Complex128Array( 2 ); + +zreplicate.ndarray( 1, 2, x, 1, 1, out, 1, 0 ); +// out => [ 3.0, 4.0, 3.0, 4.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0` or `k <= 0`, both functions return `out` unchanged. +- Both functions assume that the output array supports `N*k` indexed elements. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zreplicate = require( '@stdlib/blas/ext/base/zreplicate' ); + +var xbuf = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +console.log( x ); + +var out = new Complex128Array( x.length * 5 ); +console.log( out ); + +zreplicate( x.length, 5, x, 1, out, 1 ); +console.log( out ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/zreplicate.h" +``` + +#### stdlib_strided_zreplicate( N, k, \*X, strideX, \*Out, strideOut ) + +Replicates each element in a double-precision complex floating-point strided array a specified number of times. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_zreplicate( 2, 2, (stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)out, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Out**: `[out] stdlib_complex128_t*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. + +```c +void stdlib_strided_zreplicate( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *Out, const CBLAS_INT strideOut ); +``` + + + +#### stdlib_strided_zreplicate_ndarray( N, k, \*X, strideX, offsetX, \*Out, strideOut, offsetOut ) + + + +Replicates each element in a double-precision complex floating-point strided array a specified number of times using alternative indexing semantics. + +```c +const double x[] = { 1.0, 2.0, 3.0, 4.0 }; +double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + +stdlib_strided_zreplicate_ndarray( 2, 2, (stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)out, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **k**: `[in] CBLAS_INT` number of times to replicate each element. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Out**: `[out] stdlib_complex128_t*` output array. +- **strideOut**: `[in] CBLAS_INT` stride length for `Out`. +- **offsetOut**: `[in] CBLAS_INT` starting index for `Out`. + +```c +void stdlib_strided_zreplicate_ndarray( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/zreplicate.h" +#include "stdlib/complex/float64/ctor.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 2; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify strides: + const int strideX = 1; + const int strideOut = 1; + + // Replicate each element: + stdlib_strided_zreplicate( N, k, (stdlib_complex128_t *)x, strideX, (stdlib_complex128_t *)out, strideOut ); + + // Print the results: + for ( int i = 0; i < 8; i++ ) { + printf( "out[ %i ] = %lf\n", i, out[ i ] ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.js new file mode 100644 index 000000000000..e78f5e4dbef0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zreplicate = require( './../lib/zreplicate.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float64Array( len * 4 ); + x = new Complex128Array( xbuf.buffer ); + out = new Complex128Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + zreplicate( x.length, 2, x, 1, out, 1 ); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.native.js new file mode 100644 index 000000000000..e516e3bb4729 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.native.js @@ -0,0 +1,119 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zreplicate = tryRequire( resolve( __dirname, './../lib/zreplicate.native.js' ) ); +var opts = { + 'skip': ( zreplicate instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float64Array( len * 4 ); + x = new Complex128Array( xbuf.buffer ); + out = new Complex128Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + zreplicate( x.length, 2, x, 1, out, 1 ); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..d900c4badf48 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.ndarray.js @@ -0,0 +1,114 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zreplicate = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float64Array( len * 4 ); + x = new Complex128Array( xbuf.buffer ); + out = new Complex128Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + zreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..410076abcfd3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,119 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zreplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zreplicate instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var obuf; + var xbuf; + var out; + var x; + + xbuf = uniform( len * 2, -100.0, 100.0, options ); + obuf = new Float64Array( len * 4 ); + x = new Complex128Array( xbuf.buffer ); + out = new Complex128Array( obuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + xbuf[ 0 ] += 1.0; + zreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( obuf[ i % ( len * 4 ) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..bffeba2e1dad --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/benchmark/c/benchmark.length.c @@ -0,0 +1,206 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zreplicate.h" +#include "stdlib/complex/float64/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "zreplicate" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [0,1). +* +* @return random number +*/ +static double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length (number of complex elements) +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *out; + double *x; + double t; + int i; + + x = (double *) malloc( len * 2 * sizeof( double ) ); + out = (double *) malloc( len * 4 * sizeof( double ) ); + for ( i = 0; i < len * 2; i++ ) { + x[ i ] = ( rand_double()*99.0 ) + 1.0; + } + for ( i = 0; i < len * 4; i++ ) { + out[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_zreplicate( len, 2, (stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)out, 1 ); + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length (number of complex elements) +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *out; + double *x; + double t; + int i; + + x = (double *) malloc( len * 2 * sizeof( double ) ); + out = (double *) malloc( len * 4 * sizeof( double ) ); + for ( i = 0; i < len * 2; i++ ) { + x[ i ] = ( rand_double()*99.0 ) + 1.0; + } + for ( i = 0; i < len * 4; i++ ) { + out[ i ] = 0.0; + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + x[ 0 ] += 1.0; + stdlib_strided_zreplicate_ndarray( len, 2, (stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)out, 1, 0 ); + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + break; + } + } + elapsed = tic() - t; + if ( out[ 0 ] != x[ 0 ] ) { + printf( "unexpected result\n" ); + } + free( x ); + free( out ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/repl.txt new file mode 100644 index 000000000000..612f871351b5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/repl.txt @@ -0,0 +1,118 @@ + +{{alias}}( N, k, x, strideX, out, strideOut ) + Replicates each element in a double-precision complex floating-point strided + array a specified number of times. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use a typed + array view. + + If `N <= 0` or `k <= 0`, the function returns `out` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + out: Complex128Array + Output array. + + strideOut: integer + Stride length for `out`. + + Returns + ------- + out: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var out = new {{alias:@stdlib/array/complex128}}( 4 ); + > {{alias}}( x.length, 2, x, 1, out, 1 ) + [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] + + // Using `N` and stride parameters: + > x = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > out = new {{alias:@stdlib/array/complex128}}( 4 ); + > {{alias}}( 2, 2, x, 2, out, 1 ) + [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0 ] + + // Using view offsets: + > var x0 = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + > var out0 = new {{alias:@stdlib/array/complex128}}( 3 ); + > var x1 = new {{alias:@stdlib/array/complex128}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + > var out1 = new {{alias:@stdlib/array/complex128}}( out0.buffer, out0.BYTES_PER_ELEMENT*1 ); + > {{alias}}( 1, 2, x1, 2, out1, 1 ) + [ 3.0, 4.0, 3.0, 4.0 ] + > out0 + [ 0.0, 0.0, 3.0, 4.0, 3.0, 4.0 ] + + +{{alias}}.ndarray( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) + Replicates each element in a double-precision complex floating-point strided + array a specified number of times using alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + k: integer + Number of times to replicate each element. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + out: Complex128Array + Output array. + + strideOut: integer + Stride length for `out`. + + offsetOut: integer + Starting index for `out`. + + Returns + ------- + out: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var x = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > var out = new {{alias:@stdlib/array/complex128}}( 4 ); + > {{alias}}.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ) + [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0 ] + + // Advanced indexing: + > x = new {{alias:@stdlib/array/complex128}}( [ 1.0, 2.0, 3.0, 4.0 ] ); + > out = new {{alias:@stdlib/array/complex128}}( 2 ); + > {{alias}}.ndarray( 1, 2, x, 1, 1, out, 1, 0 ) + [ 3.0, 4.0, 3.0, 4.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/types/index.d.ts new file mode 100644 index 000000000000..8f1f80a2fa4c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/types/index.d.ts @@ -0,0 +1,110 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/// + +// TypeScript Version: 4.1 + +import { Complex128Array } from '@stdlib/types/array'; + +/** +* Interface describing `zreplicate`. +*/ +interface Routine { + /** + * Replicates each element in a double-precision complex floating-point strided array a specified number of times. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex128Array( 6 ); + * + * zreplicate( x.length, 2, x, 1, out, 1 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + */ + ( N: number, k: number, x: Complex128Array, strideX: number, out: Complex128Array, strideOut: number ): Complex128Array; + + /** + * Replicates each element in a double-precision complex floating-point strided array a specified number of times using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param k - number of times to replicate each element + * @param x - input array + * @param strideX - stride length for `x` + * @param offsetX - starting index for `x` + * @param out - output array + * @param strideOut - stride length for `out` + * @param offsetOut - starting index for `out` + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var out = new Complex128Array( 6 ); + * + * zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); + * // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] + */ + ndarray( N: number, k: number, x: Complex128Array, strideX: number, offsetX: number, out: Complex128Array, strideOut: number, offsetOut: number ): Complex128Array; +} + +/** +* Replicates each element in a double-precision complex floating-point strided array a specified number of times. +* +* @param N - number of indexed elements +* @param k - number of times to replicate each element +* @param x - input array +* @param strideX - stride length for `x` +* @param out - output array +* @param strideOut - stride length for `out` +* @returns output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex128Array( 6 ); +* +* zreplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex128Array( 6 ); +* +* zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +declare var zreplicate: Routine; + + +// EXPORTS // + +export = zreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/types/test.ts new file mode 100644 index 000000000000..0e59f79ba91d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/docs/types/test.ts @@ -0,0 +1,281 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import zreplicate = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate( x.length, 2, x, 1, out, 1 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate( '10', 2, x, 1, out, 1 ); // $ExpectError + zreplicate( true, 2, x, 1, out, 1 ); // $ExpectError + zreplicate( false, 2, x, 1, out, 1 ); // $ExpectError + zreplicate( null, 2, x, 1, out, 1 ); // $ExpectError + zreplicate( undefined, 2, x, 1, out, 1 ); // $ExpectError + zreplicate( [], 2, x, 1, out, 1 ); // $ExpectError + zreplicate( {}, 2, x, 1, out, 1 ); // $ExpectError + zreplicate( ( x: number ): number => x, 2, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate( x.length, '10', x, 1, out, 1 ); // $ExpectError + zreplicate( x.length, true, x, 1, out, 1 ); // $ExpectError + zreplicate( x.length, false, x, 1, out, 1 ); // $ExpectError + zreplicate( x.length, null, x, 1, out, 1 ); // $ExpectError + zreplicate( x.length, undefined, x, 1, out, 1 ); // $ExpectError + zreplicate( x.length, [], x, 1, out, 1 ); // $ExpectError + zreplicate( x.length, {}, x, 1, out, 1 ); // $ExpectError + zreplicate( x.length, ( x: number ): number => x, x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate( x.length, 2, 10, 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, '10', 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, true, 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, false, 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, null, 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, undefined, 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, [ '1' ], 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, {}, 1, out, 1 ); // $ExpectError + zreplicate( x.length, 2, ( x: number ): number => x, 1, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate( x.length, 2, x, '10', out, 1 ); // $ExpectError + zreplicate( x.length, 2, x, true, out, 1 ); // $ExpectError + zreplicate( x.length, 2, x, false, out, 1 ); // $ExpectError + zreplicate( x.length, 2, x, null, out, 1 ); // $ExpectError + zreplicate( x.length, 2, x, undefined, out, 1 ); // $ExpectError + zreplicate( x.length, 2, x, [], out, 1 ); // $ExpectError + zreplicate( x.length, 2, x, {}, out, 1 ); // $ExpectError + zreplicate( x.length, 2, x, ( x: number ): number => x, out, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + + zreplicate( x.length, 2, x, 1, 10, 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, '10', 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, true, 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, false, 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, null, 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, undefined, 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, [ '1' ], 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, {}, 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate( x.length, 2, x, 1, out, '10' ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, true ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, false ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, null ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, undefined ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, [] ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, {} ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate(); // $ExpectError + zreplicate( x.length ); // $ExpectError + zreplicate( x.length, 2 ); // $ExpectError + zreplicate( x.length, 2, x ); // $ExpectError + zreplicate( x.length, 2, x, 1 ); // $ExpectError + zreplicate( x.length, 2, x, 1, out ); // $ExpectError + zreplicate( x.length, 2, x, 1, out, 1, {} ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( '10', 2, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( true, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( false, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( null, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( undefined, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( [], 2, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( {}, 2, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( ( x: number ): number => x, 2, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( x.length, '10', x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, true, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, false, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, null, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, undefined, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, [], x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, {}, x, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, ( x: number ): number => x, x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( x.length, 2, 10, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, '10', 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, true, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, false, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, null, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, undefined, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, [ '1' ], 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, {}, 1, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, ( x: number ): number => x, 1, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( x.length, 2, x, '10', 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, true, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, false, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, null, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, undefined, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, [], 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, {}, 0, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, ( x: number ): number => x, 0, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( x.length, 2, x, 1, '10', out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, true, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, false, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, null, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, undefined, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, [], out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, {}, out, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + + zreplicate.ndarray( x.length, 2, x, 1, 0, 10, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, '10', 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, true, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, false, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, null, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, undefined, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, {}, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( x.length, 2, x, 1, 0, out, '10', 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, true, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, false, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, null, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, undefined, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, [], 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, {}, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, '10' ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, true ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, false ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, null ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, undefined ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, [] ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, {} ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const out = new Complex128Array( 20 ); + + zreplicate.ndarray(); // $ExpectError + zreplicate.ndarray( x.length ); // $ExpectError + zreplicate.ndarray( x.length, 2 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1 ); // $ExpectError + zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/c/example.c new file mode 100644 index 000000000000..201a96e25852 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/c/example.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zreplicate.h" +#include "stdlib/complex/float64/ctor.h" +#include + +int main( void ) { + // Create strided arrays: + const double x[] = { 1.0, 2.0, 3.0, 4.0 }; + double out[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; + + // Specify the number of indexed elements: + const int N = 2; + + // Specify the number of times to replicate each element: + const int k = 2; + + // Specify strides: + const int strideX = 1; + const int strideOut = 1; + + // Replicate each element: + stdlib_strided_zreplicate( N, k, (stdlib_complex128_t *)x, strideX, (stdlib_complex128_t *)out, strideOut ); + + // Print the results: + for ( int i = 0; i < 8; i++ ) { + printf( "out[ %i ] = %lf\n", i, out[ i ] ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/index.js new file mode 100644 index 000000000000..54202dd0234c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var zreplicate = require( './../lib' ); + +var xbuf = discreteUniform( 10, -100, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +console.log( x ); + +var out = new Complex128Array( x.length * 5 ); +console.log( out ); + +zreplicate( x.length, 5, x, 1, out, 1 ); +console.log( out ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var zreplicate = require( '@stdlib/blas/ext/base/zreplicate' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex128Array( 6 ); +* +* zreplicate.ndarray( x.length, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zreplicate; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zreplicate = main; +} else { + zreplicate = tmp; +} + + +// EXPORTS // + +module.exports = zreplicate; + +// exports: { "ndarray": "zreplicate.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/main.js new file mode 100644 index 000000000000..72ca8ad67d6a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zreplicate = require( './zreplicate.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zreplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/native.js new file mode 100644 index 000000000000..fd6b6d6dfa38 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zreplicate = require( './zreplicate.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( zreplicate, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/ndarray.js new file mode 100644 index 000000000000..681eed3bacfc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/ndarray.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); + + +// MAIN // + +/** +* Replicates each element in a double-precision complex floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Complex128Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Complex128Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex128Array( 6 ); +* +* zreplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function zreplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var viewX; + var viewO; + var re; + var im; + var ix; + var io; + var i; + var j; + + if ( N <= 0 || k <= 0 ) { + return out; + } + viewX = reinterpret( x, 0 ); + viewO = reinterpret( out, 0 ); + ix = offsetX * 2; + io = offsetOut * 2; + strideX *= 2; + strideOut *= 2; + for ( i = 0; i < N; i++ ) { + re = viewX[ ix ]; + im = viewX[ ix+1 ]; + for ( j = 0; j < k; j++ ) { + viewO[ io ] = re; + viewO[ io+1 ] = im; + io += strideOut; + } + ix += strideX; + } + return out; +} + + +// EXPORTS // + +module.exports = zreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/ndarray.native.js new file mode 100644 index 000000000000..09aaa5423b33 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/ndarray.native.js @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each element in a double-precision complex floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Complex128Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {NonNegativeInteger} offsetX - starting index for `x` +* @param {Complex128Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @param {NonNegativeInteger} offsetOut - starting index for `out` +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex128Array( 6 ); +* +* zreplicate( 3, 2, x, 1, 0, out, 1, 0 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function zreplicate( N, k, x, strideX, offsetX, out, strideOut, offsetOut ) { + var viewOut; + var viewX; + + viewX = reinterpret( x, 0 ); + viewOut = reinterpret( out, 0 ); + addon.ndarray( N, k, viewX, strideX, offsetX, viewOut, strideOut, offsetOut ); + return out; +} + + +// EXPORTS // + +module.exports = zreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/zreplicate.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/zreplicate.js new file mode 100644 index 000000000000..dc7eb79db2f0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/zreplicate.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Replicates each element in a double-precision complex floating-point strided array a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Complex128Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {Complex128Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex128Array( 6 ); +* +* zreplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function zreplicate( N, k, x, strideX, out, strideOut ) { + var ox = stride2offset( N, strideX ); + var oo = stride2offset( N * k, strideOut ); + return ndarray( N, k, x, strideX, ox, out, strideOut, oo ); +} + + +// EXPORTS // + +module.exports = zreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/zreplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/zreplicate.native.js new file mode 100644 index 000000000000..36439a0f3db4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/lib/zreplicate.native.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Replicates each element in a double-precision complex floating-point strided array a specified number of times. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {PositiveInteger} k - number of times to replicate each element +* @param {Complex128Array} x - input array +* @param {integer} strideX - stride length for `x` +* @param {Complex128Array} out - output array +* @param {integer} strideOut - stride length for `out` +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var out = new Complex128Array( 6 ); +* +* zreplicate( x.length, 2, x, 1, out, 1 ); +* // out => [ 1.0, 2.0, 1.0, 2.0, 3.0, 4.0, 3.0, 4.0, 5.0, 6.0, 5.0, 6.0 ] +*/ +function zreplicate( N, k, x, strideX, out, strideOut ) { + var viewOut; + var viewX; + + viewX = reinterpret( x, 0 ); + viewOut = reinterpret( out, 0 ); + addon( N, k, viewX, strideX, viewOut, strideOut ); + return out; +} + + +// EXPORTS // + +module.exports = zreplicate; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/manifest.json new file mode 100644 index 000000000000..9a85237683e2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/manifest.json @@ -0,0 +1,81 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-complex128array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/package.json b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/package.json new file mode 100644 index 000000000000..90038b41e072 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/package.json @@ -0,0 +1,77 @@ +{ + "name": "@stdlib/blas/ext/base/zreplicate", + "version": "0.0.0", + "description": "Replicate each element in a double-precision complex floating-point strided array a specified number of times.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "replicate", + "repeat", + "copy", + "strided", + "array", + "ndarray", + "complex", + "complex128", + "complex128array", + "double-precision", + "zreplicate" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/addon.c new file mode 100644 index 000000000000..3e69470a517a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/addon.c @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zreplicate.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex128array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, Out, N * k, strideOut, argv, 4 ); + API_SUFFIX(stdlib_strided_zreplicate)( N, k, (stdlib_complex128_t *)X, strideX, (stdlib_complex128_t *)Out, strideOut ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, k, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideOut, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetOut, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, Out, N * k, strideOut, argv, 5 ); + API_SUFFIX(stdlib_strided_zreplicate_ndarray)( N, k, (stdlib_complex128_t *)X, strideX, offsetX, (stdlib_complex128_t *)Out, strideOut, offsetOut ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/main.c new file mode 100644 index 000000000000..08c2d23da97a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/src/main.c @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zreplicate.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/strided/base/stride2offset.h" +#include "stdlib/blas/base/shared.h" + +/** +* Replicates each element in a double-precision complex floating-point strided array a specified number of times. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param Out output array +* @param strideOut stride length for Out +*/ +void API_SUFFIX(stdlib_strided_zreplicate)( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *Out, const CBLAS_INT strideOut ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oo = stdlib_strided_stride2offset( N * k, strideOut ); + API_SUFFIX(stdlib_strided_zreplicate_ndarray)( N, k, X, strideX, ox, Out, strideOut, oo ); +} + +/** +* Replicates each element in a double-precision complex floating-point strided array a specified number of times using alternative indexing semantics. +* +* @param N number of indexed elements +* @param k number of times to replicate each element +* @param X input array +* @param strideX stride length for X +* @param offsetX starting index for X +* @param Out output array +* @param strideOut stride length for Out +* @param offsetOut starting index for Out +*/ +void API_SUFFIX(stdlib_strided_zreplicate_ndarray)( const CBLAS_INT N, const CBLAS_INT k, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *Out, const CBLAS_INT strideOut, const CBLAS_INT offsetOut ) { + stdlib_complex128_t v; + CBLAS_INT ix; + CBLAS_INT io; + CBLAS_INT i; + CBLAS_INT j; + + if ( N <= 0 || k <= 0 ) { + return; + } + ix = offsetX; + io = offsetOut; + for ( i = 0; i < N; i++ ) { + v = X[ ix ]; + for ( j = 0; j < k; j++ ) { + Out[ io ] = v; + io += strideOut; + } + ix += strideX; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.js new file mode 100644 index 000000000000..9d12db205cf3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var zreplicate = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zreplicate.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zreplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zreplicate, mock, 'returns expected value' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zreplicate; + var main; + + main = require( './../lib/zreplicate.js' ); + + zreplicate = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zreplicate, main, 'returns expected value' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.ndarray.js new file mode 100644 index 000000000000..c2d0ca59b432 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.ndarray.js @@ -0,0 +1,538 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var zreplicate = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( zreplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 3 ); + + zreplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 5.0, 6.0 ] ); + out = new Complex128Array( 3 ); + + zreplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 5.0, + 6.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + v = zreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 5.0, + 6.0, + 5.0, + 6.0, + 9.0, + 10.0, + 9.0, + 10.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 12 ); + + zreplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, -2, 4, out, 1, 0 ); + + expected = new Complex128Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 7.0, + 8.0 + ]); + out = new Complex128Array( 8 ); + + zreplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0, + 7.0, + 8.0, + 7.0, + 8.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Complex128Array([ + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Complex128Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.ndarray.native.js new file mode 100644 index 000000000000..126239aa0fee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.ndarray.native.js @@ -0,0 +1,547 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); + + +// VARIABLES // + +var zreplicate = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zreplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( zreplicate.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 3 ); + + zreplicate( x.length, 1, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 5.0, 6.0 ] ); + out = new Complex128Array( 3 ); + + zreplicate( 1, 3, x, 1, 0, out, 1, 0 ); + expected = new Complex128Array([ + 5.0, + 6.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + v = zreplicate( x.length, 2, x, 1, 0, out, 1, 0 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( -1, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( 0, 2, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( x.length, -1, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( x.length, 0, x, 1, 0, out, 1, 0 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 2, 0, out, 1, 0 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 5.0, + 6.0, + 5.0, + 6.0, + 9.0, + 10.0, + 9.0, + 10.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 12 ); + + zreplicate( 3, 2, x, 1, 0, out, 2, 0 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, -2, 4, out, 1, 0 ); + + expected = new Complex128Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 7.0, + 8.0 + ]); + out = new Complex128Array( 8 ); + + zreplicate( 4, 2, x, 2, 1, out, 1, 0 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0, + 7.0, + 8.0, + 7.0, + 8.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output offset', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 1, 0, out, 1, 2 ); + + expected = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a zero `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 0, 1, out, 1, 0 ); + + expected = new Complex128Array([ + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( 3, 2, x, 2, 0, out, -1, 5 ); + + expected = new Complex128Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.zreplicate.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.zreplicate.js new file mode 100644 index 000000000000..3eb76229fa8e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.zreplicate.js @@ -0,0 +1,501 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var zreplicate = require( './../lib/zreplicate.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( zreplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 2, x, 1, out, 1 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 3, x, 1, out, 1 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 3 ); + + zreplicate( x.length, 1, x, 1, out, 1 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 5.0, 6.0 ] ); + out = new Complex128Array( 3 ); + + zreplicate( 1, 3, x, 1, out, 1 ); + expected = new Complex128Array( [ 5.0, 6.0, 5.0, 6.0, 5.0, 6.0 ] ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var v; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + v = zreplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( -1, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( 0, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( x.length, -1, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( x.length, 0, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, 2, out, 1 ); + + expected = new Complex128Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, 1, out, 2 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, -2, out, -1 ); + + expected = new Complex128Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, 2, out, -1 ); + + expected = new Complex128Array([ + 9.0, + 10.0, + 9.0, + 10.0, + 5.0, + 6.0, + 5.0, + 6.0, + 1.0, + 2.0, + 1.0, + 2.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0 + ]); + out0 = new Complex128Array( 9 ); + + // Create offset views... + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Complex128Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + zreplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 3.0, + 4.0, + 3.0, + 4.0, + 7.0, + 8.0, + 7.0, + 8.0, + 11.0, + 12.0, + 11.0, + 12.0 + ]); + + t.strictEqual( isSameComplex128Array( out0, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.zreplicate.native.js b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.zreplicate.native.js new file mode 100644 index 000000000000..2eaaa6121fcb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zreplicate/test/test.zreplicate.native.js @@ -0,0 +1,497 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); + + +// VARIABLES // + +var zreplicate = tryRequire( resolve( __dirname, './../lib/zreplicate.native.js' ) ); +var opts = { + 'skip': ( zreplicate instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zreplicate, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( zreplicate.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function replicates each strided array element', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 2, x, 1, out, 1 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 5.0, + 6.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0 + ]); + out = new Complex128Array( 6 ); + + zreplicate( x.length, 3, x, 1, out, 1 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 1.0, + 2.0, + 1.0, + 2.0, + 3.0, + 4.0, + 3.0, + 4.0, + 3.0, + 4.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (k=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array( 3 ); + + zreplicate( x.length, 1, x, 1, out, 1 ); + expected = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function replicates each strided array element (N=1)', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 5.0, 6.0 ] ); + out = new Complex128Array( 3 ); + + zreplicate( 1, 3, x, 1, out, 1 ); + expected = new Complex128Array( [ 5.0, 6.0, 5.0, 6.0, 5.0, 6.0 ] ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var v; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array( 6 ); + + v = zreplicate( x.length, 2, x, 1, out, 1 ); + + t.strictEqual( v, out, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( -1, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( 0, 2, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `k` parameter less than or equal to `0`, the function returns the output array unchanged', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + out = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + expected = new Complex128Array([ + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0, + 13.0, + 14.0, + 15.0, + 16.0, + 17.0 + ]); + + zreplicate( x.length, -1, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + zreplicate( x.length, 0, x, 1, out, 1 ); + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, 2, out, 1 ); + + expected = new Complex128Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an output stride', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, 1, out, 2 ); + + expected = new Complex128Array([ + 1.0, + 2.0, + 0.0, + 0.0, + 1.0, + 2.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 3.0, + 4.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0, + 5.0, + 6.0, + 0.0, + 0.0 + ]); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, -2, out, -1 ); + + expected = new Complex128Array( [ 1.0, 2.0, 1.0, 2.0, 5.0, 6.0, 5.0, 6.0, 9.0, 10.0, 9.0, 10.0 ] ); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var out; + var x; + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0 + ]); + out = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + zreplicate( 3, 2, x, 2, out, -1 ); + + expected = new Complex128Array( [ 9.0, 10.0, 9.0, 10.0, 5.0, 6.0, 5.0, 6.0, 1.0, 2.0, 1.0, 2.0 ] ); + + t.strictEqual( isSameComplex128Array( out, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var out0; + var out1; + var x0; + var x1; + + // Initial arrays... + x0 = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0, + 7.0, + 8.0, + 9.0, + 10.0, + 11.0, + 12.0 + ]); + out0 = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + + // Create offset views... + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element + out1 = new Complex128Array( out0.buffer, out0.BYTES_PER_ELEMENT*3 ); // begin at 4th element + + zreplicate( 3, 2, x1, 2, out1, 1 ); + expected = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 3.0, 4.0, 3.0, 4.0, 7.0, 8.0, 7.0, 8.0, 11.0, 12.0, 11.0, 12.0 ] ); + + t.strictEqual( isSameComplex128Array( out0, expected ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/README.md b/lib/node_modules/@stdlib/blas/ext/base/zwax/README.md new file mode 100644 index 000000000000..44915528b9ee --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/README.md @@ -0,0 +1,374 @@ + + +# zwax + +> Multiply each element in a double-precision complex floating-point strided array `x` by a scalar constant and assign the results to elements in a double-precision complex floating-point strided array `w`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{w} = \alpha \cdot \mathbf{x} +``` + + + +This API is complementary to the package [`@stdlib/blas/base/zscal`][@stdlib/blas/base/zscal], which performs an in-place update. + +
+ + + +
+ +## Usage + +```javascript +var zwax = require( '@stdlib/blas/ext/base/zwax' ); +``` + +#### zwax( N, alpha, x, strideX, w, strideW ) + +Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w`. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var alpha = new Complex128( 5.0, 3.0 ); + +zwax( x.length, alpha, x, 1, w, 1 ); +// w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **alpha**: scalar constant. +- **x**: input [`Complex128Array`][@stdlib/array/complex128]. +- **strideX**: stride length for `x`. +- **w**: output [`Complex128Array`][@stdlib/array/complex128]. +- **strideW**: stride length for `w`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other element in `x` by `alpha` and assign the results to every other element in `w`: + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +var alpha = new Complex128( 5.0, 3.0 ); + +zwax( 2, alpha, x, 2, w, 2 ); +// w => [ -1.0, 13.0, 0.0, 0.0, 7.0, 45.0, 0.0, 0.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); + +// Initial arrays... +var x0 = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var w0 = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +// Create offset views... +var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var w1 = new Complex128Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +var alpha = new Complex128( 5.0, 3.0 ); + +zwax( 3, alpha, x1, 1, w1, 1 ); +// w0 => [ 0.0, 0.0, 0.0, 0.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +``` + +#### zwax.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + +Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w` using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +var alpha = new Complex128( 5.0, 3.0 ); + +zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); +// w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetW**: starting index for `w`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to multiply the last three elements of `x` by `alpha` and assign the results to the last three elements of `w`: + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + +var alpha = new Complex128( 5.0, 3.0 ); + +zwax.ndarray( 3, alpha, x, 1, x.length-3, w, 1, w.length-3 ); +// w => [ 0.0, 0.0, 0.0, 0.0, 7.0, 45.0, 11.0, 61.0, 15.0, 77.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `w` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var logEach = require( '@stdlib/console/log-each' ); +var zwax = require( '@stdlib/blas/ext/base/zwax' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var wbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +var w = new Complex128Array( wbuf.buffer ); +var alpha = new Complex128( 5.0, 3.0 ); + +zwax( x.length, alpha, x, 1, w, 1 ); +logEach( '%s', w ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/zwax.h" +``` + +#### stdlib_strided_zwax( N, alpha, \*X, strideX, \*W, strideW ) + +Multiplies each element in a double-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `W`. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; +double w[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; +const stdlib_complex128_t alpha = stdlib_complex128( 5.0, 3.0 ); + +stdlib_strided_zwax( 4, alpha, (const stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)w, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] stdlib_complex128_t` scalar constant. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **W**: `[out] stdlib_complex128_t*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. + +```c +void stdlib_strided_zwax( const CBLAS_INT N, const stdlib_complex128_t alpha, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *W, const CBLAS_INT strideW ); +``` + + + +#### stdlib_strided_zwax_ndarray( N, alpha, \*X, strideX, offsetX, \*W, strideW, offsetW ) + + + +Multiplies each element in a double-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `W` using alternative indexing semantics. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 }; +double w[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 }; +const stdlib_complex128_t alpha = stdlib_complex128( 5.0, 3.0 ); + +stdlib_strided_zwax_ndarray( 4, alpha, (const stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)w, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **alpha**: `[in] stdlib_complex128_t` scalar constant. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **W**: `[out] stdlib_complex128_t*` output array. +- **strideW**: `[in] CBLAS_INT` stride length for `W`. +- **offsetW**: `[in] CBLAS_INT` starting index for `W`. + +```c +void stdlib_strided_zwax_ndarray( const CBLAS_INT N, const stdlib_complex128_t alpha, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/zwax.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex128_t x[] = { + stdlib_complex128( 1.0, 2.0 ), + stdlib_complex128( 3.0, 4.0 ), + stdlib_complex128( 5.0, 6.0 ), + stdlib_complex128( 7.0, 8.0 ) + }; + stdlib_complex128_t w[] = { + stdlib_complex128( 0.0, 0.0 ), + stdlib_complex128( 0.0, 0.0 ), + stdlib_complex128( 0.0, 0.0 ), + stdlib_complex128( 0.0, 0.0 ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Define a scalar constant: + stdlib_complex128_t alpha = stdlib_complex128( 5.0, 3.0 ); + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_zwax( N, alpha, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "w[ %i ] = %lf + %lfi\n", i, stdlib_complex128_real( w[ i ] ), stdlib_complex128_imag( w[ i ] ) ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +[@stdlib/blas/base/zscal]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/zscal + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.js new file mode 100644 index 000000000000..420446959251 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.js @@ -0,0 +1,116 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zwax = require( './../lib/zwax.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex128Array( xbuf.buffer ); + w = new Complex128Array( wbuf.buffer ); + + alpha = new Complex128( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zwax( x.length, alpha, x, 1, w, 1 ); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.native.js new file mode 100644 index 000000000000..b35e8da9c5bc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.native.js @@ -0,0 +1,121 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zwax = tryRequire( resolve( __dirname, './../lib/zwax.native.js' ) ); +var opts = { + 'skip': ( zwax instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex128Array( xbuf.buffer ); + w = new Complex128Array( wbuf.buffer ); + + alpha = new Complex128( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zwax( x.length, alpha, x, 1, w, 1 ); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..989fd7113e7f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.ndarray.js @@ -0,0 +1,116 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zwax = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex128Array( xbuf.buffer ); + w = new Complex128Array( wbuf.buffer ); + + alpha = new Complex128( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..1fe6e4aea31e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,121 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zwax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zwax instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var alpha; + var xbuf; + var wbuf; + var x; + var w; + + xbuf = uniform( len*2, -100.0, 100.0, options ); + wbuf = uniform( len*2, -100.0, 100.0, options ); + x = new Complex128Array( xbuf.buffer ); + w = new Complex128Array( wbuf.buffer ); + + alpha = new Complex128( 5.0, 3.0 ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( wbuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..af2aecd0daea --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/benchmark/c/benchmark.length.c @@ -0,0 +1,214 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zwax.h" +#include "stdlib/complex/float64/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "zwax" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + stdlib_complex128_t alpha; + double elapsed; + double *x; + double *w; + double t; + int i; + + x = (double *)malloc( len * 2 * sizeof( double ) ); + w = (double *)malloc( len * 2 * sizeof( double ) ); + + alpha = stdlib_complex128( 5.0, 3.0 ); + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + w[ i ] = random_uniform( -100.0, 100.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_zwax( len, alpha, (const stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)w, 1 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + stdlib_complex128_t alpha; + double elapsed; + double *x; + double *w; + double t; + int i; + + x = (double *)malloc( len * 2 * sizeof( double ) ); + w = (double *)malloc( len * 2 * sizeof( double ) ); + + alpha = stdlib_complex128( 5.0, 3.0 ); + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + w[ i ] = random_uniform( -100.0, 100.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_zwax_ndarray( len, alpha, (const stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)w, 1, 0 ); + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( w[ 0 ] != w[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( w ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/zwax/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/repl.txt new file mode 100644 index 000000000000..11762f5873c4 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/repl.txt @@ -0,0 +1,138 @@ + +{{alias}}( N, alpha, x, strideX, w, strideW ) + Multiplies each element in a double-precision complex floating-point strided + array `x` by a scalar constant and assigns the results to elements in a + double-precision complex floating-point strided array `w`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `w` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: Complex128 + Scalar constant. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + w: Complex128Array + Output array. + + strideW: integer + Stride length for `w`. + + Returns + ------- + w: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/complex128}}( bufX ); + > var w = new {{alias:@stdlib/array/complex128}}( bufW ); + > var alpha = new {{alias:@stdlib/complex/float64/ctor}}( 5.0, 3.0 ); + > {{alias}}( x.length, alpha, x, 1, w, 1 ) + [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] + + // Using `N` and stride parameters: + > bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]; + > x = new {{alias:@stdlib/array/complex128}}( bufX ); + > bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > w = new {{alias:@stdlib/array/complex128}}( bufW ); + > alpha = new {{alias:@stdlib/complex/float64/ctor}}( 5.0, 3.0 ); + > {{alias}}( 2, alpha, x, 2, w, 2 ) + [ -1.0, 13.0, 0.0, 0.0, 7.0, 45.0, 0.0, 0.0 ] + + // Using view offsets: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x0 = new {{alias:@stdlib/array/complex128}}( bufX ); + > var w0 = new {{alias:@stdlib/array/complex128}}( bufW ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetW = w0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/complex128}}( x0.buffer, offsetX ); + > var w1 = new {{alias:@stdlib/array/complex128}}( w0.buffer, offsetW ); + > alpha = new {{alias:@stdlib/complex/float64/ctor}}( 5.0, 3.0 ); + > {{alias}}( 3, alpha, x1, 1, w1, 1 ) + [ 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + > w0 + [ 0.0, 0.0, 0.0, 0.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + + +{{alias}}.ndarray( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) + Multiplies each element in a double-precision complex floating-point strided + array `x` by a scalar constant and assigns the results to elements in a + double-precision complex floating-point strided array `w` using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + alpha: Complex128 + Scalar constant. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + w: Complex128Array + Output array. + + strideW: integer + Stride length for `w`. + + offsetW: integer + Starting index for `w`. + + Returns + ------- + w: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > var x = new {{alias:@stdlib/array/complex128}}( bufX ); + > var w = new {{alias:@stdlib/array/complex128}}( bufW ); + > var alpha = new {{alias:@stdlib/complex/float64/ctor}}( 5.0, 3.0 ); + > {{alias}}.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ) + [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] + + // Using index offsets: + > bufX = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 4.0, 0.0, 5.0, 0.0 ]; + > x = new {{alias:@stdlib/array/complex128}}( bufX ); + > bufW = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]; + > w = new {{alias:@stdlib/array/complex128}}( bufW ); + > alpha = new {{alias:@stdlib/complex/float64/ctor}}( 2.0, 1.0 ); + > {{alias}}.ndarray( 3, alpha, x, 1, x.length-3, w, 1, w.length-3 ) + [ 0.0, 0.0, 0.0, 0.0, 6.0, 3.0, 8.0, 4.0, 10.0, 5.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/types/index.d.ts new file mode 100644 index 000000000000..915b31bd65c5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/types/index.d.ts @@ -0,0 +1,123 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex128Array } from '@stdlib/types/array'; +import { Complex128 } from '@stdlib/types/complex'; + +/** +* Interface describing `zwax`. +*/ +interface Routine { + /** + * Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w`. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param w - output array + * @param strideW - `w` stride length + * @returns `w` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Complex128 = require( '@stdlib/complex/float64/ctor' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex128( 5.0, 3.0 ); + * + * zwax( x.length, alpha, x, 1, w, 1 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + */ + ( N: number, alpha: Complex128, x: Complex128Array, strideX: number, w: Complex128Array, strideW: number ): Complex128Array; + + /** + * Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param alpha - scalar constant + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting index for `x` + * @param w - output array + * @param strideW - `w` stride length + * @param offsetW - starting index for `w` + * @returns `w` + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * var Complex128 = require( '@stdlib/complex/float64/ctor' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); + * var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + * + * var alpha = new Complex128( 5.0, 3.0 ); + * + * zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); + * // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] + */ + ndarray( N: number, alpha: Complex128, x: Complex128Array, strideX: number, offsetX: number, w: Complex128Array, strideW: number, offsetW: number ): Complex128Array; +} + +/** +* Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w`. +* +* @param N - number of indexed elements +* @param alpha - scalar constant +* @param x - input array +* @param strideX - `x` stride length +* @param w - output array +* @param strideW - `w` stride length +* @returns `w` +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* var alpha = new Complex128( 5.0, 3.0 ); +* +* zwax( x.length, alpha, x, 1, w, 1 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* var alpha = new Complex128( 5.0, 3.0 ); +* +* zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0, 11.0, 61.0 ] +*/ +declare var zwax: Routine; + + +// EXPORTS // + +export = zwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/types/test.ts new file mode 100644 index 000000000000..2eecc2e94283 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/docs/types/test.ts @@ -0,0 +1,298 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import Complex128 = require( '@stdlib/complex/float64/ctor' ); +import zwax = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax( x.length, alpha, x, 1, w, 1 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax( '10', alpha, x, 1, w, 1 ); // $ExpectError + zwax( true, alpha, x, 1, w, 1 ); // $ExpectError + zwax( false, alpha, x, 1, w, 1 ); // $ExpectError + zwax( null, alpha, x, 1, w, 1 ); // $ExpectError + zwax( undefined, alpha, x, 1, w, 1 ); // $ExpectError + zwax( [], alpha, x, 1, w, 1 ); // $ExpectError + zwax( {}, alpha, x, 1, w, 1 ); // $ExpectError + zwax( ( x: number ): number => x, alpha, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a complex-like... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + + zwax( x.length, 10, x, 1, w, 1 ); // $ExpectError + zwax( x.length, '10', x, 1, w, 1 ); // $ExpectError + zwax( x.length, true, x, 1, w, 1 ); // $ExpectError + zwax( x.length, false, x, 1, w, 1 ); // $ExpectError + zwax( x.length, null, x, 1, w, 1 ); // $ExpectError + zwax( x.length, undefined, x, 1, w, 1 ); // $ExpectError + zwax( x.length, [], x, 1, w, 1 ); // $ExpectError + zwax( x.length, {}, x, 1, w, 1 ); // $ExpectError + zwax( x.length, ( x: number ): number => x, x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a Complex128Array... +{ + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax( 10, alpha, 10, 1, w, 1 ); // $ExpectError + zwax( 10, alpha, '10', 1, w, 1 ); // $ExpectError + zwax( 10, alpha, true, 1, w, 1 ); // $ExpectError + zwax( 10, alpha, false, 1, w, 1 ); // $ExpectError + zwax( 10, alpha, null, 1, w, 1 ); // $ExpectError + zwax( 10, alpha, undefined, 1, w, 1 ); // $ExpectError + zwax( 10, alpha, [ '1' ], 1, w, 1 ); // $ExpectError + zwax( 10, alpha, {}, 1, w, 1 ); // $ExpectError + zwax( 10, alpha, ( x: number ): number => x, 1, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax( x.length, alpha, x, '10', w, 1 ); // $ExpectError + zwax( x.length, alpha, x, true, w, 1 ); // $ExpectError + zwax( x.length, alpha, x, false, w, 1 ); // $ExpectError + zwax( x.length, alpha, x, null, w, 1 ); // $ExpectError + zwax( x.length, alpha, x, undefined, w, 1 ); // $ExpectError + zwax( x.length, alpha, x, [], w, 1 ); // $ExpectError + zwax( x.length, alpha, x, {}, w, 1 ); // $ExpectError + zwax( x.length, alpha, x, ( x: number ): number => x, w, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax( x.length, alpha, x, 1, 10, 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, '10', 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, true, 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, false, 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, null, 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, undefined, 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, [ '1' ], 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, {}, 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a sixth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax( x.length, alpha, x, 1, w, '10' ); // $ExpectError + zwax( x.length, alpha, x, 1, w, true ); // $ExpectError + zwax( x.length, alpha, x, 1, w, false ); // $ExpectError + zwax( x.length, alpha, x, 1, w, null ); // $ExpectError + zwax( x.length, alpha, x, 1, w, undefined ); // $ExpectError + zwax( x.length, alpha, x, 1, w, [] ); // $ExpectError + zwax( x.length, alpha, x, 1, w, {} ); // $ExpectError + zwax( x.length, alpha, x, 1, w, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax(); // $ExpectError + zwax( x.length ); // $ExpectError + zwax( x.length, alpha ); // $ExpectError + zwax( x.length, alpha, x ); // $ExpectError + zwax( x.length, alpha, x, 1 ); // $ExpectError + zwax( x.length, alpha, x, 1, w ); // $ExpectError + zwax( x.length, alpha, x, 1, w, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( '10', alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( true, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( false, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( null, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( undefined, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( [], alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( {}, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( ( x: number ): number => x, alpha, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a complex-like... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + + zwax.ndarray( x.length, 10, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, '10', x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, true, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, false, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, null, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, undefined, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, [], x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, {}, x, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, ( x: number ): number => x, x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a Complex128Array... +{ + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( 10, alpha, 10, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, '10', 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, true, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, false, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, null, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, undefined, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, [ '1' ], 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, {}, 1, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( 10, alpha, ( x: number ): number => x, 1, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( x.length, alpha, x, '10', 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, true, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, false, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, null, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, undefined, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, [], 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, {}, 0, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, ( x: number ): number => x, 0, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( x.length, alpha, x, 1, '10', w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, true, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, false, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, null, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, undefined, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, [], w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, {}, w, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, ( x: number ): number => x, w, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( x.length, alpha, x, 1, 0, 10, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, '10', 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, true, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, false, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, null, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, undefined, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, {}, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( x.length, alpha, x, 1, 0, w, '10', 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, true, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, false, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, null, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, undefined, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, [], 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, {}, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an eighth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, '10' ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, true ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, false ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, null ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, undefined ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, [] ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, {} ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const w = new Complex128Array( 10 ); + const alpha = new Complex128( 5.0, 3.0 ); + + zwax.ndarray(); // $ExpectError + zwax.ndarray( x.length ); // $ExpectError + zwax.ndarray( x.length, alpha ); // $ExpectError + zwax.ndarray( x.length, alpha, x ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1 ); // $ExpectError + zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/c/example.c new file mode 100644 index 000000000000..18e8d6cb1186 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/c/example.c @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zwax.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex128_t x[] = { + stdlib_complex128( 1.0, 2.0 ), + stdlib_complex128( 3.0, 4.0 ), + stdlib_complex128( 5.0, 6.0 ), + stdlib_complex128( 7.0, 8.0 ) + }; + stdlib_complex128_t w[] = { + stdlib_complex128( 0.0, 0.0 ), + stdlib_complex128( 0.0, 0.0 ), + stdlib_complex128( 0.0, 0.0 ), + stdlib_complex128( 0.0, 0.0 ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideW = 1; + + // Define a scalar constant: + stdlib_complex128_t alpha = stdlib_complex128( 5.0, 3.0 ); + + // Multiply each element in `x` by a constant and assign to `w`: + stdlib_strided_zwax( N, alpha, x, strideX, w, strideW ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "w[ %i ] = %lf + %lfi\n", i, stdlib_complex128_real( w[ i ] ), stdlib_complex128_imag( w[ i ] ) ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/index.js new file mode 100644 index 000000000000..399fb3795db0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var logEach = require( '@stdlib/console/log-each' ); +var zwax = require( './../lib' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var wbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +var w = new Complex128Array( wbuf.buffer ); +var alpha = new Complex128( 5.0, 3.0 ); + +zwax( x.length, alpha, x, 1, w, 1 ); +logEach( '%s', w ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/zwax/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0, -2.0, 30.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* var zwax = require( '@stdlib/blas/ext/base/zwax' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +* var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex128( 2.0, 2.0 ); +* +* zwax.ndarray( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -2.0, 6.0, -2.0, 14.0, -2.0, 22.0, -2.0, 30.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zwax; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zwax = main; +} else { + zwax = tmp; +} + + +// EXPORTS // + +module.exports = zwax; + +// exports: { "ndarray": "zwax.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/main.js new file mode 100644 index 000000000000..9ab4971f6da0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zwax = require( './zwax.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zwax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/native.js new file mode 100644 index 000000000000..4e972986cc74 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zwax = require( './zwax.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( zwax, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/ndarray.js new file mode 100644 index 000000000000..a5be232e0d53 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/ndarray.js @@ -0,0 +1,133 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var real = require( '@stdlib/complex/float64/real' ); +var imag = require( '@stdlib/complex/float64/imag' ); +var zcopy = require( '@stdlib/blas/base/zcopy' ).ndarray; +var cmul = require( '@stdlib/complex/float64/base/mul' ).assign; + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128} alpha - scalar constant +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex128Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex128( 5.0, 3.0 ); +* +* zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function zwax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + var xview; + var wview; + var are; + var aim; + var ix; + var iw; + var sx; + var sw; + var m; + var i; + + if ( N <= 0 ) { + return w; + } + + // Decompose the constant into its real and imaginary components: + are = real( alpha ); + aim = imag( alpha ); + + // Fast path: when alpha = 1+0i, delegate to zcopy (w = x) + if ( are === 1.0 && aim === 0.0 ) { + return zcopy( N, x, strideX, offsetX, w, strideW, offsetW ); + } + + // Reinterpret the complex input arrays as real-valued arrays: + xview = reinterpret( x, 0 ); + wview = reinterpret( w, 0 ); + + // Adjust the strides and offsets according to the real-valued arrays: + ix = offsetX * 2; + iw = offsetW * 2; + sx = strideX * 2; + sw = strideW * 2; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideW === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + cmul( are, aim, xview[ ix ], xview[ ix+1 ], wview, 1, iw ); + ix += sx; + iw += sw; + } + } + if ( N < M ) { + return w; + } + for ( i = m; i < N; i += M ) { + cmul( are, aim, xview[ ix ], xview[ ix+1 ], wview, 1, iw ); + cmul( are, aim, xview[ ix+2 ], xview[ ix+3 ], wview, 1, iw+2 ); + cmul( are, aim, xview[ ix+4 ], xview[ ix+5 ], wview, 1, iw+4 ); + cmul( are, aim, xview[ ix+6 ], xview[ ix+7 ], wview, 1, iw+6 ); + cmul( are, aim, xview[ ix+8 ], xview[ ix+9 ], wview, 1, iw+8 ); + ix += M * 2; + iw += M * 2; + } + return w; + } + for ( i = 0; i < N; i++ ) { + cmul( are, aim, xview[ ix ], xview[ ix+1 ], wview, 1, iw ); + ix += sx; + iw += sw; + } + return w; +} + + +// EXPORTS // + +module.exports = zwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/ndarray.native.js new file mode 100644 index 000000000000..b918aeed2dfd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/ndarray.native.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128} alpha - scalar constant +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex128Array} w - output array +* @param {integer} strideW - `w` stride length +* @param {NonNegativeInteger} offsetW - starting `w` index +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex128( 5.0, 3.0 ); +* +* zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function zwax( N, alpha, x, strideX, offsetX, w, strideW, offsetW ) { + var viewX = reinterpret( x, 0 ); + var viewW = reinterpret( w, 0 ); + addon.ndarray( N, alpha, viewX, strideX, offsetX, viewW, strideW, offsetW ); + return w; +} + + +// EXPORTS // + +module.exports = zwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/zwax.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/zwax.js new file mode 100644 index 000000000000..da9bc1fcabbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/zwax.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128} alpha - scalar constant +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex128Array} w - output array +* @param {integer} strideW - `w` stride length +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex128( 5.0, 3.0 ); +* +* zwax( x.length, alpha, x, 1, w, 1 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function zwax( N, alpha, x, strideX, w, strideW ) { + return ndarray( N, alpha, x, strideX, stride2offset( N, strideX ), w, strideW, stride2offset( N, strideW ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = zwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/zwax.native.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/zwax.native.js new file mode 100644 index 000000000000..0f8ec27d85b0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/lib/zwax.native.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies each element in a double-precision complex floating-point strided array `x` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `w`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128} alpha - scalar constant +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex128Array} w - output array +* @param {integer} strideW - `w` stride length +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var Complex128 = require( '@stdlib/complex/float64/ctor' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* var alpha = new Complex128( 5.0, 3.0 ); +* +* zwax( x.length, alpha, x, 1, w, 1 ); +* // w => [ -1.0, 13.0, 3.0, 29.0, 7.0, 45.0 ] +*/ +function zwax( N, alpha, x, strideX, w, strideW ) { + var viewX = reinterpret( x, 0 ); + var viewW = reinterpret( w, 0 ); + addon( N, alpha, viewX, strideX, viewW, strideW ); + return w; +} + + +// EXPORTS // + +module.exports = zwax; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/zwax/manifest.json new file mode 100644 index 000000000000..b019946cac29 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/manifest.json @@ -0,0 +1,94 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/base/zcopy", + "@stdlib/complex/float64/base/mul", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-complex128", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-complex128array" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/base/zcopy", + "@stdlib/complex/float64/base/mul", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/blas/base/zcopy", + "@stdlib/complex/float64/base/mul", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/package.json b/lib/node_modules/@stdlib/blas/ext/base/zwax/package.json new file mode 100644 index 000000000000..a52b3de232c3 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/blas/ext/base/zwax", + "version": "0.0.0", + "description": "Multiply each element in a double-precision complex floating-point strided array `x` by a scalar constant and assign the results to elements in a double-precision complex floating-point strided array `w`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "multiply", + "multiplication", + "scale", + "scaling", + "strided", + "array", + "ndarray", + "zwax", + "complex", + "complex128", + "complex128array", + "float64" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zwax/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/zwax/src/addon.c new file mode 100644 index 000000000000..51e629014848 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/src/addon.c @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zwax.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_complex128.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex128array.h" +#include "stdlib/complex/float64/ctor.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_COMPLEX128( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 5 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, W, N, strideW, argv, 4 ); + API_SUFFIX(stdlib_strided_zwax)( N, alpha, (const stdlib_complex128_t *)X, strideX, (stdlib_complex128_t *)W, strideW ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 8 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_COMPLEX128( env, alpha, argv, 1 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 ); + STDLIB_NAPI_ARGV_INT64( env, strideW, argv, 6 ); + STDLIB_NAPI_ARGV_INT64( env, offsetW, argv, 7 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, W, N, strideW, argv, 5 ); + API_SUFFIX(stdlib_strided_zwax_ndarray)( N, alpha, (const stdlib_complex128_t *)X, strideX, offsetX, (stdlib_complex128_t *)W, strideW, offsetW ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/zwax/src/main.c new file mode 100644 index 000000000000..199040ae845d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/src/main.c @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zwax.h" +#include "stdlib/blas/base/zcopy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include "stdlib/complex/float64/base/mul.h" +#include "stdlib/strided/base/stride2offset.h" + +static const CBLAS_INT M = 5; + +/** +* Multiplies each element in a double-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `W`. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param W output array +* @param strideW stride length for `W` +*/ +void API_SUFFIX(stdlib_strided_zwax)( const CBLAS_INT N, const stdlib_complex128_t alpha, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *W, const CBLAS_INT strideW ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT ow = stdlib_strided_stride2offset( N, strideW ); + API_SUFFIX(stdlib_strided_zwax_ndarray)( N, alpha, X, strideX, ox, W, strideW, ow ); +} + +/** +* Multiplies each element in a double-precision complex floating-point strided array `X` by a scalar constant and assigns the results to elements in a double-precision complex floating-point strided array `W` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param alpha scalar constant +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param W output array +* @param strideW stride length for `W` +* @param offsetW starting index for `W` +*/ +void API_SUFFIX(stdlib_strided_zwax_ndarray)( const CBLAS_INT N, const stdlib_complex128_t alpha, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *W, const CBLAS_INT strideW, const CBLAS_INT offsetW ) { + CBLAS_INT ix; + CBLAS_INT iw; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + // Fast path: when alpha = 1+0i, delegate to zcopy (w = x) + if ( stdlib_complex128_real( alpha ) == 1.0 && stdlib_complex128_imag( alpha ) == 0.0 ) { + API_SUFFIX(c_zcopy_ndarray)( N, X, strideX, offsetX, W, strideW, offsetW ); + return; + } + ix = offsetX; + iw = offsetW; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideW == 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + W[ iw ] = stdlib_base_complex128_mul( alpha, X[ ix ] ); + ix += strideX; + iw += strideW; + } + } + if ( N < M ) { + return; + } + for ( i = m; i < N; i += M ) { + W[ iw ] = stdlib_base_complex128_mul( alpha, X[ ix ] ); + W[ iw+1 ] = stdlib_base_complex128_mul( alpha, X[ ix+1 ] ); + W[ iw+2 ] = stdlib_base_complex128_mul( alpha, X[ ix+2 ] ); + W[ iw+3 ] = stdlib_base_complex128_mul( alpha, X[ ix+3 ] ); + W[ iw+4 ] = stdlib_base_complex128_mul( alpha, X[ ix+4 ] ); + ix += M; + iw += M; + } + return; + } + for ( i = 0; i < N; i++ ) { + W[ iw ] = stdlib_base_complex128_mul( alpha, X[ ix ] ); + ix += strideX; + iw += strideW; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.js new file mode 100644 index 000000000000..000ae2f0193b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var zwax = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zwax.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zwax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zwax, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zwax = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zwax, require( './../lib/main.js' ), 'returns JS implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.ndarray.js new file mode 100644 index 000000000000..c966e905c713 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.ndarray.js @@ -0,0 +1,462 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var mul = require( '@stdlib/complex/float64/base/mul' ); +var zwax = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', function test( t ) { + t.strictEqual( zwax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex128( 3.0, 2.0 ); + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex128Array( x.length ); + out = zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + zwax( 0, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + zwax( -4, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 1.0, 0.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + zwax( 3, alpha, x, 2, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex128Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 0.0, + 0.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 0.0, + 0.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 1, 0, w, 2, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex128Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + zwax( 3, alpha, x, -2, x.length-1, w, -1, w.length-1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0 // 2 + ]); + w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 2, 1, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + w = new Complex128Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex128Array([ + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 1, 0, w, 1, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0, // 2 + 0.0, + 0.0 + ]); + w = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + expected = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + 0.0, + 0.0 + ]); + + zwax( 3, alpha, x, 2, 1, w, 1, 2 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array( 100 ); + w = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + w = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.ndarray.native.js new file mode 100644 index 000000000000..7c44fbf8c56f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.ndarray.native.js @@ -0,0 +1,471 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var mul = require( '@stdlib/complex/float64/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zwax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zwax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 8', opts, function test( t ) { + t.strictEqual( zwax.length, 8, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex128( 3.0, 2.0 ); + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex128Array( x.length ); + out = zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + zwax( 0, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + zwax( -4, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 1.0, 0.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + zwax( 3, alpha, x, 2, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex128Array([ + 0.0, // 0 + 0.0, // 0 + 0.0, + 0.0, + 0.0, // 1 + 0.0, // 1 + 0.0, + 0.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 0.0, + 0.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 0.0, + 0.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 1, 0, w, 2, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex128Array([ + 0.0, // 2 + 0.0, // 2 + 0.0, // 1 + 0.0, // 1 + 0.0, // 0 + 0.0 // 0 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + zwax( 3, alpha, x, -2, x.length-1, w, -1, w.length-1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` offset', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0 // 2 + ]); + w = new Complex128Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 2, 1, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` offset', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + w = new Complex128Array([ + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex128Array([ + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 1, 0, w, 1, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports complex access patterns', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 0.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 2 + 6.0, // 2 + 0.0, + 0.0 + ]); + w = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0, // 2 + 0.0, + 0.0 + ]); + expected = new Complex128Array([ + 0.0, + 0.0, + 0.0, + 0.0, + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + 0.0, + 0.0 + ]); + + zwax( 3, alpha, x, 2, 1, w, 1, 2 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array( 100 ); + w = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + w = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, 0, w, 1, 0 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.zwax.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.zwax.js new file mode 100644 index 000000000000..8bf299e216d5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.zwax.js @@ -0,0 +1,372 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var mul = require( '@stdlib/complex/float64/base/mul' ); +var zwax = require( './../lib/zwax.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', function test( t ) { + t.strictEqual( zwax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex128( 3.0, 2.0 ); + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex128Array( x.length ); + out = zwax( x.length, alpha, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + zwax( 0, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + zwax( -4, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 1.0, 0.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex128Array( 3 ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + zwax( 3, alpha, x, 2, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex128Array([ + 0.0, // 0 + 0.0, // 0 + 30.0, + 40.0, + 0.0, // 1 + 0.0, // 1 + 10.0, + 20.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 30.0, + 40.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 10.0, + 20.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 1, w, 2 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex128Array( 5 ); + expected = new Complex128Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + 0.0, + 0.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + 0.0, + 0.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + zwax( 3, alpha, x, -2, w, -2 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var alpha; + var x0; + var w0; + var x1; + var w1; + + alpha = new Complex128( 5.0, 3.0 ); + + x0 = new Complex128Array([ + 1.0, + 2.0, + 3.0, // 0 + 4.0, // 0 + 5.0, // 1 + 6.0, // 1 + 7.0, // 2 + 8.0, // 2 + 9.0, + 10.0 + ]); + w0 = new Complex128Array([ + 10.0, + 11.0, + 12.0, + 13.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Complex128Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 11.0, + 12.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (7.0+8.0i) + 11.0, + 61.0 + ]); + + zwax( 3, alpha, x1, 1, w1, 1 ); + t.strictEqual( isSameComplex128Array( w0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array( 100 ); + w = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + w = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.zwax.native.js b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.zwax.native.js new file mode 100644 index 000000000000..ac9cd4bb4fd7 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zwax/test/test.zwax.native.js @@ -0,0 +1,381 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var mul = require( '@stdlib/complex/float64/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zwax = tryRequire( resolve( __dirname, './../lib/zwax.native.js' ) ); +var opts = { + 'skip': ( zwax instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zwax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 6', opts, function test( t ) { + t.strictEqual( zwax.length, 6, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies each element in a strided array `x` by a scalar constant and assigns the results to elements in a strided array `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 4.0, + 2.0, + -3.0, + 5.0, + -1.0, + 2.0, + -5.0, + 6.0 + ]); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (4.0+2.0i) + 14.0, + 22.0, + // (5.0+3.0i) * (-3.0+5.0i) + -30.0, + 16.0, + // (5.0+3.0i) * (-1.0+2.0i) + -11.0, + 7.0, + // (5.0+3.0i) * (-5.0+6.0i) + -43.0, + 15.0 + ]); + + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0 + ]); + + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var alpha; + var out; + var x; + var w; + + alpha = new Complex128( 3.0, 2.0 ); + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); // eslint-disable-line max-len + w = new Complex128Array( x.length ); + out = zwax( x.length, alpha, x, 1, w, 1 ); + + t.strictEqual( out, w, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `w` unchanged', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] ); + + zwax( 0, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + zwax( -4, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `alpha` equals `1`, the function assigns `x` to `w`', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 1.0, 0.0 ); + x = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); + w = new Complex128Array( x.length ); + expected = new Complex128Array( [ 3.0, -4.0, 1.0, 15.0, 4.0, 3.0 ] ); // w = x + + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 3.0, + 4.0, + 5.0, // 1 + 6.0, // 1 + 7.0, + 8.0, + 9.0, // 2 + 10.0 // 2 + ]); + w = new Complex128Array( 3 ); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (9.0+10.0i) + 15.0, + 77.0 + ]); + + zwax( 3, alpha, x, 2, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `w` stride', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 1.0, + 2.0, + 3.0, + 4.0, + 5.0, + 6.0 + ]); + w = new Complex128Array([ + 0.0, // 0 + 0.0, // 0 + 30.0, + 40.0, + 0.0, // 1 + 0.0, // 1 + 10.0, + 20.0, + 0.0, // 2 + 0.0 // 2 + ]); + expected = new Complex128Array([ + // (5.0+3.0i) * (1.0+2.0i) + -1.0, + 13.0, + 30.0, + 40.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + 10.0, + 20.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0 + ]); + + zwax( 3, alpha, x, 1, w, 2 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array([ + 2.0, // 2 + 3.0, // 2 + 4.0, + 5.0, + -5.0, // 1 + -6.0, // 1 + 7.0, + 8.0, + 6.0, // 0 + 9.0 // 0 + ]); + w = new Complex128Array( 5 ); + expected = new Complex128Array([ + // (5.0+3.0i) * (2.0+3.0i) + 1.0, + 21.0, + 0.0, + 0.0, + // (5.0+3.0i) * (-5.0-6.0i) + -7.0, + -45.0, + 0.0, + 0.0, + // (5.0+3.0i) * (6.0+9.0i) + 3.0, + 63.0 + ]); + + zwax( 3, alpha, x, -2, w, -2 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var alpha; + var x0; + var w0; + var x1; + var w1; + + alpha = new Complex128( 5.0, 3.0 ); + + x0 = new Complex128Array([ + 1.0, + 2.0, + 3.0, // 0 + 4.0, // 0 + 5.0, // 1 + 6.0, // 1 + 7.0, // 2 + 8.0, // 2 + 9.0, + 10.0 + ]); + w0 = new Complex128Array([ + 10.0, + 11.0, + 12.0, + 13.0, + 0.0, // 0 + 0.0, // 0 + 0.0, // 1 + 0.0, // 1 + 0.0, // 2 + 0.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + w1 = new Complex128Array( w0.buffer, w0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 11.0, + 12.0, + 13.0, + // (5.0+3.0i) * (3.0+4.0i) + 3.0, + 29.0, + // (5.0+3.0i) * (5.0+6.0i) + 7.0, + 45.0, + // (5.0+3.0i) * (7.0+8.0i) + 11.0, + 61.0 + ]); + + zwax( 3, alpha, x1, 1, w1, 1 ); + t.strictEqual( isSameComplex128Array( w0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies each element of a strided array by a constant', opts, function test( t ) { + var expected; + var alpha; + var x; + var w; + var z; + var i; + + alpha = new Complex128( 5.0, 3.0 ); + + x = new Complex128Array( 100 ); + w = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + w = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + z = new Complex128( i, i + 1 ); + x.set( z, i ); + expected.set( mul( alpha, z ), i ); + } + zwax( x.length, alpha, x, 1, w, 1 ); + t.strictEqual( isSameComplex128Array( w, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/README.md b/lib/node_modules/@stdlib/blas/ext/base/zxdy/README.md new file mode 100644 index 000000000000..a835ef94736b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/README.md @@ -0,0 +1,354 @@ + + +# zxdy + +> Divide elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assign the results to `y`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \oslash \mathbf{y} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var zxdy = require( '@stdlib/blas/ext/base/zxdy' ); +``` + +#### zxdy( N, x, strideX, y, strideY ) + +Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + +zxdy( x.length, x, 1, y, 1 ); +// y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Complex128Array`][@stdlib/array/complex128]. +- **strideX**: stride length for `x`. +- **y**: output [`Complex128Array`][@stdlib/array/complex128]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to divide every other element of `x` by every other element of `y`: + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 4.0, 6.0, 100.0, 200.0, 12.0, 8.0, 300.0, 400.0 ] ); +var y = new Complex128Array( [ 1.0, 1.0, 500.0, 600.0, 2.0, 2.0, 700.0, 800.0 ] ); + +zxdy( 2, x, 2, y, 2 ); +// y => [ 5.0, 1.0, 500.0, 600.0, 5.0, -1.0, 700.0, 800.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +// Initial arrays... +var x0 = new Complex128Array( [ 100.0, 200.0, 4.0, 6.0, 12.0, 8.0, 16.0, 8.0, 300.0, 400.0 ] ); +var y0 = new Complex128Array( [ 500.0, 600.0, 700.0, 800.0, 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + +// Create offset views... +var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +zxdy( 3, x1, 1, y1, 1 ); +// y0 => [ 500.0, 600.0, 700.0, 800.0, 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +``` + +#### zxdy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + +zxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to divide the last three elements of `x` by the last three elements of `y`: + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 100.0, 200.0, 300.0, 400.0, 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +var y = new Complex128Array( [ 500.0, 600.0, 700.0, 800.0, 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + +zxdy.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// y => [ 500.0, 600.0, 700.0, 800.0, 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var logEach = require( '@stdlib/console/log-each' ); +var zxdy = require( '@stdlib/blas/ext/base/zxdy' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var ybuf = discreteUniform( 20, 1, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +var y = new Complex128Array( ybuf.buffer ); + +zxdy( x.length, x, 1, y, 1 ); +logEach( '%s', y ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/zxdy.h" +``` + +#### stdlib_strided_zxdy( N, \*X, strideX, \*Y, strideY ) + +Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 }; +double y[] = { 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 }; + +stdlib_strided_zxdy( 3, (stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[inout] stdlib_complex128_t*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_zxdy( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_zxdy_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 }; +double y[] = { 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 }; + +stdlib_strided_zxdy_ndarray( 3, (stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[inout] stdlib_complex128_t*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_zxdy_ndarray( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/zxdy.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex128_t x[] = { + stdlib_complex128( 4.0, 6.0 ), + stdlib_complex128( 12.0, 8.0 ), + stdlib_complex128( 16.0, 8.0 ), + stdlib_complex128( 32.0, 16.0 ) + }; + stdlib_complex128_t y[] = { + stdlib_complex128( 1.0, 1.0 ), + stdlib_complex128( 2.0, 2.0 ), + stdlib_complex128( 4.0, 4.0 ), + stdlib_complex128( 8.0, 8.0 ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Divide elements of `x` by the corresponding elements of `y`: + stdlib_strided_zxdy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "y[ %i ] = %lf + %lfi\n", i, stdlib_complex128_real( y[ i ] ), stdlib_complex128_imag( y[ i ] ) ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.js new file mode 100644 index 000000000000..fe4b4146d82b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zxdy = require( './../lib/zxdy.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, 1.0, 10.0, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxdy( x.length, x, 1, y, 1 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..244c29d15336 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.native.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zxdy = tryRequire( resolve( __dirname, './../lib/zxdy.native.js' ) ); +var opts = { + 'skip': ( zxdy instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, 1.0, 10.0, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxdy( x.length, x, 1, y, 1 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..13b5f8dd83e9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.ndarray.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zxdy = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, 1.0, 10.0, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxdy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..78aa1b125b52 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zxdy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zxdy instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, 1.0, 10.0, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxdy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..25807aa2f438 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/benchmark/c/benchmark.length.c @@ -0,0 +1,210 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxdy.h" +#include "stdlib/complex/float64/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "zxdy" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int i; + + x = (double *)malloc( len * 2 * sizeof( double ) ); + y = (double *)malloc( len * 2 * sizeof( double ) ); + + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -0.5, 0.5 ); + y[ i ] = random_uniform( 1.0, 10.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_zxdy( len, (stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)y, 1 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int i; + + x = (double *)malloc( len * 2 * sizeof( double ) ); + y = (double *)malloc( len * 2 * sizeof( double ) ); + + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -0.5, 0.5 ); + y[ i ] = random_uniform( 1.0, 10.0 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_zxdy_ndarray( len, (stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/zxdy/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/img/equation_xdy.svg b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/img/equation_xdy.svg new file mode 100644 index 000000000000..1b0e60ad95cf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/img/equation_xdy.svg @@ -0,0 +1,16 @@ + +bold y equals bold x circled-division-slash bold y + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/repl.txt new file mode 100644 index 000000000000..80209ff02aa6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/repl.txt @@ -0,0 +1,127 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Divides elements of a double-precision complex floating-point strided array + `x` by the corresponding elements of a double-precision complex floating- + point strided array `y` and assigns the results to `y`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + y: Complex128Array + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + y: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ]; + > var bufY = [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ]; + > var x = new {{alias:@stdlib/array/complex128}}( bufX ); + > var y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}( x.length, x, 1, y, 1 ) + [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] + + // Using `N` and stride parameters: + > bufX = [ 4.0, 6.0, 100.0, 200.0, 12.0, 8.0, 300.0, 400.0 ]; + > x = new {{alias:@stdlib/array/complex128}}( bufX ); + > bufY = [ 1.0, 1.0, 500.0, 600.0, 2.0, 2.0, 700.0, 800.0 ]; + > y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}( 2, x, 2, y, 2 ) + [ 5.0, 1.0, 500.0, 600.0, 5.0, -1.0, 700.0, 800.0 ] + + // Using view offsets: + > var bufX = [ 100.0, 200.0, 4.0, 6.0, 12.0, 8.0, 16.0, 8.0, 300.0, 400.0 ]; + > var bufY = [ 500.0, 600.0, 700.0, 800.0, 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ]; + > var x0 = new {{alias:@stdlib/array/complex128}}( bufX ); + > var y0 = new {{alias:@stdlib/array/complex128}}( bufY ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetY = y0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/complex128}}( x0.buffer, offsetX ); + > var y1 = new {{alias:@stdlib/array/complex128}}( y0.buffer, offsetY ); + > {{alias}}( 3, x1, 1, y1, 1 ) + [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] + > y0 + [ 500.0,600.0,700.0,800.0, 5.0,1.0, 5.0,-1.0, 3.0,-1.0 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Divides elements of a double-precision complex floating-point strided array + `x` by the corresponding elements of a double-precision complex floating- + point strided array `y` and assigns the results to `y` using alternative + indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Complex128Array + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + y: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ]; + > var bufY = [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ]; + > var x = new {{alias:@stdlib/array/complex128}}( bufX ); + > var y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] + + // Using index offsets: + > bufX = [ 100.0, 200.0, 300.0, 400.0, 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ]; + > x = new {{alias:@stdlib/array/complex128}}( bufX ); + > bufY = [ 500.0, 600.0, 700.0, 800.0, 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ]; + > y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ) + [ 500.0,600.0,700.0,800.0, 5.0,1.0, 5.0,-1.0, 3.0,-1.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/types/index.d.ts new file mode 100644 index 000000000000..5c7f2629ac26 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/types/index.d.ts @@ -0,0 +1,107 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex128Array } from '@stdlib/types/array'; + +/** +* Interface describing `zxdy`. +*/ +interface Routine { + /** + * Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + * var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + * + * zxdy( x.length, x, 1, y, 1 ); + * // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] + */ + ( N: number, x: Complex128Array, strideX: number, y: Complex128Array, strideY: number ): Complex128Array; + + /** + * Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting `x` index + * @param y - output array + * @param strideY - `y` stride length + * @param offsetY - starting `y` index + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + * var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + * + * zxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] + */ + ndarray( N: number, x: Complex128Array, strideX: number, offsetX: number, y: Complex128Array, strideY: number, offsetY: number ): Complex128Array; +} + +/** +* Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - `x` stride length +* @param y - output array +* @param strideY - `y` stride length +* @returns output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +* var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* zxdy( x.length, x, 1, y, 1 ); +* // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +* var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* zxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +*/ +declare var zxdy: Routine; + + +// EXPORTS // + +export = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/types/test.ts new file mode 100644 index 000000000000..c77c8035d0e1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/docs/types/test.ts @@ -0,0 +1,247 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import zxdy = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy( x.length, x, 1, y, 1 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy( '10', x, 1, y, 1 ); // $ExpectError + zxdy( true, x, 1, y, 1 ); // $ExpectError + zxdy( false, x, 1, y, 1 ); // $ExpectError + zxdy( null, x, 1, y, 1 ); // $ExpectError + zxdy( undefined, x, 1, y, 1 ); // $ExpectError + zxdy( [], x, 1, y, 1 ); // $ExpectError + zxdy( {}, x, 1, y, 1 ); // $ExpectError + zxdy( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex128Array... +{ + const y = new Complex128Array( 10 ); + + zxdy( 10, 10, 1, y, 1 ); // $ExpectError + zxdy( 10, '10', 1, y, 1 ); // $ExpectError + zxdy( 10, true, 1, y, 1 ); // $ExpectError + zxdy( 10, false, 1, y, 1 ); // $ExpectError + zxdy( 10, null, 1, y, 1 ); // $ExpectError + zxdy( 10, undefined, 1, y, 1 ); // $ExpectError + zxdy( 10, [ '1' ], 1, y, 1 ); // $ExpectError + zxdy( 10, {}, 1, y, 1 ); // $ExpectError + zxdy( 10, ( x: number ): number => x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy( x.length, x, '10', y, 1 ); // $ExpectError + zxdy( x.length, x, true, y, 1 ); // $ExpectError + zxdy( x.length, x, false, y, 1 ); // $ExpectError + zxdy( x.length, x, null, y, 1 ); // $ExpectError + zxdy( x.length, x, undefined, y, 1 ); // $ExpectError + zxdy( x.length, x, [], y, 1 ); // $ExpectError + zxdy( x.length, x, {}, y, 1 ); // $ExpectError + zxdy( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + + zxdy( 10, x, 1, 10, 1 ); // $ExpectError + zxdy( 10, x, 1, '10', 1 ); // $ExpectError + zxdy( 10, x, 1, true, 1 ); // $ExpectError + zxdy( 10, x, 1, false, 1 ); // $ExpectError + zxdy( 10, x, 1, null, 1 ); // $ExpectError + zxdy( 10, x, 1, undefined, 1 ); // $ExpectError + zxdy( 10, x, 1, [ '1' ], 1 ); // $ExpectError + zxdy( 10, x, 1, {}, 1 ); // $ExpectError + zxdy( 10, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy( x.length, x, 1, y, '10' ); // $ExpectError + zxdy( x.length, x, 1, y, true ); // $ExpectError + zxdy( x.length, x, 1, y, false ); // $ExpectError + zxdy( x.length, x, 1, y, null ); // $ExpectError + zxdy( x.length, x, 1, y, undefined ); // $ExpectError + zxdy( x.length, x, 1, y, [] ); // $ExpectError + zxdy( x.length, x, 1, y, {} ); // $ExpectError + zxdy( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy(); // $ExpectError + zxdy( x.length ); // $ExpectError + zxdy( x.length, x ); // $ExpectError + zxdy( x.length, x, 1 ); // $ExpectError + zxdy( x.length, x, 1, y ); // $ExpectError + zxdy( x.length, x, 1, y, 1, 10 ); // $ExpectError +} + +// Attached to the main export is an `ndarray` method which returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex128Array... +{ + const y = new Complex128Array( 10 ); + + zxdy.ndarray( 10, 10, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, '10', 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, true, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, false, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, null, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, undefined, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, [ '1' ], 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, {}, 1, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + + zxdy.ndarray( 10, x, 1, 0, 10, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, '10', 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, true, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, false, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, null, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, undefined, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, {}, 1, 0 ); // $ExpectError + zxdy.ndarray( 10, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxdy.ndarray(); // $ExpectError + zxdy.ndarray( x.length ); // $ExpectError + zxdy.ndarray( x.length, x ); // $ExpectError + zxdy.ndarray( x.length, x, 1 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + zxdy.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/c/example.c new file mode 100644 index 000000000000..d725c9c45cdd --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/c/example.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxdy.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex128_t x[] = { + stdlib_complex128( 4.0, 6.0 ), + stdlib_complex128( 12.0, 8.0 ), + stdlib_complex128( 16.0, 8.0 ), + stdlib_complex128( 32.0, 16.0 ) + }; + stdlib_complex128_t y[] = { + stdlib_complex128( 1.0, 1.0 ), + stdlib_complex128( 2.0, 2.0 ), + stdlib_complex128( 4.0, 4.0 ), + stdlib_complex128( 8.0, 8.0 ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Divide elements of `x` by the corresponding elements of `y`: + stdlib_strided_zxdy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "y[ %i ] = %lf + %lfi\n", i, stdlib_complex128_real( y[ i ] ), stdlib_complex128_imag( y[ i ] ) ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/index.js new file mode 100644 index 000000000000..9c4a623125df --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var logEach = require( '@stdlib/console/log-each' ); +var zxdy = require( './../lib' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var ybuf = discreteUniform( 20, 1, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +var y = new Complex128Array( ybuf.buffer ); + +zxdy( x.length, x, 1, y, 1 ); +logEach( '%s', y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/zxdy/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var zxdy = require( '@stdlib/blas/ext/base/zxdy' ); +* +* var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +* var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* zxdy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zxdy; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zxdy = main; +} else { + zxdy = tmp; +} + + +// EXPORTS // + +module.exports = zxdy; + +// exports: { "ndarray": "zxdy.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/main.js new file mode 100644 index 000000000000..48885674c0eb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zxdy = require( './zxdy.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zxdy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/native.js new file mode 100644 index 000000000000..4c08cfc8d771 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zxdy = require( './zxdy.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( zxdy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/ndarray.js new file mode 100644 index 000000000000..bde3adcf5aa2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/ndarray.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var cdiv = require( '@stdlib/complex/float64/base/div' ).assign; + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +* var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* zxdy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +*/ +function zxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xview; + var yview; + var ix; + var iy; + var sx; + var sy; + var m; + var i; + + if ( N <= 0 ) { + return y; + } + + // Reinterpret the complex input arrays as real-valued arrays: + xview = reinterpret( x, 0 ); + yview = reinterpret( y, 0 ); + + // Adjust the strides and offsets according to the real-valued arrays: + ix = offsetX * 2; + iy = offsetY * 2; + sx = strideX * 2; + sy = strideY * 2; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideY === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + cdiv( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + ix += sx; + iy += sy; + } + } + if ( N < M ) { + return y; + } + for ( i = m; i < N; i += M ) { + cdiv( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + cdiv( xview[ ix+2 ], xview[ ix+3 ], yview[ iy+2 ], yview[ iy+3 ], yview, 1, iy+2 ); + cdiv( xview[ ix+4 ], xview[ ix+5 ], yview[ iy+4 ], yview[ iy+5 ], yview, 1, iy+4 ); + cdiv( xview[ ix+6 ], xview[ ix+7 ], yview[ iy+6 ], yview[ iy+7 ], yview, 1, iy+6 ); + cdiv( xview[ ix+8 ], xview[ ix+9 ], yview[ iy+8 ], yview[ iy+9 ], yview, 1, iy+8 ); + ix += M * 2; + iy += M * 2; + } + return y; + } + for ( i = 0; i < N; i++ ) { + cdiv( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + ix += sx; + iy += sy; + } + return y; +} + + +// EXPORTS // + +module.exports = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/ndarray.native.js new file mode 100644 index 000000000000..24d25a31056d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/ndarray.native.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +* var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* zxdy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +*/ +function zxdy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var viewX = reinterpret( x, 0 ); + var viewY = reinterpret( y, 0 ); + addon.ndarray( N, viewX, strideX, offsetX, viewY, strideY, offsetY ); + return y; +} + + +// EXPORTS // + +module.exports = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/zxdy.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/zxdy.js new file mode 100644 index 000000000000..a3e39de7078e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/zxdy.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +* var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* zxdy( x.length, x, 1, y, 1 ); +* // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +*/ +function zxdy( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/zxdy.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/zxdy.native.js new file mode 100644 index 000000000000..da11193ea533 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/lib/zxdy.native.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); +* var y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); +* +* zxdy( x.length, x, 1, y, 1 ); +* // y => [ 5.0, 1.0, 5.0, -1.0, 3.0, -1.0 ] +*/ +function zxdy( N, x, strideX, y, strideY ) { + var viewX = reinterpret( x, 0 ); + var viewY = reinterpret( y, 0 ); + addon( N, viewX, strideX, viewY, strideY ); + return y; +} + + +// EXPORTS // + +module.exports = zxdy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/zxdy/manifest.json new file mode 100644 index 000000000000..9c77abf3ddfb --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/manifest.json @@ -0,0 +1,108 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/div", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-complex128array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/div", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/div", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "build", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/div", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/package.json b/lib/node_modules/@stdlib/blas/ext/base/zxdy/package.json new file mode 100644 index 000000000000..16ce305b60ae --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/package.json @@ -0,0 +1,83 @@ +{ + "name": "@stdlib/blas/ext/base/zxdy", + "version": "0.0.0", + "description": "Divide elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assign the results to `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "linear", + "algebra", + "subroutines", + "divide", + "division", + "transform", + "strided", + "array", + "ndarray", + "vector", + "xdy", + "zxdy", + "complex", + "complex128", + "complex128array", + "float64", + "double" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/addon.c new file mode 100644 index 000000000000..4d0c3225c45f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxdy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex128array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_zxdy)( N, (stdlib_complex128_t *)X, strideX, (stdlib_complex128_t *)Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_zxdy_ndarray)( N, (stdlib_complex128_t *)X, strideX, offsetX, (stdlib_complex128_t *)Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/main.c new file mode 100644 index 000000000000..77642d39bb91 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/src/main.c @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxdy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/complex/float64/base/div.h" +#include "stdlib/strided/base/stride2offset.h" + +static const CBLAS_INT M = 5; + +/** +* Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param Y output array +* @param strideY stride length for `Y` +*/ +void API_SUFFIX(stdlib_strided_zxdy)( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_zxdy_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Divides elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param Y output array +* @param strideY stride length for `Y` +* @param offsetY starting index for `Y` +*/ +void API_SUFFIX(stdlib_strided_zxdy_ndarray)( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideY == 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + Y[ iy ] = stdlib_base_complex128_div( X[ ix ], Y[ iy ] ); + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return; + } + for ( i = m; i < N; i += M ) { + Y[ iy ] = stdlib_base_complex128_div( X[ ix ], Y[ iy ] ); + Y[ iy+1 ] = stdlib_base_complex128_div( X[ ix+1 ], Y[ iy+1 ] ); + Y[ iy+2 ] = stdlib_base_complex128_div( X[ ix+2 ], Y[ iy+2 ] ); + Y[ iy+3 ] = stdlib_base_complex128_div( X[ ix+3 ], Y[ iy+3 ] ); + Y[ iy+4 ] = stdlib_base_complex128_div( X[ ix+4 ], Y[ iy+4 ] ); + ix += M; + iy += M; + } + return; + } + for ( i = 0; i < N; i++ ) { + Y[ iy ] = stdlib_base_complex128_div( X[ ix ], Y[ iy ] ); + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.js new file mode 100644 index 000000000000..bc6877df1d0a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var zxdy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zxdy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zxdy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zxdy, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zxdy; + var main; + + main = require( './../lib/zxdy.js' ); + + zxdy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zxdy, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.ndarray.js new file mode 100644 index 000000000000..86708894a971 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.ndarray.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cdiv = require( '@stdlib/complex/float64/base/div' ); +var zxdy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( zxdy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 4.0, 2.0, 12.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] ); + expected = new Complex128Array([ + // (4.0+2.0i) / (1.0+1.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0 + ]); + + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + out = zxdy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxdy( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxdy( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 4.0, // 0 + 6.0, // 0 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 16.0, // 2 + 8.0 // 2 + ]); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 4.0, + 5.0, + 2.0, // 1 + 2.0, // 1 + 8.0, + 9.0, + 4.0, // 2 + 4.0 // 2 + ]); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + 4.0, + 5.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + 8.0, + 9.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 16.0, // 2 + 8.0, // 2 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 4.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 4.0, // 2 + 2.0, // 1 + 2.0, // 1 + 1.0, // 0 + 1.0 // 0 + ]); + expected = new Complex128Array([ + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0 + ]); + + zxdy( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 4.0, // 0 + 6.0, // 0 + 12.0, // 1 + 8.0, // 1 + 16.0, // 2 + 8.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 1.0, // 0 + 1.0, // 0 + 2.0, // 1 + 2.0, // 1 + 4.0, // 2 + 4.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x1, 1, 0, y1, 1, 0 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.ndarray.native.js new file mode 100644 index 000000000000..b051c743d7ed --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.ndarray.native.js @@ -0,0 +1,330 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cdiv = require( '@stdlib/complex/float64/base/div' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zxdy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zxdy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( zxdy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 4.0, 2.0, 12.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] ); + expected = new Complex128Array([ + // (4.0+2.0i) / (1.0+1.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0 + ]); + + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + out = zxdy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxdy( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxdy( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 4.0, // 0 + 6.0, // 0 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 16.0, // 2 + 8.0 // 2 + ]); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 4.0, + 5.0, + 2.0, // 1 + 2.0, // 1 + 8.0, + 9.0, + 4.0, // 2 + 4.0 // 2 + ]); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + 4.0, + 5.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + 8.0, + 9.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 16.0, // 2 + 8.0, // 2 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 4.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 4.0, // 2 + 2.0, // 1 + 2.0, // 1 + 1.0, // 0 + 1.0 // 0 + ]); + expected = new Complex128Array([ + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0 + ]); + + zxdy( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 4.0, // 0 + 6.0, // 0 + 12.0, // 1 + 8.0, // 1 + 16.0, // 2 + 8.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 1.0, // 0 + 1.0, // 0 + 2.0, // 1 + 2.0, // 1 + 4.0, // 2 + 4.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x1, 1, 0, y1, 1, 0 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.zxdy.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.zxdy.js new file mode 100644 index 000000000000..dfbcb6a8c937 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.zxdy.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cdiv = require( '@stdlib/complex/float64/base/div' ); +var zxdy = require( './../lib/zxdy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( zxdy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 4.0, 2.0, 12.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] ); + expected = new Complex128Array([ + // (4.0+2.0i) / (1.0+1.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0 + ]); + + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + out = zxdy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxdy( 0, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxdy( -4, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 4.0, // 0 + 6.0, // 0 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 16.0, // 2 + 8.0 // 2 + ]); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 2, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 4.0, + 5.0, + 2.0, // 1 + 2.0, // 1 + 8.0, + 9.0, + 4.0, // 2 + 4.0 // 2 + ]); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + 4.0, + 5.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + 8.0, + 9.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 1, y, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 16.0, // 2 + 8.0, // 2 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 4.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 4.0, // 2 + 2.0, // 1 + 2.0, // 1 + 1.0, // 0 + 1.0 // 0 + ]); + expected = new Complex128Array([ + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0 + ]); + + zxdy( 3, x, -2, y, -1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 4.0, // 0 + 6.0, // 0 + 12.0, // 1 + 8.0, // 1 + 16.0, // 2 + 8.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 1.0, // 0 + 1.0, // 0 + 2.0, // 1 + 2.0, // 1 + 4.0, // 2 + 4.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x1, 1, y1, 1 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.zxdy.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.zxdy.native.js new file mode 100644 index 000000000000..ae0c3ad9055a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxdy/test/test.zxdy.native.js @@ -0,0 +1,330 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cdiv = require( '@stdlib/complex/float64/base/div' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zxdy = tryRequire( resolve( __dirname, './../lib/zxdy.native.js' ) ); +var opts = { + 'skip': ( zxdy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxdy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( zxdy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 4.0, 2.0, 12.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] ); + expected = new Complex128Array([ + // (4.0+2.0i) / (1.0+1.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0 + ]); + + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + out = zxdy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxdy( 0, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxdy( -4, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 4.0, // 0 + 6.0, // 0 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 16.0, // 2 + 8.0 // 2 + ]); + y = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 4.0, 4.0 ] ); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 2, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 4.0, 6.0, 12.0, 8.0, 16.0, 8.0 ] ); + y = new Complex128Array([ + 1.0, // 0 + 1.0, // 0 + 4.0, + 5.0, + 2.0, // 1 + 2.0, // 1 + 8.0, + 9.0, + 4.0, // 2 + 4.0 // 2 + ]); + expected = new Complex128Array([ + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + 4.0, + 5.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + 8.0, + 9.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x, 1, y, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 16.0, // 2 + 8.0, // 2 + 0.0, + 0.0, + 12.0, // 1 + 8.0, // 1 + 0.0, + 0.0, + 4.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 4.0, // 2 + 2.0, // 1 + 2.0, // 1 + 1.0, // 0 + 1.0 // 0 + ]); + expected = new Complex128Array([ + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0 + ]); + + zxdy( 3, x, -2, y, -1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 4.0, // 0 + 6.0, // 0 + 12.0, // 1 + 8.0, // 1 + 16.0, // 2 + 8.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 1.0, // 0 + 1.0, // 0 + 2.0, // 1 + 2.0, // 1 + 4.0, // 2 + 4.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (4.0+6.0i) / (1.0+1.0i) + 5.0, + 1.0, + // (12.0+8.0i) / (2.0+2.0i) + 5.0, + -1.0, + // (16.0+8.0i) / (4.0+4.0i) + 3.0, + -1.0 + ]); + + zxdy( 3, x1, 1, y1, 1 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently divides elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cdiv( xv, yv ), i ); + } + zxdy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/README.md b/lib/node_modules/@stdlib/blas/ext/base/zxmy/README.md new file mode 100644 index 000000000000..20b72703c3c0 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/README.md @@ -0,0 +1,347 @@ + + +# zxmy + +> Multiply elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assign the results to `y`. + +
+ +This BLAS extension implements the operation + + + +```math +\mathbf{y} = \mathbf{x} \odot \mathbf{y} +``` + + + +
+ + + +
+ +## Usage + +```javascript +var zxmy = require( '@stdlib/blas/ext/base/zxmy' ); +``` + +#### zxmy( N, x, strideX, y, strideY ) + +Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + +zxmy( x.length, x, 1, y, 1 ); +// y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +``` + +The function has the following parameters: + +- **N**: number of indexed elements. +- **x**: input [`Complex128Array`][@stdlib/array/complex128]. +- **strideX**: stride length for `x`. +- **y**: output [`Complex128Array`][@stdlib/array/complex128]. +- **strideY**: stride length for `y`. + +The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to multiply every other element of `x` by every other element of `y`: + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] ); +var y = new Complex128Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 ] ); + +zxmy( 2, x, 2, y, 2 ); +// y => [ -9.0, 22.0, 9.0, 10.0, -17.0, 126.0, 13.0, 14.0 ] +``` + +Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +// Initial arrays... +var x0 = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var y0 = new Complex128Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ] ); + +// Create offset views... +var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element +var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); // start at 3rd element + +zxmy( 3, x1, 1, y1, 1 ); +// y0 => [ 7.0, 8.0, 9.0, 10.0, -15.0, 80.0, -19.0, 148.0, -23.0, 232.0 ] +``` + +#### zxmy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + +Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + +zxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +// y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +``` + +The function has the following additional parameters: + +- **offsetX**: starting index for `x`. +- **offsetY**: starting index for `y`. + +While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to multiply the last three elements of `x` by the last three elements of `y`: + + + +```javascript +var Complex128Array = require( '@stdlib/array/complex128' ); + +var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] ); +var y = new Complex128Array( [ 11.0, 12.0, 13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0 ] ); + +zxmy.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ); +// y => [ 11.0, 12.0, 13.0, 14.0, -21.0, 170.0, -25.0, 262.0, -29.0, 370.0 ] +``` + +
+ + + +
+ +## Notes + +- If `N <= 0`, both functions return `y` unchanged. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var logEach = require( '@stdlib/console/log-each' ); +var zxmy = require( '@stdlib/blas/ext/base/zxmy' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var ybuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +var y = new Complex128Array( ybuf.buffer ); + +zxmy( x.length, x, 1, y, 1 ); +logEach( '%s', y ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/blas/ext/base/zxmy.h" +``` + +#### stdlib_strided_zxmy( N, \*X, strideX, \*Y, strideY ) + +Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }; +double y[] = { 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 }; + +stdlib_strided_zxmy( 3, (stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)y, 1 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **Y**: `[inout] stdlib_complex128_t*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. + +```c +void stdlib_strided_zxmy( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *Y, const CBLAS_INT strideY ); +``` + + + +#### stdlib_strided_zxmy_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY ) + + + +Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + +```c +#include "stdlib/complex/float64/ctor.h" + +const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 }; +double y[] = { 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 }; + +stdlib_strided_zxmy_ndarray( 3, (stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)y, 1, 0 ); +``` + +The function accepts the following arguments: + +- **N**: `[in] CBLAS_INT` number of indexed elements. +- **X**: `[in] stdlib_complex128_t*` input array. +- **strideX**: `[in] CBLAS_INT` stride length for `X`. +- **offsetX**: `[in] CBLAS_INT` starting index for `X`. +- **Y**: `[inout] stdlib_complex128_t*` output array. +- **strideY**: `[in] CBLAS_INT` stride length for `Y`. +- **offsetY**: `[in] CBLAS_INT` starting index for `Y`. + +```c +void stdlib_strided_zxmy_ndarray( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/blas/ext/base/zxmy.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex128_t x[] = { + stdlib_complex128( 1.0, 2.0 ), + stdlib_complex128( 3.0, 4.0 ), + stdlib_complex128( 5.0, 6.0 ), + stdlib_complex128( 7.0, 8.0 ) + }; + stdlib_complex128_t y[] = { + stdlib_complex128( 2.0, 3.0 ), + stdlib_complex128( 4.0, 5.0 ), + stdlib_complex128( 6.0, 7.0 ), + stdlib_complex128( 8.0, 9.0 ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Multiply `x` by `y` and assign the results to `y`: + stdlib_strided_zxmy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "y[ %i ] = %lf + %lfi\n", i, stdlib_complex128_real( y[ i ] ), stdlib_complex128_imag( y[ i ] ) ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/array/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex128 + +[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.js new file mode 100644 index 000000000000..5151fa43100f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zxmy = require( './../lib/zxmy.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxmy( x.length, x, 1, y, 1 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..888079d3a7cc --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.native.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zxmy = tryRequire( resolve( __dirname, './../lib/zxmy.native.js' ) ); +var opts = { + 'skip': ( zxmy instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxmy( x.length, x, 1, y, 1 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.ndarray.js new file mode 100644 index 000000000000..829b1b6bc748 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.ndarray.js @@ -0,0 +1,112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var zxmy = require( './../lib/ndarray.js' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxmy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:ndarray:len=%d', pkg, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.ndarray.native.js new file mode 100644 index 000000000000..9ca14b793a6a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/benchmark.ndarray.native.js @@ -0,0 +1,117 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var zxmy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zxmy instanceof Error ) +}; +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Create a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var xbuf; + var ybuf; + var x; + var y; + + xbuf = uniform( len*2, -0.5, 0.5, options ); + ybuf = uniform( len*2, -0.5, 0.5, options ); + x = new Complex128Array( xbuf.buffer ); + y = new Complex128Array( ybuf.buffer ); + + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + zxmy( x.length, x, 1, 0, y, 1, 0 ); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( ybuf[ i%(len*2) ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s::native:ndarray:len=%d', pkg, len ), opts, f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/c/Makefile new file mode 100644 index 000000000000..0756dc7da20a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.length.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/c/benchmark.length.c new file mode 100644 index 000000000000..f398d3f3699f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/benchmark/c/benchmark.length.c @@ -0,0 +1,210 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxmy.h" +#include "stdlib/complex/float64/ctor.h" +#include +#include +#include +#include +#include + +#define NAME "zxmy" +#define ITERATIONS 10000000 +#define REPEATS 3 +#define MIN 1 +#define MAX 6 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param iterations number of iterations +* @param elapsed elapsed time in seconds +*/ +static void print_results( int iterations, double elapsed ) { + double rate = (double)iterations / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", iterations ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark1( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int i; + + x = (double *)malloc( len * 2 * sizeof( double ) ); + y = (double *)malloc( len * 2 * sizeof( double ) ); + + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -0.5, 0.5 ); + y[ i ] = random_uniform( -0.5, 0.5 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_zxmy( len, (stdlib_complex128_t *)x, 1, (stdlib_complex128_t *)y, 1 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Runs a benchmark. +* +* @param iterations number of iterations +* @param len array length +* @return elapsed time in seconds +*/ +static double benchmark2( int iterations, int len ) { + double elapsed; + double *x; + double *y; + double t; + int i; + + x = (double *)malloc( len * 2 * sizeof( double ) ); + y = (double *)malloc( len * 2 * sizeof( double ) ); + + for ( i = 0; i < len*2; i++ ) { + x[ i ] = random_uniform( -0.5, 0.5 ); + y[ i ] = random_uniform( -0.5, 0.5 ); + } + t = tic(); + for ( i = 0; i < iterations; i++ ) { + // cppcheck-suppress uninitvar + stdlib_strided_zxmy_ndarray( len, (stdlib_complex128_t *)x, 1, 0, (stdlib_complex128_t *)y, 1, 0 ); + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y[ 0 ] != y[ 0 ] ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int count; + int iter; + int len; + int i; + int j; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + count = 0; + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:len=%d\n", NAME, len ); + elapsed = benchmark1( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + for ( i = MIN; i <= MAX; i++ ) { + len = pow( 10, i ); + iter = ITERATIONS / pow( 10, i-1 ); + for ( j = 0; j < REPEATS; j++ ) { + count += 1; + printf( "# c::%s:ndarray:len=%d\n", NAME, len ); + elapsed = benchmark2( iter, len ); + print_results( iter, elapsed ); + printf( "ok %d benchmark finished\n", count ); + } + } + print_summary( count, count ); +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/zxmy/binding.gyp new file mode 100644 index 000000000000..60dce9d0b31a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/binding.gyp @@ -0,0 +1,265 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Fortran compiler (to override -Dfortran_compiler=): + 'fortran_compiler%': 'gfortran', + + # Fortran compiler flags: + 'fflags': [ + # Specify the Fortran standard to which a program is expected to conform: + '-std=f95', + + # Indicate that the layout is free-form source code: + '-ffree-form', + + # Aggressive optimization: + '-O3', + + # Enable commonly used warning options: + '-Wall', + + # Warn if source code contains problematic language features: + '-Wextra', + + # Warn if a procedure is called without an explicit interface: + '-Wimplicit-interface', + + # Do not transform names of entities specified in Fortran source files by appending underscores (i.e., don't mangle names, thus allowing easier usage in C wrappers): + '-fno-underscoring', + + # Warn if source code contains Fortran 95 extensions and C-language constructs: + '-pedantic', + + # Compile but do not link (output is an object file): + '-c', + ], + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + + # Define custom build actions for particular inputs: + 'rules': [ + { + # Define a rule for processing Fortran files: + 'extension': 'f', + + # Define the pathnames to be used as inputs when performing processing: + 'inputs': [ + # Full path of the current input: + '<(RULE_INPUT_PATH)' + ], + + # Define the outputs produced during processing: + 'outputs': [ + # Store an output object file in a directory for placing intermediate results (only accessible within a single target): + '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)' + ], + + # Define the rule for compiling Fortran based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + + # Rule to compile Fortran on Windows: + { + 'rule_name': 'compile_fortran_windows', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Windows...', + + 'process_outputs_as_sources': 0, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + }, + + # Rule to compile Fortran on non-Windows: + { + 'rule_name': 'compile_fortran_linux', + 'message': 'Compiling Fortran file <(RULE_INPUT_PATH) on Linux...', + + 'process_outputs_as_sources': 1, + + # Define the command-line invocation: + 'action': [ + '<(fortran_compiler)', + '<@(fflags)', + '-fPIC', # generate platform-independent code + '<@(_inputs)', + '-o', + '<@(_outputs)', + ], + } + ], # end condition (OS=="win") + ], # end conditions + }, # end rule (extension=="f") + ], # end rules + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/repl.txt new file mode 100644 index 000000000000..cab55887c141 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/repl.txt @@ -0,0 +1,127 @@ + +{{alias}}( N, x, strideX, y, strideY ) + Multiplies elements of a double-precision complex floating-point strided + array `x` by the corresponding elements of a double-precision complex + floating-point strided array `y` and assigns the results to `y`. + + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. + + Indexing is relative to the first index. To introduce an offset, use typed + array views. + + If `N <= 0`, the function returns `y` unchanged. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + y: Complex128Array + Output array. + + strideY: integer + Stride length for `y`. + + Returns + ------- + y: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufY = [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + > var x = new {{alias:@stdlib/array/complex128}}( bufX ); + > var y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}( x.length, x, 1, y, 1 ) + [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + + // Using `N` and stride parameters: + > bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]; + > x = new {{alias:@stdlib/array/complex128}}( bufX ); + > bufY = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 ]; + > y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}( 2, x, 2, y, 2 ) + [ -9.0, 22.0, 9.0, 10.0, -17.0, 126.0, 13.0, 14.0 ] + + // Using view offsets: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ]; + > var bufY = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0 ]; + > var x0 = new {{alias:@stdlib/array/complex128}}( bufX ); + > var y0 = new {{alias:@stdlib/array/complex128}}( bufY ); + > var offsetX = x0.BYTES_PER_ELEMENT * 1; + > var offsetY = y0.BYTES_PER_ELEMENT * 2; + > var x1 = new {{alias:@stdlib/array/complex128}}( x0.buffer, offsetX ); + > var y1 = new {{alias:@stdlib/array/complex128}}( y0.buffer, offsetY ); + > {{alias}}( 3, x1, 1, y1, 1 ) + [ -15.0, 80.0, -19.0, 148.0, -23.0, 232.0 ] + > y0 + [ 7, 8, 9, 10, -15, 80, -19, 148, -23, 232 ] + + +{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY ) + Multiplies elements of a double-precision complex floating-point strided + array `x` by the corresponding elements of a double-precision complex + floating-point strided array `y` and assigns the results to `y` using + alternative indexing semantics. + + While typed array views mandate a view offset based on the underlying + buffer, the offset parameters support indexing semantics based on starting + indices. + + Parameters + ---------- + N: integer + Number of indexed elements. + + x: Complex128Array + Input array. + + strideX: integer + Stride length for `x`. + + offsetX: integer + Starting index for `x`. + + y: Complex128Array + Output array. + + strideY: integer + Stride length for `y`. + + offsetY: integer + Starting index for `y`. + + Returns + ------- + y: Complex128Array + Output array. + + Examples + -------- + // Standard Usage: + > var bufX = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]; + > var bufY = [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + > var x = new {{alias:@stdlib/array/complex128}}( bufX ); + > var y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 ) + [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + + // Using index offsets: + > bufX = [ 1.0, 0.0, 2.0, 0.0, 3.0, 0.0, 4.0, 0.0, 5.0, 0.0 ]; + > x = new {{alias:@stdlib/array/complex128}}( bufX ); + > bufY = [ 6.0, 0.0, 7.0, 0.0, 8.0, 0.0, 9.0, 0.0, 10.0, 0.0 ]; + > y = new {{alias:@stdlib/array/complex128}}( bufY ); + > {{alias}}.ndarray( 3, x, 1, x.length-3, y, 1, y.length-3 ) + [ 6.0, 0.0, 7.0, 0.0, 24.0, 0.0, 36.0, 0.0, 50.0, 0.0 ] + + See Also + -------- diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/types/index.d.ts new file mode 100644 index 000000000000..b5e9b115512b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/types/index.d.ts @@ -0,0 +1,107 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Complex128Array } from '@stdlib/types/array'; + +/** +* Interface describing `zxmy`. +*/ +interface Routine { + /** + * Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param y - output array + * @param strideY - `y` stride length + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * zxmy( x.length, x, 1, y, 1 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + */ + ( N: number, x: Complex128Array, strideX: number, y: Complex128Array, strideY: number ): Complex128Array; + + /** + * Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. + * + * @param N - number of indexed elements + * @param x - input array + * @param strideX - `x` stride length + * @param offsetX - starting `x` index + * @param y - output array + * @param strideY - `y` stride length + * @param offsetY - starting `y` index + * @returns output array + * + * @example + * var Complex128Array = require( '@stdlib/array/complex128' ); + * + * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + * var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + * + * zxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); + * // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] + */ + ndarray( N: number, x: Complex128Array, strideX: number, offsetX: number, y: Complex128Array, strideY: number, offsetY: number ): Complex128Array; +} + +/** +* Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param N - number of indexed elements +* @param x - input array +* @param strideX - `x` stride length +* @param y - output array +* @param strideY - `y` stride length +* @returns output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* zxmy( x.length, x, 1, y, 1 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* zxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +declare var zxmy: Routine; + + +// EXPORTS // + +export = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/types/test.ts new file mode 100644 index 000000000000..28db973116f5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/docs/types/test.ts @@ -0,0 +1,247 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Complex128Array = require( '@stdlib/array/complex128' ); +import zxmy = require( './index' ); + + +// TESTS // + +// The function returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy( x.length, x, 1, y, 1 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy( '10', x, 1, y, 1 ); // $ExpectError + zxmy( true, x, 1, y, 1 ); // $ExpectError + zxmy( false, x, 1, y, 1 ); // $ExpectError + zxmy( null, x, 1, y, 1 ); // $ExpectError + zxmy( undefined, x, 1, y, 1 ); // $ExpectError + zxmy( [], x, 1, y, 1 ); // $ExpectError + zxmy( {}, x, 1, y, 1 ); // $ExpectError + zxmy( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Complex128Array... +{ + const y = new Complex128Array( 10 ); + + zxmy( 10, 10, 1, y, 1 ); // $ExpectError + zxmy( 10, '10', 1, y, 1 ); // $ExpectError + zxmy( 10, true, 1, y, 1 ); // $ExpectError + zxmy( 10, false, 1, y, 1 ); // $ExpectError + zxmy( 10, null, 1, y, 1 ); // $ExpectError + zxmy( 10, undefined, 1, y, 1 ); // $ExpectError + zxmy( 10, [ '1' ], 1, y, 1 ); // $ExpectError + zxmy( 10, {}, 1, y, 1 ); // $ExpectError + zxmy( 10, ( x: number ): number => x, 1, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy( x.length, x, '10', y, 1 ); // $ExpectError + zxmy( x.length, x, true, y, 1 ); // $ExpectError + zxmy( x.length, x, false, y, 1 ); // $ExpectError + zxmy( x.length, x, null, y, 1 ); // $ExpectError + zxmy( x.length, x, undefined, y, 1 ); // $ExpectError + zxmy( x.length, x, [], y, 1 ); // $ExpectError + zxmy( x.length, x, {}, y, 1 ); // $ExpectError + zxmy( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + + zxmy( 10, x, 1, 10, 1 ); // $ExpectError + zxmy( 10, x, 1, '10', 1 ); // $ExpectError + zxmy( 10, x, 1, true, 1 ); // $ExpectError + zxmy( 10, x, 1, false, 1 ); // $ExpectError + zxmy( 10, x, 1, null, 1 ); // $ExpectError + zxmy( 10, x, 1, undefined, 1 ); // $ExpectError + zxmy( 10, x, 1, [ '1' ], 1 ); // $ExpectError + zxmy( 10, x, 1, {}, 1 ); // $ExpectError + zxmy( 10, x, 1, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fifth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy( x.length, x, 1, y, '10' ); // $ExpectError + zxmy( x.length, x, 1, y, true ); // $ExpectError + zxmy( x.length, x, 1, y, false ); // $ExpectError + zxmy( x.length, x, 1, y, null ); // $ExpectError + zxmy( x.length, x, 1, y, undefined ); // $ExpectError + zxmy( x.length, x, 1, y, [] ); // $ExpectError + zxmy( x.length, x, 1, y, {} ); // $ExpectError + zxmy( x.length, x, 1, y, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy(); // $ExpectError + zxmy( x.length ); // $ExpectError + zxmy( x.length, x ); // $ExpectError + zxmy( x.length, x, 1 ); // $ExpectError + zxmy( x.length, x, 1, y ); // $ExpectError + zxmy( x.length, x, 1, y, 1, 10 ); // $ExpectError +} + +// Attached to the main export is an `ndarray` method which returns a Complex128Array... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType Complex128Array +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Complex128Array... +{ + const y = new Complex128Array( 10 ); + + zxmy.ndarray( 10, 10, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, '10', 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, true, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, false, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, null, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, undefined, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, [ '1' ], 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, {}, 1, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Complex128Array... +{ + const x = new Complex128Array( 10 ); + + zxmy.ndarray( 10, x, 1, 0, 10, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, '10', 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, true, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, false, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, null, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, undefined, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, [ '1' ], 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, {}, 1, 0 ); // $ExpectError + zxmy.ndarray( 10, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Complex128Array( 10 ); + const y = new Complex128Array( 10 ); + + zxmy.ndarray(); // $ExpectError + zxmy.ndarray( x.length ); // $ExpectError + zxmy.ndarray( x.length, x ); // $ExpectError + zxmy.ndarray( x.length, x, 1 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError + zxmy.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/c/example.c new file mode 100644 index 000000000000..b40764072178 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/c/example.c @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxmy.h" +#include "stdlib/complex/float64/ctor.h" +#include "stdlib/complex/float64/real.h" +#include "stdlib/complex/float64/imag.h" +#include + +int main( void ) { + // Create strided arrays: + const stdlib_complex128_t x[] = { + stdlib_complex128( 1.0, 2.0 ), + stdlib_complex128( 3.0, 4.0 ), + stdlib_complex128( 5.0, 6.0 ), + stdlib_complex128( 7.0, 8.0 ) + }; + stdlib_complex128_t y[] = { + stdlib_complex128( 2.0, 3.0 ), + stdlib_complex128( 4.0, 5.0 ), + stdlib_complex128( 6.0, 7.0 ), + stdlib_complex128( 8.0, 9.0 ) + }; + + // Specify the number of indexed elements: + const int N = 4; + + // Specify strides: + const int strideX = 1; + const int strideY = 1; + + // Multiply `x` by `y` and assign the results to `y`: + stdlib_strided_zxmy( N, x, strideX, y, strideY ); + + // Print the result: + for ( int i = 0; i < N; i++ ) { + printf( "y[ %i ] = %lf + %lfi\n", i, stdlib_complex128_real( y[ i ] ), stdlib_complex128_imag( y[ i ] ) ); + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/index.js new file mode 100644 index 000000000000..4cf4cf48b366 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var logEach = require( '@stdlib/console/log-each' ); +var zxmy = require( './../lib' ); + +var xbuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var ybuf = discreteUniform( 20, -100, 100, { + 'dtype': 'float64' +}); +var x = new Complex128Array( xbuf.buffer ); +var y = new Complex128Array( ybuf.buffer ); + +zxmy( x.length, x, 1, y, 1 ); +logEach( '%s', y ); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/zxmy/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* var zxmy = require( '@stdlib/blas/ext/base/zxmy' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* zxmy.ndarray( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ + +// MODULES // + +var join = require( 'path' ).join; +var tryRequire = require( '@stdlib/utils/try-require' ); +var isError = require( '@stdlib/assert/is-error' ); +var main = require( './main.js' ); + + +// MAIN // + +var zxmy; +var tmp = tryRequire( join( __dirname, './native.js' ) ); +if ( isError( tmp ) ) { + zxmy = main; +} else { + zxmy = tmp; +} + + +// EXPORTS // + +module.exports = zxmy; + +// exports: { "ndarray": "zxmy.ndarray" } diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/main.js new file mode 100644 index 000000000000..abb553a2116e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/main.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zxmy = require( './zxmy.js' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +setReadOnly( zxmy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/native.js new file mode 100644 index 000000000000..c5fad7f7f81f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/native.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var zxmy = require( './zxmy.native.js' ); +var ndarray = require( './ndarray.native.js' ); + + +// MAIN // + +setReadOnly( zxmy, 'ndarray', ndarray ); + + +// EXPORTS // + +module.exports = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/ndarray.js new file mode 100644 index 000000000000..9cd98fdbab10 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/ndarray.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable max-len */ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var cmul = require( '@stdlib/complex/float64/base/mul' ).assign; + + +// VARIABLES // + +var M = 5; + + +// MAIN // + +/** +* Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* zxmy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function zxmy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var xview; + var yview; + var ix; + var iy; + var sx; + var sy; + var m; + var i; + + if ( N <= 0 ) { + return y; + } + + // Reinterpret the complex input arrays as real-valued arrays: + xview = reinterpret( x, 0 ); + yview = reinterpret( y, 0 ); + + // Adjust the strides and offsets according to the real-valued arrays: + ix = offsetX * 2; + iy = offsetY * 2; + sx = strideX * 2; + sy = strideY * 2; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX === 1 && strideY === 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + cmul( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + ix += sx; + iy += sy; + } + } + if ( N < M ) { + return y; + } + for ( i = m; i < N; i += M ) { + cmul( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + cmul( xview[ ix+2 ], xview[ ix+3 ], yview[ iy+2 ], yview[ iy+3 ], yview, 1, iy+2 ); + cmul( xview[ ix+4 ], xview[ ix+5 ], yview[ iy+4 ], yview[ iy+5 ], yview, 1, iy+4 ); + cmul( xview[ ix+6 ], xview[ ix+7 ], yview[ iy+6 ], yview[ iy+7 ], yview, 1, iy+6 ); + cmul( xview[ ix+8 ], xview[ ix+9 ], yview[ iy+8 ], yview[ iy+9 ], yview, 1, iy+8 ); + ix += M * 2; + iy += M * 2; + } + return y; + } + for ( i = 0; i < N; i++ ) { + cmul( xview[ ix ], xview[ ix+1 ], yview[ iy ], yview[ iy+1 ], yview, 1, iy ); + ix += sx; + iy += sy; + } + return y; +} + + +// EXPORTS // + +module.exports = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/ndarray.native.js new file mode 100644 index 000000000000..8c03aabe8c90 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/ndarray.native.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {NonNegativeInteger} offsetX - starting `x` index +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @param {NonNegativeInteger} offsetY - starting `y` index +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* zxmy( x.length, x, 1, 0, y, 1, 0 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function zxmy( N, x, strideX, offsetX, y, strideY, offsetY ) { + var viewX = reinterpret( x, 0 ); + var viewY = reinterpret( y, 0 ); + addon.ndarray( N, viewX, strideX, offsetX, viewY, strideY, offsetY ); + return y; +} + + +// EXPORTS // + +module.exports = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/zxmy.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/zxmy.js new file mode 100644 index 000000000000..c21a89aa395c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/zxmy.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var stride2offset = require( '@stdlib/strided/base/stride2offset' ); +var ndarray = require( './ndarray.js' ); + + +// MAIN // + +/** +* Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* zxmy( x.length, x, 1, y, 1 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function zxmy( N, x, strideX, y, strideY ) { + return ndarray( N, x, strideX, stride2offset( N, strideX ), y, strideY, stride2offset( N, strideY ) ); // eslint-disable-line max-len +} + + +// EXPORTS // + +module.exports = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/zxmy.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/zxmy.native.js new file mode 100644 index 000000000000..538a28d6e66d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/lib/zxmy.native.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param {PositiveInteger} N - number of indexed elements +* @param {Complex128Array} x - input array +* @param {integer} strideX - `x` stride length +* @param {Complex128Array} y - output array +* @param {integer} strideY - `y` stride length +* @returns {Complex128Array} output array +* +* @example +* var Complex128Array = require( '@stdlib/array/complex128' ); +* +* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); +* var y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); +* +* zxmy( x.length, x, 1, y, 1 ); +* // y => [ -4.0, 7.0, -8.0, 31.0, -12.0, 71.0 ] +*/ +function zxmy( N, x, strideX, y, strideY ) { + var viewX = reinterpret( x, 0 ); + var viewY = reinterpret( y, 0 ); + addon( N, viewX, strideX, viewY, strideY ); + return y; +} + + +// EXPORTS // + +module.exports = zxmy; diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/zxmy/manifest.json new file mode 100644 index 000000000000..8b5cc06f5c8e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/manifest.json @@ -0,0 +1,108 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/mul", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset", + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-int64", + "@stdlib/napi/argv-strided-complex128array" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/mul", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/mul", + "@stdlib/complex/float64/real", + "@stdlib/complex/float64/imag", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + }, + { + "task": "build", + "wasm": true, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/blas/base/shared", + "@stdlib/complex/float64/base/mul", + "@stdlib/complex/float64/ctor", + "@stdlib/strided/base/stride2offset" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/package.json b/lib/node_modules/@stdlib/blas/ext/base/zxmy/package.json new file mode 100644 index 000000000000..faa620313d7c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/package.json @@ -0,0 +1,82 @@ +{ + "name": "@stdlib/blas/ext/base/zxmy", + "version": "0.0.0", + "description": "Multiply elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assign the results to `y`.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "browser": "./lib/main.js", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "extended", + "linear", + "algebra", + "subroutines", + "multiply", + "transform", + "strided", + "array", + "ndarray", + "vector", + "xmy", + "zxmy", + "complex", + "complex128", + "complex128array", + "float64", + "double" + ], + "__stdlib__": { + "wasm": false + } +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/addon.c new file mode 100644 index 000000000000..3b6545f4815c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/addon.c @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxmy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/napi/export.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_int64.h" +#include "stdlib/napi/argv_strided_complex128array.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, Y, N, strideY, argv, 3 ); + API_SUFFIX(stdlib_strided_zxmy)( N, (stdlib_complex128_t *)X, strideX, (stdlib_complex128_t *)Y, strideY ); + return NULL; +} + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon_method( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 7 ); + STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); + STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); + STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); + STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 ); + STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, X, N, strideX, argv, 1 ); + STDLIB_NAPI_ARGV_STRIDED_COMPLEX128ARRAY( env, Y, N, strideY, argv, 4 ); + API_SUFFIX(stdlib_strided_zxmy_ndarray)( N, (stdlib_complex128_t *)X, strideX, offsetX, (stdlib_complex128_t *)Y, strideY, offsetY ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method ) diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/main.c new file mode 100644 index 000000000000..e0025a3c52f8 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/src/main.c @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/blas/ext/base/zxmy.h" +#include "stdlib/blas/base/shared.h" +#include "stdlib/complex/float64/base/mul.h" +#include "stdlib/strided/base/stride2offset.h" + +static const CBLAS_INT M = 5; + +/** +* Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y`. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param Y output array +* @param strideY stride length for `Y` +*/ +void API_SUFFIX(stdlib_strided_zxmy)( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, stdlib_complex128_t *Y, const CBLAS_INT strideY ) { + CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); + CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY ); + API_SUFFIX(stdlib_strided_zxmy_ndarray)( N, X, strideX, ox, Y, strideY, oy ); +} + +/** +* Multiplies elements of a double-precision complex floating-point strided array `x` by the corresponding elements of a double-precision complex floating-point strided array `y` and assigns the results to `y` using alternative indexing semantics. +* +* @param N number of indexed elements +* @param X input array +* @param strideX stride length for `X` +* @param offsetX starting index for `X` +* @param Y output array +* @param strideY stride length for `Y` +* @param offsetY starting index for `Y` +*/ +void API_SUFFIX(stdlib_strided_zxmy_ndarray)( const CBLAS_INT N, const stdlib_complex128_t *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, stdlib_complex128_t *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { + CBLAS_INT ix; + CBLAS_INT iy; + CBLAS_INT m; + CBLAS_INT i; + + if ( N <= 0 ) { + return; + } + ix = offsetX; + iy = offsetY; + + // Use loop unrolling if both strides are equal to `1`... + if ( strideX == 1 && strideY == 1 ) { + m = N % M; + + // If we have a remainder, run a clean-up loop... + if ( m > 0 ) { + for ( i = 0; i < m; i++ ) { + Y[ iy ] = stdlib_base_complex128_mul( X[ ix ], Y[ iy ] ); + ix += strideX; + iy += strideY; + } + } + if ( N < M ) { + return; + } + for ( i = m; i < N; i += M ) { + Y[ iy ] = stdlib_base_complex128_mul( X[ ix ], Y[ iy ] ); + Y[ iy+1 ] = stdlib_base_complex128_mul( X[ ix+1 ], Y[ iy+1 ] ); + Y[ iy+2 ] = stdlib_base_complex128_mul( X[ ix+2 ], Y[ iy+2 ] ); + Y[ iy+3 ] = stdlib_base_complex128_mul( X[ ix+3 ], Y[ iy+3 ] ); + Y[ iy+4 ] = stdlib_base_complex128_mul( X[ ix+4 ], Y[ iy+4 ] ); + ix += M; + iy += M; + } + return; + } + for ( i = 0; i < N; i++ ) { + Y[ iy ] = stdlib_base_complex128_mul( X[ ix ], Y[ iy ] ); + ix += strideX; + iy += strideY; + } + return; +} diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.js new file mode 100644 index 000000000000..cc1dfc32ee2e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var proxyquire = require( 'proxyquire' ); +var IS_BROWSER = require( '@stdlib/assert/is-browser' ); +var zxmy = require( './../lib' ); + + +// VARIABLES // + +var opts = { + 'skip': IS_BROWSER +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { + t.strictEqual( typeof zxmy.ndarray, 'function', 'method is a function' ); + t.end(); +}); + +tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) { + var zxmy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zxmy, mock, 'returns native implementation' ); + t.end(); + + function tryRequire() { + return mock; + } + + function mock() { + // Mock... + } +}); + +tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) { + var zxmy; + var main; + + main = require( './../lib/zxmy.js' ); + + zxmy = proxyquire( './../lib', { + '@stdlib/utils/try-require': tryRequire + }); + + t.strictEqual( zxmy, main, 'returns JavaScript implementation' ); + t.end(); + + function tryRequire() { + return new Error( 'Cannot find module' ); + } +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.ndarray.js new file mode 100644 index 000000000000..e3cd00eaf3b5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.ndarray.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cmul = require( '@stdlib/complex/float64/base/mul' ); +var zxmy = require( './../lib/ndarray.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', function test( t ) { + t.strictEqual( zxmy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex128Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = zxmy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxmy( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxmy( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + zxmy( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + zxmy( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex128Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + zxmy( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( 3, x1, 1, 0, y1, 1, 0 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.ndarray.native.js new file mode 100644 index 000000000000..28e8ee73c2b5 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.ndarray.native.js @@ -0,0 +1,330 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cmul = require( '@stdlib/complex/float64/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zxmy = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var opts = { + 'skip': ( zxmy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 7', opts, function test( t ) { + t.strictEqual( zxmy.length, 7, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex128Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = zxmy( x.length, x, 1, 0, y, 1, 0 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxmy( 0, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxmy( -4, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + zxmy( 3, x, 2, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + zxmy( 3, x, 1, 0, y, 2, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex128Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + zxmy( 3, x, -2, 4, y, -1, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( 3, x1, 1, 0, y1, 1, 0 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, 0, y, 1, 0 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.zxmy.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.zxmy.js new file mode 100644 index 000000000000..f09cbbc6aee2 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.zxmy.js @@ -0,0 +1,321 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cmul = require( '@stdlib/complex/float64/base/mul' ); +var zxmy = require( './../lib/zxmy.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', function test( t ) { + t.strictEqual( zxmy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex128Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = zxmy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxmy( 0, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxmy( -4, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + zxmy( 3, x, 2, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + zxmy( 3, x, 1, y, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex128Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + zxmy( 3, x, -2, y, -1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( 3, x1, 1, y1, 1 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.zxmy.native.js b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.zxmy.native.js new file mode 100644 index 000000000000..51a2f2e19773 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/ext/base/zxmy/test/test.zxmy.native.js @@ -0,0 +1,330 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable stdlib/empty-line-before-comment */ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isSameComplex128Array = require( '@stdlib/assert/is-same-complex128array' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex128 = require( '@stdlib/complex/float64/ctor' ); +var cmul = require( '@stdlib/complex/float64/base/mul' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var zxmy = tryRequire( resolve( __dirname, './../lib/zxmy.native.js' ) ); +var opts = { + 'skip': ( zxmy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof zxmy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 5', opts, function test( t ) { + t.strictEqual( zxmy.length, 5, 'has expected arity' ); + t.end(); +}); + +tape( 'the function multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 5.0, 6.0, 7.0, 8.0 ] ); + expected = new Complex128Array([ + // (1.0*5.0-2.0*6.0) + (1.0*6.0+2.0*5.0)i + -7.0, + 16.0, + // (3.0*7.0-4.0*8.0) + (3.0*8.0+4.0*7.0)i + -11.0, + 52.0 + ]); + + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns a reference to the output array', opts, function test( t ) { + var out; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + out = zxmy( x.length, x, 1, y, 1 ); + + t.strictEqual( out, y, 'same reference' ); + t.end(); +}); + +tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `y` unchanged', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] ); + y = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array( [ 4.0, 5.0, 6.0, 7.0 ] ); + + zxmy( 0, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + zxmy( -4, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports an `x` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 0 + 2.0, // 0 + 0.0, + 0.0, + 5.0, // 1 + 6.0, // 1 + 0.0, + 0.0, + 9.0, // 2 + 10.0 // 2 + ]); + y = new Complex128Array( [ 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] ); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (5.0*4.0-6.0*5.0) + (5.0*5.0+6.0*4.0)i + -10.0, + 49.0, + // (9.0*6.0-10.0*7.0) + (9.0*7.0+10.0*6.0)i + -16.0, + 123.0 + ]); + + zxmy( 3, x, 2, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports a `y` stride', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); + y = new Complex128Array([ + 2.0, // 0 + 3.0, // 0 + 4.0, + 5.0, + 6.0, // 1 + 7.0, // 1 + 8.0, + 9.0, + 10.0, // 2 + 11.0 // 2 + ]); + expected = new Complex128Array([ + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + 4.0, + 5.0, + // (3.0*6.0-4.0*7.0) + (3.0*7.0+4.0*6.0)i + -10.0, + 45.0, + 8.0, + 9.0, + // (5.0*10.0-6.0*11.0) + (5.0*11.0+6.0*10.0)i + -16.0, + 115.0 + ]); + + zxmy( 3, x, 1, y, 2 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports negative strides', opts, function test( t ) { + var expected; + var x; + var y; + + x = new Complex128Array([ + 1.0, // 2 + 2.0, // 2 + 0.0, + 0.0, + 3.0, // 1 + 4.0, // 1 + 0.0, + 0.0, + 5.0, // 0 + 6.0 // 0 + ]); + y = new Complex128Array([ + 4.0, // 2 + 5.0, // 2 + 3.0, // 1 + 4.0, // 1 + 2.0, // 0 + 3.0 // 0 + ]); + expected = new Complex128Array([ + // (1.0*4.0-2.0*5.0) + (1.0*5.0+2.0*4.0)i + -6.0, + 13.0, + // (3.0*3.0-4.0*4.0) + (3.0*4.0+4.0*3.0)i + -7.0, + 24.0, + // (5.0*2.0-6.0*3.0) + (5.0*3.0+6.0*2.0)i + -8.0, + 27.0 + ]); + + zxmy( 3, x, -2, y, -1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function supports view offsets', opts, function test( t ) { + var expected; + var x0; + var y0; + var x1; + var y1; + + x0 = new Complex128Array([ + 10.0, + 0.0, + 1.0, // 0 + 2.0, // 0 + 3.0, // 1 + 4.0, // 1 + 5.0, // 2 + 6.0 // 2 + ]); + y0 = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + 2.0, // 0 + 3.0, // 0 + 4.0, // 1 + 5.0, // 1 + 6.0, // 2 + 7.0 // 2 + ]); + + x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); + y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 ); + + expected = new Complex128Array([ + 10.0, + 0.0, + 10.0, + 0.0, + // (1.0*2.0-2.0*3.0) + (1.0*3.0+2.0*2.0)i + -4.0, + 7.0, + // (3.0*4.0-4.0*5.0) + (3.0*5.0+4.0*4.0)i + -8.0, + 31.0, + // (5.0*6.0-6.0*7.0) + (5.0*7.0+6.0*6.0)i + -12.0, + 71.0 + ]); + + zxmy( 3, x1, 1, y1, 1 ); + t.strictEqual( isSameComplex128Array( y0, expected ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if both strides are equal to `1`, the function efficiently multiplies elements of `x` by the corresponding elements of `y` and assigns the results to `y`', opts, function test( t ) { + var expected; + var xv; + var yv; + var x; + var y; + var i; + + x = new Complex128Array( 100 ); + y = new Complex128Array( 100 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + x = new Complex128Array( 240 ); + y = new Complex128Array( 240 ); + expected = new Complex128Array( x.length ); + for ( i = 0; i < x.length; i++ ) { + xv = new Complex128( i, 0.0 ); + yv = new Complex128( x.length - i, 0.0 ); + x.set( xv, i ); + y.set( yv, i ); + expected.set( cmul( xv, yv ), i ); + } + zxmy( x.length, x, 1, y, 1 ); + t.strictEqual( isSameComplex128Array( y, expected ), true, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/lib/index.js b/lib/node_modules/@stdlib/blas/lib/index.js index af1b825edd0b..4f81b57dc567 100644 --- a/lib/node_modules/@stdlib/blas/lib/index.js +++ b/lib/node_modules/@stdlib/blas/lib/index.js @@ -36,6 +36,15 @@ var setReadOnly = require( '@stdlib/utils/define-read-only-property' ); */ var ns = {}; +/** +* @name asum +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/asum} +*/ +setReadOnly( ns, 'asum', require( '@stdlib/blas/asum' ) ); + /** * @name base * @memberof ns @@ -90,6 +99,15 @@ setReadOnly( ns, 'gdot', require( '@stdlib/blas/gdot' ) ); */ setReadOnly( ns, 'gswap', require( '@stdlib/blas/gswap' ) ); +/** +* @name nrm2 +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/blas/nrm2} +*/ +setReadOnly( ns, 'nrm2', require( '@stdlib/blas/nrm2' ) ); + /** * @name sdot * @memberof ns diff --git a/lib/node_modules/@stdlib/blas/nrm2/README.md b/lib/node_modules/@stdlib/blas/nrm2/README.md new file mode 100644 index 000000000000..b26d23740942 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/README.md @@ -0,0 +1,231 @@ + + +# nrm2 + +> Compute the L2-norm along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. + +
+ +## Usage + +```javascript +var nrm2 = require( '@stdlib/blas/nrm2' ); +``` + +#### nrm2( x\[, options] ) + +Computes the L2-norm along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 1.0, -2.0, 2.0 ] ); + +var y = nrm2( x ); +// returns [ 3.0 ] +``` + +The function has the following parameters: + +- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. +- **options**: function options (_optional_). + +The function accepts the following options: + +- **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. +- **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. Must be a real-valued floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. +- **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [ndarray][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`. + +By default, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform a reduction over specific dimensions, provide a `dims` option. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 3.0, 0.0, 4.0, 0.0 ], { + 'shape': [ 2, 2 ], + 'order': 'row-major' +}); +// returns [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] + +var y = nrm2( x, { + 'dims': [ 0 ] +}); +// returns [ 5.0, 0.0 ] + +y = nrm2( x, { + 'dims': [ 1 ] +}); +// returns [ 3.0, 4.0 ] + +y = nrm2( x, { + 'dims': [ 0, 1 ] +}); +// returns [ 5.0 ] +``` + +By default, the function excludes reduced dimensions from the output [ndarray][@stdlib/ndarray/ctor]. To include the reduced dimensions as singleton dimensions, set the `keepdims` option to `true`. + +```javascript +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 3.0, 0.0, 4.0, 0.0 ], { + 'shape': [ 2, 2 ], + 'order': 'row-major' +}); +// returns [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ] + +var y = nrm2( x, { + 'dims': [ 0 ], + 'keepdims': true +}); +// returns [ [ 5.0, 0.0 ] ] + +y = nrm2( x, { + 'dims': [ 1 ], + 'keepdims': true +}); +// returns [ [ 3.0 ], [ 4.0 ] ] + +y = nrm2( x, { + 'dims': [ 0, 1 ], + 'keepdims': true +}); +// returns [ [ 5.0 ] ] +``` + +By default, the function returns an [ndarray][@stdlib/ndarray/ctor] having a [data type][@stdlib/ndarray/dtypes] determined by the function's output data type [policy][@stdlib/ndarray/output-dtype-policies]. To override the default behavior, set the `dtype` option. + +```javascript +var getDType = require( '@stdlib/ndarray/dtype' ); +var array = require( '@stdlib/ndarray/array' ); + +var x = array( [ 1.0, -2.0, 2.0 ], { + 'dtype': 'generic' +}); + +var y = nrm2( x, { + 'dtype': 'float64' +}); +// returns [ 3.0 ] + +var dt = String( getDType( y ) ); +// returns 'float64' +``` + +#### nrm2.assign( x, out\[, options] ) + +Computes the L2-norm along one or more [ndarray][@stdlib/ndarray/ctor] dimensions and assigns results to a provided output [ndarray][@stdlib/ndarray/ctor]. + +```javascript +var array = require( '@stdlib/ndarray/array' ); +var zeros = require( '@stdlib/ndarray/zeros' ); + +var x = array( [ 1.0, -2.0, 2.0 ] ); +var y = zeros( [] ); + +var out = nrm2.assign( x, y ); +// returns [ 3.0 ] + +var bool = ( out === y ); +// returns true +``` + +The method has the following parameters: + +- **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. +- **out**: output [ndarray][@stdlib/ndarray/ctor]. +- **options**: function options (_optional_). + +The method accepts the following options: + +- **dims**: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. + +
+ + + +
+ +## Notes + +- Setting the `keepdims` option to `true` can be useful when wanting to ensure that the output [ndarray][@stdlib/ndarray/ctor] is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with ndarrays having the same shape as the input [ndarray][@stdlib/ndarray/ctor]. +- The output data type [policy][@stdlib/ndarray/output-dtype-policies] only applies to the main function and specifies that, by default, the function must return an [ndarray][@stdlib/ndarray/ctor] having a real-valued floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. For the `assign` method, the output [ndarray][@stdlib/ndarray/ctor] is allowed to have any supported output [data type][@stdlib/ndarray/dtypes]. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/uniform' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var nrm2 = require( '@stdlib/blas/nrm2' ); + +// Generate an array of random numbers: +var x = uniform( [ 5, 5 ], -10.0, 10.0 ); +console.log( ndarray2array( x ) ); + +// Perform a reduction: +var y = nrm2( x, { + 'dims': [ 0 ] +}); + +// Resolve the output array data type: +var dt = getDType( y ); +console.log( dt ); + +// Print the results: +console.log( ndarray2array( y ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + +[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes + +[@stdlib/ndarray/output-dtype-policies]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/output-dtype-policies + +[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes + +
+ + diff --git a/lib/node_modules/@stdlib/blas/nrm2/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/blas/nrm2/benchmark/benchmark.assign.js new file mode 100644 index 000000000000..3755b234afc1 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/benchmark/benchmark.assign.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/uniform' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var nrm2 = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var out = zeros( [], options ); + var x = uniform( [ len ], -50.0, 50.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var o; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + o = nrm2.assign( x, out ); + if ( typeof o !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( o.get() ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:assign:dtype=%s,len=%d', pkg, options.dtype, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/nrm2/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/nrm2/benchmark/benchmark.js new file mode 100644 index 000000000000..adcdf529b36f --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/benchmark/benchmark.js @@ -0,0 +1,103 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var uniform = require( '@stdlib/random/uniform' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var nrm2 = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'float64' +}; + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} len - array length +* @returns {Function} benchmark function +*/ +function createBenchmark( len ) { + var x = uniform( [ len ], -50.0, 50.0, options ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var o; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + o = nrm2( x ); + if ( typeof o !== 'object' ) { + b.fail( 'should return an ndarray' ); + } + } + b.toc(); + if ( isnan( o.get() ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var len; + var min; + var max; + var f; + var i; + + min = 1; // 10^min + max = 6; // 10^max + + for ( i = min; i <= max; i++ ) { + len = pow( 10, i ); + f = createBenchmark( len ); + bench( format( '%s:dtype=%s,len=%d', pkg, options.dtype, len ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/blas/nrm2/docs/repl.txt b/lib/node_modules/@stdlib/blas/nrm2/docs/repl.txt new file mode 100644 index 000000000000..6da321ed4603 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/docs/repl.txt @@ -0,0 +1,74 @@ + +{{alias}}( x[, options] ) + Computes the L2-norm along one or more ndarray dimensions. + + Parameters + ---------- + x: ndarray + Input array. Must have a numeric or "generic" data type. + + options: Object (optional) + Function options. + + options.dtype: string|DataType (optional) + Output array data type. Must be a real-valued floating-point or + "generic" data type. + + options.dims: Array (optional) + List of dimensions over which to perform a reduction. If not provided, + the function performs a reduction over all elements in a provided input + ndarray. + + options.keepdims: boolean (optional) + Boolean indicating whether the reduced dimensions should be included in + the returned ndarray as singleton dimensions. Default: false. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ 1.0, -2.0, 2.0 ] ); + > var y = {{alias}}( x ) + [ 3.0 ] + + +{{alias}}.assign( x, out[, options] ) + Computes the L2-norm along one or more ndarray dimensions and assigns + results to a provided output ndarray. + + Parameters + ---------- + x: ndarray + Input array. Must have a numeric or "generic" data type. + + out: ndarray + Output array. + + options: Object (optional) + Function options. + + options.dims: Array (optional) + List of dimensions over which to perform a reduction. If not provided, + the function performs a reduction over all elements in a provided input + ndarray. + + Returns + ------- + out: ndarray + Output array. + + Examples + -------- + > var x = {{alias:@stdlib/ndarray/array}}( [ 1.0, -2.0, 2.0 ] ); + > var out = {{alias:@stdlib/ndarray/zeros}}( [] ); + > var y = {{alias}}.assign( x, out ) + [ 3.0 ] + > var bool = ( out === y ) + true + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/blas/nrm2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/nrm2/docs/types/index.d.ts new file mode 100644 index 000000000000..4755b4afd9de --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/docs/types/index.d.ts @@ -0,0 +1,139 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; +import { RealFloatingPointAndGenericDataType as DataType, typedndarray } from '@stdlib/types/ndarray'; + +/** +* Input array. +*/ +type InputArray = typedndarray; + +/** +* Output array. +*/ +type OutputArray = typedndarray; + +/** +* Interface defining "base" options. +*/ +interface BaseOptions { + /** + * List of dimensions over which to perform a reduction. + */ + dims?: ArrayLike; +} + +/** +* Interface defining options. +*/ +interface Options extends BaseOptions { + /** + * Output array data type. + */ + dtype?: DataType; + + /** + * Boolean indicating whether the reduced dimensions should be included in the returned array as singleton dimensions. Default: `false`. + */ + keepdims?: boolean; +} + +/** +* Interface for performing a reduction on an ndarray. +*/ +interface Unary { + /** + * Computes the L2-norm along one or more ndarray dimensions. + * + * @param x - input ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * + * var y = nrm2( x ); + * // returns [ 3.0 ] + */ + ( x: InputArray, options?: Options ): OutputArray; // NOTE: we lose type specificity here, but retaining specificity would likely be difficult and/or tedious to completely enumerate, as the output ndarray data type is dependent on how `x` interacts with output data type policy and whether that policy has been overridden by `options.dtype`. + + /** + * Computes the L2-norm along one or more ndarray dimensions and assigns results to a provided output ndarray. + * + * @param x - input ndarray + * @param out - output ndarray + * @param options - function options + * @returns output ndarray + * + * @example + * var array = require( '@stdlib/ndarray/array' ); + * var zeros = require( '@stdlib/ndarray/zeros' ); + * + * var x = array( [ 1.0, -2.0, 2.0 ] ); + * var y = zeros( [] ); + * + * var out = nrm2.assign( x, y ); + * // returns [ 3.0 ] + * + * var bool = ( out === y ); + * // returns true + */ + assign = OutputArray>( x: InputArray, out: U, options?: BaseOptions ): U; +} + +/** +* Computes the L2-norm along one or more ndarray dimensions. +* +* @param x - input ndarray +* @param options - function options +* @returns output ndarray +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* +* var x = array( [ 1.0, -2.0, 2.0 ] ); +* +* var y = nrm2( x ); +* // returns [ 3.0 ] +* +* @example +* var array = require( '@stdlib/ndarray/array' ); +* var zeros = require( '@stdlib/ndarray/zeros' ); +* +* var x = array( [ 1.0, -2.0, 2.0 ] ); +* var y = zeros( [] ); +* +* var out = nrm2.assign( x, y ); +* // returns [ 3.0 ] +* +* var bool = ( out === y ); +* // returns true +*/ +declare const nrm2: Unary; + + +// EXPORTS // + +export = nrm2; diff --git a/lib/node_modules/@stdlib/blas/nrm2/docs/types/test.ts b/lib/node_modules/@stdlib/blas/nrm2/docs/types/test.ts new file mode 100644 index 000000000000..4ed199277da9 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/docs/types/test.ts @@ -0,0 +1,230 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/* eslint-disable space-in-parens */ + +import zeros = require( '@stdlib/ndarray/zeros' ); +import empty = require( '@stdlib/ndarray/empty' ); +import nrm2 = require( './index' ); + + +// TESTS // + +// The function returns an ndarray... +{ + nrm2( empty( [ 2, 2 ], { 'dtype': 'float64' } ) ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'float64' } ), {} ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'float32' } ) ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'float32' } ), {} ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'int32' } ) ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'int32' } ), {} ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'complex128' } ) ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'complex128' } ), {} ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'complex64' } ) ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'complex64' } ), {} ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'generic' } ) ); // $ExpectType OutputArray + nrm2( empty( [ 2, 2 ], { 'dtype': 'generic' } ), {} ); // $ExpectType OutputArray +} + +// The compiler throws an error if the function is provided a first argument which is not an ndarray... +{ + nrm2( '5' ); // $ExpectError + nrm2( 5 ); // $ExpectError + nrm2( true ); // $ExpectError + nrm2( false ); // $ExpectError + nrm2( null ); // $ExpectError + nrm2( void 0 ); // $ExpectError + nrm2( {} ); // $ExpectError + nrm2( ( x: number ): number => x ); // $ExpectError + + nrm2( '5', {} ); // $ExpectError + nrm2( 5, {} ); // $ExpectError + nrm2( true, {} ); // $ExpectError + nrm2( false, {} ); // $ExpectError + nrm2( null, {} ); // $ExpectError + nrm2( void 0, {} ); // $ExpectError + nrm2( {}, {} ); // $ExpectError + nrm2( ( x: number ): number => x, {} ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not an object... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2( x, '5' ); // $ExpectError + nrm2( x, true ); // $ExpectError + nrm2( x, false ); // $ExpectError + nrm2( x, null ); // $ExpectError + nrm2( x, [] ); // $ExpectError + nrm2( x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `dtype` option... +{ + const x = empty( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2( x, { 'dtype': '5' } ); // $ExpectError + nrm2( x, { 'dtype': 5 } ); // $ExpectError + nrm2( x, { 'dtype': true } ); // $ExpectError + nrm2( x, { 'dtype': false } ); // $ExpectError + nrm2( x, { 'dtype': null } ); // $ExpectError + nrm2( x, { 'dtype': [] } ); // $ExpectError + nrm2( x, { 'dtype': {} } ); // $ExpectError + nrm2( x, { 'dtype': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `keepdims` option... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2( x, { 'keepdims': '5' } ); // $ExpectError + nrm2( x, { 'keepdims': 5 } ); // $ExpectError + nrm2( x, { 'keepdims': null } ); // $ExpectError + nrm2( x, { 'keepdims': [] } ); // $ExpectError + nrm2( x, { 'keepdims': {} } ); // $ExpectError + nrm2( x, { 'keepdims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid `dims` option... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2( x, { 'dims': '5' } ); // $ExpectError + nrm2( x, { 'dims': 5 } ); // $ExpectError + nrm2( x, { 'dims': true } ); // $ExpectError + nrm2( x, { 'dims': false } ); // $ExpectError + nrm2( x, { 'dims': null } ); // $ExpectError + nrm2( x, { 'dims': {} } ); // $ExpectError + nrm2( x, { 'dims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2(); // $ExpectError + nrm2( x, {}, {} ); // $ExpectError +} + +// Attached to the function is an `assign` method which returns an ndarray... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2.assign( x, x ); // $ExpectType float64ndarray + nrm2.assign( x, x, {} ); // $ExpectType float64ndarray +} + +// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2.assign( '5', x ); // $ExpectError + nrm2.assign( 5, x ); // $ExpectError + nrm2.assign( true, x ); // $ExpectError + nrm2.assign( false, x ); // $ExpectError + nrm2.assign( null, x ); // $ExpectError + nrm2.assign( void 0, x ); // $ExpectError + nrm2.assign( {}, x ); // $ExpectError + nrm2.assign( ( x: number ): number => x, x ); // $ExpectError + + nrm2.assign( '5', x, {} ); // $ExpectError + nrm2.assign( 5, x, {} ); // $ExpectError + nrm2.assign( true, x, {} ); // $ExpectError + nrm2.assign( false, x, {} ); // $ExpectError + nrm2.assign( null, x, {} ); // $ExpectError + nrm2.assign( void 0, x, {} ); // $ExpectError + nrm2.assign( {}, x, {} ); // $ExpectError + nrm2.assign( ( x: number ): number => x, x, {} ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a second argument which is not an ndarray... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2.assign( x, '5' ); // $ExpectError + nrm2.assign( x, 5 ); // $ExpectError + nrm2.assign( x, true ); // $ExpectError + nrm2.assign( x, false ); // $ExpectError + nrm2.assign( x, null ); // $ExpectError + nrm2.assign( x, void 0 ); // $ExpectError + nrm2.assign( x, ( x: number ): number => x ); // $ExpectError + + nrm2.assign( x, '5', {} ); // $ExpectError + nrm2.assign( x, 5, {} ); // $ExpectError + nrm2.assign( x, true, {} ); // $ExpectError + nrm2.assign( x, false, {} ); // $ExpectError + nrm2.assign( x, null, {} ); // $ExpectError + nrm2.assign( x, void 0, {} ); // $ExpectError + nrm2.assign( x, ( x: number ): number => x, {} ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a third argument which is not an object... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2.assign( x, x, '5' ); // $ExpectError + nrm2.assign( x, x, true ); // $ExpectError + nrm2.assign( x, x, false ); // $ExpectError + nrm2.assign( x, x, null ); // $ExpectError + nrm2.assign( x, x, [] ); // $ExpectError + nrm2.assign( x, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an invalid `dims` option... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2.assign( x, x, { 'dims': '5' } ); // $ExpectError + nrm2.assign( x, x, { 'dims': 5 } ); // $ExpectError + nrm2.assign( x, x, { 'dims': true } ); // $ExpectError + nrm2.assign( x, x, { 'dims': false } ); // $ExpectError + nrm2.assign( x, x, { 'dims': null } ); // $ExpectError + nrm2.assign( x, x, { 'dims': {} } ); // $ExpectError + nrm2.assign( x, x, { 'dims': ( x: number ): number => x } ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an unsupported number of arguments... +{ + const x = zeros( [ 2, 2 ], { + 'dtype': 'float64' + }); + + nrm2.assign(); // $ExpectError + nrm2.assign( x ); // $ExpectError + nrm2.assign( x, x, {}, {} ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/blas/nrm2/examples/index.js b/lib/node_modules/@stdlib/blas/nrm2/examples/index.js new file mode 100644 index 000000000000..4c998168e02a --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/uniform' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var nrm2 = require( './../lib' ); + +// Generate an array of random numbers: +var x = uniform( [ 5, 5 ], -10.0, 10.0 ); +console.log( ndarray2array( x ) ); + +// Perform a reduction: +var y = nrm2( x, { + 'dims': [ 0 ] +}); + +// Resolve the output array data type: +var dt = getDType( y ); +console.log( dt ); + +// Print the results: +console.log( ndarray2array( y ) ); diff --git a/lib/node_modules/@stdlib/blas/nrm2/lib/index.js b/lib/node_modules/@stdlib/blas/nrm2/lib/index.js new file mode 100644 index 000000000000..e76ace961c12 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the L2-norm along one or more ndarray dimensions. +* +* @module @stdlib/blas/nrm2 +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* var nrm2 = require( '@stdlib/blas/nrm2' ); +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 0.0, 1.0, -2.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* // Define the shape of the input array: +* var sh = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create an input ndarray: +* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' ); +* +* // Perform reduction: +* var out = nrm2( x ); +* // returns [ 3.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; + +// exports: { "assign": "main.assign" } diff --git a/lib/node_modules/@stdlib/blas/nrm2/lib/main.js b/lib/node_modules/@stdlib/blas/nrm2/lib/main.js new file mode 100644 index 000000000000..68ae34f2c78d --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/lib/main.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var dtypes = require( '@stdlib/ndarray/dtypes' ); +var gnrm2 = require( '@stdlib/blas/base/ndarray/gnrm2' ); +var dnrm2 = require( '@stdlib/blas/base/ndarray/dnrm2' ); +var snrm2 = require( '@stdlib/blas/base/ndarray/snrm2' ); +var dznrm2 = require( '@stdlib/blas/base/ndarray/dznrm2' ); +var scnrm2 = require( '@stdlib/blas/base/ndarray/scnrm2' ); +var factory = require( '@stdlib/ndarray/base/unary-reduce-strided1d-dispatch-factory' ); + + +// VARIABLES // + +var idtypes = dtypes( 'numeric_and_generic' ); +var odtypes = dtypes( 'real_floating_point_and_generic' ); +var policies = { + 'output': 'real_floating_point_and_generic', + 'casting': 'none' +}; +var table = { + 'types': [ + 'float64', // input + 'float32', // input + 'complex128', // input + 'complex64' // input + ], + 'fcns': [ + dnrm2, + snrm2, + dznrm2, + scnrm2 + ], + 'default': gnrm2 +}; + + +// MAIN // + +/** +* Computes the L2-norm along one or more ndarray dimensions. +* +* @name nrm2 +* @type {Function} +* @param {ndarray} x - input ndarray +* @param {Options} [options] - function options +* @param {IntegerArray} [options.dims] - list of dimensions over which to perform a reduction +* @param {boolean} [options.keepdims=false] - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions +* @param {*} [options.dtype] - output ndarray data type +* @throws {TypeError} first argument must be an ndarray-like object +* @throws {TypeError} options argument must be an object +* @throws {RangeError} dimension indices must not exceed input ndarray bounds +* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions +* @throws {Error} must provide valid options +* @returns {ndarray} output ndarray +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var ndarray = require( '@stdlib/ndarray/ctor' ); +* +* // Create a data buffer: +* var xbuf = new Float64Array( [ 0.0, 1.0, -2.0, 0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] ); +* +* // Define the shape of the input array: +* var sh = [ 3, 1, 2 ]; +* +* // Define the array strides: +* var sx = [ 4, 4, 1 ]; +* +* // Define the index offset: +* var ox = 1; +* +* // Create an input ndarray: +* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' ); +* +* // Perform reduction: +* var out = nrm2( x ); +* // returns [ 3.0 ] +*/ +var nrm2 = factory( table, [ idtypes ], odtypes, policies ); + + +// EXPORTS // + +module.exports = nrm2; diff --git a/lib/node_modules/@stdlib/blas/nrm2/package.json b/lib/node_modules/@stdlib/blas/nrm2/package.json new file mode 100644 index 000000000000..422c770f7db6 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/blas/nrm2", + "version": "0.0.0", + "description": "Compute the L2-norm along one or more ndarray dimensions.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "blas", + "level 1", + "linear", + "algebra", + "subroutines", + "nrm2", + "norm", + "l2-norm", + "euclidean", + "magnitude", + "vector", + "array", + "ndarray" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/blas/nrm2/test/test.assign.js b/lib/node_modules/@stdlib/blas/nrm2/test/test.assign.js new file mode 100644 index 000000000000..5796080c841c --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/test/test.assign.js @@ -0,0 +1,765 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var empty = require( '@stdlib/ndarray/empty' ); +var emptyLike = require( '@stdlib/ndarray/empty-like' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var nrm2 = require( './../lib' ).assign; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof nrm2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value, out ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value, out, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value, out ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type (options)', function test( t ) { + var values; + var out; + var i; + + out = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value, out, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an ndarray-like object', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, value ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an ndarray-like object (options)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a third argument which is not an object', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, out, value ); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [ 'a' ], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [ 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ -10 ], + [ 20 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 1, 2 ], + [ 0, 1, 2, 3 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) { + var values; + var out; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + out = zeros( [], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 0 ], + [ 1, 1 ], + [ 0, 1, 0 ], + [ 1, 0, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, out, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided an output array which has an invalid shape (default)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 2, 2 ], + [ 2 ], + [ 4, 4 ], + [ 4 ], + [ 1 ], + [ 1, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + var out = zeros( value, { + 'dtype': 'generic' + }); + nrm2( x, out ); + }; + } +}); + +tape( 'the function throws an error if provided an output array which has an invalid shape (all dimensions)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 2, 2 ], + [ 2 ], + [ 4, 4 ], + [ 4 ], + [ 1 ], + [ 1, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + var out = zeros( value, { + 'dtype': 'generic' + }); + nrm2( x, out, { + 'dims': [ 0, 1 ] + }); + }; + } +}); + +tape( 'the function throws an error if provided an output array which has an invalid shape (some dimensions)', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [], + [ 4, 4 ], + [ 4 ], + [ 1 ], + [ 1, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + var out = zeros( value, { + 'dtype': 'generic' + }); + nrm2( x, out, { + 'dims': [ 0 ] + }); + }; + } +}); + +tape( 'the function performs a reduction on an ndarray (default, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = nrm2( x, out ); + expected = 5.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (default, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = nrm2( x, out ); + expected = 5.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = nrm2( x, out, { + 'dims': [ 0, 1 ] + }); + expected = 5.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [] + }); + + actual = nrm2( x, out, { + 'dims': [ 0, 1 ] + }); + expected = 5.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [ 2, 2 ] + }); + + actual = nrm2( x, out, { + 'dims': [] + }); + expected = [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [ 2, 2 ] + }); + + actual = nrm2( x, out, { + 'dims': [] + }); + expected = [ [ 3.0, 4.0 ], [ 0.0, 0.0 ] ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = nrm2( x, out, { + 'dims': [ 0 ] + }); + expected = [ 5.0, 0.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = nrm2( x, out, { + 'dims': [ 1 ] + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = nrm2( x, out, { + 'dims': [ 0 ] + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + out = emptyLike( x, { + 'shape': [ 2 ] + }); + + actual = nrm2( x, out, { + 'dims': [ 1 ] + }); + expected = [ 5.0, 0.0 ]; + + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex128)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = new Complex128Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex128', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = empty( [], { + 'dtype': 'float64' + }); + + actual = nrm2( x, out ); + expected = 5.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex64)', function test( t ) { + var expected; + var actual; + var xbuf; + var out; + var x; + + xbuf = new Complex64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + out = empty( [], { + 'dtype': 'float32' + }); + + actual = nrm2( x, out ); + expected = 5.0; + + t.strictEqual( actual, out, 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/nrm2/test/test.js b/lib/node_modules/@stdlib/blas/nrm2/test/test.js new file mode 100644 index 000000000000..59838084192e --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/test/test.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isMethod = require( '@stdlib/assert/is-method' ); +var nrm2 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof nrm2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is an `assign` method', function test( t ) { + t.strictEqual( isMethod( nrm2, 'assign' ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/blas/nrm2/test/test.main.js b/lib/node_modules/@stdlib/blas/nrm2/test/test.main.js new file mode 100644 index 000000000000..2409b88ba386 --- /dev/null +++ b/lib/node_modules/@stdlib/blas/nrm2/test/test.main.js @@ -0,0 +1,795 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' ); +var ndarray = require( '@stdlib/ndarray/ctor' ); +var zeros = require( '@stdlib/ndarray/zeros' ); +var empty = require( '@stdlib/ndarray/empty' ); +var Complex128Array = require( '@stdlib/array/complex128' ); +var Complex64Array = require( '@stdlib/array/complex64' ); +var ndarray2array = require( '@stdlib/ndarray/to-array' ); +var getDType = require( '@stdlib/ndarray/dtype' ); +var getShape = require( '@stdlib/ndarray/shape' ); +var getOrder = require( '@stdlib/ndarray/order' ); +var nrm2 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof nrm2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (options)', function test( t ) { + var values; + var i; + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type', function test( t ) { + var values; + var i; + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value ); + }; + } +}); + +tape( 'the function throws an error if provided a first argument which is not an ndarray-like object having a supported data type (options)', function test( t ) { + var values; + var i; + + values = [ + empty( [ 2, 2 ], { + 'dtype': 'bool' + }) + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( value, {} ); + }; + } +}); + +tape( 'the function throws an error if provided a second argument which is not an object', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [], + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, value ); + }; + } +}); + +tape( 'the function throws an error if provided a `dtype` option which is not a supported data type', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + 'foo', + 'bar', + 'beep', + 'boop' + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, { + 'dtype': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `keepdims` option which is not a boolean', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, { + 'keepdims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + '5', + 5, + NaN, + true, + false, + null, + void 0, + [ 'a' ], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ -10 ], + [ 0, 20 ], + [ 20 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 1, 2 ], + [ 0, 1, 2, 3 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) { + var values; + var x; + var i; + + x = zeros( [ 2, 2 ], { + 'dtype': 'generic' + }); + + values = [ + [ 0, 0 ], + [ 1, 1 ], + [ 0, 1, 0 ], + [ 1, 0, 1 ] + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + nrm2( x, { + 'dims': value + }); + }; + } +}); + +tape( 'the function performs a reduction on an ndarray (default, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x ); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (default, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x ); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [ 0, 1 ] + }); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [ 0, 1 ], + 'keepdims': false + }); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [ 0, 1 ], + 'keepdims': true + }); + expected = [ [ 5.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (all dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [ 0, 1 ] + }); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [ 0, 1 ], + 'keepdims': false + }); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [ 0, 1 ], + 'keepdims': true + }); + expected = [ [ 5.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [], + 'keepdims': false + }); + expected = [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [], + 'keepdims': true + }); + expected = [ [ 3.0, 0.0 ], [ 4.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (no dimensions, column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [], + 'keepdims': false + }); + expected = [ [ 3.0, 4.0 ], [ 0.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [], + 'keepdims': true + }); + expected = [ [ 3.0, 4.0 ], [ 0.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (row-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [ 0 ], + 'keepdims': false + }); + expected = [ 5.0, 0.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [ 0 ], + 'keepdims': true + }); + expected = [ [ 5.0, 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [ 1 ], + 'keepdims': false + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dims': [ 1 ], + 'keepdims': true + }); + expected = [ [ 3.0 ], [ 4.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying reduction dimensions (column-major)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [ 0 ], + 'keepdims': false + }); + expected = [ 3.0, 4.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [ 0 ], + 'keepdims': true + }); + expected = [ [ 3.0, 4.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 1, 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [ 1 ], + 'keepdims': false + }); + expected = [ 5.0, 0.0 ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dims': [ 1 ], + 'keepdims': true + }); + expected = [ [ 5.0 ], [ 0.0 ] ]; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'generic', 'returns expected value' ); + t.deepEqual( getShape( actual ), [ 2, 1 ], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying the output array data type', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x, { + 'dtype': 'float64' + }); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + xbuf = [ 3.0, 0.0, 4.0, 0.0 ]; + x = new ndarray( 'generic', xbuf, [ 2, 2 ], [ 1, 2 ], 0, 'column-major' ); + + actual = nrm2( x, { + 'dtype': 'float64' + }); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( getOrder( actual ), getOrder( x ), 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex128)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex128Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex128', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x ); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float64', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function performs a reduction on an ndarray (complex64)', function test( t ) { + var expected; + var actual; + var xbuf; + var x; + + xbuf = new Complex64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] ); + x = new ndarray( 'complex64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' ); + + actual = nrm2( x ); + expected = 5.0; + + t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' ); + t.strictEqual( String( getDType( actual ) ), 'float32', 'returns expected value' ); + t.deepEqual( getShape( actual ), [], 'returns expected value' ); + t.strictEqual( actual.get(), expected, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/constants/float32/e/README.md b/lib/node_modules/@stdlib/constants/float32/e/README.md index 30c74a9f504e..08ce1d6826b7 100644 --- a/lib/node_modules/@stdlib/constants/float32/e/README.md +++ b/lib/node_modules/@stdlib/constants/float32/e/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# E +# FLOAT32_E > The mathematical constant [_e_][e]. @@ -27,15 +27,15 @@ limitations under the License. ## Usage ```javascript -var E = require( '@stdlib/constants/float32/e' ); +var FLOAT32_E = require( '@stdlib/constants/float32/e' ); ``` -#### E +#### FLOAT32_E The mathematical constant [_e_][e], also known as Euler's number or Napier's constant. [_e_][e] is the base of the natural logarithm. ```javascript -var bool = ( E === 2.7182817459106445 ); +var bool = ( FLOAT32_E === 2.7182817459106445 ); // returns true ``` @@ -52,9 +52,9 @@ var bool = ( E === 2.7182817459106445 ); ```javascript -var E = require( '@stdlib/constants/float32/e' ); +var FLOAT32_E = require( '@stdlib/constants/float32/e' ); -console.log( E ); +console.log( FLOAT32_E ); // => 2.7182817459106445 ``` diff --git a/lib/node_modules/@stdlib/constants/float32/e/docs/types/index.d.ts b/lib/node_modules/@stdlib/constants/float32/e/docs/types/index.d.ts index a4af37e9df15..248a15a2a3fd 100644 --- a/lib/node_modules/@stdlib/constants/float32/e/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/constants/float32/e/docs/types/index.d.ts @@ -22,12 +22,12 @@ * Euler's number. * * @example -* var e = E; +* var e = FLOAT32_E; * // returns 2.7182817459106445 */ -declare const E: number; +declare const FLOAT32_E: number; // EXPORTS // -export = E; +export = FLOAT32_E; diff --git a/lib/node_modules/@stdlib/constants/float32/e/docs/types/test.ts b/lib/node_modules/@stdlib/constants/float32/e/docs/types/test.ts index 763c1963b354..16d394f58c95 100644 --- a/lib/node_modules/@stdlib/constants/float32/e/docs/types/test.ts +++ b/lib/node_modules/@stdlib/constants/float32/e/docs/types/test.ts @@ -16,7 +16,7 @@ * limitations under the License. */ -import E = require( './index' ); +import FLOAT32_E = require( './index' ); // TESTS // @@ -24,5 +24,5 @@ import E = require( './index' ); // The export is a number... { // eslint-disable-next-line @typescript-eslint/no-unused-expressions - E; // $ExpectType number + FLOAT32_E; // $ExpectType number } diff --git a/lib/node_modules/@stdlib/constants/float32/e/examples/index.js b/lib/node_modules/@stdlib/constants/float32/e/examples/index.js index 3ac8e579c54e..797348125c01 100644 --- a/lib/node_modules/@stdlib/constants/float32/e/examples/index.js +++ b/lib/node_modules/@stdlib/constants/float32/e/examples/index.js @@ -18,7 +18,7 @@ 'use strict'; -var E = require( './../lib' ); +var FLOAT32_E = require( './../lib' ); -console.log( E ); +console.log( FLOAT32_E ); // => 2.7182817459106445 diff --git a/lib/node_modules/@stdlib/constants/float32/e/lib/index.js b/lib/node_modules/@stdlib/constants/float32/e/lib/index.js index 6e01b0e44dc5..ce9f8e588b85 100644 --- a/lib/node_modules/@stdlib/constants/float32/e/lib/index.js +++ b/lib/node_modules/@stdlib/constants/float32/e/lib/index.js @@ -45,9 +45,9 @@ var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' ); * @see [OEIS]{@link https://oeis.org/A001113} * @see [Wikipedia]{@link https://en.wikipedia.org/wiki/E_(mathematical_constant)} */ -var E = float64ToFloat32( 2.718281828459045 ); +var FLOAT32_E = float64ToFloat32( 2.718281828459045 ); // EXPORTS // -module.exports = E; +module.exports = FLOAT32_E; diff --git a/lib/node_modules/@stdlib/constants/float32/e/test/test.js b/lib/node_modules/@stdlib/constants/float32/e/test/test.js index f34ecc589d50..2bb92564541b 100644 --- a/lib/node_modules/@stdlib/constants/float32/e/test/test.js +++ b/lib/node_modules/@stdlib/constants/float32/e/test/test.js @@ -21,18 +21,18 @@ // MODULES // var tape = require( 'tape' ); -var E = require( './../lib' ); +var FLOAT32_E = require( './../lib' ); // TESTS // tape( 'main export is a number', function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof E, 'number', 'main export is a number' ); + t.strictEqual( typeof FLOAT32_E, 'number', 'main export is a number' ); t.end(); }); tape( 'export is a single-precision floating-point number equal to 2.7182817459106445', function test( t ) { - t.strictEqual( E, 2.7182817459106445, 'returns expected value' ); + t.strictEqual( FLOAT32_E, 2.7182817459106445, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/constants/float64/fourth-root-eps/README.md b/lib/node_modules/@stdlib/constants/float64/fourth-root-eps/README.md index 3e6d2e254472..9d181374eedd 100644 --- a/lib/node_modules/@stdlib/constants/float64/fourth-root-eps/README.md +++ b/lib/node_modules/@stdlib/constants/float64/fourth-root-eps/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# FOURTH_ROOT_EPS +# FLOAT64_FOURTH_ROOT_EPS > [Fourth root][nth-root] of [double-precision floating-point epsilon][@stdlib/constants/float64/eps]. @@ -27,15 +27,15 @@ limitations under the License. ## Usage ```javascript -var FOURTH_ROOT_EPS = require( '@stdlib/constants/float64/fourth-root-eps' ); +var FLOAT64_FOURTH_ROOT_EPS = require( '@stdlib/constants/float64/fourth-root-eps' ); ``` -#### FOURTH_ROOT_EPS +#### FLOAT64_FOURTH_ROOT_EPS [Fourth root][nth-root] of [double-precision floating-point epsilon][@stdlib/constants/float64/eps]. ```javascript -var bool = ( FOURTH_ROOT_EPS === 0.0001220703125 ); +var bool = ( FLOAT64_FOURTH_ROOT_EPS === 0.0001220703125 ); // returns true ``` @@ -50,9 +50,9 @@ var bool = ( FOURTH_ROOT_EPS === 0.0001220703125 ); ```javascript -var FOURTH_ROOT_EPS = require( '@stdlib/constants/float64/fourth-root-eps' ); +var FLOAT64_FOURTH_ROOT_EPS = require( '@stdlib/constants/float64/fourth-root-eps' ); -var out = FOURTH_ROOT_EPS; +var out = FLOAT64_FOURTH_ROOT_EPS; // returns 0.0001220703125 ``` diff --git a/lib/node_modules/@stdlib/constants/float64/gamma-lanczos-g/README.md b/lib/node_modules/@stdlib/constants/float64/gamma-lanczos-g/README.md index 686ff4476f5d..2e7afb9c0624 100644 --- a/lib/node_modules/@stdlib/constants/float64/gamma-lanczos-g/README.md +++ b/lib/node_modules/@stdlib/constants/float64/gamma-lanczos-g/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# GAMMA_LANCZOS_G +# FLOAT64_GAMMA_LANCZOS_G > Arbitrary constant `g` to be used in Lanczos approximation functions. @@ -33,15 +33,15 @@ limitations under the License. ## Usage ```javascript -var GAMMA_LANCZOS_G = require( '@stdlib/constants/float64/gamma-lanczos-g' ); +var FLOAT64_GAMMA_LANCZOS_G = require( '@stdlib/constants/float64/gamma-lanczos-g' ); ``` -#### GAMMA_LANCZOS_G +#### FLOAT64_GAMMA_LANCZOS_G Arbitrary constant `g` to be used in [Lanczos approximation][lanczos-approximation] functions. ```javascript -var bool = ( GAMMA_LANCZOS_G === 10.900511 ); +var bool = ( FLOAT64_GAMMA_LANCZOS_G === 10.900511 ); // returns true ``` @@ -56,9 +56,9 @@ var bool = ( GAMMA_LANCZOS_G === 10.900511 ); ```javascript -var GAMMA_LANCZOS_G = require( '@stdlib/constants/float64/gamma-lanczos-g' ); +var FLOAT64_GAMMA_LANCZOS_G = require( '@stdlib/constants/float64/gamma-lanczos-g' ); -console.log( GAMMA_LANCZOS_G ); +console.log( FLOAT64_GAMMA_LANCZOS_G ); // => 10.900511 ``` diff --git a/lib/node_modules/@stdlib/constants/float64/log10-e/lib/index.js b/lib/node_modules/@stdlib/constants/float64/log10-e/lib/index.js index 4a79ea3d0454..afaf8807864f 100644 --- a/lib/node_modules/@stdlib/constants/float64/log10-e/lib/index.js +++ b/lib/node_modules/@stdlib/constants/float64/log10-e/lib/index.js @@ -39,7 +39,7 @@ * @type {number} * @default 0.4342944819032518 * @see [OEIS]{@link https://oeis.org/A001113} -* @see [Wikipedia]{@link https://en.wikipedia.org/wiki/E_%27mathematical_constant%28} +* @see [Wikipedia]{@link https://en.wikipedia.org/wiki/E_(mathematical_constant)} */ var LOG10E = 4.34294481903251827651128918916605082294397005803666566114453783165864649208870774729224949338431748318706106745e-01; // eslint-disable-line max-len diff --git a/lib/node_modules/@stdlib/constants/float64/log2-e/lib/index.js b/lib/node_modules/@stdlib/constants/float64/log2-e/lib/index.js index 31486b72ae76..20b753dbe352 100644 --- a/lib/node_modules/@stdlib/constants/float64/log2-e/lib/index.js +++ b/lib/node_modules/@stdlib/constants/float64/log2-e/lib/index.js @@ -39,7 +39,7 @@ * @type {number} * @default 1.4426950408889634 * @see [OEIS]{@link https://oeis.org/A001113} -* @see [Wikipedia]{@link https://en.wikipedia.org/wiki/E_%27mathematical_constant%28} +* @see [Wikipedia]{@link https://en.wikipedia.org/wiki/E_(mathematical_constant)} */ var LOG2E = 1.442695040888963407359924681001892137426645954152985934135; diff --git a/lib/node_modules/@stdlib/constants/float64/nan/README.md b/lib/node_modules/@stdlib/constants/float64/nan/README.md index fb4aed288650..e605da490f8a 100644 --- a/lib/node_modules/@stdlib/constants/float64/nan/README.md +++ b/lib/node_modules/@stdlib/constants/float64/nan/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# NAN +# FLOAT64_NAN > [Double-precision floating-point][ieee754] `NaN`. diff --git a/lib/node_modules/@stdlib/constants/float64/ninf/README.md b/lib/node_modules/@stdlib/constants/float64/ninf/README.md index f5fa27bc67b6..c90b13fd9ffa 100644 --- a/lib/node_modules/@stdlib/constants/float64/ninf/README.md +++ b/lib/node_modules/@stdlib/constants/float64/ninf/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# NINF +# FLOAT64_NINF > [Double-precision floating-point][ieee754] negative infinity. diff --git a/lib/node_modules/@stdlib/constants/float64/pinf/README.md b/lib/node_modules/@stdlib/constants/float64/pinf/README.md index cc7dc4db3798..35852909706b 100644 --- a/lib/node_modules/@stdlib/constants/float64/pinf/README.md +++ b/lib/node_modules/@stdlib/constants/float64/pinf/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# PINF +# FLOAT64_PINF > [Double-precision floating-point][ieee754] positive infinity. diff --git a/lib/node_modules/@stdlib/constants/float64/pinf/lib/index.js b/lib/node_modules/@stdlib/constants/float64/pinf/lib/index.js index 5759d844b535..8c15c27cee6a 100644 --- a/lib/node_modules/@stdlib/constants/float64/pinf/lib/index.js +++ b/lib/node_modules/@stdlib/constants/float64/pinf/lib/index.js @@ -48,7 +48,7 @@ * @default Number.POSITIVE_INFINITY * @see [IEEE 754]{@link https://en.wikipedia.org/wiki/IEEE_754-1985} */ -var FLOAT64_PINF = Number.POSITIVE_INFINITY; // eslint-disable-line stdlib/require-globals +var FLOAT64_PINF = Number.POSITIVE_INFINITY; // EXPORTS // diff --git a/lib/node_modules/@stdlib/datasets/cmudict/datapackage.json b/lib/node_modules/@stdlib/datasets/cmudict/datapackage.json index 87562e5cec7c..9ce2c0ba799a 100644 --- a/lib/node_modules/@stdlib/datasets/cmudict/datapackage.json +++ b/lib/node_modules/@stdlib/datasets/cmudict/datapackage.json @@ -92,10 +92,6 @@ } ], "keywords": [ - "stdlib", - "datasets", - "dataset", - "data", "words", "speech", "language", diff --git a/lib/node_modules/@stdlib/datasets/stopwords-en/datapackage.json b/lib/node_modules/@stdlib/datasets/stopwords-en/datapackage.json index ffea016e2e94..4e0275ec4b8c 100644 --- a/lib/node_modules/@stdlib/datasets/stopwords-en/datapackage.json +++ b/lib/node_modules/@stdlib/datasets/stopwords-en/datapackage.json @@ -37,5 +37,5 @@ "english", "en" ], - "license": "CC0 AND PDDL-1.0" + "license": "PDDL-1.0 AND CC0-1.0" } diff --git a/lib/node_modules/@stdlib/error/tools/database/data/data.csv b/lib/node_modules/@stdlib/error/tools/database/data/data.csv index 9aaef17dd440..eb7f59e26178 100644 --- a/lib/node_modules/@stdlib/error/tools/database/data/data.csv +++ b/lib/node_modules/@stdlib/error/tools/database/data/data.csv @@ -1279,3 +1279,7 @@ "Kc","invalid argument. Third argument must be a valid shape. Value: `%s`.","TypeError" "Kd","invalid argument. Fifth argument must be a recognized/supported data type. Value: `%s`.","TypeError" "Ke","invalid argument. Second argument must be a supported distance metric. Value: `%s`.","TypeError" +"Kf","invalid argument. Must provide an integer on the interval [-(2^63), 2^63-1]. Value: `%s`.","TypeError" +"Kg","invalid argument. Must provide an integer on the interval [-(2^53-1), 2^53-1]. Value: `%s`.","TypeError" +"Kh","invalid argument. First argument must be a string encoding an integer on the interval [0, 2^64). Value: `%s`.","RangeError" +"Ki","invalid argument. Second argument must be an integer on the interval [2, 36]. Value: `%s`.","RangeError" diff --git a/lib/node_modules/@stdlib/error/tools/database/data/data.json b/lib/node_modules/@stdlib/error/tools/database/data/data.json index 98b1ddeb8c07..3ac965d99158 100644 --- a/lib/node_modules/@stdlib/error/tools/database/data/data.json +++ b/lib/node_modules/@stdlib/error/tools/database/data/data.json @@ -1 +1 @@ -{"10":"invalid operation. Cannot reset a REPL which has already closed.","11":"invalid operation. Cannot clear a REPL which has already closed.","12":"invalid operation. Cannot clear the line of a REPL which has already closed.","13":"invalid operation. Cannot clear the command buffer of a REPL which has already closed.","14":"invalid argument. Provided command either does not contain an `await` expression or contains a top-level `return` which is not allowed.","15":"invalid argument. Must provide a program AST node.","16":"invalid invocation. Insufficient arguments. Must provide a REPL instance.","17":"invalid operation. No presentation to reload. Use the `load()` method to load a presentation.","18":"invalid operation. No presentation file to watch. Use the `load()` method to load a presentation.","19":"unexpected error. Encountered a \"rename\" event for the source presentation file. No longer watching source presentation file for changes.","20":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user is watching, an access token.","21":"unexpected error. Unable to resolve package directory as unable to find a `package.json` in a parent directory.","22":"invalid argument. Source code does not contain JSDoc comment with function options.","23":"unexpected error. Unable to resolve root project directory.","24":"invalid argument. An iterator must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","25":"invalid argument. Callback must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","26":"invalid argument. Array-like object arguments must have a length which is a multiple of two. Length: `%u`.","27":"invalid argument. Array-like object and typed array arguments must have a length which is a multiple of two. Length: `%u`.","28":"invalid argument. ArrayBuffer byte length must be a multiple of `%u`. Byte length: `%u`.","29":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","30":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.","31":"invalid argument. Fifth argument must be a function. Value: `%s`.","32":"invalid argument. Fourth argument must be a function. Value: `%s`.","33":"invalid argument. Second argument must be either an integer (starting index) or a callback function. Value: `%s`.","34":"invalid argument. Third argument must be either an integer (ending index) or a callback function. Value: `%s`.","35":"invalid argument. Second argument must be either an integer (starting view index) or a callback function. Value: `%s`.","36":"invalid argument. Third argument must be either an integer (ending view index) or a callback function. Value: `%s`.","37":"invalid argument. Second argument must be a recognized data type. Value: `%s`.","38":"invalid argument. First argument must be array-like. Value: `%s`.","39":"invalid argument. Second argument must be a string. Value: `%s`.","40":"invalid argument. Must provide either a Date object, a JavaScript timestamp (i.e., a nonnegative integer), or a date string. Value: `%s`.","41":"invalid option. Unrecognized rounding mode. Option: `%s`.","42":"invalid argument. Third argument must be either a nonnegative integer or an options object. Value: `%s`.","43":"invalid argument. Fourth argument must be an object. Value: `%s`.","44":"invalid argument. First argument must an iterator protocol-compliant object. Value: `%s`.","45":"invalid argument. Second argument must be a positive integer. Value: `%s`.","46":"invalid argument. First argument must be an iterator protocol-compliant object. Value: `%s`.","47":"invalid argument. Must provide an object. Value: `%s`.","48":"invalid argument. Object property values must be functions. Key: `%s`. Value: `%s`.","49":"invalid argument. First argument must be a number. Value: `%s`.","50":"invalid option. Second `%s` parameter option must be a positive integer. Option: `%s`.","51":"invalid argument. First argument must be an array. Value: `%s`.","52":"invalid argument. First argument must be an array of length `%u`. Value: `%s`.","53":"invalid argument. First argument must be an array of length %u. Value: `%s`.","54":"unexpected error. Scaling weight vector by nonpositive value, likely due to too large value of eta * lambda. Value: `%f`.","55":"invalid argument. Second argument must be a boolean. Value: `%s`.","56":"invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.","57":"invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.","58":"invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.","59":"invalid option. `%s` option must be a recognized casting mode. Option: `%s`.","60":"invalid argument. Input string must have a length equal to %u. Value: `%s`.","61":"invalid assignment. `%s` must be a boolean. Value: `%s`.","62":"invalid assignment. `%s` must be a string. Value: `%s`.","63":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","64":"invalid assignment. `%s` must be a positive number. Value: `%s`.","65":"invalid assignment. `%s` must be either an array of strings or an empty array. Value: `%s`.","66":"invalid assignment. `%s` must be a number or number array. Value: `%s`.","67":"invalid assignment. A `%s` must be a number on the interval: [0, 1]. Value: `%f`.","68":"invalid assignment. `%s` must be a string or a string array. Value: `%s`","69":"invalid assignment. Unsupported/unrecognized line style. Must be one of the following: \"%s\". Value: `%s`.","70":"invalid argument. Must provide a Uint32Array. Value: `%s`.","71":"invalid argument. First argument must be a positive number. Value: `%s`.","72":"invalid argument. Second argument must be a positive number. Value: `%s`.","73":"invalid argument. Second argument must be a probability. Value: `%s`.","74":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%s`.","75":"invalid option. `%s` option must have a `MIN` property specifying the minimum possible pseudorandom integer value.","76":"invalid option. `%s` option must have a `MAX` property specifying the maximum possible pseudorandom integer value.","77":"invalid argument. First argument must be an integer and not NaN. Value: `%s`.","78":"invalid argument. Second argument must be an integer and not NaN. Value: `%s`.","79":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d,%d]`.","80":"invalid argument. First argument must be either a string containing presentation text or an options object specifying a presentation file to load. Value: `%s`.","81":"invalid argument. Second argument must be an options object. Value: `%s`.","82":"invalid argument. Invalid presentation identifier. Must be either a string or nonnegative integer. Value: `%s`.","83":"invalid argument. Workspace name already exists. Value: `%s`.","84":"invalid argument. Must provide a string, regular expression, nonnegative integer, or an array of nonnegative integers. Value: `%s`.","85":"invalid argument. Unrecognized tutorial name. Value: `%s`.","86":"invalid argument. Documentation argument must be a string. Value: `%s`.","87":"invalid option. `%s` option must be a regular expression. Option: `%s`.","88":"internal error. Unrecognized pattern type: `%s`.","89":"invalid option. `%s` option must be a readable stream. Option: `%s`.","90":"invalid argument. Denominator degrees of freedom must be a positive number. Value: `%s`.","91":"invalid argument. Scale parameter must be a number. Value: `%s`.","92":"invalid argument. Mean parameter `%s` must be a probability. Value: `%s`.","93":"invalid argument. Population size must be a nonnegative integer. Value: `%s`.","94":"invalid argument. Subpopulation size must be a nonnegative integer. Value: `%s`.","95":"invalid argument. Number of draws must be a nonnegative integer. Value: `%s`.","96":"invalid assignment. Must be a nonnegative integer. Value: `%s`.","97":"invalid assignment. Must be larger than or equal to %u. Value: `%u`.","98":"invalid assignment. Must be less than or equal to %u. Value: `%u`.","99":"invalid argument. Number of trials until experiment is stopped must be a positive number. Value: `%s`.","00":"not implemented","01":"invalid invocation. `this` context must be a constructor.","02":"invalid invocation. `this` is not a complex number array.","03":"invalid arguments. Target array lacks sufficient storage to accommodate source values.","04":"invalid arguments. Creating a generic array from an ArrayBuffer is not supported.","05":"invalid arguments. Must provide a length, typed array, array-like object, or an iterable.","06":"invalid arguments. Generated array exceeds maximum array length.","07":"invalid arguments. If either of the first two arguments are complex numbers, the output array must be a complex number array or a \"generic\" array-like object.","08":"invalid arguments. If either of the first two arguments are complex numbers, the output array data type must be a complex number data type or \"generic\".","09":"not supported. The current environment does not support SharedArrayBuffers, and, unfortunately, SharedArrayBuffers cannot be polyfilled. For shared memory applications, upgrade your runtime environment to one which supports SharedArrayBuffers.","0A":"insufficient arguments. Must provide a search value.","0B":"invalid argument. Attempted to add duplicate listener.","0C":"exception","0D":"unexpected error. Benchmark failed.","0E":"unexpected error. Invalid benchmark.","0F":"unexpected error.","0G":"invalid invocation. Constructor must be called with the `new` keyword.","0H":"unexpected error. Max retries exceeded. Too many open files.","0I":"insufficient arguments. Must provide two or more iterators.","0J":"insufficient arguments. Must provide both an iterator and a static value.","0K":"invalid invocation. `this` is not a fluent interface iterator.","0L":"insufficient arguments. Must provide a hash function.","0M":"invalid argument. Iterator arguments must be iterator protocol-compliant objects.","0N":"insufficient arguments. Must provide at least one iterator function.","0O":"invalid argument. Providing a number is not supported.","0P":"invalid argument. Providing a complex number is not supported.","0Q":"invalid argument. Providing an ndarray is not supported.","0R":"invalid argument. Providing an array-like object is not supported.","0S":"invalid argument. If the first argument is an ndarray, the second argument must be an ndarray.","0T":"invalid argument. Output array must have the same number of elements (i.e., length) as the input array.","0U":"invalid argument. If the first argument is an array-like object, the second argument must be an array-like object.","0V":"invalid argument. Providing a number is not supported. Consider providing a zero-dimensional ndarray containing the numeric value.","0W":"invalid argument. Providing a complex number is not supported. Consider providing a zero-dimensional ndarray containing the complex number value.","0X":"invalid arguments. Must provide either a data source, array shape, or both.","0Y":"invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.","0Z":"invalid argument. Cannot broadcast an array to a shape having fewer dimensions. Arrays can only be broadcasted to shapes having the same or more dimensions.","0a":"invalid argument. First argument must contain at least one element.","0b":"invalid arguments. The length of the first argument is incompatible with the second and third arguments.","0c":"invalid argument. Must provide an ndarray having two or more dimensions.","0d":"invalid arguments. Arrays must have the same shape.","0e":"invalid invocation. Cannot write to a read-only array.","0f":"invalid argument. Fourth argument length must be equal to 1 when creating a zero-dimensional ndarray.","0g":"invalid arguments. The input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","0h":"invalid arguments. Interface must accept at least one input and/or output ndarray. Based on the provided arguments, `nin+nout` equals `0`.","0i":"invalid arguments. Fourth argument does not equal the number of input and output ndarrays.","0j":"invalid argument. Unexpected number of types. A type must be specified for each input and output ndarray for each provided ndarray function.","0k":"invalid argument. The third argument must have the same number of elements as the first argument.","0l":"invalid invocation. Insufficient arguments.","0m":"invalid invocation. Too many arguments.","0n":"invalid arguments. Unable to resolve an ndarray function supporting the provided array argument data types.","0o":"invalid operation. Unable to load Electron. Ensure Electron is installed and try again.","0p":"invalid operation. A browser environment has no support for changing the current working directory.","0q":"invalid operation. The environment does not support reading from `stdin`.","0r":"unexpected error. PRNG returned NaN.","0s":"invalid argument. Third argument must be less than or equal to the first argument.","0t":"invalid argument. Second argument must be less than or equal to the first argument.","0u":"invalid operation. Cannot delete the `base` workspace.","0v":"invalid invocation. Must provide either a string containing presentation text or an options object specifying a presentation file to load.","0w":"invalid argument. When not provided presentation text, an options argument must specify a presentation file to load.","0x":"invalid invocation. Not currently in a presentation workspace. Must provide either a string or nonnegative integer which corresponds to the identifier of the presentation to be stopped.","0y":"unexpected error. Command execution terminated.","0z":"invalid operation. Cannot load a file into a REPL which has already closed.","1A":"invalid arguments. First and second arguments must be arrays having the same length.","1B":"invalid arguments. Subpopulation size must be less than or equal to population size.","1C":"invalid arguments. Number of draws must be less than or equal to population size.","1D":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number number of observations must be greater than zero).","1E":"invalid arguments. First and second arguments must have the same length.","1F":"invalid arguments. First and second arguments must be arrays having the same length.","1G":"invalid arguments. First and second argument must have the same length.","1H":"invalid arguments. Not enough observations. First and second arguments must contain at least four observations.","1I":"invalid arguments. The first and second arguments must have the same length.","1J":"`x` or `x - y` cannot be zero for all elements.","1K":"invalid arguments. Strided array parameters are incompatible with the provided array-like object. Linear index exceeds array bounds.","1L":"invalid arguments. Unable to resolve a strided array function supporting the provided array argument data types.","1M":"invalid arguments. Interface must accept at least one strided input and/or output array. Based on the provided arguments, `nin+nout` equals `0`.","1N":"invalid argument. Unexpected number of types. A type must be specified for each strided input and output array for each provided strided array function.","1O":"invalid argument. Fourth argument is incompatible with the number of strided input and output arrays.","1P":"invalid argument. Input array offset must be a nonnegative integer.","1Q":"invalid argument. Output array offset must be a nonnegative integer.","1R":"invalid argument. Input array must be an array-like object.","1S":"invalid argument. Output array must be an array-like object.","1T":"invalid argument. Input array has insufficient elements based on the associated stride and the number of indexed elements.","1U":"invalid argument. Output array has insufficient elements based on the associated stride and the number of indexed elements.","1V":"insufficient arguments. Must provide either an array of code points or one or more code points as separate arguments.","1W":"invalid argument. Third argument must not be an empty string.","1X":"invalid argument. Pad string must not be an empty string.","1Y":"insufficient arguments. Must provide multiple functions to compose.","1Z":"insufficient arguments. Must provide multiple functions to execute sequentially.","1a":"invalid arguments. First and last arguments must be the same length.","1b":"insufficient arguments. Must provide at least two objects.","1c":"invalid invocation. `this` is not a compact adjacency matrix.","1d":"invalid argument. Cannot specify one or more accessors and a value or writable attribute in the property descriptor.","1e":"invalid argument. The list does not contain the provided list node.","1f":"unexpected error. Unable to resolve global object.","1g":"invalid argument. The output ndarray must be writable. Cannot write to a read-only ndarray.","1h":"invalid arguments. Input and output arrays must have the same length.","1i":"invalid arguments. Input and output arrays must have the same number of elements (i.e., length).","1j":"invalid arguments. Input ndarrays must be broadcast compatible.","1k":"invalid arguments. Input arrays must have the same number of elements (i.e., length).","1l":"insufficient arguments. Must provide both a target object and one or more source objects.","1m":"invalid invocation. `this` is not host tuple.","1n":"invalid invocation. `this` is not the host tuple factory.","1o":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented.","1p":"invalid argument. Second argument must have a length equal to the size of the outermost input array dimension.","1q":"evaluation error. Did not receive timing results.","1r":"evaluation error. Unable to retrieve evaluation results. Ensure that the provided snippet does not return prematurely.","1s":"invalid argument. Must provide a zipped array.","1t":"invalid argument. Array must only contain arrays.","1u":"invalid argument. Indices must be specified as an array.","1v":"invalid argument. All indices must be integers.","1w":"invalid argument. Must provide valid indices (i.e., an index must be on the interval [0, len], where len is the tuple length).","1x":"insufficient arguments. Must provide at least one array.","1y":"invalid argument. Must provide a username or, to get who an authenticated user is following, an access token.","1z":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user has starred, an access token.","2A":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","2B":"invalid argument. First argument must be an ArrayBuffer. Value: `%s`.","2C":"invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.","2D":"invalid argument. Byte offset must be a multiple of `%u`. Value: `%u`.","2E":"invalid arguments. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","2F":"invalid argument. Length must be a nonnegative integer. Value: `%s`.","2G":"invalid arguments. ArrayBuffer has insufficient capacity. Either decrease the array length or provide a bigger buffer. Minimum capacity: `%u`.","2H":"invalid argument. Second argument must be a function. Value: `%s`.","2I":"invalid argument. First argument must have a length which is a multiple of two. Length: `%u`.","2J":"invalid argument. First argument must be an array-like object or an iterable. Value: `%s`.","2K":"invalid argument. Must provide a nonnegative integer. Value: `%s`.","2L":"invalid argument. Index argument must be a nonnegative integer. Value: `%s`.","2M":"invalid argument. Index argument is out-of-bounds. Value: `%u`.","2N":"invalid argument. First argument must be either a complex number, an array-like object, or a complex number array. Value: `%s`.","2O":"invalid argument. First argument must be an array-like object. Value: `%s`.","2P":"invalid argument. Second argument must be a recognized array data type. Value: `%s`.","2Q":"invalid argument. Second argument must have a recognized/supported data type. Type: `%s`. Value: `%s`.","2R":"invalid argument. Unable to parse %s date.","2S":"invalid argument. Numeric %s date must be either a Unix or JavaScript timestamp.","2T":"invalid argument. %s date must either be a date string, Date object, Unix timestamp, or JavaScript timestamp.","2U":"invalid argument. Length must be a positive integer. Value: `%s`.","2V":"invalid argument. Options argument must be an object. Value: `%s`.","2W":"invalid option. `%s` option must be a string. Option: `%s`.","2X":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","2Y":"invalid argument. Must provide a recognized data type. Value: `%s`.","2Z":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, typed array, or array-like object. Value: `%s`.","2a":"invalid argument. Must provide a length, typed array, array-like object, or an iterable. Value: `%s`.","2b":"invalid argument. Callback argument must be a function. Value: `%s`.","2c":"invalid argument. Iterator argument must be an iterator protocol-compliant object. Value: `%s`.","2d":"invalid argument. First argument must be a nonnegative integer. Value: `%s`.","2e":"invalid argument. Third argument must be a recognized data type. Value: `%s`.","2f":"invalid argument. First argument must be either an array, typed array, or complex typed array. Value: `%s`.","2g":"invalid argument. Start must be numeric. Value: `%s`.","2h":"invalid argument. Stop must be numeric. Value: `%s`.","2i":"invalid argument. Increment must be numeric. Value: `%s`.","2j":"invalid argument. First argument must be either a real or complex number. Value: `%s`.","2k":"invalid argument. Second argument must be either a real or complex number. Value: `%s`.","2l":"invalid argument. Third argument must be an array-like object. Value: `%s`.","2m":"invalid argument. Third argument must be a nonnegative integer. Value: `%s`.","2n":"invalid option. `%s` option must be a real or complex floating-point data type or \"generic\". Option: `%s`.","2o":"invalid option. `%s` option must be a boolean. Option: `%s`.","2p":"invalid argument. Exponent of start value must be numeric. Value: `%s`.","2q":"invalid argument. Exponent of stop value must be numeric. Value: `%s`.","2r":"invalid argument. First argument must be either an array length or an array-like object. Value: `%s`.","2s":"invalid argument. Must provide a typed array or ArrayBuffer. Value: `%s`.","2t":"invalid option. `%s` option must be a nonnegative integer. Option: `%s`.","2u":"invalid argument. Must provide an array-like object. Value: `%s`.","2v":"invalid option. `%s` option must be either `1` or `-1`. Option: `%s`.","2w":"invalid argument. Second argument must be either a function or an options object. Value: `%s`.","2x":"invalid argument. Must provide a typed array. Value: `%s`.","2y":"invalid argument. Second argument must be an array-like object. Value: `%s`.","2z":"invalid argument. Third argument must be an integer. Value: `%s`.","3A":"invalid argument. Key path must be a string or a key array. Value: `%s`.","3B":"invalid argument. Must provide a string. Value: `%s`.","3C":"invalid argument. Must provide a valid position (i.e., a nonnegative integer). Value: `%s`.","3D":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%u`.","3E":"invalid argument. Second argument must be callable. Value: `%s`.","3F":"invalid argument. First argument must be a string. Value: `%s`.","3G":"invalid argument. Fourth argument must be one of the following: \"%s\". Value: `%s`.","3H":"invalid argument. Fifth argument must be one of the following: \"%s\". Value: `%s`.","3I":"invalid argument. Second argument must be either an object (except null) or a function. Value: `%s`.","3J":"invalid argument. Must provide a function. Value: `%s`.","3K":"invalid argument. Must provide either an options object or a callback function. Value: `%s`.","3L":"invalid argument. First argument must be an object. Value: `%s`.","3M":"invalid option. `%s` option must be a writable stream. Option: `%s`.","3N":"invalid argument. Third argument must be a function. Value: `%s`.","3O":"invalid option. `%s` option must be either a positive integer or `null`. Option: `%s`.","3P":"invalid option. `%s` option must be a positive integer. Option: `%s`.","3Q":"invalid argument. First argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3R":"invalid argument. Second argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3S":"invalid argument. Arrays must be the same length. First argument length: `%u`. Second argument length: `%u`.","3T":"invalid argument. First argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3U":"invalid argument. Second argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3V":"invalid argument. First argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3W":"invalid argument. Second argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3X":"invalid argument. Second argument must be a nonnegative integer. Value: `%s`.","3Y":"invalid argument. Second argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3Z":"invalid argument. Last argument must be a nonnegative integer. Value: `%s`.","3a":"invalid argument. Last argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3b":"invalid argument. Must provide a Buffer. Value: `%s`.","3c":"invalid argument. First argument must be a function. Value: `%s`.","3d":"invalid argument. Third argument must be a constructor function. Value: `%s`.","3e":"invalid argument. Real component must be a number. Value: `%s`.","3f":"invalid argument. Imaginary component must be a number. Value: `%s`.","3g":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","3h":"invalid argument. Unsupported/unrecognized dataset name. Value: `%s`.","3i":"invalid option. Unrecognized `%s`. Option: `[%s]`.","3j":"invalid option. `%s` option must be a string or an array of strings. Option: `%s`.","3k":"invalid option. `%s` option must be a positive integer or an array of positive integers. Option: `%s`.","3l":"invalid option. `%s` option must be a positive integer array of length two. Option: `%s`.","3m":"invalid option. `%s` option cannot be less than 1790. Option: `%s`.","3n":"invalid option. `%s` option cannot be greater than 5000. Option: `%s`.","3o":"invalid argument. Must provide an error object. Value: `%s`.","3p":"invalid argument. First argument must be a valid file descriptor (i.e., nonnegative integer). Value: `%s`.","3q":"invalid argument. Last argument must be a function. Value: `%s`.","3r":"invalid argument. Must provide a valid file descriptor (i.e., a nonnegative integer). Value: `%s`.","3s":"invalid argument. First argument must be an array of strings. Value: `%s`.","3t":"invalid argument. Options argument must be either a string or an object. Value: `%s`.","3u":"invalid argument. Predicate function must be a function. Value: `%s`.","3v":"invalid argument. First argument must be an iterator. Value: `%s`.","3w":"invalid argument. Must provide an iterator. Value: `%s`.","3x":"invalid argument. Must provide an iterator protocol-compliant object. Argument: `%u`. Value: `%s`.","3y":"invalid argument. Must provide an iterator protocol-compliant object. Value: `%s`.","3z":"invalid argument. Unable to parse date string. Value: `%s`.","4A":"invalid argument. Second argument must be a number. Value: `%s`.","4B":"invalid argument. Third argument must be a number. Value: `%s`.","4C":"invalid argument. Hash function argument must be a function. Value: `%s`.","4D":"invalid option. `%s` option must be a positive number. Option: `%s`.","4E":"invalid argument. Third argument must be either a nonnegative integer or an object. Value: `%s`.","4F":"invalid arguments. All arguments must be functions. Value: `%s`.","4G":"invalid argument. Each iterator function, except the last iterator function, within an iterator pipeline must return an iterator. Value: `%s`.","4H":"invalid argument. Must provide an an iterator. Value: `%s`.","4I":"invalid return value. Callback function must return an integer. Value: `%s`.","4J":"invalid argument. Fourth argument must be a boolean. Value: `%s`.","4K":"invalid return value. Callback function must return a positive integer. Value: `%s`.","4L":"invalid argument. Fifth argument must be a callback function. Value: `%s`.","4M":"invalid argument. Third argument must be either an integer (starting index) or a callback function. Value: `%s`.","4N":"invalid argument. Fourth argument must be either an integer (ending index) or a callback function. Value: `%s`.","4O":"invalid argument. Unrecognized/unsupported scale function. Value: `%s`.","4P":"invalid argument. Must provide an iterator protocol-compliant object or a number. Argument: `%u`. Value: `%s`.","4Q":"invalid argument. First argument must be a finite number. Value: `%s`.","4R":"invalid option. `%s` option must be a positive finite number. Option: `%s`.","4S":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","4T":"invalid option. `%s` option must be less than or equal to 79. Option: `%u`.","4U":"invalid option. `%s` option must be less than or equal to 77. Option: `%u`.","4V":"invalid argument. Must provide an argument having a supported data type. Value: `%s`.","4W":"invalid option. Unsupported policy for determining an output array data type. Option: `%s`.","4X":"invalid option. `%s` option must be a recognized/supported data type. Option: `%s`.","4Y":"invalid option. `%s` option must be a recognized/supported output array data type policy. Option: `%s`.","4Z":"invalid argument. Resolution table must be an object. Value: `%s`.","4a":"invalid argument. Resolution table `%s` field value must be either a function or null. Value: `%s`.","4b":"invalid argument. First argument must be a positive integer. Value: `%s`.","4c":"invalid argument. First argument must be a one-dimensional ndarray. Value: `%s`.","4d":"invalid argument. Second argument must be either +1 or -1. Value: `%s`.","4e":"invalid argument. First argument must be a one-dimensional ndarray of length %u. Actual length: `%u`.","4f":"invalid argument. First argument must be an ndarray. Value: `%s`.","4g":"invalid argument. First argument must be an ndarray whose last dimension is of size `%u`. Actual size: `%u`.","4h":"invalid argument. Second argument is incompatible with model loss function. Probability predictions are only supported when the loss function is one of the following: \"%s\". Model loss function: `%s`.","4i":"invalid argument. Second argument must be a string value equal to either \"label\", \"probability\", or \"linear\". Value: `%s`.","4j":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of `eta*lambda`. Value: `%f`.","4k":"invalid option. `%s` option must be a nonnegative number. Option: `%s`.","4l":"invalid option. `%s` option must be an array-like object. Option: `%s`.","4m":"invalid option. First `%s` option must be one of the following: \"%s\". Option: `%s`.","4n":"invalid option. Second `%s` option must be a positive number. Option: `%s`.","4o":"invalid option. Third `%s` option must be a number. Option: `%s`.","4p":"invalid argument. Argument specifying number of dimensions must be a positive integer. Value: `%s`.","4q":"invalid argument. First argument must either be a positive integer specifying the number of clusters or a matrix containing initial centroids. Value: `%s`.","4r":"invalid option. First `%s` parameter option must be greater than or equal to the number of clusters. Options: `%f`.","4s":"invalid argument. Must provide a 1-dimensional ndarray. Value: `%s`.","4t":"invalid argument. Vector length must match centroid dimensions. Expected: `%u``. Actual: `%u``.","4u":"invalid argument. Output argument must be a 1-dimensional ndarray. Value: `%s`.","4v":"invalid argument. Must provide a 2-dimensional ndarray. Value: `%s`.","4w":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u``. Actual: `%u`.","4x":"invalid argument. Output vector length must match the number of data points. Expected: `%u`. Actual: `%u`.","4y":"invalid option. `%s` option method must be one of the following: \"%s\". Option: `%s`.","4z":"invalid option. First `%s` parameter option must be a positive integer. Option: `%s`.","5A":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","5B":"invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.","5C":"invalid option. `%s` option must be a recognized order. Option: `%s`.","5D":"invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.","5E":"invalid argument. Linear index must not exceed array dimensions. Number of array elements: `%u`. Value: `%d`.","5F":"invalid argument. Input array cannot be broadcast to the specified shape, as the specified shape has a dimension whose size is less than the size of the corresponding dimension in the input array. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5G":"invalid argument. Input array and the specified shape are broadcast incompatible. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5H":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.","5I":"invalid argument. Index must be on the interval: [0, %f]. Value: `%f`.","5J":"invalid argument. Subscripts must not exceed array dimensions. Subscript: `%u`. Value: `%d`.","5K":"invalid argument. First argument must be a recognized data type. Value: `%s`.","5L":"invalid argument. First argument must have a recognized data type. Value: `%s`.","5M":"invalid arguments. Number of indices must match the number of dimensions. ndims: `%u`. nargs: `%u`.","5N":"invalid argument. Indices must be integer valued. Argument: `%u`. Value: `%s`.","5O":"invalid argument. Index must be an integer. Value: `%s`.","5P":"invalid argument. First argument must be a supported ndarray data type. Value: `%s`.","5Q":"invalid argument. Second argument must be an array-like object, typed-array-like, or a Buffer. Value: `%s`.","5R":"invalid argument. Second argument `get` and `set` properties must be functions. Value: `%s`.","5S":"invalid argument. Third argument must be an array-like object containing nonnegative integers. Value: `%s`.","5T":"invalid argument. Number of dimensions must not exceed %u due to stack limits. Value: `%u`.","5U":"invalid argument. Fourth argument must be an array-like object containing integers. Value: `%s`.","5V":"invalid argument. Fourth argument length must match the number of dimensions. Expected number of dimensions: `%u`. Strides length: `%u`.","5W":"invalid argument. Fourth argument must contain a single element equal to `0`. Value: `%d`.","5X":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.","5Y":"invalid argument. Sixth argument must be a supported order. Value: `%s`.","5Z":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%u`.","5a":"invalid option. `%s` option must be a recognized mode. Option: `%s`.","5b":"invalid option. `%s` option must be an array containing recognized modes. Option: `%s`.","5c":"invalid option. Each submode must be a recognized mode. Option: `%s`.","5d":"invalid argument. First argument must be either a function or an array of functions. Value: `%s`.","5e":"invalid argument. Third argument must be an array-like object or null. Value: `%s`.","5f":"invalid argument. Fourth argument must be a positive integer. Value: `%s`.","5g":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%s`.","5h":"invalid argument. Input array must be an ndarray-like object. Value: `%s`.","5i":"invalid argument. Output array must be an ndarray-like object. Value: `%s`.","5j":"invalid argument. Output argument must be either an array, typed array, or object. Value: `%s`.","5k":"invalid argument. Shape argument must be an array-like object containing nonnegative integers. Value: `%s`.","5l":"invalid argument. Linear index must be integer valued. Value: `%s`.","5m":"invalid option. `%s` option must be a supported/recognized mode. Option: `%s`.","5n":"invalid option. `%s` option must be a supported/recognized order. Option: `%s`.","5o":"invalid argument. First argument must be an array-like object containing nonnegative integers. Value: `%s`.","5p":"invalid argument. Number of provided subscripts must match the number of dimensions. ndims: `%u`. Number of subscripts: `%u`.","5q":"invalid argument. Subscripts must be integer valued. Argument: `%u`. Value: `%s`.","5r":"invalid option. `%s` option cannot be an empty array.","5s":"invalid argument. First argument must be either a nonnegative integer or an array of nonnegative integers. Value: `%s`.","5t":"invalid argument. First argument must be an ndarray-like object. Value: `%s`.","5u":"invalid option. `%s` option must either be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","5v":"invalid option. `%s` option must be either a Buffer or a string. Option: `%s`.","5w":"invalid argument. Request listener must be a function. Value: `%s`.","5x":"invalid argument. Third argument must be a positive integer. Value: `%s`.","5y":"invalid argument. Number of topics must be a positive integer. Value: `%s`.","5z":"invalid argument. First argument must be a nonnegative integer which is less than the total number of topics. Value: `%s`.","6A":"invalid assignment. `%s` must be a nonnegative integer or nonnegative integer array. Value: `%s`.","6B":"invalid assignment. `%s` must be a nonnegative integer. Value: `%s`.","6C":"invalid assignment. Unrecognized/unsupported `%s`. Must be one of the following: \"%s\". Value: `%s`.","6D":"invalid assignment. Unrecognized/unsupported `%s`. Value: `%s`.","6E":"invalid assignment. `%s` must be a nonnegative integer or null. Value: `%s`.","6F":"invalid assignment. `%s` must be a string or null. Value: `%s`.","6G":"invalid argument. Must provide a supported viewer. Value: `%s`.","6H":"invalid assignment. `%s` must be a function. Value: `%s`.","6I":"invalid assignment. `%s` must be either null or an array. Value: `%s`.","6J":"invalid assignment. `%s` must be a string, function, or null. Value: `%s`.","6K":"invalid argument. `options` argument must be an object. Value: `%s`.","6L":"invalid assignment. `%s` must be a number. Value: `%s`.","6M":"invalid assignment. `%s` must be a number on the interval `[0,1]`. Value: `%f`.","6N":"invalid assignment. `%s` must be array-like. Value: `%s`.","6O":"invalid arguments. Must provide equal length array-like objects. x length: `%u`, y length: `%u`.","6P":"invalid assignment. `%s` must be a string or a function. Value: `%s`.","6Q":"invalid assignment. `%s` must be a number or a function. Value: `%s`.","6R":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","6S":"invalid assignment. `%s` must be a nonnegative integer or a function. Value: `%s`.","6T":"invalid assignment. `%s` must be a supported symbol. Symbols: \"%s\". Value: `%s`.","6U":"invalid argument. `options` argument must be a plain object. Value: `%s`.","6V":"invalid assignment. `%s` must be either a string or a string array. Value: `%s`.","6W":"invalid assignment. `%s` must be a string or a string array. Value: `%s`.","6X":"invalid assignment. `%s` must be a string or string array. Value: `%s`.","6Y":"invalid assignment. Unrecognized/unsupported symbol. Value: `[%s]`.","6Z":"invalid assignment. `%s` must be an array. Value: `%s`.","6a":"invalid assignment. `%s` must be either a finite number, Date, or null. Value: `%s`.","6b":"invalid assignment. `%s` must be a boolean or boolean array. Value: `%s`.","6c":"invalid assignment. `%s` must be either a string or string array. Value: `%s`.","6d":"invalid assignment. Unrecognized/unsupported orientation. A `%s` value must be one of the following: \"%s\". Value: `%s`.","6e":"invalid assignment. `%s` must be either a finite number or null. Value: `%s`.","6f":"invalid state. x and y are different lengths. x length: `%u`, y length: `%u`.","6g":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[","6h":"invalid assignment. `%s` must be a positive integer or null. Value: `%s`.","6i":"invalid assignment. `%s` size is smaller than the number of data elements. Number of elements: `%u`. Value: `%u`.","6j":"invalid assignment. `%s` must be an array-like object or an ndarray. Value: `%s`.","6k":"invalid assignment. `%s` length exceeds maximum data buffer size. Buffer size: `%u`. Length: `%u`.","6l":"invalid assignment. `%s` must be a finite number or null. Value: `%s`.","6m":"invalid assignment. `%s` must be a finite number or null. Value: `%s.","6n":"invalid assignment. Must be an array or typed array. Value: `%s`.","6o":"invalid option. `%s` option must be an array or typed array. Option: `%s`.","6p":"invalid option. `%s` option must be a function. Option: `%s`.","6q":"invalid argument. Encoding argument must be a string. Value: `%s`.","6r":"invalid argument. Must provide either a string, nonnegative integer, or an options object. Value: `%s`.","6s":"invalid argument. First argument must be either a string or nonnegative integer. Value: `%s`.","6t":"invalid argument. Unable to parse mask expression. Ensure the expression is properly formatted, only uses the class letters \"u\", \"g\", \"o\", and \"a\", only uses the operators \"+\", \"-\", and \"=\", and only uses the permission symbols \"r\", \"w\", and \"x\". Value: `%s`.","6u":"invalid option. `%s` option must be a pseudorandom number generator function. Option: `%s`.","6v":"invalid argument. First argument must be a number and not NaN. Value: `%s`.","6w":"invalid argument. Second argument must be a number and not NaN. Value: `%s`.","6x":"invalid argument. Minimum support must be less than maximum support. Value: `[%f,%f]`.","6y":"invalid argument. First argument must be a probability. Value: `%s`.","6z":"invalid option. `%s` option must be a Uint32Array. Option: `%s`.","7A":"invalid argument. First argument must be a positive number and not NaN. Value: `%s`.","7B":"invalid argument. Second argument must be a positive number and not NaN. Value: `%s`.","7C":"invalid argument. Third argument must be a number and not NaN. Value: `%s`.","7D":"invalid argument. Third argument must be less than or equal to the first argument. Value: `%u`.","7E":"invalid argument. Second argument must be less than or equal to the first argument. Value: `%u`.","7F":"invalid %s. State array has insufficient length.","7G":"invalid %s. State array has an incompatible schema version. Expected: `%s`. Actual: `%s`.","7H":"invalid %s. State array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","7I":"invalid %s. State array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7J":"invalid %s. State array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7K":"invalid option. `%s` option must be an Int32Array. Option: `%s`.","7L":"invalid option. `%s` option must be a positive integer less than the maximum signed 32-bit integer. Option: `%u`.","7M":"invalid option. `%s` option must be either a positive integer less than the maximum signed 32-bit integer or an array-like object containing integer values less than the maximum signed 32-bit integer. Option: `%s`.","7N":"invalid argument. Must provide an Int32Array. Value: `%s`.","7O":"invalid %s. State array has an incompatible table length. Expected: `%s`. Actual: `%s`.","7P":"invalid %s. `state` array has insufficient length.","7Q":"invalid %s. `state` array has an incompatible schema version. Expected: %s. Actual: %s.","7R":"invalid %s. `state` array has an incompatible number of sections. Expected: %s. Actual: %s.","7S":"invalid %s. `state` array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7T":"invalid %s. `state` array has an incompatible section length. Expected: `%u`. Actual: `%u`.","7U":"invalid %s. `state` array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7V":"invalid option. `%s` option must be a positive integer less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7W":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7X":"invalid argument. Second argument must be on the interval: (0, 1). Value: `%f`.","7Y":"invalid option. `%s` option cannot be undefined. Option: `%s`.","7Z":"invalid option. Unrecognized/unsupported PRNG. Option: `%s`.","7a":"invalid argument. First argument must be a positive number or an options object. Value: `%s`.","7b":"invalid arguments. Parameters must satisfy the following condition: %s. Value: `[%f, %f, %f]`.","7c":"invalid argument. Scale parameter must be a positive number. Value: `%s`.","7d":"invalid argument. Shape parameter must be a positive number. Value: `%s`.","7e":"invalid argument. First argument must be an integer. Value: `%s`.","7f":"invalid argument. Second argument must be an integer. Value: `%s`.","7g":"invalid argument. `n` must be less than or equal to `N`. Value: `%u`.","7h":"invalid argument. `K` must be less than or equal to `N`. Value: `%u`.","7i":"invalid argument. `%s` argument must be array-like. Value: `%s`.","7j":"invalid input option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","7k":"invalid input option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","7l":"invalid option. `%s` option must be an array of probabilities that sum to one. Option: `%s`.","7m":"invalid argument. Minimum support must be less than maximum support. Value: `[%s,%s]`.","7n":"invalid option. `%s` option must be a string or null. Option: `%s`.","7o":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%s,%s]`.","7p":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7q":"invalid argument. Mode must be one of the following: \"%s\". Value: `%s`.","7r":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7s":"invalid operation. Alias already exists in the provided context. Alias: `%s`. Value: `%s`.","7t":"invalid argument. Unrecognized workspace name. Value: `%s`.","7u":"invalid operation. Cannot read from write-only variable `%s`.","7v":"Cannot assign to read only property %s of object #","7w":"invalid option. `%s` option must be a regular expression or an array-like object. Option: `%s`.","7x":"invalid option. `%s` option must be one of `%s`. Option: `%s`.","7y":"invalid argument. Must provide either an options object or a workspace name. Value: `%s`.","7z":"invalid argument. Must provide either a string or regular expression. Value: `%s`.","8A":"invalid argument. Must provide an integer. Value: `%s`.","8B":"invalid argument. Must provide a positive integer. Value: `%s`.","8C":"invalid argument. Presentation text must be a string. Value: `%s`.","8D":"invalid argument. REPL argument must be a REPL instance. Value: `%s`.","8E":"unexpected error. Unable to reload presentation. Error: %s","8F":"unexpected error. Unable to watch presentation source file. Error: %s","8G":"invalid option. `%s` option must be either a recognized string or boolean. Option: `%s`.","8H":"invalid option. `%s` option must be either a positive integer or null. Option: `%s`.","8I":"invalid operation. Alias already exists in REPL context. Alias: `%s`. Value: `%s`.","8J":"invalid argument. Third argument must be an object. Value: `%s`.","8K":"invalid option. `%s` option must be less than or equal to the period. Option: `%u`.","8L":"invalid option. `%s` option must be greater than 2. Option: `%s`.","8M":"invalid option. `%s` option must be an integer. Option: `%s`.","8N":"invalid option. `%s` option must be an positive integer. Option: `%s`.","8O":"invalid option. `%s` option must be less than the period. Option: `%s`.","8P":"invalid option. `%s` option must be a number. Option: `%s`.","8Q":"invalid option. `%s` option must be an positive even integer. Option: `%s`.","8R":"invalid argument. First argument must be a numeric array. Value: `%s`.","8S":"invalid argument. First argument must contain at least two elements. Value: `%s`.","8T":"invalid argument. Second argument must be an array. Value: `%s`.","8U":"invalid argument. Second argument must contain at least two unique elements. Value: `%s`.","8V":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%f`.","8W":"invalid option. `%s` option must be an array containing at least two unique elements. Option: `%s`.","8X":"invalid argument. Must provide array-like arguments. Value: `%s`.","8Y":"invalid argument. Supplied arrays cannot be empty. Value: `%s`.","8Z":"invalid option. `%s` option must be an array. Option: `%s`.","8a":"invalid argument. Minimum support must be a number. Value: `%s`.","8b":"invalid argument. Maximum support must be a number. Value: `%s`.","8c":"invalid arguments. Minimum support must be less than maximum support. Value: `%f, %f`.","8d":"invalid assignment. Must be a number. Value: `%s`.","8e":"invalid assignment. Must be less than %f. Value: `%f`.","8f":"invalid assignment. Must be greater than %f. Value: `%f`.","8g":"invalid argument. Mean parameter `p` must be a probability. Value: `%s`.","8h":"invalid assignment. Must be a probability. Value: `%s`.","8i":"invalid argument. First shape parameter must be a positive number. Value: `%s`.","8j":"invalid argument. Second shape parameter must be a positive number. Value: `%s`.","8k":"invalid assignment. Must be a positive number. Value: `%s`.","8l":"invalid argument. Number of trials must be a positive integer. Value: `%s`.","8m":"invalid argument. Success probability must be a number between 0 and 1. Value: `%s`.","8n":"invalid assignment. Must be a positive integer. Value: `%s`.","8o":"invalid assignment. Must be a number on the interval: [0, 1]. Value: `%s`.","8p":"invalid argument. Location parameter must be a number. Value: `%s`.","8q":"invalid argument. Rate parameter must be a positive number. Value: `%s`.","8r":"invalid argument. Mean parameter `%s` must be a number. Value: `%s`.","8s":"invalid argument. Minimum support must be an integer. Value: `%s`.","8t":"invalid argument. Maximum support must be an integer. Value: `%s`.","8u":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `%d, %d`.","8v":"invalid assignment. Must be an integer. Value: `%s`.","8w":"invalid assignment. Must be less than or equal to %u. Value: `%d`.","8x":"invalid assignment. Must be greater than or equal to %u. Value: `%s`.","8y":"invalid argument. Shape parameter must be a positive integer. Value: `%s`.","8z":"invalid argument. Numerator degrees of freedom must be a positive number. Value: `%s`.","9A":"invalid argument. Mean parameter `lambda` must be a positive number. Value: `%s`.","9B":"invalid argument. Mode must be a number. Value: `%s`.","9C":"invalid arguments. Parameters must satisfy the following condition: %s. a: `%f`. b: `%f`. c: `%f`.","9D":"invalid assignment. Must be less than or equal to both the maximum support and the mode. Value: `%f`.","9E":"invalid assignment. Must be greater than or equal to both the minimum support and the mode. Value: `%f`.","9F":"invalid assignment. Must be greater than or equal to the minimum support and less than or equal to the maximum support. Value: `%f`.","9G":"invalid argument. An array argument must contain two elements. Value: `%s`.","9H":"invalid argument. Must provide a nonnegative integer or a two-element array. Value: `%s`.","9I":"invalid arguments. Number of successes cannot be larger than the total number of observations. x: `%u`. n: `%u`.","9J":"invalid option. `%s` option must be a probability. Option: `%f`.","9K":"invalid argument. Unsupported/unrecognized distribution name. Value: `%s`.","9L":"invalid argument. First argument must contain nonnegative integers. Index: `%u`. Value: `%s`.","9M":"invalid argument. Probability mass function (PMF) arguments must be numbers. Argument: `%u`. Value: `%s`.","9N":"invalid argument. Second argument must be either an array-like object (or one-dimensional ndarray) of probabilities summing to one, an array-like object (or one-dimensional ndarray) of expected frequencies, or a discrete probability distribution name. Value: `%s`.","9O":"invalid argument. Second argument must only contain numbers. Index: `%u`. Value: `%s`.","9P":"invalid argument. Second argument must only contain nonnegative numbers. Index: `%u`. Value: `%d`.","9Q":"invalid option. `%s` option must be a number on the interval: [0, 1]. Value: `%s`.","9R":"invalid argument. First argument must be an array of arrays or ndarray-like object with dimension two. Value: `%s`.","9S":"invalid argument. First argument must contain nonnegative integers. Value: `%s`.","9T":"invalid argument. First argument must either specify the order of the covariance matrix or be a square 2-dimensional ndarray for storing the covariance matrix. Value: `%s`.","9U":"invalid argument. Second argument must be a 1-dimensional ndarray. Value: `%s`.","9V":"invalid argument. The number of elements (means) in the second argument must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9W":"invalid argument. Vector length must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9X":"invalid argument. Must provide a number. Value: `%s`.","9Y":"invalid argument. Must provide a nonnegative number. Value: `%s`.","9Z":"invalid argument. Must provide a nonnegative number on the interval [0,1]. Value: `%f`.","9a":"invalid argument. Output argument must be an array-like object. Value: `%s`.","9b":"invalid argument. Window size must be a positive integer. Value: `%s`.","9c":"invalid argument. Window size must be greater than or equal to 3. Value: `%s`.","9d":"invalid option. `%s` option must be on the interval [0,1]. Option: `%f`.","9e":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square 2-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","9f":"invalid argument. The number of elements (means) in the second argument must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9g":"invalid argument. Vector length must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","9h":"invalid argument. Vector length must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9i":"invalid argument. First argument must either specify the order of the correlation matrix or be a square 2-dimensional ndarray for storing the correlation matrix. Value: `%s`.","9j":"invalid argument. Unsupported/unrecognized kernel. Value: `%s`.","9k":"invalid argument. Second argument must be a numeric array. Value: `%s`.","9l":"invalid option. Lower bound `%s` must be strictly less than the upper bound `%s`.","9m":"invalid option. `%s` option must be an array of positive numbers. Option: `%s`.","9n":"invalid option. `%s` option must be an array of length two. Option: `%s`.","9o":"invalid option. `%s` option must be a string denoting a known kernel function or a custom function. Option: `%s`.","9p":"invalid arguments. First argument and `%s` must be arrays having the same length.","9q":"invalid invocation. Incorrect number of arguments. Must provide at least two array-like arguments. Value: `%s`.","9r":"invalid option. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","9s":"invalid argument. First argument must be a typed array or number array. Value: `%s`.","9t":"invalid argument. Second argument must be either a CDF function or a string. Value: `%s`.","9u":"invalid argument. Distribution parameter must be a number. Value: `%s`.","9v":"invalid option. `%s` option must contain at least two unique elements. Value: `%s`.","9w":"invalid argument. Provided arrays cannot be empty. Value: `%s`.","9x":"invalid argument. First argument must be an array of probabilities. Value: `%s`.","9y":"invalid argument. When specified, `%s` arguments must contain at least a length of %u. Value: `%u`.","9z":"invalid argument. Second argument must be one of the following: %s. Value: `%s`.","A0":"invalid option. `%s` option must be a number in `[0,1]`. Option: `%s`.","A1":"invalid option. `%s` option must be a number on the interval: [-1, 1]. Option: `%s`.","A2":"invalid argument. First argument must contain at least two elements. Value: `%s`.","A3":"invalid argument. Second argument must be either a numeric array or an options object. Value: `%s`.","A4":"invalid option. `%s` option must be either `equal` or `unequal`. Option: `%s`.","A5":"invalid argument. `%s` argument must be a numeric array. Value: `%s`.","A6":"invalid option. `%s` option must be one of the following: %s. Option: `%s`.","A7":"invalid argument. Third argument must be a positive number. Value: `%s`.","A8":"invalid argument. Fourth argument must be a positive number. Value: `%s`.","A9":"invalid operation. Serialization function must return a string or Buffer. Value: `%s`.","AA":"invalid argument. In binary mode, a provided value must be a string, Buffer, or Uint8Array. Value: `%s`.","AB":"invalid option. `%s` option must be either a string or a regular expression. Option: `%s`.","AC":"invalid argument. First input array offset must be a nonnegative integer. Value: `%s`.","AD":"invalid argument. Second input array offset must be a nonnegative integer. Value: `%s`.","AE":"invalid argument. Output array offset must be a nonnegative integer. Value: `%s`.","AF":"invalid argument. Must provided recognized data types. Unable to resolve a data type string. Value: `%s`.","AG":"invalid argument. Input array offset must be a nonnegative integer. Value: `%s`.","AH":"invalid argument. Input array stride must be an integer. Value: `%s`.","AI":"invalid argument. Output array stride must be an integer. Value: `%s`.","AJ":"invalid option. `%s` option must be an array of strings. Option: `%s`.","AK":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%s`.","AL":"invalid argument. Third argument must be a boolean. Value: `%s`.","AM":"invalid argument. Must provide valid code points (i.e., nonnegative integers). Value: `%s`.","AN":"invalid argument. Must provide a valid code point (cannot exceed max). Value: `%s`.","AO":"invalid argument. Third argument must be a string. Value: `%s`.","AP":"invalid argument. Output string length exceeds maximum allowed string length. Value: `%u`.","AQ":"invalid argument. Third argument must be a string or an array of strings. Value: `%s`.","AR":"invalid argument. At least one padding option must have a length greater than 0. Left padding: `%s`. Right padding: `%s`.","AS":"invalid argument. Second argument must be an array of strings. Value: `%s`.","AT":"invalid argument. Second argument must be a string or regular expression. Value: `%s`.","AU":"invalid argument. Third argument must be a string or replacement function. Value: `%s`.","AV":"invalid argument. Must provide a string or an array of strings. Value: `%s`.","AW":"invalid argument. If only providing a single argument, must provide a Date object. Value: `%s`.","AX":"invalid argument. First argument must be either a string or integer. Value: `%s`.","AY":"invalid argument. Day number must be on the interval: `[1, %u]`. Value: `%d`.","AZ":"invalid argument. First argument must be either a string, integer, or Date object. Value: `%s`.","Aa":"invalid argument. An integer month value must be on the interval: [1, 12]. Value: `%s`.","Ab":"invalid argument. Must provide a recognized month. Value: `%s`.","Ac":"invalid argument. Must provide either an integer or a `Date` object. Value: `%s`.","Ad":"invalid argument. Must provide either a string, integer, or Date object. Value: `%s`.","Ae":"invalid argument. Must provide an array of nonnegative integers. Value: `%s`.","Af":"invalid argument. Input array must contain two elements. Value: `%s`.","Ag":"invalid argument. Must provide a collection. Value: `%s`.","Ah":"invalid argument. First argument must be a collection. Value: `%s`.","Ai":"invalid argument. First argument must be either an array, typed array, or an array-like object. Value: `%s`.","Aj":"invalid argument. All arguments must be functions. Value: `%s`.","Ak":"invalid argument. Number of function invocations must be a nonnegative integer. Value: `%s`.","Al":"invalid argument. First argument must be an array of functions. Value: `%s`.","Am":"invalid argument. Last argument must be a collection. Value: `%s`.","An":"invalid argument. Must provide either a valid buffer size (i.e., a positive integer) or an array-like object which can serve as the underlying buffer. Value: `%s`.","Ao":"invalid argument. An iterator must return an array-like object containing vertices. Value: `%s`.","Ap":"invalid argument. Callback must return an array-like object containing vertices. Value: `%s`.","Aq":"invalid argument. Callback must return an array-like object. Value: `%s`.","Ar":"invalid argument. Each element of the adjacency list must be an array-like object. Value: `%s`.","As":"invalid argument. Each element of the edge list must be an array-like object. Value: `%s`.","At":"invalid argument. Second argument must be an array-like object or an iterable. Value: `%s`.","Au":"invalid argument. First argument exceeds matrix dimensions. Value: `%u`.","Av":"invalid argument. Second argument exceeds matrix dimensions. Value: `%u`.","Aw":"invalid argument. Vertex cannot exceed matrix dimensions. Value: `%u`.","Ax":"invalid argument. Second argument must be a recognized output path convention. Value: `%s`.","Ay":"invalid argument. Cannot convert Windows extended-length paths to POSIX paths. Value: `%s`.","Az":"invalid argument. Arity argument must be a positive integer. Value: `%s`.","B0":"invalid argument. Property descriptor must be an object. Value: `%s`.","B1":"invalid argument. The `value` property of the property descriptor must be a function. Value: `%s`.","B2":"invalid argument. Second argument must be an object of property descriptors. Value: `%s`.","B3":"invalid argument. Path must be a string. Value: `%s`.","B4":"invalid argument. Third argument must be a recognized location. Value: `%s`.","B5":"invalid argument. Must provide a recognized iteration direction. Value: `%s`.","B6":"invalid argument. Must provide an object-like value. Value: `%s`.","B7":"invalid argument. Must provide a regular expression string. Value: `%s`.","B8":"invalid argument. Filename must be a string. Value: `%s`.","B9":"invalid argument. First argument must be an array of positive integers. Value: `%s`.","BA":"invalid argument. First argument must be object-like. Value: `%s`.","BB":"invalid argument. Must provide an array of arrays. Value: `%s`.","BC":"invalid argument. Must provide a boolean. Value: `%s`.","BD":"invalid argument. Second argument must have a prototype from which another object can inherit. Value: `%s`.","BE":"invalid argument. A provided constructor must be either an object (except null) or a function. Value: `%s`.","BF":"invalid argument. If the input array is an ndarray, the output array must also be an ndarray. Value: `%s`.","BG":"invalid argument. If the input array is an array-like object, the output array must also be an array-like object. Value: `%s`.","BH":"invalid argument. First argument must be an array-like object or an ndarray. Value: `%s`.","BI":"invalid argument. If the first input array is an ndarray, the second input array must also be an ndarray. Value: `%s`.","BJ":"invalid argument. If the input arrays are ndarrays, the output array must also be an ndarray. Value: `%s`.","BK":"invalid argument. If the first input array is an array-like object, the second input array must also be an array-like object. Value: `%s`.","BL":"invalid argument. If the input arrays are array-like objects, the output array must also be an array-like object. Value: `%s`.","BM":"invalid argument. First argument must be an array-like object containing array-like objects. Index: `%u`. Value: `%s`.","BN":"invalid argument. First argument must be a three-dimensional nested array. Index: `%u`. Value: `%s`.","BO":"invalid argument. First argument must be a four-dimensional nested array. Index: `%u`. Value: `%s`.","BP":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BQ":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BR":"invalid argument. First argument must be a five-dimensional nested array. Index: `%u`. Value: `%s`.","BS":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BT":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BU":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u, %u). Value: `%s`.","BV":"invalid argument. A merge source must be an object. Value: `%s`.","BW":"invalid option. `%s` option must be either a boolean or a function. Option: `%s`.","BX":"invalid argument. Source argument must be an object. Value: `%s`.","BY":"invalid argument. Target argument must be an object. Value: `%s`.","BZ":"invalid argument. Must provide an array of strings. Value: `%s`.","Ba":"invalid argument. Field names must be distinct. Value: `%s`.","Bb":"invalid argument. Provided field name is reserved. Name: `%s`.","Bc":"invalid arguments. Arguments are incompatible with the number of tuple fields. Number of fields: `%u`. Number of data elements: `%u`.","Bd":"invalid argument. Source is incompatible with the number of tuple fields. Number of fields: `%u`. Source length: `%u`.","Be":"invalid invocation. Number of arguments is incompatible with the number of tuple fields. Number of fields: `%u`. Number of arguments: `%u`.","Bf":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","Bg":"invalid argument. Second argument must be either a string or an array of strings. Value: `%s`.","Bh":"invalid argument. Must provide a valid URI. Value: `%s`.","Bi":"unexpected error. Child process failed with exit code: `%u`.","Bj":"unexpected error. Child process failed due to termination signal: `%s`.","Bk":"invalid argument. Reviver argument must be a function. Value: `%s`.","Bl":"invalid argument. Second argument must be an array-like object containing nonnegative integers. Value: `%s`.","Bm":"invalid argument. Must provide either an array, typed array, or an array-like object. Value: `%s`.","Bn":"invalid argument. Must provide a recognized type. Value: `%s`.","Bo":"invalid argument. Second argument must be an array containing only nonnegative integers. Value: `%s`.","Bp":"invalid invocation. Unexpected number of input arguments. Expected: `%u`. Actual: `%u`.","Bq":"evaluation error. Encountered an error when evaluating snippet. %s","Br":"invalid option. `%s` option must be a positive integer or null. Option: `%s`.","Bs":"insufficient arguments. Expected %u argument(s) and only received %u argument(s).","Bt":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: %u. Actual: %u.","Bu":"invalid invocation. Number of arguments exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bv":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bw":"invalid argument. Must provide array arguments. Value: `%s`.","Bx":"invalid argument. Last argument must be either an array or an options object. Value: `%s`.","By":"invalid argument. Repository slug must be a string. Value: `%s`.","Bz":"invalid argument. Issue title must be a string. Value: `%s`.","C0":"invalid option. `%s` must be one of the following: \"%s\". Option: `%s`.","C1":"invalid argument. Repository name must be a string. Value: `%s`.","C2":"invalid option. `%s` option must be a valid URI. Option: `%s`.","C3":"invalid option. `%s` option must be a 20-character string. Option: `%s`.","C4":"invalid option. `%s` option must be a 40-character string. Option: `%s`.","C5":"invalid argument. Token id must be a nonnegative integer. Value: `%s`.","C6":"invalid argument. Workflow identifier must be a string. Value: `%s`.","C7":"invalid option. `%s` option must be an object of input key-value pairs. Option: `%s`.","C8":"invalid option. `%s` option must be a positive integer or \"last\". Option: `%s`.","C9":"invalid option. `%s` organization name option must be a string. Option: `%s`.","CA":"invalid option. Unknown method. Option: `%s`.","CB":"invalid option. Unrecognized `%s` option. Must be one of the following: \"%s\". Option: `%s`.","CC":"invalid argument. Repository slug must consist of an owner and a repository (e.g., \"stdlib-js/utils\"). Value: `%s`.","CD":"invalid argument. Topics argument must be an array of strings. Value: `%s`.","CE":"invalid option. `%s` option must be one of the following: \"%s\" or \"%s\". Option: `%s`.","CF":"invalid argument. Must provide a supported license SPDX identifier. Value: `%s`.","CG":"invalid argument. Must provide a supported file type. Value: `%s`.","CH":"invalid argument. First argument must be either a string or Buffer. Value: `%s`.","CI":"invalid argument. Second argument must be either a string or Buffer. Value: `%s`.","CJ":"invalid argument. A header object must map each filename extension to a license header string. `%s: %s`. Value: `%s`.","CK":"invalid argument. Second argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CL":"invalid argument. Second argument must be either a string, Buffer, or regular expression. Value: `%s`.","CM":"invalid argument. A header object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CN":"invalid argument. Second argument must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Value: `%s`.","CO":"invalid argument. Third argument must be either a string or Buffer. Value: `%s`.","CP":"invalid argument. Third argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CQ":"invalid argument. Database already contains an entry for the provided URI: `%s`.","CR":"invalid argument. Database already contains an entry for the provided id: `%s`.","CS":"invalid argument. First argument must be a URI. Value: `%s`.","CT":"invalid argument. Second argument must be either a string or regular expression. Value: `%s`.","CU":"invalid option. A `%s` option object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CV":"invalid option. `%s` option must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Option: `%s`.","CW":"invalid option. `%s` option must end with \"package.json\". Option: `%s`.","CX":"invalid argument. Last argument must be a callback function. Value: `%s`.","CY":"invalid option. `%s` option must be an array of package names. Option: `%s`.","CZ":"invalid argument. Version argument must be a string. Value: `%s`.","Ca":"invalid argument. Must provide either a string or a Buffer. Value: `%s`.","Cb":"invalid argument. Must provide either a string or Buffer. Value: `%s`.","Cc":"invalid argument. First argument must be either a string or array of strings. Value: `%s`.","Cd":"invalid option. `%s` option must be an object. Option: `%s`.","Ce":"unexpected error. File does not exist. Unable to resolve file: %s.","Cf":"invalid argument. Must provide either a string or an array of strings. Value: `%s`.","Cg":"invalid argument. Must provide either a string or an array of strings. Value: `%s`. Index: `%u`.","Ch":"unexpected error. Failed to sort packages. Detected the following dependency chain containing a cycle: `%s`.","Ci":"invalid node. Equation comments must have a valid label. Node: `%s`.","Cj":"invalid node. Equation comments must have valid alternate text. Node: `%s`.","Ck":"invalid node. Equation comments must have valid raw equation text. Node: `%s`.","Cl":"invalid node. Invalid equation comment. Ensure that the Markdown file includes both starting and ending equation comments. Node: `%s`.","Cm":"invalid node. Equation element must have a valid label. Node: `%s`.","Cn":"unexpected error. Code block configuration settings should be provided as comma-separated `key:value` pairs (e.g., `foo:true, bar:\"string\", baz:[\"error\",2]`). Value: `%s`.","Co":"unexpected error. Code block configuration values should be parseable as JSON. Value: `%s`.","Cp":"unexpected error. Encountered an error when executing code block. File: `%s`. Message: `%s`.","Cq":"unexpected error. Expected code block to throw an exception. File: `%s`.","Cr":"invalid node. Ensure that the Markdown file includes both a starting `
` and closing `
\\n\\n`. Node: `%s`.","Cs":"invalid node. Equation comments must have valid equation text. Node: `%s`.","Ct":"invalid node. Equation comments must have valid labels. Node: `%s`.","Cu":"invalid option. `%s` option must begin with \"@stdlib/\". Option: `%s`.","Cv":"invalid argument. First argument must be a list of file paths. Value: `%s`.","Cw":"invalid arguments. Subpopulation size must be less than or equal to the population size.","Cx":"invalid arguments. Number of draws must be less than or equal to the population size.","Cy":"invalid arguments. Fourth argument is not compatible with the number of input and output ndarrays.","Cz":"invalid arguments. Input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","D0":"invalid arguments. Length of the first argument is incompatible with the second and third arguments.","D1":"invalid argument. Provided collections must have the same length.","D2":"invalid argument. First argument must be an array-like object containing nonnegative integers.","D3":"invalid arguments. Input arrays must have the same length.","D4":"invalid argument. Must provide valid indices (i.e., must be a nonnegative integer less than or equal to the tuple length).","D5":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented. https://github.com/stdlib-js/stdlib/issues/new/choose","D6":"invalid operation. Parser is unable to parse new chunks, as the parser has been closed. To parse new chunks, create a new parser instance.","D7":"invalid operation. Parser is in an unrecoverable error state. To parse new chunks, create a new parser instance.","D8":"invalid argument. First argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","D9":"invalid argument. Second argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","DA":"invalid argument. First argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DB":"invalid argument. Second argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DC":"invalid assignment. `%s` size is less than the number of data elements. Number of elements: `%u`. Value: `%u`.","DD":"invalid assignment. `%s` must be a string or an array of strings. Value: `%s`.","DE":"invalid assignment. `%s` must be a number or an array of numbers. Value: `%s`.","DF":"invalid assignment. `%s` must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","DG":"invalid assignment. `%s` must be a finite number, Date, or null. Value: `%s`.","DH":"invalid assignment. `%s` must be a boolean or an array of booleans. Value: `%s`.","DI":"invalid assignment. `%s` must be a number or null. Value: `%s`.","DJ":"invalid assignment. `%s` must be an array of strings or an empty array. Value: `%s`.","DK":"invalid state. x and y are different lengths. x length: `%u`. y length: `%u`.","DL":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[%u].length: `%u`.","DM":"invalid assignment. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","DN":"invalid assignment. `%s` must be null or an array. Value: `%s`.","DO":"invalid arguments. Must provide equal length array-like objects. x length: `%u`. y length: `%u`.","DP":"invalid argument. The number of comparisons must be greater or equal to the number of p-values to be adjusted. Value: `%u`.","DQ":"invalid argument. Second argument must be one of the following: \"%s\". Value: `%s`.","DR":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%s`.","DS":"invalid argument. First argument must contain nonnegative integers. Indices: (%s). Value: `%s`.","DT":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Number of input array dimensions: %u.","DU":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Value: `%s`.","DV":"invalid arguments. Minimum support must be less than maximum support. Value: `(%f, %f)`.","DW":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `(%d, %d)`.","DX":"invalid argument. Mean parameter must be a positive number. Value: `%s`.","DY":"invalid argument. Mean parameter must be a probability. Value: `%s`.","DZ":"invalid option. `%s` option must be on the interval: [0, 1]. Option: `%f`.","Da":"invalid argument. Must provide a nonnegative number on the interval: [0, 1]. Value: `%f`.","Db":"invalid argument. First argument must either specify the order of the covariance matrix or be a square two-dimensional ndarray for storing the covariance matrix. Value: `%s`.","Dc":"invalid argument. Second argument must be a one-dimensional ndarray. Value: `%s`.","Dd":"invalid argument. Must provide a one-dimensional ndarray. Value: `%s`.","De":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square two-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","Df":"invalid argument. First argument must either specify the order of the correlation matrix or be a square two-dimensional ndarray for storing the correlation matrix. Value: `%s`.","Dg":"invalid argument. Input array must be an array-like object. Value: `%s`.","Dh":"invalid argument. Output array must be an array-like object. Value: `%s`.","Di":"invalid argument. Mask array offset must be a nonnegative integer. Value: `%s`.","Dj":"invalid argument. Must provide recognized data types. Unable to resolve a data type string. Value: `%s`.","Dk":"invalid option. `%s` option must be one of the following: ['%s']. Option: `%s`.","Dl":"invalid argument. Database already contains an entry for the provided URI. Value: `%s`.","Dm":"invalid argument. Database already contains an entry for the provided id. Value: `%s`.","Dn":"invalid argument. First argument must be an array of objects. Value: `%s`.","Do":"unexpected error. File does not exist. Unable to resolve file: `%s`.","Dp":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`.","Dq":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`. Index: `%u`.","Dr":"invalid argument. Must provide either an options object or a function. Value: `%s`.","Ds":"invalid option. `%s` option must be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","Dt":"invalid argument. Fourth argument must contain a single element equal to 0. Value: `%d`.","Du":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%s`.","Dv":"invalid argument. Must provide an ndarray. Value: `%s`.","Dw":"invalid argument. Second argument must be a supported data type policy. Value: `%s`.","Dx":"invalid argument. Must provide either an integer or a Date object. Value: `%s`.","Dy":"invalid argument. Must provide a valid duration string. Value: `%s`.","Dz":"invalid argument. Day number must be on the interval: [1, %u]. Value: `%d`.","E0":"invalid argument. First argument must be a string or integer. Value: `%s`.","E1":"invalid option. `%s` option must be one of the following: \"%s\". Value: `%s`.","E2":"invalid argument. Third argument must be either an integer (starting index) or a function. Value: `%s`.","E3":"invalid argument. Fourth argument must be either an integer (ending index) or a function. Value: `%s`.","E4":"invalid argument. Second argument must be a valid position (i.e., be within string bounds). Value: `%d`.","E5":"invalid argument. Must provide a valid code point (i.e., cannot exceed %u). Value: `%s`.","E6":"invalid argument. First argument must be astring. Value: `%s`.","E7":"invalid argument. Second argument must be either an integer (starting index) or a function. Value: `%s`.","E8":"invalid argument. Third argument must be either an integer (ending index) or a function. Value: `%s`.","E9":"invalid argument. ArrayBuffer byte length must be a multiple of %u. Byte length: `%u`.","EA":"invalid argument. Byte offset must be a multiple of %u. Value: `%u`.","EB":"invalid argument. First argument must have a length which is a multiple of %u. Length: `%u`.","EC":"invalid argument. Second argument must be a supported data type. Value: `%s`.","ED":"invalid argument. First argument must be one of the following data types: \"%s\". Value: `%s`.","EE":"invalid argument. Second argument must be either an integer (starting view index) or a function. Value: `%s`.","EF":"invalid argument. Third argument must be either an integer (ending view index) or a function. Value: `%s`.","EG":"invalid option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","EH":"invalid option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","EI":"invalid argument. Second argument must be either a scalar or an ndarray-like object. Value: `%s`.","EJ":"invalid argument. Minimum support must be less than maximum support. Value: `[%f, %f]`.","EK":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d, %d]`.","EL":"invalid %s. `state` array has an incompatible schema version. Expected: `%s`. Actual: `%s.`","EM":"invalid %s. `state` array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","EN":"invalid argument. Number of draws must be less than or equal to the population size. Value: `%u`.","EO":"invalid argument. Subpopulation size must be less than or equal to the population size. Value: `%u`.","EP":"invalid argument. Must provide a regular expression. Value: `%s`.","EQ":"invalid argument. Second argument must be an object containing property descriptors. Value: `%s`.","ER":"invalid argument. Must provide an object (except null). Value: `%s`.","ES":"invalid argument. First argument must be an object (except null). Value: `%s`.","ET":"unexpected error. Encountered an invalid record. Field %d on line %d contains a closing quote which is not immediately followed by a delimiter or newline.","EU":"unexpected error. Encountered an invalid record. Field %d on line %d contains an opening quote which does not immediately follow a delimiter or newline.","EV":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence which is not immediately followed by a special character sequence.","EW":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence within a quoted field which is not immediately followed by a quote sequence.","EX":"invalid argument. First argument must be a function having at least one parameter. Value: `%s`.","EY":"invalid argument. All arguments must be objects. Index: `%u`. Value: `%s`.","EZ":"invalid argument. First argument must be a non-null object. Value: `%s`.","Ea":"invalid argument. First argument must be an ndarray whose last dimension is of size %u. Actual size: `%u`.","Eb":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of eta * lambda. Value: `%f`.","Ec":"invalid argument. Output argument must be a one-dimensional ndarray. Value: `%s`.","Ed":"invalid argument. Must provide a two-dimensional ndarray. Value: `%s`.","Ee":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u`. Actual: `%u`.","Ef":"invalid argument. First argument must be an integer, null, or undefined. Value: `%s`.","Eg":"invalid argument. Second argument must be an integer, null, or undefined. Value: `%s`.","Eh":"invalid argument. Third argument must be an integer, null, or undefined. Value: `%s`.","Ei":"invalid argument. Third argument cannot be zero. Value: `%s`.","Ej":"invalid argument. First argument must be a valid subsequence string. Value: `%s`.","Ek":"invalid argument. A subsequence string must have a non-zero increment. Value: `%s`.","El":"invalid argument. The subsequence string resolves to a slice which exceeds index bounds. Value: `%s`.","Em":"invalid argument. Provided arguments must be either a Slice, integer, null, or undefined. Argument: `%d`. Value: `%s`.","En":"invalid operation. Unsupported slice operation. Value: `%s`.","Eo":"invalid operation. Number of array dimensions does not match the number of slice dimensions. Array shape: (%s). Slice dimensions: %u.","Ep":"invalid operation. Slice exceeds array bounds. Array shape: (%s).","Eq":"invalid operation. A subsequence increment must be a non-zero integer. Value: `%s`.","Er":"invalid operation. A subsequence may only include a single ellipsis. Value: `%s`.","Es":"invalid argument. Cannot write to a read-only array.","Et":"invalid argument. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Eu":"invalid argument. Slice arguments must be either a Slice, integer, null, or undefined. Value: `%s`.","Ev":"invalid operation. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Ew":"invalid operation. Assigned value cannot be safely cast to the target array data type. Data types: [%s, %s].","Ex":"invalid operation. Unsupported target array data type. Data type: `%s`.","Ey":"invalid argument. Index must be on the interval: [0, %d]. Value: `%d`.","Ez":"invalid argument. Slice exceeds array bounds. Array shape: (%s).","F0":"invalid argument. Input array values cannot be safely cast to the output array data type. Data types: [%s, %s].","F1":"invalid argument. Second argument must be an ndarray. Value: `%s`.","F2":"invalid argument. First argument must be an ndarray having at least two dimensions.","F3":"invalid argument. Second argument must be an array of nonnegative integers. Value: `%s`.","F4":"invalid option. Cannot write to read-only array.","F5":"invalid argument. First argument must be an array of nonnegative integers. Value: `%s`.","F6":"invalid argument. Must provide an ndarray having a supported data type. Value: `%s`.","F7":"invalid argument. First argument must be an ndarray having one or more dimensions. Number of dimensions: %d.","F8":"invalid argument. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","F9":"invalid argument. Third argument must be either a Slice, integer, null, or undefined. Value: `%s`.","FA":"invalid argument. First argument must be an ndarray having at least three dimensions.","FB":"invalid argument. Index must resolve to a value on the interval: [0, %d]. Value: `%d`.","FC":"invalid argument. First argument must be a recognized index mode. Value: `%s`.","FD":"invalid argument. Third argument exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","FE":"invalid argument. Number of indices does not match the number of array dimensions. Array shape: (%s). Number of indices: %u.","FF":"invalid argument. Each index argument must be either an integer, null, or undefined. Value: `%s`.","FG":"invalid argument. First argument must be a complex number. Value: `%s`.","FH":"invalid arguments. Input arrays must be broadcast compatible.","FI":"invalid argument. The first and second arguments must have the same length.","FJ":"invalid argument. First argument must be either an ndarray or an array of ndarrays. Value: `%s`.","FK":"invalid argument. An ndarray argument must be an ndarray. Value: `%s`.","FL":"invalid argument. Second argument must be a valid property name. Value: `%s`.","FM":"invalid argument. First argument must have a `%s` method.","FN":"invalid argument. Second argument must an array of strings. Value: `%s`.","FO":"invalid argument. Third argument must be a supported data type. Value: `%s`.","FP":"invalid argument. Index argument is out-of-bounds. Value: `%s`.","FQ":"invalid argument. Second argument must be a complex number. Value: `%s`.","FR":"invalid argument. Index arguments must be integers. Value: `%s`.","FS":"invalid argument. Slice exceeds array bounds. Array length: %d.","FT":"invalid argument. Input array and the output array slice are broadcast incompatible. Array length: %u. Desired length: %u.","FU":"invalid operation. Slice exceeds array bounds.","FV":"invalid argument. First argument must be a valid index array.","FW":"invalid operation. This array index instance has already been freed and can no longer be used.","FX":"invalid argument. First argument must be a complex-valued floating-point array. Value: `%s`.","FY":"invalid operation. Index exceeds array bounds.","FZ":"invalid operation. Unrecognized array index type. Value: `%s`.","Fa":"invalid operation. Unable to resolve array index. Value: `%s`.","Fb":"invalid option. `%s` option is missing a `%s` method. Option: `%s`.","Fc":"invalid operation. If not provided an initial value, an array must contain at least one element.","Fd":"invalid arguments. Must provide equal length array-like objects.","Fe":"Index out of bounds","Ff":"invalid option. `%s` option must be less than or equal to 64. Option: `%u`.","Fg":"invalid argument. Unable to parse input string as a complex number. Value: `%s`.","Fh":"invalid operation. Cannot access settings for a REPL which has already closed.","Fi":"invalid argument. First argument must be a recognized setting. Value: `%s`.","Fj":"invalid invocation. `this` is not a boolean array.","Fk":"invalid argument. Unable to parse commits for package: `%s`.","Fl":"invalid argument. Unrecognized release type: `%s`.","Fm":"invalid argument. First argument must be a supported BLAS memory layout. Value: `%s`.","Fn":"invalid argument. First argument must be an existing theme name. Value: `%s`.","Fo":"invalid argument. First argument must not be the default theme name. Value: `%s`.","Fp":"invalid argument. Second argument must be an object. Value: `%s`.","Fq":"invalid arguments. Number of values does not equal the number of falsy values in the mask array.","Fr":"invalid arguments. Insufficient values to satisfy mask array.","Fs":"invalid arguments. Input arguments are not broadcast compatible.","Ft":"invalid arguments. Number of values does not equal the number of truthy values in the mask array.","Fu":"invalid argument. Third argument cannot be safely cast to the input array data type. Data types: [%s, %s].","Fv":"invalid argument. First argument must be a boolean. Value: `%s`.","Fw":"invalid argument. The third argument must be broadcast compatible with the second argument. Array shape: (%d). Desired shape: (%d).","Fx":"invalid argument. First argument must be a valid order. Value: `%s`.","Fy":"invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","Fz":"invalid argument. Third argument must be a nonnegative integer. Value: `%d`.","G0":"invalid argument. Eighth argument must be non-zero. Value: `%d`.","G1":"invalid argument. Twelfth argument must be non-zero. Value: `%d`.","G2":"invalid argument. Seventh argument must be non-zero. Value: `%d`.","G3":"invalid argument. Tenth argument must be non-zero. Value: `%d`.","G4":"invalid argument. Fourth argument must be greater than or equal to max(1,%d). Value: `%d`.","G5":"invalid argument. First argument must be a string or an array of strings. Value: `%s`.","G6":"invalid option. `%s` option must be a valid mode. Option: `%s`.","G7":"invalid argument. First argument must be a nonnegative integer. Value: `%d`.","G8":"invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.","G9":"invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.","GA":"invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GB":"invalid argument. Sixth argument must be non-zero. Value: `%d`.","GC":"invalid argument. Tenth argument must be greater than or equal to max(1,%d). Value: `%d`.","GD":"invalid argument. First argument must specify whether the reference the lower or upper triangular matrix. Value: `%s`.","GE":"invalid argument. Second argument must be a nonnegative integer. Value: `%d`.","GF":"invalid argument. Fifth argument must be non-zero. Value: `%d`.","GG":"invalid argument. Second argument must be a valid transpose operation. Value: `%s`.","GH":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.","GI":"invalid argument. Ninth argument must be non-zero.","GJ":"invalid argument. Twelfth argument must be non-zero.","GK":"invalid argument. Eleventh argument must be non-zero.","GL":"invalid argument. Fifteenth argument must be non-zero.","GM":"invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.","GN":"invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GO":"invalid argument. Third argument must be a valid transpose operation. Value: `%s`.","GP":"invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.","GQ":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%d`.","GR":"invalid argument. Seventh argument must be greater than or equal to max(1,%d). Value: `%d`.","GS":"invalid argument. Ninth argument must be non-zero. Value: `%d`.","GT":"invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","GU":"invalid argument. Third argument must be a valid diagonal type. Value: `%s`.","GV":"invalid argument. First argument must be a valid transpose operation. Value: `%s`.","GW":"invalid argument. Tenth argument must be non-zero.","GX":"invalid argument. Fourteenth argument must be non-zero.","GY":"invalid arguments. Array must have the same shape.","GZ":"invalid argument. Second argument must be an array of integers. Value: `%s`.","Ga":"invalid argument. First argument must be an ndarray having at least %d dimensions.","Gb":"invalid argument. Dimension indices must be sorted in ascending order. Value: `%s`.","Gc":"invalid argument. Dimension indices must be unique. Value: `%s`.","Gd":"invalid argument. First argument must be an array of ndarrays. Value: `%s`.","Ge":"invalid argument. First argument must be an array of ndarrays which are broadcast-compatible. Value: `%s`.","Gf":"invalid argument. First argument must be an array of ndarrays having at least %d dimensions after broadcasting.","Gg":"invalid argument. Index argument is out-of-bounds. Value: `%d`.","Gh":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%d`.","Gi":"invalid argument. Ninth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gj":"invalid argument. Eleventh argument must be greater than or equal to max(1,%d). Value: `%d`.","Gk":"invalid argument. Fourteenth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gl":"invalid argument. First argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gm":"invalid argument. Second argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gn":"invalid argument. First argument must have at least one dimension.","Go":"invalid argument. Second argument must have at least one dimension.","Gp":"invalid argument. Third argument must be a negative integer. Value: `%s`.","Gq":"invalid argument. Third argument must be a value on the interval: [%d,%d]. Value: `%d`.","Gr":"invalid argument. The size of the contracted dimension must be the same for both input ndarrays. Dim(%s,%d) = %d. Dim(%s,%d) = %d.","Gs":"invalid arguments. Input ndarrays must be broadcast compatible. Shape(%s) = (%s). Shape(%s) = (%s).","Gt":"invalid argument. Cannot write to read-only array.","Gu":"invalid arguments. The first and second arguments must have the same shape.","Gv":"unexpected error. Environment does not support WebAssembly.","Gw":"invalid invocation. Unable to perform write operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gx":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Resize the underlying memory instance in order to accommodate the list of provided values.","Gy":"invalid invocation. Unable to perform read operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gz":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Not enough values to fill the provided output array.","H0":"invalid argument. Must provide a WebAssembly memory instance. Value: `%s`.","H1":"invalid argument. First argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H2":"invalid argument. Second argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H3":"invalid invocation. `this` is not a Float64ArrayFE.","H4":"invalid argument. First argument must be a supported byte order. Value: `%s`.","H5":"invalid argument. Second argument must a data type. Value: `%s`.","H6":"invalid argument. First argument must be an ndarray-like object having a supported data type. Value: `%s`.","H7":"invalid argument. Second argument must be an ndarray-like object having a supported data type. Value: `%s`.","H8":"invalid invocation. `this` is not %s %s.","H9":"invalid argument. First argument must be a supported data type. Value: `%s`.","HA":"invalid argument. Must provide an ArrayBuffer. Value: `%s`.","HB":"invalid argument. Second argument must be a data type. Value: `%s`.","HC":"invalid option. Each key object must have a `name` property. Value: `%s`.","HD":"invalid option. Each key object's `name` property must be a string. Value: `%s`.","HE":"invalid option. Each key object's `%s` property must be a boolean. Value: `%s`.","HF":"invalid option. Each action must be an array of objects. Value: `%s`.","HG":"invalid argument. First argument must be a valid index ndarray.","HH":"invalid operation. This ndarray index instance has already been freed and can no longer be used.","HI":"invalid operation. Unrecognized ndarray index type. Value: `%s`.","HJ":"invalid operation. Index exceeds ndarray bounds.","HK":"invalid operation. Number of indices does not match the number of array dimensions. Array shape: (%s). Index dimensions: %u.","HL":"invalid operation. Unable to resolve ndarray index. Value: `%s`.","HM":"invalid argument. First argument is not compatible with the specified index \"kind\". Type: %s. Kind: %s.","HN":"invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.","HO":"invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.","HP":"invalid argument. Must provide unique dimension indices. Value: `[%s]`.","HQ":"invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.","HR":"invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.","HS":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","HT":"invalid argument. Each key in the keybindings argument must correspond to a single action. Value: `%s`","HU":"invalid argument. First argument must be a valid action name. Value: `%s`.","HV":"invalid argument. Each key in the keys argument must correspond to a single action. Value: `%s`","HW":"invalid argument. Second argument must be an array of data types. Value: `%s`.","HX":"invalid argument. Third argument must be an array of data types. Value: `%s`.","HY":"invalid argument. Fourth argument must be a supported output data type policy. Value: `%s`.","HZ":"invalid argument. First argument must have one of the following data types: \"%s\". Data type: `%s`.","Ha":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d.","Hb":"invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].","Hc":"invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].","Hd":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].","He":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.","Hf":"invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).","Hg":"invalid argument. The second argument cannot be safely cast to the input array data type. Data type: %s. Value: `%s`.","Hh":"invalid argument. Second argument must be broadcast-compatible with the non-reduced dimensions of the input array.","Hi":"invalid argument. Second argument cannot be safely cast to the input array data type. Value: `%s`.","Hj":"invalid argument. Third argument must be an ndarray-like object. Value: `%s`.","Hk":"invalid option. `%s` option must be an array of integers. Option: `%s`.","Hl":"invalid option. `%s` option contains an out-of-bounds dimension index. Option: [%s].","Hm":"invalid option. `%s` option specifies more dimensions than exists in the input array. Number of dimensions: %d. Option: [%s].","Hn":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].","Ho":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).","Hp":"invalid argument. Second argument must be an ndarray-like object. Value: `%s`.","Hq":"invalid argument. Second argument must have one of the following data types: \"%s\". Data type: `%s`.","Hr":"invalid argument. Fourteenth argument must be non-zero. Value: `%d`.","Hs":"invalid argument. Seventeenth argument must be non-zero. Value: `%d`.","Ht":"invalid argument. Eighteenth argument must be non-zero. Value: `%d`.","Hu":"invalid option. `%s` option contains duplicate indices. Option: [%s].","Hv":"invalid argument. First argument must be an object having a \"default\" property and an associated method.","Hw":"invalid argument. Second argument must contain arrays of data types. Value: `%s`.","Hx":"invalid argument. Argument %d must have one of the following data types: \"%s\". Data type: `%s`.","Hy":"invalid argument. Argument %d must be an ndarray-like object. Value: `%s`.","Hz":"invalid arguments. Input and output arrays must have the same shape.","I0":"invalid argument. First argument specifies an unexpected number of types. A pair of input and output ndarray data types must be specified for each provided strided function.","I1":"invalid argument. First argument specifies an unexpected number of types. An input ndarray data type must be specified for each provided strided function.","I2":"invalid argument. Array arguments after the first two arrays must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","I3":"invalid argument. Loop dimensions must be consistent across all provided arrays. Input array shape: [%s]. Loop dimension indices: [%s]. Loop dimensions: [%s]. Array shape: [%s] (index: %d).","I4":"invalid argument. First argument must be an object having a \"types\" property whose associated value is an array-like object.","I5":"invalid argument. First argument must be an object having a \"fcns\" property whose associated value is an array-like object containing functions.","I6":"invalid argument. Fourth argument must be an object having a supported output data type policy. Value: `%s`.","I7":"invalid argument. Fourth argument must be an object having a supported casting policy. Value: `%s`.","I8":"invalid operation. Unable to promote the input and output data types. Input data type: %s. Output data type: %s.","I9":"invalid argument. Third argument must be a supported casting policy. Value: `%s`.","IA":"invalid option. `%s` option must be an object containing properties having values which are objects. Option: `%s`.","IB":"invalid option. `%s` option must be an object having %s `%s` property which is an array of strings. Option: `%s`.","IC":"invalid option. `%s` option must have %s `%s` property.","ID":"invalid argument. Second argument must be either an ndarray or a numeric scalar value. Value: `%s`.","IE":"invalid argument. Eleventh argument must be non-zero. Value: `%d`.","IF":"invalid option. `%s` option must be a valid memory layout. Option: `%s`.","IG":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d. ndims(z) == %d.","IH":"invalid argument. Unable to resolve an output data type. The output data type policy is \"same\" and yet the input data types are not equal. Data types: [%s].","II":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input data types can be safely cast. Data types: [%s].","IJ":"invalid argument. %s argument must have one of the following data types: \"%s\". Data type: `%s`.","IK":"invalid option. `%s` option must be a valid index mode. Option: `%s`.","IL":"invalid option. `%s` option must be a memory layout. Option: `%s`.","IM":"invalid argument. ArrayBuffer is incompatible with the specified data type. Value: `%s`.","IN":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, iterable, data type, or options object. Value: `%s`.","IO":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or iterable. Value: `%s`.","IP":"invalid argument. Third argument must be a recognized/supported data type. Value: `%s`.","IQ":"invalid argument. Fourth argument must be a recognized/supported data type. Value: `%s`.","IR":"invalid argument. Fifth argument must be greater than or equal to max(1,%d). Value: `%d`.","IS":"invalid argument. Second argument must have an integer data type. Value: `%s`.","IT":"invalid argument. Second argument must be an integer or an ndarray-like object. Value: `%s`.","IU":"invalid argument. Union types may only be initialized by a single member.","IV":"invalid invocation. `this` is not a struct instance.","IW":"invalid operation. struct does not have any fields.","IX":"unexpected error. Unrecognized data type. Value: `%s`.","IY":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Data types: [%s, %s].","IZ":"invalid argument. Field objects must have the following properties: \"%s\". Value: `%s`.","Ia":"invalid argument. Union types cannot contain nested union types. Value: `%s`.","Ib":"invalid argument. Union types can only contain one field with a default value. Value: `%s`.","Ic":"invalid argument. Union types must contain fields having the same byte length. Value: `%s`.","Id":"invalid argument. `%s` field must be a string. Value: `%s`.","Ie":"invalid argument. `%s` field must be a boolean. Value: `%s`.","If":"invalid argument. `%s` field must be a positive integer. Value: `%s`.","Ig":"invalid assignment. `%s` must be a `struct` instance. Value: `%s`.","Ih":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Value: `%s`.","Ii":"invalid assignment. `%s` must be a `struct` instance having the same byte length.","Ij":"invalid assignment. `%s` must be an array-like object. Value: `%s`.","Ik":"invalid assignment. `%s` must be an array-like object having length %u.","Il":"invalid argument. Byte length must be a nonnegative integer. Value: `%s`.","Im":"invalid argument. ArrayBuffer has insufficient capacity. Minimum capacity: `%u`.","In":"invalid argument. First argument must be a `struct` instance. Value: `%s`.","Io":"invalid argument. `%s` field must be one of the following: \"%s\". Value: `%s`.","Ip":"invalid argument. First argument must be an array of objects having unique field names. Value: `%s`.","Iq":"invalid argument. `%s` field must be a non-empty string. Value: `%s`.","Ir":"invalid argument. First argument must be an array of objects. Value: `%s`. Index: `%d`.","Is":"invalid argument. Union types must be an array of objects. Value: `%s`. Index: `%d`.","It":"invalid argument. Field name must be one of the following: \"%s\". Value: `%s`.","Iu":"invalid argument. `%s` field must be either a struct type or one of the following: \"%s\". Value: `%s`.","Iv":"invalid assignment. `%s` must be an array-like object containing `struct` instances having the same byte length.","Iw":"invalid argument. First argument must be one of the following: \"%s\". Value: `%s`.","Ix":"invalid argument. First argument must be an ArrayBuffer or a data object. Value: `%s`.","Iy":"invalid argument. First argument must be either a struct constructor or struct schema. Value: `%s`.","Iz":"invalid argument. Each element of a provided input array must be a valid object or a struct instance having the same layout as elements in the desired output array.","J0":"invalid argument. Environment lacks Symbol.iterator support. First argument must be a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","J1":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","J2":"invalid argument. Each element of a provided input iterable must be either a valid object or a struct instance having the same layout as elements in the desired output array.","J3":"invalid argument. Second argument must be a multiple of %u. Value: `%u`.","J4":"invalid argument. Second argument exceeds the bounds of the ArrayBuffer. Value: `%s`.","J5":"invalid argument. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","J6":"invalid invocation. `this` is not a %s.","J7":"invalid argument. Must provide either a valid object or a struct instance. Value: `%s`.","J8":"invalid argument. First argument must be a valid orientation. Value: `%s`.","J9":"invalid argument. Second argument must be a valid orientation. Value: `%s`.","JA":"invalid argument. The first argument must be an ndarray. Value: `%s`.","JB":"invalid argument. Second argument must be either an ndarray or a scalar value. Value: `%s`.","JC":"invalid argument. Third argument must be an ndarray. Value: `%s`.","JD":"invalid argument. Third argument must be either an ndarray or an integer. Value: `%s`.","JE":"invalid operation. Environment lacks support for HTTP/2. Ensure that you are running on a Node.js version which supports HTTP/2 and has been built to include support for the Node.js `crypto` module.","JF":"invalid argument. Input arrays must have the same number of dimensions. First array dimensions: %d. Second array dimensions: %d.","JG":"invalid argument. Input arrays must have the same shape. First array shape: [%s]. Second array shape: [%s].","JH":"invalid argument. Output array must have the same number of non-reduced dimensions as input arrays. Input array shape: [%s]. Number of non-reduced dimensions: %d. Output array shape: [%s].","JI":"invalid argument. Array arguments after the first array must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","JJ":"invalid argument. Second argument contains an out-of-bounds index. Array shape: (%s). Value: `[%s]`.","JK":"invalid argument. Thirteenth argument must be non-zero. Value: `%d`.","JL":"invalid argument. Sixth argument must be greater than or equal to max(1,%d). Value: `%d`.","JM":"invalid argument. Fifth argument must be non-zero. Value: `%s`.","JN":"invalid argument. Sixth argument must be non-zero. Value: `%s`.","JO":"invalid arguments. Unable to resolve an ndarray function supporting the provided argument data types.","JP":"invalid argument. First argument specifies an unexpected number of types. Two input ndarray data types must be specified for each provided strided function.","JQ":"invalid argument. First argument specifies an unexpected number of types. An output ndarray data type must be specified for each provided strided function.","JR":"invalid operation. Unable to promote the input and output data types. Input data types: [%s]. Output data type: %s.","JS":"invalid argument. Fourth argument must be a supported casting policy. Value: `%s`.","JT":"invalid argument. Fourth argument must be an ndarray. Value: `%s`.","JU":"invalid option. `%s` option must be a supported data type. Option: `%s`.","JV":"invalid argument. First argument must be either a supported data type string, a struct constructor, or another data type instance. Value: `%s`.","JW":"invalid argument. Second argument must be a valid sort order. Value: `%s`.","JX":"invalid argument. Second argument must be either an ndarray, a numeric scalar value, or a supported string. Value: `%s`.","JY":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input ndarrays can be safely cast. Data types: [%s].","JZ":"invalid argument. The list of input ndarrays cannot be safely cast to the data of the output ndarray. Input data types: [%s]. Output data type: %s.","Ja":"invalid argument. Second argument is not broadcast compatible with the list of input ndarrays. Array shape: (%s). Desired shape: (%s).","Jb":"invalid argument. Second argument must be a negative integer. Value: `%s`.","Jc":"invalid argument. First argument cannot be safely cast to the output data type. Data types: [%s, %s].","Jd":"invalid option. First argument cannot be safely cast to the specified data type. Input data type: %s. Option: `%s`.","Je":"invalid argument. First argument must be an ndarray having at least one dimension.","Jf":"invalid argument. Second argument must be either a number, complex number, or an ndarray. Value: `%s`.","Jg":"invalid argument. Third argument must have one of the following data types: \"%s\". Data type: `%s`.","Jh":"invalid argument. Third argument must be either a number, complex number, or an ndarray. Value: `%s`.","Ji":"invalid argument. Fourth argument must have one of the following data types: \"%s\". Data type: `%s`.","Jj":"invalid argument. Fourth argument must be either a boolean or an ndarray. Value: `%s`.","Jk":"invalid argument. First argument must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","Jl":"invalid option. `%s` option must be a supported order. Option: `%s`.","Jm":"invalid argument. Argument %d cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s.","Jn":"invalid invocation. Must provide at least two arguments.","Jo":"invalid invocation. Must provide at least one argument.","Jp":"invalid argument. Last argument must be a one-dimensional ndarray. Value: `%s`.","Jq":"invalid argument. Each ndarray argument must have fewer than two dimensions. Argument: %d.","Jr":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number of observations must be greater than zero).","Js":"invalid argument. First argument must be an ndarray having two or more dimensions.","Jt":"invalid invocation. Must provide at least three arguments.","Ju":"invalid invocation. `this` is not a floating-point number array.","Jv":"invalid argument. The number of elements (means) in the second argument must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","Jw":"%s %s failed with exit code: %s.","Jx":"%s %s failed due to termination signal: %s.","Jy":"invalid argument. Second argument must be either an ndarray or an integer. Value: `%s`.","Jz":"invalid argument. Second argument cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s.","K0":"invalid option. `%s` option must be a zero-dimensional ndarray.","K1":"invalid argument. Second argument must be either an ndarray-like object, a numeric value, or a supported string. Value: `%s`.","K2":"invalid argument. Second argument must be a zero-dimensional ndarray.","K3":"invalid argument. Must provide an integer on the interval [0, 2^64-1]. Value: `%s`.","K4":"invalid argument. Must provide an integer on the interval [0, 2^53-1]. Value: `%s`.","K5":"invalid argument. Must provide an array. Value: `%s`.","K6":"invalid argument. Must provide an array of length 2. Value: `[%s]`.","K7":"invalid argument. Must provide an array of integer values on the interval [%u, %u]. Value: `[%s]`.","K8":"invalid argument. First argument must be a nonnegative integer on the interval [%u, %u]. Value: `%s`.","K9":"invalid argument. Second argument must be a nonnegative integer on the interval [%u, %u]. Value: `%s`.","KA":"invalid argument. Must provide an integer on the interval [%d, %d]. Value: `%s`.","KB":"invalid argument. Fourth argument must be an ndarray-like object. Value: `%s`.","KC":"invalid option. `%s` option must be an array of nonnegative integers. Option: `%s`.","KD":"invalid argument. First argument must have one of the following data types: \"%s\". Value: `%s`.","KE":"invalid argument. Must provide an ndarray having two or more dimensions. Number of dimensions: `%u`.","KF":"invalid option. `%s` option must be a negative integer. Option: `%s`.","KG":"invalid argument. Third argument must be an array of integers. Value: `%s`.","KH":"invalid argument. Third argument must be an array of nonnegative integers. Value: `%s`.","KI":"invalid argument. Must provide a complex-valued floating-point ndarray. Value: `%s`.","KJ":"invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","KK":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d. ndims(z) == %d. ndims(w) == %d.","KL":"invalid argument. Second argument must have at least as many elements as the number of dimensions of the first argument. Number of input dimensions: `%u`. Number of repetitions: `%u`.","KM":"invalid argument. Must provide exactly two dimension indices. Value: `[%s]`.","KN":"invalid argument. First argument must be an ndarray having two or more dimensions. Number of dimensions: %d.","KO":"invalid argument. The first argument cannot be safely cast to the output array data type. Data type: %s. Value: `%s`.","KP":"invalid argument. Product of the sizes must be equal to the size of the dimension to be unflattened. Dimension: %d. Size: %d. Value: `[%s]`.","KQ":"invalid argument. First argument must contain one or more ndarrays. Value: `%s`.","KR":"invalid argument. First argument must be an array-like object containing one or more ndarrays. Value: `%s`.","KS":"invalid argument. Must provide one- or two-dimensional ndarrays. Number of dimensions: `%u`.","KT":"invalid argument. All ndarrays must have the same number of columns. Expected number of columns: `%u`. Actual number of columns: `%u`.","KU":"invalid argument. Second argument must be a two-dimensional ndarray. Number of dimensions: `%u`.","KV":"invalid option. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","KW":"invalid argument. All ndarrays must have the same number of rows. Expected number of rows: `%u`. Actual number of rows: `%u`.","KX":"invalid argument. Second argument must be a string or an array of strings. Value: `%s`.","KY":"invalid invocation. Insufficient arguments. Array shape: (%s). Number of indices: %u.","KZ":"invalid invocation. Too many arguments. Array shape: (%s). Number of indices: %u.","Ka":"invalid argument. Must provide a shape, ArrayBuffer, array-like object, iterable, data type, or options object. Value: `%s`.","Kb":"invalid argument. First argument must be a shape, ArrayBuffer, array-like object, or iterable. Value: `%s`.","Kc":"invalid argument. Third argument must be a valid shape. Value: `%s`.","Kd":"invalid argument. Fifth argument must be a recognized/supported data type. Value: `%s`.","Ke":"invalid argument. Second argument must be a supported distance metric. Value: `%s`."} +{"10":"invalid operation. Cannot reset a REPL which has already closed.","11":"invalid operation. Cannot clear a REPL which has already closed.","12":"invalid operation. Cannot clear the line of a REPL which has already closed.","13":"invalid operation. Cannot clear the command buffer of a REPL which has already closed.","14":"invalid argument. Provided command either does not contain an `await` expression or contains a top-level `return` which is not allowed.","15":"invalid argument. Must provide a program AST node.","16":"invalid invocation. Insufficient arguments. Must provide a REPL instance.","17":"invalid operation. No presentation to reload. Use the `load()` method to load a presentation.","18":"invalid operation. No presentation file to watch. Use the `load()` method to load a presentation.","19":"unexpected error. Encountered a \"rename\" event for the source presentation file. No longer watching source presentation file for changes.","20":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user is watching, an access token.","21":"unexpected error. Unable to resolve package directory as unable to find a `package.json` in a parent directory.","22":"invalid argument. Source code does not contain JSDoc comment with function options.","23":"unexpected error. Unable to resolve root project directory.","24":"invalid argument. An iterator must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","25":"invalid argument. Callback must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","26":"invalid argument. Array-like object arguments must have a length which is a multiple of two. Length: `%u`.","27":"invalid argument. Array-like object and typed array arguments must have a length which is a multiple of two. Length: `%u`.","28":"invalid argument. ArrayBuffer byte length must be a multiple of `%u`. Byte length: `%u`.","29":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","30":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.","31":"invalid argument. Fifth argument must be a function. Value: `%s`.","32":"invalid argument. Fourth argument must be a function. Value: `%s`.","33":"invalid argument. Second argument must be either an integer (starting index) or a callback function. Value: `%s`.","34":"invalid argument. Third argument must be either an integer (ending index) or a callback function. Value: `%s`.","35":"invalid argument. Second argument must be either an integer (starting view index) or a callback function. Value: `%s`.","36":"invalid argument. Third argument must be either an integer (ending view index) or a callback function. Value: `%s`.","37":"invalid argument. Second argument must be a recognized data type. Value: `%s`.","38":"invalid argument. First argument must be array-like. Value: `%s`.","39":"invalid argument. Second argument must be a string. Value: `%s`.","40":"invalid argument. Must provide either a Date object, a JavaScript timestamp (i.e., a nonnegative integer), or a date string. Value: `%s`.","41":"invalid option. Unrecognized rounding mode. Option: `%s`.","42":"invalid argument. Third argument must be either a nonnegative integer or an options object. Value: `%s`.","43":"invalid argument. Fourth argument must be an object. Value: `%s`.","44":"invalid argument. First argument must an iterator protocol-compliant object. Value: `%s`.","45":"invalid argument. Second argument must be a positive integer. Value: `%s`.","46":"invalid argument. First argument must be an iterator protocol-compliant object. Value: `%s`.","47":"invalid argument. Must provide an object. Value: `%s`.","48":"invalid argument. Object property values must be functions. Key: `%s`. Value: `%s`.","49":"invalid argument. First argument must be a number. Value: `%s`.","50":"invalid option. Second `%s` parameter option must be a positive integer. Option: `%s`.","51":"invalid argument. First argument must be an array. Value: `%s`.","52":"invalid argument. First argument must be an array of length `%u`. Value: `%s`.","53":"invalid argument. First argument must be an array of length %u. Value: `%s`.","54":"unexpected error. Scaling weight vector by nonpositive value, likely due to too large value of eta * lambda. Value: `%f`.","55":"invalid argument. Second argument must be a boolean. Value: `%s`.","56":"invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.","57":"invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.","58":"invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.","59":"invalid option. `%s` option must be a recognized casting mode. Option: `%s`.","60":"invalid argument. Input string must have a length equal to %u. Value: `%s`.","61":"invalid assignment. `%s` must be a boolean. Value: `%s`.","62":"invalid assignment. `%s` must be a string. Value: `%s`.","63":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","64":"invalid assignment. `%s` must be a positive number. Value: `%s`.","65":"invalid assignment. `%s` must be either an array of strings or an empty array. Value: `%s`.","66":"invalid assignment. `%s` must be a number or number array. Value: `%s`.","67":"invalid assignment. A `%s` must be a number on the interval: [0, 1]. Value: `%f`.","68":"invalid assignment. `%s` must be a string or a string array. Value: `%s`","69":"invalid assignment. Unsupported/unrecognized line style. Must be one of the following: \"%s\". Value: `%s`.","70":"invalid argument. Must provide a Uint32Array. Value: `%s`.","71":"invalid argument. First argument must be a positive number. Value: `%s`.","72":"invalid argument. Second argument must be a positive number. Value: `%s`.","73":"invalid argument. Second argument must be a probability. Value: `%s`.","74":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%s`.","75":"invalid option. `%s` option must have a `MIN` property specifying the minimum possible pseudorandom integer value.","76":"invalid option. `%s` option must have a `MAX` property specifying the maximum possible pseudorandom integer value.","77":"invalid argument. First argument must be an integer and not NaN. Value: `%s`.","78":"invalid argument. Second argument must be an integer and not NaN. Value: `%s`.","79":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d,%d]`.","80":"invalid argument. First argument must be either a string containing presentation text or an options object specifying a presentation file to load. Value: `%s`.","81":"invalid argument. Second argument must be an options object. Value: `%s`.","82":"invalid argument. Invalid presentation identifier. Must be either a string or nonnegative integer. Value: `%s`.","83":"invalid argument. Workspace name already exists. Value: `%s`.","84":"invalid argument. Must provide a string, regular expression, nonnegative integer, or an array of nonnegative integers. Value: `%s`.","85":"invalid argument. Unrecognized tutorial name. Value: `%s`.","86":"invalid argument. Documentation argument must be a string. Value: `%s`.","87":"invalid option. `%s` option must be a regular expression. Option: `%s`.","88":"internal error. Unrecognized pattern type: `%s`.","89":"invalid option. `%s` option must be a readable stream. Option: `%s`.","90":"invalid argument. Denominator degrees of freedom must be a positive number. Value: `%s`.","91":"invalid argument. Scale parameter must be a number. Value: `%s`.","92":"invalid argument. Mean parameter `%s` must be a probability. Value: `%s`.","93":"invalid argument. Population size must be a nonnegative integer. Value: `%s`.","94":"invalid argument. Subpopulation size must be a nonnegative integer. Value: `%s`.","95":"invalid argument. Number of draws must be a nonnegative integer. Value: `%s`.","96":"invalid assignment. Must be a nonnegative integer. Value: `%s`.","97":"invalid assignment. Must be larger than or equal to %u. Value: `%u`.","98":"invalid assignment. Must be less than or equal to %u. Value: `%u`.","99":"invalid argument. Number of trials until experiment is stopped must be a positive number. Value: `%s`.","00":"not implemented","01":"invalid invocation. `this` context must be a constructor.","02":"invalid invocation. `this` is not a complex number array.","03":"invalid arguments. Target array lacks sufficient storage to accommodate source values.","04":"invalid arguments. Creating a generic array from an ArrayBuffer is not supported.","05":"invalid arguments. Must provide a length, typed array, array-like object, or an iterable.","06":"invalid arguments. Generated array exceeds maximum array length.","07":"invalid arguments. If either of the first two arguments are complex numbers, the output array must be a complex number array or a \"generic\" array-like object.","08":"invalid arguments. If either of the first two arguments are complex numbers, the output array data type must be a complex number data type or \"generic\".","09":"not supported. The current environment does not support SharedArrayBuffers, and, unfortunately, SharedArrayBuffers cannot be polyfilled. For shared memory applications, upgrade your runtime environment to one which supports SharedArrayBuffers.","0A":"insufficient arguments. Must provide a search value.","0B":"invalid argument. Attempted to add duplicate listener.","0C":"exception","0D":"unexpected error. Benchmark failed.","0E":"unexpected error. Invalid benchmark.","0F":"unexpected error.","0G":"invalid invocation. Constructor must be called with the `new` keyword.","0H":"unexpected error. Max retries exceeded. Too many open files.","0I":"insufficient arguments. Must provide two or more iterators.","0J":"insufficient arguments. Must provide both an iterator and a static value.","0K":"invalid invocation. `this` is not a fluent interface iterator.","0L":"insufficient arguments. Must provide a hash function.","0M":"invalid argument. Iterator arguments must be iterator protocol-compliant objects.","0N":"insufficient arguments. Must provide at least one iterator function.","0O":"invalid argument. Providing a number is not supported.","0P":"invalid argument. Providing a complex number is not supported.","0Q":"invalid argument. Providing an ndarray is not supported.","0R":"invalid argument. Providing an array-like object is not supported.","0S":"invalid argument. If the first argument is an ndarray, the second argument must be an ndarray.","0T":"invalid argument. Output array must have the same number of elements (i.e., length) as the input array.","0U":"invalid argument. If the first argument is an array-like object, the second argument must be an array-like object.","0V":"invalid argument. Providing a number is not supported. Consider providing a zero-dimensional ndarray containing the numeric value.","0W":"invalid argument. Providing a complex number is not supported. Consider providing a zero-dimensional ndarray containing the complex number value.","0X":"invalid arguments. Must provide either a data source, array shape, or both.","0Y":"invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.","0Z":"invalid argument. Cannot broadcast an array to a shape having fewer dimensions. Arrays can only be broadcasted to shapes having the same or more dimensions.","0a":"invalid argument. First argument must contain at least one element.","0b":"invalid arguments. The length of the first argument is incompatible with the second and third arguments.","0c":"invalid argument. Must provide an ndarray having two or more dimensions.","0d":"invalid arguments. Arrays must have the same shape.","0e":"invalid invocation. Cannot write to a read-only array.","0f":"invalid argument. Fourth argument length must be equal to 1 when creating a zero-dimensional ndarray.","0g":"invalid arguments. The input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","0h":"invalid arguments. Interface must accept at least one input and/or output ndarray. Based on the provided arguments, `nin+nout` equals `0`.","0i":"invalid arguments. Fourth argument does not equal the number of input and output ndarrays.","0j":"invalid argument. Unexpected number of types. A type must be specified for each input and output ndarray for each provided ndarray function.","0k":"invalid argument. The third argument must have the same number of elements as the first argument.","0l":"invalid invocation. Insufficient arguments.","0m":"invalid invocation. Too many arguments.","0n":"invalid arguments. Unable to resolve an ndarray function supporting the provided array argument data types.","0o":"invalid operation. Unable to load Electron. Ensure Electron is installed and try again.","0p":"invalid operation. A browser environment has no support for changing the current working directory.","0q":"invalid operation. The environment does not support reading from `stdin`.","0r":"unexpected error. PRNG returned NaN.","0s":"invalid argument. Third argument must be less than or equal to the first argument.","0t":"invalid argument. Second argument must be less than or equal to the first argument.","0u":"invalid operation. Cannot delete the `base` workspace.","0v":"invalid invocation. Must provide either a string containing presentation text or an options object specifying a presentation file to load.","0w":"invalid argument. When not provided presentation text, an options argument must specify a presentation file to load.","0x":"invalid invocation. Not currently in a presentation workspace. Must provide either a string or nonnegative integer which corresponds to the identifier of the presentation to be stopped.","0y":"unexpected error. Command execution terminated.","0z":"invalid operation. Cannot load a file into a REPL which has already closed.","1A":"invalid arguments. First and second arguments must be arrays having the same length.","1B":"invalid arguments. Subpopulation size must be less than or equal to population size.","1C":"invalid arguments. Number of draws must be less than or equal to population size.","1D":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number number of observations must be greater than zero).","1E":"invalid arguments. First and second arguments must have the same length.","1F":"invalid arguments. First and second arguments must be arrays having the same length.","1G":"invalid arguments. First and second argument must have the same length.","1H":"invalid arguments. Not enough observations. First and second arguments must contain at least four observations.","1I":"invalid arguments. The first and second arguments must have the same length.","1J":"`x` or `x - y` cannot be zero for all elements.","1K":"invalid arguments. Strided array parameters are incompatible with the provided array-like object. Linear index exceeds array bounds.","1L":"invalid arguments. Unable to resolve a strided array function supporting the provided array argument data types.","1M":"invalid arguments. Interface must accept at least one strided input and/or output array. Based on the provided arguments, `nin+nout` equals `0`.","1N":"invalid argument. Unexpected number of types. A type must be specified for each strided input and output array for each provided strided array function.","1O":"invalid argument. Fourth argument is incompatible with the number of strided input and output arrays.","1P":"invalid argument. Input array offset must be a nonnegative integer.","1Q":"invalid argument. Output array offset must be a nonnegative integer.","1R":"invalid argument. Input array must be an array-like object.","1S":"invalid argument. Output array must be an array-like object.","1T":"invalid argument. Input array has insufficient elements based on the associated stride and the number of indexed elements.","1U":"invalid argument. Output array has insufficient elements based on the associated stride and the number of indexed elements.","1V":"insufficient arguments. Must provide either an array of code points or one or more code points as separate arguments.","1W":"invalid argument. Third argument must not be an empty string.","1X":"invalid argument. Pad string must not be an empty string.","1Y":"insufficient arguments. Must provide multiple functions to compose.","1Z":"insufficient arguments. Must provide multiple functions to execute sequentially.","1a":"invalid arguments. First and last arguments must be the same length.","1b":"insufficient arguments. Must provide at least two objects.","1c":"invalid invocation. `this` is not a compact adjacency matrix.","1d":"invalid argument. Cannot specify one or more accessors and a value or writable attribute in the property descriptor.","1e":"invalid argument. The list does not contain the provided list node.","1f":"unexpected error. Unable to resolve global object.","1g":"invalid argument. The output ndarray must be writable. Cannot write to a read-only ndarray.","1h":"invalid arguments. Input and output arrays must have the same length.","1i":"invalid arguments. Input and output arrays must have the same number of elements (i.e., length).","1j":"invalid arguments. Input ndarrays must be broadcast compatible.","1k":"invalid arguments. Input arrays must have the same number of elements (i.e., length).","1l":"insufficient arguments. Must provide both a target object and one or more source objects.","1m":"invalid invocation. `this` is not host tuple.","1n":"invalid invocation. `this` is not the host tuple factory.","1o":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented.","1p":"invalid argument. Second argument must have a length equal to the size of the outermost input array dimension.","1q":"evaluation error. Did not receive timing results.","1r":"evaluation error. Unable to retrieve evaluation results. Ensure that the provided snippet does not return prematurely.","1s":"invalid argument. Must provide a zipped array.","1t":"invalid argument. Array must only contain arrays.","1u":"invalid argument. Indices must be specified as an array.","1v":"invalid argument. All indices must be integers.","1w":"invalid argument. Must provide valid indices (i.e., an index must be on the interval [0, len], where len is the tuple length).","1x":"insufficient arguments. Must provide at least one array.","1y":"invalid argument. Must provide a username or, to get who an authenticated user is following, an access token.","1z":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user has starred, an access token.","2A":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","2B":"invalid argument. First argument must be an ArrayBuffer. Value: `%s`.","2C":"invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.","2D":"invalid argument. Byte offset must be a multiple of `%u`. Value: `%u`.","2E":"invalid arguments. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","2F":"invalid argument. Length must be a nonnegative integer. Value: `%s`.","2G":"invalid arguments. ArrayBuffer has insufficient capacity. Either decrease the array length or provide a bigger buffer. Minimum capacity: `%u`.","2H":"invalid argument. Second argument must be a function. Value: `%s`.","2I":"invalid argument. First argument must have a length which is a multiple of two. Length: `%u`.","2J":"invalid argument. First argument must be an array-like object or an iterable. Value: `%s`.","2K":"invalid argument. Must provide a nonnegative integer. Value: `%s`.","2L":"invalid argument. Index argument must be a nonnegative integer. Value: `%s`.","2M":"invalid argument. Index argument is out-of-bounds. Value: `%u`.","2N":"invalid argument. First argument must be either a complex number, an array-like object, or a complex number array. Value: `%s`.","2O":"invalid argument. First argument must be an array-like object. Value: `%s`.","2P":"invalid argument. Second argument must be a recognized array data type. Value: `%s`.","2Q":"invalid argument. Second argument must have a recognized/supported data type. Type: `%s`. Value: `%s`.","2R":"invalid argument. Unable to parse %s date.","2S":"invalid argument. Numeric %s date must be either a Unix or JavaScript timestamp.","2T":"invalid argument. %s date must either be a date string, Date object, Unix timestamp, or JavaScript timestamp.","2U":"invalid argument. Length must be a positive integer. Value: `%s`.","2V":"invalid argument. Options argument must be an object. Value: `%s`.","2W":"invalid option. `%s` option must be a string. Option: `%s`.","2X":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","2Y":"invalid argument. Must provide a recognized data type. Value: `%s`.","2Z":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, typed array, or array-like object. Value: `%s`.","2a":"invalid argument. Must provide a length, typed array, array-like object, or an iterable. Value: `%s`.","2b":"invalid argument. Callback argument must be a function. Value: `%s`.","2c":"invalid argument. Iterator argument must be an iterator protocol-compliant object. Value: `%s`.","2d":"invalid argument. First argument must be a nonnegative integer. Value: `%s`.","2e":"invalid argument. Third argument must be a recognized data type. Value: `%s`.","2f":"invalid argument. First argument must be either an array, typed array, or complex typed array. Value: `%s`.","2g":"invalid argument. Start must be numeric. Value: `%s`.","2h":"invalid argument. Stop must be numeric. Value: `%s`.","2i":"invalid argument. Increment must be numeric. Value: `%s`.","2j":"invalid argument. First argument must be either a real or complex number. Value: `%s`.","2k":"invalid argument. Second argument must be either a real or complex number. Value: `%s`.","2l":"invalid argument. Third argument must be an array-like object. Value: `%s`.","2m":"invalid argument. Third argument must be a nonnegative integer. Value: `%s`.","2n":"invalid option. `%s` option must be a real or complex floating-point data type or \"generic\". Option: `%s`.","2o":"invalid option. `%s` option must be a boolean. Option: `%s`.","2p":"invalid argument. Exponent of start value must be numeric. Value: `%s`.","2q":"invalid argument. Exponent of stop value must be numeric. Value: `%s`.","2r":"invalid argument. First argument must be either an array length or an array-like object. Value: `%s`.","2s":"invalid argument. Must provide a typed array or ArrayBuffer. Value: `%s`.","2t":"invalid option. `%s` option must be a nonnegative integer. Option: `%s`.","2u":"invalid argument. Must provide an array-like object. Value: `%s`.","2v":"invalid option. `%s` option must be either `1` or `-1`. Option: `%s`.","2w":"invalid argument. Second argument must be either a function or an options object. Value: `%s`.","2x":"invalid argument. Must provide a typed array. Value: `%s`.","2y":"invalid argument. Second argument must be an array-like object. Value: `%s`.","2z":"invalid argument. Third argument must be an integer. Value: `%s`.","3A":"invalid argument. Key path must be a string or a key array. Value: `%s`.","3B":"invalid argument. Must provide a string. Value: `%s`.","3C":"invalid argument. Must provide a valid position (i.e., a nonnegative integer). Value: `%s`.","3D":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%u`.","3E":"invalid argument. Second argument must be callable. Value: `%s`.","3F":"invalid argument. First argument must be a string. Value: `%s`.","3G":"invalid argument. Fourth argument must be one of the following: \"%s\". Value: `%s`.","3H":"invalid argument. Fifth argument must be one of the following: \"%s\". Value: `%s`.","3I":"invalid argument. Second argument must be either an object (except null) or a function. Value: `%s`.","3J":"invalid argument. Must provide a function. Value: `%s`.","3K":"invalid argument. Must provide either an options object or a callback function. Value: `%s`.","3L":"invalid argument. First argument must be an object. Value: `%s`.","3M":"invalid option. `%s` option must be a writable stream. Option: `%s`.","3N":"invalid argument. Third argument must be a function. Value: `%s`.","3O":"invalid option. `%s` option must be either a positive integer or `null`. Option: `%s`.","3P":"invalid option. `%s` option must be a positive integer. Option: `%s`.","3Q":"invalid argument. First argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3R":"invalid argument. Second argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3S":"invalid argument. Arrays must be the same length. First argument length: `%u`. Second argument length: `%u`.","3T":"invalid argument. First argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3U":"invalid argument. Second argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3V":"invalid argument. First argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3W":"invalid argument. Second argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3X":"invalid argument. Second argument must be a nonnegative integer. Value: `%s`.","3Y":"invalid argument. Second argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3Z":"invalid argument. Last argument must be a nonnegative integer. Value: `%s`.","3a":"invalid argument. Last argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3b":"invalid argument. Must provide a Buffer. Value: `%s`.","3c":"invalid argument. First argument must be a function. Value: `%s`.","3d":"invalid argument. Third argument must be a constructor function. Value: `%s`.","3e":"invalid argument. Real component must be a number. Value: `%s`.","3f":"invalid argument. Imaginary component must be a number. Value: `%s`.","3g":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","3h":"invalid argument. Unsupported/unrecognized dataset name. Value: `%s`.","3i":"invalid option. Unrecognized `%s`. Option: `[%s]`.","3j":"invalid option. `%s` option must be a string or an array of strings. Option: `%s`.","3k":"invalid option. `%s` option must be a positive integer or an array of positive integers. Option: `%s`.","3l":"invalid option. `%s` option must be a positive integer array of length two. Option: `%s`.","3m":"invalid option. `%s` option cannot be less than 1790. Option: `%s`.","3n":"invalid option. `%s` option cannot be greater than 5000. Option: `%s`.","3o":"invalid argument. Must provide an error object. Value: `%s`.","3p":"invalid argument. First argument must be a valid file descriptor (i.e., nonnegative integer). Value: `%s`.","3q":"invalid argument. Last argument must be a function. Value: `%s`.","3r":"invalid argument. Must provide a valid file descriptor (i.e., a nonnegative integer). Value: `%s`.","3s":"invalid argument. First argument must be an array of strings. Value: `%s`.","3t":"invalid argument. Options argument must be either a string or an object. Value: `%s`.","3u":"invalid argument. Predicate function must be a function. Value: `%s`.","3v":"invalid argument. First argument must be an iterator. Value: `%s`.","3w":"invalid argument. Must provide an iterator. Value: `%s`.","3x":"invalid argument. Must provide an iterator protocol-compliant object. Argument: `%u`. Value: `%s`.","3y":"invalid argument. Must provide an iterator protocol-compliant object. Value: `%s`.","3z":"invalid argument. Unable to parse date string. Value: `%s`.","4A":"invalid argument. Second argument must be a number. Value: `%s`.","4B":"invalid argument. Third argument must be a number. Value: `%s`.","4C":"invalid argument. Hash function argument must be a function. Value: `%s`.","4D":"invalid option. `%s` option must be a positive number. Option: `%s`.","4E":"invalid argument. Third argument must be either a nonnegative integer or an object. Value: `%s`.","4F":"invalid arguments. All arguments must be functions. Value: `%s`.","4G":"invalid argument. Each iterator function, except the last iterator function, within an iterator pipeline must return an iterator. Value: `%s`.","4H":"invalid argument. Must provide an an iterator. Value: `%s`.","4I":"invalid return value. Callback function must return an integer. Value: `%s`.","4J":"invalid argument. Fourth argument must be a boolean. Value: `%s`.","4K":"invalid return value. Callback function must return a positive integer. Value: `%s`.","4L":"invalid argument. Fifth argument must be a callback function. Value: `%s`.","4M":"invalid argument. Third argument must be either an integer (starting index) or a callback function. Value: `%s`.","4N":"invalid argument. Fourth argument must be either an integer (ending index) or a callback function. Value: `%s`.","4O":"invalid argument. Unrecognized/unsupported scale function. Value: `%s`.","4P":"invalid argument. Must provide an iterator protocol-compliant object or a number. Argument: `%u`. Value: `%s`.","4Q":"invalid argument. First argument must be a finite number. Value: `%s`.","4R":"invalid option. `%s` option must be a positive finite number. Option: `%s`.","4S":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","4T":"invalid option. `%s` option must be less than or equal to 79. Option: `%u`.","4U":"invalid option. `%s` option must be less than or equal to 77. Option: `%u`.","4V":"invalid argument. Must provide an argument having a supported data type. Value: `%s`.","4W":"invalid option. Unsupported policy for determining an output array data type. Option: `%s`.","4X":"invalid option. `%s` option must be a recognized/supported data type. Option: `%s`.","4Y":"invalid option. `%s` option must be a recognized/supported output array data type policy. Option: `%s`.","4Z":"invalid argument. Resolution table must be an object. Value: `%s`.","4a":"invalid argument. Resolution table `%s` field value must be either a function or null. Value: `%s`.","4b":"invalid argument. First argument must be a positive integer. Value: `%s`.","4c":"invalid argument. First argument must be a one-dimensional ndarray. Value: `%s`.","4d":"invalid argument. Second argument must be either +1 or -1. Value: `%s`.","4e":"invalid argument. First argument must be a one-dimensional ndarray of length %u. Actual length: `%u`.","4f":"invalid argument. First argument must be an ndarray. Value: `%s`.","4g":"invalid argument. First argument must be an ndarray whose last dimension is of size `%u`. Actual size: `%u`.","4h":"invalid argument. Second argument is incompatible with model loss function. Probability predictions are only supported when the loss function is one of the following: \"%s\". Model loss function: `%s`.","4i":"invalid argument. Second argument must be a string value equal to either \"label\", \"probability\", or \"linear\". Value: `%s`.","4j":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of `eta*lambda`. Value: `%f`.","4k":"invalid option. `%s` option must be a nonnegative number. Option: `%s`.","4l":"invalid option. `%s` option must be an array-like object. Option: `%s`.","4m":"invalid option. First `%s` option must be one of the following: \"%s\". Option: `%s`.","4n":"invalid option. Second `%s` option must be a positive number. Option: `%s`.","4o":"invalid option. Third `%s` option must be a number. Option: `%s`.","4p":"invalid argument. Argument specifying number of dimensions must be a positive integer. Value: `%s`.","4q":"invalid argument. First argument must either be a positive integer specifying the number of clusters or a matrix containing initial centroids. Value: `%s`.","4r":"invalid option. First `%s` parameter option must be greater than or equal to the number of clusters. Options: `%f`.","4s":"invalid argument. Must provide a 1-dimensional ndarray. Value: `%s`.","4t":"invalid argument. Vector length must match centroid dimensions. Expected: `%u``. Actual: `%u``.","4u":"invalid argument. Output argument must be a 1-dimensional ndarray. Value: `%s`.","4v":"invalid argument. Must provide a 2-dimensional ndarray. Value: `%s`.","4w":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u``. Actual: `%u`.","4x":"invalid argument. Output vector length must match the number of data points. Expected: `%u`. Actual: `%u`.","4y":"invalid option. `%s` option method must be one of the following: \"%s\". Option: `%s`.","4z":"invalid option. First `%s` parameter option must be a positive integer. Option: `%s`.","5A":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","5B":"invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.","5C":"invalid option. `%s` option must be a recognized order. Option: `%s`.","5D":"invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.","5E":"invalid argument. Linear index must not exceed array dimensions. Number of array elements: `%u`. Value: `%d`.","5F":"invalid argument. Input array cannot be broadcast to the specified shape, as the specified shape has a dimension whose size is less than the size of the corresponding dimension in the input array. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5G":"invalid argument. Input array and the specified shape are broadcast incompatible. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5H":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.","5I":"invalid argument. Index must be on the interval: [0, %f]. Value: `%f`.","5J":"invalid argument. Subscripts must not exceed array dimensions. Subscript: `%u`. Value: `%d`.","5K":"invalid argument. First argument must be a recognized data type. Value: `%s`.","5L":"invalid argument. First argument must have a recognized data type. Value: `%s`.","5M":"invalid arguments. Number of indices must match the number of dimensions. ndims: `%u`. nargs: `%u`.","5N":"invalid argument. Indices must be integer valued. Argument: `%u`. Value: `%s`.","5O":"invalid argument. Index must be an integer. Value: `%s`.","5P":"invalid argument. First argument must be a supported ndarray data type. Value: `%s`.","5Q":"invalid argument. Second argument must be an array-like object, typed-array-like, or a Buffer. Value: `%s`.","5R":"invalid argument. Second argument `get` and `set` properties must be functions. Value: `%s`.","5S":"invalid argument. Third argument must be an array-like object containing nonnegative integers. Value: `%s`.","5T":"invalid argument. Number of dimensions must not exceed %u due to stack limits. Value: `%u`.","5U":"invalid argument. Fourth argument must be an array-like object containing integers. Value: `%s`.","5V":"invalid argument. Fourth argument length must match the number of dimensions. Expected number of dimensions: `%u`. Strides length: `%u`.","5W":"invalid argument. Fourth argument must contain a single element equal to `0`. Value: `%d`.","5X":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.","5Y":"invalid argument. Sixth argument must be a supported order. Value: `%s`.","5Z":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%u`.","5a":"invalid option. `%s` option must be a recognized mode. Option: `%s`.","5b":"invalid option. `%s` option must be an array containing recognized modes. Option: `%s`.","5c":"invalid option. Each submode must be a recognized mode. Option: `%s`.","5d":"invalid argument. First argument must be either a function or an array of functions. Value: `%s`.","5e":"invalid argument. Third argument must be an array-like object or null. Value: `%s`.","5f":"invalid argument. Fourth argument must be a positive integer. Value: `%s`.","5g":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%s`.","5h":"invalid argument. Input array must be an ndarray-like object. Value: `%s`.","5i":"invalid argument. Output array must be an ndarray-like object. Value: `%s`.","5j":"invalid argument. Output argument must be either an array, typed array, or object. Value: `%s`.","5k":"invalid argument. Shape argument must be an array-like object containing nonnegative integers. Value: `%s`.","5l":"invalid argument. Linear index must be integer valued. Value: `%s`.","5m":"invalid option. `%s` option must be a supported/recognized mode. Option: `%s`.","5n":"invalid option. `%s` option must be a supported/recognized order. Option: `%s`.","5o":"invalid argument. First argument must be an array-like object containing nonnegative integers. Value: `%s`.","5p":"invalid argument. Number of provided subscripts must match the number of dimensions. ndims: `%u`. Number of subscripts: `%u`.","5q":"invalid argument. Subscripts must be integer valued. Argument: `%u`. Value: `%s`.","5r":"invalid option. `%s` option cannot be an empty array.","5s":"invalid argument. First argument must be either a nonnegative integer or an array of nonnegative integers. Value: `%s`.","5t":"invalid argument. First argument must be an ndarray-like object. Value: `%s`.","5u":"invalid option. `%s` option must either be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","5v":"invalid option. `%s` option must be either a Buffer or a string. Option: `%s`.","5w":"invalid argument. Request listener must be a function. Value: `%s`.","5x":"invalid argument. Third argument must be a positive integer. Value: `%s`.","5y":"invalid argument. Number of topics must be a positive integer. Value: `%s`.","5z":"invalid argument. First argument must be a nonnegative integer which is less than the total number of topics. Value: `%s`.","6A":"invalid assignment. `%s` must be a nonnegative integer or nonnegative integer array. Value: `%s`.","6B":"invalid assignment. `%s` must be a nonnegative integer. Value: `%s`.","6C":"invalid assignment. Unrecognized/unsupported `%s`. Must be one of the following: \"%s\". Value: `%s`.","6D":"invalid assignment. Unrecognized/unsupported `%s`. Value: `%s`.","6E":"invalid assignment. `%s` must be a nonnegative integer or null. Value: `%s`.","6F":"invalid assignment. `%s` must be a string or null. Value: `%s`.","6G":"invalid argument. Must provide a supported viewer. Value: `%s`.","6H":"invalid assignment. `%s` must be a function. Value: `%s`.","6I":"invalid assignment. `%s` must be either null or an array. Value: `%s`.","6J":"invalid assignment. `%s` must be a string, function, or null. Value: `%s`.","6K":"invalid argument. `options` argument must be an object. Value: `%s`.","6L":"invalid assignment. `%s` must be a number. Value: `%s`.","6M":"invalid assignment. `%s` must be a number on the interval `[0,1]`. Value: `%f`.","6N":"invalid assignment. `%s` must be array-like. Value: `%s`.","6O":"invalid arguments. Must provide equal length array-like objects. x length: `%u`, y length: `%u`.","6P":"invalid assignment. `%s` must be a string or a function. Value: `%s`.","6Q":"invalid assignment. `%s` must be a number or a function. Value: `%s`.","6R":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","6S":"invalid assignment. `%s` must be a nonnegative integer or a function. Value: `%s`.","6T":"invalid assignment. `%s` must be a supported symbol. Symbols: \"%s\". Value: `%s`.","6U":"invalid argument. `options` argument must be a plain object. Value: `%s`.","6V":"invalid assignment. `%s` must be either a string or a string array. Value: `%s`.","6W":"invalid assignment. `%s` must be a string or a string array. Value: `%s`.","6X":"invalid assignment. `%s` must be a string or string array. Value: `%s`.","6Y":"invalid assignment. Unrecognized/unsupported symbol. Value: `[%s]`.","6Z":"invalid assignment. `%s` must be an array. Value: `%s`.","6a":"invalid assignment. `%s` must be either a finite number, Date, or null. Value: `%s`.","6b":"invalid assignment. `%s` must be a boolean or boolean array. Value: `%s`.","6c":"invalid assignment. `%s` must be either a string or string array. Value: `%s`.","6d":"invalid assignment. Unrecognized/unsupported orientation. A `%s` value must be one of the following: \"%s\". Value: `%s`.","6e":"invalid assignment. `%s` must be either a finite number or null. Value: `%s`.","6f":"invalid state. x and y are different lengths. x length: `%u`, y length: `%u`.","6g":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[","6h":"invalid assignment. `%s` must be a positive integer or null. Value: `%s`.","6i":"invalid assignment. `%s` size is smaller than the number of data elements. Number of elements: `%u`. Value: `%u`.","6j":"invalid assignment. `%s` must be an array-like object or an ndarray. Value: `%s`.","6k":"invalid assignment. `%s` length exceeds maximum data buffer size. Buffer size: `%u`. Length: `%u`.","6l":"invalid assignment. `%s` must be a finite number or null. Value: `%s`.","6m":"invalid assignment. `%s` must be a finite number or null. Value: `%s.","6n":"invalid assignment. Must be an array or typed array. Value: `%s`.","6o":"invalid option. `%s` option must be an array or typed array. Option: `%s`.","6p":"invalid option. `%s` option must be a function. Option: `%s`.","6q":"invalid argument. Encoding argument must be a string. Value: `%s`.","6r":"invalid argument. Must provide either a string, nonnegative integer, or an options object. Value: `%s`.","6s":"invalid argument. First argument must be either a string or nonnegative integer. Value: `%s`.","6t":"invalid argument. Unable to parse mask expression. Ensure the expression is properly formatted, only uses the class letters \"u\", \"g\", \"o\", and \"a\", only uses the operators \"+\", \"-\", and \"=\", and only uses the permission symbols \"r\", \"w\", and \"x\". Value: `%s`.","6u":"invalid option. `%s` option must be a pseudorandom number generator function. Option: `%s`.","6v":"invalid argument. First argument must be a number and not NaN. Value: `%s`.","6w":"invalid argument. Second argument must be a number and not NaN. Value: `%s`.","6x":"invalid argument. Minimum support must be less than maximum support. Value: `[%f,%f]`.","6y":"invalid argument. First argument must be a probability. Value: `%s`.","6z":"invalid option. `%s` option must be a Uint32Array. Option: `%s`.","7A":"invalid argument. First argument must be a positive number and not NaN. Value: `%s`.","7B":"invalid argument. Second argument must be a positive number and not NaN. Value: `%s`.","7C":"invalid argument. Third argument must be a number and not NaN. Value: `%s`.","7D":"invalid argument. Third argument must be less than or equal to the first argument. Value: `%u`.","7E":"invalid argument. Second argument must be less than or equal to the first argument. Value: `%u`.","7F":"invalid %s. State array has insufficient length.","7G":"invalid %s. State array has an incompatible schema version. Expected: `%s`. Actual: `%s`.","7H":"invalid %s. State array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","7I":"invalid %s. State array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7J":"invalid %s. State array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7K":"invalid option. `%s` option must be an Int32Array. Option: `%s`.","7L":"invalid option. `%s` option must be a positive integer less than the maximum signed 32-bit integer. Option: `%u`.","7M":"invalid option. `%s` option must be either a positive integer less than the maximum signed 32-bit integer or an array-like object containing integer values less than the maximum signed 32-bit integer. Option: `%s`.","7N":"invalid argument. Must provide an Int32Array. Value: `%s`.","7O":"invalid %s. State array has an incompatible table length. Expected: `%s`. Actual: `%s`.","7P":"invalid %s. `state` array has insufficient length.","7Q":"invalid %s. `state` array has an incompatible schema version. Expected: %s. Actual: %s.","7R":"invalid %s. `state` array has an incompatible number of sections. Expected: %s. Actual: %s.","7S":"invalid %s. `state` array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7T":"invalid %s. `state` array has an incompatible section length. Expected: `%u`. Actual: `%u`.","7U":"invalid %s. `state` array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7V":"invalid option. `%s` option must be a positive integer less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7W":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7X":"invalid argument. Second argument must be on the interval: (0, 1). Value: `%f`.","7Y":"invalid option. `%s` option cannot be undefined. Option: `%s`.","7Z":"invalid option. Unrecognized/unsupported PRNG. Option: `%s`.","7a":"invalid argument. First argument must be a positive number or an options object. Value: `%s`.","7b":"invalid arguments. Parameters must satisfy the following condition: %s. Value: `[%f, %f, %f]`.","7c":"invalid argument. Scale parameter must be a positive number. Value: `%s`.","7d":"invalid argument. Shape parameter must be a positive number. Value: `%s`.","7e":"invalid argument. First argument must be an integer. Value: `%s`.","7f":"invalid argument. Second argument must be an integer. Value: `%s`.","7g":"invalid argument. `n` must be less than or equal to `N`. Value: `%u`.","7h":"invalid argument. `K` must be less than or equal to `N`. Value: `%u`.","7i":"invalid argument. `%s` argument must be array-like. Value: `%s`.","7j":"invalid input option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","7k":"invalid input option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","7l":"invalid option. `%s` option must be an array of probabilities that sum to one. Option: `%s`.","7m":"invalid argument. Minimum support must be less than maximum support. Value: `[%s,%s]`.","7n":"invalid option. `%s` option must be a string or null. Option: `%s`.","7o":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%s,%s]`.","7p":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7q":"invalid argument. Mode must be one of the following: \"%s\". Value: `%s`.","7r":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7s":"invalid operation. Alias already exists in the provided context. Alias: `%s`. Value: `%s`.","7t":"invalid argument. Unrecognized workspace name. Value: `%s`.","7u":"invalid operation. Cannot read from write-only variable `%s`.","7v":"Cannot assign to read only property %s of object #","7w":"invalid option. `%s` option must be a regular expression or an array-like object. Option: `%s`.","7x":"invalid option. `%s` option must be one of `%s`. Option: `%s`.","7y":"invalid argument. Must provide either an options object or a workspace name. Value: `%s`.","7z":"invalid argument. Must provide either a string or regular expression. Value: `%s`.","8A":"invalid argument. Must provide an integer. Value: `%s`.","8B":"invalid argument. Must provide a positive integer. Value: `%s`.","8C":"invalid argument. Presentation text must be a string. Value: `%s`.","8D":"invalid argument. REPL argument must be a REPL instance. Value: `%s`.","8E":"unexpected error. Unable to reload presentation. Error: %s","8F":"unexpected error. Unable to watch presentation source file. Error: %s","8G":"invalid option. `%s` option must be either a recognized string or boolean. Option: `%s`.","8H":"invalid option. `%s` option must be either a positive integer or null. Option: `%s`.","8I":"invalid operation. Alias already exists in REPL context. Alias: `%s`. Value: `%s`.","8J":"invalid argument. Third argument must be an object. Value: `%s`.","8K":"invalid option. `%s` option must be less than or equal to the period. Option: `%u`.","8L":"invalid option. `%s` option must be greater than 2. Option: `%s`.","8M":"invalid option. `%s` option must be an integer. Option: `%s`.","8N":"invalid option. `%s` option must be an positive integer. Option: `%s`.","8O":"invalid option. `%s` option must be less than the period. Option: `%s`.","8P":"invalid option. `%s` option must be a number. Option: `%s`.","8Q":"invalid option. `%s` option must be an positive even integer. Option: `%s`.","8R":"invalid argument. First argument must be a numeric array. Value: `%s`.","8S":"invalid argument. First argument must contain at least two elements. Value: `%s`.","8T":"invalid argument. Second argument must be an array. Value: `%s`.","8U":"invalid argument. Second argument must contain at least two unique elements. Value: `%s`.","8V":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%f`.","8W":"invalid option. `%s` option must be an array containing at least two unique elements. Option: `%s`.","8X":"invalid argument. Must provide array-like arguments. Value: `%s`.","8Y":"invalid argument. Supplied arrays cannot be empty. Value: `%s`.","8Z":"invalid option. `%s` option must be an array. Option: `%s`.","8a":"invalid argument. Minimum support must be a number. Value: `%s`.","8b":"invalid argument. Maximum support must be a number. Value: `%s`.","8c":"invalid arguments. Minimum support must be less than maximum support. Value: `%f, %f`.","8d":"invalid assignment. Must be a number. Value: `%s`.","8e":"invalid assignment. Must be less than %f. Value: `%f`.","8f":"invalid assignment. Must be greater than %f. Value: `%f`.","8g":"invalid argument. Mean parameter `p` must be a probability. Value: `%s`.","8h":"invalid assignment. Must be a probability. Value: `%s`.","8i":"invalid argument. First shape parameter must be a positive number. Value: `%s`.","8j":"invalid argument. Second shape parameter must be a positive number. Value: `%s`.","8k":"invalid assignment. Must be a positive number. Value: `%s`.","8l":"invalid argument. Number of trials must be a positive integer. Value: `%s`.","8m":"invalid argument. Success probability must be a number between 0 and 1. Value: `%s`.","8n":"invalid assignment. Must be a positive integer. Value: `%s`.","8o":"invalid assignment. Must be a number on the interval: [0, 1]. Value: `%s`.","8p":"invalid argument. Location parameter must be a number. Value: `%s`.","8q":"invalid argument. Rate parameter must be a positive number. Value: `%s`.","8r":"invalid argument. Mean parameter `%s` must be a number. Value: `%s`.","8s":"invalid argument. Minimum support must be an integer. Value: `%s`.","8t":"invalid argument. Maximum support must be an integer. Value: `%s`.","8u":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `%d, %d`.","8v":"invalid assignment. Must be an integer. Value: `%s`.","8w":"invalid assignment. Must be less than or equal to %u. Value: `%d`.","8x":"invalid assignment. Must be greater than or equal to %u. Value: `%s`.","8y":"invalid argument. Shape parameter must be a positive integer. Value: `%s`.","8z":"invalid argument. Numerator degrees of freedom must be a positive number. Value: `%s`.","9A":"invalid argument. Mean parameter `lambda` must be a positive number. Value: `%s`.","9B":"invalid argument. Mode must be a number. Value: `%s`.","9C":"invalid arguments. Parameters must satisfy the following condition: %s. a: `%f`. b: `%f`. c: `%f`.","9D":"invalid assignment. Must be less than or equal to both the maximum support and the mode. Value: `%f`.","9E":"invalid assignment. Must be greater than or equal to both the minimum support and the mode. Value: `%f`.","9F":"invalid assignment. Must be greater than or equal to the minimum support and less than or equal to the maximum support. Value: `%f`.","9G":"invalid argument. An array argument must contain two elements. Value: `%s`.","9H":"invalid argument. Must provide a nonnegative integer or a two-element array. Value: `%s`.","9I":"invalid arguments. Number of successes cannot be larger than the total number of observations. x: `%u`. n: `%u`.","9J":"invalid option. `%s` option must be a probability. Option: `%f`.","9K":"invalid argument. Unsupported/unrecognized distribution name. Value: `%s`.","9L":"invalid argument. First argument must contain nonnegative integers. Index: `%u`. Value: `%s`.","9M":"invalid argument. Probability mass function (PMF) arguments must be numbers. Argument: `%u`. Value: `%s`.","9N":"invalid argument. Second argument must be either an array-like object (or one-dimensional ndarray) of probabilities summing to one, an array-like object (or one-dimensional ndarray) of expected frequencies, or a discrete probability distribution name. Value: `%s`.","9O":"invalid argument. Second argument must only contain numbers. Index: `%u`. Value: `%s`.","9P":"invalid argument. Second argument must only contain nonnegative numbers. Index: `%u`. Value: `%d`.","9Q":"invalid option. `%s` option must be a number on the interval: [0, 1]. Value: `%s`.","9R":"invalid argument. First argument must be an array of arrays or ndarray-like object with dimension two. Value: `%s`.","9S":"invalid argument. First argument must contain nonnegative integers. Value: `%s`.","9T":"invalid argument. First argument must either specify the order of the covariance matrix or be a square 2-dimensional ndarray for storing the covariance matrix. Value: `%s`.","9U":"invalid argument. Second argument must be a 1-dimensional ndarray. Value: `%s`.","9V":"invalid argument. The number of elements (means) in the second argument must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9W":"invalid argument. Vector length must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9X":"invalid argument. Must provide a number. Value: `%s`.","9Y":"invalid argument. Must provide a nonnegative number. Value: `%s`.","9Z":"invalid argument. Must provide a nonnegative number on the interval [0,1]. Value: `%f`.","9a":"invalid argument. Output argument must be an array-like object. Value: `%s`.","9b":"invalid argument. Window size must be a positive integer. Value: `%s`.","9c":"invalid argument. Window size must be greater than or equal to 3. Value: `%s`.","9d":"invalid option. `%s` option must be on the interval [0,1]. Option: `%f`.","9e":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square 2-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","9f":"invalid argument. The number of elements (means) in the second argument must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9g":"invalid argument. Vector length must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","9h":"invalid argument. Vector length must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9i":"invalid argument. First argument must either specify the order of the correlation matrix or be a square 2-dimensional ndarray for storing the correlation matrix. Value: `%s`.","9j":"invalid argument. Unsupported/unrecognized kernel. Value: `%s`.","9k":"invalid argument. Second argument must be a numeric array. Value: `%s`.","9l":"invalid option. Lower bound `%s` must be strictly less than the upper bound `%s`.","9m":"invalid option. `%s` option must be an array of positive numbers. Option: `%s`.","9n":"invalid option. `%s` option must be an array of length two. Option: `%s`.","9o":"invalid option. `%s` option must be a string denoting a known kernel function or a custom function. Option: `%s`.","9p":"invalid arguments. First argument and `%s` must be arrays having the same length.","9q":"invalid invocation. Incorrect number of arguments. Must provide at least two array-like arguments. Value: `%s`.","9r":"invalid option. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","9s":"invalid argument. First argument must be a typed array or number array. Value: `%s`.","9t":"invalid argument. Second argument must be either a CDF function or a string. Value: `%s`.","9u":"invalid argument. Distribution parameter must be a number. Value: `%s`.","9v":"invalid option. `%s` option must contain at least two unique elements. Value: `%s`.","9w":"invalid argument. Provided arrays cannot be empty. Value: `%s`.","9x":"invalid argument. First argument must be an array of probabilities. Value: `%s`.","9y":"invalid argument. When specified, `%s` arguments must contain at least a length of %u. Value: `%u`.","9z":"invalid argument. Second argument must be one of the following: %s. Value: `%s`.","A0":"invalid option. `%s` option must be a number in `[0,1]`. Option: `%s`.","A1":"invalid option. `%s` option must be a number on the interval: [-1, 1]. Option: `%s`.","A2":"invalid argument. First argument must contain at least two elements. Value: `%s`.","A3":"invalid argument. Second argument must be either a numeric array or an options object. Value: `%s`.","A4":"invalid option. `%s` option must be either `equal` or `unequal`. Option: `%s`.","A5":"invalid argument. `%s` argument must be a numeric array. Value: `%s`.","A6":"invalid option. `%s` option must be one of the following: %s. Option: `%s`.","A7":"invalid argument. Third argument must be a positive number. Value: `%s`.","A8":"invalid argument. Fourth argument must be a positive number. Value: `%s`.","A9":"invalid operation. Serialization function must return a string or Buffer. Value: `%s`.","AA":"invalid argument. In binary mode, a provided value must be a string, Buffer, or Uint8Array. Value: `%s`.","AB":"invalid option. `%s` option must be either a string or a regular expression. Option: `%s`.","AC":"invalid argument. First input array offset must be a nonnegative integer. Value: `%s`.","AD":"invalid argument. Second input array offset must be a nonnegative integer. Value: `%s`.","AE":"invalid argument. Output array offset must be a nonnegative integer. Value: `%s`.","AF":"invalid argument. Must provided recognized data types. Unable to resolve a data type string. Value: `%s`.","AG":"invalid argument. Input array offset must be a nonnegative integer. Value: `%s`.","AH":"invalid argument. Input array stride must be an integer. Value: `%s`.","AI":"invalid argument. Output array stride must be an integer. Value: `%s`.","AJ":"invalid option. `%s` option must be an array of strings. Option: `%s`.","AK":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%s`.","AL":"invalid argument. Third argument must be a boolean. Value: `%s`.","AM":"invalid argument. Must provide valid code points (i.e., nonnegative integers). Value: `%s`.","AN":"invalid argument. Must provide a valid code point (cannot exceed max). Value: `%s`.","AO":"invalid argument. Third argument must be a string. Value: `%s`.","AP":"invalid argument. Output string length exceeds maximum allowed string length. Value: `%u`.","AQ":"invalid argument. Third argument must be a string or an array of strings. Value: `%s`.","AR":"invalid argument. At least one padding option must have a length greater than 0. Left padding: `%s`. Right padding: `%s`.","AS":"invalid argument. Second argument must be an array of strings. Value: `%s`.","AT":"invalid argument. Second argument must be a string or regular expression. Value: `%s`.","AU":"invalid argument. Third argument must be a string or replacement function. Value: `%s`.","AV":"invalid argument. Must provide a string or an array of strings. Value: `%s`.","AW":"invalid argument. If only providing a single argument, must provide a Date object. Value: `%s`.","AX":"invalid argument. First argument must be either a string or integer. Value: `%s`.","AY":"invalid argument. Day number must be on the interval: `[1, %u]`. Value: `%d`.","AZ":"invalid argument. First argument must be either a string, integer, or Date object. Value: `%s`.","Aa":"invalid argument. An integer month value must be on the interval: [1, 12]. Value: `%s`.","Ab":"invalid argument. Must provide a recognized month. Value: `%s`.","Ac":"invalid argument. Must provide either an integer or a `Date` object. Value: `%s`.","Ad":"invalid argument. Must provide either a string, integer, or Date object. Value: `%s`.","Ae":"invalid argument. Must provide an array of nonnegative integers. Value: `%s`.","Af":"invalid argument. Input array must contain two elements. Value: `%s`.","Ag":"invalid argument. Must provide a collection. Value: `%s`.","Ah":"invalid argument. First argument must be a collection. Value: `%s`.","Ai":"invalid argument. First argument must be either an array, typed array, or an array-like object. Value: `%s`.","Aj":"invalid argument. All arguments must be functions. Value: `%s`.","Ak":"invalid argument. Number of function invocations must be a nonnegative integer. Value: `%s`.","Al":"invalid argument. First argument must be an array of functions. Value: `%s`.","Am":"invalid argument. Last argument must be a collection. Value: `%s`.","An":"invalid argument. Must provide either a valid buffer size (i.e., a positive integer) or an array-like object which can serve as the underlying buffer. Value: `%s`.","Ao":"invalid argument. An iterator must return an array-like object containing vertices. Value: `%s`.","Ap":"invalid argument. Callback must return an array-like object containing vertices. Value: `%s`.","Aq":"invalid argument. Callback must return an array-like object. Value: `%s`.","Ar":"invalid argument. Each element of the adjacency list must be an array-like object. Value: `%s`.","As":"invalid argument. Each element of the edge list must be an array-like object. Value: `%s`.","At":"invalid argument. Second argument must be an array-like object or an iterable. Value: `%s`.","Au":"invalid argument. First argument exceeds matrix dimensions. Value: `%u`.","Av":"invalid argument. Second argument exceeds matrix dimensions. Value: `%u`.","Aw":"invalid argument. Vertex cannot exceed matrix dimensions. Value: `%u`.","Ax":"invalid argument. Second argument must be a recognized output path convention. Value: `%s`.","Ay":"invalid argument. Cannot convert Windows extended-length paths to POSIX paths. Value: `%s`.","Az":"invalid argument. Arity argument must be a positive integer. Value: `%s`.","B0":"invalid argument. Property descriptor must be an object. Value: `%s`.","B1":"invalid argument. The `value` property of the property descriptor must be a function. Value: `%s`.","B2":"invalid argument. Second argument must be an object of property descriptors. Value: `%s`.","B3":"invalid argument. Path must be a string. Value: `%s`.","B4":"invalid argument. Third argument must be a recognized location. Value: `%s`.","B5":"invalid argument. Must provide a recognized iteration direction. Value: `%s`.","B6":"invalid argument. Must provide an object-like value. Value: `%s`.","B7":"invalid argument. Must provide a regular expression string. Value: `%s`.","B8":"invalid argument. Filename must be a string. Value: `%s`.","B9":"invalid argument. First argument must be an array of positive integers. Value: `%s`.","BA":"invalid argument. First argument must be object-like. Value: `%s`.","BB":"invalid argument. Must provide an array of arrays. Value: `%s`.","BC":"invalid argument. Must provide a boolean. Value: `%s`.","BD":"invalid argument. Second argument must have a prototype from which another object can inherit. Value: `%s`.","BE":"invalid argument. A provided constructor must be either an object (except null) or a function. Value: `%s`.","BF":"invalid argument. If the input array is an ndarray, the output array must also be an ndarray. Value: `%s`.","BG":"invalid argument. If the input array is an array-like object, the output array must also be an array-like object. Value: `%s`.","BH":"invalid argument. First argument must be an array-like object or an ndarray. Value: `%s`.","BI":"invalid argument. If the first input array is an ndarray, the second input array must also be an ndarray. Value: `%s`.","BJ":"invalid argument. If the input arrays are ndarrays, the output array must also be an ndarray. Value: `%s`.","BK":"invalid argument. If the first input array is an array-like object, the second input array must also be an array-like object. Value: `%s`.","BL":"invalid argument. If the input arrays are array-like objects, the output array must also be an array-like object. Value: `%s`.","BM":"invalid argument. First argument must be an array-like object containing array-like objects. Index: `%u`. Value: `%s`.","BN":"invalid argument. First argument must be a three-dimensional nested array. Index: `%u`. Value: `%s`.","BO":"invalid argument. First argument must be a four-dimensional nested array. Index: `%u`. Value: `%s`.","BP":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BQ":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BR":"invalid argument. First argument must be a five-dimensional nested array. Index: `%u`. Value: `%s`.","BS":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BT":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BU":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u, %u). Value: `%s`.","BV":"invalid argument. A merge source must be an object. Value: `%s`.","BW":"invalid option. `%s` option must be either a boolean or a function. Option: `%s`.","BX":"invalid argument. Source argument must be an object. Value: `%s`.","BY":"invalid argument. Target argument must be an object. Value: `%s`.","BZ":"invalid argument. Must provide an array of strings. Value: `%s`.","Ba":"invalid argument. Field names must be distinct. Value: `%s`.","Bb":"invalid argument. Provided field name is reserved. Name: `%s`.","Bc":"invalid arguments. Arguments are incompatible with the number of tuple fields. Number of fields: `%u`. Number of data elements: `%u`.","Bd":"invalid argument. Source is incompatible with the number of tuple fields. Number of fields: `%u`. Source length: `%u`.","Be":"invalid invocation. Number of arguments is incompatible with the number of tuple fields. Number of fields: `%u`. Number of arguments: `%u`.","Bf":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","Bg":"invalid argument. Second argument must be either a string or an array of strings. Value: `%s`.","Bh":"invalid argument. Must provide a valid URI. Value: `%s`.","Bi":"unexpected error. Child process failed with exit code: `%u`.","Bj":"unexpected error. Child process failed due to termination signal: `%s`.","Bk":"invalid argument. Reviver argument must be a function. Value: `%s`.","Bl":"invalid argument. Second argument must be an array-like object containing nonnegative integers. Value: `%s`.","Bm":"invalid argument. Must provide either an array, typed array, or an array-like object. Value: `%s`.","Bn":"invalid argument. Must provide a recognized type. Value: `%s`.","Bo":"invalid argument. Second argument must be an array containing only nonnegative integers. Value: `%s`.","Bp":"invalid invocation. Unexpected number of input arguments. Expected: `%u`. Actual: `%u`.","Bq":"evaluation error. Encountered an error when evaluating snippet. %s","Br":"invalid option. `%s` option must be a positive integer or null. Option: `%s`.","Bs":"insufficient arguments. Expected %u argument(s) and only received %u argument(s).","Bt":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: %u. Actual: %u.","Bu":"invalid invocation. Number of arguments exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bv":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bw":"invalid argument. Must provide array arguments. Value: `%s`.","Bx":"invalid argument. Last argument must be either an array or an options object. Value: `%s`.","By":"invalid argument. Repository slug must be a string. Value: `%s`.","Bz":"invalid argument. Issue title must be a string. Value: `%s`.","C0":"invalid option. `%s` must be one of the following: \"%s\". Option: `%s`.","C1":"invalid argument. Repository name must be a string. Value: `%s`.","C2":"invalid option. `%s` option must be a valid URI. Option: `%s`.","C3":"invalid option. `%s` option must be a 20-character string. Option: `%s`.","C4":"invalid option. `%s` option must be a 40-character string. Option: `%s`.","C5":"invalid argument. Token id must be a nonnegative integer. Value: `%s`.","C6":"invalid argument. Workflow identifier must be a string. Value: `%s`.","C7":"invalid option. `%s` option must be an object of input key-value pairs. Option: `%s`.","C8":"invalid option. `%s` option must be a positive integer or \"last\". Option: `%s`.","C9":"invalid option. `%s` organization name option must be a string. Option: `%s`.","CA":"invalid option. Unknown method. Option: `%s`.","CB":"invalid option. Unrecognized `%s` option. Must be one of the following: \"%s\". Option: `%s`.","CC":"invalid argument. Repository slug must consist of an owner and a repository (e.g., \"stdlib-js/utils\"). Value: `%s`.","CD":"invalid argument. Topics argument must be an array of strings. Value: `%s`.","CE":"invalid option. `%s` option must be one of the following: \"%s\" or \"%s\". Option: `%s`.","CF":"invalid argument. Must provide a supported license SPDX identifier. Value: `%s`.","CG":"invalid argument. Must provide a supported file type. Value: `%s`.","CH":"invalid argument. First argument must be either a string or Buffer. Value: `%s`.","CI":"invalid argument. Second argument must be either a string or Buffer. Value: `%s`.","CJ":"invalid argument. A header object must map each filename extension to a license header string. `%s: %s`. Value: `%s`.","CK":"invalid argument. Second argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CL":"invalid argument. Second argument must be either a string, Buffer, or regular expression. Value: `%s`.","CM":"invalid argument. A header object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CN":"invalid argument. Second argument must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Value: `%s`.","CO":"invalid argument. Third argument must be either a string or Buffer. Value: `%s`.","CP":"invalid argument. Third argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CQ":"invalid argument. Database already contains an entry for the provided URI: `%s`.","CR":"invalid argument. Database already contains an entry for the provided id: `%s`.","CS":"invalid argument. First argument must be a URI. Value: `%s`.","CT":"invalid argument. Second argument must be either a string or regular expression. Value: `%s`.","CU":"invalid option. A `%s` option object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CV":"invalid option. `%s` option must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Option: `%s`.","CW":"invalid option. `%s` option must end with \"package.json\". Option: `%s`.","CX":"invalid argument. Last argument must be a callback function. Value: `%s`.","CY":"invalid option. `%s` option must be an array of package names. Option: `%s`.","CZ":"invalid argument. Version argument must be a string. Value: `%s`.","Ca":"invalid argument. Must provide either a string or a Buffer. Value: `%s`.","Cb":"invalid argument. Must provide either a string or Buffer. Value: `%s`.","Cc":"invalid argument. First argument must be either a string or array of strings. Value: `%s`.","Cd":"invalid option. `%s` option must be an object. Option: `%s`.","Ce":"unexpected error. File does not exist. Unable to resolve file: %s.","Cf":"invalid argument. Must provide either a string or an array of strings. Value: `%s`.","Cg":"invalid argument. Must provide either a string or an array of strings. Value: `%s`. Index: `%u`.","Ch":"unexpected error. Failed to sort packages. Detected the following dependency chain containing a cycle: `%s`.","Ci":"invalid node. Equation comments must have a valid label. Node: `%s`.","Cj":"invalid node. Equation comments must have valid alternate text. Node: `%s`.","Ck":"invalid node. Equation comments must have valid raw equation text. Node: `%s`.","Cl":"invalid node. Invalid equation comment. Ensure that the Markdown file includes both starting and ending equation comments. Node: `%s`.","Cm":"invalid node. Equation element must have a valid label. Node: `%s`.","Cn":"unexpected error. Code block configuration settings should be provided as comma-separated `key:value` pairs (e.g., `foo:true, bar:\"string\", baz:[\"error\",2]`). Value: `%s`.","Co":"unexpected error. Code block configuration values should be parseable as JSON. Value: `%s`.","Cp":"unexpected error. Encountered an error when executing code block. File: `%s`. Message: `%s`.","Cq":"unexpected error. Expected code block to throw an exception. File: `%s`.","Cr":"invalid node. Ensure that the Markdown file includes both a starting `
` and closing `
\\n\\n`. Node: `%s`.","Cs":"invalid node. Equation comments must have valid equation text. Node: `%s`.","Ct":"invalid node. Equation comments must have valid labels. Node: `%s`.","Cu":"invalid option. `%s` option must begin with \"@stdlib/\". Option: `%s`.","Cv":"invalid argument. First argument must be a list of file paths. Value: `%s`.","Cw":"invalid arguments. Subpopulation size must be less than or equal to the population size.","Cx":"invalid arguments. Number of draws must be less than or equal to the population size.","Cy":"invalid arguments. Fourth argument is not compatible with the number of input and output ndarrays.","Cz":"invalid arguments. Input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","D0":"invalid arguments. Length of the first argument is incompatible with the second and third arguments.","D1":"invalid argument. Provided collections must have the same length.","D2":"invalid argument. First argument must be an array-like object containing nonnegative integers.","D3":"invalid arguments. Input arrays must have the same length.","D4":"invalid argument. Must provide valid indices (i.e., must be a nonnegative integer less than or equal to the tuple length).","D5":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented. https://github.com/stdlib-js/stdlib/issues/new/choose","D6":"invalid operation. Parser is unable to parse new chunks, as the parser has been closed. To parse new chunks, create a new parser instance.","D7":"invalid operation. Parser is in an unrecoverable error state. To parse new chunks, create a new parser instance.","D8":"invalid argument. First argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","D9":"invalid argument. Second argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","DA":"invalid argument. First argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DB":"invalid argument. Second argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DC":"invalid assignment. `%s` size is less than the number of data elements. Number of elements: `%u`. Value: `%u`.","DD":"invalid assignment. `%s` must be a string or an array of strings. Value: `%s`.","DE":"invalid assignment. `%s` must be a number or an array of numbers. Value: `%s`.","DF":"invalid assignment. `%s` must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","DG":"invalid assignment. `%s` must be a finite number, Date, or null. Value: `%s`.","DH":"invalid assignment. `%s` must be a boolean or an array of booleans. Value: `%s`.","DI":"invalid assignment. `%s` must be a number or null. Value: `%s`.","DJ":"invalid assignment. `%s` must be an array of strings or an empty array. Value: `%s`.","DK":"invalid state. x and y are different lengths. x length: `%u`. y length: `%u`.","DL":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[%u].length: `%u`.","DM":"invalid assignment. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","DN":"invalid assignment. `%s` must be null or an array. Value: `%s`.","DO":"invalid arguments. Must provide equal length array-like objects. x length: `%u`. y length: `%u`.","DP":"invalid argument. The number of comparisons must be greater or equal to the number of p-values to be adjusted. Value: `%u`.","DQ":"invalid argument. Second argument must be one of the following: \"%s\". Value: `%s`.","DR":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%s`.","DS":"invalid argument. First argument must contain nonnegative integers. Indices: (%s). Value: `%s`.","DT":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Number of input array dimensions: %u.","DU":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Value: `%s`.","DV":"invalid arguments. Minimum support must be less than maximum support. Value: `(%f, %f)`.","DW":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `(%d, %d)`.","DX":"invalid argument. Mean parameter must be a positive number. Value: `%s`.","DY":"invalid argument. Mean parameter must be a probability. Value: `%s`.","DZ":"invalid option. `%s` option must be on the interval: [0, 1]. Option: `%f`.","Da":"invalid argument. Must provide a nonnegative number on the interval: [0, 1]. Value: `%f`.","Db":"invalid argument. First argument must either specify the order of the covariance matrix or be a square two-dimensional ndarray for storing the covariance matrix. Value: `%s`.","Dc":"invalid argument. Second argument must be a one-dimensional ndarray. Value: `%s`.","Dd":"invalid argument. Must provide a one-dimensional ndarray. Value: `%s`.","De":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square two-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","Df":"invalid argument. First argument must either specify the order of the correlation matrix or be a square two-dimensional ndarray for storing the correlation matrix. Value: `%s`.","Dg":"invalid argument. Input array must be an array-like object. Value: `%s`.","Dh":"invalid argument. Output array must be an array-like object. Value: `%s`.","Di":"invalid argument. Mask array offset must be a nonnegative integer. Value: `%s`.","Dj":"invalid argument. Must provide recognized data types. Unable to resolve a data type string. Value: `%s`.","Dk":"invalid option. `%s` option must be one of the following: ['%s']. Option: `%s`.","Dl":"invalid argument. Database already contains an entry for the provided URI. Value: `%s`.","Dm":"invalid argument. Database already contains an entry for the provided id. Value: `%s`.","Dn":"invalid argument. First argument must be an array of objects. Value: `%s`.","Do":"unexpected error. File does not exist. Unable to resolve file: `%s`.","Dp":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`.","Dq":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`. Index: `%u`.","Dr":"invalid argument. Must provide either an options object or a function. Value: `%s`.","Ds":"invalid option. `%s` option must be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","Dt":"invalid argument. Fourth argument must contain a single element equal to 0. Value: `%d`.","Du":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%s`.","Dv":"invalid argument. Must provide an ndarray. Value: `%s`.","Dw":"invalid argument. Second argument must be a supported data type policy. Value: `%s`.","Dx":"invalid argument. Must provide either an integer or a Date object. Value: `%s`.","Dy":"invalid argument. Must provide a valid duration string. Value: `%s`.","Dz":"invalid argument. Day number must be on the interval: [1, %u]. Value: `%d`.","E0":"invalid argument. First argument must be a string or integer. Value: `%s`.","E1":"invalid option. `%s` option must be one of the following: \"%s\". Value: `%s`.","E2":"invalid argument. Third argument must be either an integer (starting index) or a function. Value: `%s`.","E3":"invalid argument. Fourth argument must be either an integer (ending index) or a function. Value: `%s`.","E4":"invalid argument. Second argument must be a valid position (i.e., be within string bounds). Value: `%d`.","E5":"invalid argument. Must provide a valid code point (i.e., cannot exceed %u). Value: `%s`.","E6":"invalid argument. First argument must be astring. Value: `%s`.","E7":"invalid argument. Second argument must be either an integer (starting index) or a function. Value: `%s`.","E8":"invalid argument. Third argument must be either an integer (ending index) or a function. Value: `%s`.","E9":"invalid argument. ArrayBuffer byte length must be a multiple of %u. Byte length: `%u`.","EA":"invalid argument. Byte offset must be a multiple of %u. Value: `%u`.","EB":"invalid argument. First argument must have a length which is a multiple of %u. Length: `%u`.","EC":"invalid argument. Second argument must be a supported data type. Value: `%s`.","ED":"invalid argument. First argument must be one of the following data types: \"%s\". Value: `%s`.","EE":"invalid argument. Second argument must be either an integer (starting view index) or a function. Value: `%s`.","EF":"invalid argument. Third argument must be either an integer (ending view index) or a function. Value: `%s`.","EG":"invalid option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","EH":"invalid option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","EI":"invalid argument. Second argument must be either a scalar or an ndarray-like object. Value: `%s`.","EJ":"invalid argument. Minimum support must be less than maximum support. Value: `[%f, %f]`.","EK":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d, %d]`.","EL":"invalid %s. `state` array has an incompatible schema version. Expected: `%s`. Actual: `%s.`","EM":"invalid %s. `state` array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","EN":"invalid argument. Number of draws must be less than or equal to the population size. Value: `%u`.","EO":"invalid argument. Subpopulation size must be less than or equal to the population size. Value: `%u`.","EP":"invalid argument. Must provide a regular expression. Value: `%s`.","EQ":"invalid argument. Second argument must be an object containing property descriptors. Value: `%s`.","ER":"invalid argument. Must provide an object (except null). Value: `%s`.","ES":"invalid argument. First argument must be an object (except null). Value: `%s`.","ET":"unexpected error. Encountered an invalid record. Field %d on line %d contains a closing quote which is not immediately followed by a delimiter or newline.","EU":"unexpected error. Encountered an invalid record. Field %d on line %d contains an opening quote which does not immediately follow a delimiter or newline.","EV":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence which is not immediately followed by a special character sequence.","EW":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence within a quoted field which is not immediately followed by a quote sequence.","EX":"invalid argument. First argument must be a function having at least one parameter. Value: `%s`.","EY":"invalid argument. All arguments must be objects. Index: `%u`. Value: `%s`.","EZ":"invalid argument. First argument must be a non-null object. Value: `%s`.","Ea":"invalid argument. First argument must be an ndarray whose last dimension is of size %u. Actual size: `%u`.","Eb":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of eta * lambda. Value: `%f`.","Ec":"invalid argument. Output argument must be a one-dimensional ndarray. Value: `%s`.","Ed":"invalid argument. Must provide a two-dimensional ndarray. Value: `%s`.","Ee":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u`. Actual: `%u`.","Ef":"invalid argument. First argument must be an integer, null, or undefined. Value: `%s`.","Eg":"invalid argument. Second argument must be an integer, null, or undefined. Value: `%s`.","Eh":"invalid argument. Third argument must be an integer, null, or undefined. Value: `%s`.","Ei":"invalid argument. Third argument cannot be zero. Value: `%s`.","Ej":"invalid argument. First argument must be a valid subsequence string. Value: `%s`.","Ek":"invalid argument. A subsequence string must have a non-zero increment. Value: `%s`.","El":"invalid argument. The subsequence string resolves to a slice which exceeds index bounds. Value: `%s`.","Em":"invalid argument. Provided arguments must be either a Slice, integer, null, or undefined. Argument: `%d`. Value: `%s`.","En":"invalid operation. Unsupported slice operation. Value: `%s`.","Eo":"invalid operation. Number of array dimensions does not match the number of slice dimensions. Array shape: (%s). Slice dimensions: %u.","Ep":"invalid operation. Slice exceeds array bounds. Array shape: (%s).","Eq":"invalid operation. A subsequence increment must be a non-zero integer. Value: `%s`.","Er":"invalid operation. A subsequence may only include a single ellipsis. Value: `%s`.","Es":"invalid argument. Cannot write to a read-only array.","Et":"invalid argument. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Eu":"invalid argument. Slice arguments must be either a Slice, integer, null, or undefined. Value: `%s`.","Ev":"invalid operation. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Ew":"invalid operation. Assigned value cannot be safely cast to the target array data type. Data types: [%s, %s].","Ex":"invalid operation. Unsupported target array data type. Data type: `%s`.","Ey":"invalid argument. Index must be on the interval: [0, %d]. Value: `%d`.","Ez":"invalid argument. Slice exceeds array bounds. Array shape: (%s).","F0":"invalid argument. Input array values cannot be safely cast to the output array data type. Data types: [%s, %s].","F1":"invalid argument. Second argument must be an ndarray. Value: `%s`.","F2":"invalid argument. First argument must be an ndarray having at least two dimensions.","F3":"invalid argument. Second argument must be an array of nonnegative integers. Value: `%s`.","F4":"invalid option. Cannot write to read-only array.","F5":"invalid argument. First argument must be an array of nonnegative integers. Value: `%s`.","F6":"invalid argument. Must provide an ndarray having a supported data type. Value: `%s`.","F7":"invalid argument. First argument must be an ndarray having one or more dimensions. Number of dimensions: %d.","F8":"invalid argument. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","F9":"invalid argument. Third argument must be either a Slice, integer, null, or undefined. Value: `%s`.","FA":"invalid argument. First argument must be an ndarray having at least three dimensions.","FB":"invalid argument. Index must resolve to a value on the interval: [0, %d]. Value: `%d`.","FC":"invalid argument. First argument must be a recognized index mode. Value: `%s`.","FD":"invalid argument. Third argument exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","FE":"invalid argument. Number of indices does not match the number of array dimensions. Array shape: (%s). Number of indices: %u.","FF":"invalid argument. Each index argument must be either an integer, null, or undefined. Value: `%s`.","FG":"invalid argument. First argument must be a complex number. Value: `%s`.","FH":"invalid arguments. Input arrays must be broadcast compatible.","FI":"invalid argument. The first and second arguments must have the same length.","FJ":"invalid argument. First argument must be either an ndarray or an array of ndarrays. Value: `%s`.","FK":"invalid argument. An ndarray argument must be an ndarray. Value: `%s`.","FL":"invalid argument. Second argument must be a valid property name. Value: `%s`.","FM":"invalid argument. First argument must have a `%s` method.","FN":"invalid argument. Second argument must an array of strings. Value: `%s`.","FO":"invalid argument. Third argument must be a supported data type. Value: `%s`.","FP":"invalid argument. Index argument is out-of-bounds. Value: `%s`.","FQ":"invalid argument. Second argument must be a complex number. Value: `%s`.","FR":"invalid argument. Index arguments must be integers. Value: `%s`.","FS":"invalid argument. Slice exceeds array bounds. Array length: %d.","FT":"invalid argument. Input array and the output array slice are broadcast incompatible. Array length: %u. Desired length: %u.","FU":"invalid operation. Slice exceeds array bounds.","FV":"invalid argument. First argument must be a valid index array.","FW":"invalid operation. This array index instance has already been freed and can no longer be used.","FX":"invalid argument. First argument must be a complex-valued floating-point array. Value: `%s`.","FY":"invalid operation. Index exceeds array bounds.","FZ":"invalid operation. Unrecognized array index type. Value: `%s`.","Fa":"invalid operation. Unable to resolve array index. Value: `%s`.","Fb":"invalid option. `%s` option is missing a `%s` method. Option: `%s`.","Fc":"invalid operation. If not provided an initial value, an array must contain at least one element.","Fd":"invalid arguments. Must provide equal length array-like objects.","Fe":"Index out of bounds","Ff":"invalid option. `%s` option must be less than or equal to 64. Option: `%u`.","Fg":"invalid argument. Unable to parse input string as a complex number. Value: `%s`.","Fh":"invalid operation. Cannot access settings for a REPL which has already closed.","Fi":"invalid argument. First argument must be a recognized setting. Value: `%s`.","Fj":"invalid invocation. `this` is not a boolean array.","Fk":"invalid argument. Unable to parse commits for package: `%s`.","Fl":"invalid argument. Unrecognized release type: `%s`.","Fm":"invalid argument. First argument must be a supported BLAS memory layout. Value: `%s`.","Fn":"invalid argument. First argument must be an existing theme name. Value: `%s`.","Fo":"invalid argument. First argument must not be the default theme name. Value: `%s`.","Fp":"invalid argument. Second argument must be an object. Value: `%s`.","Fq":"invalid arguments. Number of values does not equal the number of falsy values in the mask array.","Fr":"invalid arguments. Insufficient values to satisfy mask array.","Fs":"invalid arguments. Input arguments are not broadcast compatible.","Ft":"invalid arguments. Number of values does not equal the number of truthy values in the mask array.","Fu":"invalid argument. Third argument cannot be safely cast to the input array data type. Data types: [%s, %s].","Fv":"invalid argument. First argument must be a boolean. Value: `%s`.","Fw":"invalid argument. The third argument must be broadcast compatible with the second argument. Array shape: (%d). Desired shape: (%d).","Fx":"invalid argument. First argument must be a valid order. Value: `%s`.","Fy":"invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","Fz":"invalid argument. Third argument must be a nonnegative integer. Value: `%d`.","G0":"invalid argument. Eighth argument must be non-zero. Value: `%d`.","G1":"invalid argument. Twelfth argument must be non-zero. Value: `%d`.","G2":"invalid argument. Seventh argument must be non-zero. Value: `%d`.","G3":"invalid argument. Tenth argument must be non-zero. Value: `%d`.","G4":"invalid argument. Fourth argument must be greater than or equal to max(1,%d). Value: `%d`.","G5":"invalid argument. First argument must be a string or an array of strings. Value: `%s`.","G6":"invalid option. `%s` option must be a valid mode. Option: `%s`.","G7":"invalid argument. First argument must be a nonnegative integer. Value: `%d`.","G8":"invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.","G9":"invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.","GA":"invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GB":"invalid argument. Sixth argument must be non-zero. Value: `%d`.","GC":"invalid argument. Tenth argument must be greater than or equal to max(1,%d). Value: `%d`.","GD":"invalid argument. First argument must specify whether the reference the lower or upper triangular matrix. Value: `%s`.","GE":"invalid argument. Second argument must be a nonnegative integer. Value: `%d`.","GF":"invalid argument. Fifth argument must be non-zero. Value: `%d`.","GG":"invalid argument. Second argument must be a valid transpose operation. Value: `%s`.","GH":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.","GI":"invalid argument. Ninth argument must be non-zero.","GJ":"invalid argument. Twelfth argument must be non-zero.","GK":"invalid argument. Eleventh argument must be non-zero.","GL":"invalid argument. Fifteenth argument must be non-zero.","GM":"invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.","GN":"invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GO":"invalid argument. Third argument must be a valid transpose operation. Value: `%s`.","GP":"invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.","GQ":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%d`.","GR":"invalid argument. Seventh argument must be greater than or equal to max(1,%d). Value: `%d`.","GS":"invalid argument. Ninth argument must be non-zero. Value: `%d`.","GT":"invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","GU":"invalid argument. Third argument must be a valid diagonal type. Value: `%s`.","GV":"invalid argument. First argument must be a valid transpose operation. Value: `%s`.","GW":"invalid argument. Tenth argument must be non-zero.","GX":"invalid argument. Fourteenth argument must be non-zero.","GY":"invalid arguments. Array must have the same shape.","GZ":"invalid argument. Second argument must be an array of integers. Value: `%s`.","Ga":"invalid argument. First argument must be an ndarray having at least %d dimensions.","Gb":"invalid argument. Dimension indices must be sorted in ascending order. Value: `%s`.","Gc":"invalid argument. Dimension indices must be unique. Value: `%s`.","Gd":"invalid argument. First argument must be an array of ndarrays. Value: `%s`.","Ge":"invalid argument. First argument must be an array of ndarrays which are broadcast-compatible. Value: `%s`.","Gf":"invalid argument. First argument must be an array of ndarrays having at least %d dimensions after broadcasting.","Gg":"invalid argument. Index argument is out-of-bounds. Value: `%d`.","Gh":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%d`.","Gi":"invalid argument. Ninth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gj":"invalid argument. Eleventh argument must be greater than or equal to max(1,%d). Value: `%d`.","Gk":"invalid argument. Fourteenth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gl":"invalid argument. First argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gm":"invalid argument. Second argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gn":"invalid argument. First argument must have at least one dimension.","Go":"invalid argument. Second argument must have at least one dimension.","Gp":"invalid argument. Third argument must be a negative integer. Value: `%s`.","Gq":"invalid argument. Third argument must be a value on the interval: [%d,%d]. Value: `%d`.","Gr":"invalid argument. The size of the contracted dimension must be the same for both input ndarrays. Dim(%s,%d) = %d. Dim(%s,%d) = %d.","Gs":"invalid arguments. Input ndarrays must be broadcast compatible. Shape(%s) = (%s). Shape(%s) = (%s).","Gt":"invalid argument. Cannot write to read-only array.","Gu":"invalid arguments. The first and second arguments must have the same shape.","Gv":"unexpected error. Environment does not support WebAssembly.","Gw":"invalid invocation. Unable to perform write operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gx":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Resize the underlying memory instance in order to accommodate the list of provided values.","Gy":"invalid invocation. Unable to perform read operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gz":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Not enough values to fill the provided output array.","H0":"invalid argument. Must provide a WebAssembly memory instance. Value: `%s`.","H1":"invalid argument. First argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H2":"invalid argument. Second argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H3":"invalid invocation. `this` is not a Float64ArrayFE.","H4":"invalid argument. First argument must be a supported byte order. Value: `%s`.","H5":"invalid argument. Second argument must a data type. Value: `%s`.","H6":"invalid argument. First argument must be an ndarray-like object having a supported data type. Value: `%s`.","H7":"invalid argument. Second argument must be an ndarray-like object having a supported data type. Value: `%s`.","H8":"invalid invocation. `this` is not %s %s.","H9":"invalid argument. First argument must be a supported data type. Value: `%s`.","HA":"invalid argument. Must provide an ArrayBuffer. Value: `%s`.","HB":"invalid argument. Second argument must be a data type. Value: `%s`.","HC":"invalid option. Each key object must have a `name` property. Value: `%s`.","HD":"invalid option. Each key object's `name` property must be a string. Value: `%s`.","HE":"invalid option. Each key object's `%s` property must be a boolean. Value: `%s`.","HF":"invalid option. Each action must be an array of objects. Value: `%s`.","HG":"invalid argument. First argument must be a valid index ndarray.","HH":"invalid operation. This ndarray index instance has already been freed and can no longer be used.","HI":"invalid operation. Unrecognized ndarray index type. Value: `%s`.","HJ":"invalid operation. Index exceeds ndarray bounds.","HK":"invalid operation. Number of indices does not match the number of array dimensions. Array shape: (%s). Index dimensions: %u.","HL":"invalid operation. Unable to resolve ndarray index. Value: `%s`.","HM":"invalid argument. First argument is not compatible with the specified index \"kind\". Type: %s. Kind: %s.","HN":"invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.","HO":"invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.","HP":"invalid argument. Must provide unique dimension indices. Value: `[%s]`.","HQ":"invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.","HR":"invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.","HS":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","HT":"invalid argument. Each key in the keybindings argument must correspond to a single action. Value: `%s`","HU":"invalid argument. First argument must be a valid action name. Value: `%s`.","HV":"invalid argument. Each key in the keys argument must correspond to a single action. Value: `%s`","HW":"invalid argument. Second argument must be an array of data types. Value: `%s`.","HX":"invalid argument. Third argument must be an array of data types. Value: `%s`.","HY":"invalid argument. Fourth argument must be a supported output data type policy. Value: `%s`.","HZ":"invalid argument. First argument must have one of the following data types: \"%s\". Data type: `%s`.","Ha":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d.","Hb":"invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].","Hc":"invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].","Hd":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].","He":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.","Hf":"invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).","Hg":"invalid argument. The second argument cannot be safely cast to the input array data type. Data type: %s. Value: `%s`.","Hh":"invalid argument. Second argument must be broadcast-compatible with the non-reduced dimensions of the input array.","Hi":"invalid argument. Second argument cannot be safely cast to the input array data type. Value: `%s`.","Hj":"invalid argument. Third argument must be an ndarray-like object. Value: `%s`.","Hk":"invalid option. `%s` option must be an array of integers. Option: `%s`.","Hl":"invalid option. `%s` option contains an out-of-bounds dimension index. Option: [%s].","Hm":"invalid option. `%s` option specifies more dimensions than exists in the input array. Number of dimensions: %d. Option: [%s].","Hn":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].","Ho":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).","Hp":"invalid argument. Second argument must be an ndarray-like object. Value: `%s`.","Hq":"invalid argument. Second argument must have one of the following data types: \"%s\". Data type: `%s`.","Hr":"invalid argument. Fourteenth argument must be non-zero. Value: `%d`.","Hs":"invalid argument. Seventeenth argument must be non-zero. Value: `%d`.","Ht":"invalid argument. Eighteenth argument must be non-zero. Value: `%d`.","Hu":"invalid option. `%s` option contains duplicate indices. Option: [%s].","Hv":"invalid argument. First argument must be an object having a \"default\" property and an associated method.","Hw":"invalid argument. Second argument must contain arrays of data types. Value: `%s`.","Hx":"invalid argument. Argument %d must have one of the following data types: \"%s\". Data type: `%s`.","Hy":"invalid argument. Argument %d must be an ndarray-like object. Value: `%s`.","Hz":"invalid arguments. Input and output arrays must have the same shape.","I0":"invalid argument. First argument specifies an unexpected number of types. A pair of input and output ndarray data types must be specified for each provided strided function.","I1":"invalid argument. First argument specifies an unexpected number of types. An input ndarray data type must be specified for each provided strided function.","I2":"invalid argument. Array arguments after the first two arrays must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","I3":"invalid argument. Loop dimensions must be consistent across all provided arrays. Input array shape: [%s]. Loop dimension indices: [%s]. Loop dimensions: [%s]. Array shape: [%s] (index: %d).","I4":"invalid argument. First argument must be an object having a \"types\" property whose associated value is an array-like object.","I5":"invalid argument. First argument must be an object having a \"fcns\" property whose associated value is an array-like object containing functions.","I6":"invalid argument. Fourth argument must be an object having a supported output data type policy. Value: `%s`.","I7":"invalid argument. Fourth argument must be an object having a supported casting policy. Value: `%s`.","I8":"invalid operation. Unable to promote the input and output data types. Input data type: %s. Output data type: %s.","I9":"invalid argument. Third argument must be a supported casting policy. Value: `%s`.","IA":"invalid option. `%s` option must be an object containing properties having values which are objects. Option: `%s`.","IB":"invalid option. `%s` option must be an object having %s `%s` property which is an array of strings. Option: `%s`.","IC":"invalid option. `%s` option must have %s `%s` property.","ID":"invalid argument. Second argument must be either an ndarray or a numeric scalar value. Value: `%s`.","IE":"invalid argument. Eleventh argument must be non-zero. Value: `%d`.","IF":"invalid option. `%s` option must be a valid memory layout. Option: `%s`.","IG":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d. ndims(z) == %d.","IH":"invalid argument. Unable to resolve an output data type. The output data type policy is \"same\" and yet the input data types are not equal. Data types: [%s].","II":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input data types can be safely cast. Data types: [%s].","IJ":"invalid argument. %s argument must have one of the following data types: \"%s\". Data type: `%s`.","IK":"invalid option. `%s` option must be a valid index mode. Option: `%s`.","IL":"invalid option. `%s` option must be a memory layout. Option: `%s`.","IM":"invalid argument. ArrayBuffer is incompatible with the specified data type. Value: `%s`.","IN":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, iterable, data type, or options object. Value: `%s`.","IO":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or iterable. Value: `%s`.","IP":"invalid argument. Third argument must be a recognized/supported data type. Value: `%s`.","IQ":"invalid argument. Fourth argument must be a recognized/supported data type. Value: `%s`.","IR":"invalid argument. Fifth argument must be greater than or equal to max(1,%d). Value: `%d`.","IS":"invalid argument. Second argument must have an integer data type. Value: `%s`.","IT":"invalid argument. Second argument must be an integer or an ndarray-like object. Value: `%s`.","IU":"invalid argument. Union types may only be initialized by a single member.","IV":"invalid invocation. `this` is not a struct instance.","IW":"invalid operation. struct does not have any fields.","IX":"unexpected error. Unrecognized data type. Value: `%s`.","IY":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Data types: [%s, %s].","IZ":"invalid argument. Field objects must have the following properties: \"%s\". Value: `%s`.","Ia":"invalid argument. Union types cannot contain nested union types. Value: `%s`.","Ib":"invalid argument. Union types can only contain one field with a default value. Value: `%s`.","Ic":"invalid argument. Union types must contain fields having the same byte length. Value: `%s`.","Id":"invalid argument. `%s` field must be a string. Value: `%s`.","Ie":"invalid argument. `%s` field must be a boolean. Value: `%s`.","If":"invalid argument. `%s` field must be a positive integer. Value: `%s`.","Ig":"invalid assignment. `%s` must be a `struct` instance. Value: `%s`.","Ih":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Value: `%s`.","Ii":"invalid assignment. `%s` must be a `struct` instance having the same byte length.","Ij":"invalid assignment. `%s` must be an array-like object. Value: `%s`.","Ik":"invalid assignment. `%s` must be an array-like object having length %u.","Il":"invalid argument. Byte length must be a nonnegative integer. Value: `%s`.","Im":"invalid argument. ArrayBuffer has insufficient capacity. Minimum capacity: `%u`.","In":"invalid argument. First argument must be a `struct` instance. Value: `%s`.","Io":"invalid argument. `%s` field must be one of the following: \"%s\". Value: `%s`.","Ip":"invalid argument. First argument must be an array of objects having unique field names. Value: `%s`.","Iq":"invalid argument. `%s` field must be a non-empty string. Value: `%s`.","Ir":"invalid argument. First argument must be an array of objects. Value: `%s`. Index: `%d`.","Is":"invalid argument. Union types must be an array of objects. Value: `%s`. Index: `%d`.","It":"invalid argument. Field name must be one of the following: \"%s\". Value: `%s`.","Iu":"invalid argument. `%s` field must be either a struct type or one of the following: \"%s\". Value: `%s`.","Iv":"invalid assignment. `%s` must be an array-like object containing `struct` instances having the same byte length.","Iw":"invalid argument. First argument must be one of the following: \"%s\". Value: `%s`.","Ix":"invalid argument. First argument must be an ArrayBuffer or a data object. Value: `%s`.","Iy":"invalid argument. First argument must be either a struct constructor or struct schema. Value: `%s`.","Iz":"invalid argument. Each element of a provided input array must be a valid object or a struct instance having the same layout as elements in the desired output array.","J0":"invalid argument. Environment lacks Symbol.iterator support. First argument must be a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","J1":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","J2":"invalid argument. Each element of a provided input iterable must be either a valid object or a struct instance having the same layout as elements in the desired output array.","J3":"invalid argument. Second argument must be a multiple of %u. Value: `%u`.","J4":"invalid argument. Second argument exceeds the bounds of the ArrayBuffer. Value: `%s`.","J5":"invalid argument. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","J6":"invalid invocation. `this` is not a %s.","J7":"invalid argument. Must provide either a valid object or a struct instance. Value: `%s`.","J8":"invalid argument. First argument must be a valid orientation. Value: `%s`.","J9":"invalid argument. Second argument must be a valid orientation. Value: `%s`.","JA":"invalid argument. The first argument must be an ndarray. Value: `%s`.","JB":"invalid argument. Second argument must be either an ndarray or a scalar value. Value: `%s`.","JC":"invalid argument. Third argument must be an ndarray. Value: `%s`.","JD":"invalid argument. Third argument must be either an ndarray or an integer. Value: `%s`.","JE":"invalid operation. Environment lacks support for HTTP/2. Ensure that you are running on a Node.js version which supports HTTP/2 and has been built to include support for the Node.js `crypto` module.","JF":"invalid argument. Input arrays must have the same number of dimensions. First array dimensions: %d. Second array dimensions: %d.","JG":"invalid argument. Input arrays must have the same shape. First array shape: [%s]. Second array shape: [%s].","JH":"invalid argument. Output array must have the same number of non-reduced dimensions as input arrays. Input array shape: [%s]. Number of non-reduced dimensions: %d. Output array shape: [%s].","JI":"invalid argument. Array arguments after the first array must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","JJ":"invalid argument. Second argument contains an out-of-bounds index. Array shape: (%s). Value: `[%s]`.","JK":"invalid argument. Thirteenth argument must be non-zero. Value: `%d`.","JL":"invalid argument. Sixth argument must be greater than or equal to max(1,%d). Value: `%d`.","JM":"invalid argument. Fifth argument must be non-zero. Value: `%s`.","JN":"invalid argument. Sixth argument must be non-zero. Value: `%s`.","JO":"invalid arguments. Unable to resolve an ndarray function supporting the provided argument data types.","JP":"invalid argument. First argument specifies an unexpected number of types. Two input ndarray data types must be specified for each provided strided function.","JQ":"invalid argument. First argument specifies an unexpected number of types. An output ndarray data type must be specified for each provided strided function.","JR":"invalid operation. Unable to promote the input and output data types. Input data types: [%s]. Output data type: %s.","JS":"invalid argument. Fourth argument must be a supported casting policy. Value: `%s`.","JT":"invalid argument. Fourth argument must be an ndarray. Value: `%s`.","JU":"invalid option. `%s` option must be a supported data type. Option: `%s`.","JV":"invalid argument. First argument must be either a supported data type string, a struct constructor, or another data type instance. Value: `%s`.","JW":"invalid argument. Second argument must be a valid sort order. Value: `%s`.","JX":"invalid argument. Second argument must be either an ndarray, a numeric scalar value, or a supported string. Value: `%s`.","JY":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input ndarrays can be safely cast. Data types: [%s].","JZ":"invalid argument. The list of input ndarrays cannot be safely cast to the data of the output ndarray. Input data types: [%s]. Output data type: %s.","Ja":"invalid argument. Second argument is not broadcast compatible with the list of input ndarrays. Array shape: (%s). Desired shape: (%s).","Jb":"invalid argument. Second argument must be a negative integer. Value: `%s`.","Jc":"invalid argument. First argument cannot be safely cast to the output data type. Data types: [%s, %s].","Jd":"invalid option. First argument cannot be safely cast to the specified data type. Input data type: %s. Option: `%s`.","Je":"invalid argument. First argument must be an ndarray having at least one dimension.","Jf":"invalid argument. Second argument must be either a number, complex number, or an ndarray. Value: `%s`.","Jg":"invalid argument. Third argument must have one of the following data types: \"%s\". Data type: `%s`.","Jh":"invalid argument. Third argument must be either a number, complex number, or an ndarray. Value: `%s`.","Ji":"invalid argument. Fourth argument must have one of the following data types: \"%s\". Data type: `%s`.","Jj":"invalid argument. Fourth argument must be either a boolean or an ndarray. Value: `%s`.","Jk":"invalid argument. First argument must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","Jl":"invalid option. `%s` option must be a supported order. Option: `%s`.","Jm":"invalid argument. Argument %d cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s.","Jn":"invalid invocation. Must provide at least two arguments.","Jo":"invalid invocation. Must provide at least one argument.","Jp":"invalid argument. Last argument must be a one-dimensional ndarray. Value: `%s`.","Jq":"invalid argument. Each ndarray argument must have fewer than two dimensions. Argument: %d.","Jr":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number of observations must be greater than zero).","Js":"invalid argument. First argument must be an ndarray having two or more dimensions.","Jt":"invalid invocation. Must provide at least three arguments.","Ju":"invalid invocation. `this` is not a floating-point number array.","Jv":"invalid argument. The number of elements (means) in the second argument must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","Jw":"%s %s failed with exit code: %s.","Jx":"%s %s failed due to termination signal: %s.","Jy":"invalid argument. Second argument must be either an ndarray or an integer. Value: `%s`.","Jz":"invalid argument. Second argument cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s.","K0":"invalid option. `%s` option must be a zero-dimensional ndarray.","K1":"invalid argument. Second argument must be either an ndarray-like object, a numeric value, or a supported string. Value: `%s`.","K2":"invalid argument. Second argument must be a zero-dimensional ndarray.","K3":"invalid argument. Must provide an integer on the interval [0, 2^64-1]. Value: `%s`.","K4":"invalid argument. Must provide an integer on the interval [0, 2^53-1]. Value: `%s`.","K5":"invalid argument. Must provide an array. Value: `%s`.","K6":"invalid argument. Must provide an array of length 2. Value: `[%s]`.","K7":"invalid argument. Must provide an array of integer values on the interval [%u, %u]. Value: `[%s]`.","K8":"invalid argument. First argument must be a nonnegative integer on the interval [%u, %u]. Value: `%s`.","K9":"invalid argument. Second argument must be a nonnegative integer on the interval [%u, %u]. Value: `%s`.","KA":"invalid argument. Must provide an integer on the interval [%d, %d]. Value: `%s`.","KB":"invalid argument. Fourth argument must be an ndarray-like object. Value: `%s`.","KC":"invalid option. `%s` option must be an array of nonnegative integers. Option: `%s`.","KD":"invalid argument. First argument must have one of the following data types: \"%s\". Value: `%s`.","KE":"invalid argument. Must provide an ndarray having two or more dimensions. Number of dimensions: `%u`.","KF":"invalid option. `%s` option must be a negative integer. Option: `%s`.","KG":"invalid argument. Third argument must be an array of integers. Value: `%s`.","KH":"invalid argument. Third argument must be an array of nonnegative integers. Value: `%s`.","KI":"invalid argument. Must provide a complex-valued floating-point ndarray. Value: `%s`.","KJ":"invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","KK":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d. ndims(z) == %d. ndims(w) == %d.","KL":"invalid argument. Second argument must have at least as many elements as the number of dimensions of the first argument. Number of input dimensions: `%u`. Number of repetitions: `%u`.","KM":"invalid argument. Must provide exactly two dimension indices. Value: `[%s]`.","KN":"invalid argument. First argument must be an ndarray having two or more dimensions. Number of dimensions: %d.","KO":"invalid argument. The first argument cannot be safely cast to the output array data type. Data type: %s. Value: `%s`.","KP":"invalid argument. Product of the sizes must be equal to the size of the dimension to be unflattened. Dimension: %d. Size: %d. Value: `[%s]`.","KQ":"invalid argument. First argument must contain one or more ndarrays. Value: `%s`.","KR":"invalid argument. First argument must be an array-like object containing one or more ndarrays. Value: `%s`.","KS":"invalid argument. Must provide one- or two-dimensional ndarrays. Number of dimensions: `%u`.","KT":"invalid argument. All ndarrays must have the same number of columns. Expected number of columns: `%u`. Actual number of columns: `%u`.","KU":"invalid argument. Second argument must be a two-dimensional ndarray. Number of dimensions: `%u`.","KV":"invalid option. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","KW":"invalid argument. All ndarrays must have the same number of rows. Expected number of rows: `%u`. Actual number of rows: `%u`.","KX":"invalid argument. Second argument must be a string or an array of strings. Value: `%s`.","KY":"invalid invocation. Insufficient arguments. Array shape: (%s). Number of indices: %u.","KZ":"invalid invocation. Too many arguments. Array shape: (%s). Number of indices: %u.","Ka":"invalid argument. Must provide a shape, ArrayBuffer, array-like object, iterable, data type, or options object. Value: `%s`.","Kb":"invalid argument. First argument must be a shape, ArrayBuffer, array-like object, or iterable. Value: `%s`.","Kc":"invalid argument. Third argument must be a valid shape. Value: `%s`.","Kd":"invalid argument. Fifth argument must be a recognized/supported data type. Value: `%s`.","Ke":"invalid argument. Second argument must be a supported distance metric. Value: `%s`.","Kf":"invalid argument. Must provide an integer on the interval [-(2^63), 2^63-1]. Value: `%s`.","Kg":"invalid argument. Must provide an integer on the interval [-(2^53-1), 2^53-1]. Value: `%s`.","Kh":"invalid argument. First argument must be a string encoding an integer on the interval [0, 2^64). Value: `%s`.","Ki":"invalid argument. Second argument must be an integer on the interval [2, 36]. Value: `%s`."} diff --git a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv index bee041acfcee..766db347e4ad 100644 --- a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv @@ -194,8 +194,46 @@ "295",@stdlib/stats-strided-dmeanpw "296",@stdlib/stats/strided/dmeanwd "297",@stdlib/stats-strided-dmeanwd -"298",@stdlib/stats/strided/dmediansorted -"299",@stdlib/stats-strided-dmediansorted +"300",@stdlib/blas/ext/base/cxmy +"301",@stdlib/blas-ext-base-cxmy +"302",@stdlib/blas/ext/base/dfill-equal +"303",@stdlib/blas-ext-base-dfill-equal +"304",@stdlib/blas/ext/base/dfill-nan +"305",@stdlib/blas-ext-base-dfill-nan +"306",@stdlib/blas/ext/base/dfill-not-equal +"307",@stdlib/blas-ext-base-dfill-not-equal +"308",@stdlib/blas/ext/base/dfirst-index-equal +"309",@stdlib/blas-ext-base-dfirst-index-equal +"310",@stdlib/blas/ext/base/ndarray/zxmy +"311",@stdlib/blas-ext-base-ndarray-zxmy +"312",@stdlib/blas/ext/base/sfill-equal +"313",@stdlib/blas-ext-base-sfill-equal +"314",@stdlib/blas/ext/base/sfill-nan +"315",@stdlib/blas-ext-base-sfill-nan +"316",@stdlib/blas/ext/base/sfill-not-equal +"317",@stdlib/blas-ext-base-sfill-not-equal +"318",@stdlib/blas/ext/base/sfirst-index-equal +"319",@stdlib/blas-ext-base-sfirst-index-equal +"320",@stdlib/number/uint64/base/set-high-word +"321",@stdlib/number-uint64-base-set-high-word +"322",@stdlib/number/uint64/base/string2words +"323",@stdlib/number-uint64-base-string2words +"324",@stdlib/stats/base/dists/anglit/cdf +"325",@stdlib/stats-base-dists-anglit-cdf +"326",@stdlib/stats/base/dists/anglit/entropy +"327",@stdlib/stats-base-dists-anglit-entropy +"328",@stdlib/stats/base/dists/anglit/mode +"329",@stdlib/stats-base-dists-anglit-mode +"330",@stdlib/stats/incr/nanmsumprod +"331",@stdlib/stats-incr-nanmsumprod +"332",@stdlib/stats/incr/nanmvmr +"333",@stdlib/stats-incr-nanmvmr +"334",@stdlib/stats/incr/nanpcorr +"335",@stdlib/stats-incr-nanpcorr +"336",@stdlib/stats/incr/nanpcorr2 +"337",@stdlib/stats-incr-nanpcorr2 +"338",@stdlib/stats/incr/nanpcorrdist +"339",@stdlib/stats-incr-nanpcorrdist "1Yi",@stdlib/array/base/accessor-getter "1Yj",@stdlib/array-base-accessor-getter "1Yk",@stdlib/array/base/accessor-setter @@ -1297,6 +1335,8 @@ "06v",@stdlib/assert-is-int16array "06w",@stdlib/assert/is-int32array "06x",@stdlib/assert-is-int32array +"2zW",@stdlib/assert/is-int64 +"2zX",@stdlib/assert-is-int64 "06y",@stdlib/assert/is-int8array "06z",@stdlib/assert-is-int8array "070",@stdlib/assert/is-integer-array @@ -1792,6 +1832,8 @@ "2dJ",@stdlib/blas-base-ndarray-caxpy "2dK",@stdlib/blas/base/ndarray/ccopy "2dL",@stdlib/blas-base-ndarray-ccopy +"2zY",@stdlib/blas/base/ndarray/cgemv +"2zZ",@stdlib/blas-base-ndarray-cgemv "2dM",@stdlib/blas/base/ndarray/cscal "2dN",@stdlib/blas-base-ndarray-cscal "2dO",@stdlib/blas/base/ndarray/csscal @@ -1806,14 +1848,22 @@ "2dX",@stdlib/blas-base-ndarray-dcopy "2Ss",@stdlib/blas/base/ndarray/ddot "2St",@stdlib/blas-base-ndarray-ddot +"2za",@stdlib/blas/base/ndarray/dgemv +"2zb",@stdlib/blas-base-ndarray-dgemv +"2zc",@stdlib/blas/base/ndarray/dger +"2zd",@stdlib/blas-base-ndarray-dger "2dY",@stdlib/blas/base/ndarray/dnrm2 "2dZ",@stdlib/blas-base-ndarray-dnrm2 "2da",@stdlib/blas/base/ndarray/dscal "2db",@stdlib/blas-base-ndarray-dscal "2dc",@stdlib/blas/base/ndarray/dsdot "2dd",@stdlib/blas-base-ndarray-dsdot +"2ze",@stdlib/blas/base/ndarray/dspr +"2zf",@stdlib/blas-base-ndarray-dspr "2de",@stdlib/blas/base/ndarray/dswap "2df",@stdlib/blas-base-ndarray-dswap +"2zg",@stdlib/blas/base/ndarray/dsyr2 +"2zh",@stdlib/blas-base-ndarray-dsyr2 "2dg",@stdlib/blas/base/ndarray/dzasum "2dh",@stdlib/blas-base-ndarray-dzasum "2di",@stdlib/blas/base/ndarray/dznrm2 @@ -1826,12 +1876,20 @@ "2dp",@stdlib/blas-base-ndarray-gcopy "2Su",@stdlib/blas/base/ndarray/gdot "2Sv",@stdlib/blas-base-ndarray-gdot +"2zi",@stdlib/blas/base/ndarray/ggemm +"2zj",@stdlib/blas-base-ndarray-ggemm +"2zk",@stdlib/blas/base/ndarray/ggemv +"2zl",@stdlib/blas-base-ndarray-ggemv +"2zm",@stdlib/blas/base/ndarray/gger +"2zn",@stdlib/blas-base-ndarray-gger "2dq",@stdlib/blas/base/ndarray/gnrm2 "2dr",@stdlib/blas-base-ndarray-gnrm2 "2ds",@stdlib/blas/base/ndarray/gscal "2dt",@stdlib/blas-base-ndarray-gscal "2du",@stdlib/blas/base/ndarray/gswap "2dv",@stdlib/blas-base-ndarray-gswap +"2zo",@stdlib/blas/base/ndarray/gsyr +"2zp",@stdlib/blas-base-ndarray-gsyr "2dw",@stdlib/blas/base/ndarray/idamax "2dx",@stdlib/blas-base-ndarray-idamax "2us",@stdlib/blas/base/ndarray/igamax @@ -1854,10 +1912,16 @@ "2Sx",@stdlib/blas-base-ndarray-sdot "2eA",@stdlib/blas/base/ndarray/sdsdot "2eB",@stdlib/blas-base-ndarray-sdsdot +"2zq",@stdlib/blas/base/ndarray/sgemv +"2zr",@stdlib/blas-base-ndarray-sgemv +"2zs",@stdlib/blas/base/ndarray/sger +"2zt",@stdlib/blas-base-ndarray-sger "2eC",@stdlib/blas/base/ndarray/snrm2 "2eD",@stdlib/blas-base-ndarray-snrm2 "2eE",@stdlib/blas/base/ndarray/sscal "2eF",@stdlib/blas-base-ndarray-sscal +"2zu",@stdlib/blas/base/ndarray/sspr +"2zv",@stdlib/blas-base-ndarray-sspr "2eG",@stdlib/blas/base/ndarray/sswap "2eH",@stdlib/blas-base-ndarray-sswap "2eI",@stdlib/blas/base/ndarray/zaxpy @@ -2034,6 +2098,8 @@ "2ed",@stdlib/blas-ext-base-clast-index-of-row "2ee",@stdlib/blas/ext/base/cone-to "2ef",@stdlib/blas-ext-base-cone-to +"2zw",@stdlib/blas/ext/base/creplicate +"2zx",@stdlib/blas-ext-base-creplicate "2Hs",@stdlib/blas/ext/base/csum "2Ht",@stdlib/blas-ext-base-csum "2Hu",@stdlib/blas/ext/base/csumkbn @@ -2042,6 +2108,8 @@ "2eh",@stdlib/blas-ext-base-cunitspace "2xe",@stdlib/blas/ext/base/cwapx "2xf",@stdlib/blas-ext-base-cwapx +"2zy",@stdlib/blas/ext/base/cwax +"2zz",@stdlib/blas-ext-base-cwax "2ei",@stdlib/blas/ext/base/cwhere "2ej",@stdlib/blas-ext-base-cwhere "2v0",@stdlib/blas/ext/base/cwxsa @@ -2110,6 +2178,8 @@ "2f3",@stdlib/blas-ext-base-dindex-of-column "2vE",@stdlib/blas/ext/base/dindex-of-falsy "2vF",@stdlib/blas-ext-base-dindex-of-falsy +"30A",@stdlib/blas/ext/base/dindex-of-not-equal +"30B",@stdlib/blas-ext-base-dindex-of-not-equal "2f4",@stdlib/blas/ext/base/dindex-of-row "2f5",@stdlib/blas-ext-base-dindex-of-row "2vG",@stdlib/blas/ext/base/dindex-of-truthy @@ -2166,6 +2236,8 @@ "2fD",@stdlib/blas-ext-base-done-to "2vM",@stdlib/blas/ext/base/dones "2vN",@stdlib/blas-ext-base-dones +"30C",@stdlib/blas/ext/base/dreplicate +"30D",@stdlib/blas-ext-base-dreplicate "0D8",@stdlib/blas/ext/base/drev "0D9",@stdlib/blas-ext-base-drev "2YQ",@stdlib/blas/ext/base/drrss @@ -2226,10 +2298,14 @@ "2fP",@stdlib/blas-ext-base-dvander "2vQ",@stdlib/blas/ext/base/dwapx "2vR",@stdlib/blas-ext-base-dwapx +"30E",@stdlib/blas/ext/base/dwax +"30F",@stdlib/blas-ext-base-dwax "2fQ",@stdlib/blas/ext/base/dwhere "2fR",@stdlib/blas-ext-base-dwhere "2vS",@stdlib/blas/ext/base/dwxsa "2vT",@stdlib/blas-ext-base-dwxsa +"30G",@stdlib/blas/ext/base/dxdy +"30H",@stdlib/blas-ext-base-dxdy "2xq",@stdlib/blas/ext/base/dxmy "2xr",@stdlib/blas-ext-base-dxmy "2vU",@stdlib/blas/ext/base/dxpy @@ -2298,18 +2374,38 @@ "2vj",@stdlib/blas-ext-base-gevery "0EC",@stdlib/blas/ext/base/gfill-by "0ED",@stdlib/blas-ext-base-gfill-by +"30I",@stdlib/blas/ext/base/gfill-equal +"30J",@stdlib/blas-ext-base-gfill-equal +"30K",@stdlib/blas/ext/base/gfill-less-than +"30L",@stdlib/blas-ext-base-gfill-less-than +"30M",@stdlib/blas/ext/base/gfill-nan +"30N",@stdlib/blas-ext-base-gfill-nan +"30O",@stdlib/blas/ext/base/gfill-not-equal +"30P",@stdlib/blas-ext-base-gfill-not-equal "0EE",@stdlib/blas/ext/base/gfill "0EF",@stdlib/blas-ext-base-gfill "2Sy",@stdlib/blas/ext/base/gfind-index "2Sz",@stdlib/blas-ext-base-gfind-index "2T0",@stdlib/blas/ext/base/gfind-last-index "2T1",@stdlib/blas-ext-base-gfind-last-index +"30Q",@stdlib/blas/ext/base/gfirst-index-equal +"30R",@stdlib/blas-ext-base-gfirst-index-equal +"30S",@stdlib/blas/ext/base/gfirst-index-greater-than +"30T",@stdlib/blas-ext-base-gfirst-index-greater-than +"30U",@stdlib/blas/ext/base/gfirst-index-less-than +"30V",@stdlib/blas-ext-base-gfirst-index-less-than +"30W",@stdlib/blas/ext/base/gfirst-index-not-equal +"30X",@stdlib/blas-ext-base-gfirst-index-not-equal "2fo",@stdlib/blas/ext/base/gindex-of-column "2fp",@stdlib/blas-ext-base-gindex-of-column "2vk",@stdlib/blas/ext/base/gindex-of-falsy "2vl",@stdlib/blas-ext-base-gindex-of-falsy +"30Y",@stdlib/blas/ext/base/gindex-of-not-equal +"30Z",@stdlib/blas-ext-base-gindex-of-not-equal "2W2",@stdlib/blas/ext/base/gindex-of-row "2W3",@stdlib/blas-ext-base-gindex-of-row +"30a",@stdlib/blas/ext/base/gindex-of-same-value +"30b",@stdlib/blas-ext-base-gindex-of-same-value "2vm",@stdlib/blas/ext/base/gindex-of-truthy "2vn",@stdlib/blas-ext-base-gindex-of-truthy "2No",@stdlib/blas/ext/base/gindex-of @@ -2318,6 +2414,8 @@ "2fr",@stdlib/blas-ext-base-gjoin-between "2Yw",@stdlib/blas/ext/base/gjoin "2Yx",@stdlib/blas-ext-base-gjoin +"30c",@stdlib/blas/ext/base/glast-index-equal +"30d",@stdlib/blas-ext-base-glast-index-equal "2xu",@stdlib/blas/ext/base/glast-index-of-falsy "2xv",@stdlib/blas-ext-base-glast-index-of-falsy "2fs",@stdlib/blas/ext/base/glast-index-of-row @@ -2404,6 +2502,8 @@ "2w1",@stdlib/blas-ext-base-gwxsa "2y4",@stdlib/blas/ext/base/gwxsy "2y5",@stdlib/blas-ext-base-gwxsy +"30e",@stdlib/blas/ext/base/gxdy +"30f",@stdlib/blas-ext-base-gxdy "2y6",@stdlib/blas/ext/base/gxmy "2y7",@stdlib/blas-ext-base-gxmy "2w2",@stdlib/blas/ext/base/gxpy @@ -2428,6 +2528,8 @@ "2Yz",@stdlib/blas-ext-base-ndarray-csumkbn "2gK",@stdlib/blas/ext/base/ndarray/cunitspace "2gL",@stdlib/blas-ext-base-ndarray-cunitspace +"30g",@stdlib/blas/ext/base/ndarray/cxmy +"30h",@stdlib/blas-ext-base-ndarray-cxmy "2yA",@stdlib/blas/ext/base/ndarray/cxpy "2yB",@stdlib/blas-ext-base-ndarray-cxpy "2gM",@stdlib/blas/ext/base/ndarray/cxsa @@ -2436,6 +2538,8 @@ "2yD",@stdlib/blas-ext-base-ndarray-cxsy "2gO",@stdlib/blas/ext/base/ndarray/czero-to "2gP",@stdlib/blas-ext-base-ndarray-czero-to +"30i",@stdlib/blas/ext/base/ndarray/dany +"30j",@stdlib/blas-ext-base-ndarray-dany "2gQ",@stdlib/blas/ext/base/ndarray/daxpb "2gR",@stdlib/blas-ext-base-ndarray-daxpb "2w6",@stdlib/blas/ext/base/ndarray/daxpby @@ -2454,6 +2558,8 @@ "2gX",@stdlib/blas-ext-base-ndarray-dcusumpw "2w8",@stdlib/blas/ext/base/ndarray/ddiff "2w9",@stdlib/blas-ext-base-ndarray-ddiff +"30k",@stdlib/blas/ext/base/ndarray/dfill-not-equal +"30l",@stdlib/blas-ext-base-ndarray-dfill-not-equal "2wA",@stdlib/blas/ext/base/ndarray/dindex-of-falsy "2wB",@stdlib/blas-ext-base-ndarray-dindex-of-falsy "2Ns",@stdlib/blas/ext/base/ndarray/dindex-of @@ -2494,6 +2600,8 @@ "2gt",@stdlib/blas-ext-base-ndarray-dsumpw "2gu",@stdlib/blas/ext/base/ndarray/dunitspace "2gv",@stdlib/blas-ext-base-ndarray-dunitspace +"30m",@stdlib/blas/ext/base/ndarray/dxmy +"30n",@stdlib/blas-ext-base-ndarray-dxmy "2yE",@stdlib/blas/ext/base/ndarray/dxpy "2yF",@stdlib/blas-ext-base-ndarray-dxpy "2gw",@stdlib/blas/ext/base/ndarray/dxsa @@ -2502,6 +2610,8 @@ "2yH",@stdlib/blas-ext-base-ndarray-dxsy "2gy",@stdlib/blas/ext/base/ndarray/dzero-to "2gz",@stdlib/blas-ext-base-ndarray-dzero-to +"30o",@stdlib/blas/ext/base/ndarray/gany +"30p",@stdlib/blas-ext-base-ndarray-gany "2h0",@stdlib/blas/ext/base/ndarray/gaxpb "2h1",@stdlib/blas-ext-base-ndarray-gaxpb "2wC",@stdlib/blas/ext/base/ndarray/gaxpby @@ -2518,6 +2628,8 @@ "2h9",@stdlib/blas-ext-base-ndarray-gcusumors "2hA",@stdlib/blas/ext/base/ndarray/gcusumpw "2hB",@stdlib/blas-ext-base-ndarray-gcusumpw +"30q",@stdlib/blas/ext/base/ndarray/gfill-not-equal +"30r",@stdlib/blas-ext-base-ndarray-gfill-not-equal "2T4",@stdlib/blas/ext/base/ndarray/gfind-index "2T5",@stdlib/blas-ext-base-ndarray-gfind-index "2T6",@stdlib/blas/ext/base/ndarray/gfind-last-index @@ -2564,6 +2676,8 @@ "2hV",@stdlib/blas-ext-base-ndarray-gsumpw "2hW",@stdlib/blas/ext/base/ndarray/gunitspace "2hX",@stdlib/blas-ext-base-ndarray-gunitspace +"30s",@stdlib/blas/ext/base/ndarray/gxmy +"30t",@stdlib/blas-ext-base-ndarray-gxmy "2yI",@stdlib/blas/ext/base/ndarray/gxpy "2yJ",@stdlib/blas-ext-base-ndarray-gxpy "2wI",@stdlib/blas/ext/base/ndarray/gxsa @@ -2574,6 +2688,8 @@ "2hZ",@stdlib/blas-ext-base-ndarray-gzero-to "2FM",@stdlib/blas/ext/base/ndarray "2FN",@stdlib/blas-ext-base-ndarray +"30u",@stdlib/blas/ext/base/ndarray/sany +"30v",@stdlib/blas-ext-base-ndarray-sany "2ha",@stdlib/blas/ext/base/ndarray/saxpb "2hb",@stdlib/blas-ext-base-ndarray-saxpb "2wK",@stdlib/blas/ext/base/ndarray/saxpby @@ -2590,6 +2706,8 @@ "2ZH",@stdlib/blas-ext-base-ndarray-scusumkbn2 "2he",@stdlib/blas/ext/base/ndarray/scusumors "2hf",@stdlib/blas-ext-base-ndarray-scusumors +"30w",@stdlib/blas/ext/base/ndarray/sfill-not-equal +"30x",@stdlib/blas-ext-base-ndarray-sfill-not-equal "2O0",@stdlib/blas/ext/base/ndarray/sindex-of "2O1",@stdlib/blas-ext-base-ndarray-sindex-of "2O2",@stdlib/blas/ext/base/ndarray/slast-index-of @@ -2624,6 +2742,8 @@ "2hx",@stdlib/blas-ext-base-ndarray-ssumpw "2hy",@stdlib/blas/ext/base/ndarray/sunitspace "2hz",@stdlib/blas-ext-base-ndarray-sunitspace +"30y",@stdlib/blas/ext/base/ndarray/sxmy +"30z",@stdlib/blas-ext-base-ndarray-sxmy "2yM",@stdlib/blas/ext/base/ndarray/sxpy "2yN",@stdlib/blas-ext-base-ndarray-sxpy "2i0",@stdlib/blas/ext/base/ndarray/sxsa @@ -2656,6 +2776,8 @@ "2iD",@stdlib/blas-ext-base-ndarray-zzero-to "0Eq",@stdlib/blas/ext/base "0Er",@stdlib/blas-ext-base +"2zE",@stdlib/blas/ext/base/sany +"2zF",@stdlib/blas-ext-base-sany "0Es",@stdlib/blas/ext/base/sapx "0Et",@stdlib/blas-ext-base-sapx "0Eu",@stdlib/blas/ext/base/sapxsum @@ -2762,6 +2884,8 @@ "2iZ",@stdlib/blas-ext-base-sone-to "2wm",@stdlib/blas/ext/base/sones "2wn",@stdlib/blas-ext-base-sones +"31A",@stdlib/blas/ext/base/sreplicate +"31B",@stdlib/blas-ext-base-sreplicate "0Fe",@stdlib/blas/ext/base/srev "0Ff",@stdlib/blas-ext-base-srev "2yc",@stdlib/blas/ext/base/ssome @@ -2796,10 +2920,14 @@ "2if",@stdlib/blas-ext-base-svander "2wo",@stdlib/blas/ext/base/swapx "2wp",@stdlib/blas-ext-base-swapx +"31C",@stdlib/blas/ext/base/swax +"31D",@stdlib/blas-ext-base-swax "2ig",@stdlib/blas/ext/base/swhere "2ih",@stdlib/blas-ext-base-swhere "2wq",@stdlib/blas/ext/base/swxsa "2wr",@stdlib/blas-ext-base-swxsa +"31E",@stdlib/blas/ext/base/sxdy +"31F",@stdlib/blas-ext-base-sxdy "2ye",@stdlib/blas/ext/base/sxmy "2yf",@stdlib/blas-ext-base-sxmy "2ws",@stdlib/blas/ext/base/sxpy @@ -2848,6 +2976,8 @@ "2it",@stdlib/blas-ext-base-zindex-of-column "2iu",@stdlib/blas/ext/base/zindex-of-row "2iv",@stdlib/blas-ext-base-zindex-of-row +"31G",@stdlib/blas/ext/base/zindex-of-truthy +"31H",@stdlib/blas-ext-base-zindex-of-truthy "2iw",@stdlib/blas/ext/base/zindex-of "2ix",@stdlib/blas-ext-base-zindex-of "2iy",@stdlib/blas/ext/base/zlast-index-of-row @@ -2856,6 +2986,8 @@ "2j1",@stdlib/blas-ext-base-znancount "2j2",@stdlib/blas/ext/base/zone-to "2j3",@stdlib/blas-ext-base-zone-to +"31I",@stdlib/blas/ext/base/zreplicate +"31J",@stdlib/blas-ext-base-zreplicate "2I2",@stdlib/blas/ext/base/zsum "2I3",@stdlib/blas-ext-base-zsum "2I4",@stdlib/blas/ext/base/zsumkbn @@ -2864,10 +2996,14 @@ "2j5",@stdlib/blas-ext-base-zunitspace "2yi",@stdlib/blas/ext/base/zwapx "2yj",@stdlib/blas-ext-base-zwapx +"31K",@stdlib/blas/ext/base/zwax +"31L",@stdlib/blas-ext-base-zwax "2j6",@stdlib/blas/ext/base/zwhere "2j7",@stdlib/blas-ext-base-zwhere "2wy",@stdlib/blas/ext/base/zwxsa "2wz",@stdlib/blas-ext-base-zwxsa +"31M",@stdlib/blas/ext/base/zxmy +"31N",@stdlib/blas-ext-base-zxmy "2x0",@stdlib/blas/ext/base/zxpy "2x1",@stdlib/blas-ext-base-zxpy "2j8",@stdlib/blas/ext/base/zxsa @@ -2914,6 +3050,8 @@ "0G5",@stdlib/blas-gdot "0G6",@stdlib/blas/gswap "0G7",@stdlib/blas-gswap +"31O",@stdlib/blas/nrm2 +"31P",@stdlib/blas-nrm2 "0G9",@stdlib/blas "0GA",@stdlib/blas/sdot "0GB",@stdlib/blas-sdot @@ -3713,6 +3851,8 @@ "2x3",@stdlib/fft-base-fftpack-cffti "2x4",@stdlib/fft/base/fftpack/cosqi "2x5",@stdlib/fft-base-fftpack-cosqi +"31Q",@stdlib/fft/base/fftpack/costi +"31R",@stdlib/fft-base-fftpack-costi "2kI",@stdlib/fft/base/fftpack/decompose "2kJ",@stdlib/fft-base-fftpack-decompose "2x6",@stdlib/fft/base/fftpack @@ -3721,6 +3861,8 @@ "2x9",@stdlib/fft-base-fftpack-rffti "2ym",@stdlib/fft/base/fftpack/sinqi "2yn",@stdlib/fft-base-fftpack-sinqi +"31S",@stdlib/fft/base/fftpack/sinti +"31T",@stdlib/fft-base-fftpack-sinti "2xA",@stdlib/fft/base "2xB",@stdlib/fft-base "2xD",@stdlib/fft @@ -5347,6 +5489,32 @@ "2l1",@stdlib/ml-base-kmeans-metrics "2xG",@stdlib/ml/base/kmeans/results/struct-factory "2xH",@stdlib/ml-base-kmeans-results-struct-factory +"31U",@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient +"31V",@stdlib/ml-base-loss-float64-epsilon-insensitive-gradient +"31W",@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient +"31X",@stdlib/ml-base-loss-float64-squared-epsilon-insensitive-gradient +"31Y",@stdlib/ml/base/loss/float64/squared-error-gradient +"31Z",@stdlib/ml-base-loss-float64-squared-error-gradient +"31a",@stdlib/ml/base/sgd-classification/learning-rate-enum2str +"31b",@stdlib/ml-base-sgd-classification-learning-rate-enum2str +"31c",@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum +"31d",@stdlib/ml-base-sgd-classification-learning-rate-resolve-enum +"31e",@stdlib/ml/base/sgd-classification/learning-rate-resolve-str +"31f",@stdlib/ml-base-sgd-classification-learning-rate-resolve-str +"31g",@stdlib/ml/base/sgd-classification/learning-rate-str2enum +"31h",@stdlib/ml-base-sgd-classification-learning-rate-str2enum +"31i",@stdlib/ml/base/sgd-classification/learning-rates +"31j",@stdlib/ml-base-sgd-classification-learning-rates +"31k",@stdlib/ml/base/sgd-classification/loss-function-enum2str +"31l",@stdlib/ml-base-sgd-classification-loss-function-enum2str +"31m",@stdlib/ml/base/sgd-classification/loss-function-resolve-enum +"31n",@stdlib/ml-base-sgd-classification-loss-function-resolve-enum +"31o",@stdlib/ml/base/sgd-classification/loss-function-resolve-str +"31p",@stdlib/ml-base-sgd-classification-loss-function-resolve-str +"31q",@stdlib/ml/base/sgd-classification/loss-function-str2enum +"31r",@stdlib/ml-base-sgd-classification-loss-function-str2enum +"31s",@stdlib/ml/base/sgd-classification/loss-functions +"31t",@stdlib/ml-base-sgd-classification-loss-functions "0h0",@stdlib/ml/incr/binary-classification "0h1",@stdlib/ml-incr-binary-classification "0h2",@stdlib/ml/incr/kmeans @@ -6519,6 +6687,8 @@ "0lh",@stdlib/number-int32-base-to-uint32 "0li",@stdlib/number/int32 "0lj",@stdlib/number-int32 +"2zG",@stdlib/number/int64/ctor +"2zH",@stdlib/number-int64-ctor "2Tw",@stdlib/number/int8/base/identity "2Tx",@stdlib/number-int8-base-identity "2Ya",@stdlib/number/int8/base @@ -6568,6 +6738,14 @@ "2xN",@stdlib/number-uint64-base-add "2xO",@stdlib/number/uint64/base/assert/is-equal "2xP",@stdlib/number-uint64-base-assert-is-equal +"31u",@stdlib/number/uint64/base/bigint2words +"31v",@stdlib/number-uint64-base-bigint2words +"31w",@stdlib/number/uint64/base/get-high-word +"31x",@stdlib/number-uint64-base-get-high-word +"31y",@stdlib/number/uint64/base/get-low-word +"31z",@stdlib/number-uint64-base-get-low-word +"2zI",@stdlib/number/uint64/base/number2words +"2zJ",@stdlib/number-uint64-base-number2words "2xQ",@stdlib/number/uint64/base/to-words "2xR",@stdlib/number-uint64-base-to-words "2p4",@stdlib/number/uint64/ctor @@ -7522,6 +7700,12 @@ "2xT",@stdlib/stats-base-dists-anglit-mean "2xU",@stdlib/stats/base/dists/anglit/median "2xV",@stdlib/stats-base-dists-anglit-median +"2zK",@stdlib/stats/base/dists/anglit/quantile +"2zL",@stdlib/stats-base-dists-anglit-quantile +"32A",@stdlib/stats/base/dists/anglit/stdev +"32B",@stdlib/stats-base-dists-anglit-stdev +"32C",@stdlib/stats/base/dists/anglit/variance +"32D",@stdlib/stats-base-dists-anglit-variance "0ty",@stdlib/stats/base/dists/arcsine/cdf "0tz",@stdlib/stats-base-dists-arcsine-cdf "0u0",@stdlib/stats/base/dists/arcsine/ctor @@ -8164,6 +8348,18 @@ "14X",@stdlib/stats-base-dists-levy-stdev "14Y",@stdlib/stats/base/dists/levy/variance "14Z",@stdlib/stats-base-dists-levy-variance +"32E",@stdlib/stats/base/dists/log-logistic/cdf +"32F",@stdlib/stats-base-dists-log-logistic-cdf +"2zM",@stdlib/stats/base/dists/log-logistic/mean +"2zN",@stdlib/stats-base-dists-log-logistic-mean +"2zO",@stdlib/stats/base/dists/log-logistic/median +"2zP",@stdlib/stats-base-dists-log-logistic-median +"2zQ",@stdlib/stats/base/dists/log-logistic/mode +"2zR",@stdlib/stats-base-dists-log-logistic-mode +"2zS",@stdlib/stats/base/dists/log-logistic/pdf +"2zT",@stdlib/stats-base-dists-log-logistic-pdf +"32G",@stdlib/stats/base/dists/log-logistic/quantile +"32H",@stdlib/stats-base-dists-log-logistic-quantile "14a",@stdlib/stats/base/dists/logistic/cdf "14b",@stdlib/stats-base-dists-logistic-cdf "14c",@stdlib/stats/base/dists/logistic/ctor @@ -8438,6 +8634,8 @@ "18x",@stdlib/stats-base-dists-triangular-pdf "18y",@stdlib/stats/base/dists/triangular/quantile "18z",@stdlib/stats-base-dists-triangular-quantile +"2zU",@stdlib/stats/base/dists/tukey-lambda/mode +"2zV",@stdlib/stats-base-dists-tukey-lambda-mode "19A",@stdlib/stats/base/dists/uniform/cdf "19B",@stdlib/stats-base-dists-uniform-cdf "19C",@stdlib/stats/base/dists/uniform/ctor @@ -9082,6 +9280,8 @@ "1J3",@stdlib/stats-incr-mrss "1J4",@stdlib/stats/incr/mse "1J5",@stdlib/stats-incr-mse +"32I",@stdlib/stats/incr/mskewness +"32J",@stdlib/stats-incr-mskewness "1J6",@stdlib/stats/incr/mstdev "1J7",@stdlib/stats-incr-mstdev "1J8",@stdlib/stats/incr/msum @@ -9100,24 +9300,66 @@ "1JL",@stdlib/stats-incr-mvmr "1JM",@stdlib/stats/incr/nancount "1JN",@stdlib/stats-incr-nancount +"32K",@stdlib/stats/incr/nancovariance +"32L",@stdlib/stats-incr-nancovariance +"32M",@stdlib/stats/incr/nancv +"32N",@stdlib/stats-incr-nancv +"32O",@stdlib/stats/incr/nanewstdev +"32P",@stdlib/stats-incr-nanewstdev +"32Q",@stdlib/stats/incr/nanewvariance +"32R",@stdlib/stats-incr-nanewvariance "2We",@stdlib/stats/incr/nangmean "2Wf",@stdlib/stats-incr-nangmean "2Wg",@stdlib/stats/incr/nanhmean "2Wh",@stdlib/stats-incr-nanhmean +"32S",@stdlib/stats/incr/nankurtosis +"32T",@stdlib/stats-incr-nankurtosis +"32U",@stdlib/stats/incr/nanmae +"32V",@stdlib/stats-incr-nanmae +"32W",@stdlib/stats/incr/nanmapcorr +"32X",@stdlib/stats-incr-nanmapcorr +"32Y",@stdlib/stats/incr/nanmape +"32Z",@stdlib/stats-incr-nanmape +"32a",@stdlib/stats/incr/nanmax +"32b",@stdlib/stats-incr-nanmax "2GU",@stdlib/stats/incr/nanmaxabs "2GV",@stdlib/stats-incr-nanmaxabs "2Yo",@stdlib/stats/incr/nanmcv "2Yp",@stdlib/stats-incr-nanmcv +"32c",@stdlib/stats/incr/nanmda +"32d",@stdlib/stats-incr-nanmda +"32e",@stdlib/stats/incr/nanme +"32f",@stdlib/stats-incr-nanme "2As",@stdlib/stats/incr/nanmean "2At",@stdlib/stats-incr-nanmean "2Au",@stdlib/stats/incr/nanmeanabs "2Av",@stdlib/stats-incr-nanmeanabs +"32g",@stdlib/stats/incr/nanmeanvar +"32h",@stdlib/stats-incr-nanmeanvar +"32i",@stdlib/stats/incr/nanmgmean +"32j",@stdlib/stats-incr-nanmgmean +"32k",@stdlib/stats/incr/nanmhmean +"32l",@stdlib/stats-incr-nanmhmean +"32m",@stdlib/stats/incr/nanmidrange +"32n",@stdlib/stats-incr-nanmidrange "2Wi",@stdlib/stats/incr/nanmin "2Wj",@stdlib/stats-incr-nanmin "2tC",@stdlib/stats/incr/nanmmape "2tD",@stdlib/stats-incr-nanmmape +"32o",@stdlib/stats/incr/nanmmaxabs +"32p",@stdlib/stats-incr-nanmmaxabs +"32q",@stdlib/stats/incr/nanmmean +"32r",@stdlib/stats-incr-nanmmean +"32s",@stdlib/stats/incr/nanmmin +"32t",@stdlib/stats-incr-nanmmin "2tE",@stdlib/stats/incr/nanmmse "2tF",@stdlib/stats-incr-nanmmse +"32u",@stdlib/stats/incr/nanmpcorr +"32v",@stdlib/stats-incr-nanmpcorr +"32w",@stdlib/stats/incr/nanmrange +"32x",@stdlib/stats-incr-nanmrange +"32y",@stdlib/stats/incr/nanmrss +"32z",@stdlib/stats-incr-nanmrss "2xW",@stdlib/stats/incr/nanmse "2xX",@stdlib/stats-incr-nanmse "2GW",@stdlib/stats/incr/nanmstdev @@ -9126,6 +9368,10 @@ "2QD",@stdlib/stats-incr-nanmsum "2xY",@stdlib/stats/incr/nanmsumabs "2xZ",@stdlib/stats-incr-nanmsumabs +"33A",@stdlib/stats/incr/nanprod +"33B",@stdlib/stats-incr-nanprod +"33C",@stdlib/stats/incr/nanrange +"33D",@stdlib/stats-incr-nanrange "2xa",@stdlib/stats/incr/nanrmse "2xb",@stdlib/stats-incr-nanrmse "2Aw",@stdlib/stats/incr/nanskewness @@ -9413,6 +9659,8 @@ "2QP",@stdlib/stats-strided-dmeanvar "2QQ",@stdlib/stats/strided/dmeanvarpn "2QR",@stdlib/stats-strided-dmeanvarpn +"33E",@stdlib/stats/strided/dmedian-sorted +"33F",@stdlib/stats-strided-dmedian-sorted "29A",@stdlib/stats/strided/dmidrange "29B",@stdlib/stats-strided-dmidrange "2to",@stdlib/stats/strided/dmidrangeabs diff --git a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json index 15494cafc934..fd9ef0139380 100644 --- a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json +++ b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json @@ -1 +1 @@ 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om-array","24o":"@stdlib/ndarray/base/from-scalar-like","24p":"@stdlib/ndarray-base-from-scalar-like","0ig":"@stdlib/ndarray/base/from-scalar","0ih":"@stdlib/ndarray-base-from-scalar","2lg":"@stdlib/ndarray/base/full-by","2lh":"@stdlib/ndarray-base-full-by","2li":"@stdlib/ndarray/base/full","2lj":"@stdlib/ndarray-base-full","0ii":"@stdlib/ndarray/base/function-object","0ij":"@stdlib/ndarray-base-function-object","2Dy":"@stdlib/ndarray/base/includes","2Dz":"@stdlib/ndarray-base-includes","0ik":"@stdlib/ndarray/base/ind","0il":"@stdlib/ndarray-base-ind","0im":"@stdlib/ndarray/base/ind2sub","0in":"@stdlib/ndarray-base-ind2sub","0io":"@stdlib/ndarray/base/iteration-order","0ip":"@stdlib/ndarray-base-iteration-order","2H6":"@stdlib/ndarray/base/loop-interchange-order","2H7":"@stdlib/ndarray-base-loop-interchange-order","1zU":"@stdlib/ndarray/base/map","1zV":"@stdlib/ndarray-base-map","0iq":"@stdlib/ndarray/base/max-view-buffer-index","0ir":"@stdlib/ndarray-base-max-view-buffer-index","2lk":"@stdlib/ndarray/base/maybe-broadcast-array-except-dimensions","2ll":"@stdlib/ndarray-base-maybe-broadcast-array-except-dimensions","0is":"@stdlib/ndarray/base/maybe-broadcast-array","0it":"@stdlib/ndarray-base-maybe-broadcast-array","1nY":"@stdlib/ndarray/base/maybe-broadcast-arrays","1nZ":"@stdlib/ndarray-base-maybe-broadcast-arrays","0iu":"@stdlib/ndarray/base/meta-data-props","0iv":"@stdlib/ndarray-base-meta-data-props","24q":"@stdlib/ndarray/base/min-signed-integer-dtype","24r":"@stdlib/ndarray-base-min-signed-integer-dtype","24s":"@stdlib/ndarray/base/min-unsigned-integer-dtype","24t":"@stdlib/ndarray-base-min-unsigned-integer-dtype","0iw":"@stdlib/ndarray/base/min-view-buffer-index","0ix":"@stdlib/ndarray-base-min-view-buffer-index","0iy":"@stdlib/ndarray/base/minmax-view-buffer-index","0iz":"@stdlib/ndarray-base-minmax-view-buffer-index","2lm":"@stdlib/ndarray/base/nans-like","2ln":"@stdlib/ndarray-base-nans-like","2lo":"@stdlib/ndarray/base/nans","2lp":"@stdlib/ndarray-base-nans","0j0":"@stdlib/ndarray/base/napi/addon-arguments","0j1":"@stdlib/ndarray-base-napi-addon-arguments","0j2":"@stdlib/ndarray/base/napi/dtype-string-to-dtype","0j3":"@stdlib/ndarray-base-napi-dtype-string-to-dtype","0j4":"@stdlib/ndarray/base/napi","0j5":"@stdlib/ndarray-base-napi","0j6":"@stdlib/ndarray/base/napi/typedarray-type-to-dtype","0j7":"@stdlib/ndarray-base-napi-typedarray-type-to-dtype","0j8":"@stdlib/ndarray/base/napi/unary","0j9":"@stdlib/ndarray-base-napi-unary","2lq":"@stdlib/ndarray/base/ndarraylike2descriptor","2lr":"@stdlib/ndarray-base-ndarraylike2descriptor","1zW":"@stdlib/ndarray/base/ndarraylike2ndarray","1zX":"@stdlib/ndarray-base-ndarraylike2ndarray","0jA":"@stdlib/ndarray/base/ndarraylike2object","0jB":"@stdlib/ndarray-base-ndarraylike2object","2OS":"@stdlib/ndarray/base/ndarraylike2scalar","2OT":"@stdlib/ndarray-base-ndarraylike2scalar","1jc":"@stdlib/ndarray/base/ndims","1jd":"@stdlib/ndarray-base-ndims","1je":"@stdlib/ndarray/base/next-cartesian-index","1jf":"@stdlib/ndarray-base-next-cartesian-index","0jC":"@stdlib/ndarray/base/nonsingleton-dimensions","0jD":"@stdlib/ndarray-base-nonsingleton-dimensions","1l8":"@stdlib/ndarray/base/normalize-index","1l9":"@stdlib/ndarray-base-normalize-index","25y":"@stdlib/ndarray/base/normalize-indices","25z":"@stdlib/ndarray-base-normalize-indices","1d8":"@stdlib/ndarray/base/nullary-loop-interchange-order","1d9":"@stdlib/ndarray-base-nullary-loop-interchange-order","2WE":"@stdlib/ndarray/base/nullary-strided1d-dispatch-factory","2WF":"@stdlib/ndarray-base-nullary-strided1d-dispatch-factory","2Ve":"@stdlib/ndarray/base/nullary-strided1d-dispatch","2Vf":"@stdlib/ndarray-base-nullary-strided1d-dispatch","2V6":"@stdlib/ndarray/base/nullary-strided1d","2V7":"@stdlib/ndarray-base-nullary-strided1d","1dA":"@stdlib/ndarray/base/nullary-tiling-block-size","1dB":"@stdlib/ndarray-base-nullary-tiling-block-size","1dC":"@stdlib/ndarray/base/nullary","1dD":"@stdlib/ndarray-base-nullary","2ls":"@stdlib/ndarray/base/nulls-like","2lt":"@stdlib/ndarray-base-nulls-like","2lu":"@stdlib/ndarray/base/nulls","2lv":"@stdlib/ndarray-base-nulls","1nu":"@stdlib/ndarray/base/numel-dimension","1nv":"@stdlib/ndarray-base-numel-dimension","0jE":"@stdlib/ndarray/base/numel","0jF":"@stdlib/ndarray-base-numel","1jg":"@stdlib/ndarray/base/offset","1jh":"@stdlib/ndarray-base-offset","2lw":"@stdlib/ndarray/base/ones-like","2lx":"@stdlib/ndarray-base-ones-like","2ly":"@stdlib/ndarray/base/ones","2lz":"@stdlib/ndarray-base-ones","1kM":"@stdlib/ndarray/base/order","1kN":"@stdlib/ndarray-base-order","2Gm":"@stdlib/ndarray/base/output-dtype","2Gn":"@stdlib/ndarray-base-output-dtype","2m0":"@stdlib/ndarray/base/output-order","2m1":"@stdlib/ndarray-base-output-order","1dE":"@stdlib/ndarray/base/output-policy-enum2str","1dF":"@stdlib/ndarray-base-output-policy-enum2str","1dG":"@stdlib/ndarray/base/output-policy-resolve-enum","1dH":"@stdlib/ndarray-base-output-policy-resolve-enum","1dI":"@stdlib/ndarray/base/output-policy-re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diff --git a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv index ea5cbd156e9e..c97624808fd0 100644 --- a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv +++ b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv @@ -11434,3 +11434,253 @@ "@stdlib/ndarray-matrix",2zB "@stdlib/stats/strided/dmax-sorted",2zC "@stdlib/stats-strided-dmax-sorted",2zD +"@stdlib/blas/ext/base/sany",2zE +"@stdlib/blas-ext-base-sany",2zF +"@stdlib/number/int64/ctor",2zG +"@stdlib/number-int64-ctor",2zH +"@stdlib/number/uint64/base/number2words",2zI +"@stdlib/number-uint64-base-number2words",2zJ +"@stdlib/stats/base/dists/anglit/quantile",2zK +"@stdlib/stats-base-dists-anglit-quantile",2zL +"@stdlib/stats/base/dists/log-logistic/mean",2zM +"@stdlib/stats-base-dists-log-logistic-mean",2zN +"@stdlib/stats/base/dists/log-logistic/median",2zO +"@stdlib/stats-base-dists-log-logistic-median",2zP +"@stdlib/stats/base/dists/log-logistic/mode",2zQ +"@stdlib/stats-base-dists-log-logistic-mode",2zR +"@stdlib/stats/base/dists/log-logistic/pdf",2zS +"@stdlib/stats-base-dists-log-logistic-pdf",2zT +"@stdlib/stats/base/dists/tukey-lambda/mode",2zU +"@stdlib/stats-base-dists-tukey-lambda-mode",2zV +"@stdlib/assert/is-int64",2zW +"@stdlib/assert-is-int64",2zX +"@stdlib/blas/base/ndarray/cgemv",2zY +"@stdlib/blas-base-ndarray-cgemv",2zZ +"@stdlib/blas/base/ndarray/dgemv",2za +"@stdlib/blas-base-ndarray-dgemv",2zb +"@stdlib/blas/base/ndarray/dger",2zc +"@stdlib/blas-base-ndarray-dger",2zd +"@stdlib/blas/base/ndarray/dspr",2ze +"@stdlib/blas-base-ndarray-dspr",2zf +"@stdlib/blas/base/ndarray/dsyr2",2zg +"@stdlib/blas-base-ndarray-dsyr2",2zh +"@stdlib/blas/base/ndarray/ggemm",2zi +"@stdlib/blas-base-ndarray-ggemm",2zj +"@stdlib/blas/base/ndarray/ggemv",2zk +"@stdlib/blas-base-ndarray-ggemv",2zl +"@stdlib/blas/base/ndarray/gger",2zm +"@stdlib/blas-base-ndarray-gger",2zn 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/README.md b/lib/node_modules/@stdlib/fft/base/fftpack/README.md index 1b72212f23bb..7161ddc48a11 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/README.md +++ b/lib/node_modules/@stdlib/fft/base/fftpack/README.md @@ -45,9 +45,11 @@ var o = ns; - [`cffti( N, workspace, strideW, offsetW )`][@stdlib/fft/base/fftpack/cffti]: initialize a workspace array for performing a complex-valued Fourier transform. - [`cosqi( N, workspace, strideW, offsetW )`][@stdlib/fft/base/fftpack/cosqi]: initialize a workspace array for performing a quarter-wave cosine transform. +- [`costi( N, workspace, strideW, offsetW )`][@stdlib/fft/base/fftpack/costi]: initialize a workspace array for performing a cosine transform. - [`decompose( N, M, initial, si, oi, out, so, oo )`][@stdlib/fft/base/fftpack/decompose]: factorize a sequence length into a product of integers. - [`rffti( N, workspace, strideW, offsetW )`][@stdlib/fft/base/fftpack/rffti]: initialize a workspace array for performing a real-valued Fourier transform. - [`sinqi( N, workspace, strideW, offsetW )`][@stdlib/fft/base/fftpack/sinqi]: initialize a workspace array for performing a quarter-wave sine transform. +- [`sinti( N, workspace, strideW, offsetW )`][@stdlib/fft/base/fftpack/sinti]: initialize a workspace array for performing a sine transform. @@ -94,12 +96,16 @@ console.log( objectKeys( ns ) ); [@stdlib/fft/base/fftpack/cosqi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/fft/base/fftpack/cosqi +[@stdlib/fft/base/fftpack/costi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/fft/base/fftpack/costi + [@stdlib/fft/base/fftpack/decompose]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/fft/base/fftpack/decompose [@stdlib/fft/base/fftpack/rffti]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/fft/base/fftpack/rffti [@stdlib/fft/base/fftpack/sinqi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/fft/base/fftpack/sinqi +[@stdlib/fft/base/fftpack/sinti]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/fft/base/fftpack/sinti + diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/README.md b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/README.md index 333fbb3a6b0c..68495efc0e52 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/README.md +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/README.md @@ -60,7 +60,7 @@ var cosineTable = workspace.slice( 0, N ); // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] var twiddleFactors = workspace.slice( 2*N, 3*N ); -// returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +// returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/benchmark/benchmark.js b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/benchmark/benchmark.js index 63182a9da54c..d8ee9c302270 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/benchmark/benchmark.js @@ -53,12 +53,12 @@ function createBenchmark( N ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { cosqi( N, workspace, 1, 0 ); - if ( isnan( workspace[ ( 2*N ) + 1 ] ) ) { + if ( isnan( workspace[ 2*N ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( workspace[ ( 2*N ) + 1 ] ) ) { + if ( isnan( workspace[ 2*N ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/repl.txt b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/repl.txt index 4f4b51a8647b..e3c7577722a8 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/repl.txt +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/repl.txt @@ -52,7 +52,7 @@ > var cosineTable = workspace.slice( 0, N ) [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] > var twiddleFactors = workspace.slice( 2*N, 3*N ) - [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] + [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] > var factors = workspace.slice( 3*N, ( 3*N ) + 4 ) [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/types/index.d.ts b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/types/index.d.ts index f7eed0a72f1c..212032236dca 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/docs/types/index.d.ts @@ -51,7 +51,7 @@ import { Collection } from '@stdlib/types/array'; * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/index.js index 41eb9cce42e6..a0b5ef720735 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/index.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/index.js @@ -40,7 +40,7 @@ * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/main.js b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/main.js index 6e36d16e3983..24d6b4da6a29 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/main.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/lib/main.js @@ -153,7 +153,7 @@ var rffti = require( '@stdlib/fft/base/fftpack/rffti' ); * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/large.json b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/large.json index 763e523a5bdf..59059ed184c3 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/large.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/large.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/medium.json b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/medium.json index 07704064ab79..7825df644a03 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/medium.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/medium.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/small.json b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/small.json index 7e5210a3a308..4e069a37b2ec 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/small.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/fixtures/c/fftpack/small.json @@ -1 +1 @@ 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+{"lengths":[15,2,13,8,15,5,4,6,13,6],"offsets":[0,15,17,30,38,53,58,62,68,81],"cosines":[0.99452189536827329,0.97814760073380569,0.95105651629515353,0.91354545764260087,0.86602540378443871,0.80901699437494745,0.74314482547739436,0.66913060635885824,0.58778525229247314,0.50000000000000011,0.40673664307580037,0.30901699437494745,0.20791169081775945,0.10452846326765368,6.123233995736766e-17,0.70710678118654757,6.123233995736766e-17,0.99270887409805397,0.97094181742605201,0.93501624268541483,0.88545602565320991,0.82298386589365646,0.74851074817110119,0.6631226582407953,0.56806474673115581,0.46472317204376862,0.35460488704253579,0.23931566428755782,0.12053668025532323,6.123233995736766e-17,0.98078528040323043,0.92387953251128674,0.83146961230254524,0.70710678118654757,0.55557023301960229,0.38268343236508984,0.19509032201612833,6.123233995736766e-17,0.99452189536827329,0.97814760073380569,0.95105651629515353,0.91354545764260087,0.86602540378443871,0.80901699437494745,0.74314482547739436,0.66913060635885824,0.58778525229247314,0.50000000000000011,0.40673664307580037,0.30901699437494745,0.20791169081775945,0.10452846326765368,6.123233995736766e-17,0.95105651629515353,0.80901699437494745,0.58778525229247314,0.30901699437494745,6.123233995736766e-17,0.92387953251128674,0.70710678118654757,0.38268343236508984,6.123233995736766e-17,0.96592582628906831,0.86602540378443871,0.70710678118654757,0.50000000000000011,0.25881904510252096,6.123233995736766e-17,0.99270887409805397,0.97094181742605201,0.93501624268541483,0.88545602565320991,0.82298386589365646,0.74851074817110119,0.6631226582407953,0.56806474673115581,0.46472317204376862,0.35460488704253579,0.23931566428755782,0.12053668025532323,6.123233995736766e-17,0.96592582628906831,0.86602540378443871,0.70710678118654757,0.50000000000000011,0.25881904510252096,6.123233995736766e-17],"twiddles":[0.91354545764260087,0.40673664307580015,0.66913060635885824,0.74314482547739424,0,0.66913060635885824,0.74314482547739424,-0.10452846326765333,0.9945218953682734,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.70710678118654757,0.70710678118654746,0,0,0,0,0,0,0.91354545764260087,0.40673664307580015,0.66913060635885824,0.74314482547739424,0,0.66913060635885824,0.74314482547739424,-0.10452846326765333,0.9945218953682734,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.50000000000000011,0.8660254037844386,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.50000000000000011,0.8660254037844386,0,0,0,0]} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/test.js b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/test.js index f76560a784ca..ba823af6d8a1 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/test.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/cosqi/test/test.js @@ -117,9 +117,9 @@ tape( 'the function correctly initializes twiddle factors (small sequence length workspace = new Float64Array( ( 3*N ) + 34 ); cosqi( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ (2*N) + i + 1 ]; + t.strictEqual( workspace[ (2*N) - 1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ (2*N) + i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -185,9 +185,9 @@ tape( 'the function correctly initializes twiddle factors (medium sequence lengt workspace = new Float64Array( ( 3*N ) + 34 ); cosqi( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ (2*N) + i + 1 ]; + t.strictEqual( workspace[ (2*N) - 1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ (2*N) + i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -253,9 +253,9 @@ tape( 'the function correctly initializes twiddle factors (large sequence length workspace = new Float64Array( ( 3*N ) + 34 ); cosqi( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ (2*N) + i + 1 ]; + t.strictEqual( workspace[ (2*N) - 1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ (2*N) + i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -307,8 +307,8 @@ tape( 'the function correctly handles stride and offset parameters', function te expected = new Float64Array( ( 3*N ) + 34 ); cosqi( N, expected, 1, 0 ); - for ( i = 0; i < N-1; i++ ) { - t.strictEqual( workspace[ offset + ( ( (2*N)+i+1 ) * stride ) ], expected[ (2*N)+i+1 ], 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + t.strictEqual( workspace[ offset + ( ( (2*N)+i ) * stride ) ], expected[ (2*N)+i ], 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/README.md b/lib/node_modules/@stdlib/fft/base/fftpack/costi/README.md new file mode 100644 index 000000000000..66a10f8c654e --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/README.md @@ -0,0 +1,173 @@ + + +# costi + +> Initialize a workspace array for performing a cosine transform. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var costi = require( '@stdlib/fft/base/fftpack/costi' ); +``` + +#### costi( N, workspace, strideW, offsetW ) + +Initializes a workspace array for performing a cosine transform. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var N = 9; +var workspace = new Float64Array( ( 3*N ) + 34 ); + +var out = costi( N, workspace, 1, 0 ); +// returns + +var bool = ( out === workspace ); +// returns true + +var cosineTable = workspace.slice( 0, N ); +// returns [ 0, ~0.765, ~1.414, ~1.848, 0, ~0.765, ~1.414, ~1.848, 0 ] + +var twiddleFactors = workspace.slice( (2*N)-1, (3*N)-2 ); +// returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] + +var factors = workspace.slice( (3*N)-2, (3*N)+2 ); +// returns [ 8, 2, 2, 4 ] +``` + +The function accepts the following arguments: + +- **N**: length of the sequence to transform. +- **workspace**: workspace array. +- **strideW**: stride length for `workspace`. +- **offsetW**: starting index for `workspace`. + +
+ + + + + +
+ +## Notes + +- The workspace array is divided into four sections: + + ```text + size = N N-1 N-1 2+ceil(log2(N-1)/2) + ↓ ↓ ↓ ↓ + | sine / cosine table | scratch / workspace | twiddle factors | radix factor table | + ↑ ↑ ↑ ↑ + i = 0 ... N ... 2N-1 ... 3N-2 ... + ``` + + - **sine/cosine table**: a table of precomputed sine/cosine coefficients used by cosine transforms. + - **scratch/workspace**: used as a scratch space when performing transforms. This section is not updated during initialization. + - **twiddle factors**: a table of reusable complex-exponential constants stored as cosine/sine pairs. + - **radix factor table**: a table containing the sequence length `N-1`, the number of factors into which `N-1` was decomposed, and the individual integer radix factors. + +- In general, a workspace array should have `3N + 34` indexed elements (as `log2(N-1)/2 ≤ 32` for all `2^64`). During initialization, only the sections for storing the cosine coefficients, twiddle factors, and the factorization of `N-1` are updated. + +- The radix factor table is comprised as follows: + + ```text + | sequence_length | number_of_factors | integer_factors | + ``` + +
+ + + +
+ +## Examples + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); +var zeroTo = require( '@stdlib/array/zero-to' ); +var logEach = require( '@stdlib/console/log-each' ); +var costi = require( '@stdlib/fft/base/fftpack/costi' ); + +var N = 9; +var workspace = new Float64Array( ( 3*N ) + 34 ); + +costi( N, workspace, 1, 0 ); +console.log( 'Sequence length: %d', N ); + +console.log( 'Sine/Cosine table:' ); +var idx = zeroTo( N, 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( 0, N ) ); + +console.log( 'Twiddle factors:' ); +idx = zeroTo( N-1, 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( (2*N)-1, (3*N)-2 ) ); + +console.log( 'Factorization:' ); +var nf = workspace[ (3*N)-1 ]; + +console.log( ' number of factors: %d', nf ); +idx = zeroTo( nf, 'generic' ); +logEach( ' factor[ %d ]: %d', idx, workspace.slice( 3*N, (3*N)+nf ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/benchmark/benchmark.js b/lib/node_modules/@stdlib/fft/base/fftpack/costi/benchmark/benchmark.js new file mode 100644 index 000000000000..10d37c7de95a --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/benchmark/benchmark.js @@ -0,0 +1,101 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var Float64Array = require( '@stdlib/array/float64' ); +var pkg = require( './../package.json' ).name; +var costi = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - sequence length +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var workspace = new Float64Array( ( 3*N ) + 34 ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + costi( N, workspace, 1, 0 ); + if ( isnan( workspace[ (2*N)-1 ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( workspace[ (2*N)-1 ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var lengths; + var N; + var f; + var i; + + lengths = [ + 9, + 17, + 33, + 65, + 129, + 257, + 513, + 1025 + ]; + + for ( i = 0; i < lengths.length; i++ ) { + N = lengths[ i ]; + f = createBenchmark( N ); + bench( format( '%s:N=%d', pkg, N ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/repl.txt b/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/repl.txt new file mode 100644 index 000000000000..65db9bb0b311 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/repl.txt @@ -0,0 +1,60 @@ + +{{alias}}( N, workspace, strideW, offsetW ) + Initializes a workspace array for performing a cosine transform. + + The workspace array is divided into four sections: + + 1. sine/cosine table: the section ranges from indices 0 to N-1 and is used + to store a table of precomputed sine and cosine coefficients used by cosine + transforms. + + 2. scratch/workspace: the section ranges from indices N to 2N-2 and is used + while performing transforms. This section is not updated during + initialization. + + 3. twiddle factors: the section ranges from indices 2N-1 to 3N-3 and stores + a table of reusable complex exponential constants as cosine/sine pairs. + + 4. radix factor table: the section starts at index 3N-2 and stores the + sequence length N-1, the number of factors into which N-1 was decomposed, + and the individual integer radix factors. + + Any remaining array space remains as unused storage. + + Parameters + ---------- + N: integer + Length of the sequence. + + workspace: ArrayLikeObject + Workspace array. + + strideW: integer + Stride length for `workspace`. + + offsetW: integer + Starting index for `workspace`. + + Returns + ------- + out: ArrayLikeObject + Workspace array. + + Examples + -------- + > var N = 9; + > var workspace = new {{alias:@stdlib/array/float64}}( ( 3*N ) + 34 ); + > var out = {{alias}}( N, workspace, 1, 0 ) + + > var bool = ( out === workspace ) + true + > var cosineTable = workspace.slice( 0, N ) + [ 0, ~0.765, ~1.414, ~1.848, 0, ~0.765, ~1.414, ~1.848, 0 ] + > var twiddleFactors = workspace.slice( (2*N)-1, (3*N)-2 ) + [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] + > var factors = workspace.slice( (3*N)-2, (3*N)+2 ) + [ 8, 2, 2, 4 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/types/index.d.ts b/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/types/index.d.ts new file mode 100644 index 000000000000..c07e61126440 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/types/index.d.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Initializes a workspace array for performing a cosine transform. +* +* ## Notes +* +* - The workspace array should have a length of at least `( 3*N ) + 34` elements. +* +* @param N - length of the sequence +* @param workspace - workspace array +* @param strideW - stride length for `workspace` +* @param offsetW - starting index for `workspace` +* @returns workspace array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var N = 9; +* var workspace = new Float64Array( ( 3*N ) + 34 ); +* +* var out = costi( N, workspace, 1, 0 ); +* // returns +* +* var bool = ( out === workspace ); +* // returns true +* +* var cosineTable = workspace.slice( 0, N ); +* // returns [ 0, ~0.765, ~1.414, ~1.848, 0, ~0.765, ~1.414, ~1.848, 0 ] +* +* var twiddleFactors = workspace.slice( (2*N)-1, (3*N)-2 ); +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] +* +* var factors = workspace.slice( (3*N)-2, (3*N)+2 ); +* // returns [ 8, 2, 2, 4 ] +*/ +declare function costi>( N: number, workspace: T, strideW: number, offsetW: number ): T; + + +// EXPORTS // + +export = costi; diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/types/test.ts b/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/types/test.ts new file mode 100644 index 000000000000..519ce5795600 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/docs/types/test.ts @@ -0,0 +1,94 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import costi = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const workspace = new Float64Array( ( 3*9 ) + 34 ); + + costi( 9, workspace, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const workspace = new Float64Array( ( 3*9 ) + 34 ); + + costi( '9', workspace, 1, 0 ); // $ExpectError + costi( true, workspace, 1, 0 ); // $ExpectError + costi( false, workspace, 1, 0 ); // $ExpectError + costi( null, workspace, 1, 0 ); // $ExpectError + costi( void 0, workspace, 1, 0 ); // $ExpectError + costi( [], workspace, 1, 0 ); // $ExpectError + costi( {}, workspace, 1, 0 ); // $ExpectError + costi( ( x: number ): number => x, workspace, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + costi( 9, '50', 1, 0 ); // $ExpectError + costi( 9, 50, 1, 0 ); // $ExpectError + costi( 9, true, 1, 0 ); // $ExpectError + costi( 9, false, 1, 0 ); // $ExpectError + costi( 9, null, 1, 0 ); // $ExpectError + costi( 9, void 0, 1, 0 ); // $ExpectError + costi( 9, {}, 1, 0 ); // $ExpectError + costi( 9, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const workspace = new Float64Array( ( 3*9 ) + 34 ); + + costi( 9, workspace, '1', 0 ); // $ExpectError + costi( 9, workspace, true, 0 ); // $ExpectError + costi( 9, workspace, false, 0 ); // $ExpectError + costi( 9, workspace, null, 0 ); // $ExpectError + costi( 9, workspace, void 0, 0 ); // $ExpectError + costi( 9, workspace, [], 0 ); // $ExpectError + costi( 9, workspace, {}, 0 ); // $ExpectError + costi( 9, workspace, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const workspace = new Float64Array( ( 3*9 ) + 34 ); + + costi( 9, workspace, 1, '0' ); // $ExpectError + costi( 9, workspace, 1, true ); // $ExpectError + costi( 9, workspace, 1, false ); // $ExpectError + costi( 9, workspace, 1, null ); // $ExpectError + costi( 9, workspace, 1, void 0 ); // $ExpectError + costi( 9, workspace, 1, [] ); // $ExpectError + costi( 9, workspace, 1, {} ); // $ExpectError + costi( 9, workspace, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const workspace = new Float64Array( ( 3*9 ) + 34 ); + + costi(); // $ExpectError + costi( 9 ); // $ExpectError + costi( 9, workspace ); // $ExpectError + costi( 9, workspace, 1 ); // $ExpectError + costi( 9, workspace, 1, 0, 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/examples/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/costi/examples/index.js new file mode 100644 index 000000000000..355a9b5e8e24 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Float64Array = require( '@stdlib/array/float64' ); +var zeroTo = require( '@stdlib/array/zero-to' ); +var logEach = require( '@stdlib/console/log-each' ); +var costi = require( './../lib' ); + +var N = 9; +var workspace = new Float64Array( ( 3*N ) + 34 ); + +costi( N, workspace, 1, 0 ); +console.log( 'Sequence length: %d', N ); + +console.log( 'Sine/Cosine table:' ); +var idx = zeroTo( N, 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( 0, N ) ); + +console.log( 'Twiddle factors:' ); +idx = zeroTo( N-1, 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( (2*N)-1, (3*N)-2 ) ); + +console.log( 'Factorization:' ); +var nf = workspace[ (3*N)-1 ]; + +console.log( ' number of factors: %d', nf ); +idx = zeroTo( nf, 'generic' ); +logEach( ' factor[ %d ]: %d', idx, workspace.slice( 3*N, (3*N)+nf ) ); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/lib/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/costi/lib/index.js new file mode 100644 index 000000000000..161842e74fa3 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/lib/index.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Initialize a workspace array for performing a cosine transform. +* +* @module @stdlib/fft/base/fftpack/costi +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var costi = require( '@stdlib/fft/base/fftpack/costi' ); +* +* var N = 9; +* var workspace = new Float64Array( ( 3*N ) + 34 ); +* +* var out = costi( N, workspace, 1, 0 ); +* // returns +* +* var bool = ( out === workspace ); +* // returns true +* +* var cosineTable = workspace.slice( 0, N ); +* // returns [ 0, ~0.765, ~1.414, ~1.848, 0, ~0.765, ~1.414, ~1.848, 0 ] +* +* var twiddleFactors = workspace.slice( (2*N)-1, (3*N)-2 ); +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] +* +* var factors = workspace.slice( (3*N)-2, (3*N)+2 ); +* // returns [ 8, 2, 2, 4 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/lib/main.js b/lib/node_modules/@stdlib/fft/base/fftpack/costi/lib/main.js new file mode 100644 index 000000000000..7c289635ee44 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/lib/main.js @@ -0,0 +1,210 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The original C code and copyright notice are from the [PFFFT library]{@link https://github.com/marton78/pffft/blob/0b4ee12c4ba45a4a8e567550c16d96d1679f50ce/src/fftpack.c}. The implementation follows the original, but has been modified for JavaScript. +* +* ```text +* Copyright (c) 2004 the University Corporation for Atmospheric +* Research ("UCAR"). All rights reserved. Developed by NCAR's +* Computational and Information Systems Laboratory, UCAR, +* www.cisl.ucar.edu. +* +* Redistribution and use of the Software in source and binary forms, +* with or without modification, is permitted provided that the +* following conditions are met: +* +* - Neither the names of NCAR's Computational and Information Systems +* Laboratory, the University Corporation for Atmospheric Research, +* nor the names of its sponsors or contributors may be used to +* endorse or promote products derived from this Software without +* specific prior written permission. +* +* - Redistributions of source code must retain the above copyright +* notices, this list of conditions, and the disclaimer below. +* +* - Redistributions in binary form must reproduce the above copyright +* notice, this list of conditions, and the disclaimer below in the +* documentation and/or other materials provided with the +* distribution. +* +* THIS SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +* EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO THE WARRANTIES OF +* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +* NONINFRINGEMENT. IN NO EVENT SHALL THE CONTRIBUTORS OR COPYRIGHT +* HOLDERS BE LIABLE FOR ANY CLAIM, INDIRECT, INCIDENTAL, SPECIAL, +* EXEMPLARY, OR CONSEQUENTIAL DAMAGES OR OTHER LIABILITY, WHETHER IN AN +* ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN +* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS WITH THE +* SOFTWARE. +* ``` +*/ + +'use strict'; + +// MODULES // + +var sincos = require( '@stdlib/math/base/special/sincos' ).assign; +var PI = require( '@stdlib/constants/float64/pi' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var rffti = require( '@stdlib/fft/base/fftpack/rffti' ); + + +// VARIABLES // + +// Reusable buffer for storing computed sine and cosine values: +var SINCOS_WORKSPACE = [ 0.0, 0.0 ]; + + +// MAIN // + +/** +* Initializes a workspace array for performing a cosine transform. +* +* ## Notes +* +* The workspace array is divided into four sections: +* +* ```text +* size = N N-1 N-1 2+ceil(log2(N-1)/2) +* ↓ ↓ ↓ ↓ +* | sine/cosine table | scratch/workspace | twiddle factors | radix factor table | +* ↑ ↑ ↑ ↑ +* i = 0 ... N ... 2N-1 ... 3N-2 ... +* ``` +* +* where +* +* - **sine/cosine table**: a table of precomputed sine/cosine coefficients used by cosine transforms. +* - **scratch/workspace**: used as a scratch space when performing transforms. This section is not updated during initialization. +* - **twiddle factors**: a table of reusable complex-exponential constants stored as cosine/sine pairs. +* - **radix factor table**: a table containing the radix factorization of `N-1`. +* +* In general, a workspace array should have `3N + 34` indexed elements (as `log2(N-1)/2 ≤ 32` for all `2^64`). During initialization, only the sections for storing the sine/cosine coefficients, twiddle factors, and the factorization of `N-1` are updated. +* +* > Note: FFTPACK only requires `3N+15`, but we increase that number here to accommodate larger workspace arrays, where `N` may exceed `2^30` indexed elements. +* +* The factorization section is comprised as follows: +* +* ```text +* | sequence_length | number_of_factors | integer_factors | +* ``` +* +* The sequence length and number of factors (`nf`) comprise a single element each. Only the first `nf` elements in the integer factors section are written to, with the rest being unused. +* +* As for twiddle factors, these are small, reusable complex-exponential constants that appear inside each "butterfly" stage of a Cooley–Tukey–style FFT. Every arithmetic step in an FFT multiplies one intermediate value by some +* +* ```tex +* W_N^k +* ``` +* +* where `W_N^k` is an N-th root of unity. Formally, in a forward FFT, +* +* ```tex +* W_N^k = e^{-2\pi ik/N} +* ``` +* +* In a backward FFT, +* +* ```tex +* W_N^k = e^{+2\pi ik/N} +* ``` +* +* As may be observed, `W_N^k` for forward and backward FFTs is the same, except the sign of the exponent is flipped. As a consequence, both forward and backward FFT callers can reuse the same set of twiddle factors, with those performing a forward transform multiplying with `(cos,-sin)` and those performing a backward transform multiplying with `(cos,+sin)`. +* +* Because these constants only depend on the transform length `N` (and **not** on the input data), we can pre-compute and store them once, then "twiddle" them (i.e., reuse them with different indices) as we proceed through the factorization. +* +* > As a quick aside regarding the name "twiddle", early FFT papers (notably Gentleman & Sande, 1966) described how you "twiddle" one branch of each butterfly by a complex rotation before adding/subtracting. The coefficients themselves inherited the nickname "twiddle factors," and the term stuck. +* +* By reusing the workspace array when computing multiple transforms of the same length `N`, every subsequent `*f` (forward) or `*b` (backward) call can simply look up the pre-stored twiddle factors instead of recomputing sine and cosine on-the-fly. +* +* In short, twiddle factors are cached roots of unity that allow each stage of the algorithm to rotate data quickly and predictably. +* +* During initialization, `costi` first writes the sine/cosine table, and then initializes the remaining three sections using `rffti`. +* +* @param {PositiveInteger} N - length of the sequence to transform +* @param {Collection} workspace - workspace array +* @param {integer} strideW - stride length for `workspace` +* @param {NonNegativeInteger} offsetW - starting index for `workspace` +* @returns {Collection} workspace array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var N = 9; +* var workspace = new Float64Array( ( 3*N ) + 34 ); +* +* var out = costi( N, workspace, 1, 0 ); +* // returns +* +* var bool = ( out === workspace ); +* // returns true +* +* var cosineTable = workspace.slice( 0, N ); +* // returns [ 0, ~0.765, ~1.414, ~1.848, 0, ~0.765, ~1.414, ~1.848, 0 ] +* +* var twiddleFactors = workspace.slice( (2*N)-1, (3*N)-2 ); +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] +* +* var factors = workspace.slice( (3*N)-2, (3*N)+2 ); +* // returns [ 8, 2, 2, 4 ] +*/ +function costi( N, workspace, strideW, offsetW ) { + var offsetR; + var ns2; + var iwc; + var iws; + var dt; + var fk; + var i; + + if ( N <= 3 ) { + return workspace; + } + // Compute the number of sine/cosine pairs to store: + ns2 = floor( N / 2 ); + + // Compute the angular increment: + dt = PI / ( N - 1 ); + + // Compute and store the sine/cosine table: + fk = 0.0; + iws = offsetW + strideW; + iwc = offsetW + ( (N-2)*strideW ); + for ( i = 1; i < ns2; i++ ) { + fk += 1.0; + sincos( fk*dt, SINCOS_WORKSPACE, 1, 0 ); + workspace[ iws ] = SINCOS_WORKSPACE[ 0 ] * 2.0; + workspace[ iwc ] = SINCOS_WORKSPACE[ 1 ] * 2.0; + iws += strideW; + iwc -= strideW; + } + // Resolve the starting index for the `rffti` workspace: + offsetR = offsetW + ( N*strideW ); + + // Initialize the real FFT workspace for a sequence of length N-1: + rffti( N-1, workspace, strideW, offsetR ); + + return workspace; +} + + +// EXPORTS // + +module.exports = costi; diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/package.json b/lib/node_modules/@stdlib/fft/base/fftpack/costi/package.json new file mode 100644 index 000000000000..eae44f1cec64 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/package.json @@ -0,0 +1,64 @@ +{ + "name": "@stdlib/fft/base/fftpack/costi", + "version": "0.0.0", + "description": "Initialize a workspace array for performing a cosine transform.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "fft", + "fftpack", + "costi", + "fourier", + "transform", + "twiddle", + "workspace", + "initialization", + "cosine" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/Makefile b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/Makefile new file mode 100644 index 000000000000..7ce16281940d --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/Makefile @@ -0,0 +1,137 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +endif + +# Specify the path to FFTPACK: +FFTPACK ?= + +# Specify a list of FFTPACK source files: +FFTPACK_SRC ?= + +# Determine the OS: +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate [position independent code][1]: +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of C targets: +c_targets := runner.out + + +# RULES # + +#/ +# Compiles C source files. +# +# @param {string} [C_COMPILER] - C compiler +# @param {string} [CFLAGS] - C compiler flags +# @param {(string|void)} [fPIC] - flag indicating whether to generate position independent code +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler +# @param {string} CFLAGS - C compiler flags +# @param {(string|void)} fPIC - flag indicating whether to generate position independent code +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) -DFFTPACK_DOUBLE_PRECISION $(fPIC) -o $@ $(FFTPACK_SRC) $< -lm + +#/ +# Generates test fixtures. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean + +#/ +# Removes generated test fixtures. +# +# @example +# make clean-fixtures +#/ +clean-fixtures: + $(QUIET) -rm -f *.json + +.PHONY: clean-fixtures diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/large.json b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/large.json new file mode 100644 index 000000000000..3f6163310f81 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/large.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/medium.json b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/medium.json new file mode 100644 index 000000000000..defc24a0cdda --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/medium.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/runner.c b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/runner.c new file mode 100644 index 000000000000..92ab037366e8 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/runner.c @@ -0,0 +1,304 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/** +* Generate FFTPACK test fixtures. +* +* ## Notes +* +* - Run this script from the directory in which fixtures should be written. +* +*/ + +#include +#include +#include + +/** +* Define prototypes for external functions. +*/ +extern void costi( int n, double *wsave ); + +/** +* Generates a random number on the interval [0,1]. +* +* @return random number +*/ +double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Generates an array of pseudorandom integers drawn from a uniform distribution. +* +* ## Notes +* +* - WARNING: the method used here is not particularly robust, as some integer values may be sampled more frequently than others. +* +* +* @param out output array +* @param len array length +* @param a lower bound (inclusive) +* @param b upper bound (exclusive) +*/ +void rand_array_i32( int *out, const unsigned int len, const int a, const int b ) { + unsigned int i; + unsigned int r; + double delta; + + delta = (double)b - (double)a; + + for ( i = 0; i < len; i++ ) { + r = (unsigned int)( delta * rand_double() ); // truncation + out[ i ] = (int)( a + r ); + } +} + +/** +* Writes an array of doubles to a file as a series of comma-separated values. +* +* @param f file to write to +* @param x array of doubles +* @param len array length +*/ +void write_array_f64( FILE *f, const double *x, const unsigned int len ) { + unsigned int i; + + for ( i = 0; i < len; i++ ) { + fprintf( f, "%.17g", x[ i ] ); + if ( i < len-1 ) { + fprintf( f, "," ); + } + } +} + +/** +* Writes an array of integers to a file as a series of comma-separated values. +* +* @param f file to write to +* @param x array of integers +* @param len array length +*/ +void write_array_i32( FILE *f, const int *x, const unsigned int len ) { + unsigned int i; + + for ( i = 0; i < len; i++ ) { + fprintf( f, "%d", x[ i ] ); + if ( i < len-1 ) { + fprintf( f, "," ); + } + } +} + +/** +* Writes a named array of doubles to a file as JSON. +* +* @param f file to write to +* @param name array name +* @param x data +* @param len array length +*/ +void write_named_array_f64( FILE *f, const char *name, const double *x, const unsigned int len ) { + fprintf( f, "\"%s\":[", name ); + write_array_f64( f, x, len ); + fprintf( f, "]" ); +} + +/** +* Writes a named array of integers to a file as JSON. +* +* @param f file to write to +* @param name array name +* @param x data +* @param len array length +*/ +void write_named_array_i32( FILE *f, const char *name, const int *x, const unsigned int len ) { + fprintf( f, "\"%s\":[", name ); + write_array_i32( f, x, len ); + fprintf( f, "]" ); +} + +/** +* Writes data to a file as JSON. +* +* ## Notes +* +* - This function SHOULD be tailored to the input data (e.g., input types, output types, number of arguments, etc) and may vary from use case to use case. +* +* +* @param f file to write to +* @param lengths sequence lengths +* @param offsets cosine and twiddle offsets +* @param cosines cosine values +* @param twiddles twiddle factors +* @param num number of sequence lengths +* @param total total number of cosine and twiddle values +*/ +void write_data_as_json( FILE *f, const int *lengths, const int *offsets, const double *cosines, const double *twiddles, const unsigned int num, const unsigned int total ) { + fprintf( f, "{" ); + write_named_array_i32( f, "lengths", lengths, num ); + fprintf( f, "," ); + write_named_array_i32( f, "offsets", offsets, num ); + fprintf( f, "," ); + write_named_array_f64( f, "cosines", cosines, total ); + fprintf( f, "," ); + write_named_array_f64( f, "twiddles", twiddles, total ); + fprintf( f, "}\n" ); +} + +/** +* Generates test fixtures. +* +* @param lengths sequence lengths +* @param offsets cosine and twiddle offsets into flat output array +* @param num number of sequence lengths +* @param total total number of cosine and twiddle values +* @param name output filename +*/ +void generate( const int *lengths, const int *offsets, const unsigned int num, const unsigned int total, const char *name ) { + double *twiddles; + double *cosines; + unsigned int i; + unsigned int j; + double *wsave; + FILE *f; + int off; + int n; + + // Allocate an output array for cosine values: + cosines = (double*) malloc( total * sizeof(double) ); + if ( cosines == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Allocate an output array for twiddle factors: + twiddles = (double*) malloc( total * sizeof(double) ); + if ( twiddles == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Generate fixture data: + for ( i = 0; i < num; i++ ) { + n = lengths[ i ]; + wsave = (double*) calloc( 3*n + 15, sizeof(double) ); + if ( wsave == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + costi( n, wsave ); + + // Copy cosine region into flat array (N values starting at wsave[0]): + off = offsets[ i ]; + for ( j = 0; j < (unsigned int)n; j++ ) { + cosines[ off + j ] = wsave[ j ]; + } + + // Copy twiddle region into flat array (N-1 values starting at wsave[(2*n)-1]): + off = offsets[ i ]; + for ( j = 0; j < (unsigned int)( n - 1 ); j++ ) { + twiddles[ off + j ] = wsave[ ( 2*n ) - 1 + j ]; + } + free( wsave ); + } + // Open a new file: + f = fopen( name, "w" ); + if ( f == NULL ) { + printf( "Error opening file.\n" ); + exit( 1 ); + } + + // Write data as JSON: + write_data_as_json( f, lengths, offsets, cosines, twiddles, num, total ); + + // Close the file: + fclose( f ); + + // Free allocated memory: + free( cosines ); + free( twiddles ); +} + +/** +* Computes offsets into flat cosine and twiddle arrays for each sequence length. +* +* @param offsets output array of offsets +* @param lengths sequence lengths +* @param num number of sequence lengths +* @return total number of cosine and twiddle values +*/ +unsigned int compute_offsets( int *offsets, const int *lengths, const unsigned int num ) { + unsigned int total; + unsigned int i; + + total = 0; + for ( i = 0; i < num; i++ ) { + offsets[ i ] = total; + total += lengths[ i ]; + } + return total; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + unsigned int total; + unsigned int num; + int *lengths; + int *offsets; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + // Define the number of sequence lengths per range: + num = 10; + + // Allocate arrays: + lengths = (int*) malloc( num * sizeof(int) ); + if ( lengths == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + offsets = (int*) malloc( num * sizeof(int) ); + if ( offsets == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Generate fixture data: + rand_array_i32( lengths, num, 2, 16 ); + total = compute_offsets( offsets, lengths, num ); + generate( lengths, offsets, num, total, "small.json" ); + + rand_array_i32( lengths, num, 16, 128 ); + total = compute_offsets( offsets, lengths, num ); + generate( lengths, offsets, num, total, "medium.json" ); + + rand_array_i32( lengths, num, 128, 1024 ); + total = compute_offsets( offsets, lengths, num ); + generate( lengths, offsets, num, total, "large.json" ); + + // Free allocated memory: + free( lengths ); + free( offsets ); + + return 0; +} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/small.json b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/small.json new file mode 100644 index 000000000000..03372bfa74b5 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/fixtures/c/fftpack/small.json @@ -0,0 +1 @@ +{"lengths":[9,2,8,7,12,11,2,4,10,12],"offsets":[0,9,11,19,26,38,49,51,55,65],"cosines":[0,0.76536686473017956,1.4142135623730949,1.8477590650225735,0,0.76536686473017967,1.4142135623730951,1.8477590650225735,0,0,0,0,0.86776747823511624,1.5636629649360596,1.9498558243636472,0.4450418679126289,1.2469796037174672,1.8019377358048383,0,0,0.99999999999999989,1.7320508075688772,0,1.0000000000000002,1.7320508075688774,0,0,0.56346511368285934,1.0812816349111951,1.5114991487085165,1.8192639907090367,1.9796428837618654,0.28462967654657023,0.83083002600377287,1.3097214678905702,1.6825070656623624,1.9189859472289947,0,0,0.61803398874989479,1.1755705045849463,1.6180339887498949,1.9021130325903071,0,0.6180339887498949,1.1755705045849463,1.6180339887498949,1.9021130325903071,0,0,0,0,1.7320508075688772,1.0000000000000002,0,0,0.68404028665133743,1.2855752193730785,1.7320508075688772,1.969615506024416,0.34729635533386083,1.0000000000000002,1.532088886237956,1.8793852415718169,0,0,0.56346511368285934,1.0812816349111951,1.5114991487085165,1.8192639907090367,1.9796428837618654,0.28462967654657023,0.83083002600377287,1.3097214678905702,1.6825070656623624,1.9189859472289947,0],"twiddles":[0.70710678118654757,0.70710678118654746,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.50000000000000011,0.8660254037844386,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.80901699437494745,0.58778525229247314,0.30901699437494745,0.95105651629515353,0,0,0,0,0,0,0,0,0,0,0,0,0,0.76604444311897801,0.64278760968653925,0,0.17364817766693041,0.98480775301220802,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/test.js b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/test.js new file mode 100644 index 000000000000..0602234a1a93 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/costi/test/test.js @@ -0,0 +1,314 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var costi = require( './../lib' ); + + +// FIXTURES // + +var small = require( './fixtures/c/fftpack/small.json' ); +var medium = require( './fixtures/c/fftpack/medium.json' ); +var large = require( './fixtures/c/fftpack/large.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof costi, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( costi.length, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the workspace array', function test( t ) { + var workspace; + var out; + var N; + + N = 8; + workspace = new Float64Array( ( 3*N ) + 34 ); + out = costi( N, workspace, 1, 0 ); + + t.strictEqual( out, workspace, 'same reference' ); + t.end(); +}); + +tape( 'the function correctly initializes sine and cosine values (small sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = small.lengths; + offsets = small.offsets; + expected = small.cosines; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + workspace = new Float64Array( ( 3*N ) + 34 ); + costi( N, workspace, 1, 0 ); + + t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes twiddle factors (small sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = small.lengths; + offsets = small.offsets; + expected = small.twiddles; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + workspace = new Float64Array( ( 3*N ) + 34 ); + costi( N, workspace, 1, 0 ); + + t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); + for ( i = 0; i < N-1; i++ ) { + y = workspace[ (2*N) - 1 + i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes sine and cosine values (medium sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = medium.lengths; + offsets = medium.offsets; + expected = medium.cosines; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + workspace = new Float64Array( ( 3*N ) + 34 ); + costi( N, workspace, 1, 0 ); + + t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes twiddle factors (medium sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = medium.lengths; + offsets = medium.offsets; + expected = medium.twiddles; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + workspace = new Float64Array( ( 3*N ) + 34 ); + costi( N, workspace, 1, 0 ); + + t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); + for ( i = 0; i < N-1; i++ ) { + y = workspace[ (2*N) - 1 + i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes sine and cosine values (large sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = large.lengths; + offsets = large.offsets; + expected = large.cosines; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + workspace = new Float64Array( ( 3*N ) + 34 ); + costi( N, workspace, 1, 0 ); + + t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes twiddle factors (large sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = large.lengths; + offsets = large.offsets; + expected = large.twiddles; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + workspace = new Float64Array( ( 3*N ) + 34 ); + costi( N, workspace, 1, 0 ); + + t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); + for ( i = 0; i < N-1; i++ ) { + y = workspace[ (2*N) - 1 + i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function does not modify the scratch region of the workspace', function test( t ) { + var workspace; + var N; + var i; + + N = 8; + workspace = new Float64Array( ( 3*N ) + 34 ); + + for ( i = 0; i < workspace.length; i++ ) { + workspace[ i ] = i + 1.0; + } + costi( N, workspace, 1, 0 ); + for ( i = N; i < (2*N) - 1; i++ ) { + t.strictEqual( workspace[ i ], i + 1.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function correctly handles stride and offset parameters', function test( t ) { + var workspace; + var expected; + var stride; + var offset; + var nf; + var N; + var i; + + N = 9; + stride = 2; + offset = 3; + workspace = new Float64Array( offset + ( ( ( 3*N ) + 34 ) * stride ) ); + + costi( N, workspace, stride, offset ); + + t.strictEqual( workspace[ offset + ( ( (3*N)-2 ) * stride ) ], N-1, 'returns expected value' ); + + nf = workspace[ offset + ( ( (3*N)-1 ) * stride ) ]; + t.strictEqual( nf, 2, 'returns expected value' ); + t.strictEqual( workspace[ offset + ( ( 3*N ) * stride ) ], 2, 'returns expected value' ); + t.strictEqual( workspace[ offset + ( ( (3*N)+1 ) * stride ) ], 4, 'returns expected value' ); + + expected = new Float64Array( ( 3*N ) + 34 ); + costi( N, expected, 1, 0 ); + + for ( i = 0; i < N-1; i++ ) { + t.strictEqual( workspace[ offset + ( ( (2*N)-1+i ) * stride ) ], expected[ (2*N)-1+i ], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/docs/types/index.d.ts b/lib/node_modules/@stdlib/fft/base/fftpack/docs/types/index.d.ts index 489f138b7da4..a628f4d39fce 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/fft/base/fftpack/docs/types/index.d.ts @@ -22,9 +22,11 @@ import cffti = require( '@stdlib/fft/base/fftpack/cffti' ); import cosqi = require( '@stdlib/fft/base/fftpack/cosqi' ); +import costi = require( '@stdlib/fft/base/fftpack/costi' ); import decompose = require( '@stdlib/fft/base/fftpack/decompose' ); import rffti = require( '@stdlib/fft/base/fftpack/rffti' ); import sinqi = require( '@stdlib/fft/base/fftpack/sinqi' ); +import sinti = require( '@stdlib/fft/base/fftpack/sinti' ); /** * Interface describing the `fftpack` namespace. @@ -93,13 +95,49 @@ interface Namespace { * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); - * // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] + * // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] */ cosqi: typeof cosqi; + /** + * Initializes a workspace array for performing a cosine transform. + * + * ## Notes + * + * - The workspace array should have a length of at least `( 3*N ) + 34` elements. + * + * @param N - length of the sequence + * @param workspace - workspace array + * @param strideW - stride length for `workspace` + * @param offsetW - starting index for `workspace` + * @returns workspace array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * + * var N = 9; + * var workspace = new Float64Array( ( 3*N ) + 34 ); + * + * var out = ns.costi( N, workspace, 1, 0 ); + * // returns + * + * var bool = ( out === workspace ); + * // returns true + * + * var cosineTable = workspace.slice( 0, N ); + * // returns [ 0, ~0.765, ~1.414, ~1.848, 0, ~0.765, ~1.414, ~1.848, 0 ] + * + * var twiddleFactors = workspace.slice( (2*N)-1, (3*N)-2 ); + * // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] + * + * var factors = workspace.slice( (3*N)-2, (3*N)+2 ); + * // returns [ 8, 2, 2, 4 ] + */ + costi: typeof costi; + /** * Factorizes a sequence length into a product of integers. * @@ -149,7 +187,7 @@ interface Namespace { * // returns true * * var twiddleFactors = workspace.slice( N, 2*N ); - * // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] + * // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 2*N, ( 2*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] @@ -185,12 +223,49 @@ interface Namespace { * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); - * // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] + * // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] */ sinqi: typeof sinqi; + + /** + * Initializes a workspace array for performing a sine transform. + * + * ## Notes + * + * - The workspace array should have a length of at least `( 2.5*N ) + 34` elements. + * + * @param N - length of the sequence + * @param workspace - workspace array + * @param strideW - stride length for `workspace` + * @param offsetW - starting index for `workspace` + * @returns workspace array + * + * @example + * var Float64Array = require( '@stdlib/array/float64' ); + * var floor = require( '@stdlib/math/base/special/floor' ); + * + * var N = 7; + * var workspace = new Float64Array( floor( 2.5*N ) + 34 ); + * + * var out = ns.sinti( N, workspace, 1, 0 ); + * // returns + * + * var bool = ( out === workspace ); + * // returns true + * + * var sineTable = workspace.slice( 0, floor( N/2 ) ); + * // returns [ ~0.765, ~1.414, ~1.848 ] + * + * var twiddleFactors = workspace.slice( floor( 3*N/2 ) + 1, floor( 5*N/2 ) + 2 ); + * // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] + * + * var factors = workspace.slice( floor( 5*N/2 ) + 2, floor( 5*N/2 ) + 2 + 4 ); + * // returns [ 8, 2, 2, 4 ] + */ + sinti: typeof sinti; } /** diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/lib/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/lib/index.js index 179b47fcacbe..0c5488fd1d9d 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/lib/index.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/lib/index.js @@ -58,6 +58,15 @@ setReadOnly( ns, 'cffti', require( '@stdlib/fft/base/fftpack/cffti' ) ); */ setReadOnly( ns, 'cosqi', require( '@stdlib/fft/base/fftpack/cosqi' ) ); +/** +* @name costi +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/fft/base/fftpack/costi} +*/ +setReadOnly( ns, 'costi', require( '@stdlib/fft/base/fftpack/costi' ) ); + /** * @name decompose * @memberof ns @@ -85,6 +94,15 @@ setReadOnly( ns, 'rffti', require( '@stdlib/fft/base/fftpack/rffti' ) ); */ setReadOnly( ns, 'sinqi', require( '@stdlib/fft/base/fftpack/sinqi' ) ); +/** +* @name sinti +* @memberof ns +* @readonly +* @type {Function} +* @see {@link module:@stdlib/fft/base/fftpack/sinti} +*/ +setReadOnly( ns, 'sinti', require( '@stdlib/fft/base/fftpack/sinti' ) ); + // EXPORTS // diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/README.md b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/README.md index a3a7c1a21138..e5228324e714 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/README.md +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/README.md @@ -57,7 +57,7 @@ var bool = ( out === workspace ); // returns true var twiddleFactors = workspace.slice( N, 2*N ); -// returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +// returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] var factors = workspace.slice( 2*N, ( 2*N ) + 4 ); // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/benchmark/benchmark.js b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/benchmark/benchmark.js index 07feddfa216b..b2f4afc682ca 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/benchmark/benchmark.js @@ -53,12 +53,12 @@ function createBenchmark( N ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { rffti( N, workspace, 1, 0 ); - if ( isnan( workspace[ N+1 ] ) ) { + if ( isnan( workspace[ N ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( workspace[ N+1 ] ) ) { + if ( isnan( workspace[ N ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/repl.txt b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/repl.txt index 92606b3192fa..8edb96270359 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/repl.txt +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/repl.txt @@ -46,7 +46,7 @@ > var bool = ( out === workspace ) true > var twiddleFactors = workspace.slice( N, 2*N ) - [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] + [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] > var factors = workspace.slice( 2*N, ( 2*N ) + 4 ) [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/types/index.d.ts b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/types/index.d.ts index 4083a9a87d20..94af8df9504d 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/docs/types/index.d.ts @@ -49,7 +49,7 @@ import { Collection } from '@stdlib/types/array'; * // returns true * * var twiddleFactors = workspace.slice( N, 2*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 2*N, ( 2*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/index.js index 51c16c7bcb35..b927441e8dcf 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/index.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/index.js @@ -37,7 +37,7 @@ * // returns true * * var twiddleFactors = workspace.slice( N, 2*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 2*N, ( 2*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/main.js b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/main.js index ba81b6c219a1..1b045b91a18c 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/main.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/main.js @@ -147,7 +147,7 @@ var rffti1 = require( './rffti1.js' ); * // returns true * * var twiddleFactors = workspace.slice( N, 2*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 2*N, ( 2*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/rffti1.js b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/rffti1.js index 9d4c242a83ac..ba401e085efc 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/rffti1.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/lib/rffti1.js @@ -116,7 +116,7 @@ function rffti1( N, twiddles, strideT, offsetT, factors, strideF, offsetF ) { argh = TWO_PI / N; // Define the location of the first sine term we want to compute: - im = 2; + im = 1; // Initialize a running product of factors already processed: l1 = 1; diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/large.json b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/large.json index 01ea1093cdc9..f8983602724c 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/large.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/large.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/medium.json b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/medium.json index 9426aa08c1c5..92bc8b5c15e7 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/medium.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/medium.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/runner.c b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/runner.c index 6f783f0bf820..ee9a53000bd4 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/runner.c +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/runner.c @@ -194,9 +194,9 @@ void generate( const int *lengths, const int *offsets, const unsigned int num, c } rffti( n, wsave ); - // Copy twiddle region into flat array (N-1 values starting at wsave[n]): + // Copy twiddle region into flat array (N values starting at wsave[n]): off = offsets[ i ]; - for ( j = 0; j < (unsigned int)( n - 1 ); j++ ) { + for ( j = 0; j < (unsigned int)n; j++ ) { twiddles[ off + j ] = wsave[ n + j ]; } free( wsave ); @@ -233,7 +233,7 @@ unsigned int compute_offsets( int *offsets, const int *lengths, const unsigned i total = 0; for ( i = 0; i < num; i++ ) { offsets[ i ] = total; - total += lengths[ i ] - 1; + total += lengths[ i ]; } return total; } diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/small.json b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/small.json index fbf7013f13bc..843a8a90f932 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/small.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/fixtures/c/fftpack/small.json @@ -1 +1 @@ -{"lengths":[13,13,12,9,14,4,5,5,15,11],"offsets":[0,12,24,35,43,56,59,63,67,81],"twiddles":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.86602540378443871,0.49999999999999994,0,0.50000000000000011,0.8660254037844386,0,6.123233995736766e-17,1,0,0,0,0.76604444311897801,0.64278760968653925,0,0.17364817766693041,0.98480775301220802,0,0,0,0.90096886790241915,0.43388373911755812,0.62348980185873359,0.7818314824680298,0.22252093395631445,0.97492791218182362,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.91354545764260087,0.40673664307580015,0.66913060635885824,0.74314482547739424,0,0.66913060635885824,0.74314482547739424,-0.10452846326765333,0.9945218953682734,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]} +{"lengths":[11,10,14,12,10,13,11,3,12,7],"offsets":[0,11,21,35,47,57,70,81,84,96],"twiddles":[0,0,0,0,0,0,0,0,0,0,0,0.80901699437494745,0.58778525229247314,0.30901699437494745,0.95105651629515353,0,0,0,0,0,0,0.90096886790241915,0.43388373911755812,0.62348980185873359,0.7818314824680298,0.22252093395631445,0.97492791218182362,0,0,0,0,0,0,0,0,0.86602540378443871,0.49999999999999994,0,0.50000000000000011,0.8660254037844386,0,6.123233995736766e-17,1,0,0,0,0,0.80901699437494745,0.58778525229247314,0.30901699437494745,0.95105651629515353,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.86602540378443871,0.49999999999999994,0,0.50000000000000011,0.8660254037844386,0,6.123233995736766e-17,1,0,0,0,0,0,0,0,0,0,0,0]} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/test.js b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/test.js index 8173a6ee269a..dbb843b8ba34 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/test.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/rffti/test/test.js @@ -83,9 +83,9 @@ tape( 'the function correctly initializes twiddle factors (small sequence length workspace = new Float64Array( ( 2*N ) + 34 ); rffti( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ N+i+1 ]; + t.strictEqual( workspace[ N-1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ N+i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -117,9 +117,9 @@ tape( 'the function correctly initializes twiddle factors (medium sequence lengt workspace = new Float64Array( ( 2*N ) + 34 ); rffti( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ N+i+1 ]; + t.strictEqual( workspace[ N-1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ N+i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -151,9 +151,9 @@ tape( 'the function correctly initializes twiddle factors (large sequence length workspace = new Float64Array( ( 2*N ) + 34 ); rffti( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ N+i+1 ]; + t.strictEqual( workspace[ N-1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ N+i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -224,8 +224,8 @@ tape( 'the function correctly handles stride and offset parameters', function te expected = new Float64Array( ( 2*N ) + 34 ); rffti( N, expected, 1, 0 ); - for ( i = 0; i < N-1; i++ ) { - t.strictEqual( workspace[ offset + ( ( N+i+1 ) * stride ) ], expected[ N+i+1 ], 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + t.strictEqual( workspace[ offset + ( ( N+i ) * stride ) ], expected[ N+i ], 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/README.md b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/README.md index 6a122b979129..7b08061e0f11 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/README.md +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/README.md @@ -60,7 +60,7 @@ var cosineTable = workspace.slice( 0, N ); // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] var twiddleFactors = workspace.slice( 2*N, 3*N ); -// returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +// returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/benchmark/benchmark.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/benchmark/benchmark.js index 859a68244c81..6eca980065f6 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/benchmark/benchmark.js @@ -53,12 +53,12 @@ function createBenchmark( N ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { sinqi( N, workspace, 1, 0 ); - if ( isnan( workspace[ ( 2*N ) + 1 ] ) ) { + if ( isnan( workspace[ 2*N ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( workspace[ ( 2*N ) + 1 ] ) ) { + if ( isnan( workspace[ 2*N ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/repl.txt b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/repl.txt index 7864186153f9..a1306dd597ab 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/repl.txt +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/repl.txt @@ -51,7 +51,7 @@ > var cosineTable = workspace.slice( 0, N ) [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] > var twiddleFactors = workspace.slice( 2*N, 3*N ) - [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] + [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] > var factors = workspace.slice( 3*N, ( 3*N ) + 4 ) [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/types/index.d.ts b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/types/index.d.ts index 681e25e4f029..6e5a33c1eb91 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/docs/types/index.d.ts @@ -51,7 +51,7 @@ import { Collection } from '@stdlib/types/array'; * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/index.js index ea0d92bbec78..10f4e9017dd2 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/index.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/index.js @@ -40,7 +40,7 @@ * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/main.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/main.js index 1b724874275e..3638dd6fcef1 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/main.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/lib/main.js @@ -151,7 +151,7 @@ var cosqi = require( '@stdlib/fft/base/fftpack/cosqi' ); * // returns [ ~0.98, ~0.92, ~0.83, ~0.7, ~0.56, ~0.38, ~0.2, ~0.0 ] * * var twiddleFactors = workspace.slice( 2*N, 3*N ); -* // returns [ 0, ~0.707, ~0.707, 0, 0, 0, 0, 0 ] +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] * * var factors = workspace.slice( 3*N, ( 3*N ) + 4 ); * // returns [ 8, 2, 2, 4 ] diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/large.json b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/large.json index d85386469224..4c3c35410e99 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/large.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/large.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/medium.json b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/medium.json index c17b5e118a8e..f87f8df28cfd 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/medium.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/medium.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/small.json b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/small.json index e43dbbea66f5..3146cddf05bd 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/small.json +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/fixtures/c/fftpack/small.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/test.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/test.js index a6f7eca690a1..61f26b47c8dc 100644 --- a/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/test.js +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinqi/test/test.js @@ -117,9 +117,9 @@ tape( 'the function correctly initializes twiddle factors (small sequence length workspace = new Float64Array( ( 3*N ) + 34 ); sinqi( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ (2*N) + i + 1 ]; + t.strictEqual( workspace[ (2*N) - 1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ (2*N) + i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -185,9 +185,9 @@ tape( 'the function correctly initializes twiddle factors (medium sequence lengt workspace = new Float64Array( ( 3*N ) + 34 ); sinqi( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ (2*N) + i + 1 ]; + t.strictEqual( workspace[ (2*N) - 1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ (2*N) + i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -253,9 +253,9 @@ tape( 'the function correctly initializes twiddle factors (large sequence length workspace = new Float64Array( ( 3*N ) + 34 ); sinqi( N, workspace, 1, 0 ); - t.strictEqual( workspace[ N ], 0.0, 'returns expected value' ); - for ( i = 0; i < N-1; i++ ) { - y = workspace[ (2*N) + i + 1 ]; + t.strictEqual( workspace[ (2*N) - 1 ], 0.0, 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + y = workspace[ (2*N) + i ]; e = expected[ off+i ]; t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); } @@ -307,8 +307,8 @@ tape( 'the function correctly handles stride and offset parameters', function te expected = new Float64Array( ( 3*N ) + 34 ); sinqi( N, expected, 1, 0 ); - for ( i = 0; i < N-1; i++ ) { - t.strictEqual( workspace[ offset + ( ( (2*N)+i+1 ) * stride ) ], expected[ (2*N)+i+1 ], 'returns expected value' ); + for ( i = 0; i < N; i++ ) { + t.strictEqual( workspace[ offset + ( ( (2*N)+i ) * stride ) ], expected[ (2*N)+i ], 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/README.md b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/README.md new file mode 100644 index 000000000000..3b63a5e9b1a6 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/README.md @@ -0,0 +1,175 @@ + + +# sinti + +> Initialize a workspace array for performing a sine transform. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var sinti = require( '@stdlib/fft/base/fftpack/sinti' ); +``` + +#### sinti( N, workspace, strideW, offsetW ) + +Initializes a workspace array for performing a sine transform. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); +var floor = require( '@stdlib/math/base/special/floor' ); + +var N = 7; +var workspace = new Float64Array( floor( 2.5*N ) + 34 ); + +var out = sinti( N, workspace, 1, 0 ); +// returns + +var bool = ( out === workspace ); +// returns true + +var sineTable = workspace.slice( 0, floor( N/2 ) ); +// returns [ ~0.765, ~1.414, ~1.848 ] + +var twiddleFactors = workspace.slice( floor( 3*N/2 ) + 1, floor( 5*N/2 ) + 2 ); +// returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] + +var factors = workspace.slice( floor( 5*N/2 ) + 2, floor( 5*N/2 ) + 2 + 4 ); +// returns [ 8, 2, 2, 4 ] +``` + +The function accepts the following arguments: + +- **N**: length of the sequence to transform. +- **workspace**: workspace array. +- **strideW**: stride length for `workspace`. +- **offsetW**: starting index for `workspace`. + +
+ + + + + +
+ +## Notes + +- The workspace array is divided into four sections: + + ```text + size = N/2 N+1 N+1 2+ceil(log2(N+1)/2) + ↓ ↓ ↓ ↓ + | sine table | scratch/workspace | twiddle factors | radix factor table | + ↑ ↑ ↑ ↑ + i = 0 ... N/2 ... (3N/2)+1 ... (5N/2)+2 ... + ``` + + - **sine table**: a table of precomputed sine coefficients used by sine transforms. + - **scratch/workspace**: used as a scratch space when performing transforms. This section is not updated during initialization. + - **twiddle factors**: a table of reusable complex-exponential constants stored as cosine/sine pairs. + - **radix factor table**: a table containing the sequence length `N+1`, the number of factors into which `N+1` was decomposed, and the individual integer radix factors. + +- In general, a workspace array should have `2.5N + 34` indexed elements (as `log2(N+1)/2 ≤ 32` for all `2^64`). During initialization, only the sections for storing the sine coefficients, twiddle factors, and the factorization of `N+1` are updated. + +- The radix factor table is comprised as follows: + + ```text + | sequence_length | number_of_factors | integer_factors | + ``` + +
+ + + +
+ +## Examples + + + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); +var zeroTo = require( '@stdlib/array/zero-to' ); +var logEach = require( '@stdlib/console/log-each' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var sinti = require( '@stdlib/fft/base/fftpack/sinti' ); + +var N = 7; +var workspace = new Float64Array( floor( 2.5*N ) + 34 ); + +sinti( N, workspace, 1, 0 ); +console.log( 'Sequence length: %d', N ); + +console.log( 'Sine table:' ); +var idx = zeroTo( floor( N/2 ), 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( 0, floor( N/2 ) ) ); + +console.log( 'Twiddle factors:' ); +idx = zeroTo( N+1, 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( floor( 3*N/2 ) + 1, floor( 5*N/2 ) + 2 ) ); + +console.log( 'Factorization:' ); +var nf = workspace[ floor( 5*N/2 ) + 3 ]; + +console.log( ' number of factors: %d', nf ); +idx = zeroTo( nf, 'generic' ); +logEach( ' factor[ %d ]: %d', idx, workspace.slice( floor( 5*N/2 ) + 4, floor( 5*N/2 ) + 4 + nf ) ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/benchmark/benchmark.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/benchmark/benchmark.js new file mode 100644 index 000000000000..a4e586b1414e --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/benchmark/benchmark.js @@ -0,0 +1,102 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var Float64Array = require( '@stdlib/array/float64' ); +var pkg = require( './../package.json' ).name; +var sinti = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Creates a benchmark function. +* +* @private +* @param {PositiveInteger} N - sequence length +* @returns {Function} benchmark function +*/ +function createBenchmark( N ) { + var workspace = new Float64Array( floor( 2.5*N ) + 34 ); + return benchmark; + + /** + * Benchmark function. + * + * @private + * @param {Benchmark} b - benchmark instance + */ + function benchmark( b ) { + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + sinti( N, workspace, 1, 0 ); + if ( isnan( workspace[ floor( 3*N/2 ) + 1 ] ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( workspace[ floor( 3*N/2 ) + 1 ] ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); + } +} + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +*/ +function main() { + var lengths; + var N; + var f; + var i; + + lengths = [ + 7, + 15, + 31, + 63, + 127, + 255, + 511, + 1023 + ]; + + for ( i = 0; i < lengths.length; i++ ) { + N = lengths[ i ]; + f = createBenchmark( N ); + bench( format( '%s:N=%d', pkg, N ), f ); + } +} + +main(); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/repl.txt b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/repl.txt new file mode 100644 index 000000000000..387fdf2987d4 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/repl.txt @@ -0,0 +1,64 @@ + +{{alias}}( N, workspace, strideW, offsetW ) + Initializes a workspace array for performing a sine transform. + + The workspace array is divided into four sections: + + 1. sine table: the section ranges from indices 0 to N/2 and is used to + store a table of precomputed sine coefficients used by sine transforms. + + 2. scratch/workspace: the section ranges from indices N/2 to 3N/2 and is + used while performing transforms. This section is not updated during + initialization. + + 3. twiddle factors: the section ranges from indices (3N/2)+1 to (5N/2)+1 + and stores a table of reusable complex exponential constants as cosine/sine + pairs. + + 4. radix factor table: the section starts at index (5N/2)+2 and stores the + sequence length N+1, the number of factors into which N+1 was decomposed, + and the individual integer radix factors. + + Any remaining array space remains as unused storage. + + Parameters + ---------- + N: integer + Length of the sequence. + + workspace: ArrayLikeObject + Workspace array. + + strideW: integer + Stride length for `workspace`. + + offsetW: integer + Starting index for `workspace`. + + Returns + ------- + out: ArrayLikeObject + Workspace array. + + Examples + -------- + > var N = 7; + > var len = {{alias:@stdlib/math/base/special/floor}}( 2.5*N ) + 34; + > var workspace = new {{alias:@stdlib/array/float64}}( len ); + > var out = {{alias}}( N, workspace, 1, 0 ) + + > var bool = ( out === workspace ) + true + > var ns2 = {{alias:@stdlib/math/base/special/floor}}( N/2 ); + > var sineTable = workspace.slice( 0, ns2 ) + [ ~0.765, ~1.414, ~1.848 ] + > var iw = ns2 + N + 1; + > var twiddleFactors = workspace.slice( iw, iw + (N+1) ) + [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] + > var fw = ns2 + 2*(N+1); + > var factors = workspace.slice( fw, fw + 4 ) + [ 8, 2, 2, 4 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/types/index.d.ts b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/types/index.d.ts new file mode 100644 index 000000000000..58cd8e06ba3d --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/types/index.d.ts @@ -0,0 +1,65 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection } from '@stdlib/types/array'; + +/** +* Initializes a workspace array for performing a sine transform. +* +* ## Notes +* +* - The workspace array should have a length of at least `( 2.5*N ) + 34` elements. +* +* @param N - length of the sequence +* @param workspace - workspace array +* @param strideW - stride length for `workspace` +* @param offsetW - starting index for `workspace` +* @returns workspace array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var floor = require( '@stdlib/math/base/special/floor' ); +* +* var N = 7; +* var workspace = new Float64Array( floor( 2.5*N ) + 34 ); +* +* var out = sinti( N, workspace, 1, 0 ); +* // returns +* +* var bool = ( out === workspace ); +* // returns true +* +* var sineTable = workspace.slice( 0, floor( N/2 ) ); +* // returns [ ~0.765, ~1.414, ~1.848 ] +* +* var twiddleFactors = workspace.slice( floor( 3*N/2 ) + 1, floor( 5*N/2 ) + 2 ); +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] +* +* var factors = workspace.slice( floor( 5*N/2 ) + 2, floor( 5*N/2 ) + 2 + 4 ); +* // returns [ 8, 2, 2, 4 ] +*/ +declare function sinti>( N: number, workspace: T, strideW: number, offsetW: number ): T; + + +// EXPORTS // + +export = sinti; diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/types/test.ts b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/types/test.ts new file mode 100644 index 000000000000..1cf202c7bbcb --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/docs/types/test.ts @@ -0,0 +1,95 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import floor = require( '@stdlib/math/base/special/floor' ); +import sinti = require( './index' ); + + +// TESTS // + +// The function returns a collection... +{ + const workspace = new Float64Array( floor( 2.5*7 ) + 34 ); + + sinti( 7, workspace, 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const workspace = new Float64Array( floor( 2.5*7 ) + 34 ); + + sinti( '7', workspace, 1, 0 ); // $ExpectError + sinti( true, workspace, 1, 0 ); // $ExpectError + sinti( false, workspace, 1, 0 ); // $ExpectError + sinti( null, workspace, 1, 0 ); // $ExpectError + sinti( void 0, workspace, 1, 0 ); // $ExpectError + sinti( [], workspace, 1, 0 ); // $ExpectError + sinti( {}, workspace, 1, 0 ); // $ExpectError + sinti( ( x: number ): number => x, workspace, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a collection... +{ + sinti( 7, '50', 1, 0 ); // $ExpectError + sinti( 7, 50, 1, 0 ); // $ExpectError + sinti( 7, true, 1, 0 ); // $ExpectError + sinti( 7, false, 1, 0 ); // $ExpectError + sinti( 7, null, 1, 0 ); // $ExpectError + sinti( 7, void 0, 1, 0 ); // $ExpectError + sinti( 7, {}, 1, 0 ); // $ExpectError + sinti( 7, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const workspace = new Float64Array( floor( 2.5*7 ) + 34 ); + + sinti( 7, workspace, '1', 0 ); // $ExpectError + sinti( 7, workspace, true, 0 ); // $ExpectError + sinti( 7, workspace, false, 0 ); // $ExpectError + sinti( 7, workspace, null, 0 ); // $ExpectError + sinti( 7, workspace, void 0, 0 ); // $ExpectError + sinti( 7, workspace, [], 0 ); // $ExpectError + sinti( 7, workspace, {}, 0 ); // $ExpectError + sinti( 7, workspace, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + const workspace = new Float64Array( floor( 2.5*7 ) + 34 ); + + sinti( 7, workspace, 1, '0' ); // $ExpectError + sinti( 7, workspace, 1, true ); // $ExpectError + sinti( 7, workspace, 1, false ); // $ExpectError + sinti( 7, workspace, 1, null ); // $ExpectError + sinti( 7, workspace, 1, void 0 ); // $ExpectError + sinti( 7, workspace, 1, [] ); // $ExpectError + sinti( 7, workspace, 1, {} ); // $ExpectError + sinti( 7, workspace, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const workspace = new Float64Array( floor( 2.5*7 ) + 34 ); + + sinti(); // $ExpectError + sinti( 7 ); // $ExpectError + sinti( 7, workspace ); // $ExpectError + sinti( 7, workspace, 1 ); // $ExpectError + sinti( 7, workspace, 1, 0, 123 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/examples/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/examples/index.js new file mode 100644 index 000000000000..e006767c0961 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/examples/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Float64Array = require( '@stdlib/array/float64' ); +var zeroTo = require( '@stdlib/array/zero-to' ); +var logEach = require( '@stdlib/console/log-each' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var sinti = require( './../lib' ); + +var N = 7; +var workspace = new Float64Array( floor( 2.5*N ) + 34 ); + +sinti( N, workspace, 1, 0 ); +console.log( 'Sequence length: %d', N ); + +console.log( 'Sine table:' ); +var idx = zeroTo( floor( N/2 ), 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( 0, floor( N/2 ) ) ); + +console.log( 'Twiddle factors:' ); +idx = zeroTo( N+1, 'generic' ); +logEach( ' workspace[ %d ] = %0.4f', idx, workspace.slice( floor( 3*N/2 ) + 1, floor( 5*N/2 ) + 2 ) ); + +console.log( 'Factorization:' ); +var nf = workspace[ floor( 5*N/2 ) + 3 ]; + +console.log( ' number of factors: %d', nf ); +idx = zeroTo( nf, 'generic' ); +logEach( ' factor[ %d ]: %d', idx, workspace.slice( floor( 5*N/2 ) + 4, floor( 5*N/2 ) + 4 + nf ) ); diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/lib/index.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/lib/index.js new file mode 100644 index 000000000000..409ddc984fe1 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Initialize a workspace array for performing a sine transform. +* +* @module @stdlib/fft/base/fftpack/sinti +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var floor = require( '@stdlib/math/base/special/floor' ); +* var sinti = require( '@stdlib/fft/base/fftpack/sinti' ); +* +* var N = 7; +* var workspace = new Float64Array( floor( 2.5*N ) + 34 ); +* +* var out = sinti( N, workspace, 1, 0 ); +* // returns +* +* var bool = ( out === workspace ); +* // returns true +* +* var sineTable = workspace.slice( 0, floor( N/2 ) ); +* // returns [ ~0.765, ~1.414, ~1.848 ] +* +* var twiddleFactors = workspace.slice( floor( 3*N/2 ) + 1, floor( 5*N/2 ) + 2 ); +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] +* +* var factors = workspace.slice( floor( 5*N/2 ) + 2, floor( 5*N/2 ) + 2 + 4 ); +* // returns [ 8, 2, 2, 4 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/lib/main.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/lib/main.js new file mode 100644 index 000000000000..45262315d789 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/lib/main.js @@ -0,0 +1,200 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The original C code and copyright notice are from the [PFFFT library]{@link https://github.com/marton78/pffft/blob/0b4ee12c4ba45a4a8e567550c16d96d1679f50ce/src/fftpack.c}. The implementation follows the original, but has been modified for JavaScript. +* +* ```text +* Copyright (c) 2004 the University Corporation for Atmospheric +* Research ("UCAR"). All rights reserved. Developed by NCAR's +* Computational and Information Systems Laboratory, UCAR, +* www.cisl.ucar.edu. +* +* Redistribution and use of the Software in source and binary forms, +* with or without modification, is permitted provided that the +* following conditions are met: +* +* - Neither the names of NCAR's Computational and Information Systems +* Laboratory, the University Corporation for Atmospheric Research, +* nor the names of its sponsors or contributors may be used to +* endorse or promote products derived from this Software without +* specific prior written permission. +* +* - Redistributions of source code must retain the above copyright +* notices, this list of conditions, and the disclaimer below. +* +* - Redistributions in binary form must reproduce the above copyright +* notice, this list of conditions, and the disclaimer below in the +* documentation and/or other materials provided with the +* distribution. +* +* THIS SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +* EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO THE WARRANTIES OF +* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +* NONINFRINGEMENT. IN NO EVENT SHALL THE CONTRIBUTORS OR COPYRIGHT +* HOLDERS BE LIABLE FOR ANY CLAIM, INDIRECT, INCIDENTAL, SPECIAL, +* EXEMPLARY, OR CONSEQUENTIAL DAMAGES OR OTHER LIABILITY, WHETHER IN AN +* ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN +* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS WITH THE +* SOFTWARE. +* ``` +*/ + +'use strict'; + +// MODULES // + +var sin = require( '@stdlib/math/base/special/sin' ); +var PI = require( '@stdlib/constants/float64/pi' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var rffti = require( '@stdlib/fft/base/fftpack/rffti' ); + + +// MAIN // + +/** +* Initializes a workspace array for performing a sine transform. +* +* ## Notes +* +* The workspace array is divided into four sections: +* +* ```text +* size = N/2 N+1 N+1 2+ceil(log2(N+1)/2) +* ↓ ↓ ↓ ↓ +* | sine table | scratch/workspace | twiddle factors | radix factor table | +* ↑ ↑ ↑ ↑ +* i = 0 ... N/2 ... (3N/2)+1 ... (5N/2)+2 ... +* ``` +* +* where +* +* - **sine table**: a table of precomputed sine coefficients used by sine transforms. +* - **scratch/workspace**: used as a scratch space when performing transforms. This section is not updated during initialization. +* - **twiddle factors**: a table of reusable complex-exponential constants stored as cosine/sine pairs. +* - **radix factor table**: a table containing the radix factorization of `N+1`. +* +* In general, a workspace array should have `2.5N + 34` indexed elements (as `log2(N+1)/2 ≤ 32` for all `2^64`). During initialization, only the sections for storing the sine coefficients, twiddle factors, and the factorization of `N+1` are updated. +* +* > Note: FFTPACK only requires `2.5N+15`, but we increase that number here to accommodate larger workspace arrays, where `N` may exceed `2^30` indexed elements. +* +* The factorization section is comprised as follows: +* +* ```text +* | sequence_length | number_of_factors | integer_factors | +* ``` +* +* The sequence length and number of factors (`nf`) comprise a single element each. Only the first `nf` elements in the integer factors section are written to, with the rest being unused. +* +* As for twiddle factors, these are small, reusable complex-exponential constants that appear inside each "butterfly" stage of a Cooley–Tukey–style FFT. Every arithmetic step in an FFT multiplies one intermediate value by some +* +* ```tex +* W_N^k +* ``` +* +* where `W_N^k` is an N-th root of unity. Formally, in a forward FFT, +* +* ```tex +* W_N^k = e^{-2\pi ik/N} +* ``` +* +* In a backward FFT, +* +* ```tex +* W_N^k = e^{+2\pi ik/N} +* ``` +* +* As may be observed, `W_N^k` for forward and backward FFTs is the same, except the sign of the exponent is flipped. As a consequence, both forward and backward FFT callers can reuse the same set of twiddle factors, with those performing a forward transform multiplying with `(cos,-sin)` and those performing a backward transform multiplying with `(cos,+sin)`. +* +* Because these constants only depend on the transform length `N` (and **not** on the input data), we can pre-compute and store them once, then "twiddle" them (i.e., reuse them with different indices) as we proceed through the factorization. +* +* > As a quick aside regarding the name "twiddle", early FFT papers (notably Gentleman & Sande, 1966) described how you "twiddle" one branch of each butterfly by a complex rotation before adding/subtracting. The coefficients themselves inherited the nickname "twiddle factors," and the term stuck. +* +* By reusing the workspace array when computing multiple transforms of the same length `N`, every subsequent `*f` (forward) or `*b` (backward) call can simply look up the pre-stored twiddle factors instead of recomputing sine and cosine on-the-fly. +* +* In short, twiddle factors are cached roots of unity that allow each stage of the algorithm to rotate data quickly and predictably. +* +* During initialization, `sinti` first writes the sine table, and then initializes the remaining three sections using `rffti`. +* +* @param {PositiveInteger} N - length of the sequence to transform +* @param {Collection} workspace - workspace array +* @param {integer} strideW - stride length for `workspace` +* @param {NonNegativeInteger} offsetW - starting index for `workspace` +* @returns {Collection} workspace array +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* var floor = require( '@stdlib/math/base/special/floor' ); +* +* var N = 7; +* var workspace = new Float64Array( floor( 2.5*N ) + 34 ); +* +* var out = sinti( N, workspace, 1, 0 ); +* // returns +* +* var bool = ( out === workspace ); +* // returns true +* +* var sineTable = workspace.slice( 0, floor( N/2 ) ); +* // returns [ ~0.765, ~1.414, ~1.848 ] +* +* var twiddleFactors = workspace.slice( floor( 3*N/2 ) + 1, floor( 5*N/2 ) + 2 ); +* // returns [ ~0.707, ~0.707, 0, 0, 0, 0, 0, 0 ] +* +* var factors = workspace.slice( floor( 5*N/2 ) + 2, floor( 5*N/2 ) + 2 + 4 ); +* // returns [ 8, 2, 2, 4 ] +*/ +function sinti( N, workspace, strideW, offsetW ) { + var offsetR; + var ns2; + var dt; + var fk; + var iw; + var i; + + if ( N <= 1 ) { + return workspace; + } + + // Compute the number of sine values to store: + ns2 = floor( N / 2 ); + + // Compute the angular increment: + dt = PI / ( N + 1 ); + + // Compute and store the sine table: + fk = 0.0; + iw = offsetW; + for ( i = 0; i < ns2; i++ ) { + fk += 1.0; + workspace[ iw+(i*strideW) ] = sin( fk*dt ) * 2.0; + } + // Resolve the starting index for the `rffti` workspace: + offsetR = offsetW + (ns2*strideW); + + // Initialize the real FFT workspace for a sequence of length N+1: + rffti( N+1, workspace, strideW, offsetR ); + + return workspace; +} + + +// EXPORTS // + +module.exports = sinti; diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/package.json b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/package.json new file mode 100644 index 000000000000..a88dc20f43a2 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/package.json @@ -0,0 +1,64 @@ +{ + "name": "@stdlib/fft/base/fftpack/sinti", + "version": "0.0.0", + "description": "Initialize a workspace array for performing a sine transform.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "fft", + "fftpack", + "sinti", + "fourier", + "transform", + "twiddle", + "workspace", + "initialization", + "sine" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/Makefile b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/Makefile new file mode 100644 index 000000000000..7ce16281940d --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/Makefile @@ -0,0 +1,137 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +endif + +# Specify the path to FFTPACK: +FFTPACK ?= + +# Specify a list of FFTPACK source files: +FFTPACK_SRC ?= + +# Determine the OS: +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate [position independent code][1]: +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of C targets: +c_targets := runner.out + + +# RULES # + +#/ +# Compiles C source files. +# +# @param {string} [C_COMPILER] - C compiler +# @param {string} [CFLAGS] - C compiler flags +# @param {(string|void)} [fPIC] - flag indicating whether to generate position independent code +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler +# @param {string} CFLAGS - C compiler flags +# @param {(string|void)} fPIC - flag indicating whether to generate position independent code +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) -DFFTPACK_DOUBLE_PRECISION $(fPIC) -o $@ $(FFTPACK_SRC) $< -lm + +#/ +# Generates test fixtures. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean + +#/ +# Removes generated test fixtures. +# +# @example +# make clean-fixtures +#/ +clean-fixtures: + $(QUIET) -rm -f *.json + +.PHONY: clean-fixtures diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/large.json b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/large.json new file mode 100644 index 000000000000..867e4abd85b0 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/large.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/medium.json b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/medium.json new file mode 100644 index 000000000000..5b71d20d3c92 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/medium.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/runner.c b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/runner.c new file mode 100644 index 000000000000..1844165535d8 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/runner.c @@ -0,0 +1,304 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/** +* Generate FFTPACK test fixtures. +* +* ## Notes +* +* - Run this script from the directory in which fixtures should be written. +* +*/ + +#include +#include +#include + +/** +* Define prototypes for external functions. +*/ +extern void sinti( int n, double *wsave ); + +/** +* Generates a random number on the interval [0,1]. +* +* @return random number +*/ +double rand_double( void ) { + int r = rand(); + return (double)r / ( (double)RAND_MAX + 1.0 ); +} + +/** +* Generates an array of pseudorandom integers drawn from a uniform distribution. +* +* ## Notes +* +* - WARNING: the method used here is not particularly robust, as some integer values may be sampled more frequently than others. +* +* +* @param out output array +* @param len array length +* @param a lower bound (inclusive) +* @param b upper bound (exclusive) +*/ +void rand_array_i32( int *out, const unsigned int len, const int a, const int b ) { + unsigned int i; + unsigned int r; + double delta; + + delta = (double)b - (double)a; + + for ( i = 0; i < len; i++ ) { + r = (unsigned int)( delta * rand_double() ); // truncation + out[ i ] = (int)( a + r ); + } +} + +/** +* Writes an array of doubles to a file as a series of comma-separated values. +* +* @param f file to write to +* @param x array of doubles +* @param len array length +*/ +void write_array_f64( FILE *f, const double *x, const unsigned int len ) { + unsigned int i; + + for ( i = 0; i < len; i++ ) { + fprintf( f, "%.17g", x[ i ] ); + if ( i < len-1 ) { + fprintf( f, "," ); + } + } +} + +/** +* Writes an array of integers to a file as a series of comma-separated values. +* +* @param f file to write to +* @param x array of integers +* @param len array length +*/ +void write_array_i32( FILE *f, const int *x, const unsigned int len ) { + unsigned int i; + + for ( i = 0; i < len; i++ ) { + fprintf( f, "%d", x[ i ] ); + if ( i < len-1 ) { + fprintf( f, "," ); + } + } +} + +/** +* Writes a named array of doubles to a file as JSON. +* +* @param f file to write to +* @param name array name +* @param x data +* @param len array length +*/ +void write_named_array_f64( FILE *f, const char *name, const double *x, const unsigned int len ) { + fprintf( f, "\"%s\":[", name ); + write_array_f64( f, x, len ); + fprintf( f, "]" ); +} + +/** +* Writes a named array of integers to a file as JSON. +* +* @param f file to write to +* @param name array name +* @param x data +* @param len array length +*/ +void write_named_array_i32( FILE *f, const char *name, const int *x, const unsigned int len ) { + fprintf( f, "\"%s\":[", name ); + write_array_i32( f, x, len ); + fprintf( f, "]" ); +} + +/** +* Writes data to a file as JSON. +* +* ## Notes +* +* - This function SHOULD be tailored to the input data (e.g., input types, output types, number of arguments, etc) and may vary from use case to use case. +* +* +* @param f file to write to +* @param lengths sequence lengths +* @param offsets sine and twiddle offsets +* @param sines sine values +* @param twiddles twiddle factors +* @param num number of sequence lengths +* @param total total number of sine and twiddle values +*/ +void write_data_as_json( FILE *f, const int *lengths, const int *offsets, const double *sines, const double *twiddles, const unsigned int num, const unsigned int total ) { + fprintf( f, "{" ); + write_named_array_i32( f, "lengths", lengths, num ); + fprintf( f, "," ); + write_named_array_i32( f, "offsets", offsets, num ); + fprintf( f, "," ); + write_named_array_f64( f, "sines", sines, total ); + fprintf( f, "," ); + write_named_array_f64( f, "twiddles", twiddles, total ); + fprintf( f, "}\n" ); +} + +/** +* Generates test fixtures. +* +* @param lengths sequence lengths +* @param offsets sine and twiddle offsets into flat output array +* @param num number of sequence lengths +* @param total total number of sine and twiddle values +* @param name output filename +*/ +void generate( const int *lengths, const int *offsets, const unsigned int num, const unsigned int total, const char *name ) { + unsigned int i; + unsigned int j; + double *sines; + double *twiddles; + double *wsave; + FILE *f; + int off; + int n; + + // Allocate an output array for sine values: + sines = (double*) calloc( total, sizeof(double) ); + if ( sines == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Allocate an output array for twiddle factors: + twiddles = (double*) calloc( total, sizeof(double) ); + if ( twiddles == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Generate fixture data: + for ( i = 0; i < num; i++ ) { + n = lengths[ i ]; + wsave = (double*) calloc( (int)(2.5*n) + 15, sizeof(double) ); + if ( wsave == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + sinti( n, wsave ); + + // Copy sine region into flat array (N/2 values starting at wsave[0]): + off = offsets[ i ]; + for ( j = 0; j < (unsigned int)(n/2); j++ ) { + sines[ off + j ] = wsave[ j ]; + } + + // Copy twiddle region into flat array (N+1 values starting at wsave[(n/2)+n+1]): + off = offsets[ i ]; + for ( j = 0; j < (unsigned int)( n + 1 ); j++ ) { + twiddles[ off + j ] = wsave[ ( n/2 ) + n + 1 + j ]; + } + free( wsave ); + } + // Open a new file: + f = fopen( name, "w" ); + if ( f == NULL ) { + printf( "Error opening file.\n" ); + exit( 1 ); + } + + // Write data as JSON: + write_data_as_json( f, lengths, offsets, sines, twiddles, num, total ); + + // Close the file: + fclose( f ); + + // Free allocated memory: + free( sines ); + free( twiddles ); +} + +/** +* Computes offsets into flat sine and twiddle arrays for each sequence length. +* +* @param offsets output array of offsets +* @param lengths sequence lengths +* @param num number of sequence lengths +* @return total number of sine and twiddle values +*/ +unsigned int compute_offsets( int *offsets, const int *lengths, const unsigned int num ) { + unsigned int total; + unsigned int i; + + total = 0; + for ( i = 0; i < num; i++ ) { + offsets[ i ] = total; + total += lengths[ i ] + 1; + } + return total; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + unsigned int total; + unsigned int num; + int *lengths; + int *offsets; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + // Define the number of sequence lengths per range: + num = 10; + + // Allocate arrays: + lengths = (int*) malloc( num * sizeof(int) ); + if ( lengths == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + offsets = (int*) malloc( num * sizeof(int) ); + if ( offsets == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Generate fixture data: + rand_array_i32( lengths, num, 2, 16 ); + total = compute_offsets( offsets, lengths, num ); + generate( lengths, offsets, num, total, "small.json" ); + + rand_array_i32( lengths, num, 16, 128 ); + total = compute_offsets( offsets, lengths, num ); + generate( lengths, offsets, num, total, "medium.json" ); + + rand_array_i32( lengths, num, 128, 1024 ); + total = compute_offsets( offsets, lengths, num ); + generate( lengths, offsets, num, total, "large.json" ); + + // Free allocated memory: + free( lengths ); + free( offsets ); + + return 0; +} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/small.json b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/small.json new file mode 100644 index 000000000000..dc1e4ec8bbb5 --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/fixtures/c/fftpack/small.json @@ -0,0 +1 @@ +{"lengths":[5,3,6,7,9,7,15,9,11,9],"offsets":[0,6,10,17,25,35,43,59,69,81],"sines":[0.99999999999999989,1.7320508075688772,0,0,0,0,1.4142135623730949,0,0,0,0.86776747823511624,1.5636629649360596,1.9498558243636472,0,0,0,0,0.76536686473017956,1.4142135623730949,1.8477590650225735,0,0,0,0,0,0.61803398874989479,1.1755705045849463,1.6180339887498949,1.9021130325903071,0,0,0,0,0,0,0.76536686473017956,1.4142135623730949,1.8477590650225735,0,0,0,0,0,0.3901806440322565,0.76536686473017956,1.1111404660392044,1.4142135623730949,1.6629392246050905,1.8477590650225735,1.9615705608064609,0,0,0,0,0,0,0,0,0,0.61803398874989479,1.1755705045849463,1.6180339887498949,1.9021130325903071,0,0,0,0,0,0,0.51763809020504148,0.99999999999999989,1.4142135623730949,1.7320508075688772,1.9318516525781364,0,0,0,0,0,0,0,0.61803398874989479,1.1755705045849463,1.6180339887498949,1.9021130325903071,0,0,0,0,0,0],"twiddles":[0.50000000000000011,0.8660254037844386,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.70710678118654757,0.70710678118654746,0,0,0,0,0,0,0.80901699437494745,0.58778525229247314,0.30901699437494745,0.95105651629515353,0,0,0,0,0,0,0.70710678118654757,0.70710678118654746,0,0,0,0,0,0,0.92387953251128674,0.38268343236508978,0,0,0.70710678118654757,0.70710678118654746,0,0,0.38268343236508984,0.92387953251128674,0,0,0,0,0,0,0.80901699437494745,0.58778525229247314,0.30901699437494745,0.95105651629515353,0,0,0,0,0,0,0.86602540378443871,0.49999999999999994,0,0.50000000000000011,0.8660254037844386,0,6.123233995736766e-17,1,0,0,0,0,0.80901699437494745,0.58778525229247314,0.30901699437494745,0.95105651629515353,0,0,0,0,0,0]} diff --git a/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/test.js b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/test.js new file mode 100644 index 000000000000..a6960135d70d --- /dev/null +++ b/lib/node_modules/@stdlib/fft/base/fftpack/sinti/test/test.js @@ -0,0 +1,335 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Float64Array = require( '@stdlib/array/float64' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var floor = require( '@stdlib/math/base/special/floor' ); +var sinti = require( './../lib' ); + + +// FIXTURES // + +var small = require( './fixtures/c/fftpack/small.json' ); +var medium = require( './fixtures/c/fftpack/medium.json' ); +var large = require( './fixtures/c/fftpack/large.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof sinti, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function has an arity of 4', function test( t ) { + t.strictEqual( sinti.length, 4, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns a reference to the workspace array', function test( t ) { + var workspace; + var out; + var N; + + N = 8; + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + out = sinti( N, workspace, 1, 0 ); + + t.strictEqual( out, workspace, 'same reference' ); + t.end(); +}); + +tape( 'the function correctly initializes sine values (small sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var ns2; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = small.lengths; + offsets = small.offsets; + expected = small.sines; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + ns2 = floor( N / 2 ); + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + sinti( N, workspace, 1, 0 ); + + for ( i = 0; i < ns2; i++ ) { + y = workspace[ i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes twiddle factors (small sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var ns2; + var off; + var iw; + var y; + var e; + var N; + var i; + var k; + + lengths = small.lengths; + offsets = small.offsets; + expected = small.twiddles; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + ns2 = floor( N / 2 ); + iw = ns2 + N + 1; + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + sinti( N, workspace, 1, 0 ); + + for ( i = 0; i < N+1; i++ ) { + y = workspace[ iw + i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes sine values (medium sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var ns2; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = medium.lengths; + offsets = medium.offsets; + expected = medium.sines; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + ns2 = floor( N / 2 ); + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + sinti( N, workspace, 1, 0 ); + + for ( i = 0; i < ns2; i++ ) { + y = workspace[ i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes twiddle factors (medium sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var ns2; + var off; + var iw; + var y; + var e; + var N; + var i; + var k; + + lengths = medium.lengths; + offsets = medium.offsets; + expected = medium.twiddles; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + ns2 = floor( N / 2 ); + iw = ns2 + N + 1; + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + sinti( N, workspace, 1, 0 ); + + for ( i = 0; i < N+1; i++ ) { + y = workspace[ iw + i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes sine values (large sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var ns2; + var off; + var y; + var e; + var N; + var i; + var k; + + lengths = large.lengths; + offsets = large.offsets; + expected = large.sines; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + ns2 = floor( N / 2 ); + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + sinti( N, workspace, 1, 0 ); + + for ( i = 0; i < ns2; i++ ) { + y = workspace[ i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function correctly initializes twiddle factors (large sequence lengths)', function test( t ) { + var workspace; + var expected; + var lengths; + var offsets; + var ulps; + var ns2; + var off; + var iw; + var y; + var e; + var N; + var i; + var k; + + lengths = large.lengths; + offsets = large.offsets; + expected = large.twiddles; + + ulps = 1; + for ( k = 0; k < lengths.length; k++ ) { + N = lengths[ k ]; + off = offsets[ k ]; + ns2 = floor( N / 2 ); + iw = ns2 + N + 1; + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + sinti( N, workspace, 1, 0 ); + + for ( i = 0; i < N+1; i++ ) { + y = workspace[ iw + i ]; + e = expected[ off+i ]; + t.strictEqual( isAlmostSameValue( y, e, ulps ), true, 'within '+ulps+' ULPs. N: '+N+'. y: '+y+'. E: '+e ); + } + } + t.end(); +}); + +tape( 'the function does not modify the scratch region of the workspace', function test( t ) { + var workspace; + var ns2; + var N; + var i; + + N = 8; + ns2 = floor( N / 2 ); + workspace = new Float64Array( floor( 2.5*N ) + 34 ); + + for ( i = 0; i < workspace.length; i++ ) { + workspace[ i ] = i + 1.0; + } + sinti( N, workspace, 1, 0 ); + for ( i = ns2; i < ns2 + N + 1; i++ ) { + t.strictEqual( workspace[ i ], i + 1.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function correctly handles stride and offset parameters', function test( t ) { + var workspace; + var expected; + var stride; + var offset; + var ns2; + var nf; + var iw; + var fw; + var N; + var i; + + N = 9; + ns2 = floor( N / 2 ); + stride = 2; + offset = 3; + workspace = new Float64Array( offset + ( ( floor( 2.5*N ) + 34 ) * stride ) ); + + sinti( N, workspace, stride, offset ); + + fw = ns2 + ( 2 * ( N+1 ) ); + t.strictEqual( workspace[ offset + ( fw * stride ) ], N+1, 'returns expected value' ); + + nf = workspace[ offset + ( ( fw+1 ) * stride ) ]; + t.strictEqual( nf, 2, 'returns expected value' ); + t.strictEqual( workspace[ offset + ( ( fw+2 ) * stride ) ], 2, 'returns expected value' ); + t.strictEqual( workspace[ offset + ( ( fw+3 ) * stride ) ], 5, 'returns expected value' ); + + expected = new Float64Array( floor( 2.5*N ) + 34 ); + sinti( N, expected, 1, 0 ); + + iw = ns2 + N + 1; + for ( i = 0; i < N+1; i++ ) { + t.strictEqual( workspace[ offset + ( ( iw+i ) * stride ) ], expected[ iw+i ], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/fs/append-file/lib/index.js b/lib/node_modules/@stdlib/fs/append-file/lib/index.js index cc1adb27a525..218ecf91b7ee 100644 --- a/lib/node_modules/@stdlib/fs/append-file/lib/index.js +++ b/lib/node_modules/@stdlib/fs/append-file/lib/index.js @@ -39,7 +39,7 @@ * * var err = appendFileSync( './beep/boop.txt', 'data to append\n' ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ diff --git a/lib/node_modules/@stdlib/fs/append-file/lib/sync.js b/lib/node_modules/@stdlib/fs/append-file/lib/sync.js index 436f3402cccd..2f3cabbb4c49 100644 --- a/lib/node_modules/@stdlib/fs/append-file/lib/sync.js +++ b/lib/node_modules/@stdlib/fs/append-file/lib/sync.js @@ -36,7 +36,7 @@ var appendFile = require( 'fs' ).appendFileSync; * @example * var err = appendFileSync( './beep/boop.txt', 'data to append\n' ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ function appendFileSync( path, data, options ) { diff --git a/lib/node_modules/@stdlib/fs/close/lib/index.js b/lib/node_modules/@stdlib/fs/close/lib/index.js index fd77462c5319..c87068ac6b46 100644 --- a/lib/node_modules/@stdlib/fs/close/lib/index.js +++ b/lib/node_modules/@stdlib/fs/close/lib/index.js @@ -29,7 +29,7 @@ * * function done( error ) { * if ( error ) { -* throw error; +* console.error( error.message ); * } * } * @@ -52,7 +52,7 @@ * * var err = closeSync( fd ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ diff --git a/lib/node_modules/@stdlib/fs/close/lib/main.js b/lib/node_modules/@stdlib/fs/close/lib/main.js index 5dccf1db43c3..5b8972e8122f 100644 --- a/lib/node_modules/@stdlib/fs/close/lib/main.js +++ b/lib/node_modules/@stdlib/fs/close/lib/main.js @@ -41,7 +41,7 @@ var format = require( '@stdlib/string/format' ); * * function done( error ) { * if ( error ) { -* throw error; +* console.error( error.message ); * } * } * diff --git a/lib/node_modules/@stdlib/fs/close/lib/sync.js b/lib/node_modules/@stdlib/fs/close/lib/sync.js index 7277d465e83f..75f391da8f8a 100644 --- a/lib/node_modules/@stdlib/fs/close/lib/sync.js +++ b/lib/node_modules/@stdlib/fs/close/lib/sync.js @@ -45,7 +45,7 @@ var format = require( '@stdlib/string/format' ); * * var err = closeSync( fd ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ function closeSync( fd ) { diff --git a/lib/node_modules/@stdlib/fs/open/lib/index.js b/lib/node_modules/@stdlib/fs/open/lib/index.js index a8f35e692354..c185f87d107b 100644 --- a/lib/node_modules/@stdlib/fs/open/lib/index.js +++ b/lib/node_modules/@stdlib/fs/open/lib/index.js @@ -29,7 +29,8 @@ * * function onOpen( error, fd ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * closeSync( fd ); * } diff --git a/lib/node_modules/@stdlib/fs/open/lib/main.js b/lib/node_modules/@stdlib/fs/open/lib/main.js index 49e87365d138..70786d371fba 100644 --- a/lib/node_modules/@stdlib/fs/open/lib/main.js +++ b/lib/node_modules/@stdlib/fs/open/lib/main.js @@ -41,7 +41,8 @@ var defaults = require( './defaults.json' ); * * function onOpen( error, fd ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * closeSync( fd ); * } diff --git a/lib/node_modules/@stdlib/fs/read-file-list/lib/index.js b/lib/node_modules/@stdlib/fs/read-file-list/lib/index.js index 141c05de2ff4..273c1fe6a73b 100644 --- a/lib/node_modules/@stdlib/fs/read-file-list/lib/index.js +++ b/lib/node_modules/@stdlib/fs/read-file-list/lib/index.js @@ -32,7 +32,8 @@ * * function onFiles( error, files ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.dir( files ); * } diff --git a/lib/node_modules/@stdlib/fs/read-file/lib/index.js b/lib/node_modules/@stdlib/fs/read-file/lib/index.js index 43d43a38bd1f..fb3f814ad212 100644 --- a/lib/node_modules/@stdlib/fs/read-file/lib/index.js +++ b/lib/node_modules/@stdlib/fs/read-file/lib/index.js @@ -28,7 +28,8 @@ * * function onFile( error, data ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( data ); * } diff --git a/lib/node_modules/@stdlib/fs/read-file/lib/main.js b/lib/node_modules/@stdlib/fs/read-file/lib/main.js index f83ce1821e87..212ef5cc9191 100644 --- a/lib/node_modules/@stdlib/fs/read-file/lib/main.js +++ b/lib/node_modules/@stdlib/fs/read-file/lib/main.js @@ -37,7 +37,8 @@ var readfile = require( 'fs' ).readFile; * @example * function onFile( error, data ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( data ); * } diff --git a/lib/node_modules/@stdlib/fs/read-json/lib/async.js b/lib/node_modules/@stdlib/fs/read-json/lib/async.js index 8d01b124132c..0b986501f39d 100644 --- a/lib/node_modules/@stdlib/fs/read-json/lib/async.js +++ b/lib/node_modules/@stdlib/fs/read-json/lib/async.js @@ -51,7 +51,8 @@ var format = require( '@stdlib/string/format' ); * * function onJSON( error, data ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.dir( data ); * } diff --git a/lib/node_modules/@stdlib/fs/read-json/lib/index.js b/lib/node_modules/@stdlib/fs/read-json/lib/index.js index c585761e66d3..32e14e9dfe12 100644 --- a/lib/node_modules/@stdlib/fs/read-json/lib/index.js +++ b/lib/node_modules/@stdlib/fs/read-json/lib/index.js @@ -29,7 +29,8 @@ * * function onJSON( error, data ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.dir( data ); * } diff --git a/lib/node_modules/@stdlib/fs/read-ndjson/lib/async.js b/lib/node_modules/@stdlib/fs/read-ndjson/lib/async.js index a362c8fb4fcd..91afbf46c7af 100644 --- a/lib/node_modules/@stdlib/fs/read-ndjson/lib/async.js +++ b/lib/node_modules/@stdlib/fs/read-ndjson/lib/async.js @@ -51,7 +51,8 @@ var format = require( '@stdlib/string/format' ); * * function onNDJSON( error, data ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.dir( data ); * } diff --git a/lib/node_modules/@stdlib/fs/read-ndjson/lib/index.js b/lib/node_modules/@stdlib/fs/read-ndjson/lib/index.js index 0d5d4e075d01..a82f87028502 100644 --- a/lib/node_modules/@stdlib/fs/read-ndjson/lib/index.js +++ b/lib/node_modules/@stdlib/fs/read-ndjson/lib/index.js @@ -29,7 +29,8 @@ * * function clbk( error, data ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( data ); * } diff --git a/lib/node_modules/@stdlib/fs/read-wasm/lib/async.js b/lib/node_modules/@stdlib/fs/read-wasm/lib/async.js index 7439f6270cc0..36031bf795fc 100644 --- a/lib/node_modules/@stdlib/fs/read-wasm/lib/async.js +++ b/lib/node_modules/@stdlib/fs/read-wasm/lib/async.js @@ -49,7 +49,8 @@ var format = require( '@stdlib/string/format' ); * * function onRead( error, buf ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( buf ); * } diff --git a/lib/node_modules/@stdlib/fs/read-wasm/lib/index.js b/lib/node_modules/@stdlib/fs/read-wasm/lib/index.js index 18031698b765..85321c250ce6 100644 --- a/lib/node_modules/@stdlib/fs/read-wasm/lib/index.js +++ b/lib/node_modules/@stdlib/fs/read-wasm/lib/index.js @@ -32,9 +32,10 @@ * * function onRead( error, buf ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } -* console.log( out ); +* console.log( buf ); * } * * @example diff --git a/lib/node_modules/@stdlib/fs/rename/lib/index.js b/lib/node_modules/@stdlib/fs/rename/lib/index.js index 9c67b5f2f1ea..c5d8f6311f17 100644 --- a/lib/node_modules/@stdlib/fs/rename/lib/index.js +++ b/lib/node_modules/@stdlib/fs/rename/lib/index.js @@ -28,7 +28,7 @@ * * function done( error ) { * if ( error ) { -* throw error; +* console.error( error.message ); * } * } * @@ -39,7 +39,7 @@ * * var err = renameSync( './beep/boop.txt', './beep/foo.txt' ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ diff --git a/lib/node_modules/@stdlib/fs/rename/lib/main.js b/lib/node_modules/@stdlib/fs/rename/lib/main.js index 5d265744c6fb..ec4ac7895750 100644 --- a/lib/node_modules/@stdlib/fs/rename/lib/main.js +++ b/lib/node_modules/@stdlib/fs/rename/lib/main.js @@ -35,7 +35,7 @@ var native = require( 'fs' ).rename; * @example * function done( error ) { * if ( error ) { -* throw error; +* console.error( error.message ); * } * } * diff --git a/lib/node_modules/@stdlib/fs/rename/lib/sync.js b/lib/node_modules/@stdlib/fs/rename/lib/sync.js index 910b9f166b73..25ac6595ac1d 100644 --- a/lib/node_modules/@stdlib/fs/rename/lib/sync.js +++ b/lib/node_modules/@stdlib/fs/rename/lib/sync.js @@ -35,7 +35,7 @@ var rename = require( 'fs' ).renameSync; * @example * var err = renameSync( './beep/boop.txt', './beep/foo.txt' ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ function renameSync( oldPath, newPath ) { diff --git a/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/async.js b/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/async.js index 8fea7d50951a..d96fafea6675 100644 --- a/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/async.js +++ b/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/async.js @@ -54,7 +54,8 @@ var validate = require( './validate.js' ); * * function onPath( error, path ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( path ); * } diff --git a/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/index.js b/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/index.js index 60ce87745104..808a34e18a2a 100644 --- a/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/index.js +++ b/lib/node_modules/@stdlib/fs/resolve-parent-path-by/lib/index.js @@ -34,7 +34,8 @@ * * function onPath( error, path ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( path ); * } diff --git a/lib/node_modules/@stdlib/fs/resolve-parent-path/lib/index.js b/lib/node_modules/@stdlib/fs/resolve-parent-path/lib/index.js index 3216262b91e0..710f454d9995 100644 --- a/lib/node_modules/@stdlib/fs/resolve-parent-path/lib/index.js +++ b/lib/node_modules/@stdlib/fs/resolve-parent-path/lib/index.js @@ -30,7 +30,8 @@ * * function onPath( error, path ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( path ); * } diff --git a/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/index.js b/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/index.js index a118ad53b2d3..cc0fccdffa9d 100644 --- a/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/index.js +++ b/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/index.js @@ -30,7 +30,8 @@ * * function onPaths( error, paths ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( paths ); * } diff --git a/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/main.js b/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/main.js index 3a637720560b..3ea1abe164f1 100644 --- a/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/main.js +++ b/lib/node_modules/@stdlib/fs/resolve-parent-paths/lib/main.js @@ -366,7 +366,8 @@ function each( paths, dir, done ) { * * function onPaths( error, paths ) { * if ( error ) { -* throw error; +* console.error( error.message ); +* return; * } * console.log( paths ); * } diff --git a/lib/node_modules/@stdlib/fs/unlink/lib/main.js b/lib/node_modules/@stdlib/fs/unlink/lib/main.js index 145a061a5448..80ebe543788a 100644 --- a/lib/node_modules/@stdlib/fs/unlink/lib/main.js +++ b/lib/node_modules/@stdlib/fs/unlink/lib/main.js @@ -34,7 +34,7 @@ var remove = require( 'fs' ).unlink; * @example * function done( error ) { * if ( error ) { -* throw error; +* console.error( error.message ); * } * } * diff --git a/lib/node_modules/@stdlib/fs/write-file/lib/index.js b/lib/node_modules/@stdlib/fs/write-file/lib/index.js index c622cfa1cdf3..b0a6b382a252 100644 --- a/lib/node_modules/@stdlib/fs/write-file/lib/index.js +++ b/lib/node_modules/@stdlib/fs/write-file/lib/index.js @@ -28,7 +28,7 @@ * * function onWrite( error ) { * if ( error ) { -* throw error; +* console.error( error.message ); * } * } * @@ -39,7 +39,7 @@ * * var err = writeFileSync( './beep/boop.txt', 'beep boop\n' ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ diff --git a/lib/node_modules/@stdlib/fs/write-file/lib/main.js b/lib/node_modules/@stdlib/fs/write-file/lib/main.js index 01737c4fd8b2..55d3ad5eef7a 100644 --- a/lib/node_modules/@stdlib/fs/write-file/lib/main.js +++ b/lib/node_modules/@stdlib/fs/write-file/lib/main.js @@ -36,7 +36,7 @@ var write = require( 'fs' ).writeFile; * @example * function onWrite( error ) { * if ( error ) { -* throw error; +* console.error( error.message ); * } * } * diff --git a/lib/node_modules/@stdlib/fs/write-file/lib/sync.js b/lib/node_modules/@stdlib/fs/write-file/lib/sync.js index 33cc33c88b8e..8e0c8bdb6a5e 100644 --- a/lib/node_modules/@stdlib/fs/write-file/lib/sync.js +++ b/lib/node_modules/@stdlib/fs/write-file/lib/sync.js @@ -36,7 +36,7 @@ var writeFile = require( 'fs' ).writeFileSync; * @example * var err = writeFileSync( './beep/boop.txt', 'beep boop\n' ); * if ( err instanceof Error ) { -* throw err; +* console.error( err.message ); * } */ function writeFileSync( file, data, options ) { diff --git a/lib/node_modules/@stdlib/lapack/base/clacgv/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/ndarray.js index ffadb6887658..78222d27edca 100644 --- a/lib/node_modules/@stdlib/lapack/base/clacgv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/clacgv/lib/ndarray.js @@ -26,7 +26,7 @@ var reinterpret = require( '@stdlib/strided/base/reinterpret-complex64' ); // MAIN // /** -* Conjugates each element in a single-precision complex floating-point vector. +* Conjugates each element in a single-precision complex floating-point vector using alternative indexing semantics. * * @param {PositiveInteger} N - number of indexed elements * @param {Complex64Array} cx - input array diff --git a/lib/node_modules/@stdlib/lapack/base/claset/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/claset/lib/ndarray.js index 230989aeb9c0..bdb6d6c99769 100644 --- a/lib/node_modules/@stdlib/lapack/base/claset/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/claset/lib/ndarray.js @@ -26,7 +26,7 @@ var base = require( './base.js' ); // MAIN // /** -* Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values. +* Sets the off-diagonal elements and the diagonal elements of a single-precision complex floating-point matrix to specified values using alternative indexing semantics. * * @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` * @param {NonNegativeInteger} M - number of rows in matrix `A` diff --git a/lib/node_modules/@stdlib/lapack/base/claswp/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/claswp/lib/ndarray.js index d5d373062cb8..d171c9f7777b 100644 --- a/lib/node_modules/@stdlib/lapack/base/claswp/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/claswp/lib/ndarray.js @@ -26,7 +26,7 @@ var base = require( './base.js' ); // MAIN // /** -* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV`. +* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV` and alternative indexing semantics. * * @param {PositiveInteger} N - number of columns in `A` * @param {Complex64Array} A - input matrix diff --git a/lib/node_modules/@stdlib/lapack/base/crot/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/crot/lib/ndarray.js index b93b00a917d8..e8b4ce0b6ccc 100644 --- a/lib/node_modules/@stdlib/lapack/base/crot/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/crot/lib/ndarray.js @@ -29,7 +29,7 @@ var imagf = require( '@stdlib/complex/float32/imag' ); // MAIN // /** -* Applies a plane rotation with real cosine and complex sine. +* Applies a plane rotation with real cosine and complex sine using alternative indexing semantics. * * @param {PositiveInteger} N - number of indexed elements * @param {Complex64Array} cx - first input array diff --git a/lib/node_modules/@stdlib/lapack/base/dgttrf/README.md b/lib/node_modules/@stdlib/lapack/base/dgttrf/README.md index ec6ea4c7dcc1..abdee2ccf4c5 100644 --- a/lib/node_modules/@stdlib/lapack/base/dgttrf/README.md +++ b/lib/node_modules/@stdlib/lapack/base/dgttrf/README.md @@ -32,6 +32,11 @@ The `dgttrf` routine computes an LU factorization of a real N-by-N tridiagonal m A = L U ``` + + where `L` is a product of permutation and unit lower bidiagonal matrices and `U` is upper triangular with non-zeros in only the main diagonal and first two superdiagonals. @@ -41,17 +46,14 @@ For a 5-by-5 tridiagonal matrix `A`, elements are stored in three arrays: ```math -A = \left[ -\begin{array}{rrrrr} - d_1 & du_1 & 0 & 0 & 0 \\ - dl_1 & d_2 & du_2 & 0 & 0 \\ - 0 & dl_2 & d_3 & du_3 & 0 \\ - 0 & 0 & dl_3 & d_4 & du_4 \\ - 0 & 0 & 0 & dl_4 & d_5 - \end{array} -\right] +A = \left[\begin{array}{rrrrr}d_1 & du_1 & 0 & 0 & 0 \\dl_1 & d_2 & du_2 & 0 & 0 \\0 & dl_2 & d_3 & du_3 & 0 \\0 & 0 & dl_3 & d_4 & du_4 \\0 & 0 & 0 & dl_4 & d_5\end{array}\right] ``` + + where: @@ -71,33 +73,27 @@ The resulting `L` and `U` matrices have the following structure: ```math -L = \left[ - \begin{array}{rrrrr} - 1 & 0 & 0 & 0 & 0 \\ - l_1 & 1 & 0 & 0 & 0 \\ - 0 & l_2 & 1 & 0 & 0 \\ - 0 & 0 & l_3 & 1 & 0 \\ - 0 & 0 & 0 & l_4 & 1 - \end{array} -\right] +L = \left[\begin{array}{rrrrr}1 & 0 & 0 & 0 & 0 \\l_1 & 1 & 0 & 0 & 0 \\0 & l_2 & 1 & 0 & 0 \\0 & 0 & l_3 & 1 & 0 \\0 & 0 & 0 & l_4 & 1\end{array}\right] ``` + + ```math -U = \left[ - \begin{array}{rrrrr} - u_{1,1} & u_{1,2} & u_{1,3} & 0 & 0 \\ - 0 & u_{2,2} & u_{2,3} & u_{2,4} & 0 \\ - 0 & 0 & u_{3,3} & u_{3,4} & u_{3,5} \\ - 0 & 0 & 0 & u_{4,4} & u_{4,5} \\ - 0 & 0 & 0 & 0 & u_{5,5} - \end{array} -\right] +U = \left[\begin{array}{rrrrr}u_{1,1} & u_{1,2} & u_{1,3} & 0 & 0 \\0 & u_{2,2} & u_{2,3} & u_{2,4} & 0 \\0 & 0 & u_{3,3} & u_{3,4} & u_{3,5} \\0 & 0 & 0 & u_{4,4} & u_{4,5} \\0 & 0 & 0 & 0 & u_{5,5}\end{array}\right] ``` + + where the `l(i)` values are stored in `DL`, the diagonal elements `u(i,i)` are stored in `D`, and the superdiagonal elements `u(i,i+1)` and `u(i,i+2)` are stored in `DU` and `DU2`, respectively. @@ -241,8 +237,6 @@ The function has the following additional parameters: While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, - - ```javascript var Float64Array = require( '@stdlib/array/float64' ); var Int32Array = require( '@stdlib/array/int32' ); diff --git a/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_lu_decomposition.svg b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_lu_decomposition.svg new file mode 100644 index 000000000000..98f2c6e39275 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_lu_decomposition.svg @@ -0,0 +1,15 @@ + +upper A equals upper L upper U + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_a.svg b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_a.svg new file mode 100644 index 000000000000..f002c029f19a --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_a.svg @@ -0,0 +1,144 @@ + +upper A equals Start 5 By 5 Matrix 1st Row 1st Column d 1 2nd Column d u 1 3rd Column 0 4th Column 0 5th Column 0 2nd Row 1st Column d l 1 2nd Column d 2 3rd Column d u 2 4th Column 0 5th Column 0 3rd Row 1st Column 0 2nd Column d l 2 3rd Column d 3 4th Column d u 3 5th Column 0 4th Row 1st Column 0 2nd Column 0 3rd Column d l 3 4th Column d 4 5th Column d u 4 5th Row 1st Column 0 2nd Column 0 3rd Column 0 4th Column d l 4 5th Column d 5 EndMatrix + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_l.svg b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_l.svg new file mode 100644 index 000000000000..43f238843285 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_l.svg @@ -0,0 +1,90 @@ + +upper L equals Start 5 By 5 Matrix 1st Row 1st Column 1 2nd Column 0 3rd Column 0 4th Column 0 5th Column 0 2nd Row 1st Column l 1 2nd Column 1 3rd Column 0 4th Column 0 5th Column 0 3rd Row 1st Column 0 2nd Column l 2 3rd Column 1 4th Column 0 5th Column 0 4th Row 1st Column 0 2nd Column 0 3rd Column l 3 4th Column 1 5th Column 0 5th Row 1st Column 0 2nd Column 0 3rd Column 0 4th Column l 4 5th Column 1 EndMatrix + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_u.svg b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_u.svg new file mode 100644 index 000000000000..05f494fc5798 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/dgttrf/docs/img/equation_matrix_u.svg @@ -0,0 +1,164 @@ + +upper U equals Start 5 By 5 Matrix 1st Row 1st Column u Subscript 1 comma 1 Baseline 2nd Column u Subscript 1 comma 2 Baseline 3rd Column u Subscript 1 comma 3 Baseline 4th Column 0 5th Column 0 2nd Row 1st Column 0 2nd Column u Subscript 2 comma 2 Baseline 3rd Column u Subscript 2 comma 3 Baseline 4th Column u Subscript 2 comma 4 Baseline 5th Column 0 3rd Row 1st Column 0 2nd Column 0 3rd Column u Subscript 3 comma 3 Baseline 4th Column u Subscript 3 comma 4 Baseline 5th Column u Subscript 3 comma 5 Baseline 4th Row 1st Column 0 2nd Column 0 3rd Column 0 4th Column u Subscript 4 comma 4 Baseline 5th Column u Subscript 4 comma 5 Baseline 5th Row 1st Column 0 2nd Column 0 3rd Column 0 4th Column 0 5th Column u Subscript 5 comma 5 EndMatrix + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/lapack/base/dladiv/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/dladiv/lib/ndarray.js index 75ad6e5dcac0..d80a86e59eb4 100644 --- a/lib/node_modules/@stdlib/lapack/base/dladiv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/dladiv/lib/ndarray.js @@ -26,7 +26,7 @@ var base = require( './base.js' ); // MAIN // /** -* Divides two double-precision complex floating-point numbers in real arithmetic. +* Divides two double-precision complex floating-point numbers in real arithmetic using alternative indexing semantics. * * @param {number} a - real component of numerator * @param {number} b - imaginary component of numerator diff --git a/lib/node_modules/@stdlib/lapack/base/dlarf/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlarf/lib/ndarray.js index 98c017be6491..2e18bb48ab5c 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlarf/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/dlarf/lib/ndarray.js @@ -32,7 +32,7 @@ var base = require( './base.js' ); // MAIN // /** -* Applies a real elementary reflector `H = I - tau * v * v^T` to a real M by N matrix `C`. +* Applies a real elementary reflector `H = I - tau * v * v^T` to a real M by N matrix `C` using alternative indexing semantics. * * ## Notes * diff --git a/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/base.js b/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/base.js index 5ab4295edda4..13df105fc02c 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/base.js +++ b/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/base.js @@ -108,16 +108,17 @@ function dlarf1f( side, M, N, V, strideV, offsetV, tau, C, strideC1, strideC2, o i = offsetV + ( ( lastv-1 ) * strideV ); // Move `i` to the last non-zero element in `V`, where we assume that V[0] = 1, and it is not stored, so we shouldn't access it... - while ( lastv > 0 && V[ i ] === 0.0 ) { + while ( lastv > 1 && V[ i ] === 0.0 ) { // `lastv` should be greater than 1 as it represents the last one-based index with a zero value lastv -= 1; i -= strideV; } + if ( isLeftSide( side ) ) { // Scan for the last non-zero column in `C`: - lastc = iladlc( lastv + 1, N, C, strideC1, strideC2, offsetC ) + 1; // adjust by `+1` to account for the difference between zero-based and one-based indexing + lastc = iladlc( lastv, N, C, strideC1, strideC2, offsetC ) + 1; // adjust by `+1` to account for the difference between zero-based and one-based indexing } else { // Scan for the last non-zero row in `C`: - lastc = iladlr( M, lastv + 1, C, strideC1, strideC2, offsetC ) + 1; // // adjust by `+1` to account for the difference between zero-based and one-based indexing + lastc = iladlr( M, lastv, C, strideC1, strideC2, offsetC ) + 1; // adjust by `+1` to account for the difference between zero-based and one-based indexing } // Return `C` unchanged if all elements in `C` are zero... if ( lastc === 0 ) { @@ -127,7 +128,7 @@ function dlarf1f( side, M, N, V, strideV, offsetV, tau, C, strideC1, strideC2, o // Form: H*C // If `lastv = 1`, this means `V = 1`, so we just need to compute `C = H*C = (1-tau)*C`... - if ( lastv === 0 ) { + if ( lastv === 1 ) { // C[0,0:lastc] = (1-tau)*C[0,0:lastc] dscal( lastc, 1.0-tau, C, strideC2, offsetC ); // scale the first row } else { @@ -154,7 +155,7 @@ function dlarf1f( side, M, N, V, strideV, offsetV, tau, C, strideC1, strideC2, o // Form: C*H // If `N = 1`, then `V = 1`, so we just need to compute `C = CH = C*(1-tau)`... - if ( lastv === 0 ) { + if ( lastv === 1 ) { // C[0:lastc,0] = ( 1-tau ) * C[0:lastc,0] dscal( lastc, 1.0-tau, C, strideC1, offsetC ); // scale the first column return C; diff --git a/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/ndarray.js index 4dfa0851e489..f89920029c34 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/dlarf1f/lib/ndarray.js @@ -32,7 +32,7 @@ var base = require( './base.js' ); // MAIN // /** -* Applies a real elementary reflector `H = I - tau * v * v^T` to a real M by N matrix `C`. +* Applies a real elementary reflector `H = I - tau * v * v^T` to a real M by N matrix `C` using alternative indexing semantics. * * ## Notes * diff --git a/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/fixtures/indexing.json b/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/fixtures/indexing.json new file mode 100644 index 000000000000..c3ea94c81a63 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/fixtures/indexing.json @@ -0,0 +1,36 @@ +{ + "order": "column-major", + + "side": "left", + + "M": 3, + "N": 1, + + "V": [ 1.0, 0.0, 0.0, 0.0, -1.0, 0.0 ], + "strideV": 1, + "offsetV": 0, + + "tau": 2.0, + + "C": [ 1.0, 0.0, 0.0, 0.0, -1.0, 0.0 ], + "strideC1": 1, + "strideC2": 3, + "offsetC": 0, + "LDC": 3, + "C_mat": [ + [ 1.0, 0.0 ], + [ 0.0, -1.0 ], + [ 0.0, 0.0 ] + ], + + "work": [ 64.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ], + "strideWork": 1, + "offsetWork": 0, + + "C_out": [ -1.0, 0.0, 0.0, -0.0, -1.0, -0.0 ], + "C_out_mat": [ + [ -1.0, 0.0 ], + [ 0.0, -1.0 ], + [ 0.0, 0.0 ] + ] +} diff --git a/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.dlarf1f.js b/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.dlarf1f.js index 3ac015122405..77164fcfba76 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.dlarf1f.js +++ b/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.dlarf1f.js @@ -38,6 +38,7 @@ var RIGHT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/right_lastv_eq_zero_row var RIGHT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/right_lastv_eq_zero_col_major.json' ); var RIGHT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/right_lastv_gt_zero_row_major.json' ); var RIGHT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/right_lastv_gt_zero_col_major.json' ); +var INDEXING = require( './fixtures/indexing.json' ); // TESTS // @@ -367,3 +368,24 @@ tape( 'the function applies an elementary refactor (side=right, lastv > 0, colum t.deepEqual( out, expectedC, 'returns expected value' ); t.end(); }); + +tape( 'the function follows consistent indexing with LAPACK', function test( t ) { + var expectedC; + var data; + var work; + var out; + var V; + var C; + + data = INDEXING; + + V = new Float64Array( data.V ); + C = new Float64Array( data.C ); + work = new Float64Array( data.work ); + + out = dlarf1f( data.order, data.side, data.M, data.N, V, data.strideV, data.tau, C, data.LDC, work ); + expectedC = new Float64Array( data.C_out ); + + t.deepEqual( out, expectedC, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.ndarray.js index 52b6148a923c..1635f21a6443 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/dlarf1f/test/test.ndarray.js @@ -38,46 +38,39 @@ var RIGHT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/right_lastv_eq_zero_row var RIGHT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/right_lastv_eq_zero_col_major.json' ); var RIGHT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/right_lastv_gt_zero_row_major.json' ); var RIGHT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/right_lastv_gt_zero_col_major.json' ); - var MIXED_STRIDES_RIGHT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/mixed_strides/right_lastv_gt_zero_row_major.json' ); var NEGATIVE_STRIDES_RIGHT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/negative_strides/right_lastv_gt_zero_row_major.json' ); var LARGE_STRIDES_RIGHT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/large_strides/right_lastv_gt_zero_row_major.json' ); var OFFSETS_RIGHT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/offsets/right_lastv_gt_zero_row_major.json' ); - var NEGATIVE_STRIDES_RIGHT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/negative_strides/right_lastv_gt_zero_col_major.json' ); var MIXED_STRIDES_RIGHT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/mixed_strides/right_lastv_gt_zero_col_major.json' ); var LARGE_STRIDES_RIGHT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/large_strides/right_lastv_gt_zero_col_major.json' ); var OFFSETS_RIGHT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/offsets/right_lastv_gt_zero_col_major.json' ); - var MIXED_STRIDES_RIGHT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/mixed_strides/right_lastv_eq_zero_row_major.json' ); var NEGATIVE_STRIDES_RIGHT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/negative_strides/right_lastv_eq_zero_row_major.json' ); var LARGE_STRIDES_RIGHT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/large_strides/right_lastv_eq_zero_row_major.json' ); var OFFSETS_RIGHT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/offsets/right_lastv_eq_zero_row_major.json' ); - var NEGATIVE_STRIDES_RIGHT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/negative_strides/right_lastv_eq_zero_col_major.json' ); var MIXED_STRIDES_RIGHT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/mixed_strides/right_lastv_eq_zero_col_major.json' ); var LARGE_STRIDES_RIGHT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/large_strides/right_lastv_eq_zero_col_major.json' ); var OFFSETS_RIGHT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/offsets/right_lastv_eq_zero_col_major.json' ); - var NEGATIVE_STRIDES_LEFT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/negative_strides/left_lastv_gt_zero_row_major.json' ); var MIXED_STRIDES_LEFT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/mixed_strides/left_lastv_gt_zero_row_major.json' ); var LARGE_STRIDES_LEFT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/large_strides/left_lastv_gt_zero_row_major.json' ); var OFFSETS_LEFT_LASTV_GT_ZERO_ROW_MAJOR = require( './fixtures/offsets/left_lastv_gt_zero_row_major.json' ); - var MIXED_STRIDES_LEFT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/mixed_strides/left_lastv_gt_zero_col_major.json' ); var LARGE_STRIDES_LEFT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/large_strides/left_lastv_gt_zero_col_major.json' ); var OFFSETS_LEFT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/offsets/left_lastv_gt_zero_col_major.json' ); var NEGATIVE_STRIDES_LEFT_LASTV_GT_ZERO_COL_MAJOR = require( './fixtures/negative_strides/left_lastv_gt_zero_col_major.json' ); - var MIXED_STRIDES_LEFT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/mixed_strides/left_lastv_eq_zero_row_major.json' ); var LARGE_STRIDES_LEFT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/large_strides/left_lastv_eq_zero_row_major.json' ); var OFFSETS_LEFT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/offsets/left_lastv_eq_zero_row_major.json' ); var NEGATIVE_STRIDES_LEFT_LASTV_EQ_ZERO_ROW_MAJOR = require( './fixtures/negative_strides/left_lastv_eq_zero_row_major.json' ); - var MIXED_STRIDES_LEFT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/mixed_strides/left_lastv_eq_zero_col_major.json' ); var LARGE_STRIDES_LEFT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/large_strides/left_lastv_eq_zero_col_major.json' ); var OFFSETS_LEFT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/offsets/left_lastv_eq_zero_col_major.json' ); var NEGATIVE_STRIDES_LEFT_LASTV_EQ_ZERO_COL_MAJOR = require( './fixtures/negative_strides/left_lastv_eq_zero_col_major.json' ); +var INDEXING = require( './fixtures/indexing.json' ); // TESTS // @@ -340,6 +333,27 @@ tape( 'the function applies an elementary reflector (side=right, lastv > 0, colu t.end(); }); +tape( 'the function follows indexing consistent with LAPACK', function test( t ) { + var expectedC; + var data; + var work; + var out; + var V; + var C; + + data = INDEXING; + + V = new Float64Array( data.V ); + C = new Float64Array( data.C ); + work = new Float64Array( data.work ); + + out = dlarf1f( data.side, data.M, data.N, V, data.strideV, data.offsetV, data.tau, C, data.strideC1, data.strideC2, data.offsetC, work, data.strideWork, data.offsetWork ); + expectedC = new Float64Array( data.C_out ); + + t.deepEqual( out, expectedC, 'returns expected value' ); + t.end(); +}); + tape( 'the function applies an elementary reflector (side=right, lastv > 0, row-major, mixed strides)', function test( t ) { var expectedC; var data; diff --git a/lib/node_modules/@stdlib/lapack/base/dlassq/README.md b/lib/node_modules/@stdlib/lapack/base/dlassq/README.md index 63826edd883a..dc610bce913e 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlassq/README.md +++ b/lib/node_modules/@stdlib/lapack/base/dlassq/README.md @@ -28,10 +28,14 @@ This routine returns the values $s_{textrm{out}}$ and $\\textrm{ss}_{\\textrm{ou -
- Sum of squares represented in scaled form +```math +s_{\textrm{out}}^2 \cdot \textrm{ss}_{\textrm{out}} = x_0^2 + \ldots + x_{N-1}^2 + s_{\textrm{in}}^2 \cdot \textrm{ss}_{\textrm{in}} +``` + + @@ -113,8 +117,6 @@ The function has the following additional parameters: While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, - - ```javascript var Float64Array = require( '@stdlib/array/float64' ); diff --git a/lib/node_modules/@stdlib/lapack/base/dlassq/docs/img/equation_sum_of_squares.svg b/lib/node_modules/@stdlib/lapack/base/dlassq/docs/img/equation_sum_of_squares.svg new file mode 100644 index 000000000000..4cf5dac35ec3 --- /dev/null +++ b/lib/node_modules/@stdlib/lapack/base/dlassq/docs/img/equation_sum_of_squares.svg @@ -0,0 +1,77 @@ + +s Subscript out Superscript 2 Baseline dot ss Subscript out Baseline equals x 0 squared plus ellipsis plus x Subscript upper N minus 1 Superscript 2 Baseline plus s Subscript in Superscript 2 Baseline dot ss Subscript in + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/lapack/base/dlaswp/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/dlaswp/lib/ndarray.js index 4b1cfd7610dd..b3875fde724c 100644 --- a/lib/node_modules/@stdlib/lapack/base/dlaswp/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/dlaswp/lib/ndarray.js @@ -26,7 +26,7 @@ var base = require( './base.js' ); // MAIN // /** -* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV`. +* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV` and alternative indexing semantics. * * @param {PositiveInteger} N - number of columns in `A` * @param {Float64Array} A - input matrix diff --git a/lib/node_modules/@stdlib/lapack/base/dpttrf/README.md b/lib/node_modules/@stdlib/lapack/base/dpttrf/README.md index 89026cde78f3..86a70e04b82a 100644 --- a/lib/node_modules/@stdlib/lapack/base/dpttrf/README.md +++ b/lib/node_modules/@stdlib/lapack/base/dpttrf/README.md @@ -95,8 +95,6 @@ The function has the following additional parameters: While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, - - ```javascript var Float64Array = require( '@stdlib/array/float64' ); diff --git a/lib/node_modules/@stdlib/lapack/base/iladlr/lib/iladlr.js b/lib/node_modules/@stdlib/lapack/base/iladlr/lib/iladlr.js index 937b6fe597c7..e5fd5893b18f 100644 --- a/lib/node_modules/@stdlib/lapack/base/iladlr/lib/iladlr.js +++ b/lib/node_modules/@stdlib/lapack/base/iladlr/lib/iladlr.js @@ -33,6 +33,10 @@ var base = require( './base.js' ); /** * Returns the index of the last non-zero row in a matrix `A`. * +* ## Notes +* +* - If provided an empty matrix or a matrix containing only zeros, the function returns `-1` (i.e., an invalid index). +* * @param {string} order - storage layout * @param {PositiveInteger} M - number of rows in `A` * @param {PositiveInteger} N - number of columns in `A` diff --git a/lib/node_modules/@stdlib/lapack/base/slaswp/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/slaswp/lib/ndarray.js index aede91e37164..4628de109f7a 100644 --- a/lib/node_modules/@stdlib/lapack/base/slaswp/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/slaswp/lib/ndarray.js @@ -26,7 +26,7 @@ var base = require( './base.js' ); // MAIN // /** -* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV`. +* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV` and alternative indexing semantics. * * @param {PositiveInteger} N - number of columns in `A` * @param {Float32Array} A - input matrix diff --git a/lib/node_modules/@stdlib/lapack/base/spttrf/README.md b/lib/node_modules/@stdlib/lapack/base/spttrf/README.md index b267ad710e3f..47c1e7e2ac11 100644 --- a/lib/node_modules/@stdlib/lapack/base/spttrf/README.md +++ b/lib/node_modules/@stdlib/lapack/base/spttrf/README.md @@ -95,8 +95,6 @@ The function has the following additional parameters: While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, - - ```javascript var Float32Array = require( '@stdlib/array/float32' ); diff --git a/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/ndarray.js index e3e14b95a140..81abde0564a1 100644 --- a/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/zlacgv/lib/ndarray.js @@ -26,7 +26,7 @@ var reinterpret = require( '@stdlib/strided/base/reinterpret-complex128' ); // MAIN // /** -* Conjugates each element in a double-precision complex floating-point vector. +* Conjugates each element in a double-precision complex floating-point vector using alternative indexing semantics. * * @param {PositiveInteger} N - number of indexed elements * @param {Complex128Array} zx - input array diff --git a/lib/node_modules/@stdlib/lapack/base/zlaset/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/ndarray.js index 4bd206ea4798..859146403916 100644 --- a/lib/node_modules/@stdlib/lapack/base/zlaset/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/zlaset/lib/ndarray.js @@ -26,7 +26,7 @@ var base = require( './base.js' ); // MAIN // /** -* Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values. +* Sets the off-diagonal elements and the diagonal elements of a double-precision complex floating-point matrix to specified values using alternative indexing semantics. * * @param {string} uplo - specifies whether to set the upper or lower triangular/trapezoidal part of matrix `A` * @param {NonNegativeInteger} M - number of rows in matrix `A` diff --git a/lib/node_modules/@stdlib/lapack/base/zlaswp/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zlaswp/lib/ndarray.js index ba712704ae18..bd7345905686 100644 --- a/lib/node_modules/@stdlib/lapack/base/zlaswp/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/zlaswp/lib/ndarray.js @@ -26,7 +26,7 @@ var base = require( './base.js' ); // MAIN // /** -* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV`. +* Performs a series of row interchanges on a matrix `A` using pivot indices stored in `IPIV` and alternative indexing semantics. * * @param {PositiveInteger} N - number of columns in `A` * @param {Complex128Array} A - input matrix diff --git a/lib/node_modules/@stdlib/lapack/base/zrot/lib/ndarray.js b/lib/node_modules/@stdlib/lapack/base/zrot/lib/ndarray.js index c783ee636b4e..0efd72a191e9 100644 --- a/lib/node_modules/@stdlib/lapack/base/zrot/lib/ndarray.js +++ b/lib/node_modules/@stdlib/lapack/base/zrot/lib/ndarray.js @@ -28,7 +28,7 @@ var imag = require( '@stdlib/complex/float64/imag' ); // MAIN // /** -* Applies a plane rotation with real cosine and complex sine. +* Applies a plane rotation with real cosine and complex sine using alternative indexing semantics. * * @param {PositiveInteger} N - number of indexed elements * @param {Complex128Array} zx - first input array diff --git a/lib/node_modules/@stdlib/math/base/special/README.md b/lib/node_modules/@stdlib/math/base/special/README.md index c1e91989e287..59fbd65ea53e 100644 --- a/lib/node_modules/@stdlib/math/base/special/README.md +++ b/lib/node_modules/@stdlib/math/base/special/README.md @@ -348,7 +348,7 @@ var fcns = special; - [`gamma( x )`][@stdlib/math/base/special/gamma]: gamma function. - [`gamma1pm1( x )`][@stdlib/math/base/special/gamma1pm1]: compute `gamma(x+1) - 1`. - [`gammainc( x, s[, regularized[, upper ]] )`][@stdlib/math/base/special/gammainc]: incomplete gamma function. -- [`gammaincinv( p, s[, upper ] )`][@stdlib/math/base/special/gammaincinv]: inverse of incomplete gamma function. +- [`gammaincinv( p, a[, upper ] )`][@stdlib/math/base/special/gammaincinv]: inverse of incomplete gamma function. - [`gammaln( x )`][@stdlib/math/base/special/gammaln]: natural logarithm of the gamma function. - [`gammasgn( x )`][@stdlib/math/base/special/gammasgn]: sign of the gamma function. - [`gammasgnf( x )`][@stdlib/math/base/special/gammasgnf]: sign of the gamma function for a single-precision floating-point number. diff --git a/lib/node_modules/@stdlib/math/base/special/acos/manifest.json b/lib/node_modules/@stdlib/math/base/special/acos/manifest.json index 3c6a30c2270f..761fd6920af4 100644 --- a/lib/node_modules/@stdlib/math/base/special/acos/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/acos/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/special/asin", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/fourth-pi" + "@stdlib/constants/float64/fourth-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/special/asin", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/fourth-pi" + "@stdlib/constants/float64/fourth-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/special/asin", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/fourth-pi" + "@stdlib/constants/float64/fourth-pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/acos/src/main.c b/lib/node_modules/@stdlib/math/base/special/acos/src/main.c index b22d65d97279..94793e19b1e9 100644 --- a/lib/node_modules/@stdlib/math/base/special/acos/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/acos/src/main.c @@ -35,6 +35,7 @@ #include "stdlib/math/base/special/asin.h" #include "stdlib/math/base/special/sqrt.h" #include "stdlib/constants/float64/fourth_pi.h" +#include "stdlib/constants/float64/nan.h" #include static const double MOREBITS = 6.123233995736765886130e-17; // pi/2 = PIO2 + MOREBITS. @@ -81,10 +82,10 @@ static const double MOREBITS = 6.123233995736765886130e-17; // pi/2 = PIO2 + MOR double stdlib_base_acos( const double x ) { double z; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x < -1.0 || x > 1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x > 0.5 ) { return 2.0 * stdlib_base_asin( stdlib_base_sqrt( 0.5 - ( 0.5 * x ) ) ); diff --git a/lib/node_modules/@stdlib/math/base/special/acosh/manifest.json b/lib/node_modules/@stdlib/math/base/special/acosh/manifest.json index c8420422370f..c046f462b2c5 100644 --- a/lib/node_modules/@stdlib/math/base/special/acosh/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/acosh/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/acosh/src/main.c b/lib/node_modules/@stdlib/math/base/special/acosh/src/main.c index e998e6aeb888..d53894439ba4 100644 --- a/lib/node_modules/@stdlib/math/base/special/acosh/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/acosh/src/main.c @@ -36,6 +36,7 @@ #include "stdlib/math/base/special/sqrt.h" #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/ln_two.h" +#include "stdlib/constants/float64/nan.h" #include static const double HUGE = 1 << 28; // 2**28 @@ -79,7 +80,7 @@ static const double HUGE = 1 << 28; // 2**28 double stdlib_base_acosh( const double x ) { double t; if ( stdlib_base_is_nan( x ) || x < 1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 1.0 ) { return 0.0; diff --git a/lib/node_modules/@stdlib/math/base/special/asin/manifest.json b/lib/node_modules/@stdlib/math/base/special/asin/manifest.json index c470fe9c8dbd..e0a2eb81c3ea 100644 --- a/lib/node_modules/@stdlib/math/base/special/asin/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/asin/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/fourth-pi" + "@stdlib/constants/float64/fourth-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/fourth-pi" + "@stdlib/constants/float64/fourth-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/fourth-pi" + "@stdlib/constants/float64/fourth-pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/asin/src/main.c b/lib/node_modules/@stdlib/math/base/special/asin/src/main.c index 836f08fa3587..e04fef739967 100644 --- a/lib/node_modules/@stdlib/math/base/special/asin/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/asin/src/main.c @@ -34,6 +34,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/sqrt.h" #include "stdlib/constants/float64/fourth_pi.h" +#include "stdlib/constants/float64/nan.h" #include static const double MOREBITS = 6.123233995736765886130e-17; // pi/2 = PIO2 + MOREBITS @@ -165,7 +166,7 @@ double stdlib_base_asin( const double x ) { double z; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x > 0.0 ) { sgn = 0; @@ -175,7 +176,7 @@ double stdlib_base_asin( const double x ) { a = -x; } if ( a > 1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( a > 0.625 ) { // arcsin(1-x) = pi/2 - sqrt(2x)(1+R(x)) diff --git a/lib/node_modules/@stdlib/math/base/special/asin/test/test.js b/lib/node_modules/@stdlib/math/base/special/asin/test/test.js index a896e206c6bc..c6db08cd3815 100644 --- a/lib/node_modules/@stdlib/math/base/special/asin/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/asin/test/test.js @@ -24,7 +24,7 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var randu = require( '@stdlib/random/base/randu' ); var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); var asin = require( './../lib' ); @@ -47,8 +47,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function computes the arcsine', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -58,21 +56,13 @@ tape( 'the function computes the arcsine', function test( t ) { for ( i = 0; i < x.length; i++ ) { y = asin( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the arcsine (small negative values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -82,21 +72,13 @@ tape( 'the function computes the arcsine (small negative values)', function test for ( i = 0; i < x.length; i++ ) { y = asin( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the arcsine (small positive values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -106,13 +88,7 @@ tape( 'the function computes the arcsine (small positive values)', function test for ( i = 0; i < x.length; i++ ) { y = asin( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/asin/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/asin/test/test.native.js index aa90cce3e475..3429912504ab 100644 --- a/lib/node_modules/@stdlib/math/base/special/asin/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/asin/test/test.native.js @@ -26,7 +26,7 @@ var isnan = require( '@stdlib/math/base/assert/is-nan' ); var randu = require( '@stdlib/random/base/randu' ); var tryRequire = require( '@stdlib/utils/try-require' ); var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); @@ -56,8 +56,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function computes the arcsine', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -67,21 +65,13 @@ tape( 'the function computes the arcsine', opts, function test( t ) { for ( i = 0; i < x.length; i++ ) { y = asin( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the arcsine (small negative values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -91,21 +81,13 @@ tape( 'the function computes the arcsine (small negative values)', opts, functio for ( i = 0; i < x.length; i++ ) { y = asin( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the arcsine (small positive values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -115,13 +97,7 @@ tape( 'the function computes the arcsine (small positive values)', opts, functio for ( i = 0; i < x.length; i++ ) { y = asin( x[i] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/atan2/manifest.json b/lib/node_modules/@stdlib/math/base/special/atan2/manifest.json index be476ede25fb..b37fe7cd3617 100755 --- a/lib/node_modules/@stdlib/math/base/special/atan2/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/atan2/manifest.json @@ -43,7 +43,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/atan", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -63,7 +64,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/atan", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -83,7 +85,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/atan", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/atan2/src/main.c b/lib/node_modules/@stdlib/math/base/special/atan2/src/main.c index 228c30752179..5b742c377182 100755 --- a/lib/node_modules/@stdlib/math/base/special/atan2/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/atan2/src/main.c @@ -37,6 +37,7 @@ #include "stdlib/math/base/special/atan.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/pi.h" +#include "stdlib/constants/float64/nan.h" #include /** @@ -81,7 +82,7 @@ double stdlib_base_atan2( const double y, const double x ) { double q; if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) ) { if ( x == STDLIB_CONSTANT_FLOAT64_PINF ) { diff --git a/lib/node_modules/@stdlib/math/base/special/atan2/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/atan2/test/test.native.js index 4bdd9899b0e6..2f3a3db1f619 100755 --- a/lib/node_modules/@stdlib/math/base/special/atan2/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/atan2/test/test.native.js @@ -25,9 +25,8 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var tryRequire = require( '@stdlib/utils/try-require' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); var PI = require( '@stdlib/constants/float64/pi' ); @@ -196,8 +195,6 @@ tape( 'the function returns `-PI/2` if provided a negative `y` and `x=-0`', opts tape( 'the function evaluates the `atan2` function (when x and y are positive)', opts, function test( t ) { var expected; var actual; - var delta; - var tol; var x; var y; var i; @@ -207,9 +204,7 @@ tape( 'the function evaluates the `atan2` function (when x and y are positive)', expected = positivePositive.expected; for ( i = 0; i < x.length; i++ ) { actual = atan2( y[i], x[i] ); - delta = abs( actual - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. y: '+y[i]+'. x: '+x[i]+'. Actual: '+actual+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( actual, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); @@ -217,8 +212,6 @@ tape( 'the function evaluates the `atan2` function (when x and y are positive)', tape( 'the function evaluates the `atan2` function (when x is negative and y is positive)', opts, function test( t ) { var expected; var actual; - var delta; - var tol; var x; var y; var i; @@ -228,9 +221,7 @@ tape( 'the function evaluates the `atan2` function (when x is negative and y is expected = negativePositive.expected; for ( i = 0; i < x.length; i++ ) { actual = atan2( y[i], x[i] ); - delta = abs( actual - expected[i] ); - tol = 2.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. y: '+y[i]+'. x: '+x[i]+'. Actual: '+actual+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( actual, expected[ i ], 2 ), true, 'returns expected value' ); } t.end(); }); @@ -238,8 +229,6 @@ tape( 'the function evaluates the `atan2` function (when x is negative and y is tape( 'the function evaluates the `atan2` function (when x and y are negative)', opts, function test( t ) { var expected; var actual; - var delta; - var tol; var x; var y; var i; @@ -249,9 +238,7 @@ tape( 'the function evaluates the `atan2` function (when x and y are negative)', expected = negativeNegative.expected; for ( i = 0; i < x.length; i++ ) { actual = atan2( y[i], x[i] ); - delta = abs( actual - expected[i] ); - tol = 2.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. y: '+y[i]+'. x: '+x[i]+'. Actual: '+actual+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( actual, expected[ i ], 2 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/atanh/manifest.json b/lib/node_modules/@stdlib/math/base/special/atanh/manifest.json index 4678a491a177..b306081da595 100644 --- a/lib/node_modules/@stdlib/math/base/special/atanh/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/atanh/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/atanh/src/main.c b/lib/node_modules/@stdlib/math/base/special/atanh/src/main.c index 954b9f671f17..6dc9e0ab3b9d 100644 --- a/lib/node_modules/@stdlib/math/base/special/atanh/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/atanh/src/main.c @@ -35,6 +35,7 @@ #include "stdlib/math/base/special/log1p.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include static const double NEAR_ZERO = 1.0 / (1 << 28); // 2**-28 @@ -83,7 +84,7 @@ double stdlib_base_atanh( const double x ) { double ax; double t; if ( stdlib_base_is_nan( x ) || x < -1.0 || x > 1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 1.0 ) { return STDLIB_CONSTANT_FLOAT64_PINF; diff --git a/lib/node_modules/@stdlib/math/base/special/bernoulli/manifest.json b/lib/node_modules/@stdlib/math/base/special/bernoulli/manifest.json index e8352697c730..3180f59fe901 100644 --- a/lib/node_modules/@stdlib/math/base/special/bernoulli/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/bernoulli/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/assert/is-odd", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", - "@stdlib/math/base/assert/is-nonnegative-integer" + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/assert/is-odd", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", - "@stdlib/math/base/assert/is-nonnegative-integer" + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/assert/is-odd", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", - "@stdlib/math/base/assert/is-nonnegative-integer" + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/bernoulli/src/main.c b/lib/node_modules/@stdlib/math/base/special/bernoulli/src/main.c index b1eb3203f5bd..c8aeaa89e989 100644 --- a/lib/node_modules/@stdlib/math/base/special/bernoulli/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/bernoulli/src/main.c @@ -20,6 +20,7 @@ #include "stdlib/math/base/assert/is_odd.h" #include "stdlib/constants/float64/ninf.h" #include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/bernoulli.h" #include #include @@ -172,7 +173,7 @@ int32_t MAX_BERNOULLI = 258; */ double stdlib_base_bernoulli( const double n ) { if ( !stdlib_base_is_nonnegative_integer( n ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( n == 1.0 ) { return 0.5; diff --git a/lib/node_modules/@stdlib/math/base/special/bessely0/manifest.json b/lib/node_modules/@stdlib/math/base/special/bessely0/manifest.json index 0f5c4b1295c2..4795c8012d8c 100644 --- a/lib/node_modules/@stdlib/math/base/special/bessely0/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/bessely0/manifest.json @@ -44,7 +44,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/sqrt-pi" + "@stdlib/constants/float64/sqrt-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/sqrt-pi" + "@stdlib/constants/float64/sqrt-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/sqrt-pi" + "@stdlib/constants/float64/sqrt-pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/bessely0/src/main.c b/lib/node_modules/@stdlib/math/base/special/bessely0/src/main.c index 9eb39650b1f1..51db37ff3fa0 100644 --- a/lib/node_modules/@stdlib/math/base/special/bessely0/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/bessely0/src/main.c @@ -38,6 +38,7 @@ #include "stdlib/constants/float64/ninf.h" #include "stdlib/constants/float64/pi.h" #include "stdlib/constants/float64/sqrt_pi.h" +#include "stdlib/constants/float64/nan.h" static const double ONE_DIV_SQRT_PI = 1.0 / STDLIB_CONSTANT_FLOAT64_SQRT_PI; static const double TWO_DIV_PI = 2.0 / STDLIB_CONSTANT_FLOAT64_PI; @@ -287,7 +288,7 @@ double stdlib_base_bessely0( const double x ) { double z; if ( x < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 0.0 ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/bessely1/manifest.json b/lib/node_modules/@stdlib/math/base/special/bessely1/manifest.json index aae8696944f8..524dcf064741 100644 --- a/lib/node_modules/@stdlib/math/base/special/bessely1/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/bessely1/manifest.json @@ -44,7 +44,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/sqrt-pi" + "@stdlib/constants/float64/sqrt-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/sqrt-pi" + "@stdlib/constants/float64/sqrt-pi", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/sqrt-pi" + "@stdlib/constants/float64/sqrt-pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/bessely1/src/main.c b/lib/node_modules/@stdlib/math/base/special/bessely1/src/main.c index 62fcc640dc1b..0560893abc62 100644 --- a/lib/node_modules/@stdlib/math/base/special/bessely1/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/bessely1/src/main.c @@ -40,6 +40,7 @@ #include "stdlib/constants/float64/ninf.h" #include "stdlib/constants/float64/pi.h" #include "stdlib/constants/float64/sqrt_pi.h" +#include "stdlib/constants/float64/nan.h" static const double ONE_DIV_SQRT_PI = 1.0 / STDLIB_CONSTANT_FLOAT64_SQRT_PI; static const double TWO_DIV_PI = 2.0 / STDLIB_CONSTANT_FLOAT64_PI; @@ -244,7 +245,7 @@ double stdlib_base_bessely1( double x ) { double f; if ( x < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 0.0 ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/beta/manifest.json b/lib/node_modules/@stdlib/math/base/special/beta/manifest.json index 64b2a1183de5..e2631db7f4aa 100644 --- a/lib/node_modules/@stdlib/math/base/special/beta/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/beta/manifest.json @@ -44,7 +44,8 @@ "@stdlib/math/base/special/exp", "@stdlib/math/base/special/pow", "@stdlib/constants/float64/e", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/math/base/special/exp", "@stdlib/math/base/special/pow", "@stdlib/constants/float64/e", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/math/base/special/exp", "@stdlib/math/base/special/pow", "@stdlib/constants/float64/e", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/beta/src/main.c b/lib/node_modules/@stdlib/math/base/special/beta/src/main.c index cd7f2ae5de8f..20c10aa455fe 100644 --- a/lib/node_modules/@stdlib/math/base/special/beta/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/beta/src/main.c @@ -38,6 +38,7 @@ #include "stdlib/math/base/special/pow.h" #include "stdlib/constants/float64/e.h" #include "stdlib/constants/float64/eps.h" +#include "stdlib/constants/float64/nan.h" static const double G = 10.90051099999999983936049829935654997826; @@ -109,10 +110,10 @@ double stdlib_base_beta( const double a, const double b ) { double c; if ( stdlib_base_is_nan( a ) || stdlib_base_is_nan( b ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( a < 0.0 || b < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( b == 1.0 ) { return 1.0 / a; diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/README.md b/lib/node_modules/@stdlib/math/base/special/betainc/README.md index 73b777db6387..5d3a7fcb828c 100644 --- a/lib/node_modules/@stdlib/math/base/special/betainc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/betainc/README.md @@ -120,6 +120,106 @@ logEachMap( 'x: %0.4f, \t a: %0.4f, \t b: %0.4f, \t f(x,a,b): %0.4f', x, a, b, b + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/math/base/special/betainc.h" +``` + +#### stdlib_base_betainc( x, a, b, regularized, upper ) + +Evaluates the incomplete beta function. + +```c +double y = stdlib_base_betainc( 0.5, 2.0, 2.0, true, false ); +// returns 0.5 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` function parameter. +- **a**: `[in] double` function parameter. +- **b**: `[in] double` function parameter. +- **regularized**: `[in] bool` indicating if the function should evaluate the regularized incomplete beta function. +- **upper**: `[in] bool` indicating if the function should return the upper tail of the incomplete beta function. + +```c +double stdlib_base_betainc( const double x, const double a, const double b, const bool regularized, const bool upper ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/math/base/special/betainc.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double a; + double b; + double v; + int i; + + for ( i = 0; i < 100; i++ ) { + x = random_uniform( 0.0, 1.0 ); + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( 0.0, 10.0 ); + v = stdlib_base_betainc( x, a, b, true, false ); + printf( "x: %lf, a: %lf, b: %lf, f(x,a,b): %lf\n", x, a, b, v ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/benchmark.js index 105edd62d979..dc8937bd452a 100644 --- a/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/benchmark.js @@ -31,15 +31,19 @@ var betainc = require( './../lib' ); // MAIN // bench( pkg, function benchmark( assert ) { + var opts; var x; var y; var a; var b; var i; - x = uniform( 100, 0.0, 1.0 ); - a = uniform( 100, EPS, 1000.0 ); - b = uniform( 100, EPS, 1000.0 ); + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 1.0, opts ); + a = uniform( 100, EPS, 1000.0, opts ); + b = uniform( 100, EPS, 1000.0, opts ); assert.tic(); for ( i = 0; i < assert.iterations; i++ ) { diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/benchmark.native.js new file mode 100644 index 000000000000..798535deb6a6 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/benchmark.native.js @@ -0,0 +1,161 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var betainc = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( betainc instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native:regularized=true,upper=true', pkg ), opts, function benchmark( assert ) { + var arrayOpts; + var x; + var y; + var a; + var b; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 1.0, arrayOpts ); + a = uniform( 100, EPS, 1000.0, arrayOpts ); + b = uniform( 100, EPS, 1000.0, arrayOpts ); + + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + y = betainc( x[ i % x.length ], a[ i % a.length ], b[ i % b.length ], true, true ); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); + +bench( format( '%s::native:regularized=true,upper=false', pkg ), opts, function benchmark( assert ) { + var arrayOpts; + var x; + var y; + var a; + var b; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 1.0, arrayOpts ); + a = uniform( 100, EPS, 1000.0, arrayOpts ); + b = uniform( 100, EPS, 1000.0, arrayOpts ); + + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + y = betainc( x[ i % x.length ], a[ i % a.length ], b[ i % b.length ], true, false ); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); + +bench( format( '%s::native:regularized=false,upper=true', pkg ), opts, function benchmark( assert ) { + var arrayOpts; + var x; + var y; + var a; + var b; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 1.0, arrayOpts ); + a = uniform( 100, EPS, 1000.0, arrayOpts ); + b = uniform( 100, EPS, 1000.0, arrayOpts ); + + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + y = betainc( x[ i % x.length ], a[ i % a.length ], b[ i % b.length ], false, true ); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); + +bench( format( '%s::native:regularized=false,upper=false', pkg ), opts, function benchmark( assert ) { + var arrayOpts; + var x; + var y; + var a; + var b; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 1.0, arrayOpts ); + a = uniform( 100, EPS, 1000.0, arrayOpts ); + b = uniform( 100, EPS, 1000.0, arrayOpts ); + + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + y = betainc( x[ i % x.length ], a[ i % a.length ], b[ i % b.length ], false, false ); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( y ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/c/native/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..adfab5f8c5c9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/benchmark/c/native/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/betainc.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "betainc" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double x[ 100 ]; + double a[ 100 ]; + double b[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0.0, 1.0 ); + a[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 1000.0 ); + b[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 1000.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_betainc( x[ i % 100 ], a[ i % 100 ], b[ i % 100 ], true, false ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/binding.gyp b/lib/node_modules/@stdlib/math/base/special/betainc/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/betainc/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/betainc/examples/c/example.c new file mode 100644 index 000000000000..a9a35d3f26f3 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/betainc.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double a; + double b; + double v; + int i; + + for ( i = 0; i < 100; i++ ) { + x = random_uniform( 0.0, 1.0 ); + a = random_uniform( 0.0, 10.0 ); + b = random_uniform( 0.0, 10.0 ); + v = stdlib_base_betainc( x, a, b, true, false ); + printf( "x: %lf, a: %lf, b: %lf, f(x,a,b): %lf\n", x, a, b, v ); + } +} diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/include.gypi b/lib/node_modules/@stdlib/math/base/special/betainc/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Evaluates the incomplete beta function. +*/ +double stdlib_base_betainc( const double x, const double a, const double b, const bool regularized, const bool upper ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_MATH_BASE_SPECIAL_BETAINC_H diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/lib/native.js b/lib/node_modules/@stdlib/math/base/special/betainc/lib/native.js new file mode 100644 index 000000000000..fa794fb502b5 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/lib/native.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Evaluates the incomplete beta function. +* +* @private +* @param {Probability} x - function parameter +* @param {NonNegativeNumber} a - function parameter +* @param {NonNegativeNumber} b - function parameter +* @param {boolean} [regularized=true] - boolean indicating if the function should evaluate the regularized or non-regularized incomplete beta function +* @param {boolean} [upper=false] - boolean indicating if the function should return the upper tail of the incomplete beta function +* @returns {number} function value +* +* @example +* var y = betainc( 0.5, 2.0, 2.0 ); +* // returns 0.5 +* +* @example +* var y = betainc( 0.5, 2.0, 2.0, false ); +* // returns ~0.083 +* +* @example +* var y = betainc( 0.2, 1.0, 2.0 ); +* // returns 0.36 +*/ +function betainc( x, a, b, regularized, upper ) { + regularized = ( regularized === false ) ? false : true; // eslint-disable-line no-unneeded-ternary + upper = ( upper === true ) ? true : false; // eslint-disable-line no-unneeded-ternary + return addon( x, a, b, regularized, upper ); +} + + +// EXPORTS // + +module.exports = betainc; diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/manifest.json b/lib/node_modules/@stdlib/math/base/special/betainc/manifest.json new file mode 100644 index 000000000000..db5f96f93e5f --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/manifest.json @@ -0,0 +1,77 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-bool", + "@stdlib/napi/create-double", + "@stdlib/math/base/special/kernel-betainc" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/kernel-betainc", + "@stdlib/constants/float64/eps" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/special/kernel-betainc" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/package.json b/lib/node_modules/@stdlib/math/base/special/betainc/package.json index e10af830ef5c..54490fe7877a 100644 --- a/lib/node_modules/@stdlib/math/base/special/betainc/package.json +++ b/lib/node_modules/@stdlib/math/base/special/betainc/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/src/Makefile b/lib/node_modules/@stdlib/math/base/special/betainc/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/src/addon.c b/lib/node_modules/@stdlib/math/base/special/betainc/src/addon.c new file mode 100644 index 000000000000..b24abec1a217 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/src/addon.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/betainc.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_bool.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/create_double.h" +#include "stdlib/napi/export.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 5 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, a, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, b, argv, 2 ); + STDLIB_NAPI_ARGV_BOOL( env, regularized, argv, 3 ); + STDLIB_NAPI_ARGV_BOOL( env, upper, argv, 4 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_base_betainc( x, a, b, regularized, upper ), out ); + return out; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/src/main.c b/lib/node_modules/@stdlib/math/base/special/betainc/src/main.c new file mode 100644 index 000000000000..75f55463a082 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/src/main.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/betainc.h" +#include "stdlib/math/base/special/kernel_betainc.h" +#include + +/** +* Evaluates the incomplete beta function. +* +* @param x function parameter +* @param a function parameter +* @param b function parameter +* @param regularized boolean indicating if the function should evaluate the regularized or non-regularized incomplete beta function +* @param upper boolean indicating if the function should return the upper tail of the incomplete beta function +* @return function value +* +* @example +* double y = stdlib_base_betainc( 0.5, 2.0, 2.0, true, false ); +* // returns 0.5 +*/ +double stdlib_base_betainc( const double x, const double a, const double b, const bool regularized, const bool upper ) { + double derivative; + double out; + + stdlib_base_kernel_betainc( x, a, b, regularized, upper, &out, &derivative ); + return out; +} diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/test/test.js b/lib/node_modules/@stdlib/math/base/special/betainc/test/test.js index b839f64be596..be9ac09f4cf3 100644 --- a/lib/node_modules/@stdlib/math/base/special/betainc/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/betainc/test/test.js @@ -22,8 +22,7 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); -var EPS = require( '@stdlib/constants/float64/eps' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var betainc = require( './../lib' ); @@ -71,84 +70,52 @@ tape( 'the function returns `NaN` negative `a` or `b`', function test( t ) { tape( 'the function evaluates the lower regularized incomplete beta function', function test( t ) { var expected; - var delta; - var tol; var i; var y; expected = lowerRegularized; for ( i = 0; i < x.length; i++ ) { y = betainc( x[i], a[i], b[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+'. a: '+a[i]+'. b: '+b[i]+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 50.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 85 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the lower unregularized incomplete beta function', function test( t ) { var expected; - var delta; - var tol; var i; var y; expected = lowerUnregularized; for ( i = 0; i < x.length; i++ ) { y = betainc( x[i], a[i], b[i], false ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+'. a: '+a[i]+'. b: '+b[i]+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 80.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 100 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the upper regularized incomplete beta function', function test( t ) { var expected; - var delta; - var tol; var i; var y; expected = upperRegularized; for ( i = 0; i < x.length; i++ ) { y = betainc( x[i], a[i], b[i], true, true ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+'. a: '+a[i]+'. b: '+b[i]+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 50.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 75 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function evaluates the upper unregularized incomplete beta function', function test( t ) { var expected; - var delta; - var tol; var i; var y; expected = upperUnregularized; for ( i = 0; i < x.length; i++ ) { y = betainc( x[i], a[i], b[i], false, true ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+'. a: '+a[i]+'. b: '+b[i]+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = 80.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. a: '+a[i]+'. b: '+b[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 120 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/betainc/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/betainc/test/test.native.js new file mode 100644 index 000000000000..1c5c1106a94b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/betainc/test/test.native.js @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); + + +// VARIABLES // + +var betainc = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( betainc instanceof Error ) +}; + + +// FIXTURES // + +var fixtures = require( './fixtures/cpp/output.json' ); +var lowerRegularized = fixtures.lower_regularized; +var lowerUnregularized = fixtures.lower_unregularized; +var upperRegularized = fixtures.upper_regularized; +var upperUnregularized = fixtures.upper_unregularized; +var x = fixtures.x; +var a = fixtures.a; +var b = fixtures.b; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof betainc, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `NaN` if `x` is outside `[0,1]`', opts, function test( t ) { + var val = betainc( -0.2, 1.0, 1.0 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + val = betainc( 1.1, 1.0, 1.0 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `NaN` negative `a` or `b`', opts, function test( t ) { + var val = betainc( 0.5, -1.0, 1.0 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + val = betainc( 0.5, 1.0, -1.0 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + val = betainc( 0.5, -1.0, -1.0 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function', opts, function test( t ) { + var expected; + var i; + var y; + + expected = lowerRegularized; + for ( i = 0; i < x.length; i++ ) { + y = betainc( x[i], a[i], b[i] ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 85 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function', opts, function test( t ) { + var expected; + var i; + var y; + + expected = lowerUnregularized; + for ( i = 0; i < x.length; i++ ) { + y = betainc( x[i], a[i], b[i], false ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 100 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function', opts, function test( t ) { + var expected; + var i; + var y; + + expected = upperRegularized; + for ( i = 0; i < x.length; i++ ) { + y = betainc( x[i], a[i], b[i], true, true ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 75 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function', opts, function test( t ) { + var expected; + var i; + var y; + + expected = upperUnregularized; + for ( i = 0; i < x.length; i++ ) { + y = betainc( x[i], a[i], b[i], false, true ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 120 ), true, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/betaln/manifest.json b/lib/node_modules/@stdlib/math/base/special/betaln/manifest.json index 8b449c8c22b4..85367e5c2107 100644 --- a/lib/node_modules/@stdlib/math/base/special/betaln/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/betaln/manifest.json @@ -46,7 +46,8 @@ "@stdlib/math/base/special/ln", "@stdlib/constants/float64/ln-sqrt-two-pi", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -69,7 +70,8 @@ "@stdlib/math/base/special/ln", "@stdlib/constants/float64/ln-sqrt-two-pi", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -92,7 +94,8 @@ "@stdlib/math/base/special/ln", "@stdlib/constants/float64/ln-sqrt-two-pi", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/betaln/src/main.c b/lib/node_modules/@stdlib/math/base/special/betaln/src/main.c index bd0acbe283e8..c0bc26793b46 100644 --- a/lib/node_modules/@stdlib/math/base/special/betaln/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/betaln/src/main.c @@ -34,6 +34,7 @@ #include "stdlib/constants/float64/ln_sqrt_two_pi.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include static const double ALGMCS[ 15 ] = { @@ -76,7 +77,7 @@ static double dceval( const double x ) { int32_t i; if ( x < -1.1 || x > 1.1 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } b1 = 0.0; b0 = 0.0; @@ -101,7 +102,7 @@ static double dceval( const double x ) { */ static double gammaCorrection( const double x ) { if ( x < 10.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Check for underflow... @@ -134,7 +135,7 @@ double stdlib_base_betaln( const double a, const double b ) { q = stdlib_base_max( a, b ); if ( p < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( p == 0.0 ) { return STDLIB_CONSTANT_FLOAT64_PINF; diff --git a/lib/node_modules/@stdlib/math/base/special/binet/manifest.json b/lib/node_modules/@stdlib/math/base/special/binet/manifest.json index b9595c178516..4a78423ff8cd 100644 --- a/lib/node_modules/@stdlib/math/base/special/binet/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/binet/manifest.json @@ -42,7 +42,8 @@ "@stdlib/math/base/special/pow", "@stdlib/constants/float64/phi", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/math/base/special/pow", "@stdlib/constants/float64/phi", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/math/base/special/pow", "@stdlib/constants/float64/phi", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/binet/src/main.c b/lib/node_modules/@stdlib/math/base/special/binet/src/main.c index 07f470b67ac4..63f6acaeea0d 100644 --- a/lib/node_modules/@stdlib/math/base/special/binet/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/binet/src/main.c @@ -23,6 +23,7 @@ #include "stdlib/constants/float64/phi.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" static const double SQRT_5 = 2.23606797749979; @@ -49,7 +50,7 @@ double stdlib_base_binet( const double x ) { double b; if ( stdlib_base_is_nan( x ) || x == STDLIB_CONSTANT_FLOAT64_PINF || x == STDLIB_CONSTANT_FLOAT64_NINF ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } a = stdlib_base_pow( STDLIB_CONSTANT_FLOAT64_PHI, x ); b = stdlib_base_cospi( x ) / a; diff --git a/lib/node_modules/@stdlib/math/base/special/binomcoef/manifest.json b/lib/node_modules/@stdlib/math/base/special/binomcoef/manifest.json index 7b8ffed68392..fe3b44db9727 100644 --- a/lib/node_modules/@stdlib/math/base/special/binomcoef/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/binomcoef/manifest.json @@ -44,7 +44,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/max-safe-integer", "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-odd" + "@stdlib/math/base/assert/is-odd", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/max-safe-integer", "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-odd" + "@stdlib/math/base/assert/is-odd", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/max-safe-integer", "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-odd" + "@stdlib/math/base/assert/is-odd", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/binomcoef/src/main.c b/lib/node_modules/@stdlib/math/base/special/binomcoef/src/main.c index fd33fc6f8b0d..12326a367fda 100644 --- a/lib/node_modules/@stdlib/math/base/special/binomcoef/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/binomcoef/src/main.c @@ -23,6 +23,7 @@ #include "stdlib/math/base/special/gcd.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/max_safe_integer.h" +#include "stdlib/constants/float64/nan.h" /** * Computes the binomial coefficient of two integers. @@ -47,7 +48,7 @@ double stdlib_base_binomcoef( const double n, const double k ) { double s; if ( !stdlib_base_is_integer( n ) || !stdlib_base_is_integer( k ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( k < 0 ) { diff --git a/lib/node_modules/@stdlib/math/base/special/binomcoefln/manifest.json b/lib/node_modules/@stdlib/math/base/special/binomcoefln/manifest.json index 6d00652ac194..6938e86c2944 100644 --- a/lib/node_modules/@stdlib/math/base/special/binomcoefln/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/binomcoefln/manifest.json @@ -43,7 +43,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/ln", "@stdlib/constants/float64/ninf", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -63,7 +64,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/ln", "@stdlib/constants/float64/ninf", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -83,7 +85,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/ln", "@stdlib/constants/float64/ninf", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/binomcoefln/src/main.c b/lib/node_modules/@stdlib/math/base/special/binomcoefln/src/main.c index 1383054e43b8..df42856acf90 100644 --- a/lib/node_modules/@stdlib/math/base/special/binomcoefln/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/binomcoefln/src/main.c @@ -22,6 +22,7 @@ #include "stdlib/math/base/special/abs.h" #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" /** * Computes the natural logarithm of the binomial coefficient of two integers. @@ -36,7 +37,7 @@ */ double stdlib_base_binomcoefln( const double n, const double k ) { if ( !stdlib_base_is_integer( n ) || !stdlib_base_is_integer( k ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( n < 0 ) { return stdlib_base_binomcoefln( -n + k - 1, k ); diff --git a/lib/node_modules/@stdlib/math/base/special/boxcox/manifest.json b/lib/node_modules/@stdlib/math/base/special/boxcox/manifest.json index 464a6b0dc65d..c32050a85727 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcox/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/boxcox/manifest.json @@ -42,7 +42,8 @@ "@stdlib/math/base/assert/is-positive-zero", "@stdlib/math/base/special/ln", "@stdlib/math/base/special/expm1", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/math/base/assert/is-positive-zero", "@stdlib/math/base/special/ln", "@stdlib/math/base/special/expm1", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/math/base/assert/is-positive-zero", "@stdlib/math/base/special/ln", "@stdlib/math/base/special/expm1", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/boxcox/src/main.c b/lib/node_modules/@stdlib/math/base/special/boxcox/src/main.c index 1def199b1e2c..aa7fb9b7afa4 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcox/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/boxcox/src/main.c @@ -23,6 +23,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/math/base/special/expm1.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" /** * Computes a one-parameter Box-Cox transformation. @@ -43,7 +44,7 @@ */ double stdlib_base_boxcox( const double x, const double lambda ) { if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( lambda ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_positive_zero( x ) && lambda < 0.0 ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/boxcox1p/manifest.json b/lib/node_modules/@stdlib/math/base/special/boxcox1p/manifest.json index ccc37a013671..0004c8a0f759 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcox1p/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/boxcox1p/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/expm1", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/expm1", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/expm1", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/boxcox1p/src/main.c b/lib/node_modules/@stdlib/math/base/special/boxcox1p/src/main.c index 6aceb3a5c228..9921c0a10c25 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcox1p/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/boxcox1p/src/main.c @@ -22,6 +22,7 @@ #include "stdlib/math/base/special/log1p.h" #include "stdlib/math/base/special/expm1.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" /** * Computes a one-parameter Box-Cox transformation of `1+x`. @@ -38,7 +39,7 @@ double stdlib_base_boxcox1p( const double x, const double lambda ) { double lgx; if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( lambda ) || x < -1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == -1.0 && lambda < 0.0 ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/manifest.json b/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/manifest.json index a54b735fc6bb..d50b595987be 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/special/expm1" + "@stdlib/math/base/special/expm1", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/special/expm1" + "@stdlib/math/base/special/expm1", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/special/expm1" + "@stdlib/math/base/special/expm1", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/src/main.c b/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/src/main.c index 34f8e87e6802..4b07d856aa54 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/boxcox1pinv/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/boxcox1pinv.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/expm1.h" #include "stdlib/math/base/special/log1p.h" #include "stdlib/math/base/special/abs.h" @@ -37,7 +38,7 @@ double stdlib_base_boxcox1pinv( const double y, const double lambda ) { double ly; if ( stdlib_base_is_nan( y ) || stdlib_base_is_nan( lambda ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( lambda == 0.0 ) { return stdlib_base_expm1( y ); diff --git a/lib/node_modules/@stdlib/math/base/special/boxcoxinv/manifest.json b/lib/node_modules/@stdlib/math/base/special/boxcoxinv/manifest.json index 0c074e7620e8..4c6fef4cf5c1 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcoxinv/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/boxcoxinv/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/binary", "@stdlib/math/base/special/exp", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/special/exp", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/special/exp", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/boxcoxinv/src/main.c b/lib/node_modules/@stdlib/math/base/special/boxcoxinv/src/main.c index 481e82e9edb4..32f8ba28e85a 100644 --- a/lib/node_modules/@stdlib/math/base/special/boxcoxinv/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/boxcoxinv/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/boxcoxinv.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/exp.h" #include "stdlib/math/base/special/log1p.h" #include "stdlib/math/base/assert/is_nan.h" @@ -34,7 +35,7 @@ */ double stdlib_base_boxcoxinv( const double y, const double lambda ) { if ( stdlib_base_is_nan( y ) || stdlib_base_is_nan( lambda ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( lambda == 0.0 ) { return stdlib_base_exp( y ); diff --git a/lib/node_modules/@stdlib/math/base/special/cabs2/README.md b/lib/node_modules/@stdlib/math/base/special/cabs2/README.md index adc6fc65849a..73d6aecd8c3e 100644 --- a/lib/node_modules/@stdlib/math/base/special/cabs2/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cabs2/README.md @@ -83,8 +83,6 @@ var y = cabs2( new Complex128( 5.0, 3.0 ) ); ## Examples - - ```javascript diff --git a/lib/node_modules/@stdlib/math/base/special/cabs2f/README.md b/lib/node_modules/@stdlib/math/base/special/cabs2f/README.md index 791ff508ad3b..db7515073a24 100644 --- a/lib/node_modules/@stdlib/math/base/special/cabs2f/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cabs2f/README.md @@ -83,8 +83,6 @@ var y = cabs2f( new Complex64( 5.0, 3.0 ) ); ## Examples - - ```javascript diff --git a/lib/node_modules/@stdlib/math/base/special/cabsf/README.md b/lib/node_modules/@stdlib/math/base/special/cabsf/README.md index 287e9f4e478f..55c9836bff20 100644 --- a/lib/node_modules/@stdlib/math/base/special/cabsf/README.md +++ b/lib/node_modules/@stdlib/math/base/special/cabsf/README.md @@ -72,8 +72,6 @@ var y = cabsf( new Complex64( 5.0, 3.0 ) ); ## Examples - - ```javascript diff --git a/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.js b/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.js index 30cbb6a374a3..870236bbfe80 100644 --- a/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.js @@ -26,8 +26,7 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var PINF = require( '@stdlib/constants/float32/pinf' ); var NINF = require( '@stdlib/constants/float32/ninf' ); -var EPS = require( '@stdlib/constants/float32/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValuef = require( '@stdlib/number/float32/base/assert/is-almost-same-value' ); var cbrtf = require( './../lib' ); @@ -59,8 +58,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function evaluates the cubic root of `x` on the interval `[-50,-500]', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -72,9 +69,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-50,-500]' if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -82,8 +77,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-50,-500]' tape( 'the function evaluates the cubic root of `x` on the interval `[50,500]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -95,9 +88,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[50,500]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -105,8 +96,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[50,500]`', tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-50]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -118,9 +107,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-50]`' if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -128,8 +115,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-50]`' tape( 'the function evaluates the cubic root of `x` on the interval `[20,50]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -141,9 +126,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[20,50]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -151,8 +134,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[20,50]`', tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-3]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -164,9 +145,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-3]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -174,8 +153,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-3]`', tape( 'the function evaluates the cubic root of `x` on the interval `[3,20]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -187,9 +164,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[3,20]`', f if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -197,8 +172,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[3,20]`', f tape( 'the function evaluates the cubic root of `x` on the interval `[-3,-0.8]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -210,9 +183,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-3,-0.8]`' if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -220,8 +191,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-3,-0.8]`' tape( 'the function evaluates the cubic root of `x` on the interval `[0.8,3]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -233,9 +202,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[0.8,3]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -243,8 +210,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[0.8,3]`', tape( 'the function evaluates cubic root of `x` on the interval `[-0.8,0.8]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -256,9 +221,7 @@ tape( 'the function evaluates cubic root of `x` on the interval `[-0.8,0.8]`', f if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -266,8 +229,6 @@ tape( 'the function evaluates cubic root of `x` on the interval `[-0.8,0.8]`', f tape( 'the function evaluates the cubic root of `x` on the interval `[-1e-300,-1e-308]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -279,9 +240,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-1e-300,-1 if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -289,8 +248,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-1e-300,-1 tape( 'the function evaluates the cubic root of `x` on the interval `[1e-300,1e-308]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -302,9 +259,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[1e-300,1e- if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -312,8 +267,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[1e-300,1e- tape( 'the function evaluates the cubic root of subnormal `x`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -325,9 +278,7 @@ tape( 'the function evaluates the cubic root of subnormal `x`', function test( t if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -335,8 +286,6 @@ tape( 'the function evaluates the cubic root of subnormal `x`', function test( t tape( 'the function evaluates the cubic root of `x` (huge negative)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -349,9 +298,7 @@ tape( 'the function evaluates the cubic root of `x` (huge negative)', function t if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -359,8 +306,6 @@ tape( 'the function evaluates the cubic root of `x` (huge negative)', function t tape( 'the function evaluates the cubic root of `x` (huge positive)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -373,9 +318,7 @@ tape( 'the function evaluates the cubic root of `x` (huge positive)', function t if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.native.js index 6fe4957785ca..6f8a373d350c 100644 --- a/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/cbrtf/test/test.native.js @@ -27,8 +27,7 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' ); var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' ); var PINF = require( '@stdlib/constants/float32/pinf' ); var NINF = require( '@stdlib/constants/float32/ninf' ); -var EPS = require( '@stdlib/constants/float32/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValuef = require( '@stdlib/number/float32/base/assert/is-almost-same-value' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -68,8 +67,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function evaluates the cubic root of `x` on the interval `[-50,-500]', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -81,9 +78,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-50,-500]' if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -91,8 +86,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-50,-500]' tape( 'the function evaluates the cubic root of `x` on the interval `[50,500]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -104,9 +97,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[50,500]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -114,8 +105,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[50,500]`', tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-50]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -127,9 +116,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-50]`' if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -137,8 +124,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-50]`' tape( 'the function evaluates the cubic root of `x` on the interval `[20,50]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -150,9 +135,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[20,50]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -160,8 +143,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[20,50]`', tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-3]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -173,9 +154,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-3]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -183,8 +162,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-20,-3]`', tape( 'the function evaluates the cubic root of `x` on the interval `[3,20]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -196,9 +173,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[3,20]`', o if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -206,8 +181,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[3,20]`', o tape( 'the function evaluates the cubic root of `x` on the interval `[-3,-0.8]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -219,9 +192,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-3,-0.8]`' if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -229,8 +200,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-3,-0.8]`' tape( 'the function evaluates the cubic root of `x` on the interval `[0.8,3]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -242,9 +211,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[0.8,3]`', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -252,8 +219,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[0.8,3]`', tape( 'the function evaluates cubic root of `x` on the interval `[-0.8,0.8]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -265,9 +230,7 @@ tape( 'the function evaluates cubic root of `x` on the interval `[-0.8,0.8]`', o if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -275,8 +238,6 @@ tape( 'the function evaluates cubic root of `x` on the interval `[-0.8,0.8]`', o tape( 'the function evaluates the cubic root of `x` on the interval `[-1e-300,-1e-308]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -288,9 +249,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-1e-300,-1 if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -298,8 +257,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[-1e-300,-1 tape( 'the function evaluates the cubic root of `x` on the interval `[1e-300,1e-308]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -311,9 +268,7 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[1e-300,1e- if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -321,8 +276,6 @@ tape( 'the function evaluates the cubic root of `x` on the interval `[1e-300,1e- tape( 'the function evaluates the cubic root of subnormal `x`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -334,9 +287,7 @@ tape( 'the function evaluates the cubic root of subnormal `x`', opts, function t if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -344,8 +295,6 @@ tape( 'the function evaluates the cubic root of subnormal `x`', opts, function t tape( 'the function evaluates the cubic root of `x` (huge negative)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -358,9 +307,7 @@ tape( 'the function evaluates the cubic root of `x` (huge negative)', opts, func if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -368,8 +315,6 @@ tape( 'the function evaluates the cubic root of `x` (huge negative)', opts, func tape( 'the function evaluates the cubic root of `x` (huge positive)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -382,9 +327,7 @@ tape( 'the function evaluates the cubic root of `x` (huge positive)', opts, func if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol ); + t.strictEqual( isAlmostSameValuef( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/ceilb/manifest.json b/lib/node_modules/@stdlib/math/base/special/ceilb/manifest.json index 0ecff79da0d4..4ee3e4824ccc 100644 --- a/lib/node_modules/@stdlib/math/base/special/ceilb/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/ceilb/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/ceil", "@stdlib/math/base/special/ceiln", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/ceil", "@stdlib/math/base/special/ceiln", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/ceil", "@stdlib/math/base/special/ceiln", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/ceilb/src/main.c b/lib/node_modules/@stdlib/math/base/special/ceilb/src/main.c index fd3bb060f180..7b550c544f91 100644 --- a/lib/node_modules/@stdlib/math/base/special/ceilb/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/ceilb/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/ceilb.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/ceil.h" @@ -41,7 +42,7 @@ double stdlib_base_ceilb( const double x, const int32_t n, const int32_t b ) { double s; if ( stdlib_base_is_nan( x ) || b <= 0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/ceilsd/manifest.json b/lib/node_modules/@stdlib/math/base/special/ceilsd/manifest.json index 1b5e4b62f055..160ae05e6737 100644 --- a/lib/node_modules/@stdlib/math/base/special/ceilsd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/ceilsd/manifest.json @@ -45,7 +45,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/ceil", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -67,7 +68,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/ceil", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -89,7 +91,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/ceil", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/ceilsd/src/main.c b/lib/node_modules/@stdlib/math/base/special/ceilsd/src/main.c index 74065dd3715c..e1ee36218813 100644 --- a/lib/node_modules/@stdlib/math/base/special/ceilsd/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/ceilsd/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/ceilsd.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/pow.h" @@ -46,7 +47,7 @@ double stdlib_base_ceilsd( const double x, const int32_t n, const int32_t b ) { double y; if ( stdlib_base_is_nan( x ) || n < 1 || b <= 0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/cexp/manifest.json b/lib/node_modules/@stdlib/math/base/special/cexp/manifest.json index ddfa5646c158..759ce59d5adb 100644 --- a/lib/node_modules/@stdlib/math/base/special/cexp/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/cexp/manifest.json @@ -45,7 +45,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/copysign", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -67,7 +68,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/copysign", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -89,7 +91,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/copysign", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/cexp/src/main.c b/lib/node_modules/@stdlib/math/base/special/cexp/src/main.c index 44ef8126a47f..a144517293e4 100644 --- a/lib/node_modules/@stdlib/math/base/special/cexp/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/cexp/src/main.c @@ -24,6 +24,7 @@ #include "stdlib/constants/float64/pinf.h" #include "stdlib/math/base/special/copysign.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/complex/float64/ctor.h" #include "stdlib/complex/float64/reim.h" @@ -55,18 +56,18 @@ stdlib_complex128_t stdlib_base_cexp( const stdlib_complex128_t z ) { stdlib_complex128_reim( z, &re, &im ); if ( stdlib_base_is_nan( re ) ) { - re = 0.0 / 0.0; // NaN + re = STDLIB_CONSTANT_FLOAT64_NAN; im = ( im == 0.0 ) ? im : re; } else if ( stdlib_base_is_infinite( im ) ) { if ( re == STDLIB_CONSTANT_FLOAT64_PINF ) { re = -re; - im = 0.0 / 0.0; // NaN + im = STDLIB_CONSTANT_FLOAT64_NAN; } else if ( re == STDLIB_CONSTANT_FLOAT64_NINF ) { re = -0.0; im = stdlib_base_copysign( 0.0, im ); } else { - re = 0.0 / 0.0; // NaN - im = 0.0 / 0.0; // NaN + re = STDLIB_CONSTANT_FLOAT64_NAN; + im = STDLIB_CONSTANT_FLOAT64_NAN; } } else { e = stdlib_base_exp( re ); diff --git a/lib/node_modules/@stdlib/math/base/special/clamp/manifest.json b/lib/node_modules/@stdlib/math/base/special/clamp/manifest.json index a5c30237a9e4..f32c1f2e7f67 100644 --- a/lib/node_modules/@stdlib/math/base/special/clamp/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/clamp/manifest.json @@ -40,7 +40,8 @@ "dependencies": [ "@stdlib/math/base/napi/ternary", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/clamp/src/main.c b/lib/node_modules/@stdlib/math/base/special/clamp/src/main.c index defb3767570b..792246d83458 100644 --- a/lib/node_modules/@stdlib/math/base/special/clamp/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/clamp/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/clamp.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_negative_zero.h" @@ -42,7 +43,7 @@ double stdlib_base_clamp( const double v, const double min, const double max ) { stdlib_base_is_nan( min ) || stdlib_base_is_nan( max ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Simple cases... if ( v < min ) { diff --git a/lib/node_modules/@stdlib/math/base/special/cos/manifest.json b/lib/node_modules/@stdlib/math/base/special/cos/manifest.json index cf19df411559..b513eb55cdf6 100644 --- a/lib/node_modules/@stdlib/math/base/special/cos/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/cos/manifest.json @@ -42,7 +42,8 @@ "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/kernel-sin", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/kernel-sin", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/kernel-sin", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/cos/src/main.c b/lib/node_modules/@stdlib/math/base/special/cos/src/main.c index ce0d6a3c74a1..e73b9d7680ea 100644 --- a/lib/node_modules/@stdlib/math/base/special/cos/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/cos/src/main.c @@ -34,6 +34,7 @@ #include "stdlib/number/float64/base/get_high_word.h" #include "stdlib/constants/float64/high_word_abs_mask.h" #include "stdlib/constants/float64/high_word_exponent_mask.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/kernel_cos.h" #include "stdlib/math/base/special/kernel_sin.h" #include "stdlib/math/base/special/rempio2.h" @@ -90,7 +91,7 @@ double stdlib_base_cos( const double x ) { } // Case: cos(Inf or NaN) is NaN */ if ( ix >= STDLIB_CONSTANT_FLOAT64_HIGH_WORD_EXPONENT_MASK ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Case: Argument reduction needed... n = stdlib_base_rempio2( x, &Y[ 0 ], &Y[ 1 ] ); diff --git a/lib/node_modules/@stdlib/math/base/special/cosd/manifest.json b/lib/node_modules/@stdlib/math/base/special/cosd/manifest.json index 1c40675a5d6e..6daba4116798 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/cosd/manifest.json @@ -43,7 +43,8 @@ "@stdlib/math/base/special/kernel-sin", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/abs", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] }, { @@ -63,7 +64,8 @@ "@stdlib/math/base/special/kernel-sin", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/abs", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] }, { @@ -83,7 +85,8 @@ "@stdlib/math/base/special/kernel-sin", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/abs", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/cosd/src/main.c b/lib/node_modules/@stdlib/math/base/special/cosd/src/main.c index 3e4dfd667a0d..b1fc3944300e 100644 --- a/lib/node_modules/@stdlib/math/base/special/cosd/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/cosd/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/cosd.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/kernel_sin.h" #include "stdlib/math/base/special/kernel_cos.h" #include "stdlib/math/base/special/deg2rad.h" @@ -39,7 +40,7 @@ double stdlib_base_cosd( const double x ) { double rx; if ( stdlib_base_is_infinite( x ) || stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } rx = stdlib_base_abs( stdlib_base_fmod( x, 360.0 ) ); diff --git a/lib/node_modules/@stdlib/math/base/special/cospi/manifest.json b/lib/node_modules/@stdlib/math/base/special/cospi/manifest.json index f96cd620858a..17a785396fde 100644 --- a/lib/node_modules/@stdlib/math/base/special/cospi/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/cospi/manifest.json @@ -47,7 +47,8 @@ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/fmod", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/max-safe-integer" + "@stdlib/constants/float64/max-safe-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +72,8 @@ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/fmod", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/max-safe-integer" + "@stdlib/constants/float64/max-safe-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -95,7 +97,8 @@ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/fmod", "@stdlib/constants/float64/pi", - "@stdlib/constants/float64/max-safe-integer" + "@stdlib/constants/float64/max-safe-integer", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/cospi/src/main.c b/lib/node_modules/@stdlib/math/base/special/cospi/src/main.c index b51c47377cb5..1350787be0ac 100644 --- a/lib/node_modules/@stdlib/math/base/special/cospi/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/cospi/src/main.c @@ -26,6 +26,7 @@ #include "stdlib/math/base/special/fmod.h" #include "stdlib/constants/float64/pi.h" #include "stdlib/constants/float64/max_safe_integer.h" +#include "stdlib/constants/float64/nan.h" static const double MAX_INTEGER_P1 = STDLIB_CONSTANT_FLOAT64_MAX_SAFE_INTEGER + 1; @@ -54,7 +55,7 @@ double stdlib_base_cospi( const double x ) { double y; if ( stdlib_base_is_nan( x ) || stdlib_base_is_infinite( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } ax = stdlib_base_abs( x ); if ( ax > MAX_INTEGER_P1 ) { diff --git a/lib/node_modules/@stdlib/math/base/special/digamma/manifest.json b/lib/node_modules/@stdlib/math/base/special/digamma/manifest.json index bbc94721cd33..e532992995b9 100644 --- a/lib/node_modules/@stdlib/math/base/special/digamma/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/digamma/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/tan", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/tan", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/tan", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/digamma/src/main.c b/lib/node_modules/@stdlib/math/base/special/digamma/src/main.c index 70fdf933ccec..c6678f53a814 100644 --- a/lib/node_modules/@stdlib/math/base/special/digamma/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/digamma/src/main.c @@ -35,6 +35,7 @@ #include "stdlib/math/base/special/tan.h" #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/pi.h" +#include "stdlib/constants/float64/nan.h" static const double MIN_SAFE_ASYMPTOTIC = 10.0; // BIG! static const double root1 = 1569415565.0 / 1073741824.0; @@ -223,7 +224,7 @@ double stdlib_base_digamma( const double x ) { double xc; if ( stdlib_base_is_nan( x ) || x == 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // If `x` is negative, use reflection... @@ -242,7 +243,7 @@ double stdlib_base_digamma( const double x ) { // Check for evaluation at a negative pole: if ( rem == 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } tmp = STDLIB_CONSTANT_FLOAT64_PI / stdlib_base_tan( STDLIB_CONSTANT_FLOAT64_PI * rem ); } else { diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-delta/manifest.json b/lib/node_modules/@stdlib/math/base/special/dirac-delta/manifest.json index 8dee620b1e2c..d113d3f6517a 100644 --- a/lib/node_modules/@stdlib/math/base/special/dirac-delta/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/dirac-delta/manifest.json @@ -38,7 +38,8 @@ "dependencies": [ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -53,7 +54,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +70,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/dirac-delta/src/main.c b/lib/node_modules/@stdlib/math/base/special/dirac-delta/src/main.c index 7cf9b85352e6..789ecf3bdaf8 100644 --- a/lib/node_modules/@stdlib/math/base/special/dirac-delta/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/dirac-delta/src/main.c @@ -19,6 +19,7 @@ #include "stdlib/math/base/special/dirac_delta.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float64/nan.h" /** * Evaluates the Dirac delta function. @@ -32,7 +33,7 @@ */ double stdlib_base_dirac_delta( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 0.0 ) { return STDLIB_CONSTANT_FLOAT64_PINF; diff --git a/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/manifest.json b/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/manifest.json index 629c9eb58123..987fb3882fd4 100644 --- a/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/special/powm1", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/riemann-zeta", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/special/powm1", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/riemann-zeta", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/special/powm1", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/riemann-zeta", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/src/main.c b/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/src/main.c index 22fbf425edbf..be1e3a2799da 100644 --- a/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/dirichlet-eta/src/main.c @@ -20,6 +20,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/powm1.h" #include "stdlib/constants/float64/ln_two.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/riemann_zeta.h" /** @@ -34,7 +35,7 @@ */ double stdlib_base_eta( const double s ) { if ( stdlib_base_is_nan( s ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( s == 1.0 ) { // Alternating harmonic series... diff --git a/lib/node_modules/@stdlib/math/base/special/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/special/docs/types/index.d.ts index e4bea751f6f3..de091e0f9c44 100644 --- a/lib/node_modules/@stdlib/math/base/special/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/special/docs/types/index.d.ts @@ -6043,8 +6043,8 @@ interface Namespace { * @param x - function input * @param a - function parameter * @param b - function parameter - * @param invert - boolean indicating if the function should return the upper tail of the incomplete beta function instead - * @param normalized - boolean indicating if the function should evaluate the regularized boolean beta function + * @param regularized - boolean indicating if the function should evaluate the regularized incomplete beta function + * @param upper - boolean indicating if the function should return the upper tail of the incomplete beta function instead * @returns function value and first derivative * * @example diff --git a/lib/node_modules/@stdlib/math/base/special/ellipe/manifest.json b/lib/node_modules/@stdlib/math/base/special/ellipe/manifest.json index 9a8d6384fc80..6bbec8c25224 100644 --- a/lib/node_modules/@stdlib/math/base/special/ellipe/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/ellipe/manifest.json @@ -41,7 +41,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/math/base/special/ellipk" + "@stdlib/math/base/special/ellipk", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/math/base/special/ellipk" + "@stdlib/math/base/special/ellipk", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/math/base/special/ellipk" + "@stdlib/math/base/special/ellipk", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/ellipe/src/main.c b/lib/node_modules/@stdlib/math/base/special/ellipe/src/main.c index fc6bfd9663e5..92324c26cf1a 100644 --- a/lib/node_modules/@stdlib/math/base/special/ellipe/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/ellipe/src/main.c @@ -53,6 +53,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/half_pi.h" +#include "stdlib/constants/float64/nan.h" #include /* Begin auto-generated functions. The following functions are auto-generated. Do not edit directly. */ @@ -331,7 +332,7 @@ double stdlib_base_ellipe( const double m ) { return 1.0; } if ( x > 1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x < 0.1 ) { t = poly_p1( x - 0.05 ); diff --git a/lib/node_modules/@stdlib/math/base/special/ellipj/manifest.json b/lib/node_modules/@stdlib/math/base/special/ellipj/manifest.json index 00be502cf2a4..8442d7cc1b36 100644 --- a/lib/node_modules/@stdlib/math/base/special/ellipj/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/ellipj/manifest.json @@ -55,7 +55,8 @@ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/sqrt-eps", "@stdlib/constants/float64/eps", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -84,7 +85,8 @@ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/sqrt-eps", "@stdlib/constants/float64/eps", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -113,7 +115,8 @@ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/sqrt-eps", "@stdlib/constants/float64/eps", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/ellipj/src/main.c b/lib/node_modules/@stdlib/math/base/special/ellipj/src/main.c index 70393ba4e742..dcc1371f7b74 100644 --- a/lib/node_modules/@stdlib/math/base/special/ellipj/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/ellipj/src/main.c @@ -32,6 +32,7 @@ #include "stdlib/constants/float64/sqrt_eps.h" #include "stdlib/constants/float64/eps.h" #include "stdlib/constants/float64/pi.h" +#include "stdlib/constants/float64/nan.h" #include #include @@ -100,7 +101,7 @@ void stdlib_base_ellipj( const double u, const double m, double* sn, double* cn, *sn = ( out[ 0 ] / out[ 2 ] ) / k1inv; *cn = out[ 1 ] / out[ 2 ]; *dn = 1.0 / out[ 2 ]; - *am = 0.0 / 0.0; // NaN + *am = STDLIB_CONSTANT_FLOAT64_NAN; return; } else if ( m > 1.0 ) { // A&S 16.11.1 for reciprocal parameter, mapping m > 1 to 0 < mu < 1: @@ -109,7 +110,7 @@ void stdlib_base_ellipj( const double u, const double m, double* sn, double* cn, *sn = out[ 0 ] / k; *cn = out[ 2 ]; *dn = out[ 1 ]; - *am = 0.0 / 0.0; // NaN + *am = STDLIB_CONSTANT_FLOAT64_NAN; return; } else if ( m == 0.0 ) { // A&S table 16.6, limiting case m = 0: circular trigonometric functions: @@ -179,10 +180,10 @@ void stdlib_base_ellipj( const double u, const double m, double* sn, double* cn, if ( N > 8 ) { // Warning: Overflow encountered in iteration. Returning NaN for all output values: NANFLG = true; - *sn = 0.0 / 0.0; // NaN - *cn = 0.0 / 0.0; // NaN - *dn = 0.0 / 0.0; // NaN - *am = 0.0 / 0.0; // NaN + *sn = STDLIB_CONSTANT_FLOAT64_NAN; + *cn = STDLIB_CONSTANT_FLOAT64_NAN; + *dn = STDLIB_CONSTANT_FLOAT64_NAN; + *am = STDLIB_CONSTANT_FLOAT64_NAN; break; } atmp = ( a + b ) * 0.5; diff --git a/lib/node_modules/@stdlib/math/base/special/ellipk/manifest.json b/lib/node_modules/@stdlib/math/base/special/ellipk/manifest.json index 436f90cc4854..a5332ec2fcfe 100644 --- a/lib/node_modules/@stdlib/math/base/special/ellipk/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/ellipk/manifest.json @@ -40,7 +40,8 @@ "@stdlib/constants/float64/half-pi", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/constants/float64/half-pi", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/constants/float64/half-pi", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/ellipk/src/main.c b/lib/node_modules/@stdlib/math/base/special/ellipk/src/main.c index 02df49586be0..384320054227 100644 --- a/lib/node_modules/@stdlib/math/base/special/ellipk/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/ellipk/src/main.c @@ -52,6 +52,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/half_pi.h" +#include "stdlib/constants/float64/nan.h" #include static const double ONE_DIV_PI = 0.3183098861837907; @@ -358,7 +359,7 @@ double stdlib_base_ellipk( const double m ) { return STDLIB_CONSTANT_FLOAT64_PINF; } if ( x > 1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x < 0.1 ) { t = poly_p1( x - 0.05 ); diff --git a/lib/node_modules/@stdlib/math/base/special/erf/manifest.json b/lib/node_modules/@stdlib/math/base/special/erf/manifest.json index 461e8c261ba7..55e8af143481 100644 --- a/lib/node_modules/@stdlib/math/base/special/erf/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/erf/manifest.json @@ -43,7 +43,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/exp", - "@stdlib/number/float64/base/set-low-word" + "@stdlib/number/float64/base/set-low-word", + "@stdlib/constants/float64/nan" ] }, { @@ -62,7 +63,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/exp", - "@stdlib/number/float64/base/set-low-word" + "@stdlib/number/float64/base/set-low-word", + "@stdlib/constants/float64/nan" ] }, { @@ -81,7 +83,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/exp", - "@stdlib/number/float64/base/set-low-word" + "@stdlib/number/float64/base/set-low-word", + "@stdlib/constants/float64/nan" ] }, { @@ -100,7 +103,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/exp", - "@stdlib/number/float64/base/set-low-word" + "@stdlib/number/float64/base/set-low-word", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/erf/src/main.c b/lib/node_modules/@stdlib/math/base/special/erf/src/main.c index e2762eab12af..4a139114eb88 100644 --- a/lib/node_modules/@stdlib/math/base/special/erf/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/erf/src/main.c @@ -36,6 +36,7 @@ #include "stdlib/number/float64/base/set_low_word.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include static const double TINY = 1.0e-300; @@ -457,7 +458,7 @@ double stdlib_base_erf( const double x ) { // Special case: NaN if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Special case: +infinity if ( x == STDLIB_CONSTANT_FLOAT64_PINF ) { diff --git a/lib/node_modules/@stdlib/math/base/special/erfc/manifest.json b/lib/node_modules/@stdlib/math/base/special/erfc/manifest.json index 4c4cf755fe88..d81a9b57b5c4 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfc/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/erfc/manifest.json @@ -41,7 +41,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/exp", - "@stdlib/number/float64/base/set-low-word" + "@stdlib/number/float64/base/set-low-word", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/exp", - "@stdlib/number/float64/base/set-low-word" + "@stdlib/number/float64/base/set-low-word", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/exp", - "@stdlib/number/float64/base/set-low-word" + "@stdlib/number/float64/base/set-low-word", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/erfc/src/main.c b/lib/node_modules/@stdlib/math/base/special/erfc/src/main.c index cb9b4a3b4482..738d157eef6f 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfc/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/erfc/src/main.c @@ -36,6 +36,7 @@ #include "stdlib/number/float64/base/set_low_word.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include static const double TINY = 1.0e-300; @@ -454,7 +455,7 @@ double stdlib_base_erfc( const double x ) { // Special case: NaN if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Special case: +infinity if ( x == STDLIB_CONSTANT_FLOAT64_PINF ) { diff --git a/lib/node_modules/@stdlib/math/base/special/erfcinv/manifest.json b/lib/node_modules/@stdlib/math/base/special/erfcinv/manifest.json index 97742cc77f41..3e7183e5a7a8 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfcinv/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/erfcinv/manifest.json @@ -41,7 +41,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/erfcinv/src/main.c b/lib/node_modules/@stdlib/math/base/special/erfcinv/src/main.c index 8e4e61e66cef..ee0660485870 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfcinv/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/erfcinv/src/main.c @@ -35,6 +35,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include static const double Y1 = 8.91314744949340820313e-2; @@ -340,7 +341,7 @@ double stdlib_base_erfcinv( const double x ) { // Special case: NaN if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Special case: 0 if ( x == 0.0 ) { @@ -355,7 +356,7 @@ double stdlib_base_erfcinv( const double x ) { return 0.0; } if ( x > 2.0 || x < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Argument reduction (reduce to interval [0,1]). If `x` is outside [0,1], we can take advantage of the complementary error function reflection formula: `erfc(-z) = 2 - erfc(z)`, by negating the result once finished. if ( x > 1.0 ) { diff --git a/lib/node_modules/@stdlib/math/base/special/erfinv/manifest.json b/lib/node_modules/@stdlib/math/base/special/erfinv/manifest.json index 97742cc77f41..3e7183e5a7a8 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfinv/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/erfinv/manifest.json @@ -41,7 +41,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/sqrt", - "@stdlib/math/base/special/ln" + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/erfinv/src/main.c b/lib/node_modules/@stdlib/math/base/special/erfinv/src/main.c index d4ec84de8e3b..a088d3d1b6fa 100644 --- a/lib/node_modules/@stdlib/math/base/special/erfinv/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/erfinv/src/main.c @@ -35,6 +35,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include static const double Y1 = 8.91314744949340820313e-2; @@ -272,7 +273,7 @@ double stdlib_base_erfinv( const double x ) { // Special case: NaN if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Special case: 1 if ( x == 1.0 ) { @@ -288,7 +289,7 @@ double stdlib_base_erfinv( const double x ) { } // Special case: |x| > 1 (range error) if ( x > 1.0 || x < -1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Argument reduction (reduce to interval [0,1]). If `x` is negative, we can safely negate the value, taking advantage of the error function being an odd function; i.e., `erf(-x) = -erf(x)`. if ( x < 0.0 ) { diff --git a/lib/node_modules/@stdlib/math/base/special/exp10/manifest.json b/lib/node_modules/@stdlib/math/base/special/exp10/manifest.json index 22c8c12ca3bd..89e4c46efeae 100644 --- a/lib/node_modules/@stdlib/math/base/special/exp10/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/exp10/manifest.json @@ -42,7 +42,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/ldexp", - "@stdlib/constants/float64/min-base10-exponent" + "@stdlib/constants/float64/min-base10-exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/ldexp", - "@stdlib/constants/float64/min-base10-exponent" + "@stdlib/constants/float64/min-base10-exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/ldexp", - "@stdlib/constants/float64/min-base10-exponent" + "@stdlib/constants/float64/min-base10-exponent", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/exp10/src/main.c b/lib/node_modules/@stdlib/math/base/special/exp10/src/main.c index c8eea140c600..42ff65360c46 100644 --- a/lib/node_modules/@stdlib/math/base/special/exp10/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/exp10/src/main.c @@ -37,6 +37,7 @@ #include "stdlib/constants/float64/max_base10_exponent.h" #include "stdlib/constants/float64/min_base10_exponent.h" #include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float64/nan.h" #include static const double LOG210 = 3.32192809488736234787e0; @@ -123,7 +124,7 @@ double stdlib_base_exp10( const double x ) { int32_t n; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x > STDLIB_CONSTANT_FLOAT64_MAX_BASE10_EXPONENT ) { return STDLIB_CONSTANT_FLOAT64_PINF; diff --git a/lib/node_modules/@stdlib/math/base/special/expit/manifest.json b/lib/node_modules/@stdlib/math/base/special/expit/manifest.json index 8ca7869951dd..84884b62f51f 100644 --- a/lib/node_modules/@stdlib/math/base/special/expit/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/expit/manifest.json @@ -38,7 +38,8 @@ "dependencies": [ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/exp" + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/nan" ] }, { @@ -53,7 +54,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/exp" + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +70,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/exp" + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/expit/src/main.c b/lib/node_modules/@stdlib/math/base/special/expit/src/main.c index 2ebf91c958d1..0a74ba0f7418 100644 --- a/lib/node_modules/@stdlib/math/base/special/expit/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/expit/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/expit.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/exp.h" #include "stdlib/math/base/assert/is_nan.h" @@ -32,7 +33,7 @@ */ double stdlib_base_expit( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return 1.0 / ( 1.0 + stdlib_base_exp( -x ) ); } diff --git a/lib/node_modules/@stdlib/math/base/special/factorial/manifest.json b/lib/node_modules/@stdlib/math/base/special/factorial/manifest.json index 5b4e388f472f..e33219b192a2 100644 --- a/lib/node_modules/@stdlib/math/base/special/factorial/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/factorial/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-integer", "@stdlib/math/base/special/gamma", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-integer", "@stdlib/math/base/special/gamma", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-integer", "@stdlib/math/base/special/gamma", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/factorial/src/main.c b/lib/node_modules/@stdlib/math/base/special/factorial/src/main.c index c12d0da63bb0..51d438e19c8f 100644 --- a/lib/node_modules/@stdlib/math/base/special/factorial/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/factorial/src/main.c @@ -22,6 +22,7 @@ #include "stdlib/math/base/special/gamma.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/max_nth_factorial.h" +#include "stdlib/constants/float64/nan.h" #include static const double FACTORIALS[ 171 ] = { @@ -211,11 +212,11 @@ static const double FACTORIALS[ 171 ] = { */ double stdlib_base_factorial( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_integer( x ) ) { if ( x < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x <= STDLIB_CONSTANT_FLOAT64_MAX_NTH_FACTORIAL ) { return FACTORIALS[ (int32_t)x ]; diff --git a/lib/node_modules/@stdlib/math/base/special/factorial2/manifest.json b/lib/node_modules/@stdlib/math/base/special/factorial2/manifest.json index ba5469173d4c..e748db7d9200 100644 --- a/lib/node_modules/@stdlib/math/base/special/factorial2/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/factorial2/manifest.json @@ -41,7 +41,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/max-nth-double-factorial", "@stdlib/math/base/assert/is-nonnegative-integer", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/max-nth-double-factorial", "@stdlib/math/base/assert/is-nonnegative-integer", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/constants/float64/pinf", "@stdlib/constants/float64/max-nth-double-factorial", "@stdlib/math/base/assert/is-nonnegative-integer", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/factorial2/src/main.c b/lib/node_modules/@stdlib/math/base/special/factorial2/src/main.c index e50252653a33..d440184dfa76 100644 --- a/lib/node_modules/@stdlib/math/base/special/factorial2/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/factorial2/src/main.c @@ -22,6 +22,7 @@ #include "stdlib/math/base/assert/is_nonnegative_integer.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/max_nth_double_factorial.h" +#include "stdlib/constants/float64/nan.h" /** * Evaluates the double factorial of `n`. @@ -40,7 +41,7 @@ double stdlib_base_factorial2( const double n ) { double i; if ( stdlib_base_is_nan( n ) || !stdlib_base_is_nonnegative_integer( n ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( n > STDLIB_CONSTANT_FLOAT64_MAX_NTH_DOUBLE_FACTORIAL ) { return STDLIB_CONSTANT_FLOAT64_PINF; diff --git a/lib/node_modules/@stdlib/math/base/special/factorialln/manifest.json b/lib/node_modules/@stdlib/math/base/special/factorialln/manifest.json index 213d4fd06e9f..48f9714d9802 100644 --- a/lib/node_modules/@stdlib/math/base/special/factorialln/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/factorialln/manifest.json @@ -38,7 +38,8 @@ "dependencies": [ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-negative-integer", - "@stdlib/math/base/special/gammaln" + "@stdlib/math/base/special/gammaln", + "@stdlib/constants/float64/nan" ] }, { @@ -53,7 +54,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-negative-integer", - "@stdlib/math/base/special/gammaln" + "@stdlib/math/base/special/gammaln", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +70,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-negative-integer", - "@stdlib/math/base/special/gammaln" + "@stdlib/math/base/special/gammaln", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/factorialln/src/main.c b/lib/node_modules/@stdlib/math/base/special/factorialln/src/main.c index 596b05ad8e03..c8be4e611932 100644 --- a/lib/node_modules/@stdlib/math/base/special/factorialln/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/factorialln/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/factorialln.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_negative_integer.h" #include "stdlib/math/base/special/gammaln.h" @@ -32,7 +33,7 @@ */ double stdlib_base_factorialln( const double x ) { if ( stdlib_base_is_negative_integer( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return stdlib_base_gammaln( x + 1.0 ); } diff --git a/lib/node_modules/@stdlib/math/base/special/falling-factorial/manifest.json b/lib/node_modules/@stdlib/math/base/special/falling-factorial/manifest.json index a3c2f970e229..384bd26dbb0c 100644 --- a/lib/node_modules/@stdlib/math/base/special/falling-factorial/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/falling-factorial/manifest.json @@ -45,7 +45,8 @@ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/max", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -67,7 +68,8 @@ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/max", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -89,7 +91,8 @@ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/max", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/falling-factorial/src/main.c b/lib/node_modules/@stdlib/math/base/special/falling-factorial/src/main.c index 1515fcb958d2..316900bfa5d9 100644 --- a/lib/node_modules/@stdlib/math/base/special/falling-factorial/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/falling-factorial/src/main.c @@ -39,6 +39,7 @@ #include "stdlib/constants/float64/max.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/max_nth_factorial.h" +#include "stdlib/constants/float64/nan.h" #include #include @@ -78,7 +79,7 @@ static double risingFactorial( const double x, const int32_t n ) { bool inv; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } nc = n; xc = x; @@ -146,7 +147,7 @@ double stdlib_base_falling_factorial( const double x, const int32_t n ) { double xc; if ( stdlib_base_is_nan( x ) || !stdlib_base_is_nonnegative_integer( n ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 0.0 ) { return 0.0; diff --git a/lib/node_modules/@stdlib/math/base/special/fast/acosh/manifest.json b/lib/node_modules/@stdlib/math/base/special/fast/acosh/manifest.json index 26ed895f38cb..148b8bfa1e1b 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/acosh/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/acosh/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/math/base/assert/is-infinite" + "@stdlib/math/base/assert/is-infinite", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/math/base/assert/is-infinite" + "@stdlib/math/base/assert/is-infinite", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/ln", - "@stdlib/math/base/assert/is-infinite" + "@stdlib/math/base/assert/is-infinite", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/fast/acosh/src/main.c b/lib/node_modules/@stdlib/math/base/special/fast/acosh/src/main.c index aadb31e8e2bc..13335f8de861 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/acosh/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/fast/acosh/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/fast/acosh.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/ln.h" @@ -35,7 +36,7 @@ */ double stdlib_base_fast_acosh( const double x ) { if ( x < 1.0 ) { - return 0.0 / 0.0 ; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_nan( x ) || stdlib_base_is_infinite( x ) ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/fast/atanh/manifest.json b/lib/node_modules/@stdlib/math/base/special/fast/atanh/manifest.json index 3086e38c4d7e..9f25da00bea8 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/atanh/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/atanh/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/ln", - "@stdlib/math/base/assert/is-infinite" + "@stdlib/math/base/assert/is-infinite", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/ln", - "@stdlib/math/base/assert/is-infinite" + "@stdlib/math/base/assert/is-infinite", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/ln", - "@stdlib/math/base/assert/is-infinite" + "@stdlib/math/base/assert/is-infinite", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/fast/atanh/src/main.c b/lib/node_modules/@stdlib/math/base/special/fast/atanh/src/main.c index a814f378b4b2..ef5701352fb6 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/atanh/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/fast/atanh/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/fast/atanh.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/ln.h" @@ -37,7 +38,7 @@ double stdlib_base_fast_atanh( const double x ) { return x; } if ( stdlib_base_is_nan( x ) || stdlib_base_is_infinite( x ) ) { - return 0.0 / 0.0 ; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return 0.5 * stdlib_base_ln( ( 1.0 + x ) / ( 1.0 - x ) ); } diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/manifest.json b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/manifest.json index 880ad9c327f1..333866c685b1 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/manifest.json @@ -40,7 +40,8 @@ "dependencies": [ "@stdlib/math/base/napi/binary", "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c index b5ca5a2a4c3e..3666ced52236 100644 --- a/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/fast/pow-int/src/main.c @@ -19,6 +19,7 @@ #include "stdlib/math/base/special/fast/pow_int.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float64/nan.h" int32_t ONE = 1; int32_t ZERO = 0; @@ -42,7 +43,7 @@ double stdlib_base_fast_pow( const double x, const int32_t y ) { xc = x; yc = y; if ( stdlib_base_is_nan( xc ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( yc < ZERO ) { yc = -yc; diff --git a/lib/node_modules/@stdlib/math/base/special/fibonacci-index/manifest.json b/lib/node_modules/@stdlib/math/base/special/fibonacci-index/manifest.json index d9f4316aeb68..31a5d80d4ce6 100644 --- a/lib/node_modules/@stdlib/math/base/special/fibonacci-index/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/fibonacci-index/manifest.json @@ -42,7 +42,8 @@ "@stdlib/math/base/special/round", "@stdlib/math/base/special/ln", "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/math/base/special/round", "@stdlib/math/base/special/ln", "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/math/base/special/round", "@stdlib/math/base/special/ln", "@stdlib/math/base/assert/is-integer", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/fibonacci-index/src/main.c b/lib/node_modules/@stdlib/math/base/special/fibonacci-index/src/main.c index 5983d6e98f30..57b4a0651300 100644 --- a/lib/node_modules/@stdlib/math/base/special/fibonacci-index/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/fibonacci-index/src/main.c @@ -23,6 +23,7 @@ #include "stdlib/math/base/special/round.h" #include "stdlib/constants/float64/phi.h" #include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float64/nan.h" #include static const double SQRT_5 = 2.23606797749979; @@ -45,7 +46,7 @@ double stdlib_base_fibonacci_index( const double F ) { double x; if ( stdlib_base_is_nan( F ) || stdlib_base_is_integer( F ) == false || F <= 1 || F == STDLIB_CONSTANT_FLOAT64_PINF ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } x = ( F * SQRT_5 ) + 0.5; return stdlib_base_round( stdlib_base_ln( x ) / stdlib_base_ln( STDLIB_CONSTANT_FLOAT64_PHI ) ); diff --git a/lib/node_modules/@stdlib/math/base/special/floorb/manifest.json b/lib/node_modules/@stdlib/math/base/special/floorb/manifest.json index 5c67bfd871d4..80a774e7fb15 100644 --- a/lib/node_modules/@stdlib/math/base/special/floorb/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/floorb/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/floorn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/floorn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/floorn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/floorb/src/main.c b/lib/node_modules/@stdlib/math/base/special/floorb/src/main.c index 44671bba319a..14b36aa7013e 100644 --- a/lib/node_modules/@stdlib/math/base/special/floorb/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/floorb/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/floorb.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/floor.h" @@ -41,7 +42,7 @@ double stdlib_base_floorb( const double x, const int32_t n, const int32_t b ) { double s; if ( stdlib_base_is_nan( x ) || b <= 0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/floorsd/manifest.json b/lib/node_modules/@stdlib/math/base/special/floorsd/manifest.json index 4fce81c4238d..2a189f19e0e0 100644 --- a/lib/node_modules/@stdlib/math/base/special/floorsd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/floorsd/manifest.json @@ -44,7 +44,8 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/floorsd/src/main.c b/lib/node_modules/@stdlib/math/base/special/floorsd/src/main.c index b87b9ea9d277..455b018651bc 100644 --- a/lib/node_modules/@stdlib/math/base/special/floorsd/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/floorsd/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/floorsd.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/pow.h" @@ -45,7 +46,7 @@ double stdlib_base_floorsd( const double x, const int32_t n, const int32_t b ) { double y; if ( stdlib_base_is_nan( x ) || n < 1 || b <= 0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/gamma/manifest.json b/lib/node_modules/@stdlib/math/base/special/gamma/manifest.json index 0b051015bd59..95be3c49993e 100644 --- a/lib/node_modules/@stdlib/math/base/special/gamma/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/gamma/manifest.json @@ -49,7 +49,8 @@ "@stdlib/constants/float64/eulergamma", "@stdlib/constants/float64/sqrt-two-pi", "@stdlib/math/base/special/pow", - "@stdlib/math/base/special/exp" + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/nan" ] }, { @@ -75,7 +76,8 @@ "@stdlib/constants/float64/eulergamma", "@stdlib/constants/float64/sqrt-two-pi", "@stdlib/math/base/special/pow", - "@stdlib/math/base/special/exp" + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/nan" ] }, { @@ -101,7 +103,8 @@ "@stdlib/constants/float64/eulergamma", "@stdlib/constants/float64/sqrt-two-pi", "@stdlib/math/base/special/pow", - "@stdlib/math/base/special/exp" + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/gamma/src/main.c b/lib/node_modules/@stdlib/math/base/special/gamma/src/main.c index 0fa02d54f960..29b600d65a55 100644 --- a/lib/node_modules/@stdlib/math/base/special/gamma/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/gamma/src/main.c @@ -42,6 +42,7 @@ #include "stdlib/constants/float64/pi.h" #include "stdlib/constants/float64/eulergamma.h" #include "stdlib/constants/float64/sqrt_two_pi.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/pow.h" #include "stdlib/math/base/special/exp.h" #include @@ -187,7 +188,7 @@ double stdlib_base_gamma( const double x ) { double z; if ( ( stdlib_base_is_integer( x ) && x < 0 ) || x == STDLIB_CONSTANT_FLOAT64_NINF || stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 0.0 ) { if ( stdlib_base_is_negative_zero( x ) ) { @@ -207,7 +208,7 @@ double stdlib_base_gamma( const double x ) { return stirlingApprox( x ); } p = stdlib_base_floor( q ); - + // Check whether `x` is even... i = (int32_t)p; if ( ( i & 1 ) == 0 ) { @@ -223,7 +224,7 @@ double stdlib_base_gamma( const double x ) { z = q * stdlib_base_sin( STDLIB_CONSTANT_FLOAT64_PI * z ); return sign * STDLIB_CONSTANT_FLOAT64_PI / ( stdlib_base_abs( z ) * stirlingApprox( q ) ); } - + // Reduce `x`... z = 1.0; xc = x; diff --git a/lib/node_modules/@stdlib/math/base/special/gamma1pm1/manifest.json b/lib/node_modules/@stdlib/math/base/special/gamma1pm1/manifest.json index 578c9d461e59..96dbc5c32258 100644 --- a/lib/node_modules/@stdlib/math/base/special/gamma1pm1/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/gamma1pm1/manifest.json @@ -42,7 +42,8 @@ "@stdlib/math/base/special/expm1", "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/math/base/special/expm1", "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/math/base/special/expm1", "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/gamma1pm1/src/main.c b/lib/node_modules/@stdlib/math/base/special/gamma1pm1/src/main.c index d582ac3ec03c..4a8c7ad04390 100644 --- a/lib/node_modules/@stdlib/math/base/special/gamma1pm1/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/gamma1pm1/src/main.c @@ -39,6 +39,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/constants/float64/eps.h" +#include "stdlib/constants/float64/nan.h" static const double Y1 = 0.158963680267333984375; static const double Y2 = 0.52815341949462890625; @@ -282,7 +283,7 @@ static double lgammaSmallImp( const double z, const double zm1, const double zm2 */ double stdlib_base_gamma1pm1( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x < 0.0 ) { if ( x < -0.5 ) { diff --git a/lib/node_modules/@stdlib/math/base/special/gammainc/manifest.json b/lib/node_modules/@stdlib/math/base/special/gammainc/manifest.json index d38ecfe1028a..ffcd69f19940 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammainc/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/gammainc/manifest.json @@ -69,7 +69,8 @@ "@stdlib/constants/float64/e", "@stdlib/constants/float64/gamma-lanczos-g", "@stdlib/constants/float32/smallest-normal", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -111,7 +112,8 @@ "@stdlib/constants/float64/e", "@stdlib/constants/float64/gamma-lanczos-g", "@stdlib/constants/float32/smallest-normal", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -153,7 +155,8 @@ "@stdlib/constants/float64/e", "@stdlib/constants/float64/gamma-lanczos-g", "@stdlib/constants/float32/smallest-normal", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/gammainc/src/main.c b/lib/node_modules/@stdlib/math/base/special/gammainc/src/main.c index b2173e5d1e2e..b61792e91d7b 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammainc/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/gammainc/src/main.c @@ -62,6 +62,7 @@ #include "stdlib/constants/float64/max.h" #include "stdlib/constants/float64/pi.h" #include "stdlib/constants/float64/e.h" +#include "stdlib/constants/float64/nan.h" #include #include @@ -1017,7 +1018,7 @@ double stdlib_base_gammainc( const double x, const double a, const bool regulari bool invert; if ( x < 0.0 || a <= 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } invert = upper; if ( a >= MAX_NTH_FACTORIAL && !regularized ) { diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/README.md b/lib/node_modules/@stdlib/math/base/special/gammaincinv/README.md index 7426de70ddd1..f867574c65ca 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammaincinv/README.md +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/README.md @@ -70,7 +70,7 @@ Again, for given `p` and `a` the function returns the `x` which satisfies `p = Q var gammaincinv = require( '@stdlib/math/base/special/gammaincinv' ); ``` -#### gammaincinv( p, s\[, upper ] ) +#### gammaincinv( p, a\[, upper ] ) Inverts the regularized incomplete gamma function. Contrary to the more commonly used definition, in this implementation the first argument is the probability `p` and the second argument is the scale factor `a`. By default, the function inverts the _lower_ regularized incomplete gamma function, `P(x,a)`. To invert the _upper_ function instead, i.e. `Q(x,a)`, set the `upper` argument to `true`. @@ -136,6 +136,109 @@ logEachMap( 'p: %0.4f, \t a: %0.4f, \t P^(-1)(p, a): %0.4f', p, a, gammaincinv ) + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/math/base/special/gammaincinv.h" +``` + +#### stdlib_base_gammaincinv( p, a, upper ) + +Inverts the regularized incomplete gamma function. + +```c +double y = stdlib_base_gammaincinv( 0.5, 2.0, false ); +// returns ~1.678 + +y = stdlib_base_gammaincinv( 0.1, 10.0, false ); +// returns ~6.221 + +y = stdlib_base_gammaincinv( 0.75, 3.0, true ); +// returns ~1.727 +``` + +The function accepts the following arguments: + +- **p**: `[in] double` input probability. +- **a**: `[in] double` scale parameter. +- **upper**: `[in] bool` boolean indicating if the function should invert the upper tail of the incomplete gamma function. + +```c +double stdlib_base_gammaincinv( const double p, const double a, const bool upper ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/math/base/special/gammaincinv.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double a; + double y; + int i; + + for ( i = 0; i < 100; i++ ) { + p = random_uniform( 0.0, 1.0 ); + a = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_gammaincinv( p, a, false ); + printf( "p: %lf, a: %lf, y: %lf\n", p, a, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/benchmark.native.js new file mode 100644 index 000000000000..3f103847e1af --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/benchmark.native.js @@ -0,0 +1,64 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var gammaincinv = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( gammaincinv instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var x; + var y; + var z; + var i; + + x = uniform( 100, 0.0, 1.0 ); + y = uniform( 100, 0.1, 1000.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = gammaincinv( x[ i%x.length ], y[ i%y.length ] ); + if ( isnan( z ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( z ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/c/native/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..966b86ae5d77 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/benchmark/c/native/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/gammaincinv.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include +#include + +#define NAME "gammaincinv" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double p[ 100 ]; + double a[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + p[ i ] = random_uniform( 0.0, 1.0 ); + a[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_gammaincinv( p[ i%100 ], a[ i%100 ], false ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/binding.gyp b/lib/node_modules/@stdlib/math/base/special/gammaincinv/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/gammaincinv/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/gammaincinv/examples/c/example.c new file mode 100644 index 000000000000..31f312581a61 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/gammaincinv.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double p; + double a; + double y; + int i; + + for ( i = 0; i < 100; i++ ) { + p = random_uniform( 0.0, 1.0 ); + a = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + y = stdlib_base_gammaincinv( p, a, false ); + printf( "p: %lf, a: %lf, y: %lf\n", p, a, y ); + } +} diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/include.gypi b/lib/node_modules/@stdlib/math/base/special/gammaincinv/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Computes the inverse of the incomplete gamma function. +*/ +double stdlib_base_gammaincinv( const double p, const double a, const bool upper ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_MATH_BASE_SPECIAL_GAMMAINCINV_H diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/lib/native.js b/lib/node_modules/@stdlib/math/base/special/gammaincinv/lib/native.js new file mode 100644 index 000000000000..d4367104c552 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/lib/native.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Inverts the lower gamma function; i.e., computes `xr` such that `P(a,xr) = p`. +* +* @private +* @param {Probability} p - probability value +* @param {number} a - scale parameter +* @param {boolean} [upper=false] - boolean indicating if the function should invert the upper tail of the incomplete gamma function instead; i.e., compute `xr` such that `Q(a,xr) = p`. +* @returns {number} function value of the inverse +* +* @example +* var v = gammaincinv( 0.5, 2.0 ); +* // returns ~1.678 +*/ +function gammaincinv( p, a, upper ) { + if ( arguments.length < 3 ) { + upper = false; + } + return addon( p, a, upper ); +} + + +// EXPORTS // + +module.exports = gammaincinv; diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/manifest.json b/lib/node_modules/@stdlib/math/base/special/gammaincinv/manifest.json new file mode 100644 index 000000000000..3040765fc7bb --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/manifest.json @@ -0,0 +1,129 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-bool", + "@stdlib/napi/create-double", + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float32/smallest-normal", + "@stdlib/constants/float64/pinf", + "@stdlib/math/base/special/gammaln", + "@stdlib/math/base/special/erfcinv", + "@stdlib/math/base/special/gamma", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/abs", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/min", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/ln-sqrt-two-pi", + "@stdlib/constants/float64/sqrt-two-pi", + "@stdlib/constants/float32/max", + "@stdlib/constants/float64/two-pi", + "@stdlib/math/base/special/gammainc", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float32/smallest-normal", + "@stdlib/constants/float64/pinf", + "@stdlib/math/base/special/gammaln", + "@stdlib/math/base/special/erfcinv", + "@stdlib/math/base/special/gamma", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/abs", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/min", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/ln-sqrt-two-pi", + "@stdlib/constants/float64/sqrt-two-pi", + "@stdlib/constants/float32/max", + "@stdlib/constants/float64/two-pi", + "@stdlib/constants/float64/eps", + "@stdlib/math/base/special/gammainc", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float32/smallest-normal", + "@stdlib/constants/float64/pinf", + "@stdlib/math/base/special/gammaln", + "@stdlib/math/base/special/erfcinv", + "@stdlib/math/base/special/gamma", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/abs", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/min", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/ln", + "@stdlib/constants/float64/ln-sqrt-two-pi", + "@stdlib/constants/float64/sqrt-two-pi", + "@stdlib/constants/float32/max", + "@stdlib/constants/float64/two-pi", + "@stdlib/constants/float64/eps", + "@stdlib/math/base/special/gammainc", + "@stdlib/constants/float64/nan" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/package.json b/lib/node_modules/@stdlib/math/base/special/gammaincinv/package.json index 3bc5f2084385..5344be32824e 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammaincinv/package.json +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/package.json @@ -14,12 +14,15 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", "scripts": "./scripts", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalpoly.js b/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalpoly.js index 7f27b9817f0e..b80a7af42895 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalpoly.js +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalpoly.js @@ -24,10 +24,15 @@ // MODULES // var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; var writeFileSync = require( '@stdlib/fs/write-file' ).sync; var currentYear = require( '@stdlib/time/current-year' ); +var substringBefore = require( '@stdlib/string/substring-before' ); +var substringAfter = require( '@stdlib/string/substring-after' ); +var format = require( '@stdlib/string/format' ); var licenseHeader = require( '@stdlib/_tools/licenses/header' ); var compile = require( '@stdlib/math/base/tools/evalpoly-compile' ); +var compileC = require( '@stdlib/math/base/tools/evalpoly-compile-c' ); // VARIABLES // @@ -74,6 +79,33 @@ var header = licenseHeader( 'Apache-2.0', 'js', { header += '\n/* This is a generated file. Do not edit directly. */\n'; +// FUNCTIONS // + +/** +* Inserts a compiled function into file content. +* +* @private +* @param {string} text - source content +* @param {string} id - function identifier +* @param {string} str - function string +* @returns {string} updated content +*/ +function insert( text, id, str ) { + var before; + var after; + var begin; + var end; + + begin = '// BEGIN: '+id; + end = '// END: '+id; + + before = substringBefore( text, begin ); + after = substringAfter( text, end ); + + return format( '%s// BEGIN: %s\n\n%s\n%s%s', before, id, str, end, after ); +} + + // MAIN // /** @@ -83,7 +115,9 @@ header += '\n/* This is a generated file. Do not edit directly. */\n'; */ function main() { var fpath; + var copts; var opts; + var file; var str; opts = { @@ -105,6 +139,32 @@ function main() { fpath = resolve( __dirname, '..', 'lib', 'polyval_ak2.js' ); str = header + compile( AK2 ); writeFileSync( fpath, str, opts ); + + copts = { + 'dtype': 'double', + 'name': '' + }; + + fpath = resolve( __dirname, '..', 'src', 'main.c' ); + file = readFileSync( fpath, opts ); + + copts.name = 'polyval_c'; + str = compileC( C, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'polyval_d'; + str = compileC( D, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'polyval_ak1'; + str = compileC( AK1, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'polyval_ak2'; + str = compileC( AK2, copts ); + file = insert( file, copts.name, str ); + + writeFileSync( fpath, file, opts ); } main(); diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalrational.js b/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalrational.js index 670b90cef310..bed682fe5e63 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalrational.js +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/scripts/evalrational.js @@ -24,10 +24,15 @@ // MODULES // var resolve = require( 'path' ).resolve; +var readFileSync = require( '@stdlib/fs/read-file' ).sync; var writeFileSync = require( '@stdlib/fs/write-file' ).sync; var currentYear = require( '@stdlib/time/current-year' ); +var substringBefore = require( '@stdlib/string/substring-before' ); +var substringAfter = require( '@stdlib/string/substring-after' ); +var format = require( '@stdlib/string/format' ); var licenseHeader = require( '@stdlib/_tools/licenses/header' ); var compile = require( '@stdlib/math/base/tools/evalrational-compile' ); +var compileC = require( '@stdlib/math/base/tools/evalrational-compile-c' ); // VARIABLES // @@ -176,6 +181,33 @@ var header = licenseHeader( 'Apache-2.0', 'js', { header += '\n/* This is a generated file. Do not edit directly. */\n'; +// FUNCTIONS // + +/** +* Inserts a compiled function into file content. +* +* @private +* @param {string} text - source content +* @param {string} id - function identifier +* @param {string} str - function string +* @returns {string} updated content +*/ +function insert( text, id, str ) { + var before; + var after; + var begin; + var end; + + begin = '// BEGIN: '+id; + end = '// END: '+id; + + before = substringBefore( text, begin ); + after = substringAfter( text, end ); + + return format( '%s// BEGIN: %s\n\n%s\n%s%s', before, id, str, end, after ); +} + + // MAIN // /** @@ -185,7 +217,9 @@ header += '\n/* This is a generated file. Do not edit directly. */\n'; */ function main() { var fpath; + var copts; var opts; + var file; var str; opts = { @@ -227,6 +261,52 @@ function main() { fpath = resolve( __dirname, '..', 'lib', 'rational_ak8bk8.js' ); str = header + compile( AK8, BK8 ); writeFileSync( fpath, str, opts ); + + copts = { + 'dtype': 'double', + 'name': '' + }; + + fpath = resolve( __dirname, '..', 'src', 'main.c' ); + file = readFileSync( fpath, opts ); + + copts.name = 'rational_ak0bk0'; + str = compileC( AK0, BK0, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak1bk1'; + str = compileC( AK1, BK1, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak2bk2'; + str = compileC( AK2, BK2, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak3bk3'; + str = compileC( AK3, BK3, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak4bk4'; + str = compileC( AK4, BK4, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak5bk5'; + str = compileC( AK5, BK5, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak6bk6'; + str = compileC( AK6, BK6, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak7bk7'; + str = compileC( AK7, BK7, copts ); + file = insert( file, copts.name, str ); + + copts.name = 'rational_ak8bk8'; + str = compileC( AK8, BK8, copts ); + file = insert( file, copts.name, str ); + + writeFileSync( fpath, file, opts ); } main(); diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/Makefile b/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/addon.c b/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/addon.c new file mode 100644 index 000000000000..ab56f1350e8d --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/addon.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/gammaincinv.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_bool.h" +#include "stdlib/napi/create_double.h" +#include "stdlib/napi/export.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 3 ); + STDLIB_NAPI_ARGV_DOUBLE( env, p, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, a, argv, 1 ); + STDLIB_NAPI_ARGV_BOOL( env, upper, argv, 2 ); + STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_base_gammaincinv( p, a, upper ), out ); + return out; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/main.c b/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/main.c new file mode 100644 index 000000000000..7e7ae30dc90e --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/src/main.c @@ -0,0 +1,1112 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The implementation was translated from the Fortran module by +* +* ```text +* ---------------------------------------------------------------------- +* Authors: +* Amparo Gil (U. Cantabria, Santander, Spain) +* e-mail: amparo.gil@unican.es +* Javier Segura (U. Cantabria, Santander, Spain) +* e-mail: javier.segura@unican.es +* Nico M. Temme (CWI, Amsterdam, The Netherlands) +* e-mail: nico.temme@cwi.nl +* --------------------------------------------------------------------- +* ``` +*/ + +#include "stdlib/math/base/special/gammaincinv.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/gammainc.h" +#include "stdlib/math/base/special/erfcinv.h" +#include "stdlib/math/base/special/gammaln.h" +#include "stdlib/math/base/special/gamma.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/math/base/special/abs.h" +#include "stdlib/math/base/special/exp.h" +#include "stdlib/math/base/special/min.h" +#include "stdlib/math/base/special/pow.h" +#include "stdlib/math/base/special/ln.h" +#include "stdlib/constants/float32/smallest_normal.h" +#include "stdlib/constants/float64/ln_sqrt_two_pi.h" +#include "stdlib/constants/float64/sqrt_two_pi.h" +#include "stdlib/constants/float64/two_pi.h" +#include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float32/max.h" +#include "stdlib/constants/float64/nan.h" +#include +#include + +static const double PINF = STDLIB_CONSTANT_FLOAT64_PINF; +static const float SMALLEST_NORMAL_FLOAT32 = STDLIB_CONSTANT_FLOAT32_SMALLEST_NORMAL; +static const double SQRT_TWO_PI = STDLIB_CONSTANT_FLOAT64_SQRT_TWO_PI; +static const float MAX_FLOAT32 = STDLIB_CONSTANT_FLOAT32_MAX; +static const double TWO_PI = STDLIB_CONSTANT_FLOAT64_TWO_PI; +static const double LN_SQRT_TWO_PI = STDLIB_CONSTANT_FLOAT64_LN_SQRT_TWO_PI; + +static const double HALF = 0.5; +static const double ONEO3 = 0.333333333333333333333333333333; +static const double ONEO4 = 0.25; +static const double ONEO5 = 0.2; +static const double ONEO6 = 0.166666666666666666666666666667; +static const double ONEO12 = 0.0833333333333333333333333333333; +static const double ONEO24 = 0.0416666666666666666666666666667; +static const double ONEO120 = 0.00833333333333333333333333333333; +static const double THRESHOLD = 1.0e-8; +static const double C6 = 0.30865217988013567769; + +// Chebyshev polynomial coefficients... +static const double A[ 18 ] = { + 1.996379051590076518221, + -0.17971032528832887213e-2, + 0.131292857963846713e-4, + -0.2340875228178749e-6, + 0.72291210671127e-8, + -0.3280997607821e-9, + 0.198750709010e-10, + -0.15092141830e-11, + 0.1375340084e-12, + -0.145728923e-13, + 0.17532367e-14, + -0.2351465e-15, + 0.346551e-16, + -0.55471e-17, + 0.9548e-18, + -0.1748e-18, + 0.332e-19, + -0.58e-20 +}; + +/* Begin auto-generated functions. The following functions are auto-generated. Do not edit directly. */ + +// BEGIN: polyval_ak1 + +/** +* Evaluates a polynomial. +* +* ## Notes +* +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the polynomial +* @return evaluated polynomial +*/ +static double polyval_ak1( const double x ) { + return 0.0 + (x * (1.0 + (x * (1.0 + (x * (1.5 + (x * (2.6666666666666665 + (x * (5.208333333333333 + (x * 10.8))))))))))); +} + +// END: polyval_ak1 + +// BEGIN: polyval_ak2 + +/** +* Evaluates a polynomial. +* +* ## Notes +* +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the polynomial +* @return evaluated polynomial +*/ +static double polyval_ak2( const double x ) { + return 1.0 + (x * (1.0 + (x * (0.3333333333333333 + (x * (0.027777777777777776 + (x * (-0.003703703703703704 + (x * (0.0002314814814814815 + (x * 0.00005878894767783657))))))))))); +} + +// END: polyval_ak2 + +// BEGIN: polyval_c + +/** +* Evaluates a polynomial. +* +* ## Notes +* +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the polynomial +* @return evaluated polynomial +*/ +static double polyval_c( const double x ) { + return 0.025721014990011306 + (x * (0.08247596616699963 + (x * (-0.0025328157302663564 + (x * (0.0006099292666946337 + (x * (-0.00033543297638406 + (x * 0.000250505279903))))))))); +} + +// END: polyval_c + +// BEGIN: polyval_d + +/** +* Evaluates a polynomial. +* +* ## Notes +* +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the polynomial +* @return evaluated polynomial +*/ +static double polyval_d( const double x ) { + return 0.08333333333333333 + (x * (-0.002777777777777778 + (x * (0.0007936507936507937 + (x * -0.0005952380952380953))))); +} + +// END: polyval_d + +// BEGIN: rational_ak0bk0 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak0bk0( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return -0.3333333333438; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = -0.3333333333438 + (x * (-0.2070740359969 + (x * (-0.05041806657154 + (x * (-0.004923635739372 + (x * -0.00004293658292782))))))); + s2 = 1.0 + (x * (0.7045554412463 + (x * (0.2118190062224 + (x * (0.03048648397436 + (x * 0.001605037988091))))))); + } else { + ix = 1.0 / x; + s1 = -0.00004293658292782 + (ix * (-0.004923635739372 + (ix * (-0.05041806657154 + (ix * (-0.2070740359969 + (ix * -0.3333333333438))))))); + s2 = 0.001605037988091 + (ix * (0.03048648397436 + (ix * (0.2118190062224 + (ix * (0.7045554412463 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak0bk0 + +// BEGIN: rational_ak1bk1 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak1bk1( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return -0.0172847633523; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = -0.0172847633523 + (x * (-0.0159372646475 + (x * (-0.00464910887221 + (x * (-0.00060683488776 + (x * -0.00000614830384279))))))); + s2 = 1.0 + (x * (0.764050615669 + (x * (0.297143406325 + (x * (0.0579490176079 + (x * 0.00574558524851))))))); + } else { + ix = 1.0 / x; + s1 = -0.00000614830384279 + (ix * (-0.00060683488776 + (ix * (-0.00464910887221 + (ix * (-0.0159372646475 + (ix * -0.0172847633523))))))); + s2 = 0.00574558524851 + (ix * (0.0579490176079 + (ix * (0.297143406325 + (ix * (0.764050615669 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak1bk1 + +// BEGIN: rational_ak2bk2 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak2bk2( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return -0.0172839517431; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = -0.0172839517431 + (x * (-0.0146362417966 + (x * (-0.00357406772616 + (x * (-0.000391032032692 + (x * 0.00000249634036069))))))); + s2 = 1.0 + (x * (0.690560400696 + (x * (0.249962384741 + (x * (0.0443843438769 + (x * 0.00424073217211))))))); + } else { + ix = 1.0 / x; + s1 = 0.00000249634036069 + (ix * (-0.000391032032692 + (ix * (-0.00357406772616 + (ix * (-0.0146362417966 + (ix * -0.0172839517431))))))); + s2 = 0.00424073217211 + (ix * (0.0443843438769 + (ix * (0.249962384741 + (ix * (0.690560400696 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak2bk2 + +// BEGIN: rational_ak3bk3 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak3bk3( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return 0.99994466948; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = 0.99994466948 + (x * (104.649839762 + (x * (857.204033806 + (x * (731.901559577 + (x * 45.5174411671))))))); + s2 = 1.0 + (x * (104.526456943 + (x * (823.313447808 + (x * (3119.93802124 + (x * 3970.03311219))))))); + } else { + ix = 1.0 / x; + s1 = 45.5174411671 + (ix * (731.901559577 + (ix * (857.204033806 + (ix * (104.649839762 + (ix * 0.99994466948))))))); + s2 = 3970.03311219 + (ix * (3119.93802124 + (ix * (823.313447808 + (ix * (104.526456943 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak3bk3 + +// BEGIN: rational_ak4bk4 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak4bk4( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return 0.0495346498136; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = 0.0495346498136 + (x * (0.0299521337141 + (x * (0.00688296911516 + (x * (0.000512634846317 + (x * -0.0000201411722031))))))); + s2 = 1.0 + (x * (0.759803615283 + (x * (0.261547111595 + (x * (0.0464854522477 + (x * 0.00403751193496))))))); + } else { + ix = 1.0 / x; + s1 = -0.0000201411722031 + (ix * (0.000512634846317 + (ix * (0.00688296911516 + (ix * (0.0299521337141 + (ix * 0.0495346498136))))))); + s2 = 0.00403751193496 + (ix * (0.0464854522477 + (ix * (0.261547111595 + (ix * (0.759803615283 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak4bk4 + +// BEGIN: rational_ak5bk5 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak5bk5( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return 0.00452313583942; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = 0.00452313583942 + (x * (0.00120744920113 + (x * (-0.0000789724156582 + (x * (-0.0000504476066942 + (x * -0.00000535770949796))))))); + s2 = 1.0 + (x * (0.912203410349 + (x * (0.405368773071 + (x * (0.0901638932349 + (x * 0.00948935714996))))))); + } else { + ix = 1.0 / x; + s1 = -0.00000535770949796 + (ix * (-0.0000504476066942 + (ix * (-0.0000789724156582 + (ix * (0.00120744920113 + (ix * 0.00452313583942))))))); + s2 = 0.00948935714996 + (ix * (0.0901638932349 + (ix * (0.405368773071 + (ix * (0.912203410349 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak5bk5 + +// BEGIN: rational_ak6bk6 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak6bk6( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return 0.00439937562904; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = 0.00439937562904 + (x * (0.000487225670639 + (x * (-0.000128470657374 + (x * (0.00000529110969589 + (x * 1.5716677175e-7))))))); + s2 = 1.0 + (x * (0.794435257415 + (x * (0.333094721709 + (x * (0.0703527806143 + (x * 0.00806110846078))))))); + } else { + ix = 1.0 / x; + s1 = 1.5716677175e-7 + (ix * (0.00000529110969589 + (ix * (-0.000128470657374 + (ix * (0.000487225670639 + (ix * 0.00439937562904))))))); + s2 = 0.00806110846078 + (ix * (0.0703527806143 + (ix * (0.333094721709 + (ix * (0.794435257415 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak6bk6 + +// BEGIN: rational_ak7bk7 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak7bk7( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return -0.0011481191232; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = -0.0011481191232 + (x * (-0.112850923276 + (x * (1.51623048511 + (x * (-0.218472031183 + (x * 0.0730002451555))))))); + s2 = 1.0 + (x * (14.2482206905 + (x * (69.7360396285 + (x * (218.938950816 + (x * 277.067027185))))))); + } else { + ix = 1.0 / x; + s1 = 0.0730002451555 + (ix * (-0.218472031183 + (ix * (1.51623048511 + (ix * (-0.112850923276 + (ix * -0.0011481191232))))))); + s2 = 277.067027185 + (ix * (218.938950816 + (ix * (69.7360396285 + (ix * (14.2482206905 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak7bk7 + +// BEGIN: rational_ak8bk8 + +/** +* Evaluates a rational function (i.e., the ratio of two polynomials described by the coefficients stored in \\(P\\) and \\(Q\\)). +* +* ## Notes +* +* - Coefficients should be sorted in ascending degree. +* - The implementation uses [Horner's rule][horners-method] for efficient computation. +* +* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method +* +* @param x value at which to evaluate the rational function +* @return evaluated rational function +*/ +static double rational_ak8bk8( const double x ) { + double ax; + double ix; + double s1; + double s2; + if ( x == 0.0 ) { + return -0.000145727889667; + } + if ( x < 0.0 ) { + ax = -x; + } else { + ax = x; + } + if ( ax <= 1.0 ) { + s1 = -0.000145727889667 + (x * (-0.290806748131 + (x * (-13.308504545 + (x * (199.722374056 + (x * -11.4311378756))))))); + s2 = 1.0 + (x * (139.612587808 + (x * (2189.01116348 + (x * (7115.24019009 + (x * 45574.6081453))))))); + } else { + ix = 1.0 / x; + s1 = -11.4311378756 + (ix * (199.722374056 + (ix * (-13.308504545 + (ix * (-0.290806748131 + (ix * -0.000145727889667))))))); + s2 = 45574.6081453 + (ix * (7115.24019009 + (ix * (2189.01116348 + (ix * (139.612587808 + (ix * 1.0))))))); + } + return s1 / s2; +} + +// END: rational_ak8bk8 + +/* End auto-generated functions. */ + +/** +* Computes the sum of a Chebyshev polynomial. +* +* @param n degree of polynomial +* @param t input value +* @return Chebyshev sum +*/ +static double chepolsum( const int32_t n, const double t ) { + double tt; + double u0; + double u1; + double u2; + int32_t k; + + u0 = 0.0; + u1 = 0.0; + tt = t + t; + k = n; + do { + u2 = u1; + u1 = u0; + u0 = ( tt*u1 ) - u2 + A[ k ]; + k -= 1; + } while ( k >= 0 ); + return ( u0-u2 ) / 2.0; +} + +/** +* Computes the Stirling series corresponding to asymptotic series for the logarithm of the gamma function. +* +* ```tex +* \frac{1}{12x}-\frac{1}{360x^3}\ldots; x \ge 3 +* ``` +* +* @param x input value +* @return function value +*/ +static double stirling( const double x ) { + double z; + + if ( x < SMALLEST_NORMAL_FLOAT32 ) { + return MAX_FLOAT32; + } + if ( x < 1.0 ) { + return stdlib_base_gammaln( x+1.0 ) - ( ( x+0.5 ) * stdlib_base_ln( x ) ) + x - LN_SQRT_TWO_PI; + } + if ( x < 2.0 ) { + return stdlib_base_gammaln( x ) - ( ( x-0.5 ) * stdlib_base_ln( x ) ) + x - LN_SQRT_TWO_PI; + } + if ( x < 3.0 ) { + return stdlib_base_gammaln( x-1.0 ) - ( ( x-0.5 ) * stdlib_base_ln( x ) ) + x - LN_SQRT_TWO_PI + stdlib_base_ln( x-1.0 ); + } + if ( x < 12.0 ) { + z = ( 18.0/( x*x ) ) - 1.0; + return chepolsum( 17, z ) / ( 12.0*x ); + } + z = 1.0 / ( x*x ); + if ( x < 1000.0 ) { + return polyval_c( z ) / ( C6+z ) / x; + } + return polyval_d( z ) / x; +} + +/** +* Computes the regulated gamma function. +* +* @param x input value +* @return function value +*/ +static double gamstar( const double x ) { + if ( x >= 3.0 ) { + return stdlib_base_exp( stirling( x ) ); + } + if ( x > 0.0 ) { + return stdlib_base_gamma( x ) / ( stdlib_base_exp( -x + ( ( x-0.5 ) * stdlib_base_ln( x ) ) ) * SQRT_TWO_PI ); + } + // Case: x <= 0.0 + return MAX_FLOAT32; +} + +/** +* Returns the positive number satisfying \\( \eta^2/2=\lambda-1-\ln(\lambda) \\) with \\( \operatorname{sign}(\lambda-1)=\operatorname{sign}(\eta) \\). +* +* @param eta eta value +* @return value satisfying equation +*/ +static double lambdaeta( const double eta ) { + double AK[ 6 ]; + double L2; + double L3; + double L4; + double L5; + double la; + double L; + double q; + double r; + double s; + + s = eta * eta * 0.5; + if ( eta == 0.0 ) { + la = 0.0; + } else if ( eta < -1.0 ) { + r = stdlib_base_exp( -1.0 - s ); + la = polyval_ak1( r ); + } else if ( eta < 1.0 ) { + r = eta; + la = polyval_ak2( r ); + } else { + r = 11.0 + s; + L = stdlib_base_ln( r ); + la = r + L; + r = 1.0 / r; + L2 = L * L; + L3 = L2 * L; + L4 = L3 * L; + L5 = L4 * L; + AK[ 0 ] = 1.0; + AK[ 1 ] = ( 2.0-L ) * 0.5; + AK[ 2 ] = ( ( -9.0*L ) + 6.0 + ( 2.0*L2 ) ) / 6.0; + AK[ 3 ] = -( (3.0*L3) + (36.0*L) - (22.0*L2) - 12.0 ) * ONEO12; + AK[ 4 ] = ( 60.0 + (350.0*L2) - (300.0*L) - (125.0*L3) + (12.0*L4) ) / 60.0; + AK[ 5 ] = -( -120.0 - (274.0*L4) + (900.0*L) - (1700.0*L2) + (1125.0*L3) + (20.0*L5) ) * ONEO120; + la += ( L * r * ( AK[ 0 ] + ( r * ( AK[ 1 ] + ( r * ( AK[ 2 ] + ( r * ( AK[ 3 ] + ( r * ( AK[ 4 ] + ( r*AK[ 5 ] ) ) ) ) ) ) ) ) ) ) ); + } + if ( + ( eta > -3.5 && eta < -0.03 ) || + ( eta > 0.03 && eta < 40.0 ) + ) { + r = 1.0; + q = la; + do { + la = q * ( s+stdlib_base_ln( q ) ) / ( q-1.0 ); + r = stdlib_base_abs( ( q/la ) - 1.0 ); + q = la; + } while ( r > THRESHOLD ); + } + return la; +} + +/** +* Evaluates the `eps1` function. +* +* @param eta eta value +* @return function value +*/ +static double eps1( const double eta ) { + double la; + + if ( stdlib_base_abs( eta ) < 1.0 ) { + return rational_ak0bk0( eta ); + } + la = lambdaeta( eta ); + return stdlib_base_ln( eta / ( la-1.0 ) ) / eta; +} + +/** +* Evaluates the `eps2` function. +* +* @param eta eta value +* @return function value +*/ +static double eps2( const double eta ) { + double lnmeta; + double x; + + if ( eta < -5.0 ) { + x = eta * eta; + lnmeta = stdlib_base_ln( -eta ); + return ( 12.0 - x - ( 6.0*( lnmeta*lnmeta ) ) ) / ( 12.0*x*eta ); + } + if ( eta < -2.0 ) { + return rational_ak1bk1( eta ); + } + if ( eta < 2.0 ) { + return rational_ak2bk2( eta ); + } + if ( eta < 1000.0 ) { + return rational_ak3bk3( eta ) / ( -12.0*eta ); + } + return -1.0 / ( 12.0*eta ); +} + +/** +* Evaluates the `eps3` function. +* +* @param eta eta value +* @return function value +*/ +static double eps3( const double eta ) { + double x; + double y; + + if ( eta < -8.0 ) { + x = eta * eta; + y = stdlib_base_ln( -eta ) / eta; + return ( -30.0 + ( eta*y*( (6.0*x*y*y) - 12.0 + x ) ) ) / ( 12.0*eta*x*x ); + } + if ( eta < -4.0 ) { + return rational_ak4bk4( eta ) / ( eta*eta ); + } + if ( eta < -2.0 ) { + return rational_ak5bk5( eta ); + } + if ( eta < 2.0 ) { + return rational_ak6bk6( eta ); + } + if ( eta < 10.0 ) { + x = 1.0 / eta; + return rational_ak7bk7( x ) / ( eta*eta ); + } + if ( eta < 100.0 ) { + x = 1.0 / eta; + return rational_ak8bk8( x ) / ( eta*eta ); + } + return -stdlib_base_ln( eta ) / ( 12.0*eta*eta*eta ); +} + +/** +* Implementation of the high order Newton-like method. +* +* @param x0 initial value +* @param a scale parameter +* @param m indicator +* @param p probability value +* @param q probability value +* @param lgama logarithm of scale parameter +* @param invfp one over `fp` +* @param pcase boolean indicating whether `p < 0.5` +* @return function value of the inverse +*/ +static double higherNewton( double x0, const double a, const int32_t m, const double p, const double q, const double lgama, const double invfp, const bool pcase ) { + double dlnr; + double xini; + double ck0; + double ck1; + double ck2; + double a2; + double x2; + double px; + double qx; + double xr; + double t; + int32_t n; + double r; + double x; + + x = x0; + t = 1.0; + n = 1; + a2 = a * a; + xini = x0; + do { + x = x0; + x2 = x * x; + if ( m == 0 ) { + dlnr = ( ( 1.0-a ) * stdlib_base_ln( x ) ) + x + lgama; + if ( dlnr > stdlib_base_ln( MAX_FLOAT32 ) ) { + // Overflow problems in one or more steps of the computation; the initial approximation to the root is returned... + return xini; + } + r = stdlib_base_exp( dlnr ); + } else { + r = -invfp * x; + } + if ( pcase ) { + // Call: gammainc( x, s[, regularized = true ][, upper = false ] ) + px = stdlib_base_gammainc( x, a, true, false ); + ck0 = -r * ( px - p ); + } else { + // Call: gammainc( x, s[, regularized = true ][, upper = true ] ) + qx = stdlib_base_gammainc( x, a, true, true ); + ck0 = r * ( qx - q ); + } + r = ck0; + if ( ( p > 1e-120 ) || ( n > 1 ) ) { + ck1 = 0.5 * ( x - a + 1.0 ) / x; + ck2 = ( (2.0*x2) - (4.0*x*a) + (4.0*x) + (2.0*a2) - (3.0*a) + 1.0 ) / x2; + ck2 /= 6.0; + x0 = x + ( r * ( 1.0 + ( r * ( ck1 + (r*ck2) ) ) ) ); + } else { + x0 = x + r; + } + t = stdlib_base_abs( ( x/x0 ) - 1.0 ); + n += 1; + x = x0; + if ( x < 0.0 ) { + x = xini; + n = 100; + } + } while ( ( t > 2e-14 ) && ( n < 35 ) ); + if ( x == 0.0 || stdlib_base_is_nan( x ) ) { + xr = 0.0; + } else { + xr = x; + } + return xr; +} + +/** +* Computes `x` in the equations `P(a,xr) = p` and `Q(a,xr) = q`, where `a` is a positive parameter and `p` and `q` satisfy `p+q = 1`. +* +* ## Notes +* +* - The equation is inverted with `min(p,q)`. +* +* @param a scale value of incomplete gamma function +* @param p probability value +* @param q probability value +* @return solution of the equations `P(a,xr) = p` and `Q(a,xr) = q` where `a` is a positive parameter +*/ +static double compute( const double a, const double p, const double q ) { + double CK[ 5 ]; + double ap1inv; + double invfp; + double lgama; + bool pcase; + double porq; + double ainv; + double logr; + double ap22; + double ap14; + double ap13; + double ap12; + double vgam; + double vmin; + double xini; + double ap1; + double ap2; + double ap3; + double eta; + double p6; + double p5; + double x0; + double a2; + double L2; + double L3; + double L4; + double b2; + double b3; + double p3; + double a4; + double fp; + double p4; + double p2; + double a3; + double xr; + double ck; + double b; + double L; + int32_t i; + int32_t k; + int32_t m; + double r; + double s; + double t; + double y; + + invfp = 0.0; + lgama = 0.0; + if ( p < HALF ) { + pcase = true; + porq = p; + s = -1.0; + } else { + pcase = false; + porq = q; + s = 1.0; + } + k = 0; + if ( stdlib_base_abs( a-1.0 ) < 1.0e-4 ) { + m = 0; + if ( pcase ) { + if ( p < 1.0e-3 ) { + p2 = p * p; + p3 = p2 * p; + p4 = p3 * p; + p5 = p4 * p; + p6 = p5 * p; + x0 = p + ( p2*HALF ) + ( p3*ONEO3 ) + ( p4*ONEO4 ) + ( p5*ONEO5 ) + ( p6*ONEO6 ); + } else { + x0 = -stdlib_base_ln( 1.0-p ); + } + } else { + x0 = -stdlib_base_ln( q ); + } + if ( a == 1.0 ) { + k = 2; + xr = x0; + } else { + lgama = stdlib_base_gammaln( a ); + k = 1; + } + } + if ( q < 1.0e-30 && a < HALF ) { + m = 0; + x0 = -stdlib_base_ln( q*stdlib_base_gamma( a ) ) + ( ( a-1.0 ) * stdlib_base_ln( -stdlib_base_ln( q*stdlib_base_gamma( a ) ) ) ); + k = 1; + lgama = stdlib_base_gammaln( a ); + } + if ( a > 1.0 && a < 500.0 && p < 1.0e-80 ) { + m = 0; + ainv = 1.0 / a; + ap1inv = 1.0 / ( a+1.0 ); + x0 = ( stdlib_base_gammaln( a+1.0 ) + stdlib_base_ln( p ) ) * ainv; + x0 = stdlib_base_exp( x0 ); + xini = x0; + for ( i = 0; i < 10; i++ ) { + x0 = xini * stdlib_base_exp( x0*ainv ) * stdlib_base_pow( 1.0-( x0*ap1inv ), ainv ); + } + k = 1; + lgama = stdlib_base_gammaln( a ); + } + logr = ( 1.0/a ) * ( stdlib_base_ln( p ) + stdlib_base_gammaln( a+1.0 ) ); + if ( ( logr < stdlib_base_ln( ONEO5 * ( 1.0+a ) ) ) && ( k == 0 ) ) { + r = stdlib_base_exp( logr ); + m = 0; + a2 = a * a; + a3 = a2 * a; + a4 = a3 * a; + ap1 = a + 1.0; + ap12 = ap1 * ap1; + ap13 = ap1 * ap12; + ap14 = ap12 * ap12; + ap2 = a + 2.0; + ap22 = ap2 * ap2; + ap3 = a + 3.0; + CK[ 0 ] = 1.0; + CK[ 1 ] = 1.0 / ap1; + CK[ 2 ] = HALF * ( ( 3.0*a ) + 5.0 ) / ( ap12*ap2 ); + CK[ 3 ] = ONEO3 * ( 31.0 + (8.0*a2) + (33.0*a) ) / ( ap13*ap2*ap3 ); + CK[ 4 ] = ONEO24 * ( 2888.0 + (1179.0*a3) + (125.0*a4) + (3971.0*a2) + (5661.0*a) ) / ( ap14*ap22*ap3*( a+4.0 ) ); + x0 = r * ( CK[ 0 ] + ( r * ( CK[ 1 ] + ( r * ( CK[ 2 ] + ( r * ( CK[ 3 ] + ( r*CK[ 4 ] ) ) ) ) ) ) ) ); + lgama = stdlib_base_gammaln( a ); + k = 1; + } + if ( ( a < 10.0 ) && ( k == 0 ) ) { + vgam = stdlib_base_sqrt( a ) / ( gamstar( a )*SQRT_TWO_PI ); + vmin = stdlib_base_min( 0.02, vgam ); + if ( q < vmin ) { + m = 0; + b = 1.0 - a; + b2 = b * b; + b3 = b2 * b; + eta = stdlib_base_sqrt( -2.0/a * stdlib_base_ln( q/vgam ) ); + x0 = a * lambdaeta( eta ); + L = stdlib_base_ln( x0 ); + if ( x0 > 5.0 ) { + L2 = L * L; + L3 = L2 * L; + L4 = L3 * L; + r = 1.0 / x0; + CK[ 0 ] = L - 1.0; + CK[ 1 ] = ( (3.0*b) - (2.0*b*L) + L2 - ( 2.0*L ) + 2.0 ) * HALF; + CK[ 2 ] = ( (24.0*b*L) - (11.0*b2) - (24.0*b) - (6.0*L2) + (12.0*L) - 12.0 - (9.0*b*L2) + (6.0*b2*L) + (2.0*L3) ) * ONEO6; + CK[ 3 ] = ( (-12.0*b3*L) + (8.04*b*L2) - (114.0*b2*L) + (72.0+(36.0*L2)) + (((3.0*L4)-(72.0*L)+162.0) * (b-(168.0*b*L))) - ((12.0*L3)+(25.0*b3)) - ( (22.0*b*L3)+(36.0*b2*L2)+(120.0*b2) ) ) * ONEO12; + CK[ 4 ] = 0.0; + x0 = x0 - L + ( b*r*( CK[ 0 ] + ( r * ( CK[ 1 ] + ( r * ( CK[ 2 ] + ( r * ( CK[ 3 ] + ( r*CK[ 4 ] ) ) ) ) ) ) ) ) ); + } else { + r = 1.0 / x0; + ck = L - 1.0; + t = L - ( b*r*ck ); + if ( t < x0 ) { + x0 -= t; + } + } + lgama = stdlib_base_gammaln( a ); + k = 1; + } + } + if ( ( stdlib_base_abs( porq-HALF ) < 1.0e-5 ) && ( k == 0 ) ) { + m = 0; + ainv = 1.0 / a; + x0 = a - ONEO3 + ( ( 0.0197530864197530864197530864198 + ( 0.00721144424848128551832255535959*ainv ) ) * ainv ); + lgama = stdlib_base_gammaln( a ); + k = 1; + } + if ( ( a < 1.0 ) && ( k == 0 ) ) { + m = 0; + if ( pcase ) { + x0 = stdlib_base_exp( ( 1.0/a ) * ( stdlib_base_ln( porq ) + stdlib_base_gammaln( a+1.0 ) ) ); + } else { + x0 = stdlib_base_exp( ( 1.0/a ) * ( stdlib_base_ln( 1.0-porq ) + stdlib_base_gammaln( a+1.0 ) ) ); + } + lgama = stdlib_base_gammaln( a ); + k = 1; + } + if ( k == 0 ) { + m = 1; + ainv = 1.0 / a; + r = stdlib_base_erfcinv( 2.0 * porq ); + eta = s * r / stdlib_base_sqrt( a*HALF ); + if ( r < MAX_FLOAT32 ) { + eta += ( eps1( eta ) + ( ( eps2( eta )+( eps3( eta )*ainv ) )*ainv ) ) * ainv; + x0 = a * lambdaeta( eta ); + y = eta; + fp = -stdlib_base_sqrt( a/TWO_PI ) * stdlib_base_exp( -HALF*a*y*y ) / ( gamstar( a ) ); + invfp = 1.0 / fp; + } else { + // Overflow problems in one or more steps of the computation... + return STDLIB_CONSTANT_FLOAT64_NAN; + } + } + if ( k < 2 ) { + xr = higherNewton( x0, a, m, p, q, lgama, invfp, pcase ); + } + return xr; +} + +/** +* Inverts the lower gamma function; i.e., computes `xr` such that `P(a,xr) = p`. +* +* ## Method +* +* The present code uses different methods of computation depending on the values of the input values: Taylor, asymptotic expansions and high-order Newton methods. +* +* ## Notes +* +* - The claimed accuracy obtained using this inversion routine is near `1e-12`. +* +* ## References +* +* - A. Gil, J. Segura and N.M. Temme, GammaCHI: a package for the inversion and computation of the gamma and chi-square distribution functions (central and noncentral). Computer Physics Commun +* - A. Gil, J. Segura and N.M. Temme. Efficient and accurate algorithms for the computation and inversion of the incomplete gamma function ratios. SIAM J Sci Comput. (2012) 34(6), A2965-A2981 +* +* @param p probability value +* @param a scale parameter +* @param upper boolean indicating if the function should invert the upper tail of the incomplete gamma function instead; i.e., compute `xr` such that `Q(a,xr) = p` +* @return function value of the inverse +* +* @example +* double y = stdlib_base_gammaincinv( 0.5, 2.0, false ); +* // returns ~1.678 +*/ +double stdlib_base_gammaincinv( const double p, const double a, const bool upper ) { + if ( stdlib_base_is_nan( p ) || stdlib_base_is_nan( a ) ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + if ( a < SMALLEST_NORMAL_FLOAT32 ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + if ( p > 1.0 || p < 0.0 ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + // Case: invert upper gamma function + if ( upper ) { + if ( p == 0.0 ) { + return PINF; + } + if ( p == 1.0 ) { + return 0.0; + } + return compute( a, 1.0-p, p ); + } + // Default: invert lower gamma function + if ( p == 0.0 ) { + return 0.0; + } + if ( p == 1.0 ) { + return PINF; + } + return compute( a, p, 1.0-p ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/test/test.js b/lib/node_modules/@stdlib/math/base/special/gammaincinv/test/test.js index 9a09c68a8156..48beadd93c19 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammaincinv/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/test/test.js @@ -25,6 +25,7 @@ var incrspace = require( '@stdlib/array/base/incrspace' ); var isfinite = require( '@stdlib/math/base/assert/is-finite' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var gammaincinv = require( './../lib' ); @@ -116,54 +117,54 @@ tape( 'the function returns `NaN` if provided `p` outside the interval `[0,1]`', t.end(); }); -tape( 'the function returns `0` if provided `p = 1`', function test( t ) { +tape( 'the function returns `+Infinity` if provided `p = 1`', function test( t ) { var val; var a; var i; - a = incrspace( 0, 100, 10 ); + a = incrspace( 10, 100, 10 ); for ( i = 0; i < a.length; i++ ) { val = gammaincinv( 1, a[ i ] ); - t.notOk( val === 0, 'returns expected value' ); + t.strictEqual( val, PINF, 'returns expected value' ); } t.end(); }); -tape( 'the function returns `+Infinity` if provided `p = 0`', function test( t ) { +tape( 'the function returns `0` if provided `p = 0`', function test( t ) { var val; var a; var i; - a = incrspace( 0, 100, 10 ); + a = incrspace( 10, 100, 10 ); for ( i = 0; i < a.length; i++ ) { val = gammaincinv( 0, a[ i ] ); - t.notOk( val === PINF, 'returns expected value' ); + t.strictEqual( val, 0.0, 'returns expected value' ); } t.end(); }); -tape( 'the function returns `0` if provided `p = 0` when `upper = true`', function test( t ) { +tape( 'the function returns `+Infinity` if provided `p = 0` when `upper = true`', function test( t ) { var val; var a; var i; - a = incrspace( 0, 100, 10 ); + a = incrspace( 10, 100, 10 ); for ( i = 0; i < a.length; i++ ) { val = gammaincinv( 0, a[ i ], true ); - t.notOk( val === 0, 'returns expected value' ); + t.strictEqual( val, PINF, 'returns expected value' ); } t.end(); }); -tape( 'the function returns `+Infinity` if provided `p = 1` when `upper = true`', function test( t ) { +tape( 'the function returns `0` if provided `p = 1` when `upper = true`', function test( t ) { var val; var a; var i; - a = incrspace( 0, 100, 10 ); + a = incrspace( 10, 100, 10 ); for ( i = 0; i < a.length; i++ ) { val = gammaincinv( 1, a[ i ], true ); - t.notOk( val === PINF, 'returns expected value' ); + t.strictEqual( val, 0.0, 'returns expected value' ); } t.end(); }); @@ -195,7 +196,7 @@ tape( 'the function inverts the upper incomplete gamma function when `upper=true var b1; var b2; var i; - for ( i = 0; i < arg1.length; i++ ) { + for ( i = 0; i < upperArg1.length; i++ ) { actual = gammaincinv( upperArg1[ i ], upperArg2[ i ], true ); b1 = isfinite( actual ); @@ -203,10 +204,10 @@ tape( 'the function inverts the upper incomplete gamma function when `upper=true t.strictEqual( b1, b2, 'returned result is ' + ( (b2) ? 'finite' : 'not finite' ) ); b1 = isnan( actual ); - b2 = isnan( expected[ i ] ); + b2 = isnan( upperExpected[ i ] ); t.strictEqual( b1, b2, 'returned result is ' + ( (b1) ? '' : 'not' ) + ' NaN' ); if ( !b1 || !b2 ) { - t.ok( abs( actual - upperExpected[ i ] ) < 5e-14, 'returned result is within tolerance. actual: ' + actual + '; expected: ' + upperExpected[ i ] + '.' ); + t.strictEqual( isAlmostSameValue( actual, upperExpected[ i ], 40.0 ), true, 'returned result is within tolerance. actual: ' + actual + '; expected: ' + upperExpected[ i ] + '.' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/gammaincinv/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/gammaincinv/test/test.native.js new file mode 100644 index 000000000000..1549d00a26fd --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/gammaincinv/test/test.native.js @@ -0,0 +1,267 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var incrspace = require( '@stdlib/array/base/incrspace' ); +var isfinite = require( '@stdlib/math/base/assert/is-finite' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); + + +// VARIABLES // + +var gammaincinv = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( gammaincinv instanceof Error ) +}; + + +// FIXTURES // + +var arg1 = require( './fixtures/r/arg1.json' ); +var arg2 = require( './fixtures/r/arg2.json' ); +var expected = require( './fixtures/r/expected.json' ); +var smallArg1 = require( './fixtures/r/small_arg1.json' ); +var smallArg2 = require( './fixtures/r/small_arg2.json' ); +var smallExpected = require( './fixtures/r/small_expected.json' ); +var largeArg1 = require( './fixtures/r/large_arg1.json' ); +var largeArg2 = require( './fixtures/r/large_arg2.json' ); +var largeExpected = require( './fixtures/r/large_expected.json' ); +var upperArg1 = require( './fixtures/r/upper_arg1.json' ); +var upperArg2 = require( './fixtures/r/upper_arg2.json' ); +var upperExpected = require( './fixtures/r/upper_expected.json' ); + +var i; +var v; +for ( i = 0; i < expected.length; i++ ) { + v = expected[ i ]; + if ( v === 'Inf' ) { + expected[ i ] = PINF; + } + else if ( v === 'NaN' ) { + expected[ i ] = NaN; + } +} +for ( i = 0; i < smallExpected.length; i++ ) { + v = smallExpected[ i ]; + if ( v === 'Inf' ) { + smallExpected[ i ] = PINF; + } + else if ( v === 'NaN' ) { + smallExpected[ i ] = NaN; + } +} +for ( i = 0; i < largeExpected.length; i++ ) { + v = largeExpected[ i ]; + if ( v === 'Inf' ) { + largeExpected[ i ] = PINF; + } + else if ( v === 'NaN' ) { + largeExpected[ i ] = NaN; + } +} +for ( i = 0; i < upperExpected.length; i++ ) { + v = upperExpected[ i ]; + if ( v === 'Inf' ) { + upperExpected[ i ] = PINF; + } + else if ( v === 'NaN' ) { + upperExpected[ i ] = NaN; + } +} + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof gammaincinv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `NaN` if provided a `NaN`', opts, function test( t ) { + var val; + + val = gammaincinv( NaN, 2 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + val = gammaincinv( 0.5, NaN ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `NaN` if provided `p` outside the interval `[0,1]`', opts, function test( t ) { + var val; + + val = gammaincinv( 1.2, 2 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + val = gammaincinv( -0.1, 2 ); + t.strictEqual( isnan( val ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `+Infinity` if provided `p = 1`', opts, function test( t ) { + var val; + var a; + var i; + + a = incrspace( 10, 100, 10 ); + for ( i = 0; i < a.length; i++ ) { + val = gammaincinv( 1, a[ i ] ); + t.strictEqual( val, PINF, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `0` if provided `p = 0`', opts, function test( t ) { + var val; + var a; + var i; + + a = incrspace( 10, 100, 10 ); + for ( i = 0; i < a.length; i++ ) { + val = gammaincinv( 0, a[ i ] ); + t.strictEqual( val, 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `+Infinity` if provided `p = 0` when `upper = true`', opts, function test( t ) { + var val; + var a; + var i; + + a = incrspace( 10, 100, 10 ); + for ( i = 0; i < a.length; i++ ) { + val = gammaincinv( 0, a[ i ], true ); + t.strictEqual( val, PINF, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `0` if provided `p = 1` when `upper = true`', opts, function test( t ) { + var val; + var a; + var i; + + a = incrspace( 10, 100, 10 ); + for ( i = 0; i < a.length; i++ ) { + val = gammaincinv( 1, a[ i ], true ); + t.strictEqual( val, 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function inverts the lower incomplete gamma function', opts, function test( t ) { + var actual; + var b1; + var b2; + var i; + for ( i = 0; i < arg1.length; i++ ) { + actual = gammaincinv( arg1[ i ], arg2[ i ] ); + + b1 = isfinite( actual ); + b2 = isfinite( expected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b2) ? 'finite' : 'not finite' ) ); + + b1 = isnan( actual ); + b2 = isnan( expected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b1) ? '' : 'not' ) + ' NaN' ); + if ( !b1 || !b2 ) { + t.strictEqual( isAlmostSameValue( actual, expected[ i ], 25.0 ), true, 'returned result is within tolerance. actual: ' + actual + '; expected: ' + expected[ i ] + '.' ); + } + } + t.end(); +}); + +tape( 'the function inverts the upper incomplete gamma function when `upper=true`', opts, function test( t ) { + var actual; + var b1; + var b2; + var i; + for ( i = 0; i < upperArg1.length; i++ ) { + actual = gammaincinv( upperArg1[ i ], upperArg2[ i ], true ); + + b1 = isfinite( actual ); + b2 = isfinite( upperExpected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b2) ? 'finite' : 'not finite' ) ); + + b1 = isnan( actual ); + b2 = isnan( upperExpected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b1) ? '' : 'not' ) + ' NaN' ); + if ( !b1 || !b2 ) { + t.strictEqual( isAlmostSameValue( actual, upperExpected[ i ], 40.0 ), true, 'returned result is within tolerance. actual: ' + actual + '; expected: ' + upperExpected[ i ] + '.' ); + } + } + t.end(); +}); + +tape( 'the function inverts the lower incomplete gamma function for `p` smaller than `1e-4`', opts, function test( t ) { + var actual; + var b1; + var b2; + var i; + for ( i = 0; i < smallArg2.length; i++ ) { + actual = gammaincinv( smallArg1[ i ], smallArg2[ i ] ); + + b1 = isfinite( actual ); + b2 = isfinite( smallExpected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b2) ? 'finite' : 'not finite' ) ); + + b1 = isnan( actual ); + b2 = isnan( smallExpected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b1) ? '' : 'not' ) + ' NaN' ); + if ( !b1 || !b2 ) { + t.strictEqual( isAlmostSameValue( actual, smallExpected[ i ], 400.0 ), true, 'returned result is within tolerance. actual: ' + actual + '; expected: ' + smallExpected[ i ] + '.' ); + } + } + t.end(); +}); + +tape( 'the function inverts the lower incomplete gamma function for `p` larger than `0.9`', opts, function test( t ) { + var actual; + var b1; + var b2; + var i; + + for ( i = 0; i < largeArg1.length; i++ ) { + actual = gammaincinv( largeArg1[ i ], largeArg2[ i ] ); + + b1 = isfinite( actual ); + b2 = isfinite( largeExpected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b2) ? 'finite' : 'not finite' ) ); + + b1 = isnan( actual ); + b2 = isnan( largeExpected[ i ] ); + t.strictEqual( b1, b2, 'returned result is ' + ( (b1) ? '' : 'not' ) + ' NaN' ); + if ( !b1 || !b2 ) { + t.strictEqual( isAlmostSameValue( actual, largeExpected[ i ], 50.0 ), true, 'returned result is within tolerance. actual: ' + actual + '; expected: ' + largeExpected[ i ] + '.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/gammasgnf/package.json b/lib/node_modules/@stdlib/math/base/special/gammasgnf/package.json index 5a6f87dcefae..30f9e6d5526a 100644 --- a/lib/node_modules/@stdlib/math/base/special/gammasgnf/package.json +++ b/lib/node_modules/@stdlib/math/base/special/gammasgnf/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/math/base/special/gammasgnf", "version": "0.0.0", - "description": "Computes the sign of the gamma function for a single-precision floating-point number.", + "description": "Compute the sign of the gamma function for a single-precision floating-point number.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/math/base/special/gcd/manifest.json b/lib/node_modules/@stdlib/math/base/special/gcd/manifest.json index 87c65f0cf256..631687723ab4 100644 --- a/lib/node_modules/@stdlib/math/base/special/gcd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/gcd/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/special/fmod", "@stdlib/math/base/assert/is-integer", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/special/fmod", "@stdlib/math/base/assert/is-integer", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/special/fmod", "@stdlib/math/base/assert/is-integer", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/gcd/src/main.c b/lib/node_modules/@stdlib/math/base/special/gcd/src/main.c index 9167bb5de935..39da1eb6161a 100644 --- a/lib/node_modules/@stdlib/math/base/special/gcd/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/gcd/src/main.c @@ -22,6 +22,7 @@ #include "stdlib/math/base/assert/is_integer.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include // 2^63 - 1 @@ -155,7 +156,7 @@ double stdlib_base_gcd( const double a, const double b ) { double bc; if ( stdlib_base_is_nan( a ) || stdlib_base_is_nan( b ) ) { - return 0.0/0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( a == STDLIB_CONSTANT_FLOAT64_PINF || @@ -163,10 +164,10 @@ double stdlib_base_gcd( const double a, const double b ) { a == STDLIB_CONSTANT_FLOAT64_NINF || b == STDLIB_CONSTANT_FLOAT64_NINF ) { - return 0.0/0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( !( stdlib_base_is_integer( a ) && stdlib_base_is_integer( b ) ) ) { - return 0.0/0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } ac = a; bc = b; diff --git a/lib/node_modules/@stdlib/math/base/special/heaviside/manifest.json b/lib/node_modules/@stdlib/math/base/special/heaviside/manifest.json index 4fcf122c4cbc..a33c9e735070 100644 --- a/lib/node_modules/@stdlib/math/base/special/heaviside/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/heaviside/manifest.json @@ -41,7 +41,8 @@ "@stdlib/napi/argv-int32", "@stdlib/napi/argv-double", "@stdlib/napi/create-double", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -69,7 +71,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/heaviside/src/main.c b/lib/node_modules/@stdlib/math/base/special/heaviside/src/main.c index 4827d43530f3..6d0e9944e044 100644 --- a/lib/node_modules/@stdlib/math/base/special/heaviside/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/heaviside/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/heaviside.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" /** @@ -32,7 +33,7 @@ */ double stdlib_base_heaviside( const double x, const enum STDLIB_BASE_HEAVISIDE_CONTINUITY continuity ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x > 0.0 ) { return 1.0; @@ -47,9 +48,9 @@ double stdlib_base_heaviside( const double x, const enum STDLIB_BASE_HEAVISIDE_C case STDLIB_BASE_HEAVISIDE_CONTINUITY_RIGHT_CONTINUOUS: return 1.0; case STDLIB_BASE_HEAVISIDE_CONTINUITY_DISCONTINUOUS: - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; default: - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } } return 0.0; diff --git a/lib/node_modules/@stdlib/math/base/special/hyp2f1/package.json b/lib/node_modules/@stdlib/math/base/special/hyp2f1/package.json index 5e92207bbc24..841ee50ad199 100644 --- a/lib/node_modules/@stdlib/math/base/special/hyp2f1/package.json +++ b/lib/node_modules/@stdlib/math/base/special/hyp2f1/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/math/base/special/hyp2f1", "version": "0.0.0", - "description": "Evaluates the Gaussian hypergeometric function.", + "description": "Evaluate the Gaussian hypergeometric function.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json b/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json index 755db550a9d9..bbc29643f6e7 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/hypot/manifest.json @@ -42,7 +42,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/sqrt", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/hypot/src/main.c b/lib/node_modules/@stdlib/math/base/special/hypot/src/main.c index f4c40fd94752..15c3aee873e2 100644 --- a/lib/node_modules/@stdlib/math/base/special/hypot/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/hypot/src/main.c @@ -21,6 +21,7 @@ #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/sqrt.h" #include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float64/nan.h" /** * Computes the hypotenuse avoiding overflow and underflow. @@ -43,7 +44,7 @@ double stdlib_base_hypot( const double x, const double y ) { return STDLIB_CONSTANT_FLOAT64_PINF; } if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } a = x; b = y; diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/README.md b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/README.md index 6c530e62732e..bda4fc8b66a3 100644 --- a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/README.md +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# Kernel Betainc +# kernelBetainc > [Incomplete beta function][incomplete-beta-function] and its first derivative. @@ -135,6 +135,111 @@ for ( i = 0; i < 100; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/math/base/special/kernel_betainc.h" +``` + +#### stdlib_base_kernel_betainc( x, a, b, regularized, upper, &out, &derivative ) + +Evaluates the incomplete beta function and its first derivative. + +```c +double out; +double derivative; + +stdlib_base_kernel_betainc( 0.2, 1.0, 2.0, true, false, &out, &derivative ); +``` + +The function accepts the following arguments: + +- **x**: `[in] double` function input. +- **a**: `[in] double` function parameter. +- **b**: `[in] double` function parameter. +- **regularized**: `[in] bool` indicating if the function should evaluate the regularized incomplete beta function. +- **upper**: `[in] bool` indicating if the function should return the upper tail of the incomplete beta function. +- **out**: `[out] double*` destination pointer to store the function value. +- **derivative**: `[out] double*` destination pointer to store the first derivative. + +```c +void stdlib_base_kernel_betainc( double x, double a, double b, const bool regularized, const bool upper, double *out, double *derivative ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/math/base/special/kernel_betainc.h" +#include "stdlib/random/base/randu.h" +#include +#include +#include + +int main( void ) { + struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 ); + double deriv; + double out; + int32_t i; + double x; + double a; + double b; + + for ( i = 0; i < 100; i++ ) { + x = stdlib_base_random_randu( obj ); + a = stdlib_base_random_randu( obj ) * 10.0; + b = stdlib_base_random_randu( obj ) * 10.0; + stdlib_base_kernel_betainc( x, a, b, true, false, &out, &deriv ); + printf( "x: %lf, a: %lf, b: %lf, f(x,a,b): %lf, f^1(x,a,b): %lf\n", x, a, b, out, deriv ); + } + + stdlib_base_random_randu_free( obj ); +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/benchmark.js index 435a5a2578ac..41ef370c711b 100644 --- a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/benchmark.js @@ -31,7 +31,7 @@ var kernelBetainc = require( './../lib' ); // MAIN // -bench( format( '%s::regularized,upper', pkg ), function benchmark( assert ) { +bench( format( '%s::regularized=true,upper=true', pkg ), function benchmark( assert ) { var out; var x; var a; @@ -58,7 +58,7 @@ bench( format( '%s::regularized,upper', pkg ), function benchmark( assert ) { assert.end(); }); -bench( format( '%s::unregularized,upper', pkg ), function benchmark( assert ) { +bench( format( '%s::regularized=false,upper=true', pkg ), function benchmark( assert ) { var out; var x; var a; @@ -85,7 +85,7 @@ bench( format( '%s::unregularized,upper', pkg ), function benchmark( assert ) { assert.end(); }); -bench( format( '%s::regularized,lower', pkg ), function benchmark( assert ) { +bench( format( '%s::regularized=true,upper=false', pkg ), function benchmark( assert ) { var out; var x; var a; @@ -112,7 +112,7 @@ bench( format( '%s::regularized,lower', pkg ), function benchmark( assert ) { assert.end(); }); -bench( format( '%s::unregularized,lower', pkg ), function benchmark( assert ) { +bench( format( '%s::regularized=false,upper=false', pkg ), function benchmark( assert ) { var out; var x; var a; diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/benchmark.native.js new file mode 100644 index 000000000000..37b1fb3e474a --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/benchmark.native.js @@ -0,0 +1,149 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var kernelBetainc = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kernelBetainc instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native:regularized=true,upper=true', pkg ), opts, function benchmark( assert ) { + var out; + var x; + var a; + var b; + var i; + + x = uniform( 100, 0.0, 1.0 ); + a = uniform( 100, EPS, 1000.0 ); + b = uniform( 100, EPS, 1000.0 ); + + out = [ 0.0, 0.0 ]; + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + out = kernelBetainc( x[ i%x.length ], a[ i%a.length ], b[ i%b.length ], true, true ); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); + +bench( format( '%s::native:regularized=false,upper=true', pkg ), opts, function benchmark( assert ) { + var out; + var x; + var a; + var b; + var i; + + x = uniform( 100, 0.0, 1.0 ); + a = uniform( 100, EPS, 1000.0 ); + b = uniform( 100, EPS, 1000.0 ); + + out = [ 0.0, 0.0 ]; + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + out = kernelBetainc( x[ i%x.length ], a[ i%a.length ], b[ i%b.length ], false, true ); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); + +bench( format( '%s::native:regularized=true,upper=false', pkg ), opts, function benchmark( assert ) { + var out; + var x; + var a; + var b; + var i; + + x = uniform( 100, 0.0, 1.0 ); + a = uniform( 100, EPS, 1000.0 ); + b = uniform( 100, EPS, 1000.0 ); + + out = [ 0.0, 0.0 ]; + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + out = kernelBetainc( x[ i%x.length ], a[ i%a.length ], b[ i%b.length ], true, false ); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); + +bench( format( '%s::native:regularized=false,upper=false', pkg ), opts, function benchmark( assert ) { + var out; + var x; + var a; + var b; + var i; + + x = uniform( 100, 0.0, 1.0 ); + a = uniform( 100, EPS, 1000.0 ); + b = uniform( 100, EPS, 1000.0 ); + + out = [ 0.0, 0.0 ]; + assert.tic(); + for ( i = 0; i < assert.iterations; i++ ) { + out = kernelBetainc( x[ i%x.length ], a[ i%a.length ], b[ i%b.length ], false, false ); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + } + assert.toc(); + if ( isnan( out[ 0 ] ) || isnan( out[ 1 ] ) ) { + assert.fail( 'should not return NaN' ); + } + assert.pass( 'benchmark finished' ); + assert.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/c/native/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..1c62a64fc720 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/benchmark/c/native/benchmark.c @@ -0,0 +1,146 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/kernel_betainc.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include +#include +#include + +#define NAME "kernel-betainc" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec / 1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double x[ 100 ]; + double a[ 100 ]; + double b[ 100 ]; + double elapsed; + double deriv; + double out; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0.0, 1.0 ); + a[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + b[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + stdlib_base_kernel_betainc( x[ i % 100 ], a[ i % 100 ], b[ i % 100 ], true, false, &out, &deriv ); + if ( out != out || deriv != deriv ) { + printf( "unexpected results\n" ); + break; + } + } + elapsed = tic() - t; + if ( out != out || deriv != deriv ) { + printf( "unexpected results\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/binding.gyp b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/index.d.ts b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/index.d.ts index a7f617ff9d6e..c8a7485611a9 100644 --- a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/index.d.ts @@ -20,10 +20,10 @@ /// -import { Collection } from '@stdlib/types/array'; +import { NumericArray } from '@stdlib/types/array'; /** -* Interface describing `kernalBetaInc`. +* Interface describing `kernelBetainc`. */ interface Routine { /** @@ -38,8 +38,8 @@ interface Routine { * @param x - function input * @param a - function parameter * @param b - function parameter - * @param invert - boolean indicating if the function should return the upper tail of the incomplete beta function instead - * @param normalized - boolean indicating if the function should evaluate the regularized boolean beta function + * @param regularized - boolean indicating if the function should evaluate the regularized incomplete beta function + * @param upper - boolean indicating if the function should return the upper tail of the incomplete beta function instead * @returns function value and first derivative * * @example @@ -50,7 +50,7 @@ interface Routine { * var out = kernelBetainc( 0.2, 1.0, 2.0, true, false ); * // returns [ 0.36, 1.6 ] */ - ( x: number, a: number, b: number, invert: boolean, normalized: boolean ): Array; + ( x: number, a: number, b: number, regularized: boolean, upper: boolean ): Array; /** * Evaluates the incomplete beta function and its first derivative and assigns results to a provided output array. @@ -64,8 +64,8 @@ interface Routine { * @param x - function input * @param a - function parameter * @param b - function parameter - * @param invert - boolean indicating if the function should return the upper tail of the incomplete beta function instead - * @param normalized - boolean indicating if the function should evaluate the regularized boolean beta function + * @param regularized - boolean indicating if the function should evaluate the regularized incomplete beta function + * @param upper - boolean indicating if the function should return the upper tail of the incomplete beta function instead * @param out - output array * @param stride - output array stride * @param offset - output array index offset @@ -79,7 +79,7 @@ interface Routine { * var bool = ( arr === out ); * // returns true */ - assign( x: number, a: number, b: number, invert: boolean, normalized: boolean, out: Collection, stride: number, offset: number ): Collection; + assign( x: number, a: number, b: number, regularized: boolean, upper: boolean, out: T, stride: number, offset: number ): T; } /** @@ -94,8 +94,8 @@ interface Routine { * @param x - function input * @param a - function parameter * @param b - function parameter -* @param invert - boolean indicating if the function should return the upper tail of the incomplete beta function instead -* @param normalized - boolean indicating if the function should evaluate the regularized boolean beta function +* @param regularized - boolean indicating if the function should evaluate the regularized incomplete beta function +* @param upper - boolean indicating if the function should return the upper tail of the incomplete beta function instead * @returns function value and first derivative * * @example diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/test.ts b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/test.ts index 7e9d70b8f777..818d9806b88a 100644 --- a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/test.ts +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/docs/types/test.ts @@ -78,7 +78,7 @@ import kernelBetainc = require( './index' ); // Attached to the main export is an `assign` method which returns a collection... { const out = [ 0.0, 0.0 ]; - kernelBetainc.assign( 0.5, 1.5, 1.5, true, false, out, 1, 0 ); // $ExpectType Collection + kernelBetainc.assign( 0.5, 1.5, 1.5, true, false, out, 1, 0 ); // $ExpectType number[] } // The compiler throws an error if the `assign` method is provided values other than three numbers for the first three parameters... diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/examples/c/Makefile b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/examples/c/example.c b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/examples/c/example.c new file mode 100644 index 000000000000..a9f046051a25 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/kernel_betainc.h" +#include "stdlib/random/base/randu.h" +#include +#include +#include + +int main( void ) { + struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 ); + double deriv; + double out; + int32_t i; + double x; + double a; + double b; + + for ( i = 0; i < 100; i++ ) { + x = stdlib_base_random_randu( obj ); + a = stdlib_base_random_randu( obj ) * 10.0; + b = stdlib_base_random_randu( obj ) * 10.0; + stdlib_base_kernel_betainc( x, a, b, true, false, &out, &deriv ); + printf( "x: %lf, a: %lf, b: %lf, f(x,a,b): %lf, f^1(x,a,b): %lf\n", x, a, b, out, deriv ); + } + + stdlib_base_random_randu_free( obj ); +} diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/include.gypi b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/* +* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler. +*/ +#ifdef __cplusplus +extern "C" { +#endif + +/** +* Evaluates the incomplete beta function and its first derivative. +*/ +void stdlib_base_kernel_betainc( double x, double a, double b, const bool regularized, const bool upper, double *out, double *derivative ); + +#ifdef __cplusplus +} +#endif + +#endif // !STDLIB_MATH_BASE_SPECIAL_KERNEL_BETAINC_H diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/lib/assign.js b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/lib/assign.js index 3868b6bd3f8c..f2b6d4b5f808 100644 --- a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/lib/assign.js +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/lib/assign.js @@ -45,6 +45,7 @@ var beta = require( '@stdlib/math/base/special/beta' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); var exp = require( '@stdlib/math/base/special/exp' ); var pow = require( '@stdlib/math/base/special/pow' ); +var powm1 = require( '@stdlib/math/base/special/powm1' ); var max = require( '@stdlib/math/base/special/max' ); var min = require( '@stdlib/math/base/special/min' ); var MAX_FLOAT64 = require( '@stdlib/constants/float64/max' ); @@ -210,7 +211,7 @@ function ibetaImp( x, a, b, regularized, upper, out, stride, offset ) { if ( y < 0.5 ) { p = ( upper ) ? -expm1( a * log1p(-y) ) : exp( a * log1p(-y) ); } else { - p = ( upper ) ? -( pow( x, a ) - 1.0 ) : pow( x, a ); + p = ( upper ) ? -powm1( x, a ) : pow( x, a ); } if ( !regularized ) { p /= a; diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/lib/native.js b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/lib/native.js new file mode 100644 index 000000000000..da35ee26a1bd --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/lib/native.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var Float64Array = require( '@stdlib/array/float64' ); +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Evaluates the incomplete beta function and its first derivative. +* +* @private +* @param {Probability} x - function input +* @param {NonNegativeNumber} a - function parameter +* @param {NonNegativeNumber} b - function parameter +* @param {boolean} regularized - boolean indicating if the function should evaluate the regularized incomplete beta function +* @param {boolean} upper - boolean indicating if the function should return the upper tail of the incomplete beta function instead +* @returns {Float64Array} function value and first derivative +* +* @example +* var out = kernelBetainc( 0.5, 2.0, 2.0, false, false ); +* // returns [ ~0.083, ~1.5 ] +* +* @example +* var out = kernelBetainc( 0.2, 1.0, 2.0, true, false ); +* // returns [ 0.36, 1.6 ] +*/ +function kernelBetainc( x, a, b, regularized, upper ) { + var out = new Float64Array( 2 ); + addon( x, a, b, regularized, upper, out ); + return out; +} + + +// EXPORTS // + +module.exports = kernelBetainc; diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/manifest.json b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/manifest.json new file mode 100644 index 000000000000..72aa52cd35ce --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/manifest.json @@ -0,0 +1,179 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/napi/export", + "@stdlib/napi/argv", + "@stdlib/napi/argv-double", + "@stdlib/napi/argv-bool", + "@stdlib/napi/argv-float64array", + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float32/smallest-normal", + "@stdlib/math/base/special/expm1", + "@stdlib/math/base/special/gammaln", + "@stdlib/math/base/special/gamma", + "@stdlib/math/base/special/binomcoef", + "@stdlib/math/base/special/floor", + "@stdlib/math/base/special/log1p", + "@stdlib/math/base/special/asin", + "@stdlib/math/base/special/gamma-delta-ratio", + "@stdlib/math/base/special/abs", + "@stdlib/math/base/special/ln", + "@stdlib/math/base/special/beta", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/powm1", + "@stdlib/math/base/special/max", + "@stdlib/math/base/special/min", + "@stdlib/math/base/special/factorial", + "@stdlib/math/base/special/minabs", + "@stdlib/math/base/special/maxabs", + "@stdlib/math/base/special/gammainc", + "@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled", + "@stdlib/constants/float64/max-ln", + "@stdlib/constants/float64/min-ln", + "@stdlib/constants/float64/max", + "@stdlib/constants/float64/smallest-normal", + "@stdlib/constants/float64/e", + "@stdlib/constants/float64/half-pi", + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/gamma-lanczos-g", + "@stdlib/constants/float64/eps", + "@stdlib/constants/int32/max", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/expm1", + "@stdlib/math/base/special/gammaln", + "@stdlib/math/base/special/gamma", + "@stdlib/constants/float32/smallest-normal", + "@stdlib/math/base/special/binomcoef", + "@stdlib/math/base/special/floor", + "@stdlib/math/base/special/log1p", + "@stdlib/math/base/special/asin", + "@stdlib/math/base/special/gamma-delta-ratio", + "@stdlib/math/base/special/abs", + "@stdlib/math/base/special/ln", + "@stdlib/math/base/special/beta", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/powm1", + "@stdlib/math/base/special/max", + "@stdlib/math/base/special/min", + "@stdlib/math/base/special/factorial", + "@stdlib/math/base/special/minabs", + "@stdlib/math/base/special/maxabs", + "@stdlib/math/base/special/gammainc", + "@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled", + "@stdlib/constants/float64/max-ln", + "@stdlib/constants/float64/min-ln", + "@stdlib/constants/float64/max", + "@stdlib/constants/float64/smallest-normal", + "@stdlib/constants/float64/e", + "@stdlib/constants/float64/half-pi", + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/gamma-lanczos-g", + "@stdlib/constants/float64/eps", + "@stdlib/constants/int32/max", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/expm1", + "@stdlib/random/base/randu", + "@stdlib/math/base/special/gammaln", + "@stdlib/constants/float32/smallest-normal", + "@stdlib/math/base/special/gamma", + "@stdlib/math/base/special/binomcoef", + "@stdlib/math/base/special/floor", + "@stdlib/math/base/special/log1p", + "@stdlib/math/base/special/asin", + "@stdlib/math/base/special/gamma-delta-ratio", + "@stdlib/math/base/special/abs", + "@stdlib/math/base/special/ln", + "@stdlib/math/base/special/beta", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/exp", + "@stdlib/math/base/special/pow", + "@stdlib/math/base/special/powm1", + "@stdlib/math/base/special/max", + "@stdlib/math/base/special/min", + "@stdlib/math/base/special/factorial", + "@stdlib/math/base/special/minabs", + "@stdlib/math/base/special/maxabs", + "@stdlib/math/base/special/gammainc", + "@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled", + "@stdlib/constants/float64/max-ln", + "@stdlib/constants/float64/min-ln", + "@stdlib/constants/float64/max", + "@stdlib/constants/float64/smallest-normal", + "@stdlib/constants/float64/e", + "@stdlib/constants/float64/half-pi", + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/gamma-lanczos-g", + "@stdlib/constants/float64/eps", + "@stdlib/constants/int32/max", + "@stdlib/constants/float64/nan" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/package.json b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/package.json index 75d6d4624166..4d2192a05e22 100644 --- a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/package.json +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/package.json @@ -14,11 +14,14 @@ } ], "main": "./lib", + "gypfile": true, "directories": { "benchmark": "./benchmark", "doc": "./docs", "example": "./examples", + "include": "./include", "lib": "./lib", + "src": "./src", "test": "./test" }, "types": "./docs/types", diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/Makefile b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/addon.c b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/addon.c new file mode 100644 index 000000000000..dccbfebc2954 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/addon.c @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/math/base/special/kernel_betainc.h" +#include "stdlib/napi/argv.h" +#include "stdlib/napi/argv_bool.h" +#include "stdlib/napi/argv_double.h" +#include "stdlib/napi/argv_float64array.h" +#include "stdlib/napi/export.h" +#include + +/** +* Receives JavaScript callback invocation data. +* +* @param env environment under which the function is invoked +* @param info callback data +* @return Node-API value +*/ +static napi_value addon( napi_env env, napi_callback_info info ) { + STDLIB_NAPI_ARGV( env, info, argv, argc, 6 ); + STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 ); + STDLIB_NAPI_ARGV_DOUBLE( env, a, argv, 1 ); + STDLIB_NAPI_ARGV_DOUBLE( env, b, argv, 2 ); + STDLIB_NAPI_ARGV_BOOL( env, regularized, argv, 3 ); + STDLIB_NAPI_ARGV_BOOL( env, upper, argv, 4 ); + STDLIB_NAPI_ARGV_FLOAT64ARRAY( env, y, ylen, argv, 5 ); + stdlib_base_kernel_betainc( x, a, b, regularized, upper, &y[ 0 ], &y[ 1 ] ); + return NULL; +} + +STDLIB_NAPI_MODULE_EXPORT_FCN( addon ) diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/main.c b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/main.c new file mode 100644 index 000000000000..9361c84f010c --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/src/main.c @@ -0,0 +1,1078 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +* +* +* ## Notice +* +* The original C++ code and copyright notice are from the [Boost library]{@link http://www.boost.org/doc/libs/1_61_0/boost/math/special_functions/beta.hpp}. The implementation has been modified according to stdlib conventions. +* +* ```text +* (C) Copyright John Maddock 2006. +* (C) Copyright Paul A. Bristow 2007. +* +* Use, modification and distribution are subject to the +* Boost Software License, Version 1.0. (See accompanying file +* LICENSE or copy at http://www.boost.org/LICENSE_1_0.txt) +* ``` +*/ + +#include "stdlib/math/base/special/kernel_betainc.h" +#include "stdlib/constants/float64/e.h" +#include "stdlib/constants/float64/eps.h" +#include "stdlib/constants/float64/gamma_lanczos_g.h" +#include "stdlib/constants/float64/half_pi.h" +#include "stdlib/constants/float64/max.h" +#include "stdlib/constants/float64/max_ln.h" +#include "stdlib/constants/float64/min_ln.h" +#include "stdlib/constants/float64/pi.h" +#include "stdlib/constants/float32/smallest_normal.h" +#include "stdlib/constants/float64/smallest_normal.h" +#include "stdlib/constants/int32/max.h" +#include "stdlib/constants/float64/nan.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/abs.h" +#include "stdlib/math/base/special/asin.h" +#include "stdlib/math/base/special/beta.h" +#include "stdlib/math/base/special/binomcoef.h" +#include "stdlib/math/base/special/exp.h" +#include "stdlib/math/base/special/expm1.h" +#include "stdlib/math/base/special/factorial.h" +#include "stdlib/math/base/special/floor.h" +#include "stdlib/math/base/special/gamma.h" +#include "stdlib/math/base/special/gamma_delta_ratio.h" +#include "stdlib/math/base/special/gamma_lanczos_sum_expg_scaled.h" +#include "stdlib/math/base/special/gammainc.h" +#include "stdlib/math/base/special/gammaln.h" +#include "stdlib/math/base/special/ln.h" +#include "stdlib/math/base/special/log1p.h" +#include "stdlib/math/base/special/max.h" +#include "stdlib/math/base/special/maxabs.h" +#include "stdlib/math/base/special/min.h" +#include "stdlib/math/base/special/minabs.h" +#include "stdlib/math/base/special/pow.h" +#include "stdlib/math/base/special/powm1.h" +#include "stdlib/math/base/special/sqrt.h" +#include +#include +#include + +static const double ONE_OVER_PI = 1.0 / STDLIB_CONSTANT_FLOAT64_PI; + +/** +* Calculates the power term prefix `(z^a)(e^-z)` used in the non-normalized incomplete gammas. +* +* @param a function parameter +* @param z function parameter +* @return power term prefix +*/ +static double fullIGammaPrefix( const double a, const double z ) { + double prefix; + double alz; + + alz = a * stdlib_base_ln( z ); + if ( z >= 1.0 ) { + if ( ( alz < STDLIB_CONSTANT_FLOAT64_MAX_LN ) && ( -z > STDLIB_CONSTANT_FLOAT64_MIN_LN ) ) { + prefix = stdlib_base_pow( z, a ) * stdlib_base_exp( -z ); + } else if ( a >= 1.0 ) { + prefix = stdlib_base_pow( z / stdlib_base_exp( z / a ), a ); + } else { + prefix = stdlib_base_exp( alz - z ); + } + } else if ( alz > STDLIB_CONSTANT_FLOAT64_MIN_LN ) { + prefix = stdlib_base_pow( z, a ) * stdlib_base_exp( -z ); + } else if ( z / a < STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + prefix = stdlib_base_pow( z / stdlib_base_exp( z / a ), a ); + } else { + prefix = stdlib_base_exp( alz - z ); + } + return prefix; +} + +/** +* Computes `(z^a)*(e^-z) / gamma(a)`. +* +* @param a input value +* @param z input value +* @return function value +*/ +static double regularizedGammaPrefix( const double a, const double z ) { + double prefix; + double amza; + double agh; + double alz; + double amz; + double sq; + double d; + + agh = a + STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G - 0.5; + d = ( ( z - a ) - STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G + 0.5 ) / agh; + if ( a < 1.0 ) { + // Treat a < 1 as a special case because our Lanczos approximations are optimized against the factorials with a > 1, and for high precision types very small values of `a` can give rather erroneous results for gamma: + if ( z <= STDLIB_CONSTANT_FLOAT64_MIN_LN ) { + // Use logs, so should be free of cancellation errors: + return stdlib_base_exp( ( a * stdlib_base_ln( z ) ) - z - stdlib_base_gammaln( a ) ); + } + // No danger of overflow as gamma(a) < 1/a for small a, so direct calculation: + return stdlib_base_pow( z, a ) * stdlib_base_exp( -z ) / stdlib_base_gamma( a ); + } + if ( stdlib_base_abs( d * d * a ) <= 100.0 && a > 150.0 ) { + // Special case for large a and a ~ z: + prefix = ( a * ( stdlib_base_log1p( d ) - d ) ) + ( z * ( 0.5 - STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G ) / agh ); + prefix = stdlib_base_exp( prefix ); + } else { + // General case. Direct computation is most accurate, but use various fallbacks for different parts of the problem domain: + alz = a * stdlib_base_ln( z / agh ); + amz = a - z; + if ( stdlib_base_min( alz, amz ) <= STDLIB_CONSTANT_FLOAT64_MIN_LN || stdlib_base_max( alz, amz ) >= STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + amza = amz / a; + if ( stdlib_base_min( alz, amz ) / 2.0 > STDLIB_CONSTANT_FLOAT64_MIN_LN && stdlib_base_max( alz, amz ) / 2.0 < STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + // Compute square root of the result and then square it: + sq = stdlib_base_pow( z / agh, a / 2.0 ) * stdlib_base_exp( amz / 2.0 ); + prefix = sq * sq; + } else if ( stdlib_base_min( alz, amz ) / 4.0 > STDLIB_CONSTANT_FLOAT64_MIN_LN && stdlib_base_max( alz, amz ) / 4.0 < STDLIB_CONSTANT_FLOAT64_MAX_LN && z > a ) { + // Compute the 4th root of the result then square it twice: + sq = stdlib_base_pow( z / agh, a / 4.0 ) * stdlib_base_exp( amz / 4.0 ); + prefix = sq * sq; + prefix *= prefix; + } else if ( amza > STDLIB_CONSTANT_FLOAT64_MIN_LN && amza < STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + prefix = stdlib_base_pow( ( z * stdlib_base_exp( amza ) ) / agh, a ); + } else { + prefix = stdlib_base_exp( alz + amz ); + } + } else { + prefix = stdlib_base_pow( z / agh, a ) * stdlib_base_exp( amz ); + } + } + prefix *= stdlib_base_sqrt( agh / STDLIB_CONSTANT_FLOAT64_E ) / stdlib_base_gamma_lanczos_sum_expg_scaled( a ); + return prefix; +} + +/** +* Continued fraction term generator for the incomplete beta. +* +* @param a function parameter +* @param b function parameter +* @param x function parameter +* @param m pointer to iteration counter (mutated) +* @param y probability equal to `1-x` +* @param out destination pointer for storing the numerator and denominator +*/ +static void ibetaFraction2t( const double a, const double b, const double x, double *m, const double y, double *out ) { + double denom; + double aN; + double bN; + + aN = ( a + ( *m ) - 1 ) * ( a + b + ( *m ) - 1 ) * ( *m ) * ( b - ( *m ) ) * x * x; + denom = a + ( 2.0 * ( *m ) ) - 1.0; + aN /= denom * denom; + bN = ( *m ); + bN += ( ( *m ) * ( b - ( *m ) ) * x ) / ( a + ( 2.0 * ( *m ) ) - 1.0 ); + bN += ( ( a + ( *m ) ) * ( ( a * y ) - ( b * x ) + 1.0 + ( ( *m ) * ( 2.0 - x ) ) ) ) / ( a + ( 2.0 * ( *m ) ) + 1.0 ); + ( *m ) += 1; + out[ 0 ] = aN; + out[ 1 ] = bN; + return; +} + +/** +* Evaluates the incomplete beta function via the continued fraction representation using the modified Lentz algorithm. +* +* ```text +* b0 + a1 +* --------------- +* b1 + a2 +* ---------- +* b2 + a3 +* ----- +* b3 + ... +* ``` +* @param a function parameter +* @param b function parameter +* @param x function parameter +* @param y probability equal to `1-x` +* @param tol tolerance for convergence +* @param maxIter maximum number of iterations +* @return continued fraction value +*/ +static double ibetaFraction2CF( const double a, const double b, const double x, const double y, const double tol, int32_t maxIter ) { + double outTerms[ 2 ]; + double delta; + double C; + double D; + double f; + double m; + + m = 0.0; + ibetaFraction2t( a, b, x, &m, y, outTerms ); + f = outTerms[ 1 ]; + if ( f == 0.0 ) { + f = STDLIB_CONSTANT_FLOAT32_SMALLEST_NORMAL; + } + C = f; + D = 0.0; + do { + ibetaFraction2t( a, b, x, &m, y, outTerms ); + D = outTerms[ 1 ] + ( outTerms[ 0 ] * D ); + if ( D == 0.0 ) { + D = STDLIB_CONSTANT_FLOAT32_SMALLEST_NORMAL; + } + C = outTerms[ 1 ] + ( outTerms[ 0 ] / C ); + if ( C == 0.0 ) { + C = STDLIB_CONSTANT_FLOAT32_SMALLEST_NORMAL; + } + D = 1.0 / D; + delta = C * D; + f *= delta; + } while ( ( stdlib_base_abs( delta - 1.0 ) > tol ) && --maxIter ); + return f; +} + +/** +* Computes the leading power terms in the incomplete beta function. +* +* When normalized, +* +* ```tex +* \frac{ x^a y^b }{ \operatorname{Beta}(a,b) } +* ``` +* +* and otherwise +* +* ```tex +* x^a y^b +* ``` +* +* ## Notes +* +* - Almost all of the error in the incomplete beta comes from this function, particularly when \\( a \\) and \\( b \\) are large. Computing large powers are _hard_ though, and using logarithms just leads to horrendous cancellation errors. +* +* - For \\( l1 * l2 > 0 \\) or \\( \operatorname{min}( a, b ) < 1 \\), the two power terms both go in the same direction (toward zero or toward infinity). In this case if either term overflows or underflows, then the product of the two must do so also. Alternatively, if one exponent is less than one, then we can't productively use it to eliminate overflow or underflow from the other term. Problems with spurious overflow/underflow can't be ruled out. In this case, but it is _very_ unlikely since one of the power terms will evaluate to a number close to 1. +* +* - If \\( \max( \abs(l1), \abs(l2) ) < 0.5 \\), both exponents are near one and both the exponents are greater than one, and, further, these two power terms tend in opposite directions (one toward zero, the other toward infinity), so we have to combine the terms to avoid any risk of overflow or underflow. We do this by moving one power term inside the other, we have: +* +* ```tex +* (1 + l_1)^a \cdot (1 + l_2)^b \\ +* = ((1 + l_1) \cdot (1 + l_2)^(b/a))^a \\ +* = (1 + l_1 + l_3 + l_1*l_3)^a +* ``` +* +* and +* +* ```tex +* l_3 = (1 + l_2)^(b/a) - 1 \\ +* = \exp((b/a) * \ln(1 + l_2)) - 1 +* ``` +* +* The tricky bit is deciding which term to move inside. By preference, we move the larger term inside, so that the size of the largest exponent is reduced. However, that can only be done as long as l3 (see above) is also small. +* +* @param a function parameter +* @param b function parameter +* @param x function parameter +* @param y probability equal to `1-x` +* @param normalized boolean indicating whether to evaluate the power terms of the regularized or non-regularized incomplete beta function +* @return power terms +*/ +static double ibetaPowerTerms( const double a, const double b, const double x, const double y, const bool normalized ) { + double result; + double smallA; + double ratio; + double agh; + double bgh; + double cgh; + double l1; + double l2; + double l3; + double p1; + double b1; + double b2; + double c; + double l; + + if ( !normalized ) { + // Can we do better here? + return stdlib_base_pow( x, a ) * stdlib_base_pow( y, b ); + } + c = a + b; + // Combine power terms with Lanczos approximation: + agh = a + STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G - 0.5; + bgh = b + STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G - 0.5; + cgh = c + STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G - 0.5; + result = stdlib_base_gamma_lanczos_sum_expg_scaled( c ); + result /= stdlib_base_gamma_lanczos_sum_expg_scaled( a ) * stdlib_base_gamma_lanczos_sum_expg_scaled( b ); + // Combine with the leftover terms from the Lanczos approximation: + result *= stdlib_base_sqrt( bgh / STDLIB_CONSTANT_FLOAT64_E ); + result *= stdlib_base_sqrt( agh / cgh ); + // `l1` and `l2` are the base of the exponents minus one: + l1 = ( ( x * b ) - ( y * agh ) ) / agh; + l2 = ( ( y * a ) - ( x * bgh ) ) / bgh; + if ( stdlib_base_minabs( l1, l2 ) < 0.2 ) { + // When the base of the exponent is very near 1 we get really gross errors unless extra care is taken: + if ( l1 * l2 > 0 || stdlib_base_min( a, b ) < 1 ) { + if ( stdlib_base_abs( l1 ) < 0.1 ) { + result *= stdlib_base_exp( a * stdlib_base_log1p( l1 ) ); + } else { + result *= stdlib_base_pow( ( x * cgh ) / agh, a ); + } + if ( stdlib_base_abs( l2 ) < 0.1 ) { + result *= stdlib_base_exp( b * stdlib_base_log1p( l2 ) ); + } else { + result *= stdlib_base_pow( ( y * cgh ) / bgh, b ); + } + } else if ( stdlib_base_maxabs( l1, l2 ) < 0.5 ) { + smallA = a < b; + ratio = b / a; + if ( ( smallA && ( ratio * l2 < 0.1 ) ) || ( !smallA && ( l1 / ratio > 0.1 ) ) ) { + l3 = stdlib_base_expm1( ratio * stdlib_base_log1p( l2 ) ); + l3 = l1 + l3 + ( l3 * l1 ); + l3 = a * stdlib_base_log1p( l3 ); + result *= stdlib_base_exp( l3 ); + } else { + l3 = stdlib_base_expm1( stdlib_base_log1p( l1 ) / ratio ); + l3 = l2 + l3 + ( l3 * l2 ); + l3 = b * stdlib_base_log1p( l3 ); + result *= stdlib_base_exp( l3 ); + } + } else if ( stdlib_base_abs( l1 ) < stdlib_base_abs( l2 ) ) { + // First base near 1 only: + l = ( a * stdlib_base_log1p( l1 ) ) + ( b * stdlib_base_ln( ( y * cgh ) / bgh ) ); + if ( l <= STDLIB_CONSTANT_FLOAT64_MIN_LN || l >= STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + l += stdlib_base_ln( result ); + if ( l >= STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + result = stdlib_base_exp( l ); + } else { + result *= stdlib_base_exp( l ); + } + } else { + // Second base near 1 only: + l = ( b * stdlib_base_log1p( l2 ) ) + ( a * stdlib_base_ln( ( x * cgh ) / agh ) ); + if ( l <= STDLIB_CONSTANT_FLOAT64_MIN_LN || l >= STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + l += stdlib_base_ln( result ); + if ( l >= STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + result = stdlib_base_exp( l ); + } else { + result *= stdlib_base_exp( l ); + } + } + } else { + // General case: + b1 = ( x * cgh ) / agh; + b2 = ( y * cgh ) / bgh; + l1 = a * stdlib_base_ln( b1 ); + l2 = b * stdlib_base_ln( b2 ); + if ( l1 >= STDLIB_CONSTANT_FLOAT64_MAX_LN || l1 <= STDLIB_CONSTANT_FLOAT64_MIN_LN || l2 >= STDLIB_CONSTANT_FLOAT64_MAX_LN || l2 <= STDLIB_CONSTANT_FLOAT64_MIN_LN ) { + // Oops, under/overflow, sidestep if we can: + if ( a < b ) { + p1 = stdlib_base_pow( b2, b / a ); + l3 = a * ( stdlib_base_ln( b1 ) + stdlib_base_ln( p1 ) ); + if ( l3 < STDLIB_CONSTANT_FLOAT64_MAX_LN && l3 > STDLIB_CONSTANT_FLOAT64_MIN_LN ) { + result *= stdlib_base_pow( p1 * b1, a ); + } else { + l2 += l1 + stdlib_base_ln( result ); + if ( l2 >= STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + result = stdlib_base_exp( l2 ); + } + } else { + p1 = stdlib_base_pow( b1, a / b ); + l3 = ( stdlib_base_ln( p1 ) + stdlib_base_ln( b2 ) ) * b; + if ( l3 < STDLIB_CONSTANT_FLOAT64_MAX_LN && l3 > STDLIB_CONSTANT_FLOAT64_MIN_LN ) { + result *= stdlib_base_pow( p1 * b2, b ); + } else { + l2 += l1 + stdlib_base_ln( result ); + if ( l2 >= STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + result = stdlib_base_exp( l2 ); + } + } + } else { + // Finally the normal case: + result *= stdlib_base_pow( b1, a ) * stdlib_base_pow( b2, b ); + } + } + return result; +} + +/** +* Evaluates the incomplete beta via the continued fraction representation. +* +* @param a function parameter +* @param b function parameter +* @param x function parameter +* @param y probability equal to `1-x` +* @param normalized boolean indicating whether to evaluate the power terms of the regularized or non-regularized incomplete beta function +* @param out destination pointer for storing the derivative term +* @return incomplete beta value +*/ +static double ibetaFraction2( const double a, const double b, const double x, const double y, const bool normalized, double *out ) { + double result; + double fract; + + result = ibetaPowerTerms( a, b, x, y, normalized ); + if ( out ) { + *out = result; + } + if ( result == 0.0 ) { + return result; + } + fract = ibetaFraction2CF( a, b, x, y, STDLIB_CONSTANT_FLOAT64_EPS, 1000 ); + return result / fract; +} + +/** +* This is DiDonato and Morris's BGRAT routine, see Eq's 9 through 9.6. +* +* @param a function parameter +* @param b function parameter +* @param x function parameter +* @param y probability equal to `1-x` +* @param s0 initial value +* @param mult initial value +* @param normalized boolean indicating whether to evaluate the regularized or non-regularized incomplete beta function +* @return function value +*/ +static double betaSmallBLargeASeries( const double a, const double b, const double x, const double y, const double s0, const double mult, const bool normalized ) { + double p[ 30 ]; + double prefix; + double tmp1; + double tnp1; + double sum; + double b2n; + double bm1; + double lx2; + double lxp; + double mbn; + double lx; + double t4; + int32_t m; + int32_t n; + double h; + double j; + double r; + double t; + double u; + + // Some values we'll need later, these are Eq 9.1: + bm1 = b - 1.0; + t = a + ( bm1 / 2.0 ); + if ( y < 0.35 ) { + lx = stdlib_base_log1p( -y ); + } else { + lx = stdlib_base_ln( x ); + } + u = -t * lx; + // And from 9.2: + h = regularizedGammaPrefix( b, u ); + if ( h <= STDLIB_CONSTANT_FLOAT64_SMALLEST_NORMAL ) { + return s0; + } + if ( normalized ) { + prefix = h / stdlib_base_gamma_delta_ratio( a, b ); + prefix /= stdlib_base_pow( t, b ); + } else { + prefix = fullIGammaPrefix( b, u ) / stdlib_base_pow( t, b ); + } + prefix *= mult; + // We need the quantity Pn. Unfortunately, this is computed recursively and requires a full history of all the previous values. No choice but to declare a big table and hope it's big enough... + p[ 0 ] = 1; // see 9.3. + // Now an initial value for J, see 9.6: gammainc( u, b, regularized, upper ) + j = stdlib_base_gammainc( u, b, true, true ); + j /= h; + // Now we can start to pull things together and evaluate the sum in Eq 9: + sum = s0 + ( prefix * j ); // Value at N = 0 + // Some variables we'll need... + tnp1 = 1.0; // 2*N+1 + lx2 = lx / 2.0; + lx2 *= lx2; + lxp = 1.0; + t4 = 4.0 * t * t; + b2n = b; + for ( n = 1; n < 30; ++n ) { + // Begin by evaluating the next Pn from Eq 9.4: + tnp1 += 2.0; + p[ n ] = 0.0; + tmp1 = 3; + for ( m = 1; m < n; ++m ) { + mbn = ( m * b ) - n; + p[ n ] += mbn * p[ n - m ] / stdlib_base_factorial( tmp1 ); + tmp1 += 2; + } + p[ n ] /= n; + p[ n ] += bm1 / stdlib_base_factorial( tnp1 ); + // Now we want Jn from Jn-1 using Eq 9.6: + j = ( ( b2n * ( b2n + 1.0 ) * j ) + ( ( u + b2n + 1.0 ) * lxp ) ) / t4; + lxp *= lx2; + b2n += 2.0; + // Pull it together with Eq 9: + r = prefix * p[ n ] * j; + sum += r; + if ( r > 1.0 ) { + if ( stdlib_base_abs( r ) < stdlib_base_abs( STDLIB_CONSTANT_FLOAT64_EPS * sum ) ) { + break; + } + } else if ( stdlib_base_abs( r / STDLIB_CONSTANT_FLOAT64_EPS ) < stdlib_base_abs( sum ) ) { + break; + } + } + return sum; +} + +/** +* Computes the difference between `ibeta(a,b,x)` and `ibeta(a+k,b,x)`. +* +* @param a function parameter +* @param b function parameter +* @param x function parameter +* @param y probability equal to `1-x` +* @param k function input +* @param normalized boolean indicating whether to evaluate the power terms of the regularized or non-regularized incomplete beta function +* @param out destination pointer for storing the derivative term +* @return difference between ibeta(a,b,x) and ibeta(a+k,b,x) +*/ +static double ibetaAStep( const double a, const double b, const double x, const double y, const double k, const bool normalized, double *out ) { + double prefix; + double term; + double sum; + double i; + + prefix = ibetaPowerTerms( a, b, x, y, normalized ); + if ( out ) { + *out = prefix; + } + prefix /= a; + if ( prefix == 0.0 ) { + return prefix; + } + sum = 1.0; + term = 1.0; + // Series summation from 0 to k-1: + for ( i = 0; i < k - 1; ++i ) { + term *= ( a + b + i ) * x / ( a + i + 1.0 ); + sum += term; + } + prefix *= sum; + return prefix; +} + +/** +* Computes the delta in `beta(a,b,x) = prefix + delta * beta(a+k,b,x)`. +* +* ## Notes +* +* Specifically, the function calculates +* +* ```tex +* \frac{ (a)(a+1)(a+2)...(a+k-1) }{ (b)(b+1)(b+2)...(b+k-1) } +* ``` +* +* The function should only called with small `k`; for large `k`, it is grossly inefficient. +* +* @param a input value +* @param b input value +* @param k input value +* @return ratio value +*/ +static double risingFactorialRatio( const double a, const double b, const double k ) { + double result; + double i; + + if ( k == 0 ) { + return 1.0; + } + result = 1.0; + for ( i = 0; i < k; i++ ) { + result *= ( a + i ) / ( b + i ); + } + return result; +} + +/** +* Calculates the next term of the incomplete beta series. +* +* @param a pointer to function parameter +* @param x function parameter +* @param poch pointer to Pochhammer term +* @param n pointer to term counter +* @param result pointer to current result value +* @return series expansion term +*/ +static double ibetaSeriesT( double *a, const double x, double *poch, int32_t *n, double *result ) { + double r; + + r = ( *result ) / ( *a ); + *a += 1.0; + *result *= ( *poch ) * x / (double)( *n ); + *n += 1; + *poch += 1.0; + return r; +} + +/** +* For integer arguments we can relate the incomplete beta to the complement of the binomial distribution cdf and use this finite sum. +* +* @param n number of trials +* @param k function input +* @param x function input +* @param y probability equal to `1-x` +* @return sum +*/ +static double binomialCCDF( const double n, const double k, const double x, const double y ) { + double startTerm; + double result; + double start; + double term; + double i; + + result = stdlib_base_pow( x, n ); + if ( result > STDLIB_CONSTANT_FLOAT64_SMALLEST_NORMAL ) { + term = result; + for ( i = stdlib_base_floor( n - 1 ); i > k; i-- ) { + term *= ( ( i + 1 ) * y ) / ( ( n - i ) * x ); + result += term; + } + } else { + // First term underflows so we need to start at the mode of the distribution and work outwards: + start = stdlib_base_floor( n * x ); + if ( start <= k + 1 ) { + start = stdlib_base_floor( k + 2 ); + } + result = stdlib_base_pow( x, start ) * stdlib_base_pow( y, n - start ); + result *= stdlib_base_binomcoef( stdlib_base_floor( n ), stdlib_base_floor( start ) ); + if ( result == 0.0 ) { + // OK, starting slightly above the mode didn't work, we'll have to sum the terms the old fashioned way: + for ( i = start - 1; i > k; i-- ) { + result += stdlib_base_pow( x, i ) * stdlib_base_pow( y, n - i ); + result *= stdlib_base_binomcoef( stdlib_base_floor( n ), stdlib_base_floor( i ) ); + } + } else { + term = result; + startTerm = result; + for ( i = start - 1; i > k; i-- ) { + term *= ( ( i + 1 ) * y ) / ( ( n - i ) * x ); + result += term; + } + term = startTerm; + for ( i = start + 1; i <= n; i++ ) { + term *= ( n - i + 1 ) * x / ( i * y ); + result += term; + } + } + } + return result; +} + +/** +* Incomplete beta series. +* +* @param a function parameter +* @param b function parameter +* @param x function parameter +* @param s0 initial value +* @param normalized boolean indicating whether to evaluate the power terms of the regularized or non-regularized incomplete beta function +* @param out destination for storing the derivative term +* @param y probability equal to `1-x` +* @return function value +*/ +static double ibetaSeries( const double a, const double b, const double x, const double s0, const bool normalized, double *out, const double y ) { + int32_t counter; + double result; + double poch; + double agh; + double bgh; + double cgh; + double sum; + double ac; + int32_t n; + double l1; + double l2; + double c; + double r; + + if ( normalized ) { + c = a + b; + // Incomplete beta power term, combined with the Lanczos approximation: + agh = a + STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G - 0.5; + bgh = b + STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G - 0.5; + cgh = c + STDLIB_CONSTANT_FLOAT64_GAMMA_LANCZOS_G - 0.5; + result = stdlib_base_gamma_lanczos_sum_expg_scaled( c ) / ( stdlib_base_gamma_lanczos_sum_expg_scaled( a ) * stdlib_base_gamma_lanczos_sum_expg_scaled( b ) ); + l1 = stdlib_base_ln( cgh / bgh ) * ( b - 0.5 ); + l2 = stdlib_base_ln( x * cgh / agh ) * a; + // Check for over/underflow in the power terms: + if ( l1 > STDLIB_CONSTANT_FLOAT64_MIN_LN && l1 < STDLIB_CONSTANT_FLOAT64_MAX_LN && l2 > STDLIB_CONSTANT_FLOAT64_MIN_LN && l2 < STDLIB_CONSTANT_FLOAT64_MAX_LN ) { + if ( a * b < bgh * 10.0 ) { + result *= stdlib_base_exp( ( b - 0.5 ) * stdlib_base_log1p( a / bgh ) ); + } else { + result *= stdlib_base_pow( cgh / bgh, b - 0.5 ); + } + result *= stdlib_base_pow( x * cgh / agh, a ); + result *= stdlib_base_sqrt( agh / STDLIB_CONSTANT_FLOAT64_E ); + if ( out ) { + *out = result * stdlib_base_pow( y, b ); + } + } else { + // We need logs, and this *will* cancel: + result = stdlib_base_ln( result ) + l1 + l2 + ( ( stdlib_base_ln( agh ) - 1.0 ) / 2.0 ); + if ( out ) { + *out = stdlib_base_exp( result + ( b * stdlib_base_ln( y ) ) ); + } + result = stdlib_base_exp( result ); + } + } else { + // Non-normalized, just compute the power: + result = stdlib_base_pow( x, a ); + } + if ( result < STDLIB_CONSTANT_FLOAT64_SMALLEST_NORMAL ) { + return s0; // Safeguard: series can't cope with denorms. + } + poch = 1.0 - b; + ac = a; + n = 1; + counter = 100; + sum = s0; + do { + r = ibetaSeriesT( &ac, x, &poch, &n, &result ); + sum += r; + } while ( ( stdlib_base_abs( STDLIB_CONSTANT_FLOAT64_EPS * sum ) < stdlib_base_abs( r ) ) && --counter ); + return sum; +} + +/** +* Evaluates the incomplete beta function and its first derivative. +* +* @param x function input +* @param a function parameter +* @param b function parameter +* @param regularized boolean indicating if the function should evaluate the regularized incomplete beta function +* @param upper boolean indicating if the function should return the upper tail of the incomplete beta function +* @param out destination pointer to store the function value +* @param derivative destination pointer to store the first derivative +* +* @example +* double out; +* double derivative; +* +* stdlib_base_kernel_betainc( 0.2, 1.0, 2.0, true, false, &out, &derivative ); +*/ +void stdlib_base_kernel_betainc( double x, double a, double b, const bool regularized, const bool upper, double *out, double *derivative ) { + double lambda; + double prefix; + double fract; + bool invert; + double bbar; + double div; + double tmp; + double k; + double n; + double p; + double y; + + invert = upper; + y = 1.0 - x; + // Derivative not set... + *derivative = -1; + if ( stdlib_base_is_nan( x ) || x < 0.0 || x > 1.0 ) { + *out = STDLIB_CONSTANT_FLOAT64_NAN; + *derivative = STDLIB_CONSTANT_FLOAT64_NAN; + return; + } + if ( regularized ) { + if ( a < 0.0 || b < 0.0 ) { + *out = STDLIB_CONSTANT_FLOAT64_NAN; + *derivative = STDLIB_CONSTANT_FLOAT64_NAN; + return; + } + // Extend to a few very special cases... + if ( a == 0.0 ) { + if ( b == 0.0 ) { + *out = STDLIB_CONSTANT_FLOAT64_NAN; + *derivative = STDLIB_CONSTANT_FLOAT64_NAN; + return; + } + if ( b > 0.0 ) { + *out = ( invert ) ? 0.0 : 1.0; + return; + } + } else if ( b == 0.0 ) { + if ( a > 0.0 ) { + *out = ( invert ) ? 1.0 : 0.0; + return; + } + } + } else if ( a <= 0.0 || b <= 0.0 ) { + *out = STDLIB_CONSTANT_FLOAT64_NAN; + *derivative = STDLIB_CONSTANT_FLOAT64_NAN; + return; + } + if ( x == 0.0 ) { + if ( a == 1.0 ) { + *derivative = 1.0; + } else { + *derivative = ( a < 1.0 ) ? STDLIB_CONSTANT_FLOAT64_MAX / 2.0 : STDLIB_CONSTANT_FLOAT64_SMALLEST_NORMAL * 2.0; + } + if ( invert ) { + *out = ( regularized ) ? 1.0 : stdlib_base_beta( a, b ); + return; + } + *out = 0.0; + return; + } + if ( x == 1.0 ) { + if ( b == 1.0 ) { + *derivative = 1.0; + } else { + *derivative = ( b < 1.0 ) ? STDLIB_CONSTANT_FLOAT64_MAX / 2.0 : STDLIB_CONSTANT_FLOAT64_SMALLEST_NORMAL * 2.0; + } + if ( invert ) { + *out = 0.0; + } else { + *out = ( regularized ) ? 1.0 : stdlib_base_beta( a, b ); + } + return; + } + if ( a == 0.5 && b == 0.5 ) { + *derivative = ONE_OVER_PI * stdlib_base_sqrt( y * x ); + // We have an arcsine distribution: + p = ( invert ) ? stdlib_base_asin( stdlib_base_sqrt( y ) ) : stdlib_base_asin( stdlib_base_sqrt( x ) ); + p /= STDLIB_CONSTANT_FLOAT64_HALF_PI; + if ( !regularized ) { + p *= STDLIB_CONSTANT_FLOAT64_PI; + } + *out = p; + return; + } + if ( a == 1.0 ) { + tmp = b; + b = a; + a = tmp; + tmp = y; + y = x; + x = tmp; + invert = !invert; + } + if ( b == 1.0 ) { + // Special case see: http://functions.wolfram.com/GammaBetaErf/BetaRegularized/03/01/01/ + if ( a == 1.0 ) { + *out = ( invert ) ? y : x; + *derivative = 1.0; + return; + } + *derivative = a * stdlib_base_pow( x, a - 1.0 ); + if ( y < 0.5 ) { + p = ( invert ) ? -stdlib_base_expm1( a * stdlib_base_log1p( -y ) ) : stdlib_base_exp( a * stdlib_base_log1p( -y ) ); + } else { + p = ( invert ) ? -stdlib_base_powm1( x, a ) : stdlib_base_pow( x, a ); + } + if ( !regularized ) { + p /= a; + } + *out = p; + return; + } + if ( stdlib_base_min( a, b ) <= 1.0 ) { + if ( x > 0.5 ) { + tmp = b; + b = a; + a = tmp; + tmp = y; + y = x; + x = tmp; + invert = !invert; + } + if ( stdlib_base_max( a, b ) <= 1.0 ) { + // Both a,b < 1: + if ( ( a >= stdlib_base_min( 0.2, b ) ) || ( stdlib_base_pow( x, a ) <= 0.9 ) ) { + if ( invert ) { + fract = -( ( regularized ) ? 1.0 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -ibetaSeries( a, b, x, fract, regularized, derivative, y ); + } else { + fract = ibetaSeries( a, b, x, 0, regularized, derivative, y ); + } + } else { + tmp = b; + b = a; + a = tmp; + tmp = y; + y = x; + x = tmp; + invert = !invert; + if ( y >= 0.3 ) { + if ( invert ) { + fract = -( ( regularized ) ? 1.0 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -ibetaSeries( a, b, x, fract, regularized, derivative, y ); + } else { + fract = ibetaSeries( a, b, x, 0, regularized, derivative, y ); + } + } else { + // Sidestep on a, and then use the series representation: + if ( regularized ) { + prefix = 1; + } else { + prefix = risingFactorialRatio( a + b, a, 20 ); + } + fract = ibetaAStep( a, b, x, y, 20, regularized, derivative ); + if ( invert ) { + fract -= ( ( regularized ) ? 1 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -betaSmallBLargeASeries( a + 20.0, b, x, y, fract, prefix, regularized ); + } else { + fract = betaSmallBLargeASeries( a + 20.0, b, x, y, fract, prefix, regularized ); + } + } + } + } else if ( b <= 1.0 || ( x < 0.1 && ( stdlib_base_pow( b * x, a ) <= 0.7 ) ) ) { + if ( invert ) { + fract = -( ( regularized ) ? 1 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -ibetaSeries( a, b, x, fract, regularized, derivative, y ); + } else { + fract = ibetaSeries( a, b, x, 0.0, regularized, derivative, y ); + } + } else { + tmp = b; + b = a; + a = tmp; + tmp = y; + y = x; + x = tmp; + invert = !invert; + if ( y >= 0.3 ) { + if ( invert ) { + fract = -( ( regularized ) ? 1.0 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -ibetaSeries( a, b, x, fract, regularized, derivative, y ); + } else { + fract = ibetaSeries( a, b, x, 0.0, regularized, derivative, y ); + } + } else if ( a >= 15.0 ) { + if ( invert ) { + fract = -( ( regularized ) ? 1.0 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -betaSmallBLargeASeries( a, b, x, y, fract, 1.0, regularized ); + } else { + fract = betaSmallBLargeASeries( a, b, x, y, 0.0, 1.0, regularized ); + } + } else { + if ( regularized ) { + prefix = 1; + } else { + // Sidestep to improve errors: + prefix = risingFactorialRatio( a + b, a, 20.0 ); + } + fract = ibetaAStep( a, b, x, y, 20.0, regularized, derivative ); + if ( invert ) { + fract -= ( ( regularized ) ? 1.0 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -betaSmallBLargeASeries( a + 20.0, b, x, y, fract, prefix, regularized ); + } else { + fract = betaSmallBLargeASeries( a + 20.0, b, x, y, fract, prefix, regularized ); + } + } + } + } else { + // Both a,b >= 1: + if ( a < b ) { + lambda = a - ( ( a + b ) * x ); + } else { + lambda = ( ( a + b ) * y ) - b; + } + if ( lambda < 0.0 ) { + tmp = b; + b = a; + a = tmp; + tmp = y; + y = x; + x = tmp; + invert = !invert; + } + if ( b < 40.0 ) { + if ( stdlib_base_floor( a ) == a && stdlib_base_floor( b ) == b && a < STDLIB_CONSTANT_INT32_MAX - 100 ) { + // Relate to the binomial distribution and use a finite sum: + k = a - 1.0; + n = b + k; + fract = binomialCCDF( n, k, x, y ); + if ( !regularized ) { + fract *= stdlib_base_beta( a, b ); + } + } else if ( b * x <= 0.7 ) { + if ( invert ) { + fract = -( ( regularized ) ? 1.0 : stdlib_base_beta( a, b ) ); + invert = false; + fract = -ibetaSeries( a, b, x, fract, regularized, derivative, y ); + } else { + fract = ibetaSeries( a, b, x, 0.0, regularized, derivative, y ); + } + } else if ( a > 15.0 ) { + // Sidestep so we can use the series representation: + n = stdlib_base_floor( b ); + if ( n == b ) { + n -= 1; + } + bbar = b - n; + if ( regularized ) { + prefix = 1; + } else { + prefix = risingFactorialRatio( a + bbar, bbar, n ); + } + fract = ibetaAStep( bbar, a, y, x, n, regularized, NULL ); + fract = betaSmallBLargeASeries( a, bbar, x, y, fract, 1.0, regularized ); + fract /= prefix; + } else if ( regularized ) { + n = stdlib_base_floor( b ); + bbar = b - n; + if ( bbar <= 0 ) { + n -= 1; + bbar += 1; + } + fract = ibetaAStep( bbar, a, y, x, n, regularized, NULL ); + fract += ibetaAStep( a, bbar, x, y, 20.0, regularized, NULL ); + if ( invert ) { + fract -= 1; + } + fract = betaSmallBLargeASeries( a + 20.0, bbar, x, y, fract, 1, regularized ); + if ( invert ) { + fract = -fract; + invert = false; + } + } else { + fract = ibetaFraction2( a, b, x, y, regularized, derivative ); + } + } else { + fract = ibetaFraction2( a, b, x, y, regularized, derivative ); + } + } + if ( *derivative < 0.0 ) { + *derivative = ibetaPowerTerms( a, b, x, y, true ); + } + div = y * x; + if ( *derivative != 0.0 ) { + if ( STDLIB_CONSTANT_FLOAT64_MAX * div < *derivative ) { + // Overflow, return an arbitrarily large value: + *derivative = STDLIB_CONSTANT_FLOAT64_MAX / 2.0; + } else { + *derivative /= div; + } + } + *out = ( invert ) ? ( ( regularized ) ? 1.0 : stdlib_base_beta( a, b ) ) - fract : fract; + return; +} diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/Makefile b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/Makefile new file mode 100644 index 000000000000..b726e14808c4 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/Makefile @@ -0,0 +1,120 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +endif + +# Specify the path to Boost: +BOOST ?= + +# Determine the OS: +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +endif +endif +endif + +# Define the program used for compiling C++ source files: +ifdef CXX_COMPILER + CXX := $(CXX_COMPILER) +else + CXX := g++ +endif + +# Define the command-line options when compiling C++ files: +CXXFLAGS ?= \ + -std=c++11 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate [position independent code][1]: +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of C++ targets: +cxx_targets := runner.out + + +# TARGETS # + +# Default target. +# +# This target is the default target. + +all: $(cxx_targets) + +.PHONY: all + + +# Compile C++ source. +# +# This target compiles C++ source files. + +$(cxx_targets): %.out: %.cpp $(BOOST) + $(QUIET) $(CXX) $(CXXFLAGS) $(fPIC) -I $(BOOST) -o $@ $< -lm + + +# Generate test fixtures. +# +# This target generates test fixtures. + +run: $(cxx_targets) + $(QUIET) ./$< + +.PHONY: run + + +# Perform clean-up. +# +# This target removes generated files. + +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean + + +# Remove fixtures. +# +# This target removes fixture data. + +clean-fixtures: + $(QUIET) -rm -f *.json + +.PHONY: clean-fixtures diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/int_values.json b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/int_values.json new file mode 100644 index 000000000000..a258b9485338 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/int_values.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/large_asym.json b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/large_asym.json new file mode 100644 index 000000000000..63bdd21ff176 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/large_asym.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/runner.cpp b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/runner.cpp new file mode 100644 index 000000000000..fb38d48c40d9 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/runner.cpp @@ -0,0 +1,497 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +/** +* Generate Boost test fixtures. +* +* ## Notes +* +* - Run this script from the directory in which fixtures should be written. +* +*/ +#include +#include +#include +#include +#include +#include +#include + +using boost::random::uniform_real_distribution; +using boost::random::uniform_int_distribution; +using boost::random::mt19937; + +// Define a new pseudorandom number generator: +mt19937 rng; + +/** +* Generates a linearly spaced numeric array of doubles. +* +* ## Notes +* +* - Assumes that the output array has at least 2 elements. +* - Output array is guaranteed to include both the start and end values. +* +* +* @param out output array +* @param len array length +* @param start first value +* @param end last value +*/ +void linspace_f64( double *out, const unsigned int len, const double start, const double end ) { + unsigned int i; + double incr; + + incr = (end-start) / (len-1); + for ( i = 0; i < len-1; i++ ) { + out[ i ] = start + (incr*i); + } + out[ i ] = end; +} + +/** +* Generates a linearly spaced numeric array of integers. +* +* ## Notes +* +* - Assumes that the output array has at least 2 elements. +* - Output array is guaranteed to include both the start and end values. +* +* +* @param out output array +* @param len array length +* @param start first value +* @param end last value +*/ +void linspace_i32( int *out, const unsigned int len, const int start, const int end ) { + unsigned int i; + int incr; + + incr = (end-start) / (len-1); + for ( i = 0; i < len-1; i++ ) { + out[ i ] = start + (incr*i); + } + out[ i ] = end; +} + +/** +* Generates an array of pseudorandom doubles drawn from a uniform distribution. +* +* @param out output array +* @param len array length +* @param a lower bound (inclusive) +* @param b upper bound (exclusive) +*/ +void rand_array_f64( double *out, const unsigned int len, const double a, const double b ) { + unsigned int i; + + // Define a uniform distribution for generating pseudorandom numbers: + uniform_real_distribution<> randu( a, b ); + + for ( i = 0; i < len; i++ ) { + out[ i ] = randu( rng ); + } +} + +/** +* Generates an array of pseudorandom integers drawn from a uniform distribution. +* +* @param out output array +* @param len array length +* @param a lower bound (inclusive) +* @param b upper bound (exclusive) +*/ +void rand_array_i32( int *out, const unsigned int len, const int a, const int b ) { + unsigned int i; + + // Define a uniform distribution for generating pseudorandom numbers: + uniform_int_distribution<> randi( a, b ); + + for ( i = 0; i < len; i++ ) { + out[ i ] = randi( rng ); + } +} + +/** +* Casts an array of integers to an array of doubles. +* +* @param out output array +* @param x input array +* @param len array length +*/ +void i32_to_f64( double *out, int *x, unsigned int len ) { + unsigned int i; + + for ( i = 0; i < len; i++ ) { + out[ i ] = (double) x[ i ]; + } +} + +/** +* Casts an array of doubles to an array of integers. +* +* @param out output array +* @param x input array +* @param len array length +*/ +void f64_to_i32( int *out, double *x, unsigned int len ) { + unsigned int i; + + for ( i = 0; i < len; i++ ) { + out[ i ] = (int) x[ i ]; + } +} + +/** +* Writes an array of doubles to a file as a series of comma-separated values. +* +* @param f file to write to +* @param x array of doubles +* @param len array length +*/ +void write_array_f64( FILE *f, const double *x, const unsigned int len ) { + unsigned int i; + for ( i = 0; i < len; i++ ) { + fprintf( f, "%.17g", x[ i ] ); + if ( i < len-1 ) { + fprintf( f, "," ); + } + } +} + +/** +* Writes an array of integers to a file as a series of comma-separated values. +* +* @param f file to write to +* @param x array of integers +* @param len array length +*/ +void write_array_i32( FILE *f, const int *x, const unsigned int len ) { + unsigned int i; + + for ( i = 0; i < len; i++ ) { + fprintf( f, "%d", x[ i ] ); + if ( i < len-1 ) { + fprintf( f, "," ); + } + } +} + +/** +* Writes a named array of doubles to a file as JSON. +* +* @param f file to write to +* @param name array name +* @param x data +* @param len array length +*/ +void write_named_array_f64( FILE *f, const char *name, const double *x, const unsigned int len ) { + fprintf( f, "\"%s\":[", name ); + write_array_f64( f, x, len ); + fprintf( f, "]" ); +} + +/** +* Writes a named array of integers to a file as JSON. +* +* @param f file to write to +* @param name array name +* @param x data +* @param len array length +*/ +void write_named_array_i32( FILE *f, const char *name, const int *x, const unsigned int len ) { + fprintf( f, "\"%s\":[", name ); + write_array_i32( f, x, len ); + fprintf( f, "]" ); +} + +/** +* Writes data to a file as JSON. +* +* ## Notes +* +* - This function SHOULD be tailored to the input data (e.g., input types, output types, number of arguments, etc) and may vary from use case to use case. +* +* +* @param f file to write to +* @param x first parameter +* @param a second parameter +* @param b third parameter +* @param lower_regularized lower regularized incomplete beta function +* @param upper_regularized upper regularized incomplete beta function +* @param lower_unregularized lower unregularized incomplete beta function +* @param upper_unregularized upper unregularized incomplete beta function +* @param len array length +*/ +void write_data_as_json( FILE *f, const double *x, const double *a, const double *b, const double *lower_regularized, const double *upper_regularized, const double *lower_unregularized, const double *upper_unregularized, const unsigned int len ) { + fprintf( f, "{" ); + write_named_array_f64( f, "x", x, len ); + fprintf( f, "," ); + write_named_array_f64( f, "a", a, len ); + fprintf( f, "," ); + write_named_array_f64( f, "b", b, len ); + fprintf( f, "," ); + write_named_array_f64( f, "lower_regularized", lower_regularized, len ); + fprintf( f, "," ); + write_named_array_f64( f, "upper_regularized", upper_regularized, len ); + fprintf( f, "," ); + write_named_array_f64( f, "lower_unregularized", lower_unregularized, len ); + fprintf( f, "," ); + write_named_array_f64( f, "upper_unregularized", upper_unregularized, len ); + fprintf( f, "}" ); +} + +/** +* Generates test fixtures. +* +* @param x first parameter +* @param a second parameter +* @param b third parameter +* @param len number of values in the domain +* @param name output filename +*/ +void generate( double *x, double *a, double *b, const unsigned int len, const char *name ) { + double *upper_unregularized; + double *lower_unregularized; + double *upper_regularized; + double *lower_regularized; + unsigned int i; + FILE *f; + + // Allocate an output array: + lower_regularized = (double*) malloc( len * sizeof(double) ); + if ( lower_regularized == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + upper_regularized = (double*) malloc( len * sizeof(double) ); + if ( upper_regularized == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + lower_unregularized = (double*) malloc( len * sizeof(double) ); + if ( lower_unregularized == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + upper_unregularized = (double*) malloc( len * sizeof(double) ); + if ( upper_unregularized == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Generate fixture data: + for ( i = 0; i < len; i++ ) { + double arg1 = a[ i ]; + double arg2 = b[ i ]; + double arg3 = x[ i ]; + lower_regularized[ i ] = boost::math::ibeta( arg1, arg2, arg3 ); + upper_regularized[ i ] = boost::math::ibetac( arg1, arg2, arg3 ); + lower_unregularized[ i ] = boost::math::beta( arg1, arg2, arg3 ); + upper_unregularized[ i ] = boost::math::betac( arg1, arg2, arg3 ); + } + // Open a new file: + f = fopen( name, "w" ); + if ( f == NULL ) { + printf( "Error opening file.\n" ); + exit( 1 ); + } + // Write data as JSON: + write_data_as_json( f, x, a, b, lower_regularized, upper_regularized, lower_unregularized, upper_unregularized, len ); + + // Close the file: + fclose( f ); + + // Free allocated memory: + free( lower_regularized ); + free( upper_regularized ); + free( lower_unregularized ); + free( upper_unregularized ); +} + +/** +* Main execution sequence. +*/ +int main( void ) { + unsigned int len; + unsigned int idx; + unsigned int i; + unsigned int j; + unsigned int k; + double exponents[ 11 ]; + double asym_exp[ 4 ]; + double asym_muls[ 20 ]; + double asym_vals[ 40 ]; + double muls[ 11 ]; + int ab_ints[ 10 ]; + double *x; + double *a; + double *b; + double a_val; + double b_val; + double x0; + double xv; + double lr; + double ur; + + // Define the array length: + len = 17600; + + // Allocate arrays: + x = (double*) malloc( len * sizeof(double) ); + if ( x == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + a = (double*) malloc( len * sizeof(double) ); + if ( a == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + b = (double*) malloc( len * sizeof(double) ); + if ( b == NULL ) { + printf( "Error allocating memory.\n" ); + exit( 1 ); + } + + // Generate fixture data for small a,b in [0,10]: + rand_array_f64( a, 500, 0.001, 10.0 ); + rand_array_f64( b, 500, 0.001, 10.0 ); + rand_array_f64( x, 500, 0.0001, 1.0 ); + generate( x, a, b, 500, "small_range.json" ); + + // Generate fixture data for medium a,b in [0,100]: + rand_array_f64( a, 500, 0.001, 100.0 ); + rand_array_f64( b, 500, 0.001, 100.0 ); + rand_array_f64( x, 500, 0.0001, 1.0 ); + generate( x, a, b, 500, "medium_range.json" ); + + // Generate fixture data for large range a,b ~ 10^-5 to 10^6: + linspace_f64( exponents, 11, -5.0, 6.0 ); + idx = 0; + for ( i = 0; i < 11; i++ ) { + for ( j = 0; j < 11; j++ ) { + for ( k = 0; k < 10; k++ ) { + uniform_real_distribution<> gen( 1.0, 5.0 ); + uniform_real_distribution<> genx( 0.0001, 1.0 ); + a[ idx ] = gen( rng ) * pow( 10.0, exponents[ i ] ); + b[ idx ] = gen( rng ) * pow( 10.0, exponents[ j ] ); + x[ idx ] = genx( rng ); + idx++; + } + } + } + generate( x, a, b, idx, "large_range.json" ); + + // Generate fixture data for integer a,b in {1,5,9,...,37}: + linspace_i32( ab_ints, 10, 1, 37 ); + idx = 0; + for ( i = 0; i < 10; i++ ) { + for ( j = 0; j < 10; j++ ) { + for ( k = 0; k < 10; k++ ) { + uniform_real_distribution<> genx( 0.0001, 1.0 ); + a[ idx ] = (double) ab_ints[ i ]; + b[ idx ] = (double) ab_ints[ j ]; + x[ idx ] = genx( rng ); + idx++; + } + } + } + generate( x, a, b, idx, "int_values.json" ); + + // Generate fixture data for large asymmetric a,b values: + muls[ 0 ] = 0.9; + muls[ 1 ] = 0.99; + muls[ 2 ] = 0.9999; + muls[ 3 ] = 0.99999; + muls[ 4 ] = 0.999999; + muls[ 5 ] = 0.99999999; + muls[ 6 ] = 1.001; + muls[ 7 ] = 1.1; + muls[ 8 ] = 1.00001; + muls[ 9 ] = 1.0000001; + muls[ 10 ] = 1.000000001; + for ( i = 0; i < 40; i++ ) { + asym_vals[ i ] = pow( 2.0, 20.0 * i / 39.0 ); + } + idx = 0; + for ( i = 0; i < 40; i++ ) { + for ( j = 0; j < 40; j++ ) { + a_val = asym_vals[ i ]; + b_val = asym_vals[ j ]; + x0 = a_val / ( a_val + b_val ); + for ( k = 0; k < 11; k++ ) { + xv = x0 * muls[ k ]; + if ( xv >= 1.0 || xv <= 0.0 ) { + continue; + } + lr = boost::math::ibeta( a_val, b_val, xv ); + ur = boost::math::ibetac( a_val, b_val, xv ); + if ( !isfinite( lr ) || !isfinite( ur ) ) { + continue; + } + if ( lr < 0.0 || lr > 1.0 || ur < 0.0 || ur > 1.0 ) { + continue; + } + a[ idx ] = a_val; + b[ idx ] = b_val; + x[ idx ] = xv; + idx++; + } + } + } + generate( x, a, b, idx, "large_asym.json" ); + + // Generate fixture data for asymptotically large a,b values: + linspace_f64( asym_exp, 4, 10.0, 18.0 ); + linspace_f64( asym_muls, 20, 1.0 - 10.0/2048.0, 1.0 + 10.0/2048.0 ); + idx = 0; + for ( i = 0; i < 4; i++ ) { + a_val = pow( 10.0, asym_exp[ i ] ); + for ( j = 0; j < 20; j++ ) { + b_val = a_val * asym_muls[ j ]; + x0 = a_val / ( a_val + b_val ); + for ( k = 0; k < 20; k++ ) { + xv = x0 * asym_muls[ k ]; + if ( xv >= 1.0 || xv <= 0.0 ) { + continue; + } + lr = boost::math::ibeta( a_val, b_val, xv ); + ur = boost::math::ibetac( a_val, b_val, xv ); + if ( !isfinite( lr ) || !isfinite( ur ) ) { + continue; + } + if ( lr < 0.0 || lr > 1.0 || ur < 0.0 || ur > 1.0 ) { + continue; + } + a[ idx ] = a_val; + b[ idx ] = b_val; + x[ idx ] = xv; + idx++; + } + } + } + generate( x, a, b, idx, "very_large_asym.json" ); + + // Free allocated memory: + free( x ); + free( a ); + free( b ); + + return 0; +} diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/small_range.json b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/small_range.json new file mode 100644 index 000000000000..2451aa589e18 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/small_range.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/very_large_asym.json b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/very_large_asym.json new file mode 100644 index 000000000000..565cb43ae348 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/fixtures/cpp/very_large_asym.json @@ -0,0 +1 @@ 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\ No newline at end of file diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/test.js b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/test.js index 90caa18694a9..b3b4260f2556 100644 --- a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/test.js @@ -23,9 +23,25 @@ var tape = require( 'tape' ); var isNaNArray = require( '@stdlib/assert/is-nan-array' ); var isArray = require( '@stdlib/assert/is-array' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var ldexp = require( '@stdlib/math/base/special/ldexp' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var SMALLEST_NORMAL = require( '@stdlib/constants/float64/smallest-normal' ); +var PI = require( '@stdlib/constants/float64/pi' ); var kernelBetainc = require( './../lib' ); +// FIXTURES // + +var smallRange = require( './fixtures/cpp/small_range.json' ); +var mediumRange = require( './fixtures/cpp/medium_range.json' ); +var largeRange = require( './fixtures/cpp/large_range.json' ); +var intValues = require( './fixtures/cpp/int_values.json' ); +var largeAsym = require( './fixtures/cpp/large_asym.json' ); +var veryLargeAsym = require( './fixtures/cpp/very_large_asym.json' ); + + // TESTS // tape( 'main export is a function', function test( t ) { @@ -68,7 +84,34 @@ tape( 'the function returns `[ NaN, NaN ]` if `x` is `NaN`', function test( t ) t.end(); }); -tape( 'the function returns `[ NaN, NaN ]` if negative `a` or `b`', function test( t ) { +tape( 'the function returns `[ NaN, NaN ]` if `a` or `b` is `NaN`', function test( t ) { + var val = kernelBetainc( 0.5, NaN, 1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, NaN, 1.0, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, NaN, 1.0, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, NaN, 1.0, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `[ NaN, NaN ]` if `a` or `b` is negative', function test( t ) { var val = kernelBetainc( 0.5, -1.0, 1.0, true, true ); t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); @@ -122,4 +165,799 @@ tape( 'attached to the function is a method which supports supplying a destinati t.end(); }); -// TODO: Add fixtures +tape( 'the function returns expected endpoint values and regularized derivatives when `x` is `0`', function test( t ) { + var val; + + val = kernelBetainc( 0.0, 1.0, 2.0, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for lower regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for lower regularized endpoint' ); + + val = kernelBetainc( 0.0, 1.0, 2.0, true, true ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value for upper regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for upper regularized endpoint' ); + + val = kernelBetainc( 0.0, 1.0, 2.0, false, false ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for lower unregularized endpoint' ); + + val = kernelBetainc( 0.0, 1.0, 2.0, false, true ); + t.strictEqual( val[ 0 ], 0.5, 'returns expected value for upper unregularized endpoint' ); + + t.end(); +}); + +tape( 'the function returns expected endpoint values and regularized derivatives when `x` is `1`', function test( t ) { + var val; + + val = kernelBetainc( 1.0, 2.0, 1.0, true, false ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value for lower regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for lower regularized endpoint' ); + + val = kernelBetainc( 1.0, 2.0, 1.0, true, true ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for upper regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for upper regularized endpoint' ); + + val = kernelBetainc( 1.0, 2.0, 1.0, false, false ); + t.strictEqual( val[ 0 ], 0.5, 'returns expected value for lower unregularized endpoint' ); + + val = kernelBetainc( 1.0, 2.0, 1.0, false, true ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for upper unregularized endpoint' ); + + t.end(); +}); + +tape( 'the function handles the `a=1` branch', function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 1.0, 2.0, true, false ); + t.strictEqual( val[ 0 ], 0.4375, 'returns expected value for lower regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.5, 'returns expected regularized derivative for lower regularized endpoint' ); + + val = kernelBetainc( 0.25, 1.0, 2.0, true, true ); + t.strictEqual( val[ 0 ], 0.5625, 'returns expected value for upper regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.5, 'returns expected regularized derivative for upper regularized endpoint' ); + + val = kernelBetainc( 0.25, 1.0, 2.0, false, false ); + t.strictEqual( val[ 0 ], 0.21875, 'returns expected value for lower unregularized endpoint' ); + + val = kernelBetainc( 0.25, 1.0, 2.0, false, true ); + t.strictEqual( val[ 0 ], 0.28125, 'returns expected value for upper unregularized endpoint' ); + + val = kernelBetainc( 32/100, 1.0, 4634/100000, true, false ); + expected = 0.017712849440718489999419956301675684844663359595318; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles the `b=1` branch', function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 2.0, 1.0, true, false ); + t.strictEqual( val[ 0 ], 0.0625, 'returns expected lower regularized value' ); + t.strictEqual( val[ 1 ], 0.5, 'returns expected regularized derivative for lower regularized value' ); + + val = kernelBetainc( 0.25, 2.0, 1.0, true, true ); + t.strictEqual( val[ 0 ], 0.9375, 'returns expected upper regularized value' ); + t.strictEqual( val[ 1 ], 0.5, 'returns expected regularized derivative for upper regularized value' ); + + val = kernelBetainc( 0.25, 2.0, 1.0, false, false ); + t.strictEqual( val[ 0 ], 0.03125, 'returns expected lower unregularized value' ); + + val = kernelBetainc( 0.25, 2.0, 1.0, false, true ); + t.strictEqual( val[ 0 ], 0.46875, 'returns expected upper unregularized value' ); + + val = kernelBetainc( 0.825, 0.5, 1, true, false ); + expected = 0.908295106229247499626759842915458109758420750043003849691665; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 0.5, 1, true, true ); + expected = 0.091704893770752500373240157084541890241579249956996150308334; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 2 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 30, 1, true, false ); + expected = 0.003116150729395132012981654047222541793435357905008020740211; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 16 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 30, 1, true, true ); + expected = 0.996883849270604867987018345952777458206564642094991979259788; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 32/100, 4634/100000, 1.0, true, false ); + expected = 0.94856839398626914764591440181367780660208493234722; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles the `a=0.5` and `b=0.5` cases', function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 0.5, 0.5, true, false ); + expected = 1.0 / 3.0; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + expected = sqrt( 3.0 ) / ( 4.0 * PI ); + t.strictEqual( isAlmostSameValue( val[ 1 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 0.5, 0.5, true, true ); + expected = 2.0 / 3.0; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + expected = PI / 3.0; + val = kernelBetainc( 0.25, 0.5, 0.5, false, false ); + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + expected = 2.0 * PI / 3.0; + val = kernelBetainc( 0.25, 0.5, 0.5, false, true ); + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.125, 0.5, 0.5, true, false ); + expected = 0.230053456162615885213780567705142893009911395270714102055874; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.125, 0.5, 0.5, true, true ); + expected = 0.769946543837384114786219432294857106990088604729285897944125; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 0.5, 0.5, true, false ); + expected = 0.725231121519469565327291851560156562956885802608457839260161; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 0.5, 0.5, true, true ); + expected = 0.274768878480530434672708148439843437043114197391542160739838; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles the a=0 and b=0 regularized boundary cases', function test( t ) { + var val; + + val = kernelBetainc( 0.5, 0, 2, true, false ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value' ); + + val = kernelBetainc( 0.5, 3, 0, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value' ); + + val = kernelBetainc( 0.5, 0, 2, true, true ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value' ); + + val = kernelBetainc( 0.5, 4, 0, true, true ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +// Source: https://raw.githubusercontent.com/boostorg/math/e1bdcad01783fe8d285c363c948b47173846e734/test/test_ibeta.hpp +tape( 'the function evaluates the lower regularized incomplete beta function for Wolfram-verified spot values', function test( t ) { + var expected; + var val; + + val = kernelBetainc( 6917/10000, 159/10000, 1184/1000000000, true, false ); + expected = 0.000075393541456247525676062058821484095548666733251733; + t.strictEqual( isAlmostSameValue( val[0], expected, 3 ), true, 'returns expected value' ); + + val = kernelBetainc( 9157/10000, 4243/100, 3001/10000, true, false ); + expected = 0.0028387319012616013434124297160711532419664289474798; + t.strictEqual( isAlmostSameValue( val[0], expected, 16 ), true, 'returns expected value' ); + + val = kernelBetainc( 8391/100000, 9713/1000, 9940/100, true, false ); + expected = 0.46116895440368248909937863372410093344466819447476; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.75, 72.5, 1.125, true, false ); + expected = 1.3423066982487051710597194786268004978931316494920e-9; + t.strictEqual( isAlmostSameValue( val[0], expected, 11 ), true, 'returns expected value' ); + + val = kernelBetainc( 7599/10000, 4985/1000, 1066/1000, true, false ); + expected = 0.27533431334486812211032939156910472371928659321347; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 1741/10000, 6813/1000, 1056/1000, true, false ); + expected = 7.6736128722762245852815040810349072461658078840945e-6; + t.strictEqual( isAlmostSameValue( val[0], expected, 7 ), true, 'returns expected value' ); + + val = kernelBetainc( 2003/10000, 4898/10000, 2251/10000, true, false ); + expected = 0.17089223868046209692215231702890838878342349377008; + t.strictEqual( isAlmostSameValue( val[0], expected, 2 ), true, 'returns expected value' ); + + val = kernelBetainc( 6537/10000, 4049/1000, 1540/10000, true, false ); + expected = 0.017273988301528087878279199511703371301647583919670; + t.strictEqual( isAlmostSameValue( val[0], expected, 10 ), true, 'returns expected value' ); + + val = kernelBetainc( 8003/10000, 7269/1000, 1190/10000, true, false ); + expected = 0.013334694467796052900138431733772122625376753696347; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 8665/100000, 2726/1000, 1151/100000, true, false ); + expected = 5.8218877068298586420691288375690562915515260230173e-6; + t.strictEqual( isAlmostSameValue( val[0], expected, 5 ), true, 'returns expected value' ); + + val = kernelBetainc( 7582/10000, 3431/10000, 4634/100000, true, false ); + expected = 0.15132819929418661038699397753916091907278005695387; + t.strictEqual( isAlmostSameValue( val[0], expected, 2 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for integer arguments', function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 3, 8, true, false ); + expected = 0.474407196044921875; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 6, 8, true, false ); + expected = 0.080212593078613281250; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 12, 1, true, false ); + expected = 5.96046447753906250e-8; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 1, 8, true, false ); + expected = 0.899887084960937500; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +// Bug cases from Rocco Romeo + +// Source: https://raw.githubusercontent.com/boostorg/math/e1bdcad01783fe8d285c363c948b47173846e734/test/test_ibeta.hpp +tape( 'the function handles extreme x values (Rocco Romeo bug cases)', function test( t ) { + // These test extreme x values near powers of 2 + var expected; + var val; + var x0; + + x0 = ldexp( 1.0, -52 ); + val = kernelBetainc( x0, 2, 24, false, false ); + expected=2.46519032881565349871772482100516780410072110983579277754743e-32; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 2 ), true, 'returns expected value' ); + + val = kernelBetainc( x0, 2, 24, true, false ); + expected=1.47911419728939209923063489260310068246043266590147566652846e-29; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + x0 = ldexp( 1.0, -270 ); + val = kernelBetainc( x0, 3, 2, false, false ); + expected=4.88182556606650701438035298707052523938789614661168065734809e-245; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( x0, 3, 2, true, false ); + expected=5.85819067927980841725642358448463028726547537593401678881771e-244; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + x0 = ldexp( 1.0, -373 ); + val = kernelBetainc( x0, 2, 31, false, false ); + expected=1.35080680244581673116149460571129957689952846520037541640260e-225; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 12 ), true, 'returns expected value' ); + + val = kernelBetainc( x0, 2, 31, true, false ); + expected=1.34000034802625019731220264886560918028433223747877241307138e-222; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the correct derivative for a naive analytical check', function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.5, 2, 3, true, false ); + expected = 1.5; + t.strictEqual( isAlmostSameValue( val[ 1 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles tiny parameter values', function test( t ) { + var small; + var tiny; + var val; + + tiny = SMALLEST_NORMAL / 2.0; + small = EPS; + if ( tiny !== 0.0 ) { + val = kernelBetainc( small, tiny, small, true, false ); + t.strictEqual( val[ 0 ], 1.0, 'ibeta(tiny, eps, eps) = 1 where tiny = smallest_normal/2' ); + } + + val = kernelBetainc( 0.0, 2, 1, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'return expected lower regularized value.' ); + + val = kernelBetainc( 0.0, 1, 2, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'return expected lower regularized value.' ); + + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for small a,b in [0,10]', function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.lower_regularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 23 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for small a,b in [0,10]', function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.upper_regularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 28 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for small a,b in [0,10]', function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.lower_unregularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 48 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for small a,b in [0,10]', function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.upper_unregularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 36 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for medium a,b in [0,100]', function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.lower_regularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 226 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for medium a,b in [0,100]', function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.upper_regularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 231 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for medium a,b in [0,100]', function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.lower_unregularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 319 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for medium a,b in [0,100]', function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.upper_unregularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 332 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for large range a,b in [1e-5,1e6]', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.lower_regularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 2897 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for large range a,b in [1e-5,1e6]', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.upper_regularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 11049 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for large range a,b in [1e-5,1e6]', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.lower_unregularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 2699 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for large range a,b in [1e-5,1e6]', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.upper_unregularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 814 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for integer a,b in {1,5,9,...,37}', function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.lower_regularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 15 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for integer a,b in {1,5,9,...,37}', function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.upper_regularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 28 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for integer a,b in {1,5,9,...,37}', function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.lower_unregularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 122 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for integer a,b in {1,5,9,...,37}', function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.upper_unregularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 117 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for x near the distribution mean a/(a+b)', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.lower_regularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1178040 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for x near the distribution mean a/(a+b)', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.upper_regularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1164470 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for x near the distribution mean a/(a+b)', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.lower_unregularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 26397 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for x near the distribution mean a/(a+b)', function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.upper_unregularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 26396 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for asymptotically large a,b values', function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.lower_regularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 13539863633 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for asymptotically large a,b values', function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.upper_regularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 15990448265 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for asymptotically large a,b values', function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.lower_unregularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for asymptotically large a,b values', function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.upper_unregularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +// Source: https://github.com/boostorg/math/blob/e1bdcad01783fe8d285c363c948b47173846e734/test/test_ibeta.hpp +tape( 'ibeta is monotonically increasing for large a,b near the median', function test( t ) { + var deltas; + var above0; + var above1; + var below0; + var below1; + var x0; + var a; + var b; + var i; + + a = 10000000272564224; + b = 9965820922822656; + x0 = a / ( a + b ); + deltas = [ 0, 1e-15, 1e-14, 1e-13, 1e-12, 1e-11, 1e-10 ]; + + for ( i = 1; i < 6; i++ ) { + above1 = kernelBetainc( x0 + deltas[ i+1 ], a, b, true, false )[ 0 ]; + above0 = kernelBetainc( x0 + deltas[ i ], a, b, true, false )[ 0 ]; + t.ok( above1 > above0, 'ibeta monotonically increasing above a/(a+b) for delta=' + deltas[ i ] ); + + below0 = kernelBetainc( x0 - deltas[ i ], a, b, true, false )[ 0 ]; + below1 = kernelBetainc( x0 - deltas[ i+1 ], a, b, true, false )[ 0 ]; + t.ok( below0 > below1, 'ibeta monotonically increasing below a/(a+b) for delta=' + deltas[ i ] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/test.native.js new file mode 100644 index 000000000000..2f1d0fbfd8e6 --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/kernel-betainc/test/test.native.js @@ -0,0 +1,957 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isNaNArray = require( '@stdlib/assert/is-nan-array' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var ldexp = require( '@stdlib/math/base/special/ldexp' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var SMALLEST_NORMAL = require( '@stdlib/constants/float64/smallest-normal' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PI = require( '@stdlib/constants/float64/pi' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var kernelBetainc = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kernelBetainc instanceof Error ) +}; + + +// FIXTURES // + +var smallRange = require( './fixtures/cpp/small_range.json' ); +var mediumRange = require( './fixtures/cpp/medium_range.json' ); +var largeRange = require( './fixtures/cpp/large_range.json' ); +var intValues = require( './fixtures/cpp/int_values.json' ); +var largeAsym = require( './fixtures/cpp/large_asym.json' ); +var veryLargeAsym = require( './fixtures/cpp/very_large_asym.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof kernelBetainc, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns `[ NaN, NaN ]` if `x` is outside `[0,1]`', opts, function test( t ) { + var val = kernelBetainc( -0.2, 1.0, 1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( -0.2, 1.0, 1.0, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( -0.2, 1.0, 1.0, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( -0.2, 1.0, 1.0, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 1.1, 1.0, 1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 1.1, 1.0, 1.0, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 1.1, 1.0, 1.0, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 1.1, 1.0, 1.0, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns `[ NaN, NaN ]` if `x` is `NaN`', opts, function test( t ) { + var val = kernelBetainc( NaN, 1.0, 1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `[ NaN, NaN ]` if `a` or `b` is `NaN`', opts, function test( t ) { + var val = kernelBetainc( 0.5, NaN, 1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, NaN, 1.0, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, NaN, 1.0, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, NaN, 1.0, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, NaN, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns `[ NaN, NaN ]` if `a` or `b` is negative', opts, function test( t ) { + var val = kernelBetainc( 0.5, -1.0, 1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, -1.0, 1.0, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, -1.0, 1.0, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, -1.0, 1.0, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, -1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, -1.0, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, -1.0, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, 1.0, -1.0, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, -1.0, -1.0, true, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, -1.0, -1.0, false, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, -1.0, -1.0, false, true ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + val = kernelBetainc( 0.5, -1.0, -1.0, true, false ); + t.strictEqual( isNaNArray( val ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns expected endpoint values and regularized derivatives when `x` is `0`', opts, function test( t ) { + var val; + + val = kernelBetainc( 0.0, 1.0, 2.0, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for lower regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for lower regularized endpoint' ); + + val = kernelBetainc( 0.0, 1.0, 2.0, true, true ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value for upper regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for upper regularized endpoint' ); + + val = kernelBetainc( 0.0, 1.0, 2.0, false, false ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for lower unregularized endpoint' ); + + val = kernelBetainc( 0.0, 1.0, 2.0, false, true ); + t.strictEqual( val[ 0 ], 0.5, 'returns expected value for upper unregularized endpoint' ); + + t.end(); +}); + +tape( 'the function returns expected endpoint values and regularized derivatives when `x` is `1`', opts, function test( t ) { + var val; + + val = kernelBetainc( 1.0, 2.0, 1.0, true, false ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value for lower regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for lower regularized endpoint' ); + + val = kernelBetainc( 1.0, 2.0, 1.0, true, true ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for upper regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.0, 'returns expected regularized derivative for upper regularized endpoint' ); + + val = kernelBetainc( 1.0, 2.0, 1.0, false, false ); + t.strictEqual( val[ 0 ], 0.5, 'returns expected value for lower unregularized endpoint' ); + + val = kernelBetainc( 1.0, 2.0, 1.0, false, true ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value for upper unregularized endpoint' ); + + t.end(); +}); + +tape( 'the function handles the `a=1` branch', opts, function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 1.0, 2.0, true, false ); + t.strictEqual( val[ 0 ], 0.4375, 'returns expected value for lower regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.5, 'returns expected regularized derivative for lower regularized endpoint' ); + + val = kernelBetainc( 0.25, 1.0, 2.0, true, true ); + t.strictEqual( val[ 0 ], 0.5625, 'returns expected value for upper regularized endpoint' ); + t.strictEqual( val[ 1 ], 1.5, 'returns expected regularized derivative for upper regularized endpoint' ); + + val = kernelBetainc( 0.25, 1.0, 2.0, false, false ); + t.strictEqual( val[ 0 ], 0.21875, 'returns expected value for lower unregularized endpoint' ); + + val = kernelBetainc( 0.25, 1.0, 2.0, false, true ); + t.strictEqual( val[ 0 ], 0.28125, 'returns expected value for upper unregularized endpoint' ); + + val = kernelBetainc( 32/100, 1.0, 4634/100000, true, false ); + expected = 0.017712849440718489999419956301675684844663359595318; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles the `b=1` branch', opts, function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 2.0, 1.0, true, false ); + t.strictEqual( val[ 0 ], 0.0625, 'returns expected lower regularized value' ); + t.strictEqual( val[ 1 ], 0.5, 'returns expected regularized derivative for lower regularized value' ); + + val = kernelBetainc( 0.25, 2.0, 1.0, true, true ); + t.strictEqual( val[ 0 ], 0.9375, 'returns expected upper regularized value' ); + t.strictEqual( val[ 1 ], 0.5, 'returns expected regularized derivative for upper regularized value' ); + + val = kernelBetainc( 0.25, 2.0, 1.0, false, false ); + t.strictEqual( val[ 0 ], 0.03125, 'returns expected lower unregularized value' ); + + val = kernelBetainc( 0.25, 2.0, 1.0, false, true ); + t.strictEqual( val[ 0 ], 0.46875, 'returns expected upper unregularized value' ); + + val = kernelBetainc( 0.825, 0.5, 1, true, false ); + expected = 0.908295106229247499626759842915458109758420750043003849691665; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 0.5, 1, true, true ); + expected = 0.091704893770752500373240157084541890241579249956996150308334; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 2 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 30, 1, true, false ); + expected = 0.003116150729395132012981654047222541793435357905008020740211; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 16 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 30, 1, true, true ); + expected = 0.996883849270604867987018345952777458206564642094991979259788; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 32/100, 4634/100000, 1.0, true, false ); + expected = 0.94856839398626914764591440181367780660208493234722; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles the `a=0.5` and `b=0.5` cases', opts, function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 0.5, 0.5, true, false ); + expected = 1.0 / 3.0; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + expected = sqrt( 3.0 ) / ( 4.0 * PI ); + t.strictEqual( isAlmostSameValue( val[ 1 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 0.5, 0.5, true, true ); + expected = 2.0 / 3.0; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + expected = PI / 3.0; + val = kernelBetainc( 0.25, 0.5, 0.5, false, false ); + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + expected = 2.0 * PI / 3.0; + val = kernelBetainc( 0.25, 0.5, 0.5, false, true ); + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.125, 0.5, 0.5, true, false ); + expected = 0.230053456162615885213780567705142893009911395270714102055874; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.125, 0.5, 0.5, true, true ); + expected = 0.769946543837384114786219432294857106990088604729285897944125; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 0.5, 0.5, true, false ); + expected = 0.725231121519469565327291851560156562956885802608457839260161; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.825, 0.5, 0.5, true, true ); + expected = 0.274768878480530434672708148439843437043114197391542160739838; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles the a=0 and b=0 regularized boundary cases', opts, function test( t ) { + var val; + + val = kernelBetainc( 0.5, 0, 2, true, false ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value' ); + + val = kernelBetainc( 0.5, 3, 0, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value' ); + + val = kernelBetainc( 0.5, 0, 2, true, true ); + t.strictEqual( val[ 0 ], 0.0, 'returns expected value' ); + + val = kernelBetainc( 0.5, 4, 0, true, true ); + t.strictEqual( val[ 0 ], 1.0, 'returns expected value' ); + + t.end(); +}); + +// Source: https://raw.githubusercontent.com/boostorg/math/e1bdcad01783fe8d285c363c948b47173846e734/test/test_ibeta.hpp +tape( 'the function evaluates the lower regularized incomplete beta function for Wolfram-verified spot values', opts, function test( t ) { + var expected; + var val; + + val = kernelBetainc( 6917/10000, 159/10000, 1184/1000000000, true, false ); + expected = 0.000075393541456247525676062058821484095548666733251733; + t.strictEqual( isAlmostSameValue( val[0], expected, 3 ), true, 'returns expected value' ); + + val = kernelBetainc( 9157/10000, 4243/100, 3001/10000, true, false ); + expected = 0.0028387319012616013434124297160711532419664289474798; + t.strictEqual( isAlmostSameValue( val[0], expected, 16 ), true, 'returns expected value' ); + + val = kernelBetainc( 8391/100000, 9713/1000, 9940/100, true, false ); + expected = 0.46116895440368248909937863372410093344466819447476; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.75, 72.5, 1.125, true, false ); + expected = 1.3423066982487051710597194786268004978931316494920e-9; + t.strictEqual( isAlmostSameValue( val[0], expected, 11 ), true, 'returns expected value' ); + + val = kernelBetainc( 7599/10000, 4985/1000, 1066/1000, true, false ); + expected = 0.27533431334486812211032939156910472371928659321347; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 1741/10000, 6813/1000, 1056/1000, true, false ); + expected = 7.6736128722762245852815040810349072461658078840945e-6; + t.strictEqual( isAlmostSameValue( val[0], expected, 7 ), true, 'returns expected value' ); + + val = kernelBetainc( 2003/10000, 4898/10000, 2251/10000, true, false ); + expected = 0.17089223868046209692215231702890838878342349377008; + t.strictEqual( isAlmostSameValue( val[0], expected, 2 ), true, 'returns expected value' ); + + val = kernelBetainc( 6537/10000, 4049/1000, 1540/10000, true, false ); + expected = 0.017273988301528087878279199511703371301647583919670; + t.strictEqual( isAlmostSameValue( val[0], expected, 10 ), true, 'returns expected value' ); + + val = kernelBetainc( 8003/10000, 7269/1000, 1190/10000, true, false ); + expected = 0.013334694467796052900138431733772122625376753696347; + t.strictEqual( isAlmostSameValue( val[0], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 8665/100000, 2726/1000, 1151/100000, true, false ); + expected = 5.8218877068298586420691288375690562915515260230173e-6; + t.strictEqual( isAlmostSameValue( val[0], expected, 5 ), true, 'returns expected value' ); + + val = kernelBetainc( 7582/10000, 3431/10000, 4634/100000, true, false ); + expected = 0.15132819929418661038699397753916091907278005695387; + t.strictEqual( isAlmostSameValue( val[0], expected, 2 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for integer arguments', opts, function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.25, 3, 8, true, false ); + expected = 0.474407196044921875; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 6, 8, true, false ); + expected = 0.080212593078613281250; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 12, 1, true, false ); + expected = 5.96046447753906250e-8; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( 0.25, 1, 8, true, false ); + expected = 0.899887084960937500; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +// Bug cases from Rocco Romeo + +// Source: https://raw.githubusercontent.com/boostorg/math/e1bdcad01783fe8d285c363c948b47173846e734/test/test_ibeta.hpp +tape( 'the function handles extreme x values (Rocco Romeo bug cases)', opts, function test( t ) { + // These test extreme x values near powers of 2 + var expected; + var val; + var x0; + + x0 = ldexp( 1.0, -52 ); + val = kernelBetainc( x0, 2, 24, false, false ); + expected=2.46519032881565349871772482100516780410072110983579277754743e-32; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 2 ), true, 'returns expected value' ); + + val = kernelBetainc( x0, 2, 24, true, false ); + expected=1.47911419728939209923063489260310068246043266590147566652846e-29; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + x0 = ldexp( 1.0, -270 ); + val = kernelBetainc( x0, 3, 2, false, false ); + expected=4.88182556606650701438035298707052523938789614661168065734809e-245; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + val = kernelBetainc( x0, 3, 2, true, false ); + expected=5.85819067927980841725642358448463028726547537593401678881771e-244; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + x0 = ldexp( 1.0, -373 ); + val = kernelBetainc( x0, 2, 31, false, false ); + expected=1.35080680244581673116149460571129957689952846520037541640260e-225; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 12 ), true, 'returns expected value' ); + + val = kernelBetainc( x0, 2, 31, true, false ); + expected=1.34000034802625019731220264886560918028433223747877241307138e-222; + t.strictEqual( isAlmostSameValue( val[ 0 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the correct derivative for a naive analytical check', opts, function test( t ) { + var expected; + var val; + + val = kernelBetainc( 0.5, 2, 3, true, false ); + expected = 1.5; + t.strictEqual( isAlmostSameValue( val[ 1 ], expected, 1 ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function handles tiny parameter values', opts, function test( t ) { + var small; + var tiny; + var val; + + tiny = SMALLEST_NORMAL / 2.0; + small = EPS; + if ( tiny !== 0.0 ) { + val = kernelBetainc( small, tiny, small, true, false ); + t.strictEqual( val[ 0 ], 1.0, 'ibeta(tiny, eps, eps) = 1 where tiny = smallest_normal/2' ); + } + + val = kernelBetainc( 0.0, 2, 1, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'return expected lower regularized value.' ); + + val = kernelBetainc( 0.0, 1, 2, true, false ); + t.strictEqual( val[ 0 ], 0.0, 'return expected lower regularized value.' ); + + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for small a,b in [0,10]', opts, function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.lower_regularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 26 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for small a,b in [0,10]', opts, function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.upper_regularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 28 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for small a,b in [0,10]', opts, function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.lower_unregularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 48 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for small a,b in [0,10]', opts, function test( t ) { + var expected; + var sv; + var sa; + var sb; + var i; + var y; + + expected = smallRange.upper_unregularized; + sv = smallRange.x; + sa = smallRange.a; + sb = smallRange.b; + for ( i = 0; i < sv.length; i++ ) { + y = kernelBetainc( sv[i], sa[i], sb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 40 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for medium a,b in [0,100]', opts, function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.lower_regularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 226 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for medium a,b in [0,100]', opts, function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.upper_regularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 231 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for medium a,b in [0,100]', opts, function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.lower_unregularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 319 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for medium a,b in [0,100]', opts, function test( t ) { + var expected; + var mv; + var ma; + var mb; + var i; + var y; + + expected = mediumRange.upper_unregularized; + mv = mediumRange.x; + ma = mediumRange.a; + mb = mediumRange.b; + for ( i = 0; i < mv.length; i++ ) { + y = kernelBetainc( mv[i], ma[i], mb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 332 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for large range a,b in [1e-5,1e6]', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.lower_regularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 2897 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for large range a,b in [1e-5,1e6]', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.upper_regularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 11049 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for large range a,b in [1e-5,1e6]', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.lower_unregularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 2699 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for large range a,b in [1e-5,1e6]', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeRange.upper_unregularized; + lv = largeRange.x; + la = largeRange.a; + lb = largeRange.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 814 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for integer a,b in {1,5,9,...,37}', opts, function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.lower_regularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 15 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for integer a,b in {1,5,9,...,37}', opts, function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.upper_regularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 28 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for integer a,b in {1,5,9,...,37}', opts, function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.lower_unregularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 122 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for integer a,b in {1,5,9,...,37}', opts, function test( t ) { + var expected; + var iv; + var ia; + var ib; + var i; + var y; + + expected = intValues.upper_unregularized; + iv = intValues.x; + ia = intValues.a; + ib = intValues.b; + for ( i = 0; i < iv.length; i++ ) { + y = kernelBetainc( iv[i], ia[i], ib[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 117 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for x near the distribution mean a/(a+b)', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.lower_regularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1178059 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for x near the distribution mean a/(a+b)', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.upper_regularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1164470 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for x near the distribution mean a/(a+b)', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.lower_unregularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 26397 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for x near the distribution mean a/(a+b)', opts, function test( t ) { + var expected; + var lv; + var la; + var lb; + var i; + var y; + + expected = largeAsym.upper_unregularized; + lv = largeAsym.x; + la = largeAsym.a; + lb = largeAsym.b; + for ( i = 0; i < lv.length; i++ ) { + y = kernelBetainc( lv[i], la[i], lb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 26399 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower regularized incomplete beta function for asymptotically large a,b values', opts, function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.lower_regularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], true, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 13539863633 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper regularized incomplete beta function for asymptotically large a,b values', opts, function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.upper_regularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], true, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 15990448265 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the lower unregularized incomplete beta function for asymptotically large a,b values', opts, function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.lower_unregularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], false, false )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function evaluates the upper unregularized incomplete beta function for asymptotically large a,b values', opts, function test( t ) { + var expected; + var vv; + var va; + var vb; + var i; + var y; + + expected = veryLargeAsym.upper_unregularized; + vv = veryLargeAsym.x; + va = veryLargeAsym.a; + vb = veryLargeAsym.b; + for ( i = 0; i < vv.length; i++ ) { + y = kernelBetainc( vv[i], va[i], vb[i], false, true )[0]; + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +// Source: https://github.com/boostorg/math/blob/e1bdcad01783fe8d285c363c948b47173846e734/test/test_ibeta.hpp +tape( 'ibeta is monotonically increasing for large a,b near the median', opts, function test( t ) { + var deltas; + var above0; + var above1; + var below0; + var below1; + var x0; + var a; + var b; + var i; + + a = 10000000272564224; + b = 9965820922822656; + x0 = a / ( a + b ); + deltas = [ 0, 1e-15, 1e-14, 1e-13, 1e-12, 1e-11, 1e-10 ]; + + for ( i = 1; i < 6; i++ ) { + above1 = kernelBetainc( x0 + deltas[ i+1 ], a, b, true, false )[ 0 ]; + above0 = kernelBetainc( x0 + deltas[ i ], a, b, true, false )[ 0 ]; + t.ok( above1 > above0, 'ibeta monotonically increasing above a/(a+b) for delta=' + deltas[ i ] ); + + below0 = kernelBetainc( x0 - deltas[ i ], a, b, true, false )[ 0 ]; + below1 = kernelBetainc( x0 - deltas[ i+1 ], a, b, true, false )[ 0 ]; + t.ok( below0 > below1, 'ibeta monotonically increasing below a/(a+b) for delta=' + deltas[ i ] ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/kronecker-delta/manifest.json b/lib/node_modules/@stdlib/math/base/special/kronecker-delta/manifest.json index 229e194f54da..c0c31c9ecebf 100644 --- a/lib/node_modules/@stdlib/math/base/special/kronecker-delta/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/kronecker-delta/manifest.json @@ -39,7 +39,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ ], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ ], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/kronecker-delta/src/main.c b/lib/node_modules/@stdlib/math/base/special/kronecker-delta/src/main.c index 058383c53839..5e3a5d71a1dd 100644 --- a/lib/node_modules/@stdlib/math/base/special/kronecker-delta/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/kronecker-delta/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/kronecker_delta.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" /** @@ -36,7 +37,7 @@ */ double stdlib_base_kronecker_delta( const double i, const double j ) { if ( stdlib_base_is_nan( i ) || stdlib_base_is_nan( j ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( i == j ) { return 1.0; diff --git a/lib/node_modules/@stdlib/math/base/special/ln/manifest.json b/lib/node_modules/@stdlib/math/base/special/ln/manifest.json index dcc9a2c1a87c..dcce5827f12c 100644 --- a/lib/node_modules/@stdlib/math/base/special/ln/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/ln/manifest.json @@ -43,7 +43,8 @@ "@stdlib/number/float64/base/set-high-word", "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/ninf", - "@stdlib/constants/float64/exponent-bias" + "@stdlib/constants/float64/exponent-bias", + "@stdlib/constants/float64/nan" ] }, { @@ -62,7 +63,8 @@ "@stdlib/number/float64/base/set-high-word", "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/ninf", - "@stdlib/constants/float64/exponent-bias" + "@stdlib/constants/float64/exponent-bias", + "@stdlib/constants/float64/nan" ] }, { @@ -81,7 +83,8 @@ "@stdlib/number/float64/base/set-high-word", "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/ninf", - "@stdlib/constants/float64/exponent-bias" + "@stdlib/constants/float64/exponent-bias", + "@stdlib/constants/float64/nan" ] }, { @@ -100,7 +103,8 @@ "@stdlib/number/float64/base/set-high-word", "@stdlib/math/base/assert/is-nan", "@stdlib/constants/float64/ninf", - "@stdlib/constants/float64/exponent-bias" + "@stdlib/constants/float64/exponent-bias", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/ln/src/main.c b/lib/node_modules/@stdlib/math/base/special/ln/src/main.c index b6a79245ca29..4e7160503c14 100644 --- a/lib/node_modules/@stdlib/math/base/special/ln/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/ln/src/main.c @@ -35,6 +35,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/constants/float64/ninf.h" #include "stdlib/constants/float64/exponent_bias.h" +#include "stdlib/constants/float64/nan.h" #include static const double LN2_HI = 6.93147180369123816490e-01; // 3FE62E42 FEE00000 @@ -127,7 +128,7 @@ double stdlib_base_ln( const double x ) { return STDLIB_CONSTANT_FLOAT64_NINF; } if ( stdlib_base_is_nan( x ) || x < 0.0 ) { - return 0.0/0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } stdlib_base_float64_get_high_word( x, &hx ); xc = x; diff --git a/lib/node_modules/@stdlib/math/base/special/log10/manifest.json b/lib/node_modules/@stdlib/math/base/special/log10/manifest.json index 216b8572261b..389a6f904dc3 100644 --- a/lib/node_modules/@stdlib/math/base/special/log10/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/log10/manifest.json @@ -46,7 +46,8 @@ "@stdlib/constants/float64/high-word-significand-mask", "@stdlib/number/float64/base/set-low-word", "@stdlib/math/base/special/kernel-log1p", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -69,7 +70,8 @@ "@stdlib/constants/float64/high-word-significand-mask", "@stdlib/number/float64/base/set-low-word", "@stdlib/math/base/special/kernel-log1p", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -92,7 +94,8 @@ "@stdlib/constants/float64/high-word-significand-mask", "@stdlib/number/float64/base/set-low-word", "@stdlib/math/base/special/kernel-log1p", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/log10/src/main.c b/lib/node_modules/@stdlib/math/base/special/log10/src/main.c index 90eab78cc4b3..8cb0267618be 100644 --- a/lib/node_modules/@stdlib/math/base/special/log10/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/log10/src/main.c @@ -39,6 +39,7 @@ #include "stdlib/constants/float64/high_word_significand_mask.h" #include "stdlib/constants/float64/exponent_bias.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/kernel_log1p.h" #include @@ -87,7 +88,7 @@ double stdlib_base_log10( const double x ) { double y; if ( stdlib_base_is_nan( x ) || x < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } xc = x; stdlib_base_float64_to_words( xc, &hx, &lx ); diff --git a/lib/node_modules/@stdlib/math/base/special/log1mexp/manifest.json b/lib/node_modules/@stdlib/math/base/special/log1mexp/manifest.json index b3cdf711a48d..2ca746256090 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1mexp/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/log1mexp/manifest.json @@ -44,7 +44,8 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/constants/float64/ln-two", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/constants/float64/ln-two", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", "@stdlib/constants/float64/ln-two", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/log1mexp/src/main.c b/lib/node_modules/@stdlib/math/base/special/log1mexp/src/main.c index 73630ddeb972..92fc023557d0 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1mexp/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/log1mexp/src/main.c @@ -25,6 +25,7 @@ #include "stdlib/math/base/special/abs.h" #include "stdlib/constants/float64/ninf.h" #include "stdlib/constants/float64/ln_two.h" +#include "stdlib/constants/float64/nan.h" /** * Computes the natural logarithm of \\( 1-\exp(-|x|) \\). @@ -39,7 +40,7 @@ double stdlib_base_log1mexp( const double x ) { double ax; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 0.0 ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/log1p/manifest.json b/lib/node_modules/@stdlib/math/base/special/log1p/manifest.json index 56c3a1ee7c44..00c00499553f 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1p/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/log1p/manifest.json @@ -42,7 +42,8 @@ "@stdlib/number/float64/base/set-high-word", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/exponent-bias" + "@stdlib/constants/float64/exponent-bias", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/number/float64/base/set-high-word", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/exponent-bias" + "@stdlib/constants/float64/exponent-bias", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/number/float64/base/set-high-word", "@stdlib/constants/float64/ninf", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/exponent-bias" + "@stdlib/constants/float64/exponent-bias", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/log1p/src/main.c b/lib/node_modules/@stdlib/math/base/special/log1p/src/main.c index 52229e3256d9..628bba9e30c3 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1p/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/log1p/src/main.c @@ -37,6 +37,7 @@ #include "stdlib/constants/float64/ninf.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/exponent_bias.h" +#include "stdlib/constants/float64/nan.h" #include // High and low words of ln(2): @@ -246,7 +247,7 @@ double stdlib_base_log1p( const double x ) { double u; if ( x < -1.0 || stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == -1.0 ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/log1pexp/manifest.json b/lib/node_modules/@stdlib/math/base/special/log1pexp/manifest.json index f02c16b65121..8c5d0c43ea83 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1pexp/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/log1pexp/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/exp", - "@stdlib/math/base/special/log1p" + "@stdlib/math/base/special/log1p", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/exp", - "@stdlib/math/base/special/log1p" + "@stdlib/math/base/special/log1p", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/exp", - "@stdlib/math/base/special/log1p" + "@stdlib/math/base/special/log1p", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/log1pexp/src/main.c b/lib/node_modules/@stdlib/math/base/special/log1pexp/src/main.c index f28a49d1b48b..c2ace388ee8d 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1pexp/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/log1pexp/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/log1pexp.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/log1p.h" #include "stdlib/math/base/special/exp.h" @@ -33,7 +34,7 @@ */ double stdlib_base_log1pexp( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x <= -37.0 ) { return stdlib_base_exp( x ); diff --git a/lib/node_modules/@stdlib/math/base/special/log1pmx/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/special/log1pmx/benchmark/benchmark.native.js new file mode 100644 index 000000000000..6e03910b64ba --- /dev/null +++ b/lib/node_modules/@stdlib/math/base/special/log1pmx/benchmark/benchmark.native.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var log1pmx = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( log1pmx instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var x; + var y; + var i; + + x = uniform( 100, -1.0, 99.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = log1pmx( x[ i%x.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/math/base/special/log1pmx/manifest.json b/lib/node_modules/@stdlib/math/base/special/log1pmx/manifest.json index f3b4915499df..9349edb6f63f 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1pmx/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/log1pmx/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/special/log1p", "@stdlib/math/base/special/ln", "@stdlib/math/base/special/abs", - "@stdlib/constants/float64/eps" + "@stdlib/constants/float64/eps", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/log1pmx/src/main.c b/lib/node_modules/@stdlib/math/base/special/log1pmx/src/main.c index 19402e19967d..7e2c3bcc4f01 100644 --- a/lib/node_modules/@stdlib/math/base/special/log1pmx/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/log1pmx/src/main.c @@ -34,6 +34,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/math/base/special/abs.h" #include "stdlib/constants/float64/eps.h" +#include "stdlib/constants/float64/nan.h" /** * Evaluates \\( \operatorname{log1pmx}(x) = \ln(1+x) - x \\). @@ -48,7 +49,7 @@ double stdlib_base_log1pmx( const double x ) { double ax; if ( x <= -1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } ax = stdlib_base_abs( x ); if ( ax > 0.95 ) { diff --git a/lib/node_modules/@stdlib/math/base/special/log2/manifest.json b/lib/node_modules/@stdlib/math/base/special/log2/manifest.json index 9a4bec85ced9..080336fadb79 100644 --- a/lib/node_modules/@stdlib/math/base/special/log2/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/log2/manifest.json @@ -46,7 +46,8 @@ "@stdlib/constants/float64/high-word-significand-mask", "@stdlib/constants/float64/exponent-bias", "@stdlib/constants/float64/ninf", - "@stdlib/math/base/special/kernel-log1p" + "@stdlib/math/base/special/kernel-log1p", + "@stdlib/constants/float64/nan" ] }, { @@ -69,7 +70,8 @@ "@stdlib/constants/float64/high-word-significand-mask", "@stdlib/constants/float64/exponent-bias", "@stdlib/constants/float64/ninf", - "@stdlib/math/base/special/kernel-log1p" + "@stdlib/math/base/special/kernel-log1p", + "@stdlib/constants/float64/nan" ] }, { @@ -92,7 +94,8 @@ "@stdlib/constants/float64/high-word-significand-mask", "@stdlib/constants/float64/exponent-bias", "@stdlib/constants/float64/ninf", - "@stdlib/math/base/special/kernel-log1p" + "@stdlib/math/base/special/kernel-log1p", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/log2/src/main.c b/lib/node_modules/@stdlib/math/base/special/log2/src/main.c index e5d0bc22f126..94a3a18f264c 100644 --- a/lib/node_modules/@stdlib/math/base/special/log2/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/log2/src/main.c @@ -26,6 +26,7 @@ #include "stdlib/constants/float64/high_word_significand_mask.h" #include "stdlib/constants/float64/exponent_bias.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/kernel_log1p.h" #include @@ -66,7 +67,7 @@ double stdlib_base_log2( const double x ) { double y; if ( stdlib_base_is_nan( x ) || x < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } xc = x; stdlib_base_float64_to_words( xc, &hx, &lx ); diff --git a/lib/node_modules/@stdlib/math/base/special/logaddexp/manifest.json b/lib/node_modules/@stdlib/math/base/special/logaddexp/manifest.json index af940f4cc361..721390e55803 100644 --- a/lib/node_modules/@stdlib/math/base/special/logaddexp/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/logaddexp/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/exp", "@stdlib/math/base/special/log1p", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/exp", "@stdlib/math/base/special/log1p", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/exp", "@stdlib/math/base/special/log1p", - "@stdlib/constants/float64/ln-two" + "@stdlib/constants/float64/ln-two", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/logaddexp/src/main.c b/lib/node_modules/@stdlib/math/base/special/logaddexp/src/main.c index 26f4c74634f0..95e969884262 100644 --- a/lib/node_modules/@stdlib/math/base/special/logaddexp/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/logaddexp/src/main.c @@ -21,6 +21,7 @@ #include "stdlib/math/base/special/exp.h" #include "stdlib/math/base/special/log1p.h" #include "stdlib/constants/float64/ln_two.h" +#include "stdlib/constants/float64/nan.h" /** * Computes the natural logarithm of `exp(x) + exp(y)`. @@ -36,7 +37,7 @@ double stdlib_base_logaddexp( const double x, const double y ) { double d; if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - return 0.0/0.0; + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == y ) { return x + STDLIB_CONSTANT_FLOAT64_LN2; diff --git a/lib/node_modules/@stdlib/math/base/special/logit/manifest.json b/lib/node_modules/@stdlib/math/base/special/logit/manifest.json index cf06f99f7f90..5ec1766c77c7 100644 --- a/lib/node_modules/@stdlib/math/base/special/logit/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/logit/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-probability", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-probability", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-probability", "@stdlib/constants/float64/pinf", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/logit/src/main.c b/lib/node_modules/@stdlib/math/base/special/logit/src/main.c index 5f61a89c3a4f..965f4ae00384 100644 --- a/lib/node_modules/@stdlib/math/base/special/logit/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/logit/src/main.c @@ -22,6 +22,7 @@ #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/pinf.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" /** * Evaluates the logit function. @@ -35,10 +36,10 @@ */ double stdlib_base_logit( const double p ) { if ( stdlib_base_is_nan( p ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( !stdlib_base_is_probability( p ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( p == 0.0 ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/lucas/manifest.json b/lib/node_modules/@stdlib/math/base/special/lucas/manifest.json index a3c987779807..1586292f3c0a 100644 --- a/lib/node_modules/@stdlib/math/base/special/lucas/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/lucas/manifest.json @@ -38,7 +38,8 @@ "dependencies": [ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-nonnegative-integer", - "@stdlib/constants/float64/max-safe-nth-lucas" + "@stdlib/constants/float64/max-safe-nth-lucas", + "@stdlib/constants/float64/nan" ] }, { @@ -53,7 +54,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nonnegative-integer", - "@stdlib/constants/float64/max-safe-nth-lucas" + "@stdlib/constants/float64/max-safe-nth-lucas", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +70,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nonnegative-integer", - "@stdlib/constants/float64/max-safe-nth-lucas" + "@stdlib/constants/float64/max-safe-nth-lucas", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/lucas/src/main.c b/lib/node_modules/@stdlib/math/base/special/lucas/src/main.c index 6547f3ed652b..d0db07be42e2 100644 --- a/lib/node_modules/@stdlib/math/base/special/lucas/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/lucas/src/main.c @@ -19,6 +19,7 @@ #include "stdlib/math/base/special/lucas.h" #include "stdlib/math/base/assert/is_nonnegative_integer.h" #include "stdlib/constants/float64/max_safe_nth_lucas.h" +#include "stdlib/constants/float64/nan.h" #include #include @@ -118,7 +119,7 @@ static const int64_t lucas_value[ 77 ] = { */ double stdlib_base_lucas( const double n ) { if ( !stdlib_base_is_nonnegative_integer( n ) || n > STDLIB_CONSTANT_FLOAT64_MAX_SAFE_NTH_LUCAS ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return lucas_value[ (size_t)n ]; } diff --git a/lib/node_modules/@stdlib/math/base/special/max/manifest.json b/lib/node_modules/@stdlib/math/base/special/max/manifest.json index 97a89b1debb4..2268662da987 100644 --- a/lib/node_modules/@stdlib/math/base/special/max/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/max/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/binary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-positive-zero", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-positive-zero", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-positive-zero", - "@stdlib/constants/float64/pinf" + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/max/src/main.c b/lib/node_modules/@stdlib/math/base/special/max/src/main.c index 4170028e3031..3eea3c2a9492 100644 --- a/lib/node_modules/@stdlib/math/base/special/max/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/max/src/main.c @@ -20,6 +20,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_positive_zero.h" #include "stdlib/constants/float64/pinf.h" +#include "stdlib/constants/float64/nan.h" /** * Returns the maximum value. @@ -38,7 +39,7 @@ */ double stdlib_base_max( const double x, const double y ) { if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == STDLIB_CONSTANT_FLOAT64_PINF || y == STDLIB_CONSTANT_FLOAT64_PINF ) { return STDLIB_CONSTANT_FLOAT64_PINF; diff --git a/lib/node_modules/@stdlib/math/base/special/min/manifest.json b/lib/node_modules/@stdlib/math/base/special/min/manifest.json index 324b6bdf5b9e..fd591e64230d 100644 --- a/lib/node_modules/@stdlib/math/base/special/min/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/min/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/binary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-negative-zero", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-negative-zero", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-negative-zero", - "@stdlib/constants/float64/ninf" + "@stdlib/constants/float64/ninf", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/min/src/main.c b/lib/node_modules/@stdlib/math/base/special/min/src/main.c index 392f7118dce9..4e3801208bab 100644 --- a/lib/node_modules/@stdlib/math/base/special/min/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/min/src/main.c @@ -20,6 +20,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_negative_zero.h" #include "stdlib/constants/float64/ninf.h" +#include "stdlib/constants/float64/nan.h" /** * Return the minimum value. @@ -38,7 +39,7 @@ */ double stdlib_base_min( const double x, const double y ) { if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == STDLIB_CONSTANT_FLOAT64_NINF || y == STDLIB_CONSTANT_FLOAT64_NINF ) { return STDLIB_CONSTANT_FLOAT64_NINF; diff --git a/lib/node_modules/@stdlib/math/base/special/minmax/manifest.json b/lib/node_modules/@stdlib/math/base/special/minmax/manifest.json index 502beab58f74..2636631021c9 100644 --- a/lib/node_modules/@stdlib/math/base/special/minmax/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/minmax/manifest.json @@ -41,7 +41,8 @@ "@stdlib/napi/argv-float64array", "@stdlib/napi/export", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -56,7 +57,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/minmax/src/main.c b/lib/node_modules/@stdlib/math/base/special/minmax/src/main.c index d710b31d4433..3c59e30e6911 100644 --- a/lib/node_modules/@stdlib/math/base/special/minmax/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/minmax/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/minmax.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_negative_zero.h" @@ -38,8 +39,8 @@ */ void stdlib_base_minmax( const double x, const double y, double* min, double* max ) { if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - *min = 0.0 / 0.0; // NaN - *max = 0.0 / 0.0; // NaN + *min = STDLIB_CONSTANT_FLOAT64_NAN; + *max = STDLIB_CONSTANT_FLOAT64_NAN; return; } if ( x == y && x == 0.0 ) { diff --git a/lib/node_modules/@stdlib/math/base/special/minmaxabs/manifest.json b/lib/node_modules/@stdlib/math/base/special/minmaxabs/manifest.json index 34d444f96a5c..d9ffce8425c4 100644 --- a/lib/node_modules/@stdlib/math/base/special/minmaxabs/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/minmaxabs/manifest.json @@ -41,7 +41,8 @@ "@stdlib/napi/argv-float64array", "@stdlib/napi/export", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/abs" + "@stdlib/math/base/special/abs", + "@stdlib/constants/float64/nan" ] }, { @@ -56,7 +57,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/abs" + "@stdlib/math/base/special/abs", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/abs" + "@stdlib/math/base/special/abs", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/minmaxabs/src/main.c b/lib/node_modules/@stdlib/math/base/special/minmaxabs/src/main.c index d915de16dad9..d6505689ddd2 100644 --- a/lib/node_modules/@stdlib/math/base/special/minmaxabs/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/minmaxabs/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/minmaxabs.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/abs.h" #include "stdlib/math/base/assert/is_nan.h" @@ -41,8 +42,8 @@ void stdlib_base_minmaxabs( const double x, const double y, double* min, double* double ay; if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - *min = 0.0 / 0.0; // NaN - *max = 0.0 / 0.0; // NaN + *min = STDLIB_CONSTANT_FLOAT64_NAN; + *max = STDLIB_CONSTANT_FLOAT64_NAN; return; } ax = stdlib_base_abs( x ); diff --git a/lib/node_modules/@stdlib/math/base/special/modf/manifest.json b/lib/node_modules/@stdlib/math/base/special/modf/manifest.json index 13505de9a57a..ae9d854fab6e 100644 --- a/lib/node_modules/@stdlib/math/base/special/modf/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/modf/manifest.json @@ -47,7 +47,8 @@ "@stdlib/constants/float64/exponent-bias", "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/constants/float64/high-word-significand-mask", - "@stdlib/constants/float64/num-high-word-significand-bits" + "@stdlib/constants/float64/num-high-word-significand-bits", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +69,8 @@ "@stdlib/constants/float64/exponent-bias", "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/constants/float64/high-word-significand-mask", - "@stdlib/constants/float64/num-high-word-significand-bits" + "@stdlib/constants/float64/num-high-word-significand-bits", + "@stdlib/constants/float64/nan" ] }, { @@ -89,7 +91,8 @@ "@stdlib/constants/float64/exponent-bias", "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/constants/float64/high-word-significand-mask", - "@stdlib/constants/float64/num-high-word-significand-bits" + "@stdlib/constants/float64/num-high-word-significand-bits", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/modf/src/main.c b/lib/node_modules/@stdlib/math/base/special/modf/src/main.c index 887504904eb3..55bc775e2780 100644 --- a/lib/node_modules/@stdlib/math/base/special/modf/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/modf/src/main.c @@ -25,6 +25,7 @@ #include "stdlib/constants/float64/high_word_exponent_mask.h" #include "stdlib/constants/float64/high_word_significand_mask.h" #include "stdlib/constants/float64/num_high_word_significand_bits.h" +#include "stdlib/constants/float64/nan.h" // 4294967295 => 0xffffffff => 11111111111111111111111111111111 static const uint32_t ALL_ONES = 4294967295; @@ -68,8 +69,8 @@ void stdlib_base_modf( const double x, double* integral, double* frac ) { return; } if ( stdlib_base_is_nan( x ) ) { - *integral = 0.0 / 0.0; // NaN - *frac = 0.0 / 0.0; // NaN + *integral = STDLIB_CONSTANT_FLOAT64_NAN; + *frac = STDLIB_CONSTANT_FLOAT64_NAN; return; } if ( x == STDLIB_CONSTANT_FLOAT64_PINF ) { diff --git a/lib/node_modules/@stdlib/math/base/special/nanmax/manifest.json b/lib/node_modules/@stdlib/math/base/special/nanmax/manifest.json index 3fdb96f82040..d4b238c916ac 100644 --- a/lib/node_modules/@stdlib/math/base/special/nanmax/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/nanmax/manifest.json @@ -38,7 +38,8 @@ "dependencies": [ "@stdlib/math/base/napi/binary", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/max" + "@stdlib/math/base/special/max", + "@stdlib/constants/float64/nan" ] }, { @@ -53,7 +54,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/max" + "@stdlib/math/base/special/max", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +70,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/max" + "@stdlib/math/base/special/max", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/nanmax/src/main.c b/lib/node_modules/@stdlib/math/base/special/nanmax/src/main.c index d6df587063ed..8fd0ef236f84 100644 --- a/lib/node_modules/@stdlib/math/base/special/nanmax/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/nanmax/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/nanmax.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/max.h" @@ -37,7 +38,7 @@ */ double stdlib_base_nanmax( const double x, const double y ) { if ( stdlib_base_is_nan( x ) ) { - return stdlib_base_is_nan( y ) ? 0.0 / 0.0 : y; + return stdlib_base_is_nan( y ) ? STDLIB_CONSTANT_FLOAT64_NAN : y; } return stdlib_base_is_nan( y ) ? x : stdlib_base_max( x, y ); } diff --git a/lib/node_modules/@stdlib/math/base/special/nanmin/manifest.json b/lib/node_modules/@stdlib/math/base/special/nanmin/manifest.json index ff2b442ff555..cb3d93b9e709 100644 --- a/lib/node_modules/@stdlib/math/base/special/nanmin/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/nanmin/manifest.json @@ -38,7 +38,8 @@ "dependencies": [ "@stdlib/math/base/napi/binary", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/min" + "@stdlib/math/base/special/min", + "@stdlib/constants/float64/nan" ] }, { @@ -53,7 +54,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/min" + "@stdlib/math/base/special/min", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +70,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/special/min" + "@stdlib/math/base/special/min", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/nanmin/src/main.c b/lib/node_modules/@stdlib/math/base/special/nanmin/src/main.c index c125e56af7c7..e12ff9bd723c 100644 --- a/lib/node_modules/@stdlib/math/base/special/nanmin/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/nanmin/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/nanmin.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/min.h" @@ -37,7 +38,7 @@ */ double stdlib_base_nanmin( const double x, const double y ) { if ( stdlib_base_is_nan( x ) ) { - return stdlib_base_is_nan( y ) ? 0.0 / 0.0 : y; + return stdlib_base_is_nan( y ) ? STDLIB_CONSTANT_FLOAT64_NAN : y; } return stdlib_base_is_nan( y ) ? x : stdlib_base_min( x, y ); } diff --git a/lib/node_modules/@stdlib/math/base/special/negafibonacci/manifest.json b/lib/node_modules/@stdlib/math/base/special/negafibonacci/manifest.json index 7bf1d197acf5..7780854a71ad 100644 --- a/lib/node_modules/@stdlib/math/base/special/negafibonacci/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/negafibonacci/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/constants/float64/max-safe-nth-fibonacci", "@stdlib/math/base/special/abs", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/constants/float64/max-safe-nth-fibonacci", "@stdlib/math/base/special/abs", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/constants/float64/max-safe-nth-fibonacci", "@stdlib/math/base/special/abs", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/negafibonacci/src/main.c b/lib/node_modules/@stdlib/math/base/special/negafibonacci/src/main.c index c64339966b34..d67fe22402ea 100644 --- a/lib/node_modules/@stdlib/math/base/special/negafibonacci/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/negafibonacci/src/main.c @@ -20,6 +20,7 @@ #include "stdlib/math/base/assert/is_integer.h" #include "stdlib/math/base/special/abs.h" #include "stdlib/constants/float64/max_safe_nth_fibonacci.h" +#include "stdlib/constants/float64/nan.h" #include static const double negafibonacci_value[ 79 ] = { @@ -117,11 +118,11 @@ static const double negafibonacci_value[ 79 ] = { double stdlib_base_negafibonacci( const double n ) { double an; if ( !stdlib_base_is_integer( n ) || n > 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } an = stdlib_base_abs( n ); if ( an > STDLIB_CONSTANT_FLOAT64_MAX_SAFE_NTH_FIBONACCI ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return negafibonacci_value[ (size_t)an ]; } diff --git a/lib/node_modules/@stdlib/math/base/special/negalucas/manifest.json b/lib/node_modules/@stdlib/math/base/special/negalucas/manifest.json index 3476ff893e32..8a5c3ecd13ca 100644 --- a/lib/node_modules/@stdlib/math/base/special/negalucas/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/negalucas/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/math/base/special/abs", "@stdlib/constants/float64/max-safe-nth-lucas", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/max-safe-nth-lucas", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/special/abs", "@stdlib/constants/float64/max-safe-nth-lucas", - "@stdlib/math/base/assert/is-integer" + "@stdlib/math/base/assert/is-integer", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/negalucas/src/main.c b/lib/node_modules/@stdlib/math/base/special/negalucas/src/main.c index 7099a731b6fe..4b659f2f7527 100644 --- a/lib/node_modules/@stdlib/math/base/special/negalucas/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/negalucas/src/main.c @@ -20,6 +20,7 @@ #include "stdlib/math/base/assert/is_integer.h" #include "stdlib/math/base/special/abs.h" #include "stdlib/constants/float64/max_safe_nth_lucas.h" +#include "stdlib/constants/float64/nan.h" #include #include @@ -120,7 +121,7 @@ static const int64_t negalucas_value[ 77 ] = { double stdlib_base_negalucas( const double n ) { double an = stdlib_base_abs( n ); if ( !stdlib_base_is_integer( n ) || n > 0.0 || an > STDLIB_CONSTANT_FLOAT64_MAX_SAFE_NTH_LUCAS ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return negalucas_value[ (size_t)an ]; } diff --git a/lib/node_modules/@stdlib/math/base/special/pdiff/manifest.json b/lib/node_modules/@stdlib/math/base/special/pdiff/manifest.json index 80656ac17472..a8cc72f1d15c 100644 --- a/lib/node_modules/@stdlib/math/base/special/pdiff/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/pdiff/manifest.json @@ -37,7 +37,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/binary", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -51,7 +52,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +67,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/pdiff/src/main.c b/lib/node_modules/@stdlib/math/base/special/pdiff/src/main.c index e25a50eea24b..d3b6fe3b271a 100644 --- a/lib/node_modules/@stdlib/math/base/special/pdiff/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/pdiff/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/pdiff.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" /** @@ -36,7 +37,7 @@ */ double stdlib_base_pdiff( const double x, const double y ) { if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x > y ) { return x - y; diff --git a/lib/node_modules/@stdlib/math/base/special/pow/manifest.json b/lib/node_modules/@stdlib/math/base/special/pow/manifest.json index 317d41fb746c..2df287eab1b0 100644 --- a/lib/node_modules/@stdlib/math/base/special/pow/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/pow/manifest.json @@ -55,7 +55,8 @@ "@stdlib/math/base/assert/is-integer", "@stdlib/math/base/special/sqrt", "@stdlib/number/float64/base/to-words", - "@stdlib/constants/float64/num-high-word-significand-bits" + "@stdlib/constants/float64/num-high-word-significand-bits", + "@stdlib/constants/float64/nan" ] }, { @@ -87,7 +88,8 @@ "@stdlib/math/base/assert/is-integer", "@stdlib/math/base/special/sqrt", "@stdlib/number/float64/base/to-words", - "@stdlib/constants/float64/num-high-word-significand-bits" + "@stdlib/constants/float64/num-high-word-significand-bits", + "@stdlib/constants/float64/nan" ] }, { @@ -119,7 +121,8 @@ "@stdlib/math/base/assert/is-integer", "@stdlib/math/base/special/sqrt", "@stdlib/number/float64/base/to-words", - "@stdlib/constants/float64/num-high-word-significand-bits" + "@stdlib/constants/float64/num-high-word-significand-bits", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/pow/src/main.c b/lib/node_modules/@stdlib/math/base/special/pow/src/main.c index ed38e0727570..b6a131f614fa 100644 --- a/lib/node_modules/@stdlib/math/base/special/pow/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/pow/src/main.c @@ -44,6 +44,7 @@ #include "stdlib/constants/float64/ln_two.h" #include "stdlib/constants/float64/exponent_bias.h" #include "stdlib/constants/float64/high_word_significand_mask.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/assert/is_integer.h" @@ -209,7 +210,7 @@ static double polyval_p( const double x ) { */ static double y_is_infinite( const double x, const double y ) { if ( x == -1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 1.0 ) { return 1.0; @@ -569,7 +570,7 @@ double stdlib_base_pow( const double x, const double y ) { xc = x; if ( stdlib_base_is_nan( xc ) || stdlib_base_is_nan( y ) ) { - return 0.0/0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Split `y` into high and low words: @@ -639,7 +640,7 @@ double stdlib_base_pow( const double x, const double y ) { stdlib_base_is_integer( y ) == false ) { // Signal NaN... - return 0.0/0.0; + return STDLIB_CONSTANT_FLOAT64_NAN; } ax = stdlib_base_abs( x ); diff --git a/lib/node_modules/@stdlib/math/base/special/powm1/manifest.json b/lib/node_modules/@stdlib/math/base/special/powm1/manifest.json index 4ad8fead0be1..6fc74537356f 100644 --- a/lib/node_modules/@stdlib/math/base/special/powm1/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/powm1/manifest.json @@ -44,8 +44,8 @@ "@stdlib/math/base/special/trunc", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/special/fmod" - + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] }, { @@ -66,7 +66,8 @@ "@stdlib/math/base/special/trunc", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] }, { @@ -87,7 +88,8 @@ "@stdlib/math/base/special/trunc", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/powm1/src/main.c b/lib/node_modules/@stdlib/math/base/special/powm1/src/main.c index eeb8ded80052..dc05d6bb306f 100644 --- a/lib/node_modules/@stdlib/math/base/special/powm1/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/powm1/src/main.c @@ -30,6 +30,7 @@ */ #include "stdlib/math/base/special/powm1.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/abs.h" #include "stdlib/math/base/special/expm1.h" #include "stdlib/math/base/special/ln.h" @@ -60,7 +61,7 @@ double stdlib_base_powm1( const double b, const double x ) { double y; if ( stdlib_base_is_nan( b ) || stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 0.0 ) { // Any number raised to zero (including 0) is always 1 => b^0 - 1 = 0 @@ -85,11 +86,11 @@ double stdlib_base_powm1( const double b, const double x ) { } } else if ( stdlib_base_trunc( x ) != x ) { // Exponentiation would yield a complex result... - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } result = stdlib_base_pow( bc, x ) - 1.0; if ( stdlib_base_is_infinite( result ) || stdlib_base_is_nan( result ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return result; } diff --git a/lib/node_modules/@stdlib/math/base/special/ramp/manifest.json b/lib/node_modules/@stdlib/math/base/special/ramp/manifest.json index ca59ad02f8c0..0f7e320c5fba 100644 --- a/lib/node_modules/@stdlib/math/base/special/ramp/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/ramp/manifest.json @@ -37,7 +37,8 @@ "libpath": [], "dependencies": [ "@stdlib/math/base/napi/unary", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -51,7 +52,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +67,8 @@ "libraries": [], "libpath": [], "dependencies": [ - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/ramp/src/main.c b/lib/node_modules/@stdlib/math/base/special/ramp/src/main.c index c757c3c4296d..5692eb1ad749 100644 --- a/lib/node_modules/@stdlib/math/base/special/ramp/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/ramp/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/ramp.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" /** @@ -35,7 +36,7 @@ */ double stdlib_base_ramp( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x > 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/rempio2/manifest.json b/lib/node_modules/@stdlib/math/base/special/rempio2/manifest.json index 69ce750a6ce5..e7b56622452f 100644 --- a/lib/node_modules/@stdlib/math/base/special/rempio2/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/rempio2/manifest.json @@ -49,7 +49,8 @@ "@stdlib/number/float64/base/from-words", "@stdlib/constants/float64/high-word-abs-mask", "@stdlib/constants/float64/high-word-exponent-mask", - "@stdlib/constants/float64/high-word-significand-mask" + "@stdlib/constants/float64/high-word-significand-mask", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +72,8 @@ "@stdlib/number/float64/base/from-words", "@stdlib/constants/float64/high-word-abs-mask", "@stdlib/constants/float64/high-word-exponent-mask", - "@stdlib/constants/float64/high-word-significand-mask" + "@stdlib/constants/float64/high-word-significand-mask", + "@stdlib/constants/float64/nan" ] }, { @@ -93,7 +95,8 @@ "@stdlib/number/float64/base/from-words", "@stdlib/constants/float64/high-word-abs-mask", "@stdlib/constants/float64/high-word-exponent-mask", - "@stdlib/constants/float64/high-word-significand-mask" + "@stdlib/constants/float64/high-word-significand-mask", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/rempio2/src/main.c b/lib/node_modules/@stdlib/math/base/special/rempio2/src/main.c index 0384913710a3..f0a1d33b557e 100644 --- a/lib/node_modules/@stdlib/math/base/special/rempio2/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/rempio2/src/main.c @@ -40,6 +40,7 @@ #include "stdlib/constants/float64/high_word_abs_mask.h" #include "stdlib/constants/float64/high_word_exponent_mask.h" #include "stdlib/constants/float64/high_word_significand_mask.h" +#include "stdlib/constants/float64/nan.h" #include static const double ZERO = 0.00000000000000000000e+00; // 0x00000000, 0x00000000 @@ -595,8 +596,8 @@ int32_t stdlib_base_rempio2( const double x, double *rem1, double *rem2 ) { } // Case: x is NaN or infinity if( ix >= STDLIB_CONSTANT_FLOAT64_HIGH_WORD_EXPONENT_MASK ) { - *rem1 = 0.0 / 0.0; // NaN - *rem2 = 0.0 / 0.0; // NaN + *rem1 = STDLIB_CONSTANT_FLOAT64_NAN; + *rem2 = STDLIB_CONSTANT_FLOAT64_NAN; return 0; } // Set z = scalbn(|x|, ilogb(x)-23)... diff --git a/lib/node_modules/@stdlib/math/base/special/rempio2f/manifest.json b/lib/node_modules/@stdlib/math/base/special/rempio2f/manifest.json index c9316fb43303..92bcea4acd07 100644 --- a/lib/node_modules/@stdlib/math/base/special/rempio2f/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/rempio2f/manifest.json @@ -47,7 +47,8 @@ "@stdlib/number/float32/base/from-word", "@stdlib/number/float32/base/to-word", "@stdlib/constants/float32/abs-mask", - "@stdlib/constants/float32/exponent-mask" + "@stdlib/constants/float32/exponent-mask", + "@stdlib/constants/float64/nan" ] }, { @@ -67,7 +68,8 @@ "@stdlib/number/float32/base/from-word", "@stdlib/number/float32/base/to-word", "@stdlib/constants/float32/abs-mask", - "@stdlib/constants/float32/exponent-mask" + "@stdlib/constants/float32/exponent-mask", + "@stdlib/constants/float64/nan" ] }, { @@ -87,7 +89,8 @@ "@stdlib/number/float32/base/from-word", "@stdlib/number/float32/base/to-word", "@stdlib/constants/float32/abs-mask", - "@stdlib/constants/float32/exponent-mask" + "@stdlib/constants/float32/exponent-mask", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/rempio2f/src/main.c b/lib/node_modules/@stdlib/math/base/special/rempio2f/src/main.c index 6b6cd893dab5..604f9a0f5d8b 100644 --- a/lib/node_modules/@stdlib/math/base/special/rempio2f/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/rempio2f/src/main.c @@ -38,6 +38,7 @@ #include "stdlib/number/float32/base/to_word.h" #include "stdlib/constants/float32/abs_mask.h" #include "stdlib/constants/float32/exponent_mask.h" +#include "stdlib/constants/float64/nan.h" #include static const double ZERO = 0.00000000000000000000e+00; // 0x00000000, 0x00000000 @@ -421,7 +422,7 @@ int32_t stdlib_base_rempio2f( const float x, double *rem ) { } // Case: x is NaN or infinity if( ix >= STDLIB_CONSTANT_FLOAT32_EXPONENT_MASK ) { - *rem = 0.0 / 0.0; // NaN + *rem = STDLIB_CONSTANT_FLOAT64_NAN; return 0; } // Set z = scalbn(|x|, ilogb(|x|)-23)... diff --git a/lib/node_modules/@stdlib/math/base/special/riemann-zeta/manifest.json b/lib/node_modules/@stdlib/math/base/special/riemann-zeta/manifest.json index e9f8bb305808..bd59301693cc 100644 --- a/lib/node_modules/@stdlib/math/base/special/riemann-zeta/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/riemann-zeta/manifest.json @@ -53,7 +53,8 @@ "@stdlib/constants/float64/two-pi", "@stdlib/constants/float64/sqrt-eps", "@stdlib/constants/float64/ln-sqrt-two-pi", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -83,7 +84,8 @@ "@stdlib/constants/float64/two-pi", "@stdlib/constants/float64/sqrt-eps", "@stdlib/constants/float64/ln-sqrt-two-pi", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -113,7 +115,8 @@ "@stdlib/constants/float64/two-pi", "@stdlib/constants/float64/sqrt-eps", "@stdlib/constants/float64/ln-sqrt-two-pi", - "@stdlib/constants/float64/max-nth-factorial" + "@stdlib/constants/float64/max-nth-factorial", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/riemann-zeta/src/main.c b/lib/node_modules/@stdlib/math/base/special/riemann-zeta/src/main.c index 4da9c0c153f1..2b03eaf1e9df 100644 --- a/lib/node_modules/@stdlib/math/base/special/riemann-zeta/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/riemann-zeta/src/main.c @@ -47,6 +47,7 @@ #include "stdlib/constants/float64/sqrt_eps.h" #include "stdlib/constants/float64/ln_sqrt_two_pi.h" #include "stdlib/constants/float64/max_nth_factorial.h" +#include "stdlib/constants/float64/nan.h" #include static const int32_t MAX_BERNOULLI_2N = 129; @@ -708,12 +709,12 @@ double stdlib_base_zeta( const double s ) { // Check for `NaN`: if ( stdlib_base_is_nan( s ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Check for a pole: if ( s == 1.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Check for large value: diff --git a/lib/node_modules/@stdlib/math/base/special/rising-factorial/manifest.json b/lib/node_modules/@stdlib/math/base/special/rising-factorial/manifest.json index 4565d1b7156a..88105a60308e 100644 --- a/lib/node_modules/@stdlib/math/base/special/rising-factorial/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/rising-factorial/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/binary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/gamma-delta-ratio", - "@stdlib/math/base/special/falling-factorial" + "@stdlib/math/base/special/falling-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/gamma-delta-ratio", - "@stdlib/math/base/special/falling-factorial" + "@stdlib/math/base/special/falling-factorial", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/gamma-delta-ratio", - "@stdlib/math/base/special/falling-factorial" + "@stdlib/math/base/special/falling-factorial", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/rising-factorial/src/main.c b/lib/node_modules/@stdlib/math/base/special/rising-factorial/src/main.c index fccd379e2b33..89ce0fb35061 100644 --- a/lib/node_modules/@stdlib/math/base/special/rising-factorial/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/rising-factorial/src/main.c @@ -31,6 +31,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/gamma_delta_ratio.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/falling_factorial.h" #include #include @@ -67,7 +68,7 @@ double stdlib_base_rising_factorial( const double x, const int32_t n ) { bool inv; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } nc = n; xc = x; diff --git a/lib/node_modules/@stdlib/math/base/special/round/manifest.json b/lib/node_modules/@stdlib/math/base/special/round/manifest.json index d52c3d1ec2b0..dca1a08f300c 100644 --- a/lib/node_modules/@stdlib/math/base/special/round/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/round/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/math/base/special/floor", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -58,7 +59,8 @@ "dependencies": [ "@stdlib/math/base/special/floor", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -75,7 +77,8 @@ "dependencies": [ "@stdlib/math/base/special/floor", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -92,7 +95,8 @@ "dependencies": [ "@stdlib/math/base/special/floor", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/round/src/main.c b/lib/node_modules/@stdlib/math/base/special/round/src/main.c index 9137b8be571c..55978a243c59 100644 --- a/lib/node_modules/@stdlib/math/base/special/round/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/round/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/round.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/floor.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_negative_zero.h" @@ -33,7 +34,7 @@ */ double stdlib_base_round( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0/0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_negative_zero( x ) || ( x >= -0.5 && x < 0.0 ) ) { return -0.0; // -0 diff --git a/lib/node_modules/@stdlib/math/base/special/roundb/manifest.json b/lib/node_modules/@stdlib/math/base/special/roundb/manifest.json index 261497985ece..8984397bd316 100644 --- a/lib/node_modules/@stdlib/math/base/special/roundb/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/roundb/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/round", "@stdlib/math/base/special/roundn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/round", "@stdlib/math/base/special/roundn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/round", "@stdlib/math/base/special/roundn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/roundb/src/main.c b/lib/node_modules/@stdlib/math/base/special/roundb/src/main.c index e36234c1c3fd..5d184ca487a3 100644 --- a/lib/node_modules/@stdlib/math/base/special/roundb/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/roundb/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/roundb.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/round.h" @@ -41,7 +42,7 @@ double stdlib_base_roundb( const double x, const int32_t n, const int32_t b ) { double s; if ( stdlib_base_is_nan( x ) || b <= 0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/roundn/manifest.json b/lib/node_modules/@stdlib/math/base/special/roundn/manifest.json index 68abf0bebf73..94ed0dd9eee7 100644 --- a/lib/node_modules/@stdlib/math/base/special/roundn/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/roundn/manifest.json @@ -47,7 +47,8 @@ "@stdlib/constants/float64/min-base10-exponent", "@stdlib/constants/float64/min-base10-exponent-subnormal", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +72,8 @@ "@stdlib/constants/float64/min-base10-exponent", "@stdlib/constants/float64/min-base10-exponent-subnormal", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -95,7 +97,8 @@ "@stdlib/constants/float64/min-base10-exponent", "@stdlib/constants/float64/min-base10-exponent-subnormal", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/roundn/src/main.c b/lib/node_modules/@stdlib/math/base/special/roundn/src/main.c index 4b1ff1255a2e..ae55806f8631 100644 --- a/lib/node_modules/@stdlib/math/base/special/roundn/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/roundn/src/main.c @@ -26,6 +26,7 @@ #include "stdlib/constants/float64/max_base10_exponent.h" #include "stdlib/constants/float64/min_base10_exponent.h" #include "stdlib/constants/float64/min_base10_exponent_subnormal.h" +#include "stdlib/constants/float64/nan.h" #include static const double MAX_INT = STDLIB_CONSTANT_FLOAT64_MAX_SAFE_INTEGER + 1.0; @@ -117,7 +118,7 @@ double stdlib_base_roundn( const double x, const int32_t n ) { double y; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( diff --git a/lib/node_modules/@stdlib/math/base/special/roundsd/manifest.json b/lib/node_modules/@stdlib/math/base/special/roundsd/manifest.json index c87297416f66..fd1aefae39b4 100644 --- a/lib/node_modules/@stdlib/math/base/special/roundsd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/roundsd/manifest.json @@ -47,7 +47,8 @@ "@stdlib/number/float64/base/exponent", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/round", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +72,8 @@ "@stdlib/number/float64/base/exponent", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/round", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -95,7 +97,8 @@ "@stdlib/number/float64/base/exponent", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/round", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/roundsd/src/main.c b/lib/node_modules/@stdlib/math/base/special/roundsd/src/main.c index e707479166be..d65c1f61e4d0 100644 --- a/lib/node_modules/@stdlib/math/base/special/roundsd/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/roundsd/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/roundsd.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/pow.h" #include "stdlib/math/base/assert/is_infinite.h" @@ -46,7 +47,7 @@ double stdlib_base_roundsd( const double x, const int32_t n, const int32_t b ) { double y; if ( stdlib_base_is_nan( x ) || n < 1 ) { - return 0.0/0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/sin/manifest.json b/lib/node_modules/@stdlib/math/base/special/sin/manifest.json index a5286e487f73..4fef571f3983 100644 --- a/lib/node_modules/@stdlib/math/base/special/sin/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/sin/manifest.json @@ -44,7 +44,8 @@ "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/kernel-sin", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/kernel-sin", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/kernel-sin", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/sin/src/main.c b/lib/node_modules/@stdlib/math/base/special/sin/src/main.c index 252f144057a7..e0b1507dec04 100644 --- a/lib/node_modules/@stdlib/math/base/special/sin/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/sin/src/main.c @@ -34,6 +34,7 @@ #include "stdlib/number/float64/base/get_high_word.h" #include "stdlib/constants/float64/high_word_abs_mask.h" #include "stdlib/constants/float64/high_word_exponent_mask.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/kernel_cos.h" #include "stdlib/math/base/special/kernel_sin.h" #include "stdlib/math/base/special/rempio2.h" @@ -90,7 +91,7 @@ double stdlib_base_sin( const double x ) { } // Case: x is NaN or infinity if ( ix >= STDLIB_CONSTANT_FLOAT64_HIGH_WORD_EXPONENT_MASK ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Argument reduction... n = stdlib_base_rempio2( x, &Y[ 0 ], &Y[ 1 ] ); diff --git a/lib/node_modules/@stdlib/math/base/special/sin/test/test.js b/lib/node_modules/@stdlib/math/base/special/sin/test/test.js index 15116b5bce9b..297ff2c50f8e 100644 --- a/lib/node_modules/@stdlib/math/base/special/sin/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/sin/test/test.js @@ -24,8 +24,7 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); var sin = require( './../lib' ); @@ -51,8 +50,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function computes the sine (medium negative values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -62,21 +59,13 @@ tape( 'the function computes the sine (medium negative values)', function test( for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (medium positive values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -86,21 +75,13 @@ tape( 'the function computes the sine (medium positive values)', function test( for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (large negative values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -110,21 +91,13 @@ tape( 'the function computes the sine (large negative values)', function test( t for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (large positive values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -134,21 +107,13 @@ tape( 'the function computes the sine (large positive values)', function test( t for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (huge negative values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -158,21 +123,13 @@ tape( 'the function computes the sine (huge negative values)', function test( t for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (huge positive values)', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -182,13 +139,7 @@ tape( 'the function computes the sine (huge positive values)', function test( t for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/sin/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/sin/test/test.native.js index a7501ea2db11..eced01919522 100644 --- a/lib/node_modules/@stdlib/math/base/special/sin/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/sin/test/test.native.js @@ -25,8 +25,7 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -60,8 +59,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function computes the sine (medium negative values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -71,21 +68,13 @@ tape( 'the function computes the sine (medium negative values)', opts, function for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (medium positive values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -95,21 +84,13 @@ tape( 'the function computes the sine (medium positive values)', opts, function for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (large negative values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -119,21 +100,13 @@ tape( 'the function computes the sine (large negative values)', opts, function t for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (large positive values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -143,21 +116,13 @@ tape( 'the function computes the sine (large positive values)', opts, function t for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (huge negative values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -167,21 +132,13 @@ tape( 'the function computes the sine (huge negative values)', opts, function te for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); tape( 'the function computes the sine (huge positive values)', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -191,13 +148,7 @@ tape( 'the function computes the sine (huge positive values)', opts, function te for ( i = 0; i < x.length; i++ ) { y = sin( x[ i ] ); - if ( y === expected[ i ] ) { - t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. Expected: '+expected[i] ); - } else { - delta = abs( y - expected[ i ] ); - tol = EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/math/base/special/sinc/manifest.json b/lib/node_modules/@stdlib/math/base/special/sinc/manifest.json index 0b6c07c7669e..90bec0abd21e 100644 --- a/lib/node_modules/@stdlib/math/base/special/sinc/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/sinc/manifest.json @@ -42,7 +42,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", "@stdlib/constants/float64/pi", - "@stdlib/math/base/special/sinpi" + "@stdlib/math/base/special/sinpi", + "@stdlib/constants/float64/nan" ] }, { @@ -61,7 +62,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", "@stdlib/constants/float64/pi", - "@stdlib/math/base/special/sinpi" + "@stdlib/math/base/special/sinpi", + "@stdlib/constants/float64/nan" ] }, { @@ -80,7 +82,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/assert/is-infinite", "@stdlib/constants/float64/pi", - "@stdlib/math/base/special/sinpi" + "@stdlib/math/base/special/sinpi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/sinc/src/main.c b/lib/node_modules/@stdlib/math/base/special/sinc/src/main.c index b1ecc5dcfdf9..1564586fe24c 100644 --- a/lib/node_modules/@stdlib/math/base/special/sinc/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/sinc/src/main.c @@ -21,6 +21,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/constants/float64/pi.h" +#include "stdlib/constants/float64/nan.h" /** * Computes the normalized cardinal sine of a number. @@ -53,7 +54,7 @@ */ double stdlib_base_sinc( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) ) { return 0.0; diff --git a/lib/node_modules/@stdlib/math/base/special/sincos/manifest.json b/lib/node_modules/@stdlib/math/base/special/sincos/manifest.json index 45918c065001..e3ea1d4c0be3 100644 --- a/lib/node_modules/@stdlib/math/base/special/sincos/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/sincos/manifest.json @@ -43,7 +43,8 @@ "@stdlib/math/base/special/rempio2", "@stdlib/number/float64/base/get-high-word", "@stdlib/constants/float64/high-word-exponent-mask", - "@stdlib/constants/float64/high-word-abs-mask" + "@stdlib/constants/float64/high-word-abs-mask", + "@stdlib/constants/float64/nan" ] }, { @@ -60,7 +61,8 @@ "@stdlib/math/base/special/rempio2", "@stdlib/number/float64/base/get-high-word", "@stdlib/constants/float64/high-word-exponent-mask", - "@stdlib/constants/float64/high-word-abs-mask" + "@stdlib/constants/float64/high-word-abs-mask", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/special/rempio2", "@stdlib/number/float64/base/get-high-word", "@stdlib/constants/float64/high-word-exponent-mask", - "@stdlib/constants/float64/high-word-abs-mask" + "@stdlib/constants/float64/high-word-abs-mask", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/sincos/src/main.c b/lib/node_modules/@stdlib/math/base/special/sincos/src/main.c index 3f38a29043dc..f8df71456e3b 100644 --- a/lib/node_modules/@stdlib/math/base/special/sincos/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/sincos/src/main.c @@ -19,6 +19,7 @@ #include "stdlib/math/base/special/sincos.h" #include "stdlib/constants/float64/high_word_abs_mask.h" #include "stdlib/constants/float64/high_word_exponent_mask.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/number/float64/base/get_high_word.h" #include "stdlib/math/base/special/rempio2.h" #include @@ -131,8 +132,8 @@ void stdlib_base_sincos( const double x, double* sine, double* cosine ) { // Case: x is NaN or infinity if ( ix >= STDLIB_CONSTANT_FLOAT64_HIGH_WORD_EXPONENT_MASK ) { - *sine = 0.0 / 0.0; // NaN - *cosine = 0.0 / 0.0; // NaN + *sine = STDLIB_CONSTANT_FLOAT64_NAN; + *cosine = STDLIB_CONSTANT_FLOAT64_NAN; return; } diff --git a/lib/node_modules/@stdlib/math/base/special/sincospi/manifest.json b/lib/node_modules/@stdlib/math/base/special/sincospi/manifest.json index 04df8f3d8103..f858caf61b9a 100644 --- a/lib/node_modules/@stdlib/math/base/special/sincospi/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/sincospi/manifest.json @@ -47,7 +47,8 @@ "@stdlib/math/base/special/fmod", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -68,7 +69,8 @@ "@stdlib/math/base/special/fmod", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -89,7 +91,8 @@ "@stdlib/math/base/special/fmod", "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/assert/is-nan", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/sincospi/src/main.c b/lib/node_modules/@stdlib/math/base/special/sincospi/src/main.c index fd8be3d48632..7f0fec5ca892 100644 --- a/lib/node_modules/@stdlib/math/base/special/sincospi/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/sincospi/src/main.c @@ -25,6 +25,7 @@ #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/constants/float64/pi.h" +#include "stdlib/constants/float64/nan.h" /** * Simultaneously computes the sine and cosine of a number times π. @@ -47,8 +48,8 @@ void stdlib_base_sincospi( const double x, double* sine, double* cosine ) { double r; if ( stdlib_base_is_nan( x ) || stdlib_base_is_infinite( x ) ) { - *sine = 0.0 / 0.0; // NaN - *cosine = 0.0 / 0.0; // NaN + *sine = STDLIB_CONSTANT_FLOAT64_NAN; + *cosine = STDLIB_CONSTANT_FLOAT64_NAN; return; } r = stdlib_base_fmod( x, 2.0 ); diff --git a/lib/node_modules/@stdlib/math/base/special/sind/manifest.json b/lib/node_modules/@stdlib/math/base/special/sind/manifest.json index 01aba340dce1..2cfd06d9d874 100644 --- a/lib/node_modules/@stdlib/math/base/special/sind/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/sind/manifest.json @@ -44,7 +44,8 @@ "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/signum", "@stdlib/math/base/special/abs", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] }, { @@ -65,7 +66,8 @@ "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/signum", "@stdlib/math/base/special/abs", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] }, { @@ -86,7 +88,8 @@ "@stdlib/math/base/special/kernel-cos", "@stdlib/math/base/special/signum", "@stdlib/math/base/special/abs", - "@stdlib/math/base/special/fmod" + "@stdlib/math/base/special/fmod", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/sind/src/main.c b/lib/node_modules/@stdlib/math/base/special/sind/src/main.c index d7be9229ac5a..39f62c1c8da9 100644 --- a/lib/node_modules/@stdlib/math/base/special/sind/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/sind/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/sind.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/kernel_sin.h" #include "stdlib/math/base/special/kernel_cos.h" #include "stdlib/math/base/special/deg2rad.h" @@ -41,7 +42,7 @@ double stdlib_base_sind( const double x ) { double rx; if ( stdlib_base_is_infinite( x ) || stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } rx = stdlib_base_fmod( x, 360.0 ); diff --git a/lib/node_modules/@stdlib/math/base/special/sind/test/test.js b/lib/node_modules/@stdlib/math/base/special/sind/test/test.js index ea718133edd2..ba716aeb20d6 100644 --- a/lib/node_modules/@stdlib/math/base/special/sind/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/sind/test/test.js @@ -21,13 +21,12 @@ // MODULES // var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); -var NINF = require( '@stdlib/constants/float64/ninf' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sind = require( './../lib' ); @@ -53,11 +52,9 @@ tape( 'if provided a `NaN`, the function returns `NaN`', function test( t ) { tape( 'the function computes the sine of an angle measured in degrees (negative values)', function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = negative.x; expected = negative.expected; @@ -67,9 +64,7 @@ tape( 'the function computes the sine of an angle measured in degrees (negative if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } } t.end(); @@ -77,11 +72,9 @@ tape( 'the function computes the sine of an angle measured in degrees (negative tape( 'the function computes the sine of an angle measured in degrees (positive values)', function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = positive.x; expected = positive.expected; @@ -91,9 +84,7 @@ tape( 'the function computes the sine of an angle measured in degrees (positive if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/sind/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/sind/test/test.native.js index 0415d184824e..ca1892826644 100644 --- a/lib/node_modules/@stdlib/math/base/special/sind/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/sind/test/test.native.js @@ -22,13 +22,12 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); -var NINF = require( '@stdlib/constants/float64/ninf' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -62,11 +61,9 @@ tape( 'if provided a `NaN`, the function returns `NaN`', opts, function test( t tape( 'the function computes the sine of an angle measured in degrees (negative values)', opts, function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = negative.x; expected = negative.expected; @@ -76,9 +73,7 @@ tape( 'the function computes the sine of an angle measured in degrees (negative if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } } t.end(); @@ -86,11 +81,9 @@ tape( 'the function computes the sine of an angle measured in degrees (negative tape( 'the function computes the sine of an angle measured in degrees (positive values)', opts, function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = positive.x; expected = positive.expected; @@ -100,9 +93,7 @@ tape( 'the function computes the sine of an angle measured in degrees (positive if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/sinpi/manifest.json b/lib/node_modules/@stdlib/math/base/special/sinpi/manifest.json index af9eaa3ea92d..7ffeb9195092 100644 --- a/lib/node_modules/@stdlib/math/base/special/sinpi/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/sinpi/manifest.json @@ -46,7 +46,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/copysign", "@stdlib/math/base/special/fmod", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -69,7 +70,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/copysign", "@stdlib/math/base/special/fmod", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] }, { @@ -92,7 +94,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/copysign", "@stdlib/math/base/special/fmod", - "@stdlib/constants/float64/pi" + "@stdlib/constants/float64/pi", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/sinpi/src/main.c b/lib/node_modules/@stdlib/math/base/special/sinpi/src/main.c index 4267f2b1722e..71a04bbd7cf6 100644 --- a/lib/node_modules/@stdlib/math/base/special/sinpi/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/sinpi/src/main.c @@ -25,6 +25,7 @@ #include "stdlib/math/base/special/copysign.h" #include "stdlib/math/base/special/fmod.h" #include "stdlib/constants/float64/pi.h" +#include "stdlib/constants/float64/nan.h" /** * Computes the value of `sin(πx)`. @@ -47,7 +48,7 @@ double stdlib_base_sinpi( const double x ) { double ar; double r; if ( stdlib_base_is_nan( x ) || stdlib_base_is_infinite( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Argument reduction (reduce to [0,2))... diff --git a/lib/node_modules/@stdlib/math/base/special/spence/manifest.json b/lib/node_modules/@stdlib/math/base/special/spence/manifest.json index 502ee8833533..b12eb457cca7 100644 --- a/lib/node_modules/@stdlib/math/base/special/spence/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/spence/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/pi-squared" + "@stdlib/constants/float64/pi-squared", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/pi-squared" + "@stdlib/constants/float64/pi-squared", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/ln", - "@stdlib/constants/float64/pi-squared" + "@stdlib/constants/float64/pi-squared", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/spence/src/main.c b/lib/node_modules/@stdlib/math/base/special/spence/src/main.c index 7b30a150ff28..fe1de1556b40 100644 --- a/lib/node_modules/@stdlib/math/base/special/spence/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/spence/src/main.c @@ -34,6 +34,7 @@ #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/ln.h" #include "stdlib/constants/float64/pi_squared.h" +#include "stdlib/constants/float64/nan.h" #include // π^2 / 6 @@ -114,7 +115,7 @@ double stdlib_base_spence( const double x ) { double z; if ( stdlib_base_is_nan( x ) || x < 0.0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( x == 1.0 ) { return 0.0; diff --git a/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/manifest.json b/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/manifest.json index ea66b59bf9ad..841491d585b9 100644 --- a/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/special/abs" + "@stdlib/math/base/special/abs", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/special/abs" + "@stdlib/math/base/special/abs", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/sqrt", "@stdlib/math/base/special/log1p", - "@stdlib/math/base/special/abs" + "@stdlib/math/base/special/abs", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/src/main.c b/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/src/main.c index ee91d95abb8d..3eb8174bcbb5 100644 --- a/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/sqrt1pm1/src/main.c @@ -30,6 +30,7 @@ */ #include "stdlib/math/base/special/sqrt1pm1.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/expm1.h" #include "stdlib/math/base/special/log1p.h" @@ -48,7 +49,7 @@ */ double stdlib_base_sqrt1pm1( const double x ) { if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_abs( x ) > 0.75 ) { return stdlib_base_sqrt( 1.0 + x ) - 1.0; diff --git a/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.js b/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.js index 1d5ac950ef04..0407fa0a4f0c 100644 --- a/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.js @@ -21,13 +21,12 @@ // MODULES // var tape = require( 'tape' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var abs = require( '@stdlib/math/base/special/abs' ); var sqrtpi = require( './../lib' ); @@ -53,8 +52,6 @@ tape( 'main export is a function', function test( t ) { tape( 'the function evaluates the principal square root when `x` is on the interval `[50,500]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -66,9 +63,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -76,8 +71,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is on the interval `[20,50]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -89,9 +82,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -99,8 +90,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is on the interval `[3,20]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -112,9 +101,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -122,8 +109,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is on the interval `[0.8,3]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -135,9 +120,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -145,8 +128,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates principal square root when `x` is on the interval `[0.0,0.8]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -158,9 +139,7 @@ tape( 'the function evaluates principal square root when `x` is on the interval if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -168,8 +147,6 @@ tape( 'the function evaluates principal square root when `x` is on the interval tape( 'the function evaluates the principal square root when `x` is on the interval `[1e-300,1e-308]`', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -181,9 +158,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -191,8 +166,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is subnormal', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -204,9 +177,7 @@ tape( 'the function evaluates the principal square root when `x` is subnormal', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -214,8 +185,6 @@ tape( 'the function evaluates the principal square root when `x` is subnormal', tape( 'the function evaluates the principal square root for huge positive numbers', function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -227,9 +196,7 @@ tape( 'the function evaluates the principal square root for huge positive number if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.native.js index 8c390c0cc9db..deeb8e611a22 100644 --- a/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/sqrtpi/test/test.native.js @@ -22,14 +22,13 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var tryRequire = require( '@stdlib/utils/try-require' ); -var abs = require( '@stdlib/math/base/special/abs' ); // FIXTURES // @@ -62,8 +61,6 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function evaluates the principal square root when `x` is on the interval `[50,500]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -75,9 +72,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -85,8 +80,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is on the interval `[20,50]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -98,9 +91,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -108,8 +99,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is on the interval `[3,20]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -121,9 +110,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -131,8 +118,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is on the interval `[0.8,3]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -144,9 +129,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -154,8 +137,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates principal square root when `x` is on the interval `[0.0,0.8]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -167,9 +148,7 @@ tape( 'the function evaluates principal square root when `x` is on the interval if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -177,8 +156,6 @@ tape( 'the function evaluates principal square root when `x` is on the interval tape( 'the function evaluates the principal square root when `x` is on the interval `[1e-300,1e-308]`', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -190,9 +167,7 @@ tape( 'the function evaluates the principal square root when `x` is on the inter if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -200,8 +175,6 @@ tape( 'the function evaluates the principal square root when `x` is on the inter tape( 'the function evaluates the principal square root when `x` is subnormal', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -213,9 +186,7 @@ tape( 'the function evaluates the principal square root when `x` is subnormal', if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); @@ -223,8 +194,6 @@ tape( 'the function evaluates the principal square root when `x` is subnormal', tape( 'the function evaluates the principal square root for huge positive numbers', opts, function test( t ) { var expected; - var delta; - var tol; var x; var y; var i; @@ -236,9 +205,7 @@ tape( 'the function evaluates the principal square root for huge positive number if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/tan/manifest.json b/lib/node_modules/@stdlib/math/base/special/tan/manifest.json index 047d2921f19c..035939f0712e 100644 --- a/lib/node_modules/@stdlib/math/base/special/tan/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/tan/manifest.json @@ -43,7 +43,8 @@ "@stdlib/constants/float64/high-word-abs-mask", "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-tan", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] }, { @@ -63,7 +64,8 @@ "@stdlib/constants/float64/high-word-abs-mask", "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-tan", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] }, { @@ -83,7 +85,8 @@ "@stdlib/constants/float64/high-word-abs-mask", "@stdlib/constants/float64/high-word-exponent-mask", "@stdlib/math/base/special/kernel-tan", - "@stdlib/math/base/special/rempio2" + "@stdlib/math/base/special/rempio2", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/tan/src/main.c b/lib/node_modules/@stdlib/math/base/special/tan/src/main.c index 2851c48042ea..e8b8475d06de 100644 --- a/lib/node_modules/@stdlib/math/base/special/tan/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/tan/src/main.c @@ -34,6 +34,7 @@ #include "stdlib/number/float64/base/get_high_word.h" #include "stdlib/constants/float64/high_word_abs_mask.h" #include "stdlib/constants/float64/high_word_exponent_mask.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/special/kernel_tan.h" #include "stdlib/math/base/special/rempio2.h" #include @@ -89,7 +90,7 @@ double stdlib_base_tan( const double x ) { } // Case: tan(Inf or NaN) is NaN if ( ix >= STDLIB_CONSTANT_FLOAT64_HIGH_WORD_EXPONENT_MASK ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } // Argument reduction... n = stdlib_base_rempio2( x, &Y[ 0 ], &Y[ 1 ] ); diff --git a/lib/node_modules/@stdlib/math/base/special/tand/test/test.js b/lib/node_modules/@stdlib/math/base/special/tand/test/test.js index d9e578cdf64e..f2607274ff39 100644 --- a/lib/node_modules/@stdlib/math/base/special/tand/test/test.js +++ b/lib/node_modules/@stdlib/math/base/special/tand/test/test.js @@ -21,13 +21,12 @@ // MODULES // var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); -var NINF = require( '@stdlib/constants/float64/ninf' ); -var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); +var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tand = require( './../lib' ); @@ -47,11 +46,9 @@ tape( 'main export is a function', function test( t ) { tape( 'the function computes the tangent of an angle measured in degrees (negative values)', function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = negative.x; expected = negative.expected; @@ -61,9 +58,7 @@ tape( 'the function computes the tangent of an angle measured in degrees (negati if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = 2.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 3 ), true, 'returns expected value' ); } } t.end(); @@ -71,11 +66,9 @@ tape( 'the function computes the tangent of an angle measured in degrees (negati tape( 'the function computes the tangent of an angle measured in degrees (positive values)', function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = positive.x; expected = positive.expected; @@ -85,9 +78,7 @@ tape( 'the function computes the tangent of an angle measured in degrees (positi if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = 2.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 3 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/tand/test/test.native.js b/lib/node_modules/@stdlib/math/base/special/tand/test/test.native.js index 861d1b109b32..5fb6233dfe61 100644 --- a/lib/node_modules/@stdlib/math/base/special/tand/test/test.native.js +++ b/lib/node_modules/@stdlib/math/base/special/tand/test/test.native.js @@ -22,13 +22,12 @@ var resolve = require( 'path' ).resolve; var tape = require( 'tape' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); -var EPS = require( '@stdlib/constants/float64/eps' ); -var PINF = require( '@stdlib/constants/float64/pinf' ); -var NINF = require( '@stdlib/constants/float64/ninf' ); -var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var isNegativeZero = require( '@stdlib/assert/is-negative-zero' ); +var isPositiveZero = require( '@stdlib/assert/is-positive-zero' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var tryRequire = require( '@stdlib/utils/try-require' ); @@ -56,11 +55,9 @@ tape( 'main export is a function', opts, function test( t ) { tape( 'the function computes the tangent of an angle measured in degrees (negative values)', opts, function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = negative.x; expected = negative.expected; @@ -70,9 +67,7 @@ tape( 'the function computes the tangent of an angle measured in degrees (negati if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = 2.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 3 ), true, 'returns expected value' ); } } t.end(); @@ -80,11 +75,9 @@ tape( 'the function computes the tangent of an angle measured in degrees (negati tape( 'the function computes the tangent of an angle measured in degrees (positive values)', opts, function test( t ) { var expected; - var delta; - var tol; + var i; var x; var y; - var i; x = positive.x; expected = positive.expected; @@ -94,9 +87,7 @@ tape( 'the function computes the tangent of an angle measured in degrees (positi if ( y === expected[ i ] ) { t.strictEqual( y, expected[ i ], 'x: '+x[i]+'. E: '+expected[i] ); } else { - delta = abs( y - expected[i] ); - tol = 2.0 * EPS * abs( expected[i] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[i]+'. y: '+y+'. E: '+expected[i]+'. tol: '+tol+'. Δ: '+delta+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[ i ], 3 ), true, 'returns expected value' ); } } t.end(); diff --git a/lib/node_modules/@stdlib/math/base/special/tribonacci/manifest.json b/lib/node_modules/@stdlib/math/base/special/tribonacci/manifest.json index f4cbee083620..a28af94964e4 100644 --- a/lib/node_modules/@stdlib/math/base/special/tribonacci/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/tribonacci/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/constants/float64/max-safe-nth-tribonacci", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-nonnegative-integer" + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/constants/float64/max-safe-nth-tribonacci", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-nonnegative-integer" + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/constants/float64/max-safe-nth-tribonacci", "@stdlib/math/base/assert/is-nan", - "@stdlib/math/base/assert/is-nonnegative-integer" + "@stdlib/math/base/assert/is-nonnegative-integer", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/tribonacci/src/main.c b/lib/node_modules/@stdlib/math/base/special/tribonacci/src/main.c index e62283fba283..11760080470f 100644 --- a/lib/node_modules/@stdlib/math/base/special/tribonacci/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/tribonacci/src/main.c @@ -18,6 +18,7 @@ #include "stdlib/math/base/special/tribonacci.h" #include "stdlib/constants/float64/max_safe_nth_tribonacci.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nonnegative_integer.h" #include "stdlib/math/base/assert/is_nan.h" #include @@ -102,7 +103,7 @@ static const int64_t tribonacci_value[ 64 ] = { */ double stdlib_base_tribonacci( const double n ) { if ( stdlib_base_is_nan( n ) || !stdlib_base_is_nonnegative_integer( n ) || n > STDLIB_CONSTANT_FLOAT64_MAX_SAFE_NTH_TRIBONACCI ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } return tribonacci_value[ (size_t)n ]; } diff --git a/lib/node_modules/@stdlib/math/base/special/trigamma/manifest.json b/lib/node_modules/@stdlib/math/base/special/trigamma/manifest.json index e0983f2170a0..91b106b80d49 100644 --- a/lib/node_modules/@stdlib/math/base/special/trigamma/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/trigamma/manifest.json @@ -39,7 +39,8 @@ "@stdlib/math/base/napi/unary", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/sinpi", - "@stdlib/constants/float64/pi-squared" + "@stdlib/constants/float64/pi-squared", + "@stdlib/constants/float64/nan" ] }, { @@ -55,7 +56,8 @@ "dependencies": [ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/sinpi", - "@stdlib/constants/float64/pi-squared" + "@stdlib/constants/float64/pi-squared", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +73,8 @@ "dependencies": [ "@stdlib/math/base/special/floor", "@stdlib/math/base/special/sinpi", - "@stdlib/constants/float64/pi-squared" + "@stdlib/constants/float64/pi-squared", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/trigamma/src/main.c b/lib/node_modules/@stdlib/math/base/special/trigamma/src/main.c index c3ca521b1ff9..d766c748062b 100644 --- a/lib/node_modules/@stdlib/math/base/special/trigamma/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/trigamma/src/main.c @@ -33,6 +33,7 @@ #include "stdlib/math/base/special/floor.h" #include "stdlib/math/base/special/sinpi.h" #include "stdlib/constants/float64/pi_squared.h" +#include "stdlib/constants/float64/nan.h" static const double YOFFSET24 = 3.558437347412109375; @@ -267,7 +268,7 @@ double stdlib_base_trigamma( const double x ) { // Check for negative arguments and use reflection: if ( x <= 0.0 ) { if ( stdlib_base_floor( x ) == x ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } s = stdlib_base_sinpi( x ); z = 1.0 - x; diff --git a/lib/node_modules/@stdlib/math/base/special/truncb/manifest.json b/lib/node_modules/@stdlib/math/base/special/truncb/manifest.json index 28036b85938b..98eb198e3c7f 100644 --- a/lib/node_modules/@stdlib/math/base/special/truncb/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/truncb/manifest.json @@ -41,7 +41,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/trunc", "@stdlib/math/base/special/truncn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -59,7 +60,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/trunc", "@stdlib/math/base/special/truncn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] }, { @@ -77,7 +79,8 @@ "@stdlib/math/base/assert/is-infinite", "@stdlib/math/base/special/trunc", "@stdlib/math/base/special/truncn", - "@stdlib/math/base/special/pow" + "@stdlib/math/base/special/pow", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/truncb/src/main.c b/lib/node_modules/@stdlib/math/base/special/truncb/src/main.c index 50b0f4885957..2d03dfef1c7d 100644 --- a/lib/node_modules/@stdlib/math/base/special/truncb/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/truncb/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/truncb.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/trunc.h" @@ -41,7 +42,7 @@ double stdlib_base_truncb( const double x, const int32_t n, const int32_t b ) { double s; if ( stdlib_base_is_nan( x ) || b <= 0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/truncn/manifest.json b/lib/node_modules/@stdlib/math/base/special/truncn/manifest.json index 1f85b8ae0824..6824a502456d 100644 --- a/lib/node_modules/@stdlib/math/base/special/truncn/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/truncn/manifest.json @@ -47,7 +47,8 @@ "@stdlib/constants/float64/min-base10-exponent", "@stdlib/constants/float64/min-base10-exponent-subnormal", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -71,7 +72,8 @@ "@stdlib/constants/float64/min-base10-exponent", "@stdlib/constants/float64/min-base10-exponent-subnormal", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] }, { @@ -95,7 +97,8 @@ "@stdlib/constants/float64/min-base10-exponent", "@stdlib/constants/float64/min-base10-exponent-subnormal", "@stdlib/math/base/assert/is-infinite", - "@stdlib/math/base/assert/is-nan" + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/truncn/src/main.c b/lib/node_modules/@stdlib/math/base/special/truncn/src/main.c index 8544aeb5cbc0..1ab4b9255b94 100644 --- a/lib/node_modules/@stdlib/math/base/special/truncn/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/truncn/src/main.c @@ -26,6 +26,7 @@ #include "stdlib/constants/float64/max_base10_exponent.h" #include "stdlib/constants/float64/min_base10_exponent.h" #include "stdlib/constants/float64/min_base10_exponent_subnormal.h" +#include "stdlib/constants/float64/nan.h" #include static const double MAX_INT = STDLIB_CONSTANT_FLOAT64_MAX_SAFE_INTEGER + 1.0; @@ -96,7 +97,7 @@ double stdlib_base_truncn( const double x, const int32_t n ) { double y; if ( stdlib_base_is_nan( x ) ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( diff --git a/lib/node_modules/@stdlib/math/base/special/truncsd/manifest.json b/lib/node_modules/@stdlib/math/base/special/truncsd/manifest.json index 1055163ccd52..474f91441603 100644 --- a/lib/node_modules/@stdlib/math/base/special/truncsd/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/truncsd/manifest.json @@ -45,7 +45,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/trunc", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -67,7 +68,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/trunc", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] }, { @@ -89,7 +91,8 @@ "@stdlib/math/base/special/abs", "@stdlib/math/base/special/floor", "@stdlib/math/base/special/trunc", - "@stdlib/number/float64/base/exponent" + "@stdlib/number/float64/base/exponent", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/truncsd/src/main.c b/lib/node_modules/@stdlib/math/base/special/truncsd/src/main.c index df49b024606b..805b612d9e6f 100644 --- a/lib/node_modules/@stdlib/math/base/special/truncsd/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/truncsd/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/truncsd.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/assert/is_infinite.h" #include "stdlib/math/base/special/pow.h" @@ -46,7 +47,7 @@ double stdlib_base_truncsd( const double x, const int32_t n, const int32_t b ) { double y; if ( stdlib_base_is_nan( x ) || n < 1 || b <= 0 ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } if ( stdlib_base_is_infinite( x ) || x == 0.0 ) { return x; diff --git a/lib/node_modules/@stdlib/math/base/special/wrap/manifest.json b/lib/node_modules/@stdlib/math/base/special/wrap/manifest.json index b2f19cbfa4f3..e7521dd7f6ff 100644 --- a/lib/node_modules/@stdlib/math/base/special/wrap/manifest.json +++ b/lib/node_modules/@stdlib/math/base/special/wrap/manifest.json @@ -40,7 +40,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/trunc", "@stdlib/math/base/special/fmod", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -57,7 +58,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/trunc", "@stdlib/math/base/special/fmod", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] }, { @@ -74,7 +76,8 @@ "@stdlib/math/base/assert/is-nan", "@stdlib/math/base/special/trunc", "@stdlib/math/base/special/fmod", - "@stdlib/math/base/assert/is-negative-zero" + "@stdlib/math/base/assert/is-negative-zero", + "@stdlib/constants/float64/nan" ] } ] diff --git a/lib/node_modules/@stdlib/math/base/special/wrap/src/main.c b/lib/node_modules/@stdlib/math/base/special/wrap/src/main.c index 490b41f6acf3..223a64e7e5e5 100644 --- a/lib/node_modules/@stdlib/math/base/special/wrap/src/main.c +++ b/lib/node_modules/@stdlib/math/base/special/wrap/src/main.c @@ -17,6 +17,7 @@ */ #include "stdlib/math/base/special/wrap.h" +#include "stdlib/constants/float64/nan.h" #include "stdlib/math/base/assert/is_nan.h" #include "stdlib/math/base/special/trunc.h" #include "stdlib/math/base/special/fmod.h" @@ -41,7 +42,7 @@ double stdlib_base_wrap( const double v, const double min, const double max ) { double vc; if ( stdlib_base_is_nan( v ) || stdlib_base_is_nan( min ) || stdlib_base_is_nan( max ) || max <= min ) { - return 0.0 / 0.0; // NaN + return STDLIB_CONSTANT_FLOAT64_NAN; } maxc = max; minc = min; diff --git a/lib/node_modules/@stdlib/math/base/tools/hermitepoly/test/test.factory.js b/lib/node_modules/@stdlib/math/base/tools/hermitepoly/test/test.factory.js index 13fdd0a5c7db..e18f4681f855 100644 --- a/lib/node_modules/@stdlib/math/base/tools/hermitepoly/test/test.factory.js +++ b/lib/node_modules/@stdlib/math/base/tools/hermitepoly/test/test.factory.js @@ -30,23 +30,18 @@ var factory = require( './../lib' ).factory; // FIXTURES // var random2 = require( './fixtures/python/random2.json' ); - var mediumNegative1 = require( './fixtures/python/medium_negative_1.json' ); var mediumNegative2 = require( './fixtures/python/medium_negative_2.json' ); var mediumNegative5 = require( './fixtures/python/medium_negative_5.json' ); - var mediumPositive1 = require( './fixtures/python/medium_positive_1.json' ); var mediumPositive2 = require( './fixtures/python/medium_positive_2.json' ); var mediumPositive5 = require( './fixtures/python/medium_positive_5.json' ); - var smallPositive1 = require( './fixtures/python/small_positive_1.json' ); var smallPositive2 = require( './fixtures/python/small_positive_2.json' ); var smallPositive5 = require( './fixtures/python/small_positive_5.json' ); - var smallNegative1 = require( './fixtures/python/small_negative_1.json' ); var smallNegative2 = require( './fixtures/python/small_negative_2.json' ); var smallNegative5 = require( './fixtures/python/small_negative_5.json' ); - var tiny1 = require( './fixtures/python/tiny_1.json' ); var tiny2 = require( './fixtures/python/tiny_2.json' ); var tiny5 = require( './fixtures/python/tiny_5.json' ); diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/algorithms/test/test.js b/lib/node_modules/@stdlib/ml/base/kmeans/algorithms/test/test.js index 5ab6aa3ad49b..b90c06383fb6 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/algorithms/test/test.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/algorithms/test/test.js @@ -66,7 +66,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/README.md b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/README.md new file mode 100644 index 000000000000..b7349bfbed1f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/README.md @@ -0,0 +1,239 @@ + + +# epsilonInsensitiveGradient + +> Compute the [epsilon insensitive loss gradient][epsilon-insensitive-loss-gradient] with respect to a model parameter. + +
+ +The [epsilon insensitive loss gradient][epsilon-insensitive-loss-gradient] is defined as + + + +```math +\frac{\partial \ell}{\partial w} =\begin{cases}-x & \text{if } y - p > \epsilon, \\x & \text{if } p - y > \epsilon, \\0 & \text{otherwise.}\end{cases} +``` + + + + + +
+ + + +
+ +## Usage + + + +```javascript +var epsilonInsensitiveGradient = require( '@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient' ); +``` + +#### epsilonInsensitiveGradient( x, e, y, p ) + +Computes the [epsilon insensitive loss gradient][epsilon-insensitive-loss-gradient] with respect to a model parameter. + + + +```javascript +var v = epsilonInsensitiveGradient( 3.0, 5.0, 10.2, 0.782 ); +// returns -3.0 + +v = epsilonInsensitiveGradient( -1.3, 1.0, 23.2, -0.999 ); +// returns 1.3 +``` + +The function accepts the following arguments: + +- **x**: input value. +- **e**: insensitivity parameter. +- **y**: true target value. +- **p**: predicted value. + +If any argument is `NaN`, the function returns `NaN`. + + + +```javascript +var v = epsilonInsensitiveGradient( NaN, 1.0, 1.0, 0.782 ); +// returns NaN + +v = epsilonInsensitiveGradient( 1.0, 1.0, NaN, 0.782 ); +// returns NaN + +v = epsilonInsensitiveGradient( NaN, NaN, 1.0, 0.782 ); +// returns NaN + +v = epsilonInsensitiveGradient( NaN, NaN, NaN, NaN ); +// returns NaN +``` + +
+ + + +
+ +## Examples + + + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var epsilonInsensitiveGradient = require( '@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var e = uniform( 100, 0.0, 5.0, { + 'dtype': 'float64' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var p = uniform( 100, -5.0, 5.0, { + 'dtype': 'float64' +}); + +logEachMap( 'epsilonInsensitiveGradient(%0.4f, %0.4f, %0.4f, %0.4f) = %0.4f', x, e, y, p, epsilonInsensitiveGradient ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/ml/base/loss/float64/epsilon_insensitive_gradient.h" +``` + +#### stdlib_base_float64_epsilon_insensitive_gradient( x, e, y, p ) + +Computes the [epsilon insensitive loss gradient][epsilon-insensitive-loss-gradient] with respect to a model parameter. + +```c +double out = stdlib_base_float64_epsilon_insensitive_gradient( 3.0, 5.0, 10.2, 0.782 ); +// returns -3.0 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **e**: `[in] double` insensitivity parameter. +- **y**: `[in] double` true target value. +- **p**: `[in] double` predicted value. + +```c +double stdlib_base_float64_epsilon_insensitive_gradient( const double x, const double e, const double y, const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/ml/base/loss/float64/epsilon_insensitive_gradient.h" +#include + +int main( void ) { + const double x[] = { -10.0, -9.56, -8.67, -7.78, -6.89, 6.89, 7.78, 8.67, 9.56, 10.0 }; + const double e[] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; + const double y[] = { -9.9, -7.7, -5.5, -3.3, -1.1, 1.1, 3.3, 5.5, 7.7, 9.9 }; + const double p[] = { -5.0, -3.89, -2.78, -1.67, -0.56, 0.56, 1.67, 2.78, 3.89, 5.0 }; + + double v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float64_epsilon_insensitive_gradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + printf( "epsilonInsensitiveGradient(%lf, %lf, %lf, %lf) = %lf\n", x[ i ], e[ i ], y[ i ], p[ i ], v ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[epsilon-insensitive-loss-gradient]: https://en.wikipedia.org/wiki/Support_vector_machine#Regression + +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/benchmark.js new file mode 100644 index 000000000000..47d79b062bb9 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var epsilonInsensitiveGradient = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0 ); + y = uniform( len, -100.0, 100.0 ); + p = uniform( len, -100.0, 100.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = epsilonInsensitiveGradient( x[ i%x.length ], 1.0, y[ i%y.length ], p[ i%p.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/benchmark.native.js new file mode 100644 index 000000000000..3cbfe94f7dd5 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var epsilonInsensitiveGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( epsilonInsensitiveGradient instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0 ); + y = uniform( len, -100.0, 100.0 ); + p = uniform( len, -100.0, 100.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = epsilonInsensitiveGradient( x[ i%x.length ], 1.0, y[ i%y.length ], p[ i%p.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/c/native/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..8ba6bc5991cd --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/benchmark/c/native/benchmark.c @@ -0,0 +1,148 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/epsilon_insensitive_gradient.h" +#include +#include +#include +#include +#include + +#define NAME "epsilon_insensitive_gradient" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double *x; + double *p; + double *y; + double v; + double t; + int i; + + x = (double *) malloc( 100 * sizeof( double ) ); + y = (double *) malloc( 100 * sizeof( double ) ); + p = (double *) malloc( 100 * sizeof( double ) ); + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + y[ i ] = random_uniform( -100.0, 100.0 ); + p[ i ] = random_uniform( -100.0, 100.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + v = stdlib_base_float64_epsilon_insensitive_gradient( x[ i%100 ], 1.0, y[ i % 100 ], p[ i % 100 ] ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + free( p ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/binding.gyp b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/img/equation_epsilon_insensitive_loss_gradient.svg b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/img/equation_epsilon_insensitive_loss_gradient.svg new file mode 100644 index 000000000000..75d13ba1caaa --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/img/equation_epsilon_insensitive_loss_gradient.svg @@ -0,0 +1,96 @@ + +StartFraction partial-differential script l Over partial-differential w EndFraction equals StartLayout Enlarged left-brace 1st Row 1st Column negative x 2nd Column if y minus p greater-than epsilon comma 2nd Row 1st Column x 2nd Column if p minus y greater-than epsilon comma 3rd Row 1st Column 0 2nd Column otherwise period EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/repl.txt new file mode 100644 index 000000000000..e077b14ceb00 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/repl.txt @@ -0,0 +1,42 @@ + +{{alias}}( x, e, y, p ) + Computes the epsilon insensitive loss gradient with respect to a model + parameter. + + If any argument is `NaN`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + e: number + Insensitivity parameter. + + y: number + True target value. + + p: number + Predicted value. + + Returns + ------- + v: number + Epsilon insensitive loss gradient. + + Examples + -------- + > var v = {{alias}}( 3.0, 5.0, 10.2, 0.782 ) + -3.0 + > v = {{alias}}( 2.5, 2.0, 8.0, 0.202 ) + -2.5 + > v = {{alias}}( -1.3, 1.0, 23.2, -0.999 ) + 1.3 + > v = {{alias}}( -2.0, 2.0, -21.0, 0.2 ) + -2.0 + > v = {{alias}}( NaN, 1.0, 1.0, 0.987 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/types/index.d.ts new file mode 100644 index 000000000000..2645998bf4e6 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/types/index.d.ts @@ -0,0 +1,59 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Computes the epsilon insensitive loss gradient with respect to a model parameter. +* +* @param x - input value +* @param e - insensitivity parameter +* @param y - true target value +* @param p - predicted value +* @returns epsilon insensitive loss gradient +* +* @example +* var v = epsilonInsensitiveGradient( 3.0, 5.0, 10.2, 0.782 ); +* // returns -3.0 +* +* @example +* var v = epsilonInsensitiveGradient( 2.5, 2.0, 8.0, 0.202 ); +* // returns -2.5 +* +* @example +* var v = epsilonInsensitiveGradient( -1.3, 1.0, 23.2, -0.999 ); +* // returns 1.3 +* +* @example +* var v = epsilonInsensitiveGradient( -2.0, 11.0, -12.2, 0.234 ); +* // returns -2.0 +* +* @example +* var v = epsilonInsensitiveGradient( -2.0, 2.0, -21.0, 0.2 ); +* // returns -2.0 +* +* @example +* var v = epsilonInsensitiveGradient( -1.3, 9.0, 4.0, -0.9 ); +* // returns 0.0 +*/ +declare function epsilonInsensitiveGradient( x: number, e: number, y: number, p: number ): number; + + +// EXPORTS // + +export = epsilonInsensitiveGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/types/test.ts new file mode 100644 index 000000000000..60843f53773b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/docs/types/test.ts @@ -0,0 +1,84 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import epsilonInsensitiveGradient = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, 0.782 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + epsilonInsensitiveGradient( true, 1.0, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( false, 1.0, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( null, 1.0, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( undefined, 1.0, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( '5', 1.0, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( [], 1.0, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( {}, 1.0, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( ( x: number ): number => x, 1.0, 1.0, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + epsilonInsensitiveGradient( 0.5869, true, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, false, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, null, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, undefined, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, '5', 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, [], 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, {}, 1.0, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, ( x: number ): number => x, 1.0, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + epsilonInsensitiveGradient( 0.5869, 1.0, true, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, false, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, null, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, undefined, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, '5', 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, [], 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, {}, 0.782 ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, ( x: number ): number => x, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, true ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, false ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, null ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, undefined ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, '5' ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, [] ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, {} ); // $ExpectError + epsilonInsensitiveGradient( 0.5869, 1.0, 1.0, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + epsilonInsensitiveGradient(); // $ExpectError + epsilonInsensitiveGradient( 1.0 ); // $ExpectError + epsilonInsensitiveGradient( 1.0, 0.900 ); // $ExpectError + epsilonInsensitiveGradient( 1.0, 0.900, 0.7873 ); // $ExpectError + epsilonInsensitiveGradient( 1.0, 0.900, 1.0, 0.787, 0.7873 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/c/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/c/example.c b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/c/example.c new file mode 100644 index 000000000000..0539856c0d2a --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/c/example.c @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/epsilon_insensitive_gradient.h" +#include + +int main( void ) { + const double x[] = { -10.0, -9.56, -8.67, -7.78, -6.89, 6.89, 7.78, 8.67, 9.56, 10.0 }; + const double e[] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; + const double y[] = { -9.9, -7.7, -5.5, -3.3, -1.1, 1.1, 3.3, 5.5, 7.7, 9.9 }; + const double p[] = { -5.0, -3.89, -2.78, -1.67, -0.56, 0.56, 1.67, 2.78, 3.89, 5.0 }; + + double v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float64_epsilon_insensitive_gradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + printf( "epsilonInsensitiveGradient(%lf, %lf, %lf, %lf) = %lf\n", x[ i ], e[ i ], y[ i ], p[ i ], v ); + } +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/index.js b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/index.js new file mode 100644 index 000000000000..05443a869f59 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var epsilonInsensitiveGradient = require( './../lib' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var e = uniform( 100, 0.0, 5.0, { + 'dtype': 'float64' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var p = uniform( 100, -5.0, 5.0, { + 'dtype': 'float64' +}); + +logEachMap( 'epsilonInsensitiveGradient(%0.4f, %0.4f, %0.4f, %0.4f) = %0.4f', x, e, y, p, epsilonInsensitiveGradient ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/include.gypi b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' e ) { + return -x; + } + if ( ( p-y ) > e ) { + return x; + } + return 0.0; +} + + +// EXPORTS // + +module.exports = epsilonInsensitiveGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/lib/native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/lib/native.js new file mode 100644 index 000000000000..3f2a368cafcd --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/lib/native.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Computes the epsilon insensitive loss gradient with respect to a model parameter. +* +* @private +* @param {number} x - input value +* @param {number} e - insensitivity parameter +* @param {number} y - true target value +* @param {number} p - predicted value +* @returns {number} epsilon insensitive loss gradient +* +* @example +* var v = epsilonInsensitiveGradient( 3.0, 5.0, 10.2, 0.782 ); +* // returns -3.0 +* +* @example +* var v = epsilonInsensitiveGradient( 2.5, 2.0, 8.0, 0.202 ); +* // returns -2.5 +* +* @example +* var v = epsilonInsensitiveGradient( -1.3, 1.0, 23.2, -0.999 ); +* // returns 1.3 +* +* @example +* var v = epsilonInsensitiveGradient( -2.0, 11.0, -12.2, 0.234 ); +* // returns -2.0 +* +* @example +* var v = epsilonInsensitiveGradient( -2.0, 2.0, -21.0, 0.2 ); +* // returns -2.0 +* +* @example +* var v = epsilonInsensitiveGradient( -1.3, 9.0, 4.0, -0.9 ); +* // returns 0.0 +*/ +function epsilonInsensitiveGradient( x, e, y, p ) { + return addon( x, e, y, p ); +} + + +// EXPORTS // + +module.exports = epsilonInsensitiveGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/manifest.json b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/manifest.json new file mode 100644 index 000000000000..4421714e344c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/manifest.json @@ -0,0 +1,75 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/quaternary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/package.json b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/package.json new file mode 100644 index 000000000000..59ca61c8ded3 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient", + "version": "0.0.0", + "description": "Compute the epsilon insensitive loss gradient with respect to a model parameter.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "machine learning", + "ml", + "loss", + "float64", + "epsilon insensitive loss", + "epsilon insensitive loss gradient", + "gradient", + "double-precision", + "double", + "dbl" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/addon.c b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/addon.c new file mode 100644 index 000000000000..0d2094167638 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/epsilon_insensitive_gradient.h" +#include "stdlib/math/base/napi/quaternary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DDDD_D( stdlib_base_float64_epsilon_insensitive_gradient ) diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/main.c b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/main.c new file mode 100644 index 000000000000..19fe2a6edfac --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/src/main.c @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/epsilon_insensitive_gradient.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/constants/float64/nan.h" + +/** +* Computes the epsilon insensitive loss gradient with respect to a model parameter. +* +* @param x input value +* @param e insensitivity parameter +* @param y true target value +* @param p predicted value +* @return epsilon insensitive loss gradient +* +* @example +* double out = stdlib_base_float64_epsilon_insensitive_gradient( 2.5, 2.0, 8.0, 0.202 ); +* // returns -2.5 +*/ +double stdlib_base_float64_epsilon_insensitive_gradient( const double x, const double e, const double y, const double p ) { + if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( e ) || stdlib_base_is_nan( y ) || stdlib_base_is_nan( p ) ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + if ( ( y-p ) > e ) { + return -x; + } + if ( ( p-y ) > e ) { + return x; + } + return 0.0; +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/REQUIRE new file mode 100644 index 000000000000..7c8193c06e65 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/REQUIRE @@ -0,0 +1,2 @@ +julia 1.4.2 +JSON 0.21.0 diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/runner.jl new file mode 100755 index 000000000000..98ab7541a1aa --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/runner.jl @@ -0,0 +1,101 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import JSON + +""" + gen( x, e, y, p, name ) + +Generate fixture data and write to file. + +# Arguments + +* `x`: input domain +* `e`: insensitivity parameter +* `y`: response domain +* `p`: prediction domain +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = range( 0.0, stop=50.0, length=503 ); +julia> e = range( 0.0, stop=5.0, length=503 ); +julia> y = range( 0.0, stop=10.0, length=503 ); +julia> p = range( 10.0, stop=0.0, length=503 ); +julia> gen( x, e, y, p, "data.json" ); +``` +""" +function gen( x, e, y, p, name ) + + d = y .- p; + v = ifelse.( d .> e, -x, + ifelse.( d .< .-e, x, 0.0 ) ); + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("e", e), + ("y", y), + ("p", p), + ("expected", v) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + write( outfile, "\n" ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname(file); + +# Positive tiny values: +x = range( 0.0, stop=20e-20, length=503 ); +e = range( 0.0, stop=5e-20, length=503 ); +y = range( 0.0, stop=10e-20, length=503 ); +p = range( 10e-20, stop=0.0, length=503 ); +gen( x, e, y, p, "tiny_positive.json" ); + +# Small positive values: +x = range( 0.0, stop=50.0, length=503 ); +e = range( 0.0, stop=5.0, length=503 ); +y = range( 0.0, stop=10.0, length=503 ); +p = range( 10.0, stop=0.0, length=503 ); +gen( x, e, y, p, "small_positive.json" ); + +# Negative tiny values: +x = range( 0.0, stop=-20e-20, length=503 ); +e = range( 0.0, stop=5e-20, length=503 ); +y = range( -10e-20, stop=0.0, length=503 ); +p = range( 0.0, stop=-10e-20, length=503 ); +gen( x, e, y, p, "tiny_negative.json" ); + +# Small negative values: +x = range( 0.0, stop=-50.0, length=503 ); +e = range( 0.0, stop=5.0, length=503 ); +y = range( -10.0, stop=0.0, length=503 ); +p = range( 0.0, stop=-10.0, length=503 ); +gen( x, e, y, p, "small_negative.json" ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/small_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/small_negative.json new file mode 100644 index 000000000000..d68a8ac4e3c0 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/small_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/small_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/small_positive.json new file mode 100644 index 000000000000..7ebdb67a487b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/small_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/tiny_negative.json new file mode 100644 index 000000000000..2662dcf561e6 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/tiny_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/tiny_positive.json new file mode 100644 index 000000000000..42ee13cd0796 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/fixtures/julia/tiny_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/test.js b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/test.js new file mode 100644 index 000000000000..f396567ee832 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/test.js @@ -0,0 +1,147 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var epsilonInsensitiveGradient = require( './../lib' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof epsilonInsensitiveGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for tiny positive values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + e = tinyPositive.e; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for small positive values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + e = smallPositive.e; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for tiny negative values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + e = tinyNegative.e; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for small negative values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + e = smallNegative.e; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', function test( t ) { + var v; + + v = epsilonInsensitiveGradient( NaN, 1.0, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( 1.0, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( NaN, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( NaN, NaN, NaN, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( NaN, NaN, NaN, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/test.native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/test.native.js new file mode 100644 index 000000000000..dd25ff8750fd --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/epsilon-insensitive-gradient/test/test.native.js @@ -0,0 +1,156 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// VARIABLES // + +var epsilonInsensitiveGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( epsilonInsensitiveGradient instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof epsilonInsensitiveGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for tiny positive values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + e = tinyPositive.e; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for small positive values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + e = smallPositive.e; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for tiny negative values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + e = tinyNegative.e; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the epsilon insensitive loss gradient for small negative values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + e = smallNegative.e; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = epsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) { + var v; + + v = epsilonInsensitiveGradient( NaN, 1.0, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( 1.0, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( NaN, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( NaN, NaN, NaN, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = epsilonInsensitiveGradient( NaN, NaN, NaN, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/README.md b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/README.md new file mode 100644 index 000000000000..86eac66eb11c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/README.md @@ -0,0 +1,237 @@ + + +# squaredEpsilonInsensitiveGradient + +> Compute the squared epsilon insensitive loss gradient with respect to a model parameter. + +
+ +The squared epsilon insensitive loss gradient is defined as + + + +```math +\frac{\partial \ell}{\partial w_i} = +\begin{cases} +-2((y - p) - \epsilon)x_i & \text{if } y - p > \epsilon, \\ +2((p - y) - \epsilon)x_i & \text{if } p - y > \epsilon, \\ +0 & \text{otherwise.} +\end{cases} +``` + + + +
+ + + +
+ +## Usage + + + +```javascript +var squaredEpsilonInsensitiveGradient = require( '@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient' ); +``` + +#### squaredEpsilonInsensitiveGradient( x, e, y, p ) + +Computes the squared epsilon insensitive loss gradient with respect to a model parameter. + + + +```javascript +var v = squaredEpsilonInsensitiveGradient( 3.0, 5.0, 10.2, 0.782 ); +// returns ~-26.508 + +v = squaredEpsilonInsensitiveGradient( -1.3, 1.0, 23.2, -0.999 ); +// returns ~60.317 +``` + +The function accepts the following arguments: + +- **x**: input value. +- **e**: insensitivity parameter. +- **y**: true target value. +- **p**: predicted value. + +If any argument is `NaN`, the function returns `NaN`. + + + +```javascript +var v = squaredEpsilonInsensitiveGradient( NaN, 1.0, 1.0, 0.782 ); +// returns NaN + +v = squaredEpsilonInsensitiveGradient( 1.0, 1.0, NaN, 0.782 ); +// returns NaN + +v = squaredEpsilonInsensitiveGradient( NaN, NaN, 1.0, 0.782 ); +// returns NaN + +v = squaredEpsilonInsensitiveGradient( NaN, NaN, NaN, NaN ); +// returns NaN +``` + +
+ + + +
+ +## Examples + + + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var squaredEpsilonInsensitiveGradient = require( '@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var e = uniform( 100, 0.0, 5.0, { + 'dtype': 'float64' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var p = uniform( 100, -5.0, 5.0, { + 'dtype': 'float64' +}); + +logEachMap( 'squaredEpsilonInsensitiveGradient(%0.4f, %0.4f, %0.4f, %0.4f) = %0.4f', x, e, y, p, squaredEpsilonInsensitiveGradient ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/ml/base/loss/float64/squared_epsilon_insensitive_gradient.h" +``` + +#### stdlib_base_float64_squared_epsilon_insensitive_gradient( x, e, y, p ) + +Computes the squared epsilon insensitive loss gradient with respect to a model parameter. + +```c +double out = stdlib_base_float64_squared_epsilon_insensitive_gradient( 3.0, 5.0, 10.2, 0.782 ); +// returns ~-26.508 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **e**: `[in] double` insensitivity parameter. +- **y**: `[in] double` true target value. +- **p**: `[in] double` predicted value. + +```c +double stdlib_base_float64_squared_epsilon_insensitive_gradient( const double x, const double e, const double y, const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/ml/base/loss/float64/squared_epsilon_insensitive_gradient.h" +#include + +int main( void ) { + const double x[] = { -10.0, -9.56, -8.67, -7.78, -6.89, 6.89, 7.78, 8.67, 9.56, 10.0 }; + const double e[] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; + const double y[] = { -9.9, -7.7, -5.5, -3.3, -1.1, 1.1, 3.3, 5.5, 7.7, 9.9 }; + const double p[] = { -5.0, -3.89, -2.78, -1.67, -0.56, 0.56, 1.67, 2.78, 3.89, 5.0 }; + + double v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float64_squared_epsilon_insensitive_gradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + printf( "squaredEpsilonInsensitiveGradient(%lf, %lf, %lf, %lf) = %lf\n", x[ i ], e[ i ], y[ i ], p[ i ], v ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/benchmark.js new file mode 100644 index 000000000000..54bd61ad5ca1 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var squaredEpsilonInsensitiveGradient = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0 ); + y = uniform( len, -100.0, 100.0 ); + p = uniform( len, -100.0, 100.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i%x.length ], 1.0, y[ i%y.length ], p[ i%p.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/benchmark.native.js new file mode 100644 index 000000000000..551a88c93fc6 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var squaredEpsilonInsensitiveGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( squaredEpsilonInsensitiveGradient instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0 ); + y = uniform( len, -100.0, 100.0 ); + p = uniform( len, -100.0, 100.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i%x.length ], 1.0, y[ i%y.length ], p[ i%p.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/c/native/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..1e1b29f7cd6f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/benchmark/c/native/benchmark.c @@ -0,0 +1,148 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_epsilon_insensitive_gradient.h" +#include +#include +#include +#include +#include + +#define NAME "squared_epsilon_insensitive_gradient" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double *x; + double *p; + double *y; + double v; + double t; + int i; + + x = (double *) malloc( 100 * sizeof( double ) ); + y = (double *) malloc( 100 * sizeof( double ) ); + p = (double *) malloc( 100 * sizeof( double ) ); + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + y[ i ] = random_uniform( -100.0, 100.0 ); + p[ i ] = random_uniform( -100.0, 100.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + v = stdlib_base_float64_squared_epsilon_insensitive_gradient( x[ i%100 ], 1.0, y[ i%100 ], p[ i%100 ] ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + free( p ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/binding.gyp b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/repl.txt new file mode 100644 index 000000000000..c7dbb998bf61 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/repl.txt @@ -0,0 +1,42 @@ + +{{alias}}( x, e, y, p ) + Computes the squared epsilon insensitive loss gradient with respect to a + model parameter. + + If any argument is `NaN`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + e: number + Insensitivity parameter. + + y: number + True target value. + + p: number + Predicted value. + + Returns + ------- + v: number + Squared epsilon insensitive loss gradient. + + Examples + -------- + > var v = {{alias}}( 3.0, 5.0, 10.2, 0.782 ) + ~-26.508 + > v = {{alias}}( 2.5, 2.0, 8.0, 0.202 ) + ~-28.99 + > v = {{alias}}( -1.3, 1.0, 23.2, -0.999 ) + ~60.317 + > v = {{alias}}( -2.0, 2.0, -21.0, 0.2 ) + -76.8 + > v = {{alias}}( NaN, 1.0, 1.0, 0.987 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/types/index.d.ts new file mode 100644 index 000000000000..be31d8f57238 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/types/index.d.ts @@ -0,0 +1,59 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Computes the squared epsilon insensitive loss gradient with respect to a model parameter. +* +* @param x - input value +* @param e - insensitivity parameter +* @param y - true target value +* @param p - predicted value +* @returns squared epsilon insensitive loss gradient +* +* @example +* var v = squaredEpsilonInsensitiveGradient( 3.0, 5.0, 10.2, 0.782 ); +* // returns ~-26.508 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( 2.5, 2.0, 8.0, 0.202 ); +* // returns ~-28.99 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -1.3, 1.0, 23.2, -0.999 ); +* // returns ~60.317 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -2.0, 11.0, -12.2, 0.234 ); +* // returns ~-5.736 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -2.0, 2.0, -21.0, 0.2 ); +* // returns -76.8 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -1.3, 9.0, 4.0, -0.9 ); +* // returns 0.0 +*/ +declare function squaredEpsilonInsensitiveGradient( x: number, e: number, y: number, p: number ): number; + + +// EXPORTS // + +export = squaredEpsilonInsensitiveGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/types/test.ts new file mode 100644 index 000000000000..52f2bc1d966c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/docs/types/test.ts @@ -0,0 +1,84 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import squaredEpsilonInsensitiveGradient = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, 0.782 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + squaredEpsilonInsensitiveGradient( true, 1.0, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( false, 1.0, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( null, 1.0, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( undefined, 1.0, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( '5', 1.0, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( [], 1.0, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( {}, 1.0, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( ( x: number ): number => x, 1.0, 1.0, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + squaredEpsilonInsensitiveGradient( 0.5869, true, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, false, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, null, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, undefined, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, '5', 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, [], 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, {}, 1.0, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, ( x: number ): number => x, 1.0, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, true, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, false, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, null, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, undefined, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, '5', 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, [], 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, {}, 0.782 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, ( x: number ): number => x, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a fourth argument which is not a number... +{ + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, true ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, false ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, null ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, undefined ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, '5' ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, [] ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, {} ); // $ExpectError + squaredEpsilonInsensitiveGradient( 0.5869, 1.0, 1.0, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + squaredEpsilonInsensitiveGradient(); // $ExpectError + squaredEpsilonInsensitiveGradient( 1.0 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 1.0, 0.900 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 1.0, 0.900, 0.7873 ); // $ExpectError + squaredEpsilonInsensitiveGradient( 1.0, 0.900, 1.0, 0.787, 0.7873 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/c/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/c/example.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/c/example.c new file mode 100644 index 000000000000..8d5284ca2738 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/c/example.c @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_epsilon_insensitive_gradient.h" +#include + +int main( void ) { + const double x[] = { -10.0, -9.56, -8.67, -7.78, -6.89, 6.89, 7.78, 8.67, 9.56, 10.0 }; + const double e[] = { 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; + const double y[] = { -9.9, -7.7, -5.5, -3.3, -1.1, 1.1, 3.3, 5.5, 7.7, 9.9 }; + const double p[] = { -5.0, -3.89, -2.78, -1.67, -0.56, 0.56, 1.67, 2.78, 3.89, 5.0 }; + + double v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float64_squared_epsilon_insensitive_gradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + printf( "squaredEpsilonInsensitiveGradient(%lf, %lf, %lf, %lf) = %lf\n", x[ i ], e[ i ], y[ i ], p[ i ], v ); + } +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/index.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/index.js new file mode 100644 index 000000000000..aecc86a9156c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var squaredEpsilonInsensitiveGradient = require( './../lib' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var e = uniform( 100, 0.0, 5.0, { + 'dtype': 'float64' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var p = uniform( 100, -5.0, 5.0, { + 'dtype': 'float64' +}); + +logEachMap( 'squaredEpsilonInsensitiveGradient(%0.4f, %0.4f, %0.4f, %0.4f) = %0.4f', x, e, y, p, squaredEpsilonInsensitiveGradient ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/include.gypi b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' e ) { + return -2.0 * ( z-e ) * x; + } + if ( z < -e ) { + return -2.0 * ( z+e ) * x; + } + return 0.0; +} + + +// EXPORTS // + +module.exports = squaredEpsilonInsensitiveGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/lib/native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/lib/native.js new file mode 100644 index 000000000000..5baccaedd020 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/lib/native.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Computes the squared epsilon insensitive loss gradient with respect to a model parameter. +* +* @private +* @param {number} x - input value +* @param {number} e - insensitivity parameter +* @param {number} y - true target value +* @param {number} p - predicted value +* @returns {number} squared epsilon insensitive loss gradient +* +* @example +* var v = squaredEpsilonInsensitiveGradient( 3.0, 5.0, 10.2, 0.782 ); +* // returns ~-26.508 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( 2.5, 2.0, 8.0, 0.202 ); +* // returns ~-28.99 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -1.3, 1.0, 23.2, -0.999 ); +* // returns ~60.317 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -2.0, 11.0, -12.2, 0.234 ); +* // returns ~-5.736 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -2.0, 2.0, -21.0, 0.2 ); +* // returns -76.8 +* +* @example +* var v = squaredEpsilonInsensitiveGradient( -1.3, 9.0, 4.0, -0.9 ); +* // returns 0.0 +*/ +function squaredEpsilonInsensitiveGradient( x, e, y, p ) { + return addon( x, e, y, p ); +} + + +// EXPORTS // + +module.exports = squaredEpsilonInsensitiveGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/manifest.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/manifest.json new file mode 100644 index 000000000000..4421714e344c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/manifest.json @@ -0,0 +1,75 @@ +{ + "options": { + "task": "build" + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/quaternary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "benchmark", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" + ] + }, + { + "task": "examples", + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/constants/float64/nan" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/package.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/package.json new file mode 100644 index 000000000000..539a63ff6688 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/package.json @@ -0,0 +1,68 @@ +{ + "name": "@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient", + "version": "0.0.0", + "description": "Compute the squared epsilon insensitive loss gradient with respect to a model parameter.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "machine learning", + "ml", + "loss", + "float64", + "squared epsilon insensitive loss", + "squared epsilon insensitive loss gradient", + "gradient", + "double-precision", + "double", + "dbl" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/addon.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/addon.c new file mode 100644 index 000000000000..960d5a870581 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_epsilon_insensitive_gradient.h" +#include "stdlib/math/base/napi/quaternary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DDDD_D( stdlib_base_float64_squared_epsilon_insensitive_gradient ) diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/main.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/main.c new file mode 100644 index 000000000000..06f349c550d9 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/src/main.c @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_epsilon_insensitive_gradient.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/constants/float64/nan.h" + +/** +* Computes the squared epsilon insensitive loss gradient with respect to a model parameter. +* +* @param x input value +* @param e insensitivity parameter +* @param y true target value +* @param p predicted value +* @return squared epsilon insensitive loss gradient +* +* @example +* double out = stdlib_base_float64_squared_epsilon_insensitive_gradient( 2.5, 2.0, 8.0, 0.202 ); +* // returns ~-28.99 +*/ +double stdlib_base_float64_squared_epsilon_insensitive_gradient( const double x, const double e, const double y, const double p ) { + double z; + + if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( e ) || stdlib_base_is_nan( y ) || stdlib_base_is_nan( p ) ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + z = y - p; + if ( z > e ) { + return -2.0 * ( z-e ) * x; + } + if ( z < -e ) { + return -2.0 * ( z+e ) * x; + } + return 0.0; +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/REQUIRE new file mode 100644 index 000000000000..7c8193c06e65 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/REQUIRE @@ -0,0 +1,2 @@ +julia 1.4.2 +JSON 0.21.0 diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/runner.jl new file mode 100755 index 000000000000..6208f9c373a3 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/runner.jl @@ -0,0 +1,106 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import JSON + +""" + gen( x, e, y, p, name ) + +Generate fixture data and write to file. + +# Arguments + +* `x`: input domain +* `e`: insensitivity parameter +* `y`: response domain +* `p`: prediction domain +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = range( 0.0, stop=50.0, length=503 ); +julia> e = range( 0.0, stop=5.0, length=503 ); +julia> y = range( 0.0, stop=10.0, length=503 ); +julia> p = range( 10.0, stop=0.0, length=503 ); +julia> gen( x, e, y, p, "data.json" ); +``` +""" +function gen( x, e, y, p, name ) + x = collect( Float64, x ); + e = collect( Float64, e ); + y = collect( Float64, y ); + p = collect( Float64, p ); + + + d = y .- p; + v = ifelse.( d .> e, -2 .* ( d .- e ) .* x, + ifelse.( d .< .-e, -2 .* ( d .+ e) .* x, 0.0 ) ); + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("e", e), + ("y", y), + ("p", p), + ("expected", v) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + write( outfile, "\n" ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname(file); + +# Positive tiny values: +x = range( 0.0, stop=20e-20, length=503 ); +e = range( 0.0, stop=5e-20, length=503 ); +y = range( 0.0, stop=10e-20, length=503 ); +p = range( 10e-20, stop=0.0, length=503 ); +gen( x, e, y, p, "tiny_positive.json" ); + +# Small positive values: +x = range( 0.0, stop=50.0, length=503 ); +e = range( 0.0, stop=5.0, length=503 ); +y = range( 0.0, stop=10.0, length=503 ); +p = range( 10.0, stop=0.0, length=503 ); +gen( x, e, y, p, "small_positive.json" ); + +# Negative tiny values: +x = range( 0.0, stop=-20e-20, length=503 ); +e = range( 0.0, stop=5e-20, length=503 ); +y = range( -10e-20, stop=0.0, length=503 ); +p = range( 0.0, stop=-10e-20, length=503 ); +gen( x, e, y, p, "tiny_negative.json" ); + +# Small negative values: +x = range( 0.0, stop=-50.0, length=503 ); +e = range( 0.0, stop=5.0, length=503 ); +y = range( -10.0, stop=0.0, length=503 ); +p = range( 0.0, stop=-10.0, length=503 ); +gen( x, e, y, p, "small_negative.json" ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/small_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/small_negative.json new file mode 100644 index 000000000000..84962adc5803 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/small_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/small_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/small_positive.json new file mode 100644 index 000000000000..48c5ccfabe0b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/small_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/tiny_negative.json new file mode 100644 index 000000000000..8b675c9d4332 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/tiny_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/tiny_positive.json new file mode 100644 index 000000000000..29a4bf39f397 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/fixtures/julia/tiny_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/test.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/test.js new file mode 100644 index 000000000000..d8643c773556 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/test.js @@ -0,0 +1,147 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var squaredEpsilonInsensitiveGradient = require( './../lib' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof squaredEpsilonInsensitiveGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for tiny positive values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + e = tinyPositive.e; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for small positive values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + e = smallPositive.e; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for tiny negative values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + e = tinyNegative.e; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for small negative values', function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + e = smallNegative.e; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', function test( t ) { + var v; + + v = squaredEpsilonInsensitiveGradient( NaN, 1.0, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( 1.0, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( NaN, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( NaN, NaN, NaN, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( NaN, NaN, NaN, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/test.native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/test.native.js new file mode 100644 index 000000000000..3f1f5eb72a63 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-epsilon-insensitive-gradient/test/test.native.js @@ -0,0 +1,156 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// VARIABLES // + +var squaredEpsilonInsensitiveGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( squaredEpsilonInsensitiveGradient instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof squaredEpsilonInsensitiveGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for tiny positive values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + e = tinyPositive.e; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for small positive values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + e = smallPositive.e; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for tiny negative values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + e = tinyNegative.e; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared epsilon insensitive loss gradient for small negative values', opts, function test( t ) { + var expected; + var e; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + e = smallNegative.e; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredEpsilonInsensitiveGradient( x[ i ], e[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 0 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) { + var v; + + v = squaredEpsilonInsensitiveGradient( NaN, 1.0, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( 1.0, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( NaN, NaN, 1.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( NaN, NaN, NaN, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredEpsilonInsensitiveGradient( NaN, NaN, NaN, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/README.md b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/README.md new file mode 100644 index 000000000000..ed893341d493 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/README.md @@ -0,0 +1,225 @@ + + +# squaredErrorGradient + +> Compute the [squared error loss gradient][squared-error-loss-gradient] with respect to a model parameter. + +
+ +The [squared error loss gradient][squared-error-loss-gradient] is defined as + + + +```math +\frac{\partial \ell}{\partial w} = -(y-p)x +``` + + + +
+ + + +
+ +## Usage + +```javascript +var squaredErrorGradient = require( '@stdlib/ml/base/loss/float64/squared-error-gradient' ); +``` + +#### squaredErrorGradient( x, y, p ) + +Computes the [squared error loss gradient][squared-error-loss-gradient] with respect to a model parameter. + +```javascript +var v = squaredErrorGradient( 5.0, -2.0, -1.782 ); +// returns ~1.09 + +v = squaredErrorGradient( -4.0, 1.0, -0.999 ); +// returns 7.996 +``` + +The function accepts the following arguments: + +- **x**: input value. +- **y**: true target value. +- **p**: predicted value. + +If any argument is `NaN`, the function returns `NaN`. + +```javascript +var v = squaredErrorGradient( NaN, 2.0, 0.782 ); +// returns NaN + +v = squaredErrorGradient( 1.0, NaN, 0.782 ); +// returns NaN + +v = squaredErrorGradient( 1.0, 2.0, NaN ); +// returns NaN + +v = squaredErrorGradient( NaN, NaN, NaN ); +// returns NaN +``` + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var squaredErrorGradient = require( '@stdlib/ml/base/loss/float64/squared-error-gradient' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var p = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +logEachMap( 'squaredErrorGradient(%0.4f, %0.4f, %0.4f) = %0.4f', x, y, p, squaredErrorGradient ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/ml/base/loss/float64/squared_error_gradient.h" +``` + +#### stdlib_base_float64_squared_error_gradient( x, y, p ) + +Computes the [squared error loss gradient][squared-error-loss-gradient] with respect to a model parameter. + +```c +double out = stdlib_base_float64_squared_error_gradient( 5.0, -2.0, -1.782 ); +// returns ~1.09 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **y**: `[in] double` true target value. +- **p**: `[in] double` predicted value. + +```c +double stdlib_base_float64_squared_error_gradient( const double x, const double y, const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/ml/base/loss/float64/squared_error_gradient.h" +#include + +int main( void ) { + const double x[] = { -10.0, -9.56, -8.67, -7.78, -6.89, 6.89, 7.78, 8.67, 9.56, 10.0 }; + const double y[] = { -1.0, -1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0 }; + const double p[] = { -5.0, -3.89, -2.78, -1.67, -0.56, 0.56, 1.67, 2.78, 3.89, 5.0 }; + + double v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float64_squared_error_gradient( x[ i ], y[ i ], p[ i ] ); + printf( "squaredErrorGradient(%lf, %lf, %lf) = %lf\n", x[ i ], y[ i ], p[ i ], v ); + } +} +``` + +
+ + + +
+ + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[squared-error-loss-gradient]: https://en.wikipedia.org/wiki/Mean_squared_error#Loss_function + +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/benchmark.js new file mode 100644 index 000000000000..ff467a7231be --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var squaredErrorGradient = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0 ); + y = uniform( len, -100.0, 100.0 ); + p = uniform( len, -100.0, 100.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = squaredErrorGradient( x[ i%x.length ], y[ i%y.length ], p[ i%p.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/benchmark.native.js new file mode 100644 index 000000000000..942df4d5c960 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var squaredErrorGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( squaredErrorGradient instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var len; + var x; + var y; + var p; + var v; + var i; + + len = 100; + x = uniform( len, -100.0, 100.0 ); + y = uniform( len, -100.0, 100.0 ); + p = uniform( len, -100.0, 100.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = squaredErrorGradient( x[ i%x.length ], y[ i%y.length ], p[ i%p.length ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/c/native/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/c/native/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/c/native/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/c/native/benchmark.c new file mode 100644 index 000000000000..00019e154726 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/benchmark/c/native/benchmark.c @@ -0,0 +1,148 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_error_gradient.h" +#include +#include +#include +#include +#include + +#define NAME "squared_error_gradient" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double *x; + double *y; + double *p; + double v; + double t; + int i; + + x = (double *) malloc( 100 * sizeof( double ) ); + y = (double *) malloc( 100 * sizeof( double ) ); + p = (double *) malloc( 100 * sizeof( double ) ); + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -100.0, 100.0 ); + y[ i ] = random_uniform( -100.0, 100.0 ); + p[ i ] = random_uniform( -100.0, 100.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + v = stdlib_base_float64_squared_error_gradient( x[ i % 100 ], y[ i % 100 ], p[ i % 100 ] ); + if ( v != v ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( v != v ) { + printf( "should not return NaN\n" ); + } + free( x ); + free( y ); + free( p ); + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::native::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/binding.gyp b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/repl.txt new file mode 100644 index 000000000000..c27a1edf6dcf --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( x, y, p ) + Computes the squared error loss gradient with respect to a model parameter. + + If any argument is `NaN`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + y: number + True target value. + + p: number + Predicted value. + + Returns + ------- + v: number + Squared error loss gradient. + + Examples + -------- + > var v = {{alias}}( 5.0, -2.0, -1.782 ) + ~1.09 + > v = {{alias}}( 1.0, 0.202, 0.202 ) + 0.0 + > v = {{alias}}( -4.0, 1.0, -0.999 ) + 7.996 + > v = {{alias}}( 4.723, 0.2, 0.532 ) + ~1.568 + > v = {{alias}}( 1.0, NaN, 0.987 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/types/index.d.ts new file mode 100644 index 000000000000..627126f1d999 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Computes the squared error loss gradient with respect to a model parameter. +* +* ## Notes +* +* - The squared error loss is defined as the squared difference of the observed and fitted value. +* +* @param x - input value +* @param y - true target value +* @param p - predicted value +* @returns squared error loss gradient +* +* @example +* var v = squaredErrorGradient( 5.0, -2.0, -1.782 ); +* // returns ~1.09 +* +* @example +* var v = squaredErrorGradient( 1.0, 0.202, 0.202 ); +* // returns 0.0 +* +* @example +* var v = squaredErrorGradient( -4.0, 1.0, -0.999 ); +* // returns 7.996 +* +* @example +* var v = squaredErrorGradient( -10.33, -2.4, 0.234 ); +* // returns ~-27.209 +* +* @example +* var v = squaredErrorGradient( 4.723, 0.2, 0.532 ); +* // returns ~1.568 +* +* @example +* var v = squaredErrorGradient( 11.928, -1.811, -0.9 ); +* // returns ~10.866 +*/ +declare function squaredErrorGradient( x: number, y: number, p: number ): number; + + +// EXPORTS // + +export = squaredErrorGradient; diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/types/test.ts new file mode 100644 index 000000000000..c8a4df3d6932 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/docs/types/test.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import squaredErrorGradient = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + squaredErrorGradient( 5.0, -2.0, -1.782 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + squaredErrorGradient( true, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( false, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( null, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( undefined, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( '5', -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( [], -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( {}, -2.0, 0.782 ); // $ExpectError + squaredErrorGradient( ( x: number ): number => x, -2.0, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a number... +{ + squaredErrorGradient( 1.0, true, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, false, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, null, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, undefined, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, '5', 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, [], 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, {}, 0.782 ); // $ExpectError + squaredErrorGradient( 1.0, ( x: number ): number => x, 0.782 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + squaredErrorGradient( 1.0, -2.0, true ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, false ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, null ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, undefined ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, '5' ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, [] ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, {} ); // $ExpectError + squaredErrorGradient( 1.0, -2.0, ( x: number ): number => x ); // $ExpectError +} + + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + squaredErrorGradient(); // $ExpectError + squaredErrorGradient( 1.0 ); // $ExpectError + squaredErrorGradient( 1.0, 0.7873 ); // $ExpectError + squaredErrorGradient( 1.0, 0.900, 0.7873, 0.546 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/c/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/c/example.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/c/example.c new file mode 100644 index 000000000000..50e3290c177f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/c/example.c @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_error_gradient.h" +#include + +int main( void ) { + const double x[] = { -10.0, -9.56, -8.67, -7.78, -6.89, 6.89, 7.78, 8.67, 9.56, 10.0 }; + const double y[] = { -1.0, -1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0 }; + const double p[] = { -5.0, -3.89, -2.78, -1.67, -0.56, 0.56, 1.67, 2.78, 3.89, 5.0 }; + + double v; + int i; + for ( i = 0; i < 10; i++ ) { + v = stdlib_base_float64_squared_error_gradient( x[ i ], y[ i ], p[ i ] ); + printf( "squaredErrorGradient(%lf, %lf, %lf) = %lf\n", x[ i ], y[ i ], p[ i ], v ); + } +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/index.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/index.js new file mode 100644 index 000000000000..b8047cd74eb5 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var squaredErrorGradient = require( './../lib' ); + +var x = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var y = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +var p = uniform( 100, -100.0, 100.0, { + 'dtype': 'float64' +}); +logEachMap( 'squaredErrorGradient(%0.4f, %0.4f, %0.4f) = %0.4f', x, y, p, squaredErrorGradient ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/include.gypi b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "machine learning", + "ml", + "loss", + "float64", + "squared error", + "squared error loss", + "squared error loss gradient", + "gradient", + "double-precision", + "double", + "dbl" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/Makefile b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/addon.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/addon.c new file mode 100644 index 000000000000..c2b610c4d034 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_error_gradient.h" +#include "stdlib/math/base/napi/ternary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DDD_D( stdlib_base_float64_squared_error_gradient ) diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/main.c b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/main.c new file mode 100644 index 000000000000..061aad0a5174 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/src/main.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/ml/base/loss/float64/squared_error_gradient.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/constants/float64/nan.h" + +/** +* Computes the squared error loss gradient with respect to a model parameter. +* +* @param x input value +* @param y true target value +* @param p predicted value +* @return squared error loss gradient +* +* @example +* double out = stdlib_base_float64_squared_error_gradient( 1.0, 0.202, 0.202 ); +* // returns 0.0 +*/ +double stdlib_base_float64_squared_error_gradient( const double x, const double y, const double p ) { + if ( stdlib_base_is_nan( x ) || stdlib_base_is_nan( y ) || stdlib_base_is_nan( p ) ) { + return STDLIB_CONSTANT_FLOAT64_NAN; + } + return ( p-y ) * x; +} diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/REQUIRE new file mode 100644 index 000000000000..7c8193c06e65 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/REQUIRE @@ -0,0 +1,2 @@ +julia 1.4.2 +JSON 0.21.0 diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/runner.jl new file mode 100755 index 000000000000..ebd23b463d9b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/runner.jl @@ -0,0 +1,95 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import JSON + +""" + gen( x, y, p, name ) + +Generate fixture data and write to file. + +# Arguments + +* `x`: input domain +* `y`: response domain +* `p`: prediction domain +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = range( -1000.0, 1000.0, 2001 ); +julia> y = range( -1000.0, 1000.0, 2001 ); +julia> p = range( -1000.0, 1000.0, 2001 ); +julia> gen( x, y, p, "data.json" ); +``` +""" +function gen( x, y, p, name ) + x = collect( Float64, x ); + y = collect( Float64, y ); + p = collect( Float64, p ); + + v = -( y .- p ) .* x; + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("y", y), + ("p", p), + ("expected", v) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + write( outfile, "\n" ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname(file); + +# Positive tiny values: +x = range( 0.0, stop=20e-20, length=503 ); +y = range( 0.0, stop=10e-20, length=503 ); +p = range( 10e-20, stop=0.0, length=503 ); +gen( x, y, p, "tiny_positive.json" ); + +# Small positive values: +x = range( 0.0, stop=50.0, length=503 ); +y = range( 0.0, stop=10.0, length=503 ); +p = range( 10.0, stop=0.0, length=503 ); +gen( x, y, p, "small_positive.json" ); + +# Negative tiny values: +x = range( 0.0, stop=-20e-20, length=503 ); +y = range( -10e-20, stop=0.0, length=503 ); +p = range( 0.0, stop=-10e-20, length=503 ); +gen( x, y, p, "tiny_negative.json" ); + +# Small negative values: +x = range( 0.0, stop=-50.0, length=503 ); +y = range( -10.0, stop=0.0, length=503 ); +p = range( 0.0, stop=-10.0, length=503 ); +gen( x, y, p, "small_negative.json" ); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/small_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/small_negative.json new file mode 100644 index 000000000000..f8fec80cf167 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/small_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/small_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/small_positive.json new file mode 100644 index 000000000000..ebcec7831884 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/small_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/tiny_negative.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/tiny_negative.json new file mode 100644 index 000000000000..94d3bb2cc32b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/tiny_negative.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/tiny_positive.json b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/tiny_positive.json new file mode 100644 index 000000000000..3f897819d66c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/fixtures/julia/tiny_positive.json @@ -0,0 +1 @@ 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diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/test.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/test.js new file mode 100644 index 000000000000..0b3dd8e6bd4e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/test.js @@ -0,0 +1,136 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var squaredErrorGradient = require( './../lib' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof squaredErrorGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny positive values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small positive values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny negative values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small negative values', function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', function test( t ) { + var v; + + v = squaredErrorGradient( NaN, 2.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, NaN, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, 2.0, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( NaN, NaN, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/test.native.js b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/test.native.js new file mode 100644 index 000000000000..62d305583b82 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/loss/float64/squared-error-gradient/test/test.native.js @@ -0,0 +1,145 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/number/float64/base/assert/is-almost-same-value' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var tinyPositive = require( './fixtures/julia/tiny_positive.json' ); +var smallPositive = require( './fixtures/julia/small_positive.json' ); +var tinyNegative = require( './fixtures/julia/tiny_negative.json' ); +var smallNegative = require( './fixtures/julia/small_negative.json' ); + + +// VARIABLES // + +var squaredErrorGradient = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( squaredErrorGradient instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof squaredErrorGradient, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny positive values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyPositive.x; + y = tinyPositive.y; + p = tinyPositive.p; + expected = tinyPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small positive values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallPositive.x; + y = smallPositive.y; + p = smallPositive.p; + expected = smallPositive.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for tiny negative values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = tinyNegative.x; + y = tinyNegative.y; + p = tinyNegative.p; + expected = tinyNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function computes the squared error loss gradient for small negative values', opts, function test( t ) { + var expected; + var x; + var y; + var p; + var v; + var i; + + x = smallNegative.x; + y = smallNegative.y; + p = smallNegative.p; + expected = smallNegative.expected; + for ( i = 0; i < y.length; i++ ) { + v = squaredErrorGradient( x[ i ], y[ i ], p[ i ] ); + t.strictEqual( isAlmostSameValue( v, expected[ i ], 1 ), true, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `NaN` if provided `NaN`', opts, function test( t ) { + var v; + + v = squaredErrorGradient( NaN, 2.0, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, NaN, 0.782 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( 1.0, 2.0, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = squaredErrorGradient( NaN, NaN, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/README.md new file mode 100644 index 000000000000..422657a437b1 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/README.md @@ -0,0 +1,121 @@ + + +# enum2str + +> Return the SGD classification learning rate scheduler string associated with an SGD classification learning rate scheduler enumeration constant. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var enum2str = require( '@stdlib/ml/base/sgd-classification/learning-rate-enum2str' ); +``` + +#### enum2str( value ) + +Returns the SGD classification learning rate scheduler string associated with an SGD classification learning rate scheduler enumeration constant. + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); + +var v = str2enum( 'basic' ); +// returns + +var s = enum2str( v ); +// returns 'basic' +``` + +If unable to resolve an SGD classification learning rate scheduler string, the function returns `null`. + +```javascript +var v = enum2str( -999999999 ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var enum2str = require( '@stdlib/ml/base/sgd-classification/learning-rate-enum2str' ); + +var str = enum2str( str2enum( 'basic' ) ); +// returns 'basic' + +str = enum2str( str2enum( 'constant' ) ); +// returns 'constant' +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/benchmark/benchmark.js new file mode 100644 index 000000000000..30f004c536b6 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/benchmark/benchmark.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var pkg = require( './../package.json' ).name; +var enum2str = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + str2enum( 'basic' ), + str2enum( 'constant' ), + str2enum( 'invscaling' ), + str2enum( 'pegasos' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = enum2str( values[ i%values.length ] ); + if ( typeof out !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( out ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/repl.txt new file mode 100644 index 000000000000..0a2ce6da6f66 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/repl.txt @@ -0,0 +1,23 @@ + +{{alias}}( value ) + Returns the SGD classification learning rate scheduler string associated + with an SGD classification learning rate scheduler enumeration constant. + + Parameters + ---------- + value: integer + Learning rate scheduler enumeration constant. + + Returns + ------- + out: string|null + Learning rate scheduler string. + + Examples + -------- + > var out = {{alias}}( {{alias:@stdlib/ml/base/sgd-classification/learning-rate-str2enum}}( 'basic' ) ) + 'basic' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/types/index.d.ts new file mode 100644 index 000000000000..19f7d954ec3e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/types/index.d.ts @@ -0,0 +1,41 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the SGD classification learning rate scheduler string associated with an SGD classification learning rate scheduler enumeration constant. +* +* @param value - enumeration constant +* @returns learning rate scheduler string +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +* +* var v = str2enum( 'basic' ); +* // returns +* +* var s = enum2str( v ); +* // returns 'basic' +*/ +declare function enum2str( value: number ): string | null; + + +// EXPORTS // + +export = enum2str; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/types/test.ts new file mode 100644 index 000000000000..fe80992105ef --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/docs/types/test.ts @@ -0,0 +1,39 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import enum2str = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + enum2str( 0 ); // $ExpectType string | null +} + +// The compiler throws an error if not provided a number... +{ + enum2str( '10' ); // $ExpectError + enum2str( true ); // $ExpectError + enum2str( false ); // $ExpectError + enum2str( null ); // $ExpectError + enum2str( undefined ); // $ExpectError + enum2str( [] ); // $ExpectError + enum2str( {} ); // $ExpectError + enum2str( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/examples/index.js new file mode 100644 index 000000000000..98eb0a7ca9a9 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var enum2str = require( './../lib' ); + +var str = enum2str( str2enum( 'constant' ) ); +console.log( str ); +// => 'constant' + +str = enum2str( str2enum( 'basic' ) ); +console.log( str ); +// => 'basic' diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/lib/index.js new file mode 100644 index 000000000000..27cd6a3de69d --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the SGD classification learning rate scheduler string associated with an SGD classification learning rate scheduler enumeration constant. +* +* @module @stdlib/ml/base/sgd-classification/learning-rate-enum2str +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +* var enum2str = require( '@stdlib/ml/base/sgd-classification/learning-rate-enum2str' ); +* +* var v = str2enum( 'basic' ); +* // returns +* +* var s = enum2str( v ); +* // returns 'basic' +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/lib/main.js new file mode 100644 index 000000000000..95c173ae26e2 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/lib/main.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var objectInverse = require( '@stdlib/object/inverse' ); +var enumeration = require( '@stdlib/ml/base/sgd-classification/learning-rates' ).enum; + + +// VARIABLES // + +var hash = objectInverse( enumeration(), { + 'duplicates': false +}); + + +// MAIN // + +/** +* Returns the SGD classification learning rate scheduler string associated with an SGD classification learning rate scheduler enumeration constant. +* +* @param {integer} value - learning rate scheduler enumeration constant +* @returns {(string|null)} learning rate scheduler string or null +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +* +* var v = str2enum( 'basic' ); +* // returns +* +* var s = enum2str( v ); +* // returns 'basic' +*/ +function enum2str( value ) { + var v = hash[ value ]; + return ( isString( v ) ) ? v : null; // note: we include this guard to prevent walking the prototype chain +} + + +// EXPORTS // + +module.exports = enum2str; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/package.json new file mode 100644 index 000000000000..b72245fafc31 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/learning-rate-enum2str", + "version": "0.0.0", + "description": "Return the SGD classification learning rate scheduler string associated with an SGD classification learning rate scheduler enumeration constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "learning rate", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/test/test.js new file mode 100644 index 000000000000..656a695abf22 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-enum2str/test/test.js @@ -0,0 +1,67 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var enum2str = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof enum2str, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the string associated with an enumeration constant', function test( t ) { + var i; + for ( i = 0; i < VALUES.length; i++ ) { + t.strictEqual( enum2str( str2enum( VALUES[ i ] ) ), VALUES[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve a string', function test( t ) { + var values; + var i; + + values = [ + -9999999, + -999999999, + -99999999999 + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( enum2str( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/README.md new file mode 100644 index 000000000000..e11fa2bfb2e4 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/README.md @@ -0,0 +1,124 @@ + + +# resolve + +> Return the enumeration constant associated with a supported SGD classification learning rate scheduler value. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var resolve = require( '@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum' ); +``` + +#### resolve( value ) + +Returns the enumeration constant associated with a supported SGD classification learning rate scheduler value. + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); + +var v = resolve( 'basic' ); +// returns + +v = resolve( str2enum( 'constant' ) ); +// returns +``` + +If unable to resolve an enumeration constant, the function returns `null`. + +```javascript +var v = resolve( 'beep' ); +// returns null +``` + +
+ + + + + +
+ +## Notes + +- Downstream consumers of this function should **not** rely on specific integer values (e.g., `BASIC == 0`). Instead, the function should be used in an opaque manner. + +
+ + + + + +
+ +## Examples + + + +```javascript +var resolve = require( '@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum' ); + +var v = resolve( 'basic' ); +// returns + +v = resolve( 'constant' ); +// returns +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/benchmark/benchmark.js new file mode 100644 index 000000000000..6051662a9725 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/benchmark/benchmark.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var resolve = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::string', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'number' ) { + b.fail( 'should return a number' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::integer', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + str2enum( 'basic' ), + str2enum( 'constant' ), + str2enum( 'invscaling' ), + str2enum( 'pegasos' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'number' ) { + b.fail( 'should return a number' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/repl.txt new file mode 100644 index 000000000000..16995312e2fb --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/repl.txt @@ -0,0 +1,29 @@ + +{{alias}}( value ) + Returns the enumeration constant associated with a supported SGD + classification learning rate scheduler value. + + Downstream consumers of this function should *not* rely on specific integer + values (e.g., `BASIC == 0`). Instead, the function should be used in an + opaque manner. + + Parameters + ---------- + value: any + Learning rate scheduler value. + + Returns + ------- + out: integer|null + Enumeration constant. + + Examples + -------- + > var out = {{alias}}( 'basic' ) + + > out = {{alias}}( {{alias:@stdlib/ml/base/sgd-classification/learning-rate-str2enum}}( 'basic' ) ) + + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/types/index.d.ts new file mode 100644 index 000000000000..71049f343e2f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/types/index.d.ts @@ -0,0 +1,40 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the enumeration constant associated with a supported SGD classification learning rate scheduler value. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `BASIC == 0`). Instead, the function should be used in an opaque manner. +* +* @param value - learning rate scheduler value +* @returns enumeration constant +* +* @example +* var v = resolve( 'basic' ); +* // returns +*/ +declare function resolve( value: any ): number | null; + + +// EXPORTS // + +export = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/types/test.ts new file mode 100644 index 000000000000..125d9f7a122e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/docs/types/test.ts @@ -0,0 +1,28 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import resolve = require( './index' ); + + +// TESTS // + +// The function returns a number or null... +{ + resolve( 0 ); // $ExpectType number | null + resolve( 'basic' ); // $ExpectType number | null +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/examples/index.js new file mode 100644 index 000000000000..8e913704a76b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var resolve = require( './../lib' ); + +var v = resolve( 'basic' ); +console.log( v ); +// => + +v = resolve( 'constant' ); +console.log( v ); +// => diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/lib/index.js new file mode 100644 index 000000000000..9d24b164a7ea --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the enumeration constant associated with a supported SGD classification learning rate scheduler value. +* +* @module @stdlib/ml/base/sgd-classification/learning-rate-resolve-enum +* +* @example +* var resolve = require( '@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum' ); +* +* var v = resolve( 'basic' ); +* // returns +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/lib/main.js new file mode 100644 index 000000000000..59113eefccae --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/lib/main.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var enum2str = require( '@stdlib/ml/base/sgd-classification/learning-rate-enum2str' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); + + +// MAIN // + +/** +* Returns the enumeration constant associated with a supported SGD classification learning rate scheduler value. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `BASIC == 0`). Instead, the function should be used in an opaque manner. +* +* @param {*} value - learning rate scheduler value +* @returns {(integer|null)} enumeration constant or null +* +* @example +* var v = resolve( 'basic' ); +* // returns +*/ +function resolve( value ) { + var t = ( typeof value ); + if ( t === 'number' ) { + return ( enum2str( value ) ) ? value : null; + } + if ( t === 'string' ) { + return str2enum( value ); + } + return null; +} + + +// EXPORTS // + +module.exports = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/package.json new file mode 100644 index 000000000000..785517143065 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum", + "version": "0.0.0", + "description": "Return the enumeration constant associated with a supported SGD classification learning rate scheduler value.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "learning rate", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/test/test.js new file mode 100644 index 000000000000..a96b6fc9386e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-enum/test/test.js @@ -0,0 +1,76 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var resolve = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof resolve, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the enumeration constant associated with an SGD classification learning rate scheduler value', function test( t ) { + var v; + var i; + for ( i = 0; i < VALUES.length; i++ ) { + v = str2enum( VALUES[ i ] ); + t.strictEqual( resolve( VALUES[ i ] ), v, 'returns expected value' ); + t.strictEqual( resolve( v ), v, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve an enumeration constant', function test( t ) { + var values; + var i; + + values = [ + 'beep', + 'boop', + 'foo', + 'bar', + -99999999, + -9999999999, + -9999999999999, + true, + false + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( resolve( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/README.md new file mode 100644 index 000000000000..14bdd51cce79 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/README.md @@ -0,0 +1,121 @@ + + +# resolve + +> Return the learning rate scheduler string associated with a supported SGD classification learning rate scheduler value. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var resolve = require( '@stdlib/ml/base/sgd-classification/learning-rate-resolve-str' ); +``` + +#### resolve( value ) + +Returns the learning rate scheduler string associated with a supported SGD classification learning rate scheduler value. + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); + +var v = resolve( 'constant' ); +// returns 'constant' + +v = resolve( str2enum( 'constant' ) ); +// returns 'constant' +``` + +If unable to resolve an SGD classification learning rate scheduler string, the function returns `null`. + +```javascript +var v = resolve( 'beep' ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var resolve = require( '@stdlib/ml/base/sgd-classification/learning-rate-resolve-str' ); + +var v = resolve( str2enum( 'constant' ) ); +// returns 'constant' + +v = resolve( str2enum( 'basic' ) ); +// returns 'basic' +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/benchmark/benchmark.js new file mode 100644 index 000000000000..54f10fd58dec --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/benchmark/benchmark.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var resolve = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::string', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( out ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::integer', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + str2enum( 'basic' ), + str2enum( 'constant' ), + str2enum( 'invscaling' ), + str2enum( 'pegasos' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( out ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/repl.txt new file mode 100644 index 000000000000..bb668b6cc3f3 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/repl.txt @@ -0,0 +1,25 @@ + +{{alias}}( value ) + Returns the learning rate scheduler string associated with a supported SGD + classification learning rate scheduler value. + + Parameters + ---------- + value: any + Learning rate scheduler value. + + Returns + ------- + out: string|null + Learning rate scheduler string. + + Examples + -------- + > var out = {{alias}}( 'constant' ) + 'constant' + > out = {{alias}}( {{alias:@stdlib/ml/base/sgd-classification/learning-rate-str2enum}}( 'constant' ) ) + 'constant' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/types/index.d.ts new file mode 100644 index 000000000000..01289d897440 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/types/index.d.ts @@ -0,0 +1,38 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the learning rate scheduler string associated with a supported SGD classification learning rate scheduler value. +* +* @param value - learning rate scheduler value +* @returns learning rate scheduler string or null +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +* +* var v = resolve( str2enum( 'constant' ) ); +* // returns 'constant' +*/ +declare function resolve( value: any ): string | null; + + +// EXPORTS // + +export = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/types/test.ts new file mode 100644 index 000000000000..d122510e714b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/docs/types/test.ts @@ -0,0 +1,28 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import resolve = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + resolve( 0 ); // $ExpectType string | null + resolve( 'constant' ); // $ExpectType string | null +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/examples/index.js new file mode 100644 index 000000000000..5fc4ab909923 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var resolve = require( './../lib' ); + +var v = resolve( str2enum( 'constant' ) ); +console.log( v ); +// => 'constant' + +v = resolve( str2enum( 'basic' ) ); +console.log( v ); +// => 'basic' diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/lib/index.js new file mode 100644 index 000000000000..1058ee0ac645 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/lib/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the learning rate scheduler string associated with a supported SGD classification learning rate scheduler value. +* +* @module @stdlib/ml/base/sgd-classification/learning-rate-resolve-str +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +* var resolve = require( '@stdlib/ml/base/sgd-classification/learning-rate-resolve-str' ); +* +* var v = resolve( str2enum( 'constant' ) ); +* // returns 'constant' +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/lib/main.js new file mode 100644 index 000000000000..01d31e646e6b --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/lib/main.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var enum2str = require( '@stdlib/ml/base/sgd-classification/learning-rate-enum2str' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); + + +// MAIN // + +/** +* Returns the learning rate scheduler string associated with a supported SGD classification learning rate scheduler value. +* +* @param {*} value - learning rate scheduler value +* @returns {(string|null)} learning rate scheduler string or null +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +* +* var v = resolve( str2enum( 'constant' ) ); +* // returns 'constant' +*/ +function resolve( value ) { + var t = ( typeof value ); + if ( t === 'string' ) { + return ( str2enum( value ) === null ) ? null : value; + } + if ( t === 'number' ) { + return enum2str( value ); + } + return null; +} + + +// EXPORTS // + +module.exports = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/package.json new file mode 100644 index 000000000000..03177bebed75 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/learning-rate-resolve-str", + "version": "0.0.0", + "description": "Return the learning rate scheduler string associated with a supported SGD classification learning rate scheduler value.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "learning rate", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/test/test.js new file mode 100644 index 000000000000..abf3d8bd55e6 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-resolve-str/test/test.js @@ -0,0 +1,76 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +var resolve = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof resolve, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the string associated with an SGD classification learning rate scheduler value', function test( t ) { + var v; + var i; + for ( i = 0; i < VALUES.length; i++ ) { + v = str2enum( VALUES[ i ] ); + t.strictEqual( resolve( VALUES[ i ] ), VALUES[ i ], 'returns expected value' ); + t.strictEqual( resolve( v ), VALUES[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve a string', function test( t ) { + var values; + var i; + + values = [ + 'beep', + 'boop', + 'foo', + 'bar', + -99999999, + -9999999999, + -9999999999999, + true, + false + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( resolve( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/README.md new file mode 100644 index 000000000000..908ef11eda4a --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/README.md @@ -0,0 +1,119 @@ + + +# str2enum + +> Return the enumeration constant associated with an SGD classification learning rate scheduler string. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +``` + +#### str2enum( learningRate ) + +Returns the enumeration constant associated with an SGD classification learning rate scheduler string. + +```javascript +var v = str2enum( 'constant' ); +// returns +``` + +If unable to resolve an enumeration constant, the function returns `null`. + +```javascript +var v = str2enum( 'beep' ); +// returns null +``` + +
+ + + + + +
+ +## Notes + +- Downstream consumers of this function should **not** rely on specific integer values (e.g., `BASIC == 0`). Instead, the function should be used in an opaque manner. + +
+ + + + + +
+ +## Examples + + + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); + +var v = str2enum( 'constant' ); +// returns + +v = str2enum( 'basic' ); +// returns +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/benchmark/benchmark.js new file mode 100644 index 000000000000..96cb8ab2ee54 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/benchmark/benchmark.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var pkg = require( './../package.json' ).name; +var str2enum = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = str2enum( values[ i%values.length ] ); + if ( typeof out !== 'number' ) { + b.fail( 'should return a number' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/repl.txt new file mode 100644 index 000000000000..12159a31e8c2 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/repl.txt @@ -0,0 +1,27 @@ + +{{alias}}( learningRate ) + Returns the enumeration constant associated with an SGD classification + learning rate scheduler string. + + Downstream consumers of this function should *not* rely on specific integer + values (e.g., `BASIC == 0`). Instead, the function should be used in an + opaque manner. + + Parameters + ---------- + learningRate: string + Learning rate scheduler. + + Returns + ------- + out: integer|null + Enumeration constant. + + Examples + -------- + > var out = {{alias}}( 'constant' ) + + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/types/index.d.ts new file mode 100644 index 000000000000..4069d5140271 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/types/index.d.ts @@ -0,0 +1,40 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the enumeration constant associated with an SGD classification learning rate scheduler string. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `BASIC == 0`). Instead, the function should be used in an opaque manner. +* +* @param learningRate - learning rate scheduler string +* @returns enumeration constant +* +* @example +* var v = str2enum( 'constant' ); +* // returns +*/ +declare function str2enum( learningRate: string ): number | null; + + +// EXPORTS // + +export = str2enum; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/types/test.ts new file mode 100644 index 000000000000..7d45e990746e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/docs/types/test.ts @@ -0,0 +1,39 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import str2enum = require( './index' ); + + +// TESTS // + +// The function returns a number or null... +{ + str2enum( 'constant' ); // $ExpectType number | null +} + +// The compiler throws an error if not provided a string... +{ + str2enum( 10 ); // $ExpectError + str2enum( true ); // $ExpectError + str2enum( false ); // $ExpectError + str2enum( null ); // $ExpectError + str2enum( undefined ); // $ExpectError + str2enum( [] ); // $ExpectError + str2enum( {} ); // $ExpectError + str2enum( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/examples/index.js new file mode 100644 index 000000000000..69f951ceb6bf --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var str2enum = require( './../lib' ); + +var v = str2enum( 'constant' ); +console.log( v ); +// => + +v = str2enum( 'basic' ); +console.log( v ); +// => diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/lib/index.js new file mode 100644 index 000000000000..6534b9aeae3e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the enumeration constant associated with an SGD classification learning rate scheduler string. +* +* @module @stdlib/ml/base/sgd-classification/learning-rate-str2enum +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/learning-rate-str2enum' ); +* +* var v = str2enum( 'constant' ); +* // returns +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/lib/main.js new file mode 100644 index 000000000000..25885115397e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/lib/main.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var enumeration = require( '@stdlib/ml/base/sgd-classification/learning-rates' ).enum; + + +// VARIABLES // + +var ENUM = enumeration(); + + +// MAIN // + +/** +* Returns the enumeration constant associated with an SGD classification learning rate scheduler string. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `BASIC == 0`). Instead, the function should be used in an opaque manner. +* +* @param {string} learningRate - learning rate scheduler string +* @returns {(integer|null)} integer value or null +* +* @example +* var v = str2enum( 'constant' ); +* // returns +*/ +function str2enum( learningRate ) { + var v = ENUM[ learningRate ]; + return ( isNumber( v ) ) ? v : null; // note: we include this guard to prevent walking the prototype chain +} + + +// EXPORTS // + +module.exports = str2enum; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/package.json new file mode 100644 index 000000000000..1de1c627f550 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/learning-rate-str2enum", + "version": "0.0.0", + "description": "Return the enumeration constant associated with an SGD classification learning rate scheduler string.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "learning rate", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/test/test.js new file mode 100644 index 000000000000..a8c6e430bf32 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rate-str2enum/test/test.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var enum2str = require( '@stdlib/ml/base/sgd-classification/learning-rate-enum2str' ); +var str2enum = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'constant', + 'basic', + 'invscaling', + 'pegasos' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof str2enum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the enumeration constant associated with a string', function test( t ) { + var i; + for ( i = 0; i < VALUES.length; i++ ) { + t.strictEqual( enum2str( str2enum( VALUES[ i ] ) ), VALUES[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve an enumeration constant', function test( t ) { + var values; + var i; + + values = [ + 'beep', + 'boop', + 'foo', + 'bar' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( str2enum( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/README.md new file mode 100644 index 000000000000..b010fea72323 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/README.md @@ -0,0 +1,190 @@ + + +# Learning rates + +> SGD classification learning rate schedulers. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var learningRates = require( '@stdlib/ml/base/sgd-classification/learning-rates' ); +``` + +#### learningRates() + +Returns a list of SGD classification learning rate schedulers. + +```javascript +var out = learningRates(); +// e.g., returns [ 'basic', 'constant', 'invscaling', 'pegasos' ] +``` + +The output array contains the following learning rate schedulers: + +- `basic`: basic learning rate function according to the formula `10/(10+t)` where `t` is the current iteration. +- `constant`: constant learning rate function. +- `invscaling`: inverse scaling learning rate function according to the formula `eta0/pow(t, power_t)` where `eta0` is the initial learning rate and `power_t` is the exponent controlling how quickly the learning rate decreases. +- `pegasos`: Pegasos learning rate function according to the formula `1/(lambda*t)` where `t` is the current iteration and `lambda` is the regularization parameter. + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var contains = require( '@stdlib/array/base/assert/contains' ).factory; +var learningRates = require( '@stdlib/ml/base/sgd-classification/learning-rates' ); + +var isLearningRate = contains( learningRates() ); + +var bool = isLearningRate( 'constant' ); +// returns true + +bool = isLearningRate( 'pegasos' ); +// returns true + +bool = isLearningRate( 'beep' ); +// returns false +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/ml/base/sgd-classification/learning_rates.h" +``` + +#### STDLIB_ML_SGD_CLASSIFICATION_LEARNING_RATE + +An enumeration of SGD classification learning rate schedulers with the following fields: + +- **STDLIB_ML_SGD_CLASSIFICATION_BASIC**: basic learning rate function according to the formula `10/(10+t)` where `t` is the current iteration. +- **STDLIB_ML_SGD_CLASSIFICATION_CONSTANT**: constant learning rate function. +- **STDLIB_ML_SGD_CLASSIFICATION_INVSCALING**: inverse scaling learning rate function according to the formula `eta0/pow(t, power_t)` where `eta0` is the initial learning rate and `power_t` is the exponent controlling how quickly the learning rate decreases. +- **STDLIB_ML_SGD_CLASSIFICATION_PEGASOS**: Pegasos learning rate function according to the formula `1/(lambda*t)` where `t` is the current iteration and `lambda` is the regularization parameter. + +```c +#include "stdlib/ml/base/sgd-classification/learning_rates.h" + +const enum STDLIB_ML_SGD_CLASSIFICATION_LEARNING_RATE v = STDLIB_ML_SGD_CLASSIFICATION_BASIC; +``` + +
+ + + + + +
+ +### Notes + +- Enumeration constants should be considered opaque values, and one should **not** rely on specific integer values. + +
+ + + + + +
+ +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/benchmark/benchmark.js new file mode 100644 index 000000000000..95c330ebd9fb --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/benchmark/benchmark.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; +var pkg = require( './../package.json' ).name; +var learningRates = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = learningRates(); + if ( out.length < 2 ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isStringArray( out ) ) { + b.fail( 'should return an array of strings' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/repl.txt new file mode 100644 index 000000000000..6128e38d404a --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/repl.txt @@ -0,0 +1,30 @@ + +{{alias}}() + Returns a list of SGD classification learning rate schedulers. + + The output array contains the following learning rate schedulers: + + - basic: basic learning rate function according to the formula `10/(10+t)` + where `t` is the current iteration. + - constant: constant learning rate function. + - invscaling: inverse scaling learning rate function according to the + formula `eta0/pow(t, power_t)` where `eta0` is the initial learning rate and + `power_t` is the exponent controlling how quickly the learning rate + decreases. + - pegasos: Pegasos learning rate function according to the formula + `1/(lambda*t)` where `t` is the current iteration and `lambda` is the + regularization parameter. + + Returns + ------- + out: Array + List of learning rate schedulers. + + Examples + -------- + > var out = {{alias}}() + [...] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/types/index.d.ts new file mode 100644 index 000000000000..dcffa578ea70 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/types/index.d.ts @@ -0,0 +1,35 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns a list of SGD classification learning rate schedulers. +* +* @returns list of learning rate schedulers +* +* @example +* var list = learningRates(); +* // e.g., returns [ 'basic', 'constant', 'invscaling', 'pegasos' ] +*/ +declare function learningRates(): Array; + + +// EXPORTS // + +export = learningRates; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/types/test.ts new file mode 100644 index 000000000000..c8605c6f84de --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/docs/types/test.ts @@ -0,0 +1,32 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import learningRates = require( './index' ); + + +// TESTS // + +// The function returns an array of strings... +{ + learningRates(); // $ExpectType string[] +} + +// The compiler throws an error if the function is provided any arguments... +{ + learningRates( 9 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/examples/index.js new file mode 100644 index 000000000000..c7427e0fe2fd --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var contains = require( '@stdlib/array/base/assert/contains' ).factory; +var learningRates = require( './../lib' ); + +var isLearningRate = contains( learningRates() ); + +var bool = isLearningRate( 'basic' ); +console.log( bool ); +// => true + +bool = isLearningRate( 'constant' ); +console.log( bool ); +// => true + +bool = isLearningRate( 'beep' ); +console.log( bool ); +// => false diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/include/stdlib/ml/base/sgd-classification/learning_rates.h b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/include/stdlib/ml/base/sgd-classification/learning_rates.h new file mode 100644 index 000000000000..4c6f37b1bc21 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/include/stdlib/ml/base/sgd-classification/learning_rates.h @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_ML_BASE_SGD_CLASSIFICATION_LEARNING_RATES_H +#define STDLIB_ML_BASE_SGD_CLASSIFICATION_LEARNING_RATES_H + +/** +* Enumeration of SGD classification learning rate schedulers. +*/ +enum STDLIB_ML_SGD_CLASSIFICATION_LEARNING_RATE { + // Basic learning rate function according to the formula `10/(10+t)` where `t` is the current iteration: + STDLIB_ML_SGD_CLASSIFICATION_BASIC = 0, + + // Constant learning rate function: + STDLIB_ML_SGD_CLASSIFICATION_CONSTANT, + + // Inverse scaling learning rate function according to the formula `eta0/pow(t, power_t)` where `eta0` is the initial learning rate and `power_t` is the exponent controlling how quickly the learning rate decreases: + STDLIB_ML_SGD_CLASSIFICATION_INVSCALING, + + // Pegasos learning rate function according to the formula `1/(lambda*t)` where `t` is the current iteration and `lambda` is the regularization parameter: + STDLIB_ML_SGD_CLASSIFICATION_PEGASOS +}; + +#endif // !STDLIB_ML_BASE_SGD_CLASSIFICATION_LEARNING_RATES_H diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/data.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/data.json new file mode 100644 index 000000000000..9f4424ed10e9 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/data.json @@ -0,0 +1,6 @@ +[ + "basic", + "constant", + "invscaling", + "pegasos" +] diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/enum.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/enum.js new file mode 100644 index 000000000000..27c8b2643a09 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/enum.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns an object mapping supported learning rate schedulers to integer values for purposes of C inter-operation. +* +* ## Notes +* +* - Downstream consumers of this mapping should **not** rely on specific integer values (e.g., `BASIC == 0`). Instead, the object should be used in an opaque manner. +* - The main purpose of this function is JavaScript and C inter-operation. +* +* @returns {Object} object mapping supported learning rate schedulers to integer values +* +* @example +* var table = enumerated(); +* // returns +*/ +function enumerated() { + // NOTE: the following should match the C `learning rates.h` enumeration!!!! + return { + // Basic learning rate function according to the formula `10/(10+t)` where `t` is the current iteration: + 'basic': 0, + + // Constant learning rate function: + 'constant': 1, + + // Inverse scaling learning rate function according to the formula `eta0/pow(t, power_t)` where `eta0` is the initial learning rate and `power_t` is the exponent controlling how quickly the learning rate decreases: + 'invscaling': 2, + + // Pegasos learning rate function according to the formula `1/(lambda*t)` where `t` is the current iteration and `lambda` is the regularization parameter: + 'pegasos': 3 + }; +} + + +// EXPORTS // + +module.exports = enumerated; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/index.js new file mode 100644 index 000000000000..9af59ae848b9 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/index.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a list of SGD classification learning rate schedulers. +* +* @module @stdlib/ml/base/sgd-classification/learning-rates +* +* @example +* var learningRates = require( '@stdlib/ml/base/sgd-classification/learning-rates' ); +* +* var list = learningRates(); +* // e.g., returns [ 'basic', 'constant', 'invscaling', 'pegasos' ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var enumeration = require( './enum.js' ); + + +// MAIN // + +setReadOnly( main, 'enum', enumeration ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/main.js new file mode 100644 index 000000000000..fc7d1e0cee31 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/lib/main.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var DATA = require( './data.json' ); + + +// MAIN // + +/** +* Returns a list of SGD classification learning rate schedulers. +* +* @returns {Array} list of learning rate schedulers +* +* @example +* var list = learningRates(); +* // e.g., returns [ 'basic', 'constant', 'invscaling', 'pegasos' ] +*/ +function learningRates() { + return DATA.slice(); +} + + +// EXPORTS // + +module.exports = learningRates; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/manifest.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/manifest.json new file mode 100644 index 000000000000..844d692f6439 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/manifest.json @@ -0,0 +1,36 @@ +{ + "options": {}, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "src": [], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [] + } + ] +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/package.json new file mode 100644 index 000000000000..80efce55d631 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/learning-rates", + "version": "0.0.0", + "description": "SGD classification learning rate schedulers.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "learning rates", + "learning rate schedulers", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/test/test.js new file mode 100644 index 000000000000..76e6cb305328 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/learning-rates/test/test.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive; +var learningRates = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof learningRates, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a list of SGD classification learning rate schedulers', function test( t ) { + var expected; + var actual; + + expected = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' + ]; + actual = learningRates(); + + t.deepEqual( actual, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'attached to the main function is an `enum` method to return an object mapping learning rate schedulers to integer values for C inter-operation', function test( t ) { + var obj; + var o; + var i; + + t.strictEqual( hasOwnProp( learningRates, 'enum' ), true, 'has property' ); + t.strictEqual( typeof learningRates.enum, 'function', 'has method' ); + + obj = learningRates.enum(); + t.strictEqual( typeof obj, 'object', 'returns expected value' ); + + // List of values which should be supported... + o = [ + 'basic', + 'constant', + 'invscaling', + 'pegasos' + ]; + for ( i = 0; i < o.length; i++ ) { + t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); + } + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/README.md new file mode 100644 index 000000000000..55d309dfc269 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/README.md @@ -0,0 +1,121 @@ + + +# enum2str + +> Return the SGD classification loss function string associated with an SGD classification loss function enumeration constant. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var enum2str = require( '@stdlib/ml/base/sgd-classification/loss-function-enum2str' ); +``` + +#### enum2str( value ) + +Returns the SGD classification loss function string associated with an SGD classification loss function enumeration constant. + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); + +var v = str2enum( 'epsilon-insensitive' ); +// returns + +var s = enum2str( v ); +// returns 'epsilon-insensitive' +``` + +If unable to resolve an SGD classification loss function string, the function returns `null`. + +```javascript +var v = enum2str( -999999999 ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var enum2str = require( '@stdlib/ml/base/sgd-classification/loss-function-enum2str' ); + +var str = enum2str( str2enum( 'epsilon-insensitive' ) ); +// returns 'epsilon-insensitive' + +str = enum2str( str2enum( 'hinge' ) ); +// returns 'hinge' +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/benchmark/benchmark.js new file mode 100644 index 000000000000..a0a8ff730a79 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/benchmark/benchmark.js @@ -0,0 +1,62 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var pkg = require( './../package.json' ).name; +var enum2str = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + str2enum( 'epsilon-insensitive' ), + str2enum( 'hinge' ), + str2enum( 'huber' ), + str2enum( 'log' ), + str2enum( 'modified-huber' ), + str2enum( 'perceptron' ), + str2enum( 'squared-epsilon-insensitive' ), + str2enum( 'squared-error' ), + str2enum( 'squared-hinge' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = enum2str( values[ i%values.length ] ); + if ( typeof out !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( out ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/repl.txt new file mode 100644 index 000000000000..5910c47d09bc --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/repl.txt @@ -0,0 +1,23 @@ + +{{alias}}( value ) + Returns the SGD classification loss function string associated with an SGD + classification loss function enumeration constant. + + Parameters + ---------- + value: integer + Loss function enumeration constant. + + Returns + ------- + out: string|null + Loss function string. + + Examples + -------- + > var out = {{alias}}( {{alias:@stdlib/ml/base/sgd-classification/loss-function-str2enum}}( 'epsilon-insensitive' ) ) + 'epsilon-insensitive' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/types/index.d.ts new file mode 100644 index 000000000000..f63694a7bfd2 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/types/index.d.ts @@ -0,0 +1,41 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the SGD classification loss function string associated with an SGD classification loss function enumeration constant. +* +* @param value - enumeration constant +* @returns loss function string +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +* +* var v = str2enum( 'epsilon-insensitive' ); +* // returns +* +* var s = enum2str( v ); +* // returns 'epsilon-insensitive' +*/ +declare function enum2str( value: number ): string | null; + + +// EXPORTS // + +export = enum2str; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/types/test.ts new file mode 100644 index 000000000000..fe80992105ef --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/docs/types/test.ts @@ -0,0 +1,39 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import enum2str = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + enum2str( 0 ); // $ExpectType string | null +} + +// The compiler throws an error if not provided a number... +{ + enum2str( '10' ); // $ExpectError + enum2str( true ); // $ExpectError + enum2str( false ); // $ExpectError + enum2str( null ); // $ExpectError + enum2str( undefined ); // $ExpectError + enum2str( [] ); // $ExpectError + enum2str( {} ); // $ExpectError + enum2str( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/examples/index.js new file mode 100644 index 000000000000..1a4fd46eb551 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var enum2str = require( './../lib' ); + +var str = enum2str( str2enum( 'hinge' ) ); +console.log( str ); +// => 'hinge' + +str = enum2str( str2enum( 'epsilon-insensitive' ) ); +console.log( str ); +// => 'epsilon-insensitive' diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/lib/index.js new file mode 100644 index 000000000000..743279309015 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/lib/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the SGD classification loss function string associated with an SGD classification loss function enumeration constant. +* +* @module @stdlib/ml/base/sgd-classification/loss-function-enum2str +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +* var enum2str = require( '@stdlib/ml/base/sgd-classification/loss-function-enum2str' ); +* +* var v = str2enum( 'epsilon-insensitive' ); +* // returns +* +* var s = enum2str( v ); +* // returns 'epsilon-insensitive' +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/lib/main.js new file mode 100644 index 000000000000..6b0e3744a68d --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/lib/main.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var objectInverse = require( '@stdlib/object/inverse' ); +var enumeration = require( '@stdlib/ml/base/sgd-classification/loss-functions' ).enum; + + +// VARIABLES // + +var hash = objectInverse( enumeration(), { + 'duplicates': false +}); + + +// MAIN // + +/** +* Returns the SGD classification loss function string associated with an SGD classification loss function enumeration constant. +* +* @param {integer} value - loss function enumeration constant +* @returns {(string|null)} loss function string or null +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +* +* var v = str2enum( 'epsilon-insensitive' ); +* // returns +* +* var s = enum2str( v ); +* // returns 'epsilon-insensitive' +*/ +function enum2str( value ) { + var v = hash[ value ]; + return ( isString( v ) ) ? v : null; // note: we include this guard to prevent walking the prototype chain +} + + +// EXPORTS // + +module.exports = enum2str; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/package.json new file mode 100644 index 000000000000..d08959ad4ade --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/loss-function-enum2str", + "version": "0.0.0", + "description": "Return the SGD classification loss function string associated with an SGD classification loss function enumeration constant.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "loss function", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/test/test.js new file mode 100644 index 000000000000..3b79de34d98f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-enum2str/test/test.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var enum2str = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof enum2str, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the string associated with an enumeration constant', function test( t ) { + var i; + for ( i = 0; i < VALUES.length; i++ ) { + t.strictEqual( enum2str( str2enum( VALUES[ i ] ) ), VALUES[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve a string', function test( t ) { + var values; + var i; + + values = [ + -9999999, + -999999999, + -99999999999 + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( enum2str( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/README.md new file mode 100644 index 000000000000..d26bd3e15a33 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/README.md @@ -0,0 +1,124 @@ + + +# resolve + +> Return the enumeration constant associated with a supported SGD classification loss function value. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var resolve = require( '@stdlib/ml/base/sgd-classification/loss-function-resolve-enum' ); +``` + +#### resolve( value ) + +Returns the enumeration constant associated with a supported SGD classification loss function value. + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); + +var v = resolve( 'epsilon-insensitive' ); +// returns + +v = resolve( str2enum( 'hinge' ) ); +// returns +``` + +If unable to resolve an enumeration constant, the function returns `null`. + +```javascript +var v = resolve( 'beep' ); +// returns null +``` + +
+ + + + + +
+ +## Notes + +- Downstream consumers of this function should **not** rely on specific integer values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be used in an opaque manner. + +
+ + + + + +
+ +## Examples + + + +```javascript +var resolve = require( '@stdlib/ml/base/sgd-classification/loss-function-resolve-enum' ); + +var v = resolve( 'epsilon-insensitive' ); +// returns + +v = resolve( 'hinge' ); +// returns +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/benchmark/benchmark.js new file mode 100644 index 000000000000..577fc20c9315 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/benchmark/benchmark.js @@ -0,0 +1,95 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var resolve = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::string', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'number' ) { + b.fail( 'should return a number' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::integer', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + str2enum( 'epsilon-insensitive' ), + str2enum( 'hinge' ), + str2enum( 'huber' ), + str2enum( 'log' ), + str2enum( 'modified-huber' ), + str2enum( 'perceptron' ), + str2enum( 'squared-epsilon-insensitive' ), + str2enum( 'squared-error' ), + str2enum( 'squared-hinge' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'number' ) { + b.fail( 'should return a number' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/repl.txt new file mode 100644 index 000000000000..f7254f153648 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/repl.txt @@ -0,0 +1,29 @@ + +{{alias}}( value ) + Returns the enumeration constant associated with a supported SGD + classification loss function value. + + Downstream consumers of this function should *not* rely on specific integer + values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be + used in an opaque manner. + + Parameters + ---------- + value: any + Loss function value. + + Returns + ------- + out: integer|null + Enumeration constant. + + Examples + -------- + > var out = {{alias}}( 'epsilon-insensitive' ) + + > out = {{alias}}( {{alias:@stdlib/ml/base/sgd-classification/loss-function-str2enum}}( 'epsilon-insensitive' ) ) + + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/types/index.d.ts new file mode 100644 index 000000000000..66c8c54ac895 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/types/index.d.ts @@ -0,0 +1,40 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the enumeration constant associated with a supported SGD classification loss function value. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be used in an opaque manner. +* +* @param value - loss function value +* @returns enumeration constant +* +* @example +* var v = resolve( 'epsilon-insensitive' ); +* // returns +*/ +declare function resolve( value: any ): number | null; + + +// EXPORTS // + +export = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/types/test.ts new file mode 100644 index 000000000000..eab6893aab19 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/docs/types/test.ts @@ -0,0 +1,28 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import resolve = require( './index' ); + + +// TESTS // + +// The function returns a number or null... +{ + resolve( 0 ); // $ExpectType number | null + resolve( 'epsilon-insensitive' ); // $ExpectType number | null +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/examples/index.js new file mode 100644 index 000000000000..0d237af217d2 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var resolve = require( './../lib' ); + +var v = resolve( 'epsilon-insensitive' ); +console.log( v ); +// => + +v = resolve( 'hinge' ); +console.log( v ); +// => diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/lib/index.js new file mode 100644 index 000000000000..2ce77b01dd2c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the enumeration constant associated with a supported SGD classification loss function value. +* +* @module @stdlib/ml/base/sgd-classification/loss-function-resolve-enum +* +* @example +* var resolve = require( '@stdlib/ml/base/sgd-classification/loss-function-resolve-enum' ); +* +* var v = resolve( 'epsilon-insensitive' ); +* // returns +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/lib/main.js new file mode 100644 index 000000000000..8dbe87a62e52 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/lib/main.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var enum2str = require( '@stdlib/ml/base/sgd-classification/loss-function-enum2str' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); + + +// MAIN // + +/** +* Returns the enumeration constant associated with a supported SGD classification loss function value. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be used in an opaque manner. +* +* @param {*} value - loss function value +* @returns {(integer|null)} enumeration constant or null +* +* @example +* var v = resolve( 'epsilon-insensitive' ); +* // returns +*/ +function resolve( value ) { + var t = ( typeof value ); + if ( t === 'number' ) { + return ( enum2str( value ) ) ? value : null; + } + if ( t === 'string' ) { + return str2enum( value ); + } + return null; +} + + +// EXPORTS // + +module.exports = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/package.json new file mode 100644 index 000000000000..b0d757dd7042 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/loss-function-resolve-enum", + "version": "0.0.0", + "description": "Return the enumeration constant associated with a supported SGD classification loss function value.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "loss function", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/test/test.js new file mode 100644 index 000000000000..2464bd251eb4 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-enum/test/test.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var resolve = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof resolve, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the enumeration constant associated with an SGD classification loss function value', function test( t ) { + var v; + var i; + for ( i = 0; i < VALUES.length; i++ ) { + v = str2enum( VALUES[ i ] ); + t.strictEqual( resolve( VALUES[ i ] ), v, 'returns expected value' ); + t.strictEqual( resolve( v ), v, 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve an enumeration constant', function test( t ) { + var values; + var i; + + values = [ + 'beep', + 'boop', + 'foo', + 'bar', + -99999999, + -9999999999, + -9999999999999, + true, + false + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( resolve( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/README.md new file mode 100644 index 000000000000..64cee653c72a --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/README.md @@ -0,0 +1,121 @@ + + +# resolve + +> Return the loss function string associated with a supported SGD classification loss function value. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var resolve = require( '@stdlib/ml/base/sgd-classification/loss-function-resolve-str' ); +``` + +#### resolve( value ) + +Returns the loss function string associated with a supported SGD classification loss function value. + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); + +var v = resolve( 'hinge' ); +// returns 'hinge' + +v = resolve( str2enum( 'hinge' ) ); +// returns 'hinge' +``` + +If unable to resolve an SGD classification loss function string, the function returns `null`. + +```javascript +var v = resolve( 'beep' ); +// returns null +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var resolve = require( '@stdlib/ml/base/sgd-classification/loss-function-resolve-str' ); + +var v = resolve( str2enum( 'hinge' ) ); +// returns 'hinge' + +v = resolve( str2enum( 'epsilon-insensitive' ) ); +// returns 'epsilon-insensitive' +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/benchmark/benchmark.js new file mode 100644 index 000000000000..9d362c26154c --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/benchmark/benchmark.js @@ -0,0 +1,95 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isString = require( '@stdlib/assert/is-string' ).isPrimitive; +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var resolve = require( './../lib' ); + + +// MAIN // + +bench( format( '%s::string', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( out ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::integer', pkg ), function benchmark( b ) { + var values; + var out; + var i; + + values = [ + str2enum( 'epsilon-insensitive' ), + str2enum( 'hinge' ), + str2enum( 'huber' ), + str2enum( 'log' ), + str2enum( 'modified-huber' ), + str2enum( 'perceptron' ), + str2enum( 'squared-epsilon-insensitive' ), + str2enum( 'squared-error' ), + str2enum( 'squared-hinge' ) + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = resolve( values[ i%values.length ] ); + if ( typeof out !== 'string' ) { + b.fail( 'should return a string' ); + } + } + b.toc(); + if ( !isString( out ) ) { + b.fail( 'should return a string' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/repl.txt new file mode 100644 index 000000000000..53d6145da9e2 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/repl.txt @@ -0,0 +1,25 @@ + +{{alias}}( value ) + Returns the loss function string associated with a supported SGD + classification loss function value. + + Parameters + ---------- + value: any + Loss function value. + + Returns + ------- + out: string|null + Loss function string. + + Examples + -------- + > var out = {{alias}}( 'hinge' ) + 'hinge' + > out = {{alias}}( {{alias:@stdlib/ml/base/sgd-classification/loss-function-str2enum}}( 'hinge' ) ) + 'hinge' + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/types/index.d.ts new file mode 100644 index 000000000000..1ed717add44f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/types/index.d.ts @@ -0,0 +1,38 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the loss function string associated with a supported SGD classification loss function value. +* +* @param value - loss function value +* @returns loss function string or null +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +* +* var v = resolve( str2enum( 'hinge' ) ); +* // returns 'hinge' +*/ +declare function resolve( value: any ): string | null; + + +// EXPORTS // + +export = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/types/test.ts new file mode 100644 index 000000000000..524dc352b685 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/docs/types/test.ts @@ -0,0 +1,28 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import resolve = require( './index' ); + + +// TESTS // + +// The function returns a string or null... +{ + resolve( 0 ); // $ExpectType string | null + resolve( 'hinge' ); // $ExpectType string | null +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/examples/index.js new file mode 100644 index 000000000000..e2933a7a9983 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/examples/index.js @@ -0,0 +1,30 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var resolve = require( './../lib' ); + +var v = resolve( str2enum( 'hinge' ) ); +console.log( v ); +// => 'hinge' + +v = resolve( str2enum( 'epsilon-insensitive' ) ); +console.log( v ); +// => 'epsilon-insensitive' diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/lib/index.js new file mode 100644 index 000000000000..4e04b6ed33d1 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/lib/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the loss function string associated with a supported SGD classification loss function value. +* +* @module @stdlib/ml/base/sgd-classification/loss-function-resolve-str +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +* var resolve = require( '@stdlib/ml/base/sgd-classification/loss-function-resolve-str' ); +* +* var v = resolve( str2enum( 'hinge' ) ); +* // returns 'hinge' +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/lib/main.js new file mode 100644 index 000000000000..917c429c4e7f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/lib/main.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var enum2str = require( '@stdlib/ml/base/sgd-classification/loss-function-enum2str' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); + + +// MAIN // + +/** +* Returns the loss function string associated with a supported SGD classification loss function value. +* +* @param {*} value - loss function value +* @returns {(string|null)} loss function string or null +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +* +* var v = resolve( str2enum( 'hinge' ) ); +* // returns 'hinge' +*/ +function resolve( value ) { + var t = ( typeof value ); + if ( t === 'string' ) { + return ( str2enum( value ) === null ) ? null : value; + } + if ( t === 'number' ) { + return enum2str( value ); + } + return null; +} + + +// EXPORTS // + +module.exports = resolve; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/package.json new file mode 100644 index 000000000000..12c938f4785a --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/loss-function-resolve-str", + "version": "0.0.0", + "description": "Return the loss function string associated with a supported SGD classification loss function value.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "loss function", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/test/test.js new file mode 100644 index 000000000000..b25fa6f377ba --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-resolve-str/test/test.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +var resolve = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof resolve, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the string associated with an SGD classification loss function value', function test( t ) { + var v; + var i; + for ( i = 0; i < VALUES.length; i++ ) { + v = str2enum( VALUES[ i ] ); + t.strictEqual( resolve( VALUES[ i ] ), VALUES[ i ], 'returns expected value' ); + t.strictEqual( resolve( v ), VALUES[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve a string', function test( t ) { + var values; + var i; + + values = [ + 'beep', + 'boop', + 'foo', + 'bar', + -99999999, + -9999999999, + -9999999999999, + true, + false + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( resolve( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/README.md new file mode 100644 index 000000000000..3d32a52b2ca9 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/README.md @@ -0,0 +1,119 @@ + + +# str2enum + +> Return the enumeration constant associated with an SGD classification loss function string. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +``` + +#### str2enum( lossFunction ) + +Returns the enumeration constant associated with an SGD classification loss function string. + +```javascript +var v = str2enum( 'hinge' ); +// returns +``` + +If unable to resolve an enumeration constant, the function returns `null`. + +```javascript +var v = str2enum( 'beep' ); +// returns null +``` + +
+ + + + + +
+ +## Notes + +- Downstream consumers of this function should **not** rely on specific integer values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be used in an opaque manner. + +
+ + + + + +
+ +## Examples + + + +```javascript +var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); + +var v = str2enum( 'hinge' ); +// returns + +v = str2enum( 'epsilon-insensitive' ); +// returns +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/benchmark/benchmark.js new file mode 100644 index 000000000000..250a871eefda --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/benchmark/benchmark.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var pkg = require( './../package.json' ).name; +var str2enum = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var out; + var i; + + values = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' + ]; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = str2enum( values[ i%values.length ] ); + if ( typeof out !== 'number' ) { + b.fail( 'should return a number' ); + } + } + b.toc(); + if ( !isInteger( out ) ) { + b.fail( 'should return an integer' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/repl.txt new file mode 100644 index 000000000000..c0d45e78af0d --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/repl.txt @@ -0,0 +1,27 @@ + +{{alias}}( lossFunction ) + Returns the enumeration constant associated with an SGD classification loss + function string. + + Downstream consumers of this function should *not* rely on specific integer + values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be + used in an opaque manner. + + Parameters + ---------- + lossFunction: string + Loss function. + + Returns + ------- + out: integer|null + Enumeration constant. + + Examples + -------- + > var out = {{alias}}( 'hinge' ) + + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/types/index.d.ts new file mode 100644 index 000000000000..8f107a89ac95 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/types/index.d.ts @@ -0,0 +1,40 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the enumeration constant associated with an SGD classification loss function string. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be used in an opaque manner. +* +* @param lossFunction - loss function string +* @returns enumeration constant +* +* @example +* var v = str2enum( 'hinge' ); +* // returns +*/ +declare function str2enum( lossFunction: string ): number | null; + + +// EXPORTS // + +export = str2enum; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/types/test.ts new file mode 100644 index 000000000000..250ae7ed37c1 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/docs/types/test.ts @@ -0,0 +1,39 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import str2enum = require( './index' ); + + +// TESTS // + +// The function returns a number or null... +{ + str2enum( 'hinge' ); // $ExpectType number | null +} + +// The compiler throws an error if not provided a string... +{ + str2enum( 10 ); // $ExpectError + str2enum( true ); // $ExpectError + str2enum( false ); // $ExpectError + str2enum( null ); // $ExpectError + str2enum( undefined ); // $ExpectError + str2enum( [] ); // $ExpectError + str2enum( {} ); // $ExpectError + str2enum( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/examples/index.js new file mode 100644 index 000000000000..8c89d599d7d0 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/examples/index.js @@ -0,0 +1,29 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var str2enum = require( './../lib' ); + +var v = str2enum( 'hinge' ); +console.log( v ); +// => + +v = str2enum( 'epsilon-insensitive' ); +console.log( v ); +// => diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/lib/index.js new file mode 100644 index 000000000000..9d69cc925206 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/lib/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return the enumeration constant associated with an SGD classification loss function string. +* +* @module @stdlib/ml/base/sgd-classification/loss-function-str2enum +* +* @example +* var str2enum = require( '@stdlib/ml/base/sgd-classification/loss-function-str2enum' ); +* +* var v = str2enum( 'hinge' ); +* // returns +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/lib/main.js new file mode 100644 index 000000000000..258725703538 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/lib/main.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var enumeration = require( '@stdlib/ml/base/sgd-classification/loss-functions' ).enum; + + +// VARIABLES // + +var ENUM = enumeration(); + + +// MAIN // + +/** +* Returns the enumeration constant associated with an SGD classification loss function string. +* +* ## Notes +* +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `EPSILON_INSENSITIVE == 0`). Instead, the function should be used in an opaque manner. +* +* @param {string} lossFunction - loss function string +* @returns {(integer|null)} integer value or null +* +* @example +* var v = str2enum( 'hinge' ); +* // returns +*/ +function str2enum( lossFunction ) { + var v = ENUM[ lossFunction ]; + return ( isNumber( v ) ) ? v : null; // note: we include this guard to prevent walking the prototype chain +} + + +// EXPORTS // + +module.exports = str2enum; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/package.json new file mode 100644 index 000000000000..4065a1160e9e --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/loss-function-str2enum", + "version": "0.0.0", + "description": "Return the enumeration constant associated with an SGD classification loss function string.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "loss function", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/test/test.js new file mode 100644 index 000000000000..13f990390f30 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-function-str2enum/test/test.js @@ -0,0 +1,73 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var enum2str = require( '@stdlib/ml/base/sgd-classification/loss-function-enum2str' ); +var str2enum = require( './../lib' ); + + +// VARIABLES // + +var VALUES = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' +]; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof str2enum, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns the enumeration constant associated with a string', function test( t ) { + var i; + for ( i = 0; i < VALUES.length; i++ ) { + t.strictEqual( enum2str( str2enum( VALUES[ i ] ) ), VALUES[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function returns `null` if unable to resolve an enumeration constant', function test( t ) { + var values; + var i; + + values = [ + 'beep', + 'boop', + 'foo', + 'bar' + ]; + for ( i = 0; i < values.length; i++ ) { + t.strictEqual( str2enum( values[ i ] ), null, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/README.md b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/README.md new file mode 100644 index 000000000000..010419e81e15 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/README.md @@ -0,0 +1,200 @@ + + +# Loss functions + +> SGD classification loss functions. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var lossFunctions = require( '@stdlib/ml/base/sgd-classification/loss-functions' ); +``` + +#### lossFunctions() + +Returns a list of SGD classification loss functions. + +```javascript +var out = lossFunctions(); +// e.g., returns [ 'epsilon-insensitive', 'hinge', 'huber', 'log', 'modified-huber', 'perceptron', 'squared-epsilon-insensitive', 'squared-error', 'squared-hinge' ] +``` + +The output array contains the following loss functions: + +- `epsilon-insensitive`: penalty is the absolute value of the error whenever the absolute error exceeds epsilon and zero otherwise. +- `hinge`: hinge loss function. Corresponds to a soft-margin linear Support Vector Machine (SVM), which can handle non-linearly separable data. +- `huber`: squared-error loss for observations with error smaller than epsilon in magnitude, linear loss otherwise. Should be used in order to decrease the influence of outliers on the model fit. +- `log`: logistic loss function. Corresponds to Logistic Regression. +- `modified-huber`: Huber loss function variant for classification. +- `perceptron`: hinge loss function without a margin. Corresponds to the original perceptron by Rosenblatt (1957). +- `squared-epsilon-insensitive`: squared epsilon insensitive loss function. +- `squared-error`: squared error loss (i.e., the squared difference of the observed and fitted values). +- `squared-hinge`: squared hinge loss function SVM (L2-SVM). + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var contains = require( '@stdlib/array/base/assert/contains' ).factory; +var lossFunction = require( '@stdlib/ml/base/sgd-classification/loss-functions' ); + +var isLossFunction = contains( lossFunction() ); + +var bool = isLossFunction( 'hinge' ); +// returns true + +bool = isLossFunction( 'log' ); +// returns true + +bool = isLossFunction( 'beep' ); +// returns false +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/ml/base/sgd-classification/loss_functions.h" +``` + +#### STDLIB_ML_SGD_CLASSIFICATION_LOSS_FUNCTION + +An enumeration of SGD classification loss functions with the following fields: + +- **STDLIB_ML_SGD_CLASSIFICATION_EPSILON_INSENSITIVE**: penalty is the absolute value of the error whenever the absolute error exceeds epsilon and zero otherwise. +- **STDLIB_ML_SGD_CLASSIFICATION_HINGE**: corresponds to a soft-margin linear Support Vector Machine (SVM), which can handle non-linearly separable data. +- **STDLIB_ML_SGD_CLASSIFICATION_HUBER**: squared-error loss for observations with error smaller than epsilon in magnitude, linear loss otherwise. +- **STDLIB_ML_SGD_CLASSIFICATION_LOG**: corresponds to Logistic Regression. +- **STDLIB_ML_SGD_CLASSIFICATION_MODIFIED_HUBER**: Huber loss function variant for classification. +- **STDLIB_ML_SGD_CLASSIFICATION_PERCEPTRON**: corresponds to the original perceptron by Rosenblatt (1957). +- **STDLIB_ML_SGD_CLASSIFICATION_SQUARED_EPSILON_INSENSITIVE**: squared epsilon insensitive loss function. +- **STDLIB_ML_SGD_CLASSIFICATION_SQUARED_ERROR**: squared difference of the observed and fitted values. +- **STDLIB_ML_SGD_CLASSIFICATION_SQUARED_HINGE**: squared hinge loss function SVM (L2-SVM). + +```c +#include "stdlib/ml/base/sgd-classification/loss_functions.h" + +const enum STDLIB_ML_SGD_CLASSIFICATION_LOSS_FUNCTION v = STDLIB_ML_SGD_CLASSIFICATION_HINGE; +``` + +
+ + + + + +
+ +### Notes + +- Enumeration constants should be considered opaque values, and one should **not** rely on specific integer values. + +
+ + + + + +
+ +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/benchmark/benchmark.js new file mode 100644 index 000000000000..fc9b818bd1cd --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/benchmark/benchmark.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isStringArray = require( '@stdlib/assert/is-string-array' ).primitives; +var pkg = require( './../package.json' ).name; +var lossFunctions = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var out; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + out = lossFunctions(); + if ( out.length < 2 ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isStringArray( out ) ) { + b.fail( 'should return an array of strings' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/repl.txt new file mode 100644 index 000000000000..3ee9a26c327a --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/repl.txt @@ -0,0 +1,35 @@ + +{{alias}}() + Returns a list of SGD classification loss functions. + + The output array contains the following loss functions: + + - epsilon-insensitive: penalty is the absolute value of the error whenever + the absolute error exceeds epsilon and zero otherwise. + - hinge: hinge loss function. Corresponds to a soft-margin linear Support + Vector Machine (SVM), which can handle non-linearly separable data. + - huber: squared-error loss for observations with error smaller than epsilon + in magnitude, linear loss otherwise. Should be used in order to decrease the + influence of outliers on the model fit. + - log: logistic loss function. Corresponds to Logistic Regression. + - modified-huber: Huber loss function variant for classification. + - perceptron: hinge loss function without a margin. Corresponds to the + original perceptron by Rosenblatt (1957). + - squared-epsilon-insensitive: squared epsilon insensitive loss function. + - squared-error: squared error loss (i.e., the squared difference of the + observed and fitted values). + - squared-hinge: squared hinge loss function SVM (L2-SVM). + + Returns + ------- + out: Array + List of loss functions. + + Examples + -------- + > var out = {{alias}}() + [...] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/types/index.d.ts new file mode 100644 index 000000000000..ffe179e81b20 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/types/index.d.ts @@ -0,0 +1,35 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns a list of SGD classification loss functions. +* +* @returns list of loss functions +* +* @example +* var list = lossFunctions(); +* // e.g., returns [ 'epsilon-insensitive', 'hinge', 'huber', 'log', 'modified-huber', 'perceptron', 'squared-epsilon-insensitive', 'squared-error', 'squared-hinge' ] +*/ +declare function lossFunctions(): Array; + + +// EXPORTS // + +export = lossFunctions; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/types/test.ts new file mode 100644 index 000000000000..6c51642dacaa --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/docs/types/test.ts @@ -0,0 +1,32 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import lossFunctions = require( './index' ); + + +// TESTS // + +// The function returns an array of strings... +{ + lossFunctions(); // $ExpectType string[] +} + +// The compiler throws an error if the function is provided any arguments... +{ + lossFunctions( 9 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/examples/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/examples/index.js new file mode 100644 index 000000000000..1fa9e2f61bbf --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/examples/index.js @@ -0,0 +1,36 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var contains = require( '@stdlib/array/base/assert/contains' ).factory; +var lossFunctions = require( './../lib' ); + +var isLossFunction = contains( lossFunctions() ); + +var bool = isLossFunction( 'hinge' ); +console.log( bool ); +// => true + +bool = isLossFunction( 'log' ); +console.log( bool ); +// => true + +bool = isLossFunction( 'beep' ); +console.log( bool ); +// => false diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/include/stdlib/ml/base/sgd-classification/loss_functions.h b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/include/stdlib/ml/base/sgd-classification/loss_functions.h new file mode 100644 index 000000000000..fe1820bcc94f --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/include/stdlib/ml/base/sgd-classification/loss_functions.h @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#ifndef STDLIB_ML_BASE_SGD_CLASSIFICATION_LOSS_FUNCTIONS_H +#define STDLIB_ML_BASE_SGD_CLASSIFICATION_LOSS_FUNCTIONS_H + +/** +* Enumeration of SGD classification loss functions. +*/ +enum STDLIB_ML_SGD_CLASSIFICATION_LOSS_FUNCTION { + // Penalty is the absolute value of the error whenever the absolute error exceeds epsilon and zero otherwise: + STDLIB_ML_SGD_CLASSIFICATION_EPSILON_INSENSITIVE = 0, + + // Corresponds to a soft-margin linear Support Vector Machine (SVM), which can handle non-linearly separable data: + STDLIB_ML_SGD_CLASSIFICATION_HINGE, + + // Squared-error loss for observations with error smaller than epsilon in magnitude, linear loss otherwise: + STDLIB_ML_SGD_CLASSIFICATION_HUBER, + + // Corresponds to Logistic Regression: + STDLIB_ML_SGD_CLASSIFICATION_LOG, + + // Huber loss function variant for classification: + STDLIB_ML_SGD_CLASSIFICATION_MODIFIED_HUBER, + + // Corresponds to the original perceptron by Rosenblatt (1957): + STDLIB_ML_SGD_CLASSIFICATION_PERCEPTRON, + + // Squared epsilon insensitive loss function: + STDLIB_ML_SGD_CLASSIFICATION_SQUARED_EPSILON_INSENSITIVE, + + // Squared difference of the observed and fitted values: + STDLIB_ML_SGD_CLASSIFICATION_SQUARED_ERROR, + + // Squared hinge loss function SVM (L2-SVM): + STDLIB_ML_SGD_CLASSIFICATION_SQUARED_HINGE +}; + +#endif // !STDLIB_ML_BASE_SGD_CLASSIFICATION_LOSS_FUNCTIONS_H diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/data.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/data.json new file mode 100644 index 000000000000..7398567751ce --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/data.json @@ -0,0 +1,11 @@ +[ + "epsilon-insensitive", + "hinge", + "huber", + "log", + "modified-huber", + "perceptron", + "squared-epsilon-insensitive", + "squared-error", + "squared-hinge" +] diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/enum.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/enum.js new file mode 100644 index 000000000000..c1171c01f482 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/enum.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns an object mapping supported loss functions to integer values for purposes of C inter-operation. +* +* ## Notes +* +* - Downstream consumers of this mapping should **not** rely on specific integer values (e.g., `HINGE == 0`). Instead, the object should be used in an opaque manner. +* - The main purpose of this function is JavaScript and C inter-operation. +* +* @returns {Object} object mapping supported loss functions to integer values +* +* @example +* var table = enumerated(); +* // returns +*/ +function enumerated() { + // NOTE: the following should match the C `loss_functions.h` enumeration!!!! + return { + // Penalty is the absolute value of the error whenever the absolute error exceeds epsilon and zero otherwise: + 'epsilon-insensitive': 0, + + // Corresponds to a soft-margin linear Support Vector Machine (SVM), which can handle non-linearly separable data: + 'hinge': 1, + + // Squared-error loss for observations with error smaller than epsilon in magnitude, linear loss otherwise: + 'huber': 2, + + // Corresponds to Logistic Regression: + 'log': 3, + + // Huber loss function variant for classification: + 'modified-huber': 4, + + // Corresponds to the original perceptron by Rosenblatt (1957): + 'perceptron': 5, + + // Squared epsilon insensitive loss function: + 'squared-epsilon-insensitive': 6, + + // Squared difference of the observed and fitted values: + 'squared-error': 7, + + // Squared hinge loss function SVM (L2-SVM): + 'squared-hinge': 8 + }; +} + + +// EXPORTS // + +module.exports = enumerated; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/index.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/index.js new file mode 100644 index 000000000000..01f578cb39f1 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/index.js @@ -0,0 +1,47 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a list of SGD classification loss functions. +* +* @module @stdlib/ml/base/sgd-classification/loss-functions +* +* @example +* var lossFunctions = require( '@stdlib/ml/base/sgd-classification/loss-functions' ); +* +* var list = lossFunctions(); +* // e.g., returns [ 'epsilon-insensitive', 'hinge', 'huber', 'log', 'modified-huber', 'perceptron', 'squared-epsilon-insensitive', 'squared-error', 'squared-hinge' ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var enumeration = require( './enum.js' ); + + +// MAIN // + +setReadOnly( main, 'enum', enumeration ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/main.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/main.js new file mode 100644 index 000000000000..8b5f84f33291 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/lib/main.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var DATA = require( './data.json' ); + + +// MAIN // + +/** +* Returns a list of SGD classification loss functions. +* +* @returns {Array} list of loss functions +* +* @example +* var list = lossFunctions(); +* // e.g., returns [ 'epsilon-insensitive', 'hinge', 'huber', 'log', 'modified-huber', 'perceptron', 'squared-epsilon-insensitive', 'squared-error', 'squared-hinge' ] +*/ +function lossFunctions() { + return DATA.slice(); +} + + +// EXPORTS // + +module.exports = lossFunctions; diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/manifest.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/manifest.json new file mode 100644 index 000000000000..844d692f6439 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/manifest.json @@ -0,0 +1,36 @@ +{ + "options": {}, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "src": [], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [] + } + ] +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/package.json b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/package.json new file mode 100644 index 000000000000..8fb42101d6a1 --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/ml/base/sgd-classification/loss-functions", + "version": "0.0.0", + "description": "SGD classification loss functions.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "ml", + "machine", + "learning", + "sgd classification", + "loss functions", + "utilities", + "utility", + "utils", + "util", + "enum" + ], + "__stdlib__": {} +} diff --git a/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/test/test.js b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/test/test.js new file mode 100644 index 000000000000..e8572666efbc --- /dev/null +++ b/lib/node_modules/@stdlib/ml/base/sgd-classification/loss-functions/test/test.js @@ -0,0 +1,87 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive; +var lossFunctions = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof lossFunctions, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a list of SGD classification loss functions', function test( t ) { + var expected; + var actual; + + expected = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' + ]; + actual = lossFunctions(); + + t.deepEqual( actual, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'attached to the main function is an `enum` method to return an object mapping loss functions to integer values for C inter-operation', function test( t ) { + var obj; + var o; + var i; + + t.strictEqual( hasOwnProp( lossFunctions, 'enum' ), true, 'has property' ); + t.strictEqual( typeof lossFunctions.enum, 'function', 'has method' ); + + obj = lossFunctions.enum(); + t.strictEqual( typeof obj, 'object', 'returns expected value' ); + + // List of values which should be supported... + o = [ + 'epsilon-insensitive', + 'hinge', + 'huber', + 'log', + 'modified-huber', + 'perceptron', + 'squared-epsilon-insensitive', + 'squared-error', + 'squared-hinge' + ]; + for ( i = 0; i < o.length; i++ ) { + t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); + } + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv index 178d61afac86..abae886dd175 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.csv @@ -1074,7 +1074,7 @@ base.strided.dmeanstdevpn,"@stdlib/stats/strided/dmeanstdevpn" base.strided.dmeanvar,"@stdlib/stats/strided/dmeanvar" base.strided.dmeanvarpn,"@stdlib/stats/strided/dmeanvarpn" base.strided.dmeanwd,"@stdlib/stats/strided/dmeanwd" -base.strided.dmediansorted,"@stdlib/stats/strided/dmediansorted" +base.strided.dmedianSorted,"@stdlib/stats/strided/dmedian-sorted" base.strided.dmidrange,"@stdlib/stats/strided/dmidrange" base.strided.dmin,"@stdlib/stats/strided/dmin" base.strided.dminabs,"@stdlib/stats/strided/dminabs" @@ -1997,6 +1997,7 @@ INT32_NUM_BYTES,"@stdlib/constants/int32/num-bytes" Int32Array,"@stdlib/array/int32" Int32Matrix,"@stdlib/ndarray/matrix/int32" Int32Vector,"@stdlib/ndarray/vector/int32" +Int64,"@stdlib/number/int64/ctor" IS_BIG_ENDIAN,"@stdlib/assert/is-big-endian" IS_BROWSER,"@stdlib/assert/is-browser" IS_DARWIN,"@stdlib/assert/is-darwin" diff --git a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json index a23c71053b21..161add925776 100644 --- a/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2pkg/data/data.json @@ -1 +1 @@ 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echet.kurtosis":"@stdlib/stats/base/dists/frechet/kurtosis","base.dists.frechet.logcdf":"@stdlib/stats/base/dists/frechet/logcdf","base.dists.frechet.logpdf":"@stdlib/stats/base/dists/frechet/logpdf","base.dists.frechet.mean":"@stdlib/stats/base/dists/frechet/mean","base.dists.frechet.median":"@stdlib/stats/base/dists/frechet/median","base.dists.frechet.mode":"@stdlib/stats/base/dists/frechet/mode","base.dists.frechet.pdf":"@stdlib/stats/base/dists/frechet/pdf","base.dists.frechet.quantile":"@stdlib/stats/base/dists/frechet/quantile","base.dists.frechet.skewness":"@stdlib/stats/base/dists/frechet/skewness","base.dists.frechet.stdev":"@stdlib/stats/base/dists/frechet/stdev","base.dists.frechet.variance":"@stdlib/stats/base/dists/frechet/variance","base.dists.gamma.cdf":"@stdlib/stats/base/dists/gamma/cdf","base.dists.gamma.entropy":"@stdlib/stats/base/dists/gamma/entropy","base.dists.gamma.Gamma":"@stdlib/stats/base/dists/gamma/ctor","base.dists.gamma.kurtosis":"@stdlib/stats/base/dists/gamma/kurtosis","base.dists.gamma.logcdf":"@stdlib/stats/base/dists/gamma/logcdf","base.dists.gamma.logpdf":"@stdlib/stats/base/dists/gamma/logpdf","base.dists.gamma.mean":"@stdlib/stats/base/dists/gamma/mean","base.dists.gamma.mgf":"@stdlib/stats/base/dists/gamma/mgf","base.dists.gamma.mode":"@stdlib/stats/base/dists/gamma/mode","base.dists.gamma.pdf":"@stdlib/stats/base/dists/gamma/pdf","base.dists.gamma.quantile":"@stdlib/stats/base/dists/gamma/quantile","base.dists.gamma.skewness":"@stdlib/stats/base/dists/gamma/skewness","base.dists.gamma.stdev":"@stdlib/stats/base/dists/gamma/stdev","base.dists.gamma.variance":"@stdlib/stats/base/dists/gamma/variance","base.dists.geometric.cdf":"@stdlib/stats/base/dists/geometric/cdf","base.dists.geometric.entropy":"@stdlib/stats/base/dists/geometric/entropy","base.dists.geometric.Geometric":"@stdlib/stats/base/dists/geometric/ctor","base.dists.geometric.kurtosis":"@stdlib/stats/base/dists/geometric/kurtosis","base.dists.geometric.logcdf":"@stdlib/stats/base/dists/geometric/logcdf","base.dists.geometric.logpmf":"@stdlib/stats/base/dists/geometric/logpmf","base.dists.geometric.mean":"@stdlib/stats/base/dists/geometric/mean","base.dists.geometric.median":"@stdlib/stats/base/dists/geometric/median","base.dists.geometric.mgf":"@stdlib/stats/base/dists/geometric/mgf","base.dists.geometric.mode":"@stdlib/stats/base/dists/geometric/mode","base.dists.geometric.pmf":"@stdlib/stats/base/dists/geometric/pmf","base.dists.geometric.quantile":"@stdlib/stats/base/dists/geometric/quantile","base.dists.geometric.skewness":"@stdlib/stats/base/dists/geometric/skewness","base.dists.geometric.stdev":"@stdlib/stats/base/dists/geometric/stdev","base.dists.geometric.variance":"@stdlib/stats/base/dists/geometric/variance","base.dists.gumbel.cdf":"@stdlib/stats/base/dists/gumbel/cdf","base.dists.gumbel.entropy":"@stdlib/stats/base/dists/gumbel/entropy","base.dists.gumbel.Gumbel":"@stdlib/stats/base/dists/gumbel/ctor","base.dists.gumbel.kurtosis":"@stdlib/stats/base/dists/gumbel/kurtosis","base.dists.gumbel.logcdf":"@stdlib/stats/base/dists/gumbel/logcdf","base.dists.gumbel.logpdf":"@stdlib/stats/base/dists/gumbel/logpdf","base.dists.gumbel.mean":"@stdlib/stats/base/dists/gumbel/mean","base.dists.gumbel.median":"@stdlib/stats/base/dists/gumbel/median","base.dists.gumbel.mgf":"@stdlib/stats/base/dists/gumbel/mgf","base.dists.gumbel.mode":"@stdlib/stats/base/dists/gumbel/mode","base.dists.gumbel.pdf":"@stdlib/stats/base/dists/gumbel/pdf","base.dists.gumbel.quantile":"@stdlib/stats/base/dists/gumbel/quantile","base.dists.gumbel.skewness":"@stdlib/stats/base/dists/gumbel/skewness","base.dists.gumbel.stdev":"@stdlib/stats/base/dists/gumbel/stdev","base.dists.gumbel.variance":"@stdlib/stats/base/dists/gumbel/variance","base.dists.hypergeometric.cdf":"@stdlib/stats/base/dists/hypergeometric/cdf","base.dists.hypergeometric.Hypergeometric":"@stdlib/stats/base/dists/hypergeometric/ctor","base.dists.hypergeometric.kurtosis":"@stdlib/stats/base/dists/hypergeometric/kurtosis","base.dists.hypergeometric.logpmf":"@stdlib/stats/base/dists/hypergeometric/logpmf","base.dists.hypergeometric.mean":"@stdlib/stats/base/dists/hypergeometric/mean","base.dists.hypergeometric.mode":"@stdlib/stats/base/dists/hypergeometric/mode","base.dists.hypergeometric.pmf":"@stdlib/stats/base/dists/hypergeometric/pmf","base.dists.hypergeometric.quantile":"@stdlib/stats/base/dists/hypergeometric/quantile","base.dists.hypergeometric.skewness":"@stdlib/stats/base/dists/hypergeometric/skewness","base.dists.hypergeometric.stdev":"@stdlib/stats/base/dists/hypergeometric/stdev","base.dists.hypergeometric.variance":"@stdlib/stats/base/dists/hypergeometric/variance","base.dists.invgamma.cdf":"@stdlib/stats/base/dists/invgamma/cdf","base.dists.invgamma.entropy":"@stdlib/stats/base/dists/invgamma/entropy","base.dists.invgamma.InvGamma":"@stdlib/stats/base/dists/invgamma/ctor","base.dists.invgamma.kurtosis":"@stdlib/stats/base/dists/invgamma/kurtosis","base.dists.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/ops/sub","strided.subBy":"@stdlib/math/strided/ops/sub-by","strided.trunc":"@stdlib/math/strided/special/trunc","stridedarray2iterator":"@stdlib/array/to-strided-iterator","stridedArrayStream":"@stdlib/streams/node/from-strided-array","string2buffer":"@stdlib/buffer/from-string","structFactory":"@stdlib/dstructs/struct","sub2ind":"@stdlib/ndarray/sub2ind","substringAfter":"@stdlib/string/substring-after","substringAfterLast":"@stdlib/string/substring-after-last","substringBefore":"@stdlib/string/substring-before","substringBeforeLast":"@stdlib/string/substring-before-last","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-multi-hop-sensor-network","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"@stdlib/datasets/suthaharan-single-hop-sensor-network","Symbol":"@stdlib/symbol/ctor","tabulate":"@stdlib/utils/tabulate","tabulateBy":"@stdlib/utils/tabulate-by","tabulateByAsync":"@stdlib/utils/async/tabulate-by","thunk":"@stdlib/function/thunk","tic":"@stdlib/time/tic","timeit":"@stdlib/utils/timeit","tmpdir":"@stdlib/os/tmpdir","toc":"@stdlib/time/toc","tokenize":"@stdlib/nlp/tokenize","transformStream":"@stdlib/streams/node/transform","trim":"@stdlib/string/trim","trues":"@stdlib/ndarray/trues","truesLike":"@stdlib/ndarray/trues-like","truncate":"@stdlib/string/truncate","truncateMiddle":"@stdlib/string/truncate-middle","trycatch":"@stdlib/utils/try-catch","trycatchAsync":"@stdlib/utils/async/try-catch","tryFunction":"@stdlib/utils/try-function","tryRequire":"@stdlib/utils/try-require","trythen":"@stdlib/utils/try-then","trythenAsync":"@stdlib/utils/async/try-then","ttest":"@stdlib/stats/ttest","ttest2":"@stdlib/stats/ttest2","TWO_PI":"@stdlib/constants/float64/two-pi","typedarray":"@stdlib/array/typed","typedarray2json":"@stdlib/array/to-json","typedarrayCtors":"@stdlib/array/typed-ctors","typedarrayDataTypes":"@stdlib/array/typed-dtypes","typedarraypool":"@stdlib/array/pool","typemax":"@stdlib/utils/type-max","typemin":"@stdlib/utils/type-min","typeOf":"@stdlib/utils/type-of","UINT8_MAX":"@stdlib/constants/uint8/max","UINT8_NUM_BYTES":"@stdlib/constants/uint8/num-bytes","Uint8Array":"@stdlib/array/uint8","Uint8ClampedArray":"@stdlib/array/uint8c","Uint8ClampedVector":"@stdlib/ndarray/vector/uint8c","Uint8Vector":"@stdlib/ndarray/vector/uint8","UINT16_MAX":"@stdlib/constants/uint16/max","UINT16_NUM_BYTES":"@stdlib/constants/uint16/num-bytes","Uint16Array":"@stdlib/array/uint16","Uint16Vector":"@stdlib/ndarray/vector/uint16","UINT32_MAX":"@stdlib/constants/uint32/max","UINT32_NUM_BYTES":"@stdlib/constants/uint32/num-bytes","Uint32Array":"@stdlib/array/uint32","Uint32Vector":"@stdlib/ndarray/vector/uint32","Uint64":"@stdlib/number/uint64/ctor","umask":"@stdlib/process/umask","uncapitalize":"@stdlib/string/uncapitalize","uncapitalizeKeys":"@stdlib/object/uncapitalize-keys","uncurry":"@stdlib/utils/uncurry","uncurryRight":"@stdlib/utils/uncurry-right","UNICODE_MAX":"@stdlib/constants/unicode/max","UNICODE_MAX_BMP":"@stdlib/constants/unicode/max-bmp","UnicodeColumnChartSparkline":"@stdlib/plot/sparklines/unicode/column","UnicodeLineChartSparkline":"@stdlib/plot/sparklines/unicode/line","UnicodeSparkline":"@stdlib/plot/sparklines/unicode","UnicodeTristateChartSparkline":"@stdlib/plot/sparklines/unicode/tristate","UnicodeUpDownChartSparkline":"@stdlib/plot/sparklines/unicode/up-down","UnicodeWinLossChartSparkline":"@stdlib/plot/sparklines/unicode/win-loss","unlink":"@stdlib/fs/unlink","unshift":"@stdlib/utils/unshift","until":"@stdlib/utils/until","untilAsync":"@stdlib/utils/async/until","untilEach":"@stdlib/utils/until-each","untilEachRight":"@stdlib/utils/until-each-right","unzip":"@stdlib/utils/unzip","uppercase":"@stdlib/string/uppercase","uppercaseKeys":"@stdlib/object/uppercase-keys","US_STATES_ABBR":"@stdlib/datasets/us-states-abbr","US_STATES_CAPITALS":"@stdlib/datasets/us-states-capitals","US_STATES_CAPITALS_NAMES":"@stdlib/datasets/us-states-capitals-names","US_STATES_NAMES":"@stdlib/datasets/us-states-names","US_STATES_NAMES_CAPITALS":"@stdlib/datasets/us-states-names-capitals","utf16ToUTF8Array":"@stdlib/string/utf16-to-utf8-array","vartest":"@stdlib/stats/vartest","vector":"@stdlib/ndarray/vector/ctor","waterfall":"@stdlib/utils/async/series-waterfall","WebAssemblyMemory":"@stdlib/wasm/memory","whileAsync":"@stdlib/utils/async/while","whileEach":"@stdlib/utils/while-each","whileEachRight":"@stdlib/utils/while-each-right","whilst":"@stdlib/utils/while","wilcoxon":"@stdlib/stats/wilcoxon","writableProperties":"@stdlib/utils/writable-properties","writablePropertiesIn":"@stdlib/utils/writable-properties-in","writablePropertyNames":"@stdlib/utils/writable-property-names","writablePropertyNamesIn":"@stdlib/utils/writable-property-names-in","writablePropertySymbols":"@stdlib/utils/writable-property-symbols","writablePropertySymbolsIn":"@stdlib/utils/writable-property-symbols-in","writeFile":"@stdlib/fs/write-file","zip":"@stdlib/utils/zip","ztest":"@stdlib/stats/ztest","ztest2":"@stdlib/stats/ztest2"} diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv index e1284dfab83d..5c522c0cfd94 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.csv @@ -1074,7 +1074,7 @@ base.strided.dmeanstdevpn,"base.strided.dmeanpn,base.strided.dmeanstdev,base.str base.strided.dmeanvar,"base.strided.dmean,base.strided.dvariance" base.strided.dmeanvarpn,"base.strided.dmeanpn,base.strided.dmeanstdevpn,base.strided.dmeanvar,base.strided.dvariancepn" base.strided.dmeanwd,"base.strided.dmean,base.strided.dnanmeanwd,base.strided.meanwd,base.strided.smeanwd" -base.strided.dmediansorted,"base.strided.dmean,base.strided.mediansorted,base.strided.smediansorted" +base.strided.dmedianSorted,"base.strided.dmean,base.strided.mediansorted,base.strided.smediansorted" base.strided.dmidrange,"base.strided.dmax,base.strided.dmean,base.strided.dmin,base.strided.drange,base.strided.smidrange" base.strided.dmin,"base.strided.dmax,base.strided.dnanmin,base.strided.min,base.strided.smin" base.strided.dminabs,"base.strided.dmin,base.strided.dmaxabs,base.strided.dnanminabs,base.strided.minabs,base.strided.sminabs" @@ -1252,7 +1252,7 @@ base.strided.meanors,"base.strided.dmeanors,base.strided.mean,base.strided.nanme base.strided.meanpn,"base.strided.dmeanpn,base.strided.mean,base.strided.nanmeanpn,base.strided.smeanpn" base.strided.meanpw,"base.strided.dmeanpw,base.strided.mean,base.strided.smeanpw" base.strided.meanwd,"base.strided.dmeanwd,base.strided.mean,base.strided.nanmeanwd,base.strided.smeanwd" -base.strided.mediansorted,"base.strided.dmediansorted,base.strided.mean,base.strided.smediansorted" +base.strided.mediansorted,"base.strided.dmedianSorted,base.strided.mean,base.strided.smediansorted" base.strided.metaDataProps,"" base.strided.min,"base.strided.dmin,base.strided.max,base.strided.nanmin,base.strided.smin" base.strided.minabs,"base.strided.dminabs,base.strided.maxabs,base.strided.min,base.strided.nanminabs,base.strided.sminabs" @@ -1355,7 +1355,7 @@ base.strided.smeanors,"base.strided.dmeanors,base.strided.meanors,base.strided.s base.strided.smeanpn,"base.strided.dmeanpn,base.strided.meanpn,base.strided.smean,base.strided.snanmeanpn" base.strided.smeanpw,"base.strided.dmeanpw,base.strided.meanpw,base.strided.smean" base.strided.smeanwd,"base.strided.dmeanwd,base.strided.meanwd,base.strided.smean,base.strided.snanmeanwd" -base.strided.smediansorted,"base.strided.dmediansorted,base.strided.mediansorted,base.strided.smean" +base.strided.smediansorted,"base.strided.dmedianSorted,base.strided.mediansorted,base.strided.smean" base.strided.smidrange,"base.strided.dmidrange,base.strided.smax,base.strided.smean,base.strided.smin,base.strided.srange" base.strided.smin,"base.strided.dmin,base.strided.min,base.strided.smax,base.strided.snanmin" base.strided.sminabs,"base.strided.dminabs,base.strided.minabs,base.strided.smaxabs,base.strided.smin,base.strided.snanminabs" @@ -1997,6 +1997,7 @@ INT32_NUM_BYTES,"INT16_NUM_BYTES,INT8_NUM_BYTES,UINT32_NUM_BYTES" Int32Array,"ArrayBuffer,Float32Array,Float64Array,Int16Array,Int8Array,Uint16Array,Uint32Array,Uint8Array,Uint8ClampedArray" Int32Matrix,"Float64Matrix,Float32Matrix,Complex128Matrix,Complex64Matrix,matrix,Int32Vector,ndarray" Int32Vector,"Float64Vector,Float32Vector,Int16Vector,Int8Vector,Uint8Vector,Uint16Vector,Uint32Vector,Uint8ClampedVector,Complex128Vector,Complex64Vector,BooleanVector,vector,Int32Matrix,ndarray" +Int64,"BigInt,Number,Uint64" IS_BIG_ENDIAN,"IS_LITTLE_ENDIAN" IS_BROWSER,"" IS_DARWIN,"" @@ -3162,7 +3163,7 @@ UINT32_MAX,"INT32_MAX" UINT32_NUM_BYTES,"INT32_NUM_BYTES,UINT16_NUM_BYTES,UINT8_NUM_BYTES" Uint32Array,"ArrayBuffer,Float32Array,Float64Array,Int16Array,Int32Array,Int8Array,Uint16Array,Uint8Array,Uint8ClampedArray" Uint32Vector,"Float64Vector,Float32Vector,Int16Vector,Int32Vector,Int8Vector,Uint16Vector,Uint8Vector,Uint8ClampedVector,Complex128Vector,Complex64Vector,BooleanVector,vector,ndarray" -Uint64,"Number" +Uint64,"BigInt,Number,Int64" umask,"" uncapitalize,"capitalize,lowercase" uncapitalizeKeys,"capitalizeKeys,lowercaseKeys" diff --git a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json b/lib/node_modules/@stdlib/namespace/alias2related/data/data.json index 4e0096eb9557..40bed40c1214 100644 --- a/lib/node_modules/@stdlib/namespace/alias2related/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2related/data/data.json @@ -1 +1 @@ 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isquare","random.chisquare"],"base.random.cosine":["random.array.cosine","random.iterators.cosine","random.streams.cosine","random.cosine"],"base.random.discreteUniform":["random.array.discreteUniform","random.iterators.discreteUniform","random.streams.discreteUniform","random.discreteUniform"],"base.random.erlang":["random.array.erlang","random.iterators.erlang","random.streams.erlang","random.erlang"],"base.random.exponential":["random.array.exponential","random.iterators.exponential","random.streams.exponential","random.exponential"],"base.random.f":["random.array.f","random.iterators.f","random.streams.f","random.f"],"base.random.frechet":["random.array.frechet","random.iterators.frechet","random.streams.frechet","random.frechet"],"base.random.gamma":["random.array.gamma","random.iterators.gamma","random.streams.gamma","random.gamma"],"base.random.geometric":["random.array.geometric","random.iterators.geometric","random.streams.geometric","random.geometric"],"base.random.gumbel":["random.array.gumbel","random.iterators.gumbel","random.streams.gumbel","random.gumbel"],"base.random.hypergeometric":["random.array.hypergeometric","random.iterators.hypergeometric","random.streams.hypergeometric","random.hypergeometric"],"base.random.improvedZiggurat":["random.iterators.improvedZiggurat","random.streams.improvedZiggurat"],"base.random.invgamma":["random.array.invgamma","random.iterators.invgamma","random.streams.invgamma","random.invgamma"],"base.random.kumaraswamy":["random.array.kumaraswamy","random.iterators.kumaraswamy","random.streams.kumaraswamy","random.kumaraswamy"],"base.random.laplace":["random.array.laplace","random.iterators.laplace","random.streams.laplace","random.laplace"],"base.random.levy":["random.array.levy","random.iterators.levy","random.streams.levy","random.levy"],"base.random.logistic":["random.array.logistic","random.iterators.logistic","random.streams.logistic","random.logistic"],"base.random.lognormal":["random.array.lognormal","random.iterators.lognormal","random.streams.lognormal","random.lognormal"],"base.random.minstd":["random.array.minstd","random.iterators.minstd","random.streams.minstd","base.random.minstdShuffle","base.random.mt19937","base.random.randi"],"base.random.minstdShuffle":["random.array.minstdShuffle","random.iterators.minstdShuffle","random.streams.minstdShuffle","base.random.minstd","base.random.mt19937","base.random.randi"],"base.random.mt19937":["random.array.mt19937","random.iterators.mt19937","random.streams.mt19937","base.random.minstd","base.random.randi"],"base.random.negativeBinomial":["random.array.negativeBinomial","random.iterators.negativeBinomial","random.streams.negativeBinomial","random.negativeBinomial"],"base.random.normal":["random.array.normal","random.iterators.normal","random.streams.normal","random.normal"],"base.random.pareto1":["random.array.pareto1","random.iterators.pareto1","random.streams.pareto1","random.pareto1"],"base.random.poisson":["random.array.poisson","random.iterators.poisson","random.streams.poisson","random.poisson"],"base.random.randi":["random.iterators.randi","random.streams.randi","base.random.minstd","base.random.minstdShuffle","base.random.mt19937"],"base.random.randn":["random.iterators.randn","random.streams.randn","base.random.improvedZiggurat","base.random.randu"],"base.random.randu":["random.array.randu","random.iterators.randu","random.streams.randu","base.random.discreteUniform","base.random.randn"],"base.random.rayleigh":["random.array.rayleigh","random.iterators.rayleigh","random.streams.rayleigh","random.rayleigh"],"base.random.t":["random.array.t","random.iterators.t","random.streams.t","random.t"],"base.random.triangular":["random.array.triangular","random.iterators.triangular","random.streams.triangular","random.triangular"],"base.random.uniform":["random.array.uniform","random.iterators.uniform","random.streams.uniform","random.uniform","base.random.discreteUniform","base.random.randu"],"base.random.weibull":["random.array.weibull","random.iterators.weibull","random.streams.weibull","random.weibull"],"base.rcbrt":["base.cbrt"],"base.rcbrtf":["base.rcbrt","base.cbrtf"],"base.reldiff":["base.absdiff","base.epsdiff"],"base.removeFirst":["base.removeFirstCodePoint","base.removeFirstGraphemeCluster","base.removeLast"],"base.removeFirstCodePoint":["base.removeLastCodePoint","base.removeFirstGraphemeCluster","base.removeFirst"],"base.removeFirstGraphemeCluster":["base.removeFirstCodePoint","base.removeLastGraphemeCluster","base.removeFirst"],"base.removeLast":["base.removeLastCodePoint","base.removeLastGraphemeCluster","base.removeFirst"],"base.removeLastCodePoint":["base.removeFirstCodePoint","base.removeLastGraphemeCluster","base.removeLast"],"base.removeLastGraphemeCluster":["base.removeFirstCodePoint","base.removeLastCodePoint","base.removeLast"],"base.rempio2":[],"base.repeat":[],"base.replace":["base.replaceAfter","base.replaceBefore","base.replaceAfterLast","base.replaceBeforeLast"],"base.replaceAfter"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isquare","random.chisquare"],"base.random.cosine":["random.array.cosine","random.iterators.cosine","random.streams.cosine","random.cosine"],"base.random.discreteUniform":["random.array.discreteUniform","random.iterators.discreteUniform","random.streams.discreteUniform","random.discreteUniform"],"base.random.erlang":["random.array.erlang","random.iterators.erlang","random.streams.erlang","random.erlang"],"base.random.exponential":["random.array.exponential","random.iterators.exponential","random.streams.exponential","random.exponential"],"base.random.f":["random.array.f","random.iterators.f","random.streams.f","random.f"],"base.random.frechet":["random.array.frechet","random.iterators.frechet","random.streams.frechet","random.frechet"],"base.random.gamma":["random.array.gamma","random.iterators.gamma","random.streams.gamma","random.gamma"],"base.random.geometric":["random.array.geometric","random.iterators.geometric","random.streams.geometric","random.geometric"],"base.random.gumbel":["random.array.gumbel","random.iterators.gumbel","random.streams.gumbel","random.gumbel"],"base.random.hypergeometric":["random.array.hypergeometric","random.iterators.hypergeometric","random.streams.hypergeometric","random.hypergeometric"],"base.random.improvedZiggurat":["random.iterators.improvedZiggurat","random.streams.improvedZiggurat"],"base.random.invgamma":["random.array.invgamma","random.iterators.invgamma","random.streams.invgamma","random.invgamma"],"base.random.kumaraswamy":["random.array.kumaraswamy","random.iterators.kumaraswamy","random.streams.kumaraswamy","random.kumaraswamy"],"base.random.laplace":["random.array.laplace","random.iterators.laplace","random.streams.laplace","random.laplace"],"base.random.levy":["random.array.levy","random.iterators.levy","random.streams.levy","random.levy"],"base.random.logistic":["random.array.logistic","random.iterators.logistic","random.streams.logistic","random.logistic"],"base.random.lognormal":["random.array.lognormal","random.iterators.lognormal","random.streams.lognormal","random.lognormal"],"base.random.minstd":["random.array.minstd","random.iterators.minstd","random.streams.minstd","base.random.minstdShuffle","base.random.mt19937","base.random.randi"],"base.random.minstdShuffle":["random.array.minstdShuffle","random.iterators.minstdShuffle","random.streams.minstdShuffle","base.random.minstd","base.random.mt19937","base.random.randi"],"base.random.mt19937":["random.array.mt19937","random.iterators.mt19937","random.streams.mt19937","base.random.minstd","base.random.randi"],"base.random.negativeBinomial":["random.array.negativeBinomial","random.iterators.negativeBinomial","random.streams.negativeBinomial","random.negativeBinomial"],"base.random.normal":["random.array.normal","random.iterators.normal","random.streams.normal","random.normal"],"base.random.pareto1":["random.array.pareto1","random.iterators.pareto1","random.streams.pareto1","random.pareto1"],"base.random.poisson":["random.array.poisson","random.iterators.poisson","random.streams.poisson","random.poisson"],"base.random.randi":["random.iterators.randi","random.streams.randi","base.random.minstd","base.random.minstdShuffle","base.random.mt19937"],"base.random.randn":["random.iterators.randn","random.streams.randn","base.random.improvedZiggurat","base.random.randu"],"base.random.randu":["random.array.randu","random.iterators.randu","random.streams.randu","base.random.discreteUniform","base.random.randn"],"base.random.rayleigh":["random.array.rayleigh","random.iterators.rayleigh","random.streams.rayleigh","random.rayleigh"],"base.random.t":["random.array.t","random.iterators.t","random.streams.t","random.t"],"base.random.triangular":["random.array.triangular","random.iterators.triangular","random.streams.triangular","random.triangular"],"base.random.uniform":["random.array.uniform","random.iterators.uniform","random.streams.uniform","random.uniform","base.random.discreteUniform","base.random.randu"],"base.random.weibull":["random.array.weibull","random.iterators.weibull","random.streams.weibull","random.weibull"],"base.rcbrt":["base.cbrt"],"base.rcbrtf":["base.rcbrt","base.cbrtf"],"base.reldiff":["base.absdiff","base.epsdiff"],"base.removeFirst":["base.removeFirstCodePoint","base.removeFirstGraphemeCluster","base.removeLast"],"base.removeFirstCodePoint":["base.removeLastCodePoint","base.removeFirstGraphemeCluster","base.removeFirst"],"base.removeFirstGraphemeCluster":["base.removeFirstCodePoint","base.removeLastGraphemeCluster","base.removeFirst"],"base.removeLast":["base.removeLastCodePoint","base.removeLastGraphemeCluster","base.removeFirst"],"base.removeLastCodePoint":["base.removeFirstCodePoint","base.removeLastGraphemeCluster","base.removeLast"],"base.removeLastGraphemeCluster":["base.removeFirstCodePoint","base.removeLastCodePoint","base.removeLast"],"base.rempio2":[],"base.repeat":[],"base.replace":["base.replaceAfter","base.replaceBefore","base.replaceAfterLast","base.replaceBeforeLast"],"base.replaceAfter"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diff --git a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv index cab37a0d45a6..739345c6714b 100644 --- a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.csv @@ -1074,7 +1074,7 @@ base.strided.dmeanstdevpn,"@stdlib/stats-strided-dmeanstdevpn" base.strided.dmeanvar,"@stdlib/stats-strided-dmeanvar" base.strided.dmeanvarpn,"@stdlib/stats-strided-dmeanvarpn" base.strided.dmeanwd,"@stdlib/stats-strided-dmeanwd" -base.strided.dmediansorted,"@stdlib/stats-strided-dmediansorted" +base.strided.dmedianSorted,"@stdlib/stats-strided-dmedian-sorted" base.strided.dmidrange,"@stdlib/stats-strided-dmidrange" base.strided.dmin,"@stdlib/stats-strided-dmin" base.strided.dminabs,"@stdlib/stats-strided-dminabs" @@ -1997,6 +1997,7 @@ INT32_NUM_BYTES,"@stdlib/constants-int32-num-bytes" Int32Array,"@stdlib/array-int32" Int32Matrix,"@stdlib/ndarray-matrix-int32" Int32Vector,"@stdlib/ndarray-vector-int32" +Int64,"@stdlib/number-int64-ctor" IS_BIG_ENDIAN,"@stdlib/assert-is-big-endian" IS_BROWSER,"@stdlib/assert-is-browser" IS_DARWIN,"@stdlib/assert-is-darwin" diff --git a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json index 7ef228141ce8..3931578c40df 100644 --- a/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json +++ b/lib/node_modules/@stdlib/namespace/alias2standalone/data/data.json @@ -1 +1 @@ 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echet.kurtosis":"@stdlib/stats-base-dists-frechet-kurtosis","base.dists.frechet.logcdf":"@stdlib/stats-base-dists-frechet-logcdf","base.dists.frechet.logpdf":"@stdlib/stats-base-dists-frechet-logpdf","base.dists.frechet.mean":"@stdlib/stats-base-dists-frechet-mean","base.dists.frechet.median":"@stdlib/stats-base-dists-frechet-median","base.dists.frechet.mode":"@stdlib/stats-base-dists-frechet-mode","base.dists.frechet.pdf":"@stdlib/stats-base-dists-frechet-pdf","base.dists.frechet.quantile":"@stdlib/stats-base-dists-frechet-quantile","base.dists.frechet.skewness":"@stdlib/stats-base-dists-frechet-skewness","base.dists.frechet.stdev":"@stdlib/stats-base-dists-frechet-stdev","base.dists.frechet.variance":"@stdlib/stats-base-dists-frechet-variance","base.dists.gamma.cdf":"@stdlib/stats-base-dists-gamma-cdf","base.dists.gamma.entropy":"@stdlib/stats-base-dists-gamma-entropy","base.dists.gamma.Gamma":"@stdlib/stats-base-dists-gamma-ctor","base.dists.gamma.kurtosis":"@stdlib/stats-base-dists-gamma-kurtosis","base.dists.gamma.logcdf":"@stdlib/stats-base-dists-gamma-logcdf","base.dists.gamma.logpdf":"@stdlib/stats-base-dists-gamma-logpdf","base.dists.gamma.mean":"@stdlib/stats-base-dists-gamma-mean","base.dists.gamma.mgf":"@stdlib/stats-base-dists-gamma-mgf","base.dists.gamma.mode":"@stdlib/stats-base-dists-gamma-mode","base.dists.gamma.pdf":"@stdlib/stats-base-dists-gamma-pdf","base.dists.gamma.quantile":"@stdlib/stats-base-dists-gamma-quantile","base.dists.gamma.skewness":"@stdlib/stats-base-dists-gamma-skewness","base.dists.gamma.stdev":"@stdlib/stats-base-dists-gamma-stdev","base.dists.gamma.variance":"@stdlib/stats-base-dists-gamma-variance","base.dists.geometric.cdf":"@stdlib/stats-base-dists-geometric-cdf","base.dists.geometric.entropy":"@stdlib/stats-base-dists-geometric-entropy","base.dists.geometric.Geometric":"@stdlib/stats-base-dists-geometric-ctor","base.dists.geometric.kurtosis":"@stdlib/stats-base-dists-geometric-kurtosis","base.dists.geometric.logcdf":"@stdlib/stats-base-dists-geometric-logcdf","base.dists.geometric.logpmf":"@stdlib/stats-base-dists-geometric-logpmf","base.dists.geometric.mean":"@stdlib/stats-base-dists-geometric-mean","base.dists.geometric.median":"@stdlib/stats-base-dists-geometric-median","base.dists.geometric.mgf":"@stdlib/stats-base-dists-geometric-mgf","base.dists.geometric.mode":"@stdlib/stats-base-dists-geometric-mode","base.dists.geometric.pmf":"@stdlib/stats-base-dists-geometric-pmf","base.dists.geometric.quantile":"@stdlib/stats-base-dists-geometric-quantile","base.dists.geometric.skewness":"@stdlib/stats-base-dists-geometric-skewness","base.dists.geometric.stdev":"@stdlib/stats-base-dists-geometric-stdev","base.dists.geometric.variance":"@stdlib/stats-base-dists-geometric-variance","base.dists.gumbel.cdf":"@stdlib/stats-base-dists-gumbel-cdf","base.dists.gumbel.entropy":"@stdlib/stats-base-dists-gumbel-entropy","base.dists.gumbel.Gumbel":"@stdlib/stats-base-dists-gumbel-ctor","base.dists.gumbel.kurtosis":"@stdlib/stats-base-dists-gumbel-kurtosis","base.dists.gumbel.logcdf":"@stdlib/stats-base-dists-gumbel-logcdf","base.dists.gumbel.logpdf":"@stdlib/stats-base-dists-gumbel-logpdf","base.dists.gumbel.mean":"@stdlib/stats-base-dists-gumbel-mean","base.dists.gumbel.median":"@stdlib/stats-base-dists-gumbel-median","base.dists.gumbel.mgf":"@stdlib/stats-base-dists-gumbel-mgf","base.dists.gumbel.mode":"@stdlib/stats-base-dists-gumbel-mode","base.dists.gumbel.pdf":"@stdlib/stats-base-dists-gumbel-pdf","base.dists.gumbel.quantile":"@stdlib/stats-base-dists-gumbel-quantile","base.dists.gumbel.skewness":"@stdlib/stats-base-dists-gumbel-skewness","base.dists.gumbel.stdev":"@stdlib/stats-base-dists-gumbel-stdev","base.dists.gumbel.variance":"@stdlib/stats-base-dists-gumbel-variance","base.dists.hypergeometric.cdf":"@stdlib/stats-base-dists-hypergeometric-cdf","base.dists.hypergeometric.Hypergeometric":"@stdlib/stats-base-dists-hypergeometric-ctor","base.dists.hypergeometric.kurtosis":"@stdlib/stats-base-dists-hypergeometric-kurtosis","base.dists.hypergeometric.logpmf":"@stdlib/stats-base-dists-hypergeometric-logpmf","base.dists.hypergeometric.mean":"@stdlib/stats-base-dists-hypergeometric-mean","base.dists.hypergeometric.mode":"@stdlib/stats-base-dists-hypergeometric-mode","base.dists.hypergeometric.pmf":"@stdlib/stats-base-dists-hypergeometric-pmf","base.dists.hypergeometric.quantile":"@stdlib/stats-base-dists-hypergeometric-quantile","base.dists.hypergeometric.skewness":"@stdlib/stats-base-dists-hypergeometric-skewness","base.dists.hypergeometric.stdev":"@stdlib/stats-base-dists-hypergeometric-stdev","base.dists.hypergeometric.variance":"@stdlib/stats-base-dists-hypergeometric-variance","base.dists.invgamma.cdf":"@stdlib/stats-base-dists-invgamma-cdf","base.dists.invgamma.entropy":"@stdlib/stats-base-dists-invgamma-entropy","base.dists.invgamma.InvGamma":"@stdlib/stats-base-dists-invgamma-ctor","base.dists.invgamma.kurtosis":"@stdlib/stats-base-dists-invgamma-kurtosis","base.dists.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ul","base.cmulf":"@stdlib/complex-float32-base-mul","base.cneg":"@stdlib/complex-float64-base-neg","base.cnegf":"@stdlib/complex-float32-base-neg","base.codePointAt":"@stdlib/string-base-code-point-at","base.constantcase":"@stdlib/string-base-constantcase","base.continuedFraction":"@stdlib/math-base-tools-continued-fraction","base.copysign":"@stdlib/math-base-special-copysign","base.copysignf":"@stdlib/math-base-special-copysignf","base.cos":"@stdlib/math-base-special-cos","base.cosd":"@stdlib/math-base-special-cosd","base.cosh":"@stdlib/math-base-special-cosh","base.cosm1":"@stdlib/math-base-special-cosm1","base.cospi":"@stdlib/math-base-special-cospi","base.cot":"@stdlib/math-base-special-cot","base.cotd":"@stdlib/math-base-special-cotd","base.coth":"@stdlib/math-base-special-coth","base.covercos":"@stdlib/math-base-special-covercos","base.coversin":"@stdlib/math-base-special-coversin","base.cphase":"@stdlib/math-base-special-cphase","base.cpolar":"@stdlib/math-base-special-cpolar","base.cround":"@stdlib/math-base-special-cround","base.croundn":"@stdlib/math-base-special-croundn","base.csc":"@stdlib/math-base-special-csc","base.cscd":"@stdlib/math-base-special-cscd","base.csch":"@stdlib/math-base-special-csch","base.csignum":"@stdlib/math-base-special-csignum","base.csub":"@stdlib/complex-float64-base-sub","base.csubf":"@stdlib/complex-float32-base-sub","base.deg2rad":"@stdlib/math-base-special-deg2rad","base.deg2radf":"@stdlib/math-base-special-deg2radf","base.digamma":"@stdlib/math-base-special-digamma","base.diracDelta":"@stdlib/math-base-special-dirac-delta","base.div":"@stdlib/number-float64-base-div","base.divf":"@stdlib/number-float32-base-div","base.dotcase":"@stdlib/string-base-dotcase","base.dists.arcsine.Arcsine":"@stdlib/stats-base-dists-arcsine-ctor","base.dists.arcsine.cdf":"@stdlib/stats-base-dists-arcsine-cdf","base.dists.arcsine.entropy":"@stdlib/stats-base-dists-arcsine-entropy","base.dists.arcsine.kurtosis":"@stdlib/stats-base-dists-arcsine-kurtosis","base.dists.arcsine.logcdf":"@stdlib/stats-base-dists-arcsine-logcdf","base.dists.arcsine.logpdf":"@stdlib/stats-base-dists-arcsine-logpdf","base.dists.arcsine.mean":"@stdlib/stats-base-dists-arcsine-mean","base.dists.arcsine.median":"@stdlib/stats-base-dists-arcsine-median","base.dists.arcsine.mode":"@stdlib/stats-base-dists-arcsine-mode","base.dists.arcsine.pdf":"@stdlib/stats-base-dists-arcsine-pdf","base.dists.arcsine.quantile":"@stdlib/stats-base-dists-arcsine-quantile","base.dists.arcsine.skewness":"@stdlib/stats-base-dists-arcsine-skewness","base.dists.arcsine.stdev":"@stdlib/stats-base-dists-arcsine-stdev","base.dists.arcsine.variance":"@stdlib/stats-base-dists-arcsine-variance","base.dists.bernoulli.Bernoulli":"@stdlib/stats-base-dists-bernoulli-ctor","base.dists.bernoulli.cdf":"@stdlib/stats-base-dists-bernoulli-cdf","base.dists.bernoulli.entropy":"@stdlib/stats-base-dists-bernoulli-entropy","base.dists.bernoulli.kurtosis":"@stdlib/stats-base-dists-bernoulli-kurtosis","base.dists.bernoulli.mean":"@stdlib/stats-base-dists-bernoulli-mean","base.dists.bernoulli.median":"@stdlib/stats-base-dists-bernoulli-median","base.dists.bernoulli.mgf":"@stdlib/stats-base-dists-bernoulli-mgf","base.dists.bernoulli.mode":"@stdlib/stats-base-dists-bernoulli-mode","base.dists.bernoulli.pmf":"@stdlib/stats-base-dists-bernoulli-pmf","base.dists.bernoulli.quantile":"@stdlib/stats-base-dists-bernoulli-quantile","base.dists.bernoulli.skewness":"@stdlib/stats-base-dists-bernoulli-skewness","base.dists.bernoulli.stdev":"@stdlib/stats-base-dists-bernoulli-stdev","base.dists.bernoulli.variance":"@stdlib/stats-base-dists-bernoulli-variance","base.dists.beta.Beta":"@stdlib/stats-base-dists-beta-ctor","base.dists.beta.cdf":"@stdlib/stats-base-dists-beta-cdf","base.dists.beta.entropy":"@stdlib/stats-base-dists-beta-entropy","base.dists.beta.kurtosis":"@stdlib/stats-base-dists-beta-kurtosis","base.dists.beta.logcdf":"@stdlib/stats-base-dists-beta-logcdf","base.dists.beta.logpdf":"@stdlib/stats-base-dists-beta-logpdf","base.dists.beta.mean":"@stdlib/stats-base-dists-beta-mean","base.dists.beta.median":"@stdlib/stats-base-dists-beta-median","base.dists.beta.mgf":"@stdlib/stats-base-dists-beta-mgf","base.dists.beta.mode":"@stdlib/stats-base-dists-beta-mode","base.dists.beta.pdf":"@stdlib/stats-base-dists-beta-pdf","base.dists.beta.quantile":"@stdlib/stats-base-dists-beta-quantile","base.dists.beta.skewness":"@stdlib/stats-base-dists-beta-skewness","base.dists.beta.stdev":"@stdlib/stats-base-dists-beta-stdev","base.dists.beta.variance":"@stdlib/stats-base-dists-beta-variance","base.dists.betaprime.BetaPrime":"@stdlib/stats-base-dists-betaprime-ctor","base.dists.betaprime.cdf":"@stdlib/stats-base-dists-betaprime-cdf","base.dists.betaprime.kurtosis":"@stdlib/stats-base-dists-betaprime-kurtosis","base.dists.betaprime.logcdf":"@stdlib/stats-base-dists-betaprime-logcdf","base.dists.betaprime.logpdf":"@stdlib/stats-base-dists-betaprime-logpdf","base.dists.betaprime.mean":"@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diff --git a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt index 4a2ecb834169..af5ecd048d5b 100644 --- a/lib/node_modules/@stdlib/namespace/aliases/data/data.txt +++ b/lib/node_modules/@stdlib/namespace/aliases/data/data.txt @@ -1074,7 +1074,7 @@ base.strided.dmeanstdevpn base.strided.dmeanvar base.strided.dmeanvarpn base.strided.dmeanwd -base.strided.dmediansorted +base.strided.dmedianSorted base.strided.dmidrange base.strided.dmin base.strided.dminabs @@ -1997,6 +1997,7 @@ INT32_NUM_BYTES Int32Array Int32Matrix Int32Vector +Int64 IS_BIG_ENDIAN IS_BROWSER IS_DARWIN diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js index 16ab204cc55c..28abd09f24b5 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/d.js @@ -661,9 +661,9 @@ ns.push({ }); ns.push({ - 'alias': 'base.strided.dmediansorted', - 'path': '@stdlib/stats/strided/dmediansorted', - 'value': require( '@stdlib/stats/strided/dmediansorted' ), + 'alias': 'base.strided.dmedianSorted', + 'path': '@stdlib/stats/strided/dmedian-sorted', + 'value': require( '@stdlib/stats/strided/dmedian-sorted' ), 'type': 'Function', 'related': [ '@stdlib/stats/strided/dmean', diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js index 5199022eb0bb..77befb1a066f 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/m.js @@ -209,7 +209,7 @@ ns.push({ 'value': require( '@stdlib/stats/strided/mediansorted' ), 'type': 'Function', 'related': [ - '@stdlib/stats/strided/dmediansorted', + '@stdlib/stats/strided/dmedian-sorted', '@stdlib/stats/strided/mean', '@stdlib/stats/base/median', '@stdlib/stats/base/nanmediansorted', diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js index 1fc7d12c78cb..20458ec60e50 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/base/strided/s.js @@ -750,7 +750,7 @@ ns.push({ 'value': require( '@stdlib/stats/strided/smediansorted' ), 'type': 'Function', 'related': [ - '@stdlib/stats/strided/dmediansorted', + '@stdlib/stats/strided/dmedian-sorted', '@stdlib/stats/strided/mediansorted', '@stdlib/stats/strided/smean', '@stdlib/stats/base/smedian', diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/i.js b/lib/node_modules/@stdlib/namespace/lib/namespace/i.js index ee3694d52369..556584247ceb 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/i.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/i.js @@ -1996,6 +1996,18 @@ ns.push({ ] }); +ns.push({ + 'alias': 'Int64', + 'path': '@stdlib/number/int64/ctor', + 'value': require( '@stdlib/number/int64/ctor' ), + 'type': 'Function', + 'related': [ + '@stdlib/bigint/ctor', + '@stdlib/number/ctor', + '@stdlib/number/uint64/ctor' + ] +}); + ns.push({ 'alias': 'IS_BIG_ENDIAN', 'path': '@stdlib/assert/is-big-endian', diff --git a/lib/node_modules/@stdlib/namespace/lib/namespace/u.js b/lib/node_modules/@stdlib/namespace/lib/namespace/u.js index c8ae9272b9be..ea018a4d0f94 100644 --- a/lib/node_modules/@stdlib/namespace/lib/namespace/u.js +++ b/lib/node_modules/@stdlib/namespace/lib/namespace/u.js @@ -260,6 +260,7 @@ ns.push({ 'value': require( '@stdlib/number/uint64/ctor' ), 'type': 'Function', 'related': [ + '@stdlib/bigint/ctor', '@stdlib/number/ctor', '@stdlib/number/int64/ctor' ] diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv index f113d6c9270f..c7942e89aad3 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.csv @@ -1074,7 +1074,7 @@ "@stdlib/stats/strided/dmeanvar",base.strided.dmeanvar "@stdlib/stats/strided/dmeanvarpn",base.strided.dmeanvarpn "@stdlib/stats/strided/dmeanwd",base.strided.dmeanwd -"@stdlib/stats/strided/dmediansorted",base.strided.dmediansorted +"@stdlib/stats/strided/dmedian-sorted",base.strided.dmedianSorted "@stdlib/stats/strided/dmidrange",base.strided.dmidrange "@stdlib/stats/strided/dmin",base.strided.dmin "@stdlib/stats/strided/dminabs",base.strided.dminabs @@ -1997,6 +1997,7 @@ "@stdlib/array/int32",Int32Array "@stdlib/ndarray/matrix/int32",Int32Matrix "@stdlib/ndarray/vector/int32",Int32Vector +"@stdlib/number/int64/ctor",Int64 "@stdlib/assert/is-big-endian",IS_BIG_ENDIAN "@stdlib/assert/is-browser",IS_BROWSER "@stdlib/assert/is-darwin",IS_DARWIN diff --git a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json index 11212f0892cf..c5db6abe1e5f 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2alias/data/data.json @@ -1 +1 @@ -{"@stdlib/math/special/abs":"abs","@stdlib/array/cartesian-power":"acartesianPower","@stdlib/array/cartesian-product":"acartesianProduct","@stdlib/array/cartesian-square":"acartesianSquare","@stdlib/string/acronym":"acronym","@stdlib/array/empty":"aempty","@stdlib/array/empty-like":"aemptyLike","@stdlib/datasets/afinn-96":"AFINN_96","@stdlib/datasets/afinn-111":"AFINN_111","@stdlib/array/full":"afull","@stdlib/array/full-like":"afullLike","@stdlib/namespace/alias2pkg":"alias2pkg","@stdlib/namespace/alias2related":"alias2related","@stdlib/namespace/alias2standalone":"alias2standalone","@stdlib/namespace/aliases":"aliases","@stdlib/buffer/alloc-unsafe":"allocUnsafe","@stdlib/array/mskfilter":"amskfilter","@stdlib/array/mskput":"amskput","@stdlib/array/mskreject":"amskreject","@stdlib/array/nans":"anans","@stdlib/array/nans-like":"anansLike","@stdlib/stats/anova1":"anova1","@stdlib/datasets/anscombes-quartet":"ANSCOMBES_QUARTET","@stdlib/utils/any":"any","@stdlib/utils/any-by":"anyBy","@stdlib/utils/async/any-by":"anyByAsync","@stdlib/utils/any-by-right":"anyByRight","@stdlib/utils/async/any-by-right":"anyByRightAsync","@stdlib/object/any-in-by":"anyInBy","@stdlib/object/any-own-by":"anyOwnBy","@stdlib/array/ones":"aones","@stdlib/array/ones-like":"aonesLike","@stdlib/array/one-to":"aoneTo","@stdlib/array/one-to-like":"aoneToLike","@stdlib/constants/float64/apery":"APERY","@stdlib/array/place":"aplace","@stdlib/utils/append":"append","@stdlib/array/put":"aput","@stdlib/os/arch":"ARCH","@stdlib/utils/argument-function":"argumentFunction","@stdlib/process/argv":"ARGV","@stdlib/ndarray/array":"array","@stdlib/buffer/from-array":"array2buffer","@stdlib/array/to-fancy":"array2fancy","@stdlib/array/to-iterator":"array2iterator","@stdlib/array/to-iterator-right":"array2iteratorRight","@stdlib/array/buffer":"ArrayBuffer","@stdlib/buffer/from-arraybuffer":"arraybuffer2buffer","@stdlib/array/ctors":"arrayCtors","@stdlib/array/dtype":"arrayDataType","@stdlib/array/dtypes":"arrayDataTypes","@stdlib/array/index":"ArrayIndex","@stdlib/array/min-dtype":"arrayMinDataType","@stdlib/array/mostly-safe-casts":"arrayMostlySafeCasts","@stdlib/array/next-dtype":"arrayNextDataType","@stdlib/array/promotion-rules":"arrayPromotionRules","@stdlib/array/safe-casts":"arraySafeCasts","@stdlib/array/same-kind-casts":"arraySameKindCasts","@stdlib/array/shape":"arrayShape","@stdlib/streams/node/from-array":"arrayStream","@stdlib/array/to-view-iterator":"arrayview2iterator","@stdlib/array/to-view-iterator-right":"arrayview2iteratorRight","@stdlib/array/slice":"aslice","@stdlib/symbol/async-iterator":"AsyncIteratorSymbol","@stdlib/array/take":"atake","@stdlib/array/zeros":"azeros","@stdlib/array/zeros-like":"azerosLike","@stdlib/array/zero-to":"azeroTo","@stdlib/array/zero-to-like":"azeroToLike","@stdlib/stats/bartlett-test":"bartlettTest","@stdlib/math/base/special/abs":"base.abs","@stdlib/math/base/special/abs2":"base.abs2","@stdlib/math/base/special/abs2f":"base.abs2f","@stdlib/math/base/utils/absolute-difference":"base.absdiff","@stdlib/math/base/special/absf":"base.absf","@stdlib/array/base/cartesian-power":"base.acartesianPower","@stdlib/array/base/cartesian-product":"base.acartesianProduct","@stdlib/array/base/cartesian-square":"base.acartesianSquare","@stdlib/math/base/special/acos":"base.acos","@stdlib/math/base/special/acosd":"base.acosd","@stdlib/math/base/special/acosdf":"base.acosdf","@stdlib/math/base/special/acosf":"base.acosf","@stdlib/math/base/special/acosh":"base.acosh","@stdlib/math/base/special/acot":"base.acot","@stdlib/math/base/special/acotd":"base.acotd","@stdlib/math/base/special/acotdf":"base.acotdf","@stdlib/math/base/special/acotf":"base.acotf","@stdlib/math/base/special/acoth":"base.acoth","@stdlib/math/base/special/acovercos":"base.acovercos","@stdlib/math/base/special/acoversin":"base.acoversin","@stdlib/math/base/special/acsc":"base.acsc","@stdlib/math/base/special/acscd":"base.acscd","@stdlib/math/base/special/acscdf":"base.acscdf","@stdlib/math/base/special/acscf":"base.acscf","@stdlib/math/base/special/acsch":"base.acsch","@stdlib/number/float64/base/add":"base.add","@stdlib/number/float64/base/add3":"base.add3","@stdlib/number/float64/base/add4":"base.add4","@stdlib/number/float64/base/add5":"base.add5","@stdlib/number/float32/base/add":"base.addf","@stdlib/array/base/filled":"base.afilled","@stdlib/array/base/filled2d":"base.afilled2d","@stdlib/array/base/filled2d-by":"base.afilled2dBy","@stdlib/array/base/filled3d":"base.afilled3d","@stdlib/array/base/filled3d-by":"base.afilled3dBy","@stdlib/array/base/filled4d":"base.afilled4d","@stdlib/array/base/filled4d-by":"base.afilled4dBy","@stdlib/array/base/filled5d":"base.afilled5d","@stdlib/array/base/filled5d-by":"base.afilled5dBy","@stdlib/array/base/filled-by":"base.afilledBy","@stdlib/array/base/fillednd":"base.afillednd","@stdlib/array/base/fillednd-by":"base.afilledndBy","@stdlib/array/base/filter":"base.afilter","@stdlib/array/base/first":"base.afirst","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ul","@stdlib/complex/float32/base/mul":"base.cmulf","@stdlib/complex/float64/base/neg":"base.cneg","@stdlib/complex/float32/base/neg":"base.cnegf","@stdlib/string/base/code-point-at":"base.codePointAt","@stdlib/string/base/constantcase":"base.constantcase","@stdlib/math/base/tools/continued-fraction":"base.continuedFraction","@stdlib/math/base/special/copysign":"base.copysign","@stdlib/math/base/special/copysignf":"base.copysignf","@stdlib/math/base/special/cos":"base.cos","@stdlib/math/base/special/cosd":"base.cosd","@stdlib/math/base/special/cosh":"base.cosh","@stdlib/math/base/special/cosm1":"base.cosm1","@stdlib/math/base/special/cospi":"base.cospi","@stdlib/math/base/special/cot":"base.cot","@stdlib/math/base/special/cotd":"base.cotd","@stdlib/math/base/special/coth":"base.coth","@stdlib/math/base/special/covercos":"base.covercos","@stdlib/math/base/special/coversin":"base.coversin","@stdlib/math/base/special/cphase":"base.cphase","@stdlib/math/base/special/cpolar":"base.cpolar","@stdlib/math/base/special/cround":"base.cround","@stdlib/math/base/special/croundn":"base.croundn","@stdlib/math/base/special/csc":"base.csc","@stdlib/math/base/special/cscd":"base.cscd","@stdlib/math/base/special/csch":"base.csch","@stdlib/math/base/special/csignum":"base.csignum","@stdlib/complex/float64/base/sub":"base.csub","@stdlib/complex/float32/base/sub":"base.csubf","@stdlib/math/base/special/deg2rad":"base.deg2rad","@stdlib/math/base/special/deg2radf":"base.deg2radf","@stdlib/math/base/special/digamma":"base.digamma","@stdlib/math/base/special/dirac-delta":"base.diracDelta","@stdlib/number/float64/base/div":"base.div","@stdlib/number/float32/base/div":"base.divf","@stdlib/string/base/dotcase":"base.dotcase","@stdlib/stats/base/dists/arcsine/ctor":"base.dists.arcsine.Arcsine","@stdlib/stats/base/dists/arcsine/cdf":"base.dists.arcsine.cdf","@stdlib/stats/base/dists/arcsine/entropy":"base.dists.arcsine.entropy","@stdlib/stats/base/dists/arcsine/kurtosis":"base.dists.arcsine.kurtosis","@stdlib/stats/base/dists/arcsine/logcdf":"base.dists.arcsine.logcdf","@stdlib/stats/base/dists/arcsine/logpdf":"base.dists.arcsine.logpdf","@stdlib/stats/base/dists/arcsine/mean":"base.dists.arcsine.mean","@stdlib/stats/base/dists/arcsine/median":"base.dists.arcsine.median","@stdlib/stats/base/dists/arcsine/mode":"base.dists.arcsine.mode","@stdlib/stats/base/dists/arcsine/pdf":"base.dists.arcsine.pdf","@stdlib/stats/base/dists/arcsine/quantile":"base.dists.arcsine.quantile","@stdlib/stats/base/dists/arcsine/skewness":"base.dists.arcsine.skewness","@stdlib/stats/base/dists/arcsine/stdev":"base.dists.arcsine.stdev","@stdlib/stats/base/dists/arcsine/variance":"base.dists.arcsine.variance","@stdlib/stats/base/dists/bernoulli/ctor":"base.dists.bernoulli.Bernoulli","@stdlib/stats/base/dists/bernoulli/cdf":"base.dists.bernoulli.cdf","@stdlib/stats/base/dists/bernoulli/entropy":"base.dists.bernoulli.entropy","@stdlib/stats/base/dists/bernoulli/kurtosis":"base.dists.bernoulli.kurtosis","@stdlib/stats/base/dists/bernoulli/mean":"base.dists.bernoulli.mean","@stdlib/stats/base/dists/bernoulli/median":"base.dists.bernoulli.median","@stdlib/stats/base/dists/bernoulli/mgf":"base.dists.bernoulli.mgf","@stdlib/stats/base/dists/bernoulli/mode":"base.dists.bernoulli.mode","@stdlib/stats/base/dists/bernoulli/pmf":"base.dists.bernoulli.pmf","@stdlib/stats/base/dists/bernoulli/quantile":"base.dists.bernoulli.quantile","@stdlib/stats/base/dists/bernoulli/skewness":"base.dists.bernoulli.skewness","@stdlib/stats/base/dists/bernoulli/stdev":"base.dists.bernoulli.stdev","@stdlib/stats/base/dists/bernoulli/variance":"base.dists.bernoulli.variance","@stdlib/stats/base/dists/beta/ctor":"base.dists.beta.Beta","@stdlib/stats/base/dists/beta/cdf":"base.dists.beta.cdf","@stdlib/stats/base/dists/beta/entropy":"base.dists.beta.entropy","@stdlib/stats/base/dists/beta/kurtosis":"base.dists.beta.kurtosis","@stdlib/stats/base/dists/beta/logcdf":"base.dists.beta.logcdf","@stdlib/stats/base/dists/beta/logpdf":"base.dists.beta.logpdf","@stdlib/stats/base/dists/beta/mean":"base.dists.beta.mean","@stdlib/stats/base/dists/beta/median":"base.dists.beta.median","@stdlib/stats/base/dists/beta/mgf":"base.dists.beta.mgf","@stdlib/stats/base/dists/beta/mode":"base.dists.beta.mode","@stdlib/stats/base/dists/beta/pdf":"base.dists.beta.pdf","@stdlib/stats/base/dists/beta/quantile":"base.dists.beta.quantile","@stdlib/stats/base/dists/beta/skewness":"base.dists.beta.skewness","@stdlib/stats/base/dists/beta/stdev":"base.dists.beta.stdev","@stdlib/stats/base/dists/beta/variance":"base.dists.beta.variance","@stdlib/stats/base/dists/betaprime/ctor":"base.dists.betaprime.BetaPrime","@stdlib/stats/base/dists/betaprime/cdf":"base.dists.betaprime.cdf","@stdlib/stats/base/dists/betaprime/kurtosis":"base.dists.betaprime.kurtosis","@stdlib/stats/base/dists/betaprime/logcdf":"base.dists.betaprime.logcdf","@stdlib/stats/base/dists/betaprime/logpdf":"base.dists.betaprime.logpdf","@stdlib/stats/base/dists/beta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ul","@stdlib/complex/float32/base/mul":"base.cmulf","@stdlib/complex/float64/base/neg":"base.cneg","@stdlib/complex/float32/base/neg":"base.cnegf","@stdlib/string/base/code-point-at":"base.codePointAt","@stdlib/string/base/constantcase":"base.constantcase","@stdlib/math/base/tools/continued-fraction":"base.continuedFraction","@stdlib/math/base/special/copysign":"base.copysign","@stdlib/math/base/special/copysignf":"base.copysignf","@stdlib/math/base/special/cos":"base.cos","@stdlib/math/base/special/cosd":"base.cosd","@stdlib/math/base/special/cosh":"base.cosh","@stdlib/math/base/special/cosm1":"base.cosm1","@stdlib/math/base/special/cospi":"base.cospi","@stdlib/math/base/special/cot":"base.cot","@stdlib/math/base/special/cotd":"base.cotd","@stdlib/math/base/special/coth":"base.coth","@stdlib/math/base/special/covercos":"base.covercos","@stdlib/math/base/special/coversin":"base.coversin","@stdlib/math/base/special/cphase":"base.cphase","@stdlib/math/base/special/cpolar":"base.cpolar","@stdlib/math/base/special/cround":"base.cround","@stdlib/math/base/special/croundn":"base.croundn","@stdlib/math/base/special/csc":"base.csc","@stdlib/math/base/special/cscd":"base.cscd","@stdlib/math/base/special/csch":"base.csch","@stdlib/math/base/special/csignum":"base.csignum","@stdlib/complex/float64/base/sub":"base.csub","@stdlib/complex/float32/base/sub":"base.csubf","@stdlib/math/base/special/deg2rad":"base.deg2rad","@stdlib/math/base/special/deg2radf":"base.deg2radf","@stdlib/math/base/special/digamma":"base.digamma","@stdlib/math/base/special/dirac-delta":"base.diracDelta","@stdlib/number/float64/base/div":"base.div","@stdlib/number/float32/base/div":"base.divf","@stdlib/string/base/dotcase":"base.dotcase","@stdlib/stats/base/dists/arcsine/ctor":"base.dists.arcsine.Arcsine","@stdlib/stats/base/dists/arcsine/cdf":"base.dists.arcsine.cdf","@stdlib/stats/base/dists/arcsine/entropy":"base.dists.arcsine.entropy","@stdlib/stats/base/dists/arcsine/kurtosis":"base.dists.arcsine.kurtosis","@stdlib/stats/base/dists/arcsine/logcdf":"base.dists.arcsine.logcdf","@stdlib/stats/base/dists/arcsine/logpdf":"base.dists.arcsine.logpdf","@stdlib/stats/base/dists/arcsine/mean":"base.dists.arcsine.mean","@stdlib/stats/base/dists/arcsine/median":"base.dists.arcsine.median","@stdlib/stats/base/dists/arcsine/mode":"base.dists.arcsine.mode","@stdlib/stats/base/dists/arcsine/pdf":"base.dists.arcsine.pdf","@stdlib/stats/base/dists/arcsine/quantile":"base.dists.arcsine.quantile","@stdlib/stats/base/dists/arcsine/skewness":"base.dists.arcsine.skewness","@stdlib/stats/base/dists/arcsine/stdev":"base.dists.arcsine.stdev","@stdlib/stats/base/dists/arcsine/variance":"base.dists.arcsine.variance","@stdlib/stats/base/dists/bernoulli/ctor":"base.dists.bernoulli.Bernoulli","@stdlib/stats/base/dists/bernoulli/cdf":"base.dists.bernoulli.cdf","@stdlib/stats/base/dists/bernoulli/entropy":"base.dists.bernoulli.entropy","@stdlib/stats/base/dists/bernoulli/kurtosis":"base.dists.bernoulli.kurtosis","@stdlib/stats/base/dists/bernoulli/mean":"base.dists.bernoulli.mean","@stdlib/stats/base/dists/bernoulli/median":"base.dists.bernoulli.median","@stdlib/stats/base/dists/bernoulli/mgf":"base.dists.bernoulli.mgf","@stdlib/stats/base/dists/bernoulli/mode":"base.dists.bernoulli.mode","@stdlib/stats/base/dists/bernoulli/pmf":"base.dists.bernoulli.pmf","@stdlib/stats/base/dists/bernoulli/quantile":"base.dists.bernoulli.quantile","@stdlib/stats/base/dists/bernoulli/skewness":"base.dists.bernoulli.skewness","@stdlib/stats/base/dists/bernoulli/stdev":"base.dists.bernoulli.stdev","@stdlib/stats/base/dists/bernoulli/variance":"base.dists.bernoulli.variance","@stdlib/stats/base/dists/beta/ctor":"base.dists.beta.Beta","@stdlib/stats/base/dists/beta/cdf":"base.dists.beta.cdf","@stdlib/stats/base/dists/beta/entropy":"base.dists.beta.entropy","@stdlib/stats/base/dists/beta/kurtosis":"base.dists.beta.kurtosis","@stdlib/stats/base/dists/beta/logcdf":"base.dists.beta.logcdf","@stdlib/stats/base/dists/beta/logpdf":"base.dists.beta.logpdf","@stdlib/stats/base/dists/beta/mean":"base.dists.beta.mean","@stdlib/stats/base/dists/beta/median":"base.dists.beta.median","@stdlib/stats/base/dists/beta/mgf":"base.dists.beta.mgf","@stdlib/stats/base/dists/beta/mode":"base.dists.beta.mode","@stdlib/stats/base/dists/beta/pdf":"base.dists.beta.pdf","@stdlib/stats/base/dists/beta/quantile":"base.dists.beta.quantile","@stdlib/stats/base/dists/beta/skewness":"base.dists.beta.skewness","@stdlib/stats/base/dists/beta/stdev":"base.dists.beta.stdev","@stdlib/stats/base/dists/beta/variance":"base.dists.beta.variance","@stdlib/stats/base/dists/betaprime/ctor":"base.dists.betaprime.BetaPrime","@stdlib/stats/base/dists/betaprime/cdf":"base.dists.betaprime.cdf","@stdlib/stats/base/dists/betaprime/kurtosis":"base.dists.betaprime.kurtosis","@stdlib/stats/base/dists/betaprime/logcdf":"base.dists.betaprime.logcdf","@stdlib/stats/base/dists/betaprime/logpdf":"base.dists.betaprime.logpdf","@stdlib/stats/base/dists/beta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ided.sub","@stdlib/math/strided/ops/sub-by":"strided.subBy","@stdlib/math/strided/special/trunc":"strided.trunc","@stdlib/array/to-strided-iterator":"stridedarray2iterator","@stdlib/streams/node/from-strided-array":"stridedArrayStream","@stdlib/buffer/from-string":"string2buffer","@stdlib/dstructs/struct":"structFactory","@stdlib/ndarray/sub2ind":"sub2ind","@stdlib/string/substring-after":"substringAfter","@stdlib/string/substring-after-last":"substringAfterLast","@stdlib/string/substring-before":"substringBefore","@stdlib/string/substring-before-last":"substringBeforeLast","@stdlib/datasets/suthaharan-multi-hop-sensor-network":"SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","@stdlib/datasets/suthaharan-single-hop-sensor-network":"SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","@stdlib/symbol/ctor":"Symbol","@stdlib/utils/tabulate":"tabulate","@stdlib/utils/tabulate-by":"tabulateBy","@stdlib/utils/async/tabulate-by":"tabulateByAsync","@stdlib/function/thunk":"thunk","@stdlib/time/tic":"tic","@stdlib/utils/timeit":"timeit","@stdlib/os/tmpdir":"tmpdir","@stdlib/time/toc":"toc","@stdlib/nlp/tokenize":"tokenize","@stdlib/streams/node/transform":"transformStream","@stdlib/string/trim":"trim","@stdlib/ndarray/trues":"trues","@stdlib/ndarray/trues-like":"truesLike","@stdlib/string/truncate":"truncate","@stdlib/string/truncate-middle":"truncateMiddle","@stdlib/utils/try-catch":"trycatch","@stdlib/utils/async/try-catch":"trycatchAsync","@stdlib/utils/try-function":"tryFunction","@stdlib/utils/try-require":"tryRequire","@stdlib/utils/try-then":"trythen","@stdlib/utils/async/try-then":"trythenAsync","@stdlib/stats/ttest":"ttest","@stdlib/stats/ttest2":"ttest2","@stdlib/constants/float64/two-pi":"TWO_PI","@stdlib/array/typed":"typedarray","@stdlib/array/to-json":"typedarray2json","@stdlib/array/typed-ctors":"typedarrayCtors","@stdlib/array/typed-dtypes":"typedarrayDataTypes","@stdlib/array/pool":"typedarraypool","@stdlib/utils/type-max":"typemax","@stdlib/utils/type-min":"typemin","@stdlib/utils/type-of":"typeOf","@stdlib/constants/uint8/max":"UINT8_MAX","@stdlib/constants/uint8/num-bytes":"UINT8_NUM_BYTES","@stdlib/array/uint8":"Uint8Array","@stdlib/array/uint8c":"Uint8ClampedArray","@stdlib/ndarray/vector/uint8c":"Uint8ClampedVector","@stdlib/ndarray/vector/uint8":"Uint8Vector","@stdlib/constants/uint16/max":"UINT16_MAX","@stdlib/constants/uint16/num-bytes":"UINT16_NUM_BYTES","@stdlib/array/uint16":"Uint16Array","@stdlib/ndarray/vector/uint16":"Uint16Vector","@stdlib/constants/uint32/max":"UINT32_MAX","@stdlib/constants/uint32/num-bytes":"UINT32_NUM_BYTES","@stdlib/array/uint32":"Uint32Array","@stdlib/ndarray/vector/uint32":"Uint32Vector","@stdlib/number/uint64/ctor":"Uint64","@stdlib/process/umask":"umask","@stdlib/string/uncapitalize":"uncapitalize","@stdlib/object/uncapitalize-keys":"uncapitalizeKeys","@stdlib/utils/uncurry":"uncurry","@stdlib/utils/uncurry-right":"uncurryRight","@stdlib/constants/unicode/max":"UNICODE_MAX","@stdlib/constants/unicode/max-bmp":"UNICODE_MAX_BMP","@stdlib/plot/sparklines/unicode/column":"UnicodeColumnChartSparkline","@stdlib/plot/sparklines/unicode/line":"UnicodeLineChartSparkline","@stdlib/plot/sparklines/unicode":"UnicodeSparkline","@stdlib/plot/sparklines/unicode/tristate":"UnicodeTristateChartSparkline","@stdlib/plot/sparklines/unicode/up-down":"UnicodeUpDownChartSparkline","@stdlib/plot/sparklines/unicode/win-loss":"UnicodeWinLossChartSparkline","@stdlib/fs/unlink":"unlink","@stdlib/utils/unshift":"unshift","@stdlib/utils/until":"until","@stdlib/utils/async/until":"untilAsync","@stdlib/utils/until-each":"untilEach","@stdlib/utils/until-each-right":"untilEachRight","@stdlib/utils/unzip":"unzip","@stdlib/string/uppercase":"uppercase","@stdlib/object/uppercase-keys":"uppercaseKeys","@stdlib/datasets/us-states-abbr":"US_STATES_ABBR","@stdlib/datasets/us-states-capitals":"US_STATES_CAPITALS","@stdlib/datasets/us-states-capitals-names":"US_STATES_CAPITALS_NAMES","@stdlib/datasets/us-states-names":"US_STATES_NAMES","@stdlib/datasets/us-states-names-capitals":"US_STATES_NAMES_CAPITALS","@stdlib/string/utf16-to-utf8-array":"utf16ToUTF8Array","@stdlib/stats/vartest":"vartest","@stdlib/ndarray/vector/ctor":"vector","@stdlib/utils/async/series-waterfall":"waterfall","@stdlib/wasm/memory":"WebAssemblyMemory","@stdlib/utils/async/while":"whileAsync","@stdlib/utils/while-each":"whileEach","@stdlib/utils/while-each-right":"whileEachRight","@stdlib/utils/while":"whilst","@stdlib/stats/wilcoxon":"wilcoxon","@stdlib/utils/writable-properties":"writableProperties","@stdlib/utils/writable-properties-in":"writablePropertiesIn","@stdlib/utils/writable-property-names":"writablePropertyNames","@stdlib/utils/writable-property-names-in":"writablePropertyNamesIn","@stdlib/utils/writable-property-symbols":"writablePropertySymbols","@stdlib/utils/writable-property-symbols-in":"writablePropertySymbolsIn","@stdlib/fs/write-file":"writeFile","@stdlib/utils/zip":"zip","@stdlib/stats/ztest":"ztest","@stdlib/stats/ztest2":"ztest2"} diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv index b2df286d1483..2191198666b7 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.csv @@ -1074,7 +1074,7 @@ "@stdlib/stats/strided/dmeanvar","@stdlib/stats/strided/dmean,@stdlib/stats/strided/dvariance" "@stdlib/stats/strided/dmeanvarpn","@stdlib/stats/strided/dmeanpn,@stdlib/stats/strided/dmeanstdevpn,@stdlib/stats/strided/dmeanvar,@stdlib/stats/strided/dvariancepn" "@stdlib/stats/strided/dmeanwd","@stdlib/stats/strided/dmean,@stdlib/stats/strided/dnanmeanwd,@stdlib/stats/strided/meanwd,@stdlib/stats/strided/smeanwd" -"@stdlib/stats/strided/dmediansorted","@stdlib/stats/strided/dmean,@stdlib/stats/strided/mediansorted,@stdlib/stats/strided/smediansorted" +"@stdlib/stats/strided/dmedian-sorted","@stdlib/stats/strided/dmean,@stdlib/stats/strided/mediansorted,@stdlib/stats/strided/smediansorted" "@stdlib/stats/strided/dmidrange","@stdlib/stats/strided/dmax,@stdlib/stats/strided/dmean,@stdlib/stats/strided/dmin,@stdlib/stats/strided/drange,@stdlib/stats/strided/smidrange" "@stdlib/stats/strided/dmin","@stdlib/stats/strided/dmax,@stdlib/stats/strided/dnanmin,@stdlib/stats/strided/min,@stdlib/stats/strided/smin" "@stdlib/stats/strided/dminabs","@stdlib/stats/strided/dmin,@stdlib/stats/strided/dmaxabs,@stdlib/stats/strided/dnanminabs,@stdlib/stats/strided/minabs,@stdlib/stats/strided/sminabs" @@ -1252,7 +1252,7 @@ "@stdlib/stats/strided/meanpn","@stdlib/stats/strided/dmeanpn,@stdlib/stats/strided/mean,@stdlib/stats/strided/nanmeanpn,@stdlib/stats/strided/smeanpn" "@stdlib/stats/strided/meanpw","@stdlib/stats/strided/dmeanpw,@stdlib/stats/strided/mean,@stdlib/stats/strided/smeanpw" "@stdlib/stats/strided/meanwd","@stdlib/stats/strided/dmeanwd,@stdlib/stats/strided/mean,@stdlib/stats/strided/nanmeanwd,@stdlib/stats/strided/smeanwd" -"@stdlib/stats/strided/mediansorted","@stdlib/stats/strided/dmediansorted,@stdlib/stats/strided/mean,@stdlib/stats/strided/smediansorted" +"@stdlib/stats/strided/mediansorted","@stdlib/stats/strided/dmedian-sorted,@stdlib/stats/strided/mean,@stdlib/stats/strided/smediansorted" "@stdlib/strided/base/meta-data-props","" "@stdlib/stats/strided/min","@stdlib/stats/strided/dmin,@stdlib/stats/strided/max,@stdlib/stats/strided/nanmin,@stdlib/stats/strided/smin" "@stdlib/stats/strided/minabs","@stdlib/stats/strided/dminabs,@stdlib/stats/strided/maxabs,@stdlib/stats/strided/min,@stdlib/stats/strided/nanminabs,@stdlib/stats/strided/sminabs" @@ -1355,7 +1355,7 @@ "@stdlib/stats/strided/smeanpn","@stdlib/stats/strided/dmeanpn,@stdlib/stats/strided/meanpn,@stdlib/stats/strided/smean,@stdlib/stats/strided/snanmeanpn" "@stdlib/stats/strided/smeanpw","@stdlib/stats/strided/dmeanpw,@stdlib/stats/strided/meanpw,@stdlib/stats/strided/smean" "@stdlib/stats/strided/smeanwd","@stdlib/stats/strided/dmeanwd,@stdlib/stats/strided/meanwd,@stdlib/stats/strided/smean,@stdlib/stats/strided/snanmeanwd" -"@stdlib/stats/strided/smediansorted","@stdlib/stats/strided/dmediansorted,@stdlib/stats/strided/mediansorted,@stdlib/stats/strided/smean" +"@stdlib/stats/strided/smediansorted","@stdlib/stats/strided/dmedian-sorted,@stdlib/stats/strided/mediansorted,@stdlib/stats/strided/smean" "@stdlib/stats/strided/smidrange","@stdlib/stats/strided/dmidrange,@stdlib/stats/strided/smax,@stdlib/stats/strided/smean,@stdlib/stats/strided/smin,@stdlib/stats/strided/srange" "@stdlib/stats/strided/smin","@stdlib/stats/strided/dmin,@stdlib/stats/strided/min,@stdlib/stats/strided/smax,@stdlib/stats/strided/snanmin" "@stdlib/stats/strided/sminabs","@stdlib/stats/strided/dminabs,@stdlib/stats/strided/minabs,@stdlib/stats/strided/smaxabs,@stdlib/stats/strided/smin,@stdlib/stats/strided/snanminabs" @@ -1997,6 +1997,7 @@ "@stdlib/array/int32","@stdlib/array/buffer,@stdlib/array/float32,@stdlib/array/float64,@stdlib/array/int16,@stdlib/array/int8,@stdlib/array/uint16,@stdlib/array/uint32,@stdlib/array/uint8,@stdlib/array/uint8c" "@stdlib/ndarray/matrix/int32","@stdlib/ndarray/matrix/float64,@stdlib/ndarray/matrix/float32,@stdlib/ndarray/matrix/complex128,@stdlib/ndarray/matrix/complex64,@stdlib/ndarray/matrix/ctor,@stdlib/ndarray/vector/int32,@stdlib/ndarray/ctor" "@stdlib/ndarray/vector/int32","@stdlib/ndarray/vector/float64,@stdlib/ndarray/vector/float32,@stdlib/ndarray/vector/int16,@stdlib/ndarray/vector/int8,@stdlib/ndarray/vector/uint8,@stdlib/ndarray/vector/uint16,@stdlib/ndarray/vector/uint32,@stdlib/ndarray/vector/uint8c,@stdlib/ndarray/vector/complex128,@stdlib/ndarray/vector/complex64,@stdlib/ndarray/vector/bool,@stdlib/ndarray/vector/ctor,@stdlib/ndarray/matrix/int32,@stdlib/ndarray/ctor" +"@stdlib/number/int64/ctor","@stdlib/bigint/ctor,@stdlib/number/ctor,@stdlib/number/uint64/ctor" "@stdlib/assert/is-big-endian","@stdlib/assert/is-little-endian" "@stdlib/assert/is-browser","" "@stdlib/assert/is-darwin","" @@ -3162,7 +3163,7 @@ "@stdlib/constants/uint32/num-bytes","@stdlib/constants/int32/num-bytes,@stdlib/constants/uint16/num-bytes,@stdlib/constants/uint8/num-bytes" "@stdlib/array/uint32","@stdlib/array/buffer,@stdlib/array/float32,@stdlib/array/float64,@stdlib/array/int16,@stdlib/array/int32,@stdlib/array/int8,@stdlib/array/uint16,@stdlib/array/uint8,@stdlib/array/uint8c" "@stdlib/ndarray/vector/uint32","@stdlib/ndarray/vector/float64,@stdlib/ndarray/vector/float32,@stdlib/ndarray/vector/int16,@stdlib/ndarray/vector/int32,@stdlib/ndarray/vector/int8,@stdlib/ndarray/vector/uint16,@stdlib/ndarray/vector/uint8,@stdlib/ndarray/vector/uint8c,@stdlib/ndarray/vector/complex128,@stdlib/ndarray/vector/complex64,@stdlib/ndarray/vector/bool,@stdlib/ndarray/vector/ctor,@stdlib/ndarray/ctor" -"@stdlib/number/uint64/ctor","@stdlib/number/ctor" +"@stdlib/number/uint64/ctor","@stdlib/bigint/ctor,@stdlib/number/ctor,@stdlib/number/int64/ctor" "@stdlib/process/umask","" "@stdlib/string/uncapitalize","@stdlib/string/capitalize,@stdlib/string/lowercase" "@stdlib/object/uncapitalize-keys","@stdlib/object/capitalize-keys,@stdlib/object/lowercase-keys" diff --git a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json index 0c34fd6a63ac..1ce94ffac34f 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2related/data/data.json @@ -1 +1 @@ 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diff --git a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv index 073be276725b..d67983a40b2f 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.csv @@ -1074,7 +1074,7 @@ "@stdlib/stats/strided/dmeanvar","@stdlib/stats-strided-dmeanvar" "@stdlib/stats/strided/dmeanvarpn","@stdlib/stats-strided-dmeanvarpn" "@stdlib/stats/strided/dmeanwd","@stdlib/stats-strided-dmeanwd" -"@stdlib/stats/strided/dmediansorted","@stdlib/stats-strided-dmediansorted" +"@stdlib/stats/strided/dmedian-sorted","@stdlib/stats-strided-dmedian-sorted" "@stdlib/stats/strided/dmidrange","@stdlib/stats-strided-dmidrange" "@stdlib/stats/strided/dmin","@stdlib/stats-strided-dmin" "@stdlib/stats/strided/dminabs","@stdlib/stats-strided-dminabs" @@ -1997,6 +1997,7 @@ "@stdlib/array/int32","@stdlib/array-int32" "@stdlib/ndarray/matrix/int32","@stdlib/ndarray-matrix-int32" "@stdlib/ndarray/vector/int32","@stdlib/ndarray-vector-int32" +"@stdlib/number/int64/ctor","@stdlib/number-int64-ctor" "@stdlib/assert/is-big-endian","@stdlib/assert-is-big-endian" "@stdlib/assert/is-browser","@stdlib/assert-is-browser" "@stdlib/assert/is-darwin","@stdlib/assert-is-darwin" diff --git a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json index 945793e136cb..4a998a3a9158 100644 --- a/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json +++ b/lib/node_modules/@stdlib/namespace/pkg2standalone/data/data.json @@ -1 +1 @@ -{"@stdlib/math/special/abs":"@stdlib/math-special-abs","@stdlib/array/cartesian-power":"@stdlib/array-cartesian-power","@stdlib/array/cartesian-product":"@stdlib/array-cartesian-product","@stdlib/array/cartesian-square":"@stdlib/array-cartesian-square","@stdlib/string/acronym":"@stdlib/string-acronym","@stdlib/array/empty":"@stdlib/array-empty","@stdlib/array/empty-like":"@stdlib/array-empty-like","@stdlib/datasets/afinn-96":"@stdlib/datasets-afinn-96","@stdlib/datasets/afinn-111":"@stdlib/datasets-afinn-111","@stdlib/array/full":"@stdlib/array-full","@stdlib/array/full-like":"@stdlib/array-full-like","@stdlib/namespace/alias2pkg":"@stdlib/namespace-alias2pkg","@stdlib/namespace/alias2related":"@stdlib/namespace-alias2related","@stdlib/namespace/alias2standalone":"@stdlib/namespace-alias2standalone","@stdlib/namespace/aliases":"@stdlib/namespace-aliases","@stdlib/buffer/alloc-unsafe":"@stdlib/buffer-alloc-unsafe","@stdlib/array/mskfilter":"@stdlib/array-mskfilter","@stdlib/array/mskput":"@stdlib/array-mskput","@stdlib/array/mskreject":"@stdlib/array-mskreject","@stdlib/array/nans":"@stdlib/array-nans","@stdlib/array/nans-like":"@stdlib/array-nans-like","@stdlib/stats/anova1":"@stdlib/stats-anova1","@stdlib/datasets/anscombes-quartet":"@stdlib/datasets-anscombes-quartet","@stdlib/utils/any":"@stdlib/utils-any","@stdlib/utils/any-by":"@stdlib/utils-any-by","@stdlib/utils/async/any-by":"@stdlib/utils-async-any-by","@stdlib/utils/any-by-right":"@stdlib/utils-any-by-right","@stdlib/utils/async/any-by-right":"@stdlib/utils-async-any-by-right","@stdlib/object/any-in-by":"@stdlib/object-any-in-by","@stdlib/object/any-own-by":"@stdlib/object-any-own-by","@stdlib/array/ones":"@stdlib/array-ones","@stdlib/array/ones-like":"@stdlib/array-ones-like","@stdlib/array/one-to":"@stdlib/array-one-to","@stdlib/array/one-to-like":"@stdlib/array-one-to-like","@stdlib/constants/float64/apery":"@stdlib/constants-float64-apery","@stdlib/array/place":"@stdlib/array-place","@stdlib/utils/append":"@stdlib/utils-append","@stdlib/array/put":"@stdlib/array-put","@stdlib/os/arch":"@stdlib/os-arch","@stdlib/utils/argument-function":"@stdlib/utils-argument-function","@stdlib/process/argv":"@stdlib/process-argv","@stdlib/ndarray/array":"@stdlib/ndarray-array","@stdlib/buffer/from-array":"@stdlib/buffer-from-array","@stdlib/array/to-fancy":"@stdlib/array-to-fancy","@stdlib/array/to-iterator":"@stdlib/array-to-iterator","@stdlib/array/to-iterator-right":"@stdlib/array-to-iterator-right","@stdlib/array/buffer":"@stdlib/array-buffer","@stdlib/buffer/from-arraybuffer":"@stdlib/buffer-from-arraybuffer","@stdlib/array/ctors":"@stdlib/array-ctors","@stdlib/array/dtype":"@stdlib/array-dtype","@stdlib/array/dtypes":"@stdlib/array-dtypes","@stdlib/array/index":"@stdlib/array-index","@stdlib/array/min-dtype":"@stdlib/array-min-dtype","@stdlib/array/mostly-safe-casts":"@stdlib/array-mostly-safe-casts","@stdlib/array/next-dtype":"@stdlib/array-next-dtype","@stdlib/array/promotion-rules":"@stdlib/array-promotion-rules","@stdlib/array/safe-casts":"@stdlib/array-safe-casts","@stdlib/array/same-kind-casts":"@stdlib/array-same-kind-casts","@stdlib/array/shape":"@stdlib/array-shape","@stdlib/streams/node/from-array":"@stdlib/streams-node-from-array","@stdlib/array/to-view-iterator":"@stdlib/array-to-view-iterator","@stdlib/array/to-view-iterator-right":"@stdlib/array-to-view-iterator-right","@stdlib/array/slice":"@stdlib/array-slice","@stdlib/symbol/async-iterator":"@stdlib/symbol-async-iterator","@stdlib/array/take":"@stdlib/array-take","@stdlib/array/zeros":"@stdlib/array-zeros","@stdlib/array/zeros-like":"@stdlib/array-zeros-like","@stdlib/array/zero-to":"@stdlib/array-zero-to","@stdlib/array/zero-to-like":"@stdlib/array-zero-to-like","@stdlib/stats/bartlett-test":"@stdlib/stats-bartlett-test","@stdlib/math/base/special/abs":"@stdlib/math-base-special-abs","@stdlib/math/base/special/abs2":"@stdlib/math-base-special-abs2","@stdlib/math/base/special/abs2f":"@stdlib/math-base-special-abs2f","@stdlib/math/base/utils/absolute-difference":"@stdlib/math-base-utils-absolute-difference","@stdlib/math/base/special/absf":"@stdlib/math-base-special-absf","@stdlib/array/base/cartesian-power":"@stdlib/array-base-cartesian-power","@stdlib/array/base/cartesian-product":"@stdlib/array-base-cartesian-product","@stdlib/array/base/cartesian-square":"@stdlib/array-base-cartesian-square","@stdlib/math/base/special/acos":"@stdlib/math-base-special-acos","@stdlib/math/base/special/acosd":"@stdlib/math-base-special-acosd","@stdlib/math/base/special/acosdf":"@stdlib/math-base-special-acosdf","@stdlib/math/base/special/acosf":"@stdlib/math-base-special-acosf","@stdlib/math/base/special/acosh":"@stdlib/math-base-special-acosh","@stdlib/math/base/special/acot":"@stdlib/math-base-special-acot","@stdlib/math/base/special/acotd":"@stdlib/math-base-special-acotd","@stdlib/math/base/special/acotdf":"@stdlib/math-base-special-acotdf","@stdlib/math/base/special/acotf":"@stdlib/math-base-speci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diff --git a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv index e0bfae34c7d3..9c47e3928285 100644 --- a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv +++ b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.csv @@ -1074,7 +1074,7 @@ "@stdlib/stats-strided-dmeanvar","@stdlib/stats/strided/dmeanvar" "@stdlib/stats-strided-dmeanvarpn","@stdlib/stats/strided/dmeanvarpn" "@stdlib/stats-strided-dmeanwd","@stdlib/stats/strided/dmeanwd" -"@stdlib/stats-strided-dmediansorted","@stdlib/stats/strided/dmediansorted" +"@stdlib/stats-strided-dmedian-sorted","@stdlib/stats/strided/dmedian-sorted" "@stdlib/stats-strided-dmidrange","@stdlib/stats/strided/dmidrange" "@stdlib/stats-strided-dmin","@stdlib/stats/strided/dmin" "@stdlib/stats-strided-dminabs","@stdlib/stats/strided/dminabs" @@ -1997,6 +1997,7 @@ "@stdlib/array-int32","@stdlib/array/int32" "@stdlib/ndarray-matrix-int32","@stdlib/ndarray/matrix/int32" "@stdlib/ndarray-vector-int32","@stdlib/ndarray/vector/int32" +"@stdlib/number-int64-ctor","@stdlib/number/int64/ctor" "@stdlib/assert-is-big-endian","@stdlib/assert/is-big-endian" "@stdlib/assert-is-browser","@stdlib/assert/is-browser" "@stdlib/assert-is-darwin","@stdlib/assert/is-darwin" diff --git a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json index dd1153a58cce..47180c4baa72 100644 --- a/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json +++ b/lib/node_modules/@stdlib/namespace/standalone2pkg/data/data.json @@ -1 +1 @@ -{"@stdlib/math-special-abs":"@stdlib/math/special/abs","@stdlib/array-cartesian-power":"@stdlib/array/cartesian-power","@stdlib/array-cartesian-product":"@stdlib/array/cartesian-product","@stdlib/array-cartesian-square":"@stdlib/array/cartesian-square","@stdlib/string-acronym":"@stdlib/string/acronym","@stdlib/array-empty":"@stdlib/array/empty","@stdlib/array-empty-like":"@stdlib/array/empty-like","@stdlib/datasets-afinn-96":"@stdlib/datasets/afinn-96","@stdlib/datasets-afinn-111":"@stdlib/datasets/afinn-111","@stdlib/array-full":"@stdlib/array/full","@stdlib/array-full-like":"@stdlib/array/full-like","@stdlib/namespace-alias2pkg":"@stdlib/namespace/alias2pkg","@stdlib/namespace-alias2related":"@stdlib/namespace/alias2related","@stdlib/namespace-alias2standalone":"@stdlib/namespace/alias2standalone","@stdlib/namespace-aliases":"@stdlib/namespace/aliases","@stdlib/buffer-alloc-unsafe":"@stdlib/buffer/alloc-unsafe","@stdlib/array-mskfilter":"@stdlib/array/mskfilter","@stdlib/array-mskput":"@stdlib/array/mskput","@stdlib/array-mskreject":"@stdlib/array/mskreject","@stdlib/array-nans":"@stdlib/array/nans","@stdlib/array-nans-like":"@stdlib/array/nans-like","@stdlib/stats-anova1":"@stdlib/stats/anova1","@stdlib/datasets-anscombes-quartet":"@stdlib/datasets/anscombes-quartet","@stdlib/utils-any":"@stdlib/utils/any","@stdlib/utils-any-by":"@stdlib/utils/any-by","@stdlib/utils-async-any-by":"@stdlib/utils/async/any-by","@stdlib/utils-any-by-right":"@stdlib/utils/any-by-right","@stdlib/utils-async-any-by-right":"@stdlib/utils/async/any-by-right","@stdlib/object-any-in-by":"@stdlib/object/any-in-by","@stdlib/object-any-own-by":"@stdlib/object/any-own-by","@stdlib/array-ones":"@stdlib/array/ones","@stdlib/array-ones-like":"@stdlib/array/ones-like","@stdlib/array-one-to":"@stdlib/array/one-to","@stdlib/array-one-to-like":"@stdlib/array/one-to-like","@stdlib/constants-float64-apery":"@stdlib/constants/float64/apery","@stdlib/array-place":"@stdlib/array/place","@stdlib/utils-append":"@stdlib/utils/append","@stdlib/array-put":"@stdlib/array/put","@stdlib/os-arch":"@stdlib/os/arch","@stdlib/utils-argument-function":"@stdlib/utils/argument-function","@stdlib/process-argv":"@stdlib/process/argv","@stdlib/ndarray-array":"@stdlib/ndarray/array","@stdlib/buffer-from-array":"@stdlib/buffer/from-array","@stdlib/array-to-fancy":"@stdlib/array/to-fancy","@stdlib/array-to-iterator":"@stdlib/array/to-iterator","@stdlib/array-to-iterator-right":"@stdlib/array/to-iterator-right","@stdlib/array-buffer":"@stdlib/array/buffer","@stdlib/buffer-from-arraybuffer":"@stdlib/buffer/from-arraybuffer","@stdlib/array-ctors":"@stdlib/array/ctors","@stdlib/array-dtype":"@stdlib/array/dtype","@stdlib/array-dtypes":"@stdlib/array/dtypes","@stdlib/array-index":"@stdlib/array/index","@stdlib/array-min-dtype":"@stdlib/array/min-dtype","@stdlib/array-mostly-safe-casts":"@stdlib/array/mostly-safe-casts","@stdlib/array-next-dtype":"@stdlib/array/next-dtype","@stdlib/array-promotion-rules":"@stdlib/array/promotion-rules","@stdlib/array-safe-casts":"@stdlib/array/safe-casts","@stdlib/array-same-kind-casts":"@stdlib/array/same-kind-casts","@stdlib/array-shape":"@stdlib/array/shape","@stdlib/streams-node-from-array":"@stdlib/streams/node/from-array","@stdlib/array-to-view-iterator":"@stdlib/array/to-view-iterator","@stdlib/array-to-view-iterator-right":"@stdlib/array/to-view-iterator-right","@stdlib/array-slice":"@stdlib/array/slice","@stdlib/symbol-async-iterator":"@stdlib/symbol/async-iterator","@stdlib/array-take":"@stdlib/array/take","@stdlib/array-zeros":"@stdlib/array/zeros","@stdlib/array-zeros-like":"@stdlib/array/zeros-like","@stdlib/array-zero-to":"@stdlib/array/zero-to","@stdlib/array-zero-to-like":"@stdlib/array/zero-to-like","@stdlib/stats-bartlett-test":"@stdlib/stats/bartlett-test","@stdlib/math-base-special-abs":"@stdlib/math/base/special/abs","@stdlib/math-base-special-abs2":"@stdlib/math/base/special/abs2","@stdlib/math-base-special-abs2f":"@stdlib/math/base/special/abs2f","@stdlib/math-base-utils-absolute-difference":"@stdlib/math/base/utils/absolute-difference","@stdlib/math-base-special-absf":"@stdlib/math/base/special/absf","@stdlib/array-base-cartesian-power":"@stdlib/array/base/cartesian-power","@stdlib/array-base-cartesian-product":"@stdlib/array/base/cartesian-product","@stdlib/array-base-cartesian-square":"@stdlib/array/base/cartesian-square","@stdlib/math-base-special-acos":"@stdlib/math/base/special/acos","@stdlib/math-base-special-acosd":"@stdlib/math/base/special/acosd","@stdlib/math-base-special-acosdf":"@stdlib/math/base/special/acosdf","@stdlib/math-base-special-acosf":"@stdlib/math/base/special/acosf","@stdlib/math-base-special-acosh":"@stdlib/math/base/special/acosh","@stdlib/math-base-special-acot":"@stdlib/math/base/special/acot","@stdlib/math-base-special-acotd":"@stdlib/math/base/special/acotd","@stdlib/math-base-special-acotdf":"@stdlib/math/base/special/acotdf","@stdlib/math-base-special-acotf":"@stdlib/math/base/speci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diff --git a/lib/node_modules/@stdlib/ndarray/base/assign-scalar/README.md b/lib/node_modules/@stdlib/ndarray/base/assign-scalar/README.md index 1210577c042d..a359fef3100b 100644 --- a/lib/node_modules/@stdlib/ndarray/base/assign-scalar/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/assign-scalar/README.md @@ -40,8 +40,6 @@ var assignScalar = require( '@stdlib/ndarray/base/assign-scalar' ); Assigns a scalar value to every element of an output [ndarray][@stdlib/ndarray/base/ctor]. - - ```javascript var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); var Float64Array = require( '@stdlib/array/float64' ); diff --git a/lib/node_modules/@stdlib/ndarray/base/consensus-order/README.md b/lib/node_modules/@stdlib/ndarray/base/consensus-order/README.md index 9943616d1595..75ee171690d7 100644 --- a/lib/node_modules/@stdlib/ndarray/base/consensus-order/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/consensus-order/README.md @@ -83,8 +83,6 @@ The function accepts the following arguments: ## Examples - - ```javascript diff --git a/lib/node_modules/@stdlib/ndarray/base/nullary-strided1d/lib/main_factory.js b/lib/node_modules/@stdlib/ndarray/base/nullary-strided1d/lib/main_factory.js index 872472424c2e..1f5dd733b280 100644 --- a/lib/node_modules/@stdlib/ndarray/base/nullary-strided1d/lib/main_factory.js +++ b/lib/node_modules/@stdlib/ndarray/base/nullary-strided1d/lib/main_factory.js @@ -371,15 +371,13 @@ function factory( options ) { // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... return NULLARY[ K ]( fcn, arr, views, shl, slx, ord === 1, strategyX, opts ); // eslint-disable-line max-len } - // Check whether blocked iteration is prohibited due to a requirement that the order of element traversal match the memory layout of a provided ndarray... - if ( OPTS.strictTraversalOrder && K <= MAX_DIMS ) { - // We have two choices here: (1) we could copy to contiguous memory or (2) we can perform normal nested loop iteration, even though this is not cache-optimal based on the assumption that, while this may hurt performance, for many cases (i.e., smaller ndarrays), this should be fine and likely better than performing a complete copy... - return NULLARY[ K ]( fcn, arr, views, shl, slx, ord === 1, strategyX, opts ); // eslint-disable-line max-len - } // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... if ( K <= MAX_DIMS ) { + // Check whether blocked iteration is prohibited due to a requirement that the order of element traversal match the memory layout of a provided ndarray... + if ( OPTS.strictTraversalOrder ) { + // We have two choices here: (1) we could copy to contiguous memory or (2) we can perform normal nested loop iteration, even though this is not cache-optimal based on the assumption that, while this may hurt performance, for many cases (i.e., smaller ndarrays), this should be fine and likely better than performing a complete copy... + return NULLARY[ K ]( fcn, arr, views, shl, slx, ord === 1, strategyX, opts ); // eslint-disable-line max-len + } return BLOCKED_NULLARY[ K-2 ]( fcn, arr, views, shl, slx, strategyX, opts ); // eslint-disable-line max-len } // Perform linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... diff --git a/lib/node_modules/@stdlib/ndarray/base/output-order/README.md b/lib/node_modules/@stdlib/ndarray/base/output-order/README.md index 474346eafb49..deca1ae85d20 100644 --- a/lib/node_modules/@stdlib/ndarray/base/output-order/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/output-order/README.md @@ -80,8 +80,6 @@ The function accepts the following arguments: ## Examples - - ```javascript diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-addon-dispatch/README.md b/lib/node_modules/@stdlib/ndarray/base/unary-addon-dispatch/README.md index f41fdfbe12a9..d35334e3e3f8 100644 --- a/lib/node_modules/@stdlib/ndarray/base/unary-addon-dispatch/README.md +++ b/lib/node_modules/@stdlib/ndarray/base/unary-addon-dispatch/README.md @@ -125,8 +125,6 @@ where ## Examples - - ```javascript diff --git a/lib/node_modules/@stdlib/ndarray/base/unary-strided1d/lib/main_factory.js b/lib/node_modules/@stdlib/ndarray/base/unary-strided1d/lib/main_factory.js index 84fe8be3387c..f6607ec5c0c1 100644 --- a/lib/node_modules/@stdlib/ndarray/base/unary-strided1d/lib/main_factory.js +++ b/lib/node_modules/@stdlib/ndarray/base/unary-strided1d/lib/main_factory.js @@ -499,15 +499,13 @@ function factory( options ) { // So long as iteration for each respective array always moves in the same direction (i.e., no mixed sign strides) and the memory layouts are the same, we can leverage cache-optimal (i.e., normal) nested loops without resorting to blocked iteration... return UNARY[ K ]( fcn, arr, views, shl, slx, sly, ord === 1, strategyX, strategyY, opts ); // eslint-disable-line max-len } - // Check whether blocked iteration is prohibited due to a requirement that the order of element traversal match the memory layout of a provided input ndarray... - if ( OPTS.strictTraversalOrder && K <= MAX_DIMS ) { - // We have two choices here: (1) we could copy to contiguous memory or (2) we can perform normal nested loop iteration, even though this is not cache-optimal based on the assumption that, while this may hurt performance, for many cases (i.e., smaller ndarrays), this should be fine and likely better than performing a complete copy... - return UNARY[ K ]( fcn, arr, views, shl, slx, sly, ord === 1, strategyX, strategyY, opts ); // eslint-disable-line max-len - } // At this point, we're either dealing with non-contiguous n-dimensional arrays, high dimensional n-dimensional arrays, and/or arrays having differing memory layouts, so our only hope is that we can still perform blocked iteration... - - // Determine whether we can perform blocked iteration... if ( K <= MAX_DIMS ) { + // Check whether blocked iteration is prohibited due to a requirement that the order of element traversal match the memory layout of a provided input ndarray... + if ( OPTS.strictTraversalOrder ) { + // We have two choices here: (1) we could copy to contiguous memory or (2) we can perform normal nested loop iteration, even though this is not cache-optimal based on the assumption that, while this may hurt performance, for many cases (i.e., smaller ndarrays), this should be fine and likely better than performing a complete copy... + return UNARY[ K ]( fcn, arr, views, shl, slx, sly, ord === 1, strategyX, strategyY, opts ); // eslint-disable-line max-len + } return BLOCKED_UNARY[ K-2 ]( fcn, arr, views, shl, slx, sly, strategyX, strategyY, opts ); // eslint-disable-line max-len } // Perform linear view iteration without regard for how data is stored in memory (i.e., take the slow path)... diff --git a/lib/node_modules/@stdlib/ndarray/casting-modes/test/test.js b/lib/node_modules/@stdlib/ndarray/casting-modes/test/test.js index fa63b047facc..ff1fd96dfb99 100644 --- a/lib/node_modules/@stdlib/ndarray/casting-modes/test/test.js +++ b/lib/node_modules/@stdlib/ndarray/casting-modes/test/test.js @@ -74,7 +74,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/ndarray/index-modes/benchmark/benchmark.js b/lib/node_modules/@stdlib/ndarray/index-modes/benchmark/benchmark.js index 86fa5b935b17..8eb2581d62ce 100644 --- a/lib/node_modules/@stdlib/ndarray/index-modes/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/ndarray/index-modes/benchmark/benchmark.js @@ -35,8 +35,8 @@ bench( pkg, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { out = modes(); - if ( out.length !== 3 ) { - b.fail( 'should return an array of length 3' ); + if ( out.length < 2 ) { + b.fail( 'should return an array of strings' ); } } b.toc(); diff --git a/lib/node_modules/@stdlib/ndarray/matrix/complex128/README.md b/lib/node_modules/@stdlib/ndarray/matrix/complex128/README.md index 4e4943ec3456..5910ae1246a5 100644 --- a/lib/node_modules/@stdlib/ndarray/matrix/complex128/README.md +++ b/lib/node_modules/@stdlib/ndarray/matrix/complex128/README.md @@ -263,6 +263,18 @@ console.log( ndarray2array( v ) );
+* * * + +## See Also + +- [`@stdlib/ndarray/matrix/float64`][@stdlib/ndarray/matrix/float64]: create a double-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/float32`][@stdlib/ndarray/matrix/float32]: create a single-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/int32`][@stdlib/ndarray/matrix/int32]: create a 32-bit signed integer matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex64`][@stdlib/ndarray/matrix/complex64]: create a single-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/ctor`][@stdlib/ndarray/matrix/ctor]: create a matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/vector/complex128`][@stdlib/ndarray/vector/complex128]: create a double-precision complex floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +
@@ -275,6 +287,22 @@ console.log( ndarray2array( v ) ); [@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + + +[@stdlib/ndarray/matrix/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float64 + +[@stdlib/ndarray/matrix/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float32 + +[@stdlib/ndarray/matrix/int32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/int32 + +[@stdlib/ndarray/matrix/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex64 + +[@stdlib/ndarray/matrix/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/ctor + +[@stdlib/ndarray/vector/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/complex128 + + + diff --git a/lib/node_modules/@stdlib/ndarray/matrix/ctor/README.md b/lib/node_modules/@stdlib/ndarray/matrix/ctor/README.md index da88ba6ea72f..de5044bde346 100644 --- a/lib/node_modules/@stdlib/ndarray/matrix/ctor/README.md +++ b/lib/node_modules/@stdlib/ndarray/matrix/ctor/README.md @@ -390,6 +390,18 @@ logEachMap( 'shape: [%3s]. dtype: %7s. sum: %d.', args[ 0 ], args[ 1 ], clbk );
+* * * + +## See Also + +- [`@stdlib/ndarray/matrix/float64`][@stdlib/ndarray/matrix/float64]: create a double-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/float32`][@stdlib/ndarray/matrix/float32]: create a single-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/int32`][@stdlib/ndarray/matrix/int32]: create a 32-bit signed integer matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex128`][@stdlib/ndarray/matrix/complex128]: create a double-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex64`][@stdlib/ndarray/matrix/complex64]: create a single-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/vector/ctor`][@stdlib/ndarray/vector/ctor]: create a vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +
@@ -404,6 +416,22 @@ logEachMap( 'shape: [%3s]. dtype: %7s. sum: %d.', args[ 0 ], args[ 1 ], clbk ); [@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes + + +[@stdlib/ndarray/matrix/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float64 + +[@stdlib/ndarray/matrix/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float32 + +[@stdlib/ndarray/matrix/int32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/int32 + +[@stdlib/ndarray/matrix/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex128 + +[@stdlib/ndarray/matrix/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex64 + +[@stdlib/ndarray/vector/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/ctor + + + diff --git a/lib/node_modules/@stdlib/ndarray/matrix/float32/README.md b/lib/node_modules/@stdlib/ndarray/matrix/float32/README.md index 63d8f3a952e7..facf728a2aeb 100644 --- a/lib/node_modules/@stdlib/ndarray/matrix/float32/README.md +++ b/lib/node_modules/@stdlib/ndarray/matrix/float32/README.md @@ -255,6 +255,18 @@ console.log( ndarray2array( v ) );
+* * * + +## See Also + +- [`@stdlib/ndarray/matrix/float64`][@stdlib/ndarray/matrix/float64]: create a double-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/int32`][@stdlib/ndarray/matrix/int32]: create a 32-bit signed integer matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex128`][@stdlib/ndarray/matrix/complex128]: create a double-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex64`][@stdlib/ndarray/matrix/complex64]: create a single-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/ctor`][@stdlib/ndarray/matrix/ctor]: create a matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/vector/float32`][@stdlib/ndarray/vector/float32]: create a single-precision floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +
@@ -267,6 +279,22 @@ console.log( ndarray2array( v ) ); [@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + + +[@stdlib/ndarray/matrix/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float64 + +[@stdlib/ndarray/matrix/int32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/int32 + +[@stdlib/ndarray/matrix/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex128 + +[@stdlib/ndarray/matrix/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex64 + +[@stdlib/ndarray/matrix/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/ctor + +[@stdlib/ndarray/vector/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/float32 + + + diff --git a/lib/node_modules/@stdlib/ndarray/matrix/float64/README.md b/lib/node_modules/@stdlib/ndarray/matrix/float64/README.md index 0c7de5a59146..ba38244ba109 100644 --- a/lib/node_modules/@stdlib/ndarray/matrix/float64/README.md +++ b/lib/node_modules/@stdlib/ndarray/matrix/float64/README.md @@ -255,6 +255,18 @@ console.log( ndarray2array( v ) );
+* * * + +## See Also + +- [`@stdlib/ndarray/matrix/float32`][@stdlib/ndarray/matrix/float32]: create a single-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/int32`][@stdlib/ndarray/matrix/int32]: create a 32-bit signed integer matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex128`][@stdlib/ndarray/matrix/complex128]: create a double-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex64`][@stdlib/ndarray/matrix/complex64]: create a single-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/ctor`][@stdlib/ndarray/matrix/ctor]: create a matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/vector/float64`][@stdlib/ndarray/vector/float64]: create a double-precision floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +
@@ -267,6 +279,22 @@ console.log( ndarray2array( v ) ); [@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + + +[@stdlib/ndarray/matrix/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float32 + +[@stdlib/ndarray/matrix/int32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/int32 + +[@stdlib/ndarray/matrix/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex128 + +[@stdlib/ndarray/matrix/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex64 + +[@stdlib/ndarray/matrix/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/ctor + +[@stdlib/ndarray/vector/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/float64 + + + diff --git a/lib/node_modules/@stdlib/ndarray/matrix/int32/README.md b/lib/node_modules/@stdlib/ndarray/matrix/int32/README.md index b99544f00ab2..ce88668aba3c 100644 --- a/lib/node_modules/@stdlib/ndarray/matrix/int32/README.md +++ b/lib/node_modules/@stdlib/ndarray/matrix/int32/README.md @@ -255,6 +255,18 @@ console.log( ndarray2array( v ) );
+* * * + +## See Also + +- [`@stdlib/ndarray/matrix/float64`][@stdlib/ndarray/matrix/float64]: create a double-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/float32`][@stdlib/ndarray/matrix/float32]: create a single-precision floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex128`][@stdlib/ndarray/matrix/complex128]: create a double-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/complex64`][@stdlib/ndarray/matrix/complex64]: create a single-precision complex floating-point matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/matrix/ctor`][@stdlib/ndarray/matrix/ctor]: create a matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/vector/int32`][@stdlib/ndarray/vector/int32]: create a signed 32-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +
@@ -267,6 +279,22 @@ console.log( ndarray2array( v ) ); [@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + + +[@stdlib/ndarray/matrix/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float64 + +[@stdlib/ndarray/matrix/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float32 + +[@stdlib/ndarray/matrix/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex128 + +[@stdlib/ndarray/matrix/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex64 + +[@stdlib/ndarray/matrix/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/ctor + +[@stdlib/ndarray/vector/int32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/int32 + + + diff --git a/lib/node_modules/@stdlib/ndarray/orders/test/test.js b/lib/node_modules/@stdlib/ndarray/orders/test/test.js index b37a42f576b6..fe51bbf6a151 100644 --- a/lib/node_modules/@stdlib/ndarray/orders/test/test.js +++ b/lib/node_modules/@stdlib/ndarray/orders/test/test.js @@ -66,7 +66,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/ndarray/vector/complex64/README.md b/lib/node_modules/@stdlib/ndarray/vector/complex64/README.md index 17d0f280186c..68fa7b550cef 100644 --- a/lib/node_modules/@stdlib/ndarray/vector/complex64/README.md +++ b/lib/node_modules/@stdlib/ndarray/vector/complex64/README.md @@ -189,6 +189,7 @@ console.log( v.get() ); ## See Also +- [`@stdlib/ndarray/matrix/complex64`][@stdlib/ndarray/matrix/complex64]: create a single-precision complex floating-point matrix (i.e., a two-dimensional ndarray). - [`@stdlib/ndarray/vector/float64`][@stdlib/ndarray/vector/float64]: create a double-precision floating-point vector (i.e., a one-dimensional ndarray). - [`@stdlib/ndarray/vector/float32`][@stdlib/ndarray/vector/float32]: create a single-precision floating-point vector (i.e., a one-dimensional ndarray). - [`@stdlib/ndarray/vector/int16`][@stdlib/ndarray/vector/int16]: create a signed 16-bit integer vector (i.e., a one-dimensional ndarray). @@ -217,6 +218,8 @@ console.log( v.get() ); +[@stdlib/ndarray/matrix/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/complex64 + [@stdlib/ndarray/vector/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/float64 [@stdlib/ndarray/vector/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/float32 diff --git a/lib/node_modules/@stdlib/ndarray/vector/ctor/README.md b/lib/node_modules/@stdlib/ndarray/vector/ctor/README.md index 7fe30888b768..1c7b4a993aed 100644 --- a/lib/node_modules/@stdlib/ndarray/vector/ctor/README.md +++ b/lib/node_modules/@stdlib/ndarray/vector/ctor/README.md @@ -296,8 +296,17 @@ logEachMap( 'len: %2d. dtype: %7s. sum: %d.', args[ 0 ], args[ 1 ], clbk ); - [`@stdlib/ndarray/vector/float64`][@stdlib/ndarray/vector/float64]: create a double-precision floating-point vector (i.e., a one-dimensional ndarray). - [`@stdlib/ndarray/vector/float32`][@stdlib/ndarray/vector/float32]: create a single-precision floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/int16`][@stdlib/ndarray/vector/int16]: create a signed 16-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/int32`][@stdlib/ndarray/vector/int32]: create a signed 32-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/int8`][@stdlib/ndarray/vector/int8]: create a signed 8-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint16`][@stdlib/ndarray/vector/uint16]: create an unsigned 16-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint32`][@stdlib/ndarray/vector/uint32]: create an unsigned 32-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint8`][@stdlib/ndarray/vector/uint8]: create an unsigned 8-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint8c`][@stdlib/ndarray/vector/uint8c]: create a clamped unsigned 8-bit integer vector (i.e., a one-dimensional ndarray). - [`@stdlib/ndarray/vector/complex128`][@stdlib/ndarray/vector/complex128]: create a double-precision complex floating-point vector (i.e., a one-dimensional ndarray). - [`@stdlib/ndarray/vector/complex64`][@stdlib/ndarray/vector/complex64]: create a single-precision complex floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/bool`][@stdlib/ndarray/vector/bool]: create a boolean vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/matrix/ctor`][@stdlib/ndarray/matrix/ctor]: create a matrix (i.e., a two-dimensional ndarray). - [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. @@ -320,10 +329,28 @@ logEachMap( 'len: %2d. dtype: %7s. sum: %d.', args[ 0 ], args[ 1 ], clbk ); [@stdlib/ndarray/vector/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/float32 +[@stdlib/ndarray/vector/int16]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/int16 + +[@stdlib/ndarray/vector/int32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/int32 + +[@stdlib/ndarray/vector/int8]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/int8 + +[@stdlib/ndarray/vector/uint16]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint16 + +[@stdlib/ndarray/vector/uint32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint32 + +[@stdlib/ndarray/vector/uint8]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint8 + +[@stdlib/ndarray/vector/uint8c]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint8c + [@stdlib/ndarray/vector/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/complex128 [@stdlib/ndarray/vector/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/complex64 +[@stdlib/ndarray/vector/bool]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/bool + +[@stdlib/ndarray/matrix/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/ctor + diff --git a/lib/node_modules/@stdlib/ndarray/vector/float32/README.md b/lib/node_modules/@stdlib/ndarray/vector/float32/README.md index 75f0f00502e5..ffc913523731 100644 --- a/lib/node_modules/@stdlib/ndarray/vector/float32/README.md +++ b/lib/node_modules/@stdlib/ndarray/vector/float32/README.md @@ -195,6 +195,7 @@ console.log( v.get() ); - [`@stdlib/ndarray/vector/complex64`][@stdlib/ndarray/vector/complex64]: create a single-precision complex floating-point vector (i.e., a one-dimensional ndarray). - [`@stdlib/ndarray/vector/bool`][@stdlib/ndarray/vector/bool]: create a boolean vector (i.e., a one-dimensional ndarray). - [`@stdlib/ndarray/vector/ctor`][@stdlib/ndarray/vector/ctor]: create a vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/matrix/float32`][@stdlib/ndarray/matrix/float32]: create a single-precision floating-point matrix (i.e., a two-dimensional ndarray). - [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. @@ -235,6 +236,8 @@ console.log( v.get() ); [@stdlib/ndarray/vector/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/ctor +[@stdlib/ndarray/matrix/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/float32 + diff --git a/lib/node_modules/@stdlib/ndarray/vector/int32/README.md b/lib/node_modules/@stdlib/ndarray/vector/int32/README.md index f69aa50e4d7b..1d5252a211e1 100644 --- a/lib/node_modules/@stdlib/ndarray/vector/int32/README.md +++ b/lib/node_modules/@stdlib/ndarray/vector/int32/README.md @@ -179,6 +179,25 @@ console.log( v.get() );
+* * * + +## See Also + +- [`@stdlib/ndarray/vector/float64`][@stdlib/ndarray/vector/float64]: create a double-precision floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/float32`][@stdlib/ndarray/vector/float32]: create a single-precision floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/int16`][@stdlib/ndarray/vector/int16]: create a signed 16-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/int8`][@stdlib/ndarray/vector/int8]: create a signed 8-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint8`][@stdlib/ndarray/vector/uint8]: create an unsigned 8-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint16`][@stdlib/ndarray/vector/uint16]: create an unsigned 16-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint32`][@stdlib/ndarray/vector/uint32]: create an unsigned 32-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/uint8c`][@stdlib/ndarray/vector/uint8c]: create a clamped unsigned 8-bit integer vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/complex128`][@stdlib/ndarray/vector/complex128]: create a double-precision complex floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/complex64`][@stdlib/ndarray/vector/complex64]: create a single-precision complex floating-point vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/bool`][@stdlib/ndarray/vector/bool]: create a boolean vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/vector/ctor`][@stdlib/ndarray/vector/ctor]: create a vector (i.e., a one-dimensional ndarray). +- [`@stdlib/ndarray/matrix/int32`][@stdlib/ndarray/matrix/int32]: create a 32-bit signed integer matrix (i.e., a two-dimensional ndarray). +- [`@stdlib/ndarray/ctor`][@stdlib/ndarray/ctor]: multidimensional array constructor. +
@@ -191,6 +210,36 @@ console.log( v.get() ); [@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor + + +[@stdlib/ndarray/vector/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/float64 + +[@stdlib/ndarray/vector/float32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/float32 + +[@stdlib/ndarray/vector/int16]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/int16 + +[@stdlib/ndarray/vector/int8]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/int8 + +[@stdlib/ndarray/vector/uint8]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint8 + +[@stdlib/ndarray/vector/uint16]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint16 + +[@stdlib/ndarray/vector/uint32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint32 + +[@stdlib/ndarray/vector/uint8c]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/uint8c + +[@stdlib/ndarray/vector/complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/complex128 + +[@stdlib/ndarray/vector/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/complex64 + +[@stdlib/ndarray/vector/bool]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/bool + +[@stdlib/ndarray/vector/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vector/ctor + +[@stdlib/ndarray/matrix/int32]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/matrix/int32 + + + diff --git a/lib/node_modules/@stdlib/number/float32/base/identity/lib/main.js b/lib/node_modules/@stdlib/number/float32/base/identity/lib/main.js index 173bd29e4923..98cd954616cc 100644 --- a/lib/node_modules/@stdlib/number/float32/base/identity/lib/main.js +++ b/lib/node_modules/@stdlib/number/float32/base/identity/lib/main.js @@ -18,6 +18,8 @@ 'use strict'; +// MAIN // + /** * Evaluates the identity function for a single-precision floating-point number `x`. * diff --git a/lib/node_modules/@stdlib/number/float64/base/signbit/README.md b/lib/node_modules/@stdlib/number/float64/base/signbit/README.md index 8be728bd60ea..9b11de3de16a 100644 --- a/lib/node_modules/@stdlib/number/float64/base/signbit/README.md +++ b/lib/node_modules/@stdlib/number/float64/base/signbit/README.md @@ -147,7 +147,7 @@ int8_t stdlib_base_float64_signbit( const double x ); #include int main( void ) { - double x[] = { 3.14, -3.14, 0.0, -0.0, 4.0, 1.0, -1.0, 1.0e308, -1.0e308 }; + const double x[] = { 3.14, -3.14, 0.0, -0.0, 4.0, 1.0, -1.0, 1.0e308, -1.0e308 }; int8_t out; int i; diff --git a/lib/node_modules/@stdlib/number/float64/base/signbit/examples/c/example.c b/lib/node_modules/@stdlib/number/float64/base/signbit/examples/c/example.c index 457069430682..984064b006cc 100644 --- a/lib/node_modules/@stdlib/number/float64/base/signbit/examples/c/example.c +++ b/lib/node_modules/@stdlib/number/float64/base/signbit/examples/c/example.c @@ -22,7 +22,7 @@ #include int main( void ) { - double x[] = { 3.14, -3.14, 0.0, -0.0, 4.0, 1.0, -1.0, 1.0e308, -1.0e308 }; + const double x[] = { 3.14, -3.14, 0.0, -0.0, 4.0, 1.0, -1.0, 1.0e308, -1.0e308 }; int8_t out; int i; diff --git a/lib/node_modules/@stdlib/number/int16/base/identity/lib/main.js b/lib/node_modules/@stdlib/number/int16/base/identity/lib/main.js index 6de322d8b878..05c384b9417e 100644 --- a/lib/node_modules/@stdlib/number/int16/base/identity/lib/main.js +++ b/lib/node_modules/@stdlib/number/int16/base/identity/lib/main.js @@ -18,6 +18,8 @@ 'use strict'; +// MAIN // + /** * Evaluates the identity function for a signed 16-bit integer `x`. * diff --git a/lib/node_modules/@stdlib/number/int32/base/identity/lib/main.js b/lib/node_modules/@stdlib/number/int32/base/identity/lib/main.js index 3024b88a12ca..754a74309f96 100644 --- a/lib/node_modules/@stdlib/number/int32/base/identity/lib/main.js +++ b/lib/node_modules/@stdlib/number/int32/base/identity/lib/main.js @@ -18,6 +18,8 @@ 'use strict'; +// MAIN // + /** * Evaluates the identity function for a signed 32-bit integer `x`. * diff --git a/lib/node_modules/@stdlib/number/int64/ctor/README.md b/lib/node_modules/@stdlib/number/int64/ctor/README.md index 4e1d3d1d6991..0e54cca98361 100644 --- a/lib/node_modules/@stdlib/number/int64/ctor/README.md +++ b/lib/node_modules/@stdlib/number/int64/ctor/README.md @@ -189,7 +189,7 @@ var v = x.valueOf(); ## Notes -- A 64-bit signed integer has a range of \[`-(2^63)`, `2^63-1`\]. +- A 64-bit signed integer has a range of \[`-(2^63)`, `2^63-1`]. @@ -235,7 +235,6 @@ console.log( 'JSON: %s', JSON.stringify( x ) ); -
diff --git a/lib/node_modules/@stdlib/number/int8/base/identity/lib/main.js b/lib/node_modules/@stdlib/number/int8/base/identity/lib/main.js index bd32a650f639..5fa42798b7c9 100644 --- a/lib/node_modules/@stdlib/number/int8/base/identity/lib/main.js +++ b/lib/node_modules/@stdlib/number/int8/base/identity/lib/main.js @@ -18,6 +18,8 @@ 'use strict'; +// MAIN // + /** * Evaluates the identity function for a signed 8-bit integer `x`. * diff --git a/lib/node_modules/@stdlib/number/uint16/base/identity/lib/main.js b/lib/node_modules/@stdlib/number/uint16/base/identity/lib/main.js index 7b30045149b2..69a38a6f1f7d 100644 --- a/lib/node_modules/@stdlib/number/uint16/base/identity/lib/main.js +++ b/lib/node_modules/@stdlib/number/uint16/base/identity/lib/main.js @@ -18,6 +18,8 @@ 'use strict'; +// MAIN // + /** * Evaluates the identity function for an unsigned 16-bit integer `x`. * diff --git a/lib/node_modules/@stdlib/number/uint64/base/assert/is-equal/lib/main.js b/lib/node_modules/@stdlib/number/uint64/base/assert/is-equal/lib/main.js index 3ce61146bae9..b90944b5cc53 100644 --- a/lib/node_modules/@stdlib/number/uint64/base/assert/is-equal/lib/main.js +++ b/lib/node_modules/@stdlib/number/uint64/base/assert/is-equal/lib/main.js @@ -25,8 +25,7 @@ var toWords = require( '@stdlib/number/uint64/base/to-words' ).assign; // VARIABLES // -var WORKSPACE1 = [ 0, 0 ]; -var WORKSPACE2 = [ 0, 0 ]; +var WORKSPACE = [ 0, 0, 0, 0 ]; // MAIN // @@ -48,11 +47,11 @@ var WORKSPACE2 = [ 0, 0 ]; * // returns true */ function isEqual( a, b ) { - toWords( a, WORKSPACE1, 1, 0 ); - toWords( b, WORKSPACE2, 1, 0 ); + toWords( a, WORKSPACE, 1, 0 ); + toWords( b, WORKSPACE, 1, 2 ); return ( - WORKSPACE1[ 0 ] === WORKSPACE2[ 0 ] && - WORKSPACE1[ 1 ] === WORKSPACE2[ 1 ] + WORKSPACE[ 0 ] === WORKSPACE[ 2 ] && // high words + WORKSPACE[ 1 ] === WORKSPACE[ 3 ] // low words ); } diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/README.md b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/README.md new file mode 100644 index 000000000000..3d1b098d7c02 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/README.md @@ -0,0 +1,135 @@ + + +# bigint2words + +> Split a bigint into the high and low 32-bit words of a 64-bit unsigned integer. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var bigint2words = require( '@stdlib/number/uint64/base/bigint2words' ); +``` + +#### bigint2words( value ) + +Splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer. + +```javascript +var BigInt = require( '@stdlib/bigint/ctor' ); + +var w = bigint2words( BigInt( 1234 ) ); +// returns [ 0, 1234 ] +``` + +The function returns an array containing two elements: a higher order word and a lower order word. The lower order word contains the less significant bits, while the higher order word contains the more significant bits. + +#### bigint2words.assign( value, out, stride, offset ) + +Splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer and assigns results to a provided output array. + +```javascript +var Uint32Array = require( '@stdlib/array/uint32' ); +var BigInt = require( '@stdlib/bigint/ctor' ); + +var out = new Uint32Array( 2 ); +// returns [ 0, 0 ] + +var w = bigint2words.assign( BigInt( '18446744073709551615' ), out, 1, 0 ); +// returns [ 4294967295, 4294967295 ] + +var bool = ( w === out ); +// returns true +``` + +
+ + + + + +
+ +## Notes + +- For accurate results, the input value should be an integer in the range \[`0`, `2^64-1`\]. + +
+ + + + + +
+ +## Examples + +```javascript +var BigInt = require( '@stdlib/bigint/ctor' ); +var bigint2words = require( '@stdlib/number/uint64/base/bigint2words' ); + +var w = bigint2words( BigInt( 1234 ) ); +console.log( w ); +// => [ 0, 1234 ] + +w = bigint2words( BigInt( 0x100000000 ) ); +console.log( w ); +// => [ 1, 0 ] + +w = bigint2words( BigInt( '18446744073709551615' ) ); +console.log( w ); +// => [ 4294967295, 4294967295 ] +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/benchmark/benchmark.js new file mode 100644 index 000000000000..5209ed46d988 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/benchmark/benchmark.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Uint32Array = require( '@stdlib/array/uint32' ); +var isArray = require( '@stdlib/assert/is-array' ); +var hasBigIntSupport = require( '@stdlib/assert/has-bigint-support' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var BigInt = require( '@stdlib/bigint/ctor' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var bigint2words = require( './../lib' ); + + +// VARIABLES // + +var TWO_32 = 0x100000000; // 2^32 +var opts = { + 'skip': !hasBigIntSupport() +}; +var options = { + 'dtype': 'uint32' +}; + + +// MAIN // + +bench( pkg, opts, function benchmark( b ) { + var values; + var N; + var a; + var i; + var w; + var x; + + N = 100; + x = discreteUniform( N, 0, UINT32_MAX, options ); + values = []; + for ( i = 0; i < N; i++ ) { + a = ( BigInt( x[ i ] ) * BigInt( TWO_32 ) ) + BigInt( x[ (i+1)%N ] ); + values.push( a ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + w = bigint2words( values[ i % N ] ); + if ( typeof w !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( w ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:assign', pkg ), opts, function benchmark( b ) { + var values; + var out; + var N; + var a; + var i; + var w; + var x; + + N = 100; + x = discreteUniform( N, 0, UINT32_MAX, options ); + values = []; + for ( i = 0; i < N; i++ ) { + a = ( BigInt( x[ i ] ) * BigInt( TWO_32 ) ) + BigInt( x[ (i+1)%N ] ); + values.push( a ); + } + + out = new Uint32Array( 2 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + w = bigint2words.assign( values[ i % N ], out, 1, 0 ); + if ( typeof w !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( w !== out ) { + b.fail( 'should return the output array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/repl.txt b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/repl.txt new file mode 100644 index 000000000000..587ebe4b3b6c --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/repl.txt @@ -0,0 +1,59 @@ + +{{alias}}( value ) + Splits a bigint into the high and low 32-bit words of a 64-bit unsigned + integer. + + The function returns an array with two elements: a higher order word and a + lower order word, respectively. The lower order word contains the less + significant bits, while the higher order word contains the more significant + bits. + + Parameters + ---------- + value: bigint + Integer value in the range [0, 2^64-1]. + + Returns + ------- + out: Array + High and low words as 32-bit unsigned integers. + + Examples + -------- + > var w = {{alias}}( {{alias:@stdlib/bigint/ctor}}( 1234 ) ) + [ 0, 1234 ] + + +{{alias}}.assign( value, out, stride, offset ) + Splits a bigint into the high and low 32-bit words of a 64-bit unsigned + integer and assigns results to a provided output array. + + Parameters + ---------- + value: bigint + Integer value in the range [0, 2^64-1]. + + out: Array|TypedArray|Object + Output array. + + stride: integer + Output array stride. + + offset: integer + Output array index offset. + + Returns + ------- + out: Array|TypedArray|Object + Output array. + + Examples + -------- + > var out = new {{alias:@stdlib/array/uint32}}( 2 ); + > var w = {{alias}}.assign( {{alias:@stdlib/bigint/ctor}}( '18446744073709551615' ), out, 1, 0 ) + [ 4294967295, 4294967295 ] + > var bool = ( w === out ) + true + + See Also + -------- diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/types/index.d.ts new file mode 100644 index 000000000000..87832e9addd2 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/types/index.d.ts @@ -0,0 +1,110 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, NumericArray } from '@stdlib/types/array'; + +/** +* Interface describing `bigint2words`. +*/ +interface BigIntToWords { + /** + * Splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer. + * + * @param value - integer value in the range [0, 2^64-1] + * @returns high and low words as 32-bit unsigned integers + * + * @example + * var BigInt = require( '@stdlib/bigint/ctor' ); + * + * var out = bigint2words( BigInt( 1234 ) ); + * // returns [ 0, 1234 ] + * + * out = bigint2words( BigInt( 0x100000000 ) ); + * // returns [ 1, 0 ] + * + * out = bigint2words( BigInt( '18446744073709551615' ) ); + * // returns [ 4294967295, 4294967295 ] + */ + ( value: bigint ): [ number, number ]; + + /** + * Splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer and assigns results to a provided output array. + * + * @param value - integer value in the range [0, 2^64-1] + * @param out - output array + * @param stride - stride length + * @param offset - starting index + * @returns output array + * + * @example + * var Uint32Array = require( '@stdlib/array/uint32' ); + * var BigInt = require( '@stdlib/bigint/ctor' ); + * + * var out = new Uint32Array( 2 ); + * // returns [ 0, 0 ] + * + * var w = bigint2words.assign( BigInt( '18446744073709551615' ), out, 1, 0 ); + * // returns [ 4294967295, 4294967295 ] + * + * var bool = ( w === out ); + * // returns true + */ + assign>( value: bigint, out: T, stride: number, offset: number ): T; +} + +/** +* Splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer. +* +* @param value - integer value in the range [0, 2^64-1] +* @returns high and low words as 32-bit unsigned integers +* +* @example +* var BigInt = require( '@stdlib/bigint/ctor' ); +* +* var out = bigint2words( BigInt( 1234 ) ); +* // returns [ 0, 1234 ] +* +* out = bigint2words( BigInt( 0x100000000 ) ); +* // returns [ 1, 0 ] +* +* out = bigint2words( BigInt( '18446744073709551615' ) ); +* // returns [ 4294967295, 4294967295 ] +* +* @example +* var Uint32Array = require( '@stdlib/array/uint32' ); +* var BigInt = require( '@stdlib/bigint/ctor' ); +* +* var out = new Uint32Array( 2 ); +* // returns [ 0, 0 ] +* +* var w = bigint2words.assign( BigInt( '18446744073709551615' ), out, 1, 0 ); +* // returns [ 4294967295, 4294967295 ] +* +* var bool = ( w === out ); +* // returns true +*/ +declare var bigint2words: BigIntToWords; + + +// EXPORTS // + +export = bigint2words; diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/types/test.ts b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/types/test.ts new file mode 100644 index 000000000000..e528cbfdb34d --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/docs/types/test.ts @@ -0,0 +1,111 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import bigint2words = require( './index' ); + + +// TESTS // + +// The function returns an array... +{ + bigint2words( 1234n ); // $ExpectType [number, number] +} + +// The compiler throws an error if the function is provided an argument that is not a bigint... +{ + bigint2words( 5 ); // $ExpectError + bigint2words( '5' ); // $ExpectError + bigint2words( true ); // $ExpectError + bigint2words( false ); // $ExpectError + bigint2words( null ); // $ExpectError + bigint2words( {} ); // $ExpectError + bigint2words( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + bigint2words(); // $ExpectError + bigint2words( 1n, 2n ); // $ExpectError +} + +// Attached to the main export is an `assign` method which returns an array-like object containing numbers... +{ + bigint2words.assign( 1234n, [ 0, 0 ], 1, 0 ); // $ExpectType number[] + bigint2words.assign( 1234n, new Uint32Array( 2 ), 1, 0 ); // $ExpectType Uint32Array + bigint2words.assign( 1234n, new Float64Array( 2 ), 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `assign` method is provided a first argument which is not a bigint... +{ + const out = [ 0.0, 0.0 ]; + + bigint2words.assign( 5, out, 1, 0 ); // $ExpectError + bigint2words.assign( '5', out, 1, 0 ); // $ExpectError + bigint2words.assign( true, out, 1, 0 ); // $ExpectError + bigint2words.assign( false, out, 1, 0 ); // $ExpectError + bigint2words.assign( null, out, 1, 0 ); // $ExpectError + bigint2words.assign( [], out, 1, 0 ); // $ExpectError + bigint2words.assign( {}, out, 1, 0 ); // $ExpectError + bigint2words.assign( ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a second argument which is not an array-like object... +{ + bigint2words.assign( 1234n, 1, 1, 0 ); // $ExpectError + bigint2words.assign( 1234n, true, 1, 0 ); // $ExpectError + bigint2words.assign( 1234n, false, 1, 0 ); // $ExpectError + bigint2words.assign( 1234n, null, 1, 0 ); // $ExpectError + bigint2words.assign( 1234n, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a third argument which is not a number... +{ + const out = [ 0.0, 0.0 ]; + + bigint2words.assign( 1234n, out, '5', 0 ); // $ExpectError + bigint2words.assign( 1234n, out, true, 0 ); // $ExpectError + bigint2words.assign( 1234n, out, false, 0 ); // $ExpectError + bigint2words.assign( 1234n, out, null, 0 ); // $ExpectError + bigint2words.assign( 1234n, out, [], 0 ); // $ExpectError + bigint2words.assign( 1234n, out, {}, 0 ); // $ExpectError + bigint2words.assign( 1234n, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a fourth argument which is not a number... +{ + const out = [ 0.0, 0.0 ]; + + bigint2words.assign( 1234n, out, 1, '5' ); // $ExpectError + bigint2words.assign( 1234n, out, 1, true ); // $ExpectError + bigint2words.assign( 1234n, out, 1, false ); // $ExpectError + bigint2words.assign( 1234n, out, 1, null ); // $ExpectError + bigint2words.assign( 1234n, out, 1, [] ); // $ExpectError + bigint2words.assign( 1234n, out, 1, {} ); // $ExpectError + bigint2words.assign( 1234n, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an unsupported number of arguments... +{ + const out = [ 0.0, 0.0 ]; + + bigint2words.assign(); // $ExpectError + bigint2words.assign( 1234n ); // $ExpectError + bigint2words.assign( 1234n, out ); // $ExpectError + bigint2words.assign( 1234n, out, 1 ); // $ExpectError + bigint2words.assign( 1234n, out, 1, 0, 1 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/examples/index.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/examples/index.js new file mode 100644 index 000000000000..b27a7beb8325 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var BigInt = require( '@stdlib/bigint/ctor' ); +var bigint2words = require( './../lib' ); + +var w = bigint2words( BigInt( 1234 ) ); +console.log( w ); +// => [ 0, 1234 ] + +w = bigint2words( BigInt( 0x100000000 ) ); +console.log( w ); +// => [ 1, 0 ] + +w = bigint2words( BigInt( '18446744073709551615' ) ); +console.log( w ); +// => [ 4294967295, 4294967295 ] diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/assign.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/assign.js new file mode 100644 index 000000000000..7e4fc3b9c4ac --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/assign.js @@ -0,0 +1,61 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var BigInt = require( '@stdlib/bigint/ctor' ); +var Number = require( '@stdlib/number/ctor' ); + + +// MAIN // + +/** +* Splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer and assigns results to a provided output array. +* +* @param {bigint} value - integer value in the range [0, 2^64-1] +* @param {Collection} out - output array +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - starting index +* @returns {Collection} output array +* +* @example +* var Uint32Array = require( '@stdlib/array/uint32' ); +* var BigInt = require( '@stdlib/bigint/ctor' ); +* +* var out = new Uint32Array( 2 ); +* // returns [ 0, 0 ] +* +* var w = assign( BigInt( '18446744073709551615' ), out, 1, 0 ); +* // returns [ 4294967295, 4294967295 ] +* +* var bool = ( w === out ); +* // returns true +*/ +function assign( value, out, stride, offset ) { + var v = BigInt.asUintN( 64, value ); + out[ offset ] = Number( v >> BigInt( 32 ) ) >>> 0; + out[ offset + stride ] = Number( v & BigInt( 0xffffffff ) ) >>> 0; + return out; +} + + +// EXPORTS // + +module.exports = assign; diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/index.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/index.js new file mode 100644 index 000000000000..82f8474cf05e --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Split a bigint into the high and low 32-bit words of a 64-bit unsigned integer. +* +* @module @stdlib/number/uint64/base/bigint2words +* +* @example +* var BigInt = require( '@stdlib/bigint/ctor' ); +* var bigint2words = require( '@stdlib/number/uint64/base/bigint2words' ); +* +* var out = bigint2words( BigInt( 1234 ) ); +* // returns [ 0, 1234 ] +* +* out = bigint2words( BigInt( 0x100000000 ) ); +* // returns [ 1, 0 ] +* +* out = bigint2words( BigInt( '18446744073709551615' ) ); +* // returns [ 4294967295, 4294967295 ] +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var assign = require( './assign.js' ); +var main = require( './main.js' ); + + +// MAIN // + +setReadOnly( main, 'assign', assign ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/main.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/main.js new file mode 100644 index 000000000000..824a60901d41 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/lib/main.js @@ -0,0 +1,53 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var assign = require( './assign.js' ); + + +// MAIN // + +/** +* Splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer. +* +* @param {bigint} value - integer value in the range [0, 2^64-1] +* @returns {Array} high and low words as 32-bit unsigned integers +* +* @example +* var BigInt = require( '@stdlib/bigint/ctor' ); +* +* var out = bigint2words( BigInt( 1234 ) ); +* // returns [ 0, 1234 ] +* +* out = bigint2words( BigInt( 0x100000000 ) ); +* // returns [ 1, 0 ] +* +* out = bigint2words( BigInt( '18446744073709551615' ) ); +* // returns [ 4294967295, 4294967295 ] +*/ +function bigint2words( value ) { + return assign( value, [ 0, 0 ], 1, 0 ); +} + + +// EXPORTS // + +module.exports = bigint2words; diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/package.json b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/package.json new file mode 100644 index 000000000000..5f368823d50b --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/number/uint64/base/bigint2words", + "version": "0.0.0", + "description": "Split a bigint into the high and low 32-bit words of a 64-bit unsigned integer.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "base", + "utilities", + "utility", + "utils", + "util", + "types", + "type", + "uint64", + "unsigned", + "64-bit", + "integer", + "int", + "bigint", + "words", + "split", + "high", + "low" + ] +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.assign.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.assign.js new file mode 100644 index 000000000000..e9d867c67761 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.assign.js @@ -0,0 +1,175 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Uint32Array = require( '@stdlib/array/uint32' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var hasBigIntSupport = require( '@stdlib/assert/has-bigint-support' ); +var BigInt = require( '@stdlib/bigint/ctor' ); +var MAX_SAFE_INTEGER = require( '@stdlib/constants/float64/max-safe-integer' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var bigint2words = require( './../lib/assign.js' ); + + +// VARIABLES // + +var TWO_32 = 0x100000000; // 2^32 +var opts = { + 'skip': !hasBigIntSupport() +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof bigint2words, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a two-element numeric array containing integers', opts, function test( t ) { + var out; + var w; + + out = [ 0, 0 ]; + w = bigint2words( BigInt( 1234 ), out, 1, 0 ); + + t.strictEqual( w, out, 'returns expected value' ); + t.strictEqual( isInteger( w[0] ), true, 'returns expected value' ); + t.strictEqual( isInteger( w[1] ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer', opts, function test( t ) { + var values; + var out; + var w; + var x; + var i; + + values = [ + 0, + 1, + 2, + 3, + 4, + 5, + 10, + 99, + 100, + 999, + 1000, + 999999, + 1000000, + 999999999, + 1000000000, + UINT32_MAX, + UINT32_MAX + 1, + 9007199254740881, // Largest prime under 2^53 + MAX_SAFE_INTEGER - 1, + MAX_SAFE_INTEGER, + '9007199254740992', // MAX_SAFE_INTEGER + 1 + '9999999999999999', + '10000000000000000', + '99999999999999999', + '100000000000000000', + '999999999999999999', + '1000000000000000000', + '9223372036854775783', // Largest prime under 2^63 + '9999999999999999999', + '10000000000000000000', + '18446744073709551557', // Largest prime under 2^64 + '18446744073709551615' // 2^64 - 1 + ]; + + for ( i = 0; i < values.length; i++ ) { + values[ i ] = BigInt( values[ i ] ); // Convert values to BigInt + out = [ 0, 0 ]; + w = bigint2words( values[ i ], out, 1, 0 ); + t.strictEqual( w, out, 'returns expected value' ); + + x = ( BigInt( w[0] ) * BigInt( TWO_32 ) ) + BigInt( w[1] ); // Create BigInt from words + t.strictEqual( x, values[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the function supports providing an output object (array)', opts, function test( t ) { + var out; + var w; + + out = [ 0, 0 ]; + w = bigint2words( BigInt( 4294967296 ), out, 1, 0 ); + + t.strictEqual( w, out, 'returns expected value' ); + t.strictEqual( w[ 0 ], 1, 'returns expected value' ); + t.strictEqual( w[ 1 ], 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports providing an output object (typed array)', opts, function test( t ) { + var out; + var w; + + out = new Uint32Array( 2 ); + w = bigint2words( BigInt( 4294967296 ), out, 1, 0 ); + + t.strictEqual( w, out, 'returns expected value' ); + t.strictEqual( w[ 0 ], 1, 'returns expected value' ); + t.strictEqual( w[ 1 ], 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', opts, function test( t ) { + var out; + var val; + + out = new Uint32Array( 4 ); + val = bigint2words( BigInt( 4294967298 ), out, 2, 0 ); + + t.strictEqual( val, out, 'returns expected value' ); + t.strictEqual( val[ 0 ], 1, 'returns expected value' ); + t.strictEqual( val[ 1 ], 0, 'returns expected value' ); + t.strictEqual( val[ 2 ], 2, 'returns expected value' ); + t.strictEqual( val[ 3 ], 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying an offset', opts, function test( t ) { + var out; + var val; + + out = new Uint32Array( 4 ); + val = bigint2words( BigInt( 4294967298 ), out, 2, 1 ); + + t.strictEqual( val, out, 'returns expected value' ); + t.strictEqual( val[ 0 ], 0, 'returns expected value' ); + t.strictEqual( val[ 1 ], 1, 'returns expected value' ); + t.strictEqual( val[ 2 ], 0, 'returns expected value' ); + t.strictEqual( val[ 3 ], 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.js new file mode 100644 index 000000000000..1547d5a420c0 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var bigint2words = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof bigint2words, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is an `assign` method', function test( t ) { + t.strictEqual( hasOwnProp( bigint2words, 'assign' ), true, 'has property' ); + t.strictEqual( typeof bigint2words.assign, 'function', 'has method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.main.js b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.main.js new file mode 100644 index 000000000000..9518a7fcb522 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/bigint2words/test/test.main.js @@ -0,0 +1,65 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var hasBigIntSupport = require( '@stdlib/assert/has-bigint-support' ); +var BigInt = require( '@stdlib/bigint/ctor' ); +var bigint2words = require( './../lib/main.js' ); + + +// VARIABLES // + +var opts = { + 'skip': hasBigIntSupport() +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof bigint2words, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a two-element numeric array containing integers', opts, function test( t ) { + var w; + + w = bigint2words( BigInt( 1234 ) ); + + t.strictEqual( isInteger( w[0] ), true, 'returns expected value' ); + t.strictEqual( isInteger( w[1] ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function splits a bigint into the high and low 32-bit words of a 64-bit unsigned integer', opts, function test( t ) { + var w; + + w = bigint2words( BigInt( '18446744073709551615' ) ); + + t.strictEqual( w[ 0 ], 4294967295, 'returns expected value' ); + t.strictEqual( w[ 1 ], 4294967295, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/README.md b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/README.md new file mode 100644 index 000000000000..ceba63d46f9c --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/README.md @@ -0,0 +1,100 @@ + + +# High Word + +> Return a 32-bit unsigned integer corresponding to the high 32-bit word of a [64-bit unsigned integer][@stdlib/number/uint64/ctor]. + +
+ +## Usage + +```javascript +var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +``` + +#### getHighWord( x ) + +Returns a 32-bit unsigned integer corresponding to the high 32-bit word of a [64-bit unsigned integer][@stdlib/number/uint64/ctor]. + +```javascript +var Uint64 = require( '@stdlib/number/uint64/ctor' ); + +var x = new Uint64( 4294967296 ); +var w = getHighWord( x ); +// returns 1 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); + +var x = new Uint64( 4294967296 ); +console.log( getHighWord( x ) ); +// => 1 + +x = new Uint64( 0xffffffff ); +console.log( getHighWord( x ) ); +// => 0 + +x = new Uint64( 0x123400005678 ); +console.log( getHighWord( x ) ); +// => 4660 + +x = Uint64.of( 1234, 5678 ); +console.log( getHighWord( x ) ); +// => 1234 +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/number/uint64/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/number/uint64/ctor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/benchmark/benchmark.js new file mode 100644 index 000000000000..d699c12fb35e --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/benchmark/benchmark.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/assert/is-nan' ).isPrimitive; +var bench = require( '@stdlib/bench' ); +var MAX_SAFE_INTEGER = require( '@stdlib/constants/float64/max-safe-integer' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var pkg = require( './../package.json' ).name; +var getHighWord = require( './../lib' ); + + +// VARIABLES // + +var rand = discreteUniform.factory( 0, MAX_SAFE_INTEGER ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var N; + var x; + var i; + var w; + + N = 100; + values = []; + for ( i = 0; i < N; i++ ) { + values.push( new Uint64( rand() ) ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x = values[ i % N ]; + w = getHighWord( x ); + if ( isnan( w ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( w ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/repl.txt b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/repl.txt new file mode 100644 index 000000000000..cfd856a30c5c --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/repl.txt @@ -0,0 +1,25 @@ + +{{alias}}( x ) + Returns a 32-bit unsigned integer corresponding to the high 32-bit word of a + 64-bit unsigned integer. + + Parameters + ---------- + x: Uint64 + Input value. + + Returns + ------- + out: integer + Higher order word (32-bit unsigned integer). + + Examples + -------- + > var x = new {{alias:@stdlib/number/uint64/ctor}}( 4294967296 ) + [ 4294967296n ] + > var w = {{alias}}( x ) + 1 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/types/index.d.ts new file mode 100644 index 000000000000..31751d77b748 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/types/index.d.ts @@ -0,0 +1,43 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Uint64 } from '@stdlib/types/number'; + +/** +* Returns a 32-bit unsigned integer corresponding to the high 32-bit word of a 64-bit unsigned integer. +* +* @param x - input value +* @returns higher order word (32-bit unsigned integer) +* +* @example +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* +* var x = new Uint64( 4294967296 ); +* var w = getHighWord( x ); +* // returns 1 +*/ +declare function getHighWord( x: Uint64 ): number; + + +// EXPORTS // + +export = getHighWord; diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/types/test.ts b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/types/test.ts new file mode 100644 index 000000000000..6176705aa05d --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/docs/types/test.ts @@ -0,0 +1,47 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Uint64 = require( '@stdlib/number/uint64/ctor' ); +import getHighWord = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Uint64( 5 ); + getHighWord( x ); // $ExpectType number +} + +// The compiler throws an error if the function is provided an argument that is not a 64-bit unsigned integer... +{ + getHighWord( 5 ); // $ExpectError + getHighWord( '5' ); // $ExpectError + getHighWord( true ); // $ExpectError + getHighWord( false ); // $ExpectError + getHighWord( [] ); // $ExpectError + getHighWord( {} ); // $ExpectError + getHighWord( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Uint64( 5 ); + getHighWord(); // $ExpectError + getHighWord( x, x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/examples/index.js b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/examples/index.js new file mode 100644 index 000000000000..109f27275286 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var getHighWord = require( './../lib' ); + +var x = new Uint64( 4294967296 ); +console.log( getHighWord( x ) ); +// => 1 + +x = new Uint64( 0xffffffff ); +console.log( getHighWord( x ) ); +// => 0 + +x = new Uint64( 0x123400005678 ); +console.log( getHighWord( x ) ); +// => 4660 + +x = Uint64.of( 1234, 5678 ); +console.log( getHighWord( x ) ); +// => 1234 diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/lib/index.js b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/lib/index.js new file mode 100644 index 000000000000..1fd39545cf54 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/lib/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a 32-bit unsigned integer corresponding to the high 32-bit word of a 64-bit unsigned integer. +* +* @module @stdlib/number/uint64/base/get-high-word +* +* @example +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +* +* var x = new Uint64( 4294967296 ); +* var w = getHighWord( x ); +* // returns 1 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/lib/main.js b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/lib/main.js new file mode 100644 index 000000000000..74529725a73c --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/lib/main.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns a 32-bit unsigned integer corresponding to the high 32-bit word of a 64-bit unsigned integer. +* +* @param {Uint64} x - input value +* @returns {uinteger32} higher order word +* +* @example +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* +* var x = new Uint64( 4294967296 ); +* var w = getHighWord( x ); +* // returns 1 +*/ +function getHighWord( x ) { + return x.hi; +} + + +// EXPORTS // + +module.exports = getHighWord; diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/package.json b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/package.json new file mode 100644 index 000000000000..2f1013aab93b --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/number/uint64/base/get-high-word", + "version": "0.0.0", + "description": "Return a 32-bit unsigned integer corresponding to the high 32-bit word of a 64-bit unsigned integer.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "base", + "utilities", + "utility", + "utils", + "util", + "types", + "type", + "uint64", + "unsigned", + "64-bit", + "integer", + "int", + "high", + "word" + ] +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-high-word/test/test.js b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/test/test.js new file mode 100644 index 000000000000..0151ebb5f926 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-high-word/test/test.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var getHighWord = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof getHighWord, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an integer', function test( t ) { + var x; + var w; + + x = new Uint64( 4294967296 ); + w = getHighWord( x ); + + t.ok( isInteger( w ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the high 32-bit word of a 64-bit unsigned integer', function test( t ) { + var values; + var x; + var v; + var w; + var i; + + values = [ + 0, + 1, + 2, + 3, + 4, + 5, + 10, + 99, + 100, + 999, + 1000, + 999999, + 1000000, + 999999999, + 1000000000, + UINT32_MAX + ]; + + for ( i = 0; i < values.length; i++ ) { + v = values[ i ]; + x = Uint64.of( v, 0 ); + w = getHighWord( x ); + t.strictEqual( w, v, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/README.md b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/README.md new file mode 100644 index 000000000000..0bfadb045bed --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/README.md @@ -0,0 +1,100 @@ + + +# Low Word + +> Return a 32-bit unsigned integer corresponding to the low 32-bit word of a [64-bit unsigned integer][@stdlib/number/uint64/ctor]. + +
+ +## Usage + +```javascript +var getLowWord = require( '@stdlib/number/uint64/base/get-low-word' ); +``` + +#### getLowWord( a ) + +Returns a 32-bit unsigned integer corresponding to the low 32-bit word of a [64-bit unsigned integer][@stdlib/number/uint64/ctor]. + +```javascript +var Uint64 = require( '@stdlib/number/uint64/ctor' ); + +var a = new Uint64( 4294967296 ); +var w = getLowWord( a ); +// returns 0 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var getLowWord = require( '@stdlib/number/uint64/base/get-low-word' ); + +var a = new Uint64( 4294967296 ); +console.log( getLowWord( a ) ); +// => 0 + +a = new Uint64( 0xffffffff ); +console.log( getLowWord( a ) ); +// => 4294967295 + +a = new Uint64( 0x123400005678 ); +console.log( getLowWord( a ) ); +// => 22136 + +a = Uint64.of( 1234, 5678 ); +console.log( getLowWord( a ) ); +// => 5678 +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/number/uint64/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/number/uint64/ctor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/benchmark/benchmark.js new file mode 100644 index 000000000000..7266ac325caa --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/benchmark/benchmark.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/assert/is-nan' ).isPrimitive; +var bench = require( '@stdlib/bench' ); +var MAX_SAFE_INTEGER = require( '@stdlib/constants/float64/max-safe-integer' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var pkg = require( './../package.json' ).name; +var getLowWord = require( './../lib' ); + + +// VARIABLES // + +var rand = discreteUniform.factory( 0, MAX_SAFE_INTEGER ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var N; + var a; + var i; + var w; + + N = 100; + values = []; + for ( i = 0; i < N; i++ ) { + values.push( new Uint64( rand() ) ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + a = values[ i % N ]; + w = getLowWord( a ); + if ( isnan( w ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( w ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/repl.txt b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/repl.txt new file mode 100644 index 000000000000..1fcf34f31c2d --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/repl.txt @@ -0,0 +1,25 @@ + +{{alias}}( a ) + Returns a 32-bit unsigned integer corresponding to the low 32-bit word of a + 64-bit unsigned integer. + + Parameters + ---------- + a: Uint64 + Input value. + + Returns + ------- + out: integer + Lower order word (32-bit unsigned integer). + + Examples + -------- + > var a = new {{alias:@stdlib/number/uint64/ctor}}( 4294967296 ) + [ 4294967296n ] + > var w = {{alias}}( a ) + 0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/types/index.d.ts new file mode 100644 index 000000000000..cf2dcd5b8339 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/types/index.d.ts @@ -0,0 +1,43 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Uint64 } from '@stdlib/types/number'; + +/** +* Returns a 32-bit unsigned integer corresponding to the low 32-bit word of a 64-bit unsigned integer. +* +* @param a - input value +* @returns lower order word (32-bit unsigned integer) +* +* @example +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* +* var a = new Uint64( 4294967296 ); +* var w = getLowWord( a ); +* // returns 0 +*/ +declare function getLowWord( a: Uint64 ): number; + + +// EXPORTS // + +export = getLowWord; diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/types/test.ts b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/types/test.ts new file mode 100644 index 000000000000..ef56f70c0e39 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/docs/types/test.ts @@ -0,0 +1,47 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Uint64 = require( '@stdlib/number/uint64/ctor' ); +import getLowWord = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const a = new Uint64( 5 ); + getLowWord( a ); // $ExpectType number +} + +// The compiler throws an error if the function is provided an argument that is not a 64-bit unsigned integer... +{ + getLowWord( 5 ); // $ExpectError + getLowWord( '5' ); // $ExpectError + getLowWord( true ); // $ExpectError + getLowWord( false ); // $ExpectError + getLowWord( [] ); // $ExpectError + getLowWord( {} ); // $ExpectError + getLowWord( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const a = new Uint64( 5 ); + getLowWord(); // $ExpectError + getLowWord( a, a ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/examples/index.js b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/examples/index.js new file mode 100644 index 000000000000..7192c2c6669d --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var getLowWord = require( './../lib' ); + +var a = new Uint64( 4294967296 ); +console.log( getLowWord( a ) ); +// => 0 + +a = new Uint64( 0xffffffff ); +console.log( getLowWord( a ) ); +// => 4294967295 + +a = new Uint64( 0x123400005678 ); +console.log( getLowWord( a ) ); +// => 22136 + +a = Uint64.of( 1234, 5678 ); +console.log( getLowWord( a ) ); +// => 5678 diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/lib/index.js b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/lib/index.js new file mode 100644 index 000000000000..8f6b55e45f03 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/lib/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Return a 32-bit unsigned integer corresponding to the low 32-bit word of a 64-bit unsigned integer. +* +* @module @stdlib/number/uint64/base/get-low-word +* +* @example +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* var getLowWord = require( '@stdlib/number/uint64/base/get-low-word' ); +* +* var a = new Uint64( 4294967296 ); +* var w = getLowWord( a ); +* // returns 0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/lib/main.js b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/lib/main.js new file mode 100644 index 000000000000..2a78a1e290ce --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/lib/main.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MAIN // + +/** +* Returns a 32-bit unsigned integer corresponding to the low 32-bit word of a 64-bit unsigned integer. +* +* @param {Uint64} a - input value +* @returns {uinteger32} lower order word +* +* @example +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* +* var a = new Uint64( 4294967296 ); +* var w = getLowWord( a ); +* // returns 0 +*/ +function getLowWord( a ) { + return a.lo; +} + + +// EXPORTS // + +module.exports = getLowWord; diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/package.json b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/package.json new file mode 100644 index 000000000000..9787e45393af --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/number/uint64/base/get-low-word", + "version": "0.0.0", + "description": "Return a 32-bit unsigned integer corresponding to the low 32-bit word of a 64-bit unsigned integer.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "base", + "utilities", + "utility", + "utils", + "util", + "types", + "type", + "uint64", + "unsigned", + "64-bit", + "integer", + "int", + "get", + "low", + "word" + ] +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/get-low-word/test/test.js b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/test/test.js new file mode 100644 index 000000000000..a5eeeaddfa5f --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/get-low-word/test/test.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var getLowWord = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof getLowWord, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an integer', function test( t ) { + var a; + var w; + + a = new Uint64( 4294967296 ); + w = getLowWord( a ); + + t.ok( isInteger( w ), 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the low 32-bit word of a 64-bit unsigned integer', function test( t ) { + var values; + var a; + var v; + var w; + var i; + + values = [ + 0, + 1, + 2, + 3, + 4, + 5, + 10, + 99, + 100, + 999, + 1000, + 999999, + 1000000, + 999999999, + 1000000000, + UINT32_MAX + ]; + + for ( i = 0; i < values.length; i++ ) { + v = values[ i ]; + a = Uint64.of( 0, v ); + w = getLowWord( a ); + t.strictEqual( w, v, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/README.md b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/README.md new file mode 100644 index 000000000000..48328631e9f6 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/README.md @@ -0,0 +1,112 @@ + + +# setHighWord + +> Set the high 32-bit word of a [64-bit unsigned integer][@stdlib/number/uint64/ctor]. + +
+ +## Usage + +```javascript +var setHighWord = require( '@stdlib/number/uint64/base/set-high-word' ); +``` + +#### setHighWord( x, high ) + +Sets the high 32-bit word of a [64-bit unsigned integer][@stdlib/number/uint64/ctor]. + +```javascript +var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); + +var a = new Uint64( 4294967296 ); +// returns [ 4294967296n ] + +var b = setHighWord( a, 2 ); +// returns [ 8589934592n ] + +var w = getHighWord( b ); +// returns 2 +``` + +
+ + + +
+ +## Notes + +- The function returns a new [64-bit unsigned integer][@stdlib/number/uint64/ctor] instance without modifying the input. + +
+ + + +
+ +## Examples + + + +```javascript +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var setHighWord = require( '@stdlib/number/uint64/base/set-high-word' ); + +var a = new Uint64( 4294967296 ); +// returns + +var words = discreteUniform( 100, 0, UINT32_MAX, { + 'dtype': 'uint32' +}); + +logEachMap( 'setHighWord(%s, %s) = %s', a, words, setHighWord ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[@stdlib/number/uint64/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/number/uint64/ctor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/benchmark/benchmark.js new file mode 100644 index 000000000000..e0d69a00cc08 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/benchmark/benchmark.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var pkg = require( './../package.json' ).name; +var setHighWord = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var values; + var N; + var a; + var i; + var z; + + N = 100; + values = discreteUniform( N, 0, UINT32_MAX, { + 'dtype': 'uint32' + }); + + a = new Uint64( 0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + z = setHighWord( a, values[ i % N ] ); + if ( typeof z !== 'object' ) { + b.fail( 'should return a Uint64 instance' ); + } + } + b.toc(); + if ( !( z instanceof Uint64 ) ) { + b.fail( 'should return a Uint64 instance' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/repl.txt b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/repl.txt new file mode 100644 index 000000000000..bb163a599b20 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/repl.txt @@ -0,0 +1,31 @@ + +{{alias}}( a, high ) + Sets the high 32-bit word of a 64-bit unsigned integer. + + The function returns a new Uint64 instance without modifying the input. + + Parameters + ---------- + a: Uint64 + 64-bit unsigned integer. + + high: integer + 32-bit unsigned integer to replace the high 32-bit word. + + Returns + ------- + out: Uint64 + 64-bit unsigned integer. + + Examples + -------- + > var a = new {{alias:@stdlib/number/uint64/ctor}}( 4294967296 ) + [ 4294967296n ] + > var b = {{alias}}( a, 2 ) + [ 8589934592n ] + > var w = {{alias:@stdlib/number/uint64/base/get-high-word}}( b ) + 2 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/types/index.d.ts new file mode 100644 index 000000000000..f29d35233d84 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/types/index.d.ts @@ -0,0 +1,50 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Uint64 } from '@stdlib/types/number'; + +/** +* Sets the high 32-bit word of a 64-bit unsigned integer. +* +* @param a - 64-bit unsigned integer +* @param high - 32-bit unsigned integer to replace the high 32-bit word +* @returns 64-bit unsigned integer +* +* @example +* var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* +* var a = new Uint64( 4294967296 ); +* // returns [ 4294967296n ] +* +* var b = setHighWord( a, 2 ); +* // returns [ 8589934592n ] +* +* var w = getHighWord( b ); +* // returns 2 +*/ +declare function setHighWord( a: Uint64, high: number ): Uint64; + + +// EXPORTS // + +export = setHighWord; diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/types/test.ts b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/types/test.ts new file mode 100644 index 000000000000..43f0c4e1e172 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/docs/types/test.ts @@ -0,0 +1,58 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import Uint64 = require( '@stdlib/number/uint64/ctor' ); +import setHighWord = require( './index' ); + + +// TESTS // + +// The function returns a Uint64 instance... +{ + const a = new Uint64( 5 ); + setHighWord( a, 2 ); // $ExpectType Uint64 +} + +// The compiler throws an error if the function is provided a first argument that is not a Uint64 instance... +{ + setHighWord( 'abc', 2 ); // $ExpectError + setHighWord( true, 2 ); // $ExpectError + setHighWord( false, 2 ); // $ExpectError + setHighWord( [], 2 ); // $ExpectError + setHighWord( {}, 2 ); // $ExpectError + setHighWord( ( x: number ): number => x, 2 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument that is not a number... +{ + const a = new Uint64( 5 ); + setHighWord( a, 'abc' ); // $ExpectError + setHighWord( a, true ); // $ExpectError + setHighWord( a, false ); // $ExpectError + setHighWord( a, [] ); // $ExpectError + setHighWord( a, {} ); // $ExpectError + setHighWord( a, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const a = new Uint64( 5 ); + setHighWord(); // $ExpectError + setHighWord( a ); // $ExpectError + setHighWord( a, 2, 0 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/examples/index.js b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/examples/index.js new file mode 100644 index 000000000000..253c9911cbbf --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/examples/index.js @@ -0,0 +1,34 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var setHighWord = require( './../lib' ); + +var a = new Uint64( 4294967296 ); +// returns + +var words = discreteUniform( 100, 0, UINT32_MAX, { + 'dtype': 'uint32' +}); + +logEachMap( 'setHighWord(%s, %s) = %s', a, words, setHighWord ); diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/lib/index.js b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/lib/index.js new file mode 100644 index 000000000000..c66264bff6c4 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/lib/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Set the high 32-bit word of a 64-bit unsigned integer. +* +* @module @stdlib/number/uint64/base/set-high-word +* +* @example +* var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* var setHighWord = require( '@stdlib/number/uint64/base/set-high-word' ); +* +* var a = new Uint64( 4294967296 ); +* // returns [ 4294967296n ] +* +* var b = setHighWord( a, 2 ); +* // returns [ 8589934592n ] +* +* var w = getHighWord( b ); +* // returns 2 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/lib/main.js b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/lib/main.js new file mode 100644 index 000000000000..359101dfd87c --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/lib/main.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var getLowWord = require( '@stdlib/number/uint64/base/get-low-word' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); + + +// MAIN // + +/** +* Sets the high 32-bit word of a 64-bit unsigned integer. +* +* @param {Uint64} a - 64-bit unsigned integer +* @param {uinteger32} high - 32-bit unsigned integer to replace the high 32-bit word +* @returns {Uint64} 64-bit unsigned integer +* +* @example +* var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +* var Uint64 = require( '@stdlib/number/uint64/ctor' ); +* +* var a = new Uint64( 4294967296 ); +* // returns [ 4294967296n ] +* +* var b = setHighWord( a, 2 ); +* // returns [ 8589934592n ] +* +* var w = getHighWord( b ); +* // returns 2 +*/ +function setHighWord( a, high ) { + return Uint64.of( high, getLowWord( a ) ); +} + + +// EXPORTS // + +module.exports = setHighWord; diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/package.json b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/package.json new file mode 100644 index 000000000000..5ccde4318d69 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/number/uint64/base/set-high-word", + "version": "0.0.0", + "description": "Set the high 32-bit word of a 64-bit unsigned integer.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "base", + "utilities", + "utility", + "utils", + "util", + "types", + "type", + "uint64", + "unsigned", + "64-bit", + "integer", + "int", + "set", + "high", + "word" + ] +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/set-high-word/test/test.js b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/test/test.js new file mode 100644 index 000000000000..3dee8391b415 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/set-high-word/test/test.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isUint64 = require( '@stdlib/assert/is-uint64' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +var getLowWord = require( '@stdlib/number/uint64/base/get-low-word' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var setHighWord = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof setHighWord, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a Uint64 instance', function test( t ) { + var a = new Uint64( 0 ); + var b = setHighWord( a, 2 ); + t.ok( isUint64( b ), 'returns expected value' ); + t.end(); +}); + +tape( 'the function sets the high 32-bit word of a 64-bit unsigned integer', function test( t ) { + var values; + var a; + var b; + var v; + var w; + var i; + + values = [ + 0, + 1, + 2, + 3, + 4, + 5, + 10, + 99, + 100, + 999, + 1000, + 999999, + 1000000, + 999999999, + 1000000000, + UINT32_MAX + ]; + + for ( i = 0; i < values.length; i++ ) { + v = values[ i ]; + a = new Uint64( 0 ); + w = getLowWord( a ); + b = setHighWord( a, v ); + t.strictEqual( getHighWord( b ), v, 'returns expected value' ); + t.strictEqual( getLowWord( b ), w, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/README.md b/lib/node_modules/@stdlib/number/uint64/base/string2words/README.md new file mode 100644 index 000000000000..119554771f2e --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/README.md @@ -0,0 +1,136 @@ + + +# string2words + +> Parse a string representation of a 64-bit unsigned integer into high and low 32-bit words. + + + +
+ +
+ + + + + +
+ +## Usage + +```javascript +var string2words = require( '@stdlib/number/uint64/base/string2words' ); +``` + +#### string2words( str, radix ) + +Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words. + +```javascript +var w = string2words( '1234', 10 ); +// returns [ 0, 1234 ] +``` + +The function returns an array containing two elements: a higher order word and a lower order word. The lower order word contains the less significant bits, while the higher order word contains the more significant bits. + +#### string2words.assign( str, radix, out, stride, offset ) + +Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words and assigns results to a provided output array. + +```javascript +var Uint32Array = require( '@stdlib/array/uint32' ); + +var out = new Uint32Array( 2 ); +// returns [ 0, 0 ] + +var w = string2words.assign( 'ffffffffffffffff', 16, out, 1, 0 ); +// returns [ 4294967295, 4294967295 ] + +var bool = ( w === out ); +// returns true +``` + +
+ + + + + +
+ +## Notes + +- The input string must be a valid representation of an unsigned 64-bit integer in the specified radix, containing no whitespace, sign symbols, or leading zeros. +- If the provided string represents a value greater than `2^64-1` or the radix is not an integer on the interval `[2, 36]`, the function throws a `RangeError`. + +
+ + + + + +
+ +## Examples + +```javascript +var string2words = require( '@stdlib/number/uint64/base/string2words' ); + +var w = string2words( '1234', 10 ); +console.log( w ); +// => [ 0, 1234 ] + +w = string2words( 'abcd', 16 ); +console.log( w ); +// => [ 0, 43981 ] + +w = string2words( '18446744073709551615', 10 ); +console.log( w ); +// => [ 4294967295, 4294967295 ] + +w = string2words( '3w5e11264sgsf', 36 ); +console.log( w ); +// => [ 4294967295, 4294967295 ] +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/benchmark/benchmark.js new file mode 100644 index 000000000000..97c82db9e5c7 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/benchmark/benchmark.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Uint32Array = require( '@stdlib/array/uint32' ); +var isArray = require( '@stdlib/assert/is-array' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var Uint64 = require( '@stdlib/number/uint64/ctor' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var string2words = require( './../lib' ); + + +// VARIABLES // + +var options = { + 'dtype': 'uint32' +}; + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var radices; + var values; + var rad; + var N; + var a; + var i; + var w; + var x; + + N = 100; + x = discreteUniform( N, 0, UINT32_MAX, options ); + values = []; + radices = []; + for ( i = 0; i < N; i++ ) { + a = Uint64.of( x[ i ], x[ (i+1)%N ] ); + for ( rad = 2; rad <= 36; rad++ ) { + values.push( a.toString( rad ) ); + radices.push( rad ); + } + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + w = string2words( values[ i % N ], radices[ i % N ] ); + if ( typeof w !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( !isArray( w ) ) { + b.fail( 'should return an array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:assign', pkg ), function benchmark( b ) { + var radices; + var values; + var out; + var rad; + var N; + var a; + var i; + var w; + var x; + + N = 100; + x = discreteUniform( N, 0, UINT32_MAX, options ); + values = []; + radices = []; + for ( i = 0; i < N; i++ ) { + a = Uint64.of( x[ i ], x[ (i+1)%N ] ); + for ( rad = 2; rad <= 36; rad++ ) { + values.push( a.toString( rad ) ); + radices.push( rad ); + } + } + + out = new Uint32Array( 2 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + w = string2words.assign( values[ i % N ], radices[ i % N ], out, 1, 0 ); + if ( typeof w !== 'object' ) { + b.fail( 'should return an array' ); + } + } + b.toc(); + if ( w !== out ) { + b.fail( 'should return the output array' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/repl.txt b/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/repl.txt new file mode 100644 index 000000000000..4710cc02d131 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/repl.txt @@ -0,0 +1,69 @@ + +{{alias}}( str, radix ) + Parses a string representation of a 64-bit unsigned integer into high and + low 32-bit words. + + The function returns an array with two elements: a higher order word and a + lower order word, respectively. The lower order word contains the less + significant bits, while the higher order word contains the more significant + bits. + + Parameters + ---------- + str: string + String representation of a 64-bit unsigned integer. + + radix: integer + Radix (base) to use for string conversion (2-36). + + Returns + ------- + out: Array + High and low words as 32-bit unsigned integers. + + Examples + -------- + > var w = {{alias}}( '1234', 10 ) + [ 0, 1234 ] + > w = {{alias}}( 'abcd', 16 ) + [ 0, 43981 ] + > w = {{alias}}( '3w5e11264sgsf', 36 ) + [ 4294967295, 4294967295 ] + + +{{alias}}.assign( str, radix, out, stride, offset ) + Parses a string representation of a 64-bit unsigned integer into high and + low 32-bit words and assigns results to a provided output array. + + Parameters + ---------- + str: string + String representation of a 64-bit unsigned integer. + + radix: integer + Radix (base) to use for string conversion (2-36). + + out: Array|TypedArray|Object + Output array. + + stride: integer + Output array stride. + + offset: integer + Output array index offset. + + Returns + ------- + out: Array|TypedArray|Object + Output array. + + Examples + -------- + > var out = new {{alias:@stdlib/array/uint32}}( 2 ); + > var w = {{alias}}.assign( 'ffffffffffffffff', 16, out, 1, 0 ) + [ 4294967295, 4294967295 ] + > var bool = ( w === out ) + true + + See Also + -------- diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/types/index.d.ts new file mode 100644 index 000000000000..dcd5aeb55102 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/types/index.d.ts @@ -0,0 +1,113 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { Collection, NumericArray } from '@stdlib/types/array'; + +/** +* Interface describing `string2words`. +*/ +interface StringToWords { + /** + * Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words. + * + * @param str - string representation of a 64-bit unsigned integer + * @param radix - radix (base) to use for string conversion (2-36) + * @returns output array + * + * @example + * var out = string2words( '1234', 10 ); + * // returns [ 0, 1234 ] + * + * out = string2words( '18446744073709551615', 10 ); + * // returns [ 4294967295, 4294967295 ] + * + * out = string2words( 'ffffffffffffffff', 16 ); + * // returns [ 4294967295, 4294967295 ] + * + * out = string2words( '3w5e11264sgsf', 36 ); + * // returns [ 4294967295, 4294967295 ] + */ + ( str: string, radix: number ): [ number, number ]; + + /** + * Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words and assigns results to a provided output array. + * + * @param str - string representation of a 64-bit unsigned integer + * @param radix - radix (base) to use for string conversion (2-36) + * @param out - output array + * @param stride - stride length + * @param offset - starting index + * @returns output array + * + * @example + * var Uint32Array = require( '@stdlib/array/uint32' ); + * + * var out = new Uint32Array( 2 ); + * // returns [ 0, 0 ] + * + * var w = string2words.assign( 'ffffffffffffffff', 16, out, 1, 0 ); + * // returns [ 4294967295, 4294967295 ] + * + * var bool = ( w === out ); + * // returns true + */ + assign>( str: string, radix: number, out: T, stride: number, offset: number ): T; +} + +/** +* Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words. +* +* @param str - string representation of a 64-bit unsigned integer +* @param radix - radix (base) to use for string conversion (2-36) +* @returns output array +* +* @example +* var out = string2words( '1234', 10 ); +* // returns [ 0, 1234 ] +* +* out = string2words( '18446744073709551615', 10 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = string2words( 'ffffffffffffffff', 16 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = string2words( '3w5e11264sgsf', 36 ); +* // returns [ 4294967295, 4294967295 ] +* +* @example +* var Uint32Array = require( '@stdlib/array/uint32' ); +* +* var out = new Uint32Array( 2 ); +* // returns [ 0, 0 ] +* +* var w = string2words.assign( 'ffffffffffffffff', 16, out, 1, 0 ); +* // returns [ 4294967295, 4294967295 ] +* +* var bool = ( w === out ); +* // returns true +*/ +declare var string2words: StringToWords; + + +// EXPORTS // + +export = string2words; diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/types/test.ts b/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/types/test.ts new file mode 100644 index 000000000000..08a1420095c4 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/docs/types/test.ts @@ -0,0 +1,133 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import string2words = require( './index' ); + + +// TESTS // + +// The function returns an array... +{ + string2words( '1234', 10 ); // $ExpectType [number, number] +} + +// The compiler throws an error if the function is provided a first argument that is not a string... +{ + string2words( 5, 10 ); // $ExpectError + string2words( true, 10 ); // $ExpectError + string2words( false, 10 ); // $ExpectError + string2words( null, 10 ); // $ExpectError + string2words( {}, 10 ); // $ExpectError + string2words( ( x: number ): number => x, 10 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument that is not a number... +{ + string2words( '1234', '5' ); // $ExpectError + string2words( '1234', true ); // $ExpectError + string2words( '1234', false ); // $ExpectError + string2words( '1234', null ); // $ExpectError + string2words( '1234', {} ); // $ExpectError + string2words( '1234', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + string2words(); // $ExpectError + string2words( '1234', 10, 1 ); // $ExpectError +} + +// Attached to the main export is an `assign` method which returns an array-like object containing numbers... +{ + string2words.assign( '1234', 10, [ 0, 0 ], 1, 0 ); // $ExpectType number[] + string2words.assign( '1234', 10, new Uint32Array( 2 ), 1, 0 ); // $ExpectType Uint32Array + string2words.assign( '1234', 10, new Float64Array( 2 ), 1, 0 ); // $ExpectType Float64Array +} + +// The compiler throws an error if the `assign` method is provided a first argument which is not a string... +{ + const out = [ 0.0, 0.0 ]; + + string2words.assign( 5, 10, out, 1, 0 ); // $ExpectError + string2words.assign( true, 10, out, 1, 0 ); // $ExpectError + string2words.assign( false, 10, out, 1, 0 ); // $ExpectError + string2words.assign( null, 10, out, 1, 0 ); // $ExpectError + string2words.assign( [], 10, out, 1, 0 ); // $ExpectError + string2words.assign( {}, 10, out, 1, 0 ); // $ExpectError + string2words.assign( ( x: number ): number => x, 10, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a second argument which is not a number... +{ + const out = [ 0.0, 0.0 ]; + + string2words.assign( '1234', '5', out, 1, 0 ); // $ExpectError + string2words.assign( '1234', true, out, 1, 0 ); // $ExpectError + string2words.assign( '1234', false, out, 1, 0 ); // $ExpectError + string2words.assign( '1234', null, out, 1, 0 ); // $ExpectError + string2words.assign( '1234', [], out, 1, 0 ); // $ExpectError + string2words.assign( '1234', {}, out, 1, 0 ); // $ExpectError + string2words.assign( '1234', ( x: number ): number => x, out, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a third argument which is not an array-like object... +{ + string2words.assign( '1234', 10, 1, 1, 0 ); // $ExpectError + string2words.assign( '1234', 10, true, 1, 0 ); // $ExpectError + string2words.assign( '1234', 10, false, 1, 0 ); // $ExpectError + string2words.assign( '1234', 10, null, 1, 0 ); // $ExpectError + string2words.assign( '1234', 10, {}, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a fourth argument which is not a number... +{ + const out = [ 0.0, 0.0 ]; + + string2words.assign( '1234', 10, out, '5', 0 ); // $ExpectError + string2words.assign( '1234', 10, out, true, 0 ); // $ExpectError + string2words.assign( '1234', 10, out, false, 0 ); // $ExpectError + string2words.assign( '1234', 10, out, null, 0 ); // $ExpectError + string2words.assign( '1234', 10, out, [], 0 ); // $ExpectError + string2words.assign( '1234', 10, out, {}, 0 ); // $ExpectError + string2words.assign( '1234', 10, out, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided a fifth argument which is not a number... +{ + const out = [ 0.0, 0.0 ]; + + string2words.assign( '1234', 10, out, 1, '5' ); // $ExpectError + string2words.assign( '1234', 10, out, 1, true ); // $ExpectError + string2words.assign( '1234', 10, out, 1, false ); // $ExpectError + string2words.assign( '1234', 10, out, 1, null ); // $ExpectError + string2words.assign( '1234', 10, out, 1, [] ); // $ExpectError + string2words.assign( '1234', 10, out, 1, {} ); // $ExpectError + string2words.assign( '1234', 10, out, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `assign` method is provided an unsupported number of arguments... +{ + const out = [ 0.0, 0.0 ]; + + string2words.assign(); // $ExpectError + string2words.assign( '1234' ); // $ExpectError + string2words.assign( '1234', 10 ); // $ExpectError + string2words.assign( '1234', 10, out ); // $ExpectError + string2words.assign( '1234', 10, out, 1 ); // $ExpectError + string2words.assign( '1234', 10, out, 1, 0, 1 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/examples/index.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/examples/index.js new file mode 100644 index 000000000000..d9eda984a20e --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var string2words = require( './../lib' ); + +var w = string2words( '1234', 10 ); +console.log( w ); +// => [ 0, 1234 ] + +w = string2words( 'abcd', 16 ); +console.log( w ); +// => [ 0, 43981 ] + +w = string2words( '18446744073709551615', 10 ); +console.log( w ); +// => [ 4294967295, 4294967295 ] + +w = string2words( '3w5e11264sgsf', 36 ); +console.log( w ); +// => [ 4294967295, 4294967295 ] diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/assign.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/assign.js new file mode 100644 index 000000000000..3358c8bfd5f0 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/assign.js @@ -0,0 +1,211 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var slice = require( '@stdlib/string/base/slice' ); +var format = require( '@stdlib/string/format' ); + + +// VARIABLES // + +var TWO_32 = 0x100000000; // 2^32 + +/* eslint-disable array-element-newline */ + +/** +* A flat, strided array containing metadata for parsing large numeric strings into 64-bit values within JavaScript's 53-bit safe integer precision limits. +* +* Each radix from 2 to 36 is represented by a 3-element tuple: `[chunk1_len, chunk2_len, multiplier]`. +* +* ## Tuple Properties +* +* - **chunk1_len**: the maximum number of digits that can be safely parsed in a single pass without exceeding `2^53 - 1`. +* - **chunk2_len**: the remaining number of digits required to fulfill the maximum width of a 64-bit unsigned integer for that radix. +* - **multiplier**: the positional weight scalar (`radix^chunk2_len`) used to shift the place value of the first chunk when aggregating the final 64-bit split. +* +* @private +* @name CHUNKMAP +* @type {Array} +*/ +var CHUNKMAP = [ + // , , // radix + 53, 11, 2048, // 2 + 33, 8, 6561, // 3 + 26, 6, 4096, // 4 + 22, 6, 15625, // 5 + 20, 5, 7776, // 6 + 18, 5, 16807, // 7 + 17, 5, 32768, // 8 + 16, 5, 59049, // 9 + 15, 5, 100000, // 10 + 15, 4, 14641, // 11 + 14, 4, 20736, // 12 + 14, 4, 28561, // 13 + 13, 4, 38416, // 14 + 13, 4, 50625, // 15 + 13, 3, 4096, // 16 + 12, 4, 83521, // 17 + 12, 4, 104976, // 18 + 12, 4, 130321, // 19 + 12, 3, 8000, // 20 + 12, 3, 9261, // 21 + 11, 4, 234256, // 22 + 11, 4, 279841, // 23 + 11, 3, 13824, // 24 + 11, 3, 15625, // 25 + 11, 3, 17576, // 26 + 11, 3, 19683, // 27 + 11, 3, 21952, // 28 + 10, 4, 707281, // 29 + 10, 4, 810000, // 30 + 10, 3, 29791, // 31 + 10, 3, 32768, // 32 + 10, 3, 35937, // 33 + 10, 3, 39304, // 34 + 10, 3, 42875, // 35 + 10, 3, 46656 // 36 +]; + +/* eslint-enable array-element-newline */ + +/** +* Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words using two-step chunking. +* +* @private +* @param {string} str - string representation of a 64-bit unsigned integer +* @param {PositiveInteger} radix - radix (base) to use for string conversion (2-36) +* @param {PositiveInteger} len1 - length of the first chunk +* @param {PositiveInteger} len2 - length of the second chunk +* @param {PositiveInteger} mult - multiplier for the place value calculation (radix raised to the power of len2) +* @param {Collection} out - output array +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - starting index +* @throws {RangeError} first argument must be a string encoding an integer on the interval [0, 2^64) +* @returns {Collection} output array +* +* @example +* var out = chunkedParse( '1111111111111111111111111111111111111111111111111111111111111111', 2, CHUNKMAP[0], CHUNKMAP[1], CHUNKMAP[2], [ 0, 0 ], 1, 0 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = chunkedParse( '18446744073709551615', 10, CHUNKMAP[24], CHUNKMAP[25], CHUNKMAP[26], [ 0, 0 ], 1, 0 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = chunkedParse( '3w5e11264sgsf', 36, CHUNKMAP[102], CHUNKMAP[103], CHUNKMAP[104], [ 0, 0 ], 1, 0 ); +* // returns [ 4294967295, 4294967295 ] +*/ +function chunkedParse( str, radix, len1, len2, mult, out, stride, offset ) { + var chunk1; + var chunk2; + var hi; + var lo; + + if ( str.length <= len1 ) { + // Parse in a single pass when input length is within chunk1 length: + chunk1 = parseInt( str, radix ); + } else { + // Otherwise use a big chunk1 (start-aligned) and a small chunk2 (end-aligned): + chunk1 = parseInt( slice( str, 0, -len2 ), radix ); // everything until last `len2` digits + chunk2 = parseInt( slice( str, -len2 ), radix ); // `len2` digits from the end + } + + hi = ( chunk1 / TWO_32 ) >>> 0; // integer division by 2^32 + lo = chunk1 >>> 0; // 32-bit truncation + + // Process chunk2 if applicable... + if ( str.length > len1 ) { + lo = ( lo * mult ) + chunk2; + hi = ( hi * mult ) + ( ( lo / TWO_32 ) >>> 0 ); + lo >>>= 0; // 32-bit truncation + + // Check if too big for uint64... + if ( hi >= TWO_32 ) { + throw new RangeError( format( 'invalid argument. First argument must be a string encoding an integer on the interval [0, 2^64). Value: `%s`.', str ) ); + } + } + out[ offset ] = hi; + out[ offset + stride ] = lo; + return out; +} + + +// MAIN // + +/** +* Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words and assigns results to a provided output array. +* +* @param {string} str - string representation of a 64-bit unsigned integer +* @param {PositiveInteger} radix - radix (base) to use for string conversion (2-36) +* @param {Collection} out - output array +* @param {integer} stride - stride length +* @param {NonNegativeInteger} offset - starting index +* @throws {RangeError} first argument must be a string encoding an integer on the interval [0, 2^64) +* @throws {RangeError} second argument must be an integer on the interval [2, 36] +* @returns {Collection} output array +* +* @example +* var Uint32Array = require( '@stdlib/array/uint32' ); +* +* var out = new Uint32Array( 2 ); +* // returns [ 0, 0 ] +* +* var w = assign( 'ffffffffffffffff', 16, out, 1, 0 ); +* // returns [ 4294967295, 4294967295 ] +* +* var bool = ( w === out ); +* // returns true +*/ +function assign( str, radix, out, stride, offset ) { + var len1; + var len2; + var mult; + var idx; + + // Check for an invalid radix... + if ( radix < 2 || radix > 36 ) { + throw new RangeError( format( 'invalid argument. Second argument must be an integer on the interval [2, 36]. Value: `%s`.', radix ) ); + } + // Compute the index into a pre-computed strided table: + idx = 3 * ( radix-2 ); + + // Use a pre-computed table to select chunk lengths and the multiplier: + len1 = CHUNKMAP[ idx ]; + len2 = CHUNKMAP[ idx+1 ]; + mult = CHUNKMAP[ idx+2 ]; + + // Check if too big for uint64... + if ( str.length > len1+len2 ) { + throw new RangeError( format( 'invalid argument. First argument must be a string encoding an integer on the interval [0, 2^64). Value: `%s`.', str ) ); + } + // Fast path for bases 2, 4, and 16, thanks to evenly splittable 32-bit halves... + if ( radix === 2 || radix === 4 || radix === 16 ) { + len1 = ( len1 + len2 ) / 2; + out[ offset ] = parseInt( '0' + slice( str, 0, -len1 ), radix ); // add leading zero in case the higher slice is empty + out[ offset + stride ] = parseInt( slice( str, -len1 ), radix ); + return out; + } + // General path for other bases: + return chunkedParse( str, radix, len1, len2, mult, out, stride, offset ); +} + + +// EXPORTS // + +module.exports = assign; diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/index.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/index.js new file mode 100644 index 000000000000..73cf1087db5c --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Parse a string representation of a 64-bit unsigned integer into high and low 32-bit words. +* +* @module @stdlib/number/uint64/base/string2words +* +* @example +* var string2words = require( '@stdlib/number/uint64/base/string2words' ); +* +* var out = string2words( '1234', 10 ); +* // returns [ 0, 1234 ] +* +* out = string2words( '18446744073709551615', 10 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = string2words( 'ffffffffffffffff', 16 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = string2words( '3w5e11264sgsf', 36 ); +* // returns [ 4294967295, 4294967295 ] +*/ + + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var assign = require( './assign.js' ); +var main = require( './main.js' ); + + +// MAIN // + +setReadOnly( main, 'assign', assign ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/main.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/main.js new file mode 100644 index 000000000000..27a9fb078b76 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/lib/main.js @@ -0,0 +1,55 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var assign = require( './assign.js' ); + + +// MAIN // + +/** +* Parses a string representation of a 64-bit unsigned integer into high and low 32-bit words. +* +* @param {string} str - string representation of a 64-bit unsigned integer +* @param {PositiveInteger} radix - radix (base) to use for string conversion (2-36) +* @returns {Collection} output array +* +* @example +* var out = string2words( '1234', 10 ); +* // returns [ 0, 1234 ] +* +* out = string2words( '18446744073709551615', 10 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = string2words( 'ffffffffffffffff', 16 ); +* // returns [ 4294967295, 4294967295 ] +* +* out = string2words( '3w5e11264sgsf', 36 ); +* // returns [ 4294967295, 4294967295 ] +*/ +function string2words( str, radix ) { + return assign( str, radix, [ 0, 0 ], 1, 0 ); +} + + +// EXPORTS // + +module.exports = string2words; diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/package.json b/lib/node_modules/@stdlib/number/uint64/base/string2words/package.json new file mode 100644 index 000000000000..67879c33dfe6 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/number/uint64/base/string2words", + "version": "0.0.0", + "description": "Parse a string representation of a 64-bit unsigned integer into high and low 32-bit words.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdtypes", + "base", + "utilities", + "utility", + "utils", + "util", + "types", + "type", + "uint64", + "unsigned", + "64-bit", + "integer", + "int", + "string", + "parse", + "words", + "split", + "high", + "low" + ] +} diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.assign.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.assign.js new file mode 100644 index 000000000000..53bb498a7ab7 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.assign.js @@ -0,0 +1,258 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var Uint32Array = require( '@stdlib/array/uint32' ); +var hasBigIntSupport = require( '@stdlib/assert/has-bigint-support' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var BigInt = require( '@stdlib/bigint/ctor' ); +var MAX_SAFE_INTEGER = require( '@stdlib/constants/float64/max-safe-integer' ); +var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var format = require( '@stdlib/string/format' ); +var string2words = require( './../lib/assign.js' ); + + +// VARIABLES // + +var opts = { + 'skip': !hasBigIntSupport() +}; + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof string2words, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a two-element numeric array containing integers', function test( t ) { + var out; + var w; + + out = [ 0, 0 ]; + w = string2words( '1234', 10, out, 1, 0 ); + + t.strictEqual( w, out, 'returns expected value' ); + t.strictEqual( isInteger( w[0] ), true, 'returns expected value' ); + t.strictEqual( isInteger( w[1] ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function parses a string representation of a 64-bit unsigned integer into high and low 32-bit words', function test( t ) { + var out; + var w; + + out = [ 0, 0 ]; + w = string2words( '18446744073709551615', 10, out, 1, 0 ); + + t.strictEqual( w, out, 'returns expected value' ); + t.strictEqual( w[0], 4294967295, 'returns expected value' ); + t.strictEqual( w[1], 4294967295, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function parses a string representation of a 64-bit unsigned integer into high and low 32-bit words in bases 2 through 36', opts, function test( t ) { + var values; + var out; + var rad; + var i; + var s; + var w; + var x; + + values = [ + 0, + 1, + 2, + 3, + 4, + 5, + 10, + 99, + 100, + 999, + 1000, + 999999, + 1000000, + 999999999, + 1000000000, + UINT32_MAX, + UINT32_MAX + 1, + 9007199254740881, // Largest prime under 2^53 + MAX_SAFE_INTEGER - 1, + MAX_SAFE_INTEGER, + '9007199254740992', // MAX_SAFE_INTEGER + 1 + '9999999999999999', + '10000000000000000', + '99999999999999999', + '100000000000000000', + '999999999999999999', + '1000000000000000000', + '9223372036854775783', // Largest prime under 2^63 + '9999999999999999999', + '10000000000000000000', + '18446744073709551557', // Largest prime under 2^64 + '18446744073709551615' // 2^64 - 1 + ]; + + out = [ 0, 0 ]; + + for ( i = 0; i < values.length; i++ ) { + values[ i ] = BigInt( values[ i ] ); // Convert values to BigInt + + for ( rad = 2; rad <= 36; rad++ ) { + s = values[ i ].toString( rad ); // Convert BigInt to string with a radix + w = string2words( s, rad, out, 1, 0 ); + t.strictEqual( w, out, 'returns expected value' ); + + x = ( BigInt( w[0] ) << BigInt( 32 ) ) | BigInt( w[1] ); // Create BigInt from words + t.strictEqual( x, values[ i ], 'returns expected value' ); + } + } + t.end(); +}); + +tape( 'the function throws an error if the provided string represents a value greater than 2^64-1', opts, function test( t ) { + var values; + var out; + var rad; + var i; + var s; + + values = [ + '0x10000000000000000', + '0x10000000000000001', + '0x123456789abcdef01', + '0xdeadbeef15badf00d', + '0x1337c0de4ce5b16b055', + '0x123456789abcdef0123456789abcdef0' + ]; + + out = [ 0, 0 ]; + + for ( i = 0; i < values.length; i++ ) { + values[ i ] = BigInt( values[ i ] ); // Convert values to BigInt + + for ( rad = 2; rad <= 36; rad++ ) { + s = values[ i ].toString( rad ); // Convert BigInt to string with a radix + t.throws( badValue( s, rad ), RangeError, format( 'throws an error when provided %s and %s', s, rad ) ); + } + } + t.end(); + + function badValue( str, radix ) { + return function badValue() { + string2words( str, radix, out, 1, 0 ); + }; + } +}); + +tape( 'the function throws an error if provided an invalid radix', function test( t ) { + var values; + var out; + var i; + + values = [ + 0, + 1, + 37, + 38, + 100 + ]; + + out = [ 0, 0 ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), RangeError, format( 'throws an error when provided %s', values[ i ] ) ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + string2words( '10', value, out, 1, 0 ); + }; + } +}); + +tape( 'the function supports providing an output object (array)', function test( t ) { + var out; + var w; + + out = [ 0, 0 ]; + w = string2words( '4294967296', 10, out, 1, 0 ); + + t.strictEqual( w, out, 'returns expected value' ); + t.strictEqual( w[ 0 ], 1, 'returns expected value' ); + t.strictEqual( w[ 1 ], 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports providing an output object (typed array)', function test( t ) { + var out; + var w; + + out = new Uint32Array( 2 ); + w = string2words( '4294967296', 10, out, 1, 0 ); + + t.strictEqual( w, out, 'returns expected value' ); + t.strictEqual( w[ 0 ], 1, 'returns expected value' ); + t.strictEqual( w[ 1 ], 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying a stride', function test( t ) { + var out; + var val; + + out = new Uint32Array( 4 ); + val = string2words( '4294967298', 10, out, 2, 0 ); + + t.strictEqual( val, out, 'returns expected value' ); + t.strictEqual( val[ 0 ], 1, 'returns expected value' ); + t.strictEqual( val[ 1 ], 0, 'returns expected value' ); + t.strictEqual( val[ 2 ], 2, 'returns expected value' ); + t.strictEqual( val[ 3 ], 0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function supports specifying an offset', function test( t ) { + var out; + var val; + + out = new Uint32Array( 4 ); + val = string2words( '4294967298', 10, out, 2, 1 ); + + t.strictEqual( val, out, 'returns expected value' ); + t.strictEqual( val[ 0 ], 0, 'returns expected value' ); + t.strictEqual( val[ 1 ], 1, 'returns expected value' ); + t.strictEqual( val[ 2 ], 0, 'returns expected value' ); + t.strictEqual( val[ 3 ], 2, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.js new file mode 100644 index 000000000000..4eb42e279f95 --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var hasOwnProp = require( '@stdlib/assert/has-own-property' ); +var string2words = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof string2words, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is an `assign` method', function test( t ) { + t.strictEqual( hasOwnProp( string2words, 'assign' ), true, 'has property' ); + t.strictEqual( typeof string2words.assign, 'function', 'has method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.main.js b/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.main.js new file mode 100644 index 000000000000..5b128016ec7a --- /dev/null +++ b/lib/node_modules/@stdlib/number/uint64/base/string2words/test/test.main.js @@ -0,0 +1,52 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive; +var string2words = require( './../lib/main.js' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof string2words, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a two-element numeric array containing integers', function test( t ) { + var w = string2words( '1234', 10 ); + + t.strictEqual( isInteger( w[0] ), true, 'returns expected value' ); + t.strictEqual( isInteger( w[1] ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function parses a string representation of a 64-bit unsigned integer into high and low 32-bit words', function test( t ) { + var w = string2words( '18446744073709551615', 10 ); + + t.strictEqual( w[0], 4294967295, 'returns expected value' ); + t.strictEqual( w[1], 4294967295, 'returns expected value' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/assign.js b/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/assign.js index 6c6b46b935be..dd51f343fdc7 100644 --- a/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/assign.js +++ b/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/assign.js @@ -18,6 +18,12 @@ 'use strict'; +// MODULES // + +var getHighWord = require( '@stdlib/number/uint64/base/get-high-word' ); +var getLowWord = require( '@stdlib/number/uint64/base/get-low-word' ); + + // MAIN // /** @@ -43,8 +49,8 @@ * // returns true */ function toWords( a, out, stride, offset ) { - out[ offset ] = a.hi; - out[ offset + stride ] = a.lo; + out[ offset ] = getHighWord( a ); + out[ offset + stride ] = getLowWord( a ); return out; } diff --git a/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/main.js b/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/main.js index 1d9ab871af39..37b9ea8916fd 100644 --- a/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/main.js +++ b/lib/node_modules/@stdlib/number/uint64/base/to-words/lib/main.js @@ -20,7 +20,7 @@ // MODULES // -var fcn = require( './assign.js' ); +var assign = require( './assign.js' ); // MAIN // @@ -39,7 +39,7 @@ var fcn = require( './assign.js' ); * // returns [ 1, 0 ] */ function toWords( a ) { - return fcn( a, [ 0>>>0, 0>>>0 ], 1, 0 ); + return assign( a, [ 0>>>0, 0>>>0 ], 1, 0 ); } diff --git a/lib/node_modules/@stdlib/number/uint64/ctor/README.md b/lib/node_modules/@stdlib/number/uint64/ctor/README.md index 275383dcdd9b..948d61d0843b 100644 --- a/lib/node_modules/@stdlib/number/uint64/ctor/README.md +++ b/lib/node_modules/@stdlib/number/uint64/ctor/README.md @@ -189,7 +189,7 @@ var v = x.valueOf(); ## Notes -- A 64-bit unsigned integer has a range of \[`0`, `2^64-1`\]. +- A 64-bit unsigned integer has a range of \[`0`, `2^64-1`].
@@ -224,7 +224,6 @@ console.log( 'JSON: %s', JSON.stringify( x ) ); -
@@ -237,6 +236,12 @@ console.log( 'JSON: %s', JSON.stringify( x ) );
+* * * + +## See Also + +- [`@stdlib/number/ctor`][@stdlib/number/ctor]: number constructor. +
@@ -255,6 +260,8 @@ console.log( 'JSON: %s', JSON.stringify( x ) ); +[@stdlib/number/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/number/ctor +
diff --git a/lib/node_modules/@stdlib/number/uint64/ctor/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/uint64/ctor/benchmark/benchmark.js index 5ba96db6fe0e..45e8c085af51 100644 --- a/lib/node_modules/@stdlib/number/uint64/ctor/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/number/uint64/ctor/benchmark/benchmark.js @@ -53,7 +53,7 @@ bench( format( '%s::constructor', pkg ), function benchmark( b ) { b.end(); }); -bench( format( '%s::from', pkg ), function benchmark( b ) { +bench( format( '%s:from', pkg ), function benchmark( b ) { var x; var z; var i; @@ -78,7 +78,7 @@ bench( format( '%s::from', pkg ), function benchmark( b ) { b.end(); }); -bench( format( '%s::of', pkg ), function benchmark( b ) { +bench( format( '%s:of', pkg ), function benchmark( b ) { var x; var z; var i; diff --git a/lib/node_modules/@stdlib/number/uint64/ctor/docs/repl.txt b/lib/node_modules/@stdlib/number/uint64/ctor/docs/repl.txt index 0b97b13d8848..02238b6d722b 100644 --- a/lib/node_modules/@stdlib/number/uint64/ctor/docs/repl.txt +++ b/lib/node_modules/@stdlib/number/uint64/ctor/docs/repl.txt @@ -4,7 +4,7 @@ Parameters ---------- - value: number|bigint + value: integer|bigint Integer value. Returns diff --git a/lib/node_modules/@stdlib/number/uint64/ctor/lib/main.js b/lib/node_modules/@stdlib/number/uint64/ctor/lib/main.js index 25e069dd709c..6e5579a28a06 100644 --- a/lib/node_modules/@stdlib/number/uint64/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/number/uint64/ctor/lib/main.js @@ -154,8 +154,8 @@ setReadOnly( Uint64, 'from', function fromWords( words ) { * @name of * @memberof Uint64 * @type {Function} -* @param {uinteger} high - high word (32-bit unsigned integer) -* @param {uinteger} low - low word (32-bit unsigned integer) +* @param {uinteger32} high - high word (32-bit unsigned integer) +* @param {uinteger32} low - low word (32-bit unsigned integer) * @throws {TypeError} first argument must be a nonnegative integer * @throws {TypeError} second argument must be a nonnegative integer * @returns {Uint64} 64-bit unsigned integer @@ -229,8 +229,8 @@ setReadOnly( Uint64.prototype, 'byteLength', 8 ); * * @name hi * @memberof Uint64.prototype -* @type {uinteger} -* @returns {uinteger} high word (32-bit unsigned integer) +* @type {uinteger32} +* @returns {uinteger32} high word (32-bit unsigned integer) * * @example * var x = Uint64.from( [ 1234, 5678 ] ); @@ -247,8 +247,8 @@ setReadOnlyAccessor( Uint64.prototype, 'hi', function getHighWord() { * * @name lo * @memberof Uint64.prototype -* @type {uinteger} -* @returns {uinteger} low word (32-bit unsigned integer) +* @type {uinteger32} +* @returns {uinteger32} low word (32-bit unsigned integer) * * @example * var x = Uint64.from( [ 1234, 5678 ] ); @@ -293,6 +293,7 @@ setReadOnly( Uint64.prototype, 'toString', function toString( radix ) { if ( HAS_BIGINT ) { return BigInt( this.valueOf() ).toString( rad ); } + // TODO: Refactor to use `uint64/base/words2string` later return int2str( [ this.hi, this.lo ], rad ); }); @@ -337,9 +338,9 @@ setReadOnly( Uint64.prototype, 'toJSON', function toJSON() { */ setReadOnly( Uint64.prototype, 'valueOf', function valueOf() { if ( HAS_BIGINT ) { - return ( BigInt( this._buffer[ indices.HIGH ] ) << BigInt( 32 ) ) | BigInt( this._buffer[ indices.LOW ] ); + return ( BigInt( this.hi ) << BigInt( 32 ) ) | BigInt( this.lo ); } - return ( this._buffer[ indices.HIGH ] * TWO_32 ) + this._buffer[ indices.LOW ]; + return ( this.hi * TWO_32 ) + this.lo; }); /** @@ -372,7 +373,7 @@ setReadOnly( Uint64.prototype, 'valueOf', function valueOf() { if ( hasToPrimitiveSymbolSupport() ) { setReadOnly( Uint64.prototype, ToPrimitiveSymbol, function toPrimitive( hint ) { if ( hint === 'number' ) { - return ( this._buffer[ indices.HIGH ] * TWO_32 ) + this._buffer[ indices.LOW ]; + return ( this.hi * TWO_32 ) + this.lo; } if ( hint === 'string' ) { return this.toString(); diff --git a/lib/node_modules/@stdlib/number/uint64/ctor/test/test.from.js b/lib/node_modules/@stdlib/number/uint64/ctor/test/test.from.js index 0a975d063092..5f6928a05a1d 100644 --- a/lib/node_modules/@stdlib/number/uint64/ctor/test/test.from.js +++ b/lib/node_modules/@stdlib/number/uint64/ctor/test/test.from.js @@ -21,10 +21,11 @@ // MODULES // var tape = require( 'tape' ); +var Uint32Array = require( '@stdlib/array/uint32' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var isFunction = require( '@stdlib/assert/is-function' ); var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); -var Uint32Array = require( '@stdlib/array/uint32' ); +var format = require( '@stdlib/string/format' ); var Uint64 = require( './../lib' ); @@ -37,8 +38,8 @@ tape( 'main export is a function', function test( t ) { }); tape( 'attached to the main export is a read-only `from` method', function test( t ) { - t.strictEqual( hasOwnProp( Uint64, 'from' ), true, 'has property' ); - t.strictEqual( isFunction( Uint64.from ), true, 'has method' ); + t.ok( hasOwnProp( Uint64, 'from' ), 'has property' ); + t.ok( isFunction( Uint64.from ), 'has method' ); t.throws( foo, Error, 'throws an error' ); t.end(); @@ -68,7 +69,7 @@ tape( 'the method throws an error if not provided an array-like object containin ]; for ( i = 0; i < values.length; i++ ) { - t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + t.throws( badValue( values[i] ), TypeError, format( 'throws an error when provided %s', values[i] ) ); } t.end(); @@ -83,20 +84,28 @@ tape( 'the method returns a 64-bit unsigned integer', function test( t ) { var x; x = Uint64.from( [ 0, 1 ] ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0, 'returns expected value' ); + t.strictEqual( x.lo, 1, 'returns expected value' ); x = Uint64.from( [ UINT32_MAX, UINT32_MAX ] ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, UINT32_MAX, 'returns expected value' ); + t.strictEqual( x.lo, UINT32_MAX, 'returns expected value' ); x = Uint64.from( new Uint32Array( [ 0, 1 ] ) ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0, 'returns expected value' ); + t.strictEqual( x.lo, 1, 'returns expected value' ); x = Uint64.from({ '0': 10, '1': 20, 'length': 2 }); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 10, 'returns expected value' ); + t.strictEqual( x.lo, 20, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/number/uint64/ctor/test/test.js b/lib/node_modules/@stdlib/number/uint64/ctor/test/test.js index 74ed2c3c54a7..f9ef99f49d82 100644 --- a/lib/node_modules/@stdlib/number/uint64/ctor/test/test.js +++ b/lib/node_modules/@stdlib/number/uint64/ctor/test/test.js @@ -27,6 +27,7 @@ var hasToPrimitiveSymbolSupport = require( '@stdlib/assert/has-to-primitive-symb var BigInt = require( '@stdlib/bigint/ctor' ); var MAX_SAFE_INTEGER = require( '@stdlib/constants/float64/max-safe-integer' ); var Number = require( '@stdlib/number/ctor' ); +var format = require( '@stdlib/string/format' ); var ToPrimitiveSymbol = require( '@stdlib/symbol/to-primitive' ); var Uint64 = require( './../lib' ); @@ -46,7 +47,7 @@ tape( 'main export is a function', function test( t ) { tape( 'the function is a constructor', function test( t ) { var x = new Uint64( 5 ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); t.end(); }); @@ -74,7 +75,7 @@ tape( 'the constructor throws an error if not provided a number or BigInt', func function noop() {} ]; for ( i = 0; i < values.length; i++ ) { - t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + t.throws( badValue( values[i] ), TypeError, format( 'throws an error when provided %s', values[i] ) ); } t.end(); @@ -95,7 +96,7 @@ tape( 'the constructor throws an error if provided an invalid/unsupported number 1 + MAX_SAFE_INTEGER ]; for ( i = 0; i < values.length; i++ ) { - t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + t.throws( badValue( values[i] ), TypeError, format( 'throws an error when provided %s', values[i] ) ); } t.end(); @@ -121,7 +122,7 @@ tape( 'the constructor throws an error if provided an invalid/unsupported BigInt BigInt( 1 ) << BigInt( 64 ) // 2^64 ]; for ( i = 0; i < values.length; i++ ) { - t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + t.throws( badValue( values[i] ), TypeError, format( 'throws an error when provided %s', values[i] ) ); } t.end(); @@ -137,30 +138,42 @@ tape( 'the constructor returns a 64-bit unsigned integer', function test( t ) { var x; x = new Uint64( 0 ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0, 'returns expected value' ); + t.strictEqual( x.lo, 0, 'returns expected value' ); x = new Uint64( 1234 ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0, 'returns expected value' ); + t.strictEqual( x.lo, 1234, 'returns expected value' ); x = new Uint64( MAX_SAFE_INTEGER ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 2097151, 'returns expected value' ); + t.strictEqual( x.lo, 4294967295, 'returns expected value' ); if ( HAS_BIGINT ) { x = new Uint64( BigInt( 0 ) ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0, 'returns expected value' ); + t.strictEqual( x.lo, 0, 'returns expected value' ); x = new Uint64( BigInt( 1234 ) ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0, 'returns expected value' ); + t.strictEqual( x.lo, 1234, 'returns expected value' ); x = new Uint64( BigInt( '0xffffffffffffffff' ) ); // 2^64 - 1 - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0xffffffff, 'returns expected value' ); + t.strictEqual( x.lo, 0xffffffff, 'returns expected value' ); } t.end(); }); tape( 'the constructor has a read-only `name` property', function test( t ) { - t.strictEqual( hasOwnProp( Uint64, 'name' ), true, 'has property' ); + t.ok( hasOwnProp( Uint64, 'name' ), 'has property' ); t.strictEqual( Uint64.name, 'Uint64', 'returns expected value' ); t.throws( foo, Error, 'throws an error' ); t.end(); @@ -171,7 +184,7 @@ tape( 'the constructor has a read-only `name` property', function test( t ) { }); tape( 'the constructor has a read-only `BYTES_PER_ELEMENT` property', function test( t ) { - t.strictEqual( hasOwnProp( Uint64, 'BYTES_PER_ELEMENT' ), true, 'has property' ); + t.ok( hasOwnProp( Uint64, 'BYTES_PER_ELEMENT' ), 'has property' ); t.strictEqual( Uint64.BYTES_PER_ELEMENT, 8, 'returns expected value' ); t.throws( foo, Error, 'throws an error' ); t.end(); @@ -182,7 +195,7 @@ tape( 'the constructor has a read-only `BYTES_PER_ELEMENT` property', function t }); tape( 'the constructor prototype has a read-only `BYTES_PER_ELEMENT` property', function test( t ) { - t.strictEqual( hasOwnProp( Uint64.prototype, 'BYTES_PER_ELEMENT' ), true, 'has property' ); + t.ok( hasOwnProp( Uint64.prototype, 'BYTES_PER_ELEMENT' ), 'has property' ); t.strictEqual( Uint64.prototype.BYTES_PER_ELEMENT, 8, 'returns expected value' ); t.throws( foo, Error, 'throws an error' ); t.end(); @@ -193,7 +206,7 @@ tape( 'the constructor prototype has a read-only `BYTES_PER_ELEMENT` property', }); tape( 'the constructor prototype has a read-only `byteLength` property', function test( t ) { - t.strictEqual( hasOwnProp( Uint64.prototype, 'byteLength' ), true, 'has property' ); + t.ok( hasOwnProp( Uint64.prototype, 'byteLength' ), 'has property' ); t.strictEqual( Uint64.prototype.byteLength, 8, 'returns expected value' ); t.throws( foo, Error, 'throws an error' ); t.end(); diff --git a/lib/node_modules/@stdlib/number/uint64/ctor/test/test.of.js b/lib/node_modules/@stdlib/number/uint64/ctor/test/test.of.js index 90b7f0991289..d05ff4d64f63 100644 --- a/lib/node_modules/@stdlib/number/uint64/ctor/test/test.of.js +++ b/lib/node_modules/@stdlib/number/uint64/ctor/test/test.of.js @@ -23,8 +23,8 @@ var tape = require( 'tape' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var isFunction = require( '@stdlib/assert/is-function' ); -var format = require( '@stdlib/string/format' ); var UINT32_MAX = require( '@stdlib/constants/uint32/max' ); +var format = require( '@stdlib/string/format' ); var Uint64 = require( './../lib' ); @@ -37,8 +37,8 @@ tape( 'main export is a function', function test( t ) { }); tape( 'attached to the main export is a read-only `of` method', function test( t ) { - t.strictEqual( hasOwnProp( Uint64, 'of' ), true, 'has property' ); - t.strictEqual( isFunction( Uint64.of ), true, 'has method' ); + t.ok( hasOwnProp( Uint64, 'of' ), 'has property' ); + t.ok( isFunction( Uint64.of ), 'has method' ); t.throws( foo, Error, 'throws an error' ); t.end(); @@ -52,21 +52,22 @@ tape( 'the method throws an error if not provided two unsigned 32-bit integers', var i; values = [ - [ 0, null ], - [ 0, void 0 ], - [ 0, true ], - [ 0, false ], - [ 0, [] ], - [ 0, {} ], - [ 0, function noop() {} ], - [ 0, 'foo' ], - [ 0, -1 ], - [ 0, UINT32_MAX + 1 ] + null, + void 0, + true, + false, + [], + {}, + function noop() {}, + 'foo', + -1, + UINT32_MAX + 1 ]; for ( i = 0; i < values.length; i++ ) { - t.throws( badValue( values[i][0], values[i][1] ), TypeError, format( 'throws an error when provided %s, %s', values[i][0], values[i][1] ) ); - t.throws( badValue( values[i][1], values[i][0] ), TypeError, format( 'throws an error when provided %s, %s', values[i][1], values[i][0] ) ); + t.throws( badValue( 0, values[i] ), TypeError, format( 'throws an error when provided %s, %s', 0, values[i] ) ); + t.throws( badValue( values[i], 0 ), TypeError, format( 'throws an error when provided %s, %s', values[i], 0 ) ); + t.throws( badValue( values[i], values[i] ), TypeError, format( 'throws an error when provided %s, %s', values[i], values[i] ) ); } t.end(); @@ -81,10 +82,14 @@ tape( 'the method returns a 64-bit unsigned integer', function test( t ) { var x; x = Uint64.of( 0, 1 ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, 0, 'returns expected value' ); + t.strictEqual( x.lo, 1, 'returns expected value' ); x = Uint64.of( UINT32_MAX, UINT32_MAX ); - t.strictEqual( x instanceof Uint64, true, 'returns expected value' ); + t.ok( x instanceof Uint64, 'returns expected value' ); + t.strictEqual( x.hi, UINT32_MAX, 'returns expected value' ); + t.strictEqual( x.lo, UINT32_MAX, 'returns expected value' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/number/uint8/base/identity/lib/main.js b/lib/node_modules/@stdlib/number/uint8/base/identity/lib/main.js index e1e6ad962a5b..3162f8e1d600 100644 --- a/lib/node_modules/@stdlib/number/uint8/base/identity/lib/main.js +++ b/lib/node_modules/@stdlib/number/uint8/base/identity/lib/main.js @@ -18,6 +18,8 @@ 'use strict'; +// MAIN // + /** * Evaluates the identity function for an unsigned 8-bit integer `x`. * diff --git a/lib/node_modules/@stdlib/object/none-own-by/package.json b/lib/node_modules/@stdlib/object/none-own-by/package.json index 525bb25cf34a..0522f3dc6572 100644 --- a/lib/node_modules/@stdlib/object/none-own-by/package.json +++ b/lib/node_modules/@stdlib/object/none-own-by/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/object/none-own-by", "version": "0.0.0", - "description": "Tests whether every own property of an object fails a test implemented by a predicate function.", + "description": "Test whether every own property of an object fails a test implemented by a predicate function.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/os/platform/README.md b/lib/node_modules/@stdlib/os/platform/README.md index 46dd55f668c2..b6760bed6dfe 100644 --- a/lib/node_modules/@stdlib/os/platform/README.md +++ b/lib/node_modules/@stdlib/os/platform/README.md @@ -43,6 +43,24 @@ console.log( PLATFORM ); +
+ +## Notes + +- The following values are possible: + + - `'aix'` + - `'win32'` + - `'darwin'` + - `'linux'` + - `'freebsd'` + - `'openbsd'` + - `'sunos'` + +
+ + +
## Examples diff --git a/lib/node_modules/@stdlib/random/README.md b/lib/node_modules/@stdlib/random/README.md index 4c9b393c29e9..5027a218b14e 100644 --- a/lib/node_modules/@stdlib/random/README.md +++ b/lib/node_modules/@stdlib/random/README.md @@ -61,7 +61,7 @@ The namespace contains the following functions for generating pseudorandom value - [`arcsine( shape, a, b[, options] )`][@stdlib/random/arcsine]: generate pseudorandom numbers drawn from an arcsine distribution. - [`bernoulli( shape, p[, options] )`][@stdlib/random/bernoulli]: generate pseudorandom numbers drawn from a Bernoulli distribution. - [`beta( shape, a, b[, options] )`][@stdlib/random/beta]: generate pseudorandom numbers drawn from a beta distribution. -- [`betaprime( shape, alpha, beta[, options] )`][@stdlib/random/betaprime]: generate pseudorandom numbers drawn from a betaprime distribution. +- [`betaprime( shape, alpha, beta[, options] )`][@stdlib/random/betaprime]: generate pseudorandom numbers drawn from a beta prime distribution. - [`binomial( shape, n, p[, options] )`][@stdlib/random/binomial]: generate pseudorandom numbers drawn from a binomial distribution. - [`cauchy( shape, x0, gamma[, options] )`][@stdlib/random/cauchy]: generate pseudorandom numbers drawn from a Cauchy distribution. - [`chi( shape, k[, options] )`][@stdlib/random/chi]: generate pseudorandom numbers drawn from a chi distribution. diff --git a/lib/node_modules/@stdlib/random/array/arcsine/README.md b/lib/node_modules/@stdlib/random/array/arcsine/README.md index 84637b3ec46c..8c28b7d1b6f7 100644 --- a/lib/node_modules/@stdlib/random/array/arcsine/README.md +++ b/lib/node_modules/@stdlib/random/array/arcsine/README.md @@ -358,6 +358,7 @@ logEach( '%f', x4 ); ## See Also +- [`@stdlib/random/arcsine`][@stdlib/random/arcsine]: generate pseudorandom numbers drawn from an arcsine distribution. - [`@stdlib/random/base/arcsine`][@stdlib/random/base/arcsine]: arcsine distributed pseudorandom numbers. - [`@stdlib/random/strided/arcsine`][@stdlib/random/strided/arcsine]: fill a strided array with pseudorandom numbers drawn from an arcsine distribution. @@ -379,6 +380,8 @@ logEach( '%f', x4 ); +[@stdlib/random/arcsine]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/arcsine + [@stdlib/random/strided/arcsine]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/strided/arcsine diff --git a/lib/node_modules/@stdlib/random/array/cauchy/README.md b/lib/node_modules/@stdlib/random/array/cauchy/README.md index 1fa1331a4896..5b2b1b1e68b7 100644 --- a/lib/node_modules/@stdlib/random/array/cauchy/README.md +++ b/lib/node_modules/@stdlib/random/array/cauchy/README.md @@ -358,6 +358,7 @@ logEach( '%f', x4 ); ## See Also +- [`@stdlib/random/cauchy`][@stdlib/random/cauchy]: generate pseudorandom numbers drawn from a Cauchy distribution. - [`@stdlib/random/base/cauchy`][@stdlib/random/base/cauchy]: Cauchy distributed pseudorandom numbers.
@@ -376,6 +377,12 @@ logEach( '%f', x4 ); [@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64 + + +[@stdlib/random/cauchy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/cauchy + + + diff --git a/lib/node_modules/@stdlib/random/array/tools/binary-factory/lib/main.js b/lib/node_modules/@stdlib/random/array/tools/binary-factory/lib/main.js index 02aa98289d6f..f74251891aca 100644 --- a/lib/node_modules/@stdlib/random/array/tools/binary-factory/lib/main.js +++ b/lib/node_modules/@stdlib/random/array/tools/binary-factory/lib/main.js @@ -90,7 +90,7 @@ function createFactory( prng, dtypes, dtype ) { } // TODO: tighten this up by actually validating that `dtypes` contains only recognized/supported dtype strings if ( !isStringArray( dtypes ) ) { - throw new TypeError( format( 'invalid argument. Second argument must an array of strings. Value: `%s`.', dtypes ) ); + throw new TypeError( format( 'invalid argument. Second argument must be an array of strings. Value: `%s`.', dtypes ) ); } // Require that the default output array data type be a member of the list of supported output array data types... if ( !contains( dtypes, dtype ) ) { diff --git a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/lib/main.js b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/lib/main.js index e224c9ecdd81..ce6cf044d10d 100644 --- a/lib/node_modules/@stdlib/random/array/tools/ternary-factory/lib/main.js +++ b/lib/node_modules/@stdlib/random/array/tools/ternary-factory/lib/main.js @@ -90,7 +90,7 @@ function createFactory( prng, dtypes, dtype ) { } // TODO: tighten this up by actually validating that `dtypes` contains only recognized/supported dtype strings if ( !isStringArray( dtypes ) ) { - throw new TypeError( format( 'invalid argument. Second argument must an array of strings. Value: `%s`.', dtypes ) ); + throw new TypeError( format( 'invalid argument. Second argument must be an array of strings. Value: `%s`.', dtypes ) ); } // Require that the default output array data type be a member of the list of supported output array data types... if ( !contains( dtypes, dtype ) ) { diff --git a/lib/node_modules/@stdlib/random/array/tools/unary-factory/lib/main.js b/lib/node_modules/@stdlib/random/array/tools/unary-factory/lib/main.js index 16672278670d..264966292a94 100644 --- a/lib/node_modules/@stdlib/random/array/tools/unary-factory/lib/main.js +++ b/lib/node_modules/@stdlib/random/array/tools/unary-factory/lib/main.js @@ -91,7 +91,7 @@ function createFactory( prng, dtypes, dtype ) { } // TODO: tighten this up by actually validating that `dtypes` contains only recognized/supported dtype strings if ( !isStringArray( dtypes ) ) { - throw new TypeError( format( 'invalid argument. Second argument must an array of strings. Value: `%s`.', dtypes ) ); + throw new TypeError( format( 'invalid argument. Second argument must be an array of strings. Value: `%s`.', dtypes ) ); } // Require that the default output array data type be a member of the list of supported output array data types... if ( !contains( dtypes, dtype ) ) { diff --git a/lib/node_modules/@stdlib/random/array/uniform/README.md b/lib/node_modules/@stdlib/random/array/uniform/README.md index c80b0b2d0e39..d1398223bff6 100644 --- a/lib/node_modules/@stdlib/random/array/uniform/README.md +++ b/lib/node_modules/@stdlib/random/array/uniform/README.md @@ -361,6 +361,7 @@ logEach( '%f', x4 ); - [`@stdlib/random/array/discrete-uniform`][@stdlib/random/array/discrete-uniform]: create an array containing pseudorandom numbers drawn from a discrete uniform distribution. - [`@stdlib/random/base/uniform`][@stdlib/random/base/uniform]: uniformly distributed pseudorandom numbers. - [`@stdlib/random/strided/uniform`][@stdlib/random/strided/uniform]: fill a strided array with pseudorandom numbers drawn from a continuous uniform distribution. +- [`@stdlib/random/uniform`][@stdlib/random/uniform]: generate pseudorandom numbers drawn from a continuous uniform distribution. @@ -384,6 +385,8 @@ logEach( '%f', x4 ); [@stdlib/random/strided/uniform]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/strided/uniform +[@stdlib/random/uniform]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/uniform + diff --git a/lib/node_modules/@stdlib/random/base/betaprime/README.md b/lib/node_modules/@stdlib/random/base/betaprime/README.md index 11388da03436..75ccf4138cdf 100644 --- a/lib/node_modules/@stdlib/random/base/betaprime/README.md +++ b/lib/node_modules/@stdlib/random/base/betaprime/README.md @@ -416,7 +416,7 @@ for ( i = 0; i < 100; i++ ) { - [`@stdlib/random/array/betaprime`][@stdlib/random/array/betaprime]: create an array containing pseudorandom numbers drawn from a beta prime distribution. - [`@stdlib/random/iter/betaprime`][@stdlib/random/iter/betaprime]: create an iterator for generating pseudorandom numbers drawn from a beta prime distribution. - [`@stdlib/random/streams/betaprime`][@stdlib/random/streams/betaprime]: create a readable stream for generating pseudorandom numbers drawn from a beta prime distribution. -- [`@stdlib/random/betaprime`][@stdlib/random/betaprime]: generate pseudorandom numbers drawn from a betaprime distribution. +- [`@stdlib/random/betaprime`][@stdlib/random/betaprime]: generate pseudorandom numbers drawn from a beta prime distribution. diff --git a/lib/node_modules/@stdlib/random/base/gumbel/README.md b/lib/node_modules/@stdlib/random/base/gumbel/README.md index 8b7c9e696ba9..de7901247191 100644 --- a/lib/node_modules/@stdlib/random/base/gumbel/README.md +++ b/lib/node_modules/@stdlib/random/base/gumbel/README.md @@ -408,6 +408,7 @@ for ( i = 0; i < 100; i++ ) { - [`@stdlib/random/array/gumbel`][@stdlib/random/array/gumbel]: create an array containing pseudorandom numbers drawn from a Gumbel distribution. - [`@stdlib/random/iter/gumbel`][@stdlib/random/iter/gumbel]: create an iterator for generating pseudorandom numbers drawn from a Gumbel distribution. - [`@stdlib/random/streams/gumbel`][@stdlib/random/streams/gumbel]: create a readable stream for generating pseudorandom numbers drawn from a Gumbel distribution. +- [`@stdlib/random/gumbel`][@stdlib/random/gumbel]: generate pseudorandom numbers drawn from a Gumbel distribution. @@ -429,6 +430,8 @@ for ( i = 0; i < 100; i++ ) { [@stdlib/random/streams/gumbel]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/streams/gumbel +[@stdlib/random/gumbel]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/gumbel + diff --git a/lib/node_modules/@stdlib/random/betaprime/README.md b/lib/node_modules/@stdlib/random/betaprime/README.md index 27b5ef40763f..c42baa33720a 100644 --- a/lib/node_modules/@stdlib/random/betaprime/README.md +++ b/lib/node_modules/@stdlib/random/betaprime/README.md @@ -20,7 +20,7 @@ limitations under the License. # Beta Prime Random Numbers -> Generate pseudorandom numbers drawn from a [betaprime][@stdlib/random/base/betaprime] distribution. +> Generate pseudorandom numbers drawn from a [beta prime][@stdlib/random/base/betaprime] distribution.
@@ -32,7 +32,7 @@ var betaprime = require( '@stdlib/random/betaprime' ); #### betaprime( shape, alpha, beta\[, options] ) -Returns an [ndarray][@stdlib/ndarray/ctor] containing pseudorandom numbers drawn from a [betaprime][@stdlib/random/base/betaprime] distribution. +Returns an [ndarray][@stdlib/ndarray/ctor] containing pseudorandom numbers drawn from a [beta prime][@stdlib/random/base/betaprime] distribution. ```javascript var arr = betaprime( [ 3, 3 ], 2.0, 5.0 ); @@ -106,7 +106,7 @@ var dt = String( getDType( arr ) ); #### betaprime.assign( alpha, beta, out ) -Fills an [ndarray][@stdlib/ndarray/ctor] with pseudorandom numbers drawn from a [betaprime][@stdlib/random/base/betaprime] distribution. +Fills an [ndarray][@stdlib/ndarray/ctor] with pseudorandom numbers drawn from a [beta prime][@stdlib/random/base/betaprime] distribution. ```javascript var zeros = require( '@stdlib/ndarray/zeros' ); @@ -129,7 +129,7 @@ The method has the following parameters: #### betaprime.factory( \[options] ) -Returns a function for generating pseudorandom numbers drawn from a [betaprime][@stdlib/random/base/betaprime] distribution. +Returns a function for generating pseudorandom numbers drawn from a [beta prime][@stdlib/random/base/betaprime] distribution. ```javascript var getShape = require( '@stdlib/ndarray/shape' ); diff --git a/lib/node_modules/@stdlib/random/betaprime/docs/repl.txt b/lib/node_modules/@stdlib/random/betaprime/docs/repl.txt index a7ba74520173..96e8c41dd8d5 100644 --- a/lib/node_modules/@stdlib/random/betaprime/docs/repl.txt +++ b/lib/node_modules/@stdlib/random/betaprime/docs/repl.txt @@ -1,6 +1,6 @@ {{alias}}( shape, alpha, beta[, options] ) - Returns an ndarray containing pseudorandom numbers drawn from a betaprime + Returns an ndarray containing pseudorandom numbers drawn from a beta prime distribution. Parameters @@ -61,7 +61,7 @@ {{alias}}.assign( alpha, beta, out ) - Fills an ndarray with pseudorandom numbers drawn from a betaprime + Fills an ndarray with pseudorandom numbers drawn from a beta prime distribution. Parameters @@ -93,7 +93,7 @@ {{alias}}.factory( [options] ) Returns a function for generating pseudorandom numbers drawn from a - betaprime distribution. + beta prime distribution. The returned function has the same signature and accepts the same options as `{{alias}}` above. diff --git a/lib/node_modules/@stdlib/random/betaprime/docs/types/index.d.ts b/lib/node_modules/@stdlib/random/betaprime/docs/types/index.d.ts index 4d9aad424886..c5ccfe21c5c9 100644 --- a/lib/node_modules/@stdlib/random/betaprime/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/random/betaprime/docs/types/index.d.ts @@ -119,11 +119,11 @@ interface PRNG { } /** -* Interface for generating pseudorandom numbers drawn from a betaprime distribution. +* Interface for generating pseudorandom numbers drawn from a beta prime distribution. */ interface RandomFunction extends PRNG { /** - * Returns an ndarray containing pseudorandom numbers drawn from a betaprime distribution. + * Returns an ndarray containing pseudorandom numbers drawn from a beta prime distribution. * * @param shape - output shape * @param alpha - first shape parameter @@ -135,7 +135,7 @@ interface RandomFunction extends PRNG { , U extends typedndarray>( shape: Shape, alpha: number | T, beta: number | U, options?: Options ): RandomArray; /** - * Fills an ndarray with pseudorandom numbers drawn from a betaprime distribution. + * Fills an ndarray with pseudorandom numbers drawn from a beta prime distribution. * * @param alpha - first shape parameter * @param beta - second shape parameter @@ -147,11 +147,11 @@ interface RandomFunction extends PRNG { } /** -* Interface for generating pseudorandom numbers drawn from a betaprime distribution. +* Interface for generating pseudorandom numbers drawn from a beta prime distribution. */ interface Random extends PRNG { /** - * Returns an ndarray containing pseudorandom numbers drawn from a betaprime distribution. + * Returns an ndarray containing pseudorandom numbers drawn from a beta prime distribution. * * @param shape - output shape * @param alpha - first shape parameter @@ -167,7 +167,7 @@ interface Random extends PRNG { , U extends typedndarray>( shape: Shape, alpha: number | T, beta: number | U, options?: Options ): RandomArray; /** - * Fills an ndarray with pseudorandom numbers drawn from a betaprime distribution. + * Fills an ndarray with pseudorandom numbers drawn from a beta prime distribution. * * @param alpha - first shape parameter * @param beta - second shape parameter @@ -190,7 +190,7 @@ interface Random extends PRNG { assign, U extends typedndarray, V extends typedndarray>( alpha: number | T, beta: number | U, out: V ): V; /** - * Returns a function for creating ndarrays containing pseudorandom numbers drawn from a betaprime distribution. + * Returns a function for creating ndarrays containing pseudorandom numbers drawn from a beta prime distribution. * * @param options - function options * @throws must provide a valid state @@ -213,7 +213,7 @@ interface Random extends PRNG { } /** -* Generates pseudorandom numbers drawn from a betaprime distribution. +* Generates pseudorandom numbers drawn from a beta prime distribution. * * @param shape - output shape * @param alpha - first shape parameter diff --git a/lib/node_modules/@stdlib/random/betaprime/lib/factory.js b/lib/node_modules/@stdlib/random/betaprime/lib/factory.js index 5841d67ca124..c15733727640 100644 --- a/lib/node_modules/@stdlib/random/betaprime/lib/factory.js +++ b/lib/node_modules/@stdlib/random/betaprime/lib/factory.js @@ -38,7 +38,7 @@ var policies = { // MAIN // /** -* Returns a function for generating pseudorandom numbers drawn from a betaprime distribution. +* Returns a function for generating pseudorandom numbers drawn from a beta prime distribution. * * @name factory * @type {Function} diff --git a/lib/node_modules/@stdlib/random/betaprime/lib/index.js b/lib/node_modules/@stdlib/random/betaprime/lib/index.js index 350a8eebc28b..11d10f6616e3 100644 --- a/lib/node_modules/@stdlib/random/betaprime/lib/index.js +++ b/lib/node_modules/@stdlib/random/betaprime/lib/index.js @@ -19,7 +19,7 @@ 'use strict'; /** -* Generate pseudorandom numbers drawn from a betaprime distribution. +* Generate pseudorandom numbers drawn from a beta prime distribution. * * @module @stdlib/random/betaprime * diff --git a/lib/node_modules/@stdlib/random/betaprime/lib/main.js b/lib/node_modules/@stdlib/random/betaprime/lib/main.js index 42e8fd094c83..57a4e2a7fe5f 100644 --- a/lib/node_modules/@stdlib/random/betaprime/lib/main.js +++ b/lib/node_modules/@stdlib/random/betaprime/lib/main.js @@ -26,7 +26,7 @@ var factory = require( './factory.js' ); // MAIN // /** -* Returns pseudorandom numbers drawn from a betaprime distribution. +* Returns pseudorandom numbers drawn from a beta prime distribution. * * @name betaprime * @type {Function} diff --git a/lib/node_modules/@stdlib/random/betaprime/package.json b/lib/node_modules/@stdlib/random/betaprime/package.json index 7b935e4496e3..57eb3ddafe10 100644 --- a/lib/node_modules/@stdlib/random/betaprime/package.json +++ b/lib/node_modules/@stdlib/random/betaprime/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/random/betaprime", "version": "0.0.0", - "description": "Generate pseudorandom numbers drawn from a betaprime distribution.", + "description": "Generate pseudorandom numbers drawn from a beta prime distribution.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/random/docs/types/index.d.ts b/lib/node_modules/@stdlib/random/docs/types/index.d.ts index a029d5421c4d..fc61485ea4cc 100644 --- a/lib/node_modules/@stdlib/random/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/random/docs/types/index.d.ts @@ -178,7 +178,7 @@ interface Namespace { beta: typeof beta; /** - * Generates pseudorandom numbers drawn from a betaprime distribution. + * Generates pseudorandom numbers drawn from a beta prime distribution. * * @param shape - output shape * @param alpha - first shape parameter diff --git a/lib/node_modules/@stdlib/random/scripts/scaffolds/binary/scripts/data/betaprime.json b/lib/node_modules/@stdlib/random/scripts/scaffolds/binary/scripts/data/betaprime.json index 6a2ba2056c93..794d38c1f3a4 100644 --- a/lib/node_modules/@stdlib/random/scripts/scaffolds/binary/scripts/data/betaprime.json +++ b/lib/node_modules/@stdlib/random/scripts/scaffolds/binary/scripts/data/betaprime.json @@ -27,16 +27,16 @@ "default_dtype": "float64", "default_dtype_kind": "real_floating_point", - "from_desc": "a betaprime distribution", - "readme_from_desc": "a [betaprime][@stdlib/random/base/betaprime] distribution", + "from_desc": "a beta prime distribution", + "readme_from_desc": "a [beta prime][@stdlib/random/base/betaprime] distribution", "readme_heading": "Beta Prime Random Numbers", "readme_dtype_kind_desc": "a real-valued floating-point", "readme_dtype_kind_pkg": "stdlib/ndarray/dtypes", - "repl_text_main_desc": "Returns an ndarray containing pseudorandom numbers drawn from a betaprime distribution.", - "repl_text_assign_desc": "Fills an ndarray with pseudorandom numbers drawn from a betaprime distribution.", - "repl_text_factory_desc": "Returns a function for generating pseudorandom numbers drawn from a betaprime distribution.", + "repl_text_main_desc": "Returns an ndarray containing pseudorandom numbers drawn from a beta prime distribution.", + "repl_text_assign_desc": "Fills an ndarray with pseudorandom numbers drawn from a beta prime distribution.", + "repl_text_factory_desc": "Returns a function for generating pseudorandom numbers drawn from a beta prime distribution.", "repl_text_param_1_desc": "First shape parameter. If an ndarray, must be broadcast compatible with the specified array shape.", "repl_text_param_2_desc": "Second shape parameter. If an ndarray, must be broadcast compatible with the specified array shape.", diff --git a/lib/node_modules/@stdlib/random/strided/uniform/README.md b/lib/node_modules/@stdlib/random/strided/uniform/README.md index 8e8fb60bd43d..21e73832540f 100644 --- a/lib/node_modules/@stdlib/random/strided/uniform/README.md +++ b/lib/node_modules/@stdlib/random/strided/uniform/README.md @@ -211,6 +211,7 @@ logEach( 'x1[%d] = %.2f; x2[%d] = %.2f', idx, x1, idx, x2 ); ## See Also +- [`@stdlib/random/uniform`][@stdlib/random/uniform]: generate pseudorandom numbers drawn from a continuous uniform distribution. - [`@stdlib/random/base/uniform`][@stdlib/random/base/uniform]: uniformly distributed pseudorandom numbers. - [`@stdlib/random/array/uniform`][@stdlib/random/array/uniform]: create an array containing pseudorandom numbers drawn from a continuous uniform distribution. - [`@stdlib/random/strided/discrete-uniform`][@stdlib/random/strided/discrete-uniform]: fill a strided array with pseudorandom numbers drawn from a discrete uniform distribution. @@ -231,6 +232,8 @@ logEach( 'x1[%d] = %.2f; x2[%d] = %.2f', idx, x1, idx, x2 ); +[@stdlib/random/uniform]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/uniform + [@stdlib/random/array/uniform]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/array/uniform [@stdlib/random/strided/discrete-uniform]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/strided/discrete-uniform diff --git a/lib/node_modules/@stdlib/regexp/basename/lib/index.js b/lib/node_modules/@stdlib/regexp/basename/lib/index.js index 1d901dcf1e2d..5d3a92d1b545 100644 --- a/lib/node_modules/@stdlib/regexp/basename/lib/index.js +++ b/lib/node_modules/@stdlib/regexp/basename/lib/index.js @@ -29,7 +29,7 @@ * * // On a POSIX platform... * var base = RE_BASENAME.exec( '/foo/bar/index.js' )[ 1 ]; -* // returns 'index.js' +* // e.g., returns 'index.js' * * @example * var reBasename = require( '@stdlib/regexp/basename' ); @@ -37,7 +37,7 @@ * * // On a Windows platform... * var base = RE_BASENAME.exec( 'C:\\foo\\bar\\index.js' )[ 1 ]; -* // returns 'index.js' +* // e.g., returns 'index.js' */ // MODULES // diff --git a/lib/node_modules/@stdlib/regexp/extended-length-path/package.json b/lib/node_modules/@stdlib/regexp/extended-length-path/package.json index 53eb120d9c18..21a329ce66de 100644 --- a/lib/node_modules/@stdlib/regexp/extended-length-path/package.json +++ b/lib/node_modules/@stdlib/regexp/extended-length-path/package.json @@ -57,6 +57,7 @@ "expression", "path", "test", + "match", "file", "filename", "windows", diff --git a/lib/node_modules/@stdlib/regexp/regexp/package.json b/lib/node_modules/@stdlib/regexp/regexp/package.json index 4e3e7a2d2746..9c1b70456a9d 100644 --- a/lib/node_modules/@stdlib/regexp/regexp/package.json +++ b/lib/node_modules/@stdlib/regexp/regexp/package.json @@ -57,6 +57,7 @@ "expression", "string", "pattern", - "flags" + "flags", + "match" ] } diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv index e3d7d8ac997e..6de139fb3f01 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv @@ -1780,8 +1780,8 @@ base.strided.dmeanvarpn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar ou base.strided.dmeanvarpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n" base.strided.dmeanwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanwd( 3, x1, 2 )\n" base.strided.dmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n" -base.strided.dmediansorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n" -base.strided.dmediansorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n" +base.strided.dmedianSorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmedianSorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmedianSorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmedianSorted( 3, x1, 2 )\n" +base.strided.dmedianSorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmedianSorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmedianSorted.ndarray( 3, x, 2, 1 )\n" base.strided.dmidrange,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n" base.strided.dmidrange.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n" base.strided.dmin,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n" @@ -3485,6 +3485,15 @@ Int32Array.prototype.toString,"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toS Int32Array.prototype.values,"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n" Int32Matrix,"var arr = Int32Matrix()\nvar arr = Int32Matrix( [ 2, 2 ] )\nvar arr = Int32Matrix( 2, 2 )\nvar v = [ [ 1, 2 ], [ 3, 4 ] ];\nvar arr = Int32Matrix( v )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Matrix( buf, 0, [ 8, 1 ] )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Matrix( buf, 0, 8, 1 )\n" Int32Vector,"var arr = Int32Vector()\nvar arr = Int32Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Int32Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Vector( buf, 0, 4 )\nvar len = numel( arr )\n" +Int64,"var x = new Int64( 5 )\nx.toString()\n" +Int64.name,"var str = Int64.name\n" +Int64.from,"var v = Int64.from( [ 1234, 5678 ] )\n" +Int64.of,"var v = Int64.of( 1234, 5678 )\n" +Int64.BYTES_PER_ELEMENT,"var s = Int64.BYTES_PER_ELEMENT\n" +Int64.prototype.BYTES_PER_ELEMENT,"var x = new Int64( 5 )\nvar s = x.BYTES_PER_ELEMENT\n" +Int64.prototype.byteLength,"var x = new Int64( 5 )\nvar s = x.byteLength\n" +Int64.prototype.hi,"var x = Int64.from( [ 1234, 5678 ] )\nvar w = x.hi\n" +Int64.prototype.lo,"var x = Int64.from( [ 1234, 5678 ] )\nvar w = x.lo\n" IS_BIG_ENDIAN,"IS_BIG_ENDIAN\n" IS_BROWSER,"IS_BROWSER\n" IS_DARWIN,"IS_DARWIN\n" diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json index 793661c0d504..f23121ff18d8 100644 --- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json +++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json @@ -1 +1 @@ -{"abs":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar y = abs( x )\n","abs.assign":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar sh = ndarrayShape( x );\nvar y = ndzeros( sh );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosdf":"var y = base.acosdf( 0.0 )\ny = base.acosdf( FLOAT32_PI / 6.0 )\ny = base.acosdf( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotdf":"var y = base.acotdf( 0.0 )\ny = base.acotdf( FLOAT32_PI/6.0 )\ny = base.acotdf( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( 1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.azeros":"var out = base.azeros( 3 )\n","base.azeros2d":"var out = base.azeros2d( [ 1, 3 ] )\n","base.azeros3d":"var out = base.azeros3d( [ 1, 1, 3 ] )\n","base.azeros4d":"var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n","base.azeros5d":"var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.cadd.assign":"var out = new Float64Array( 2 );\nbase.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cadd.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.caddf.assign":"var out = new Float32Array( 2 );\nbase.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.caddf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.cdiv.assign":"var out = new Float64Array( 2 );\nbase.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n","base.cdiv.strided":"var z1 = new Float64Array( [ -13.0, -1.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n","base.cinvf":"var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmul.assign":"var out = new Float64Array( 2 );\nbase.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmul.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cmulf.assign":"var out = new Float32Array( 2 );\nbase.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmulf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dotcase":"var out = base.dotcase( 'Hello World!' )\nout = base.dotcase( 'I am a tiny little teapot' )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 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base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 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2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.cdf.factory":"var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 7.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 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base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 0.4 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = 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base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n","base.dists.levy.cdf":"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.cdf.factory":"var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.levy.entropy":"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n","base.dists.levy.Levy":"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n","base.dists.levy.logcdf":"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logcdf.factory":"var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.levy.logpdf":"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logpdf.factory":"var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 11.0 )\n","base.dists.levy.mean":"var y = base.dists.levy.mean( 0.0, 1.0 )\ny = base.dists.levy.mean( 4.0, 3.0 )\ny = base.dists.levy.mean( NaN, 1.0 )\ny = base.dists.levy.mean( 0.0, NaN )\ny = base.dists.levy.mean( 0.0, 0.0 )\n","base.dists.levy.median":"var y = base.dists.levy.median( 0.0, 1.0 )\ny = base.dists.levy.median( 4.0, 3.0 )\ny = base.dists.levy.median( NaN, 1.0 )\ny = base.dists.levy.median( 0.0, NaN )\ny = base.dists.levy.median( 0.0, 0.0 )\n","base.dists.levy.mode":"var y = base.dists.levy.mode( 0.0, 1.0 )\ny = base.dists.levy.mode( 4.0, 3.0 )\ny = base.dists.levy.mode( NaN, 1.0 )\ny = base.dists.levy.mode( 0.0, NaN )\ny = base.dists.levy.mode( 0.0, 0.0 )\n","base.dists.levy.pdf":"var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.pdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.pdf( 0.0, 0.0, NaN )\ny = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.pdf.factory":"var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 11.0 )\n","base.dists.levy.quantile":"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.levy.quantile.factory":"var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 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base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n ~1.791\ny = myQuantile( 0.8 )\n ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toLocaleString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toLocaleString()\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar y = base.ndzerosLike( x )\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeMultiSlice":"var s1 = new MultiSlice( 1, 3, null );\nvar s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\nvar v = s2.data[ 0 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 1 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 2 ];\nv.start\nv.stop\nv.step\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( 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= base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nvar state = base.random.cauchy.state\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nbase.random.cauchy.state = state;\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\n","base.random.cauchy.stateLength":"var len = base.random.cauchy.stateLength;\n","base.random.cauchy.byteLength":"var sz = base.random.cauchy.byteLength;\n","base.random.cauchy.toJSON":"var o = base.random.cauchy.toJSON()\n","base.random.chi":"var r = base.random.chi( 2 );\n","base.random.chi.factory":"var rand = base.random.chi.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chi.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chi.NAME":"var str = base.random.chi.NAME\n","base.random.chi.PRNG":"var prng = base.random.chi.PRNG;\n","base.random.chi.seed":"var seed = base.random.chi.seed;\n","base.random.chi.seedLength":"var len = base.random.chi.seedLength;\n","base.random.chi.state":"var r = base.random.chi( 2 )\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nvar state = base.random.chi.state\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nbase.random.chi.state = state;\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\n","base.random.chi.stateLength":"var len = base.random.chi.stateLength;\n","base.random.chi.byteLength":"var sz = base.random.chi.byteLength;\n","base.random.chi.toJSON":"var o = base.random.chi.toJSON()\n","base.random.chisquare":"var r = base.random.chisquare( 2 );\n","base.random.chisquare.factory":"var rand = base.random.chisquare.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chisquare.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chisquare.NAME":"var str = base.random.chisquare.NAME\n","base.random.chisquare.PRNG":"var prng = base.random.chisquare.PRNG;\n","base.random.chisquare.seed":"var seed = base.random.chisquare.seed;\n","base.random.chisquare.seedLength":"var len = base.random.chisquare.seedLength;\n","base.random.chisquare.state":"var r = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nvar state = base.random.chisquare.state\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\nbase.random.chisquare.state = state;\nr = base.random.chisquare( 2 )\nr = base.random.chisquare( 2 )\n","base.random.chisquare.stateLength":"var len = base.random.chisquare.stateLength;\n","base.random.chisquare.byteLength":"var sz = base.random.chisquare.byteLength;\n","base.random.chisquare.toJSON":"var o = base.random.chisquare.toJSON()\n","base.random.cosine":"var r = base.random.cosine( 2.0, 5.0 );\n","base.random.cosine.factory":"var rand = base.random.cosine.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.cosine.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.cosine.NAME":"var str = base.random.cosine.NAME\n","base.random.cosine.PRNG":"var prng = base.random.cosine.PRNG;\n","base.random.cosine.seed":"var seed = base.random.cosine.seed;\n","base.random.cosine.seedLength":"var len = base.random.cosine.seedLength;\n","base.random.cosine.state":"var r = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nvar state = base.random.cosine.state\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\nbase.random.cosine.state = state;\nr = base.random.cosine( 2.0, 5.0 )\nr = base.random.cosine( 2.0, 5.0 )\n","base.random.cosine.stateLength":"var len = base.random.cosine.stateLength;\n","base.random.cosine.byteLength":"var sz = base.random.cosine.byteLength;\n","base.random.cosine.toJSON":"var o = base.random.cosine.toJSON()\n","base.random.discreteUniform":"var r = base.random.discreteUniform( 2, 50 );\n","base.random.discreteUniform.factory":"var rand = base.random.discreteUniform.factory();\nvar r = rand( 0, 10 );\nr = rand( -20, 20 );\nrand = base.random.discreteUniform.factory( 0, 10 );\nr = rand();\nr = rand();\n","base.random.discreteUniform.NAME":"var str = base.random.discreteUniform.NAME\n","base.random.discreteUniform.PRNG":"var prng = base.random.discreteUniform.PRNG;\n","base.random.discreteUniform.seed":"var seed = base.random.discreteUniform.seed;\n","base.random.discreteUniform.seedLength":"var len = base.random.discreteUniform.seedLength;\n","base.random.discreteUniform.state":"var r = base.random.discreteUniform( 2, 50 )\nr = base.random.discreteUniform( 2, 50 )\nr = base.random.discreteUniform( 2, 50 )\nvar state = base.random.discreteUniform.state\nr = base.random.discreteUniform( 2, 50 )\nr = base.random.discreteUniform( 2, 50 )\nbase.random.discreteUniform.state = state;\nr = base.random.discreteUniform( 2, 50 )\nr = base.random.discreteUniform( 2, 50 )\n","base.random.discreteUniform.stateLength":"var len = base.random.discreteUniform.stateLength;\n","base.random.discreteUniform.byteLength":"var sz = base.random.discreteUniform.byteLength;\n","base.random.discreteUniform.toJSON":"var o = base.random.discreteUniform.toJSON()\n","base.random.erlang":"var r = base.random.erlang( 2, 5.0 );\n","base.random.erlang.factory":"var rand = base.random.erlang.factory();\nvar r = rand( 2, 1.0 );\nr = rand( 4, 3.14 );\nrand = base.random.erlang.factory( 2, 1.5 );\nr = rand();\nr = rand();\n","base.random.erlang.NAME":"var str = base.random.erlang.NAME\n","base.random.erlang.PRNG":"var prng = base.random.erlang.PRNG;\n","base.random.erlang.seed":"var seed = base.random.erlang.seed;\n","base.random.erlang.seedLength":"var len = base.random.erlang.seedLength;\n","base.random.erlang.state":"var r = base.random.erlang( 2, 5.0 )\nr = base.random.erlang( 2, 5.0 )\nr = base.random.erlang( 2, 5.0 )\nvar state = base.random.erlang.state\nr = base.random.erlang( 2, 5.0 )\nr = base.random.erlang( 2, 5.0 )\nbase.random.erlang.state = state;\nr = base.random.erlang( 2, 5.0 )\nr = base.random.erlang( 2, 5.0 )\n","base.random.erlang.stateLength":"var len = base.random.erlang.stateLength;\n","base.random.erlang.byteLength":"var sz = base.random.erlang.byteLength;\n","base.random.erlang.toJSON":"var o = base.random.erlang.toJSON()\n","base.random.exponential":"var r = base.random.exponential( 7.9 );\n","base.random.exponential.factory":"var rand = base.random.exponential.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.exponential.factory( 10.0 );\nr = rand();\nr = rand();\n","base.random.exponential.NAME":"var str = base.random.exponential.NAME\n","base.random.exponential.PRNG":"var prng = 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base.random.randi.factory({ 'name': 'minstd' });\nr = randi();\nr = randi();\n","base.random.randi.NAME":"var str = base.random.randi.NAME\n","base.random.randi.PRNG":"var prng = base.random.randi.PRNG;\n","base.random.randi.MIN":"var v = base.random.randi.MIN;\n","base.random.randi.MAX":"var v = base.random.randi.MAX;\n","base.random.randi.seed":"var seed = base.random.randi.seed;\n","base.random.randi.seedLength":"var len = base.random.randi.seedLength;\n","base.random.randi.state":"var r = base.random.randi()\nr = base.random.randi()\nr = base.random.randi()\nvar state = base.random.randi.state;\nr = base.random.randi()\nr = base.random.randi()\nbase.random.randi.state = state;\nr = base.random.randi()\nr = base.random.randi()\n","base.random.randi.stateLength":"var len = base.random.randi.stateLength;\n","base.random.randi.byteLength":"var sz = base.random.randi.byteLength;\n","base.random.randi.toJSON":"var o = base.random.randi.toJSON()\n","base.random.randn":"var r = base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = 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)\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nvar state = base.random.triangular.state\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 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5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = ndarrayShape( x )\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\n","base.sincos.assign":"var out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 )\ny0\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nx\ny\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nx0\ny0\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nx\ny\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabsSorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabsSorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabsSorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabsSorted( 3, x1, 2 )\n","base.strided.dmaxabsSorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabsSorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabsSorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxSorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxSorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxSorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxSorted( 3, x1, 2 )\n","base.strided.dmaxSorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxSorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxSorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmean( 3, x1, 2 )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmean.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn( 3, x1, 2 )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn2( 3, x1, 2 )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanli( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanli( 3, x1, 2 )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanli.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanlipw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanlipw( 3, x1, 2 )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanors( 3, x1, 2 )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpn( 3, x1, 2 )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpw( 3, x1, 2 )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanwd( 3, x1, 2 )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasumors( 4, x1, 2 )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmean( 4, x1,2 )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanors( 4, x1, 2 )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpn( 4, x1, 2 )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpw( 4, x1, 2 )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 4, x1, 2 )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnanstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdev( 3, 1, x1, 2 )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevch( 4, 1, x1, 2 )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevpn( 4, 1, x1, 2 )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevtk( 4, 1, x1, 2 )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevwd( 4, 1, x1, 2 )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevyc( 4, 1, x1, 2 )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariance( 4, 1, x1, 2 )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancech( 4, 1, x1, 2 )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancepn( 4, 1, x1, 2 )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancetk( 4, 1, x1, 2 )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancewd( 4, 1, x1, 2 )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvarianceyc( 4, 1, x1, 2 )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsem( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsem( 3, 1, x1, 2 )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemch( 3, 1, x1, 2 )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsempn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsempn( 3, 1, x1, 2 )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemtk( 3, 1, x1, 2 )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemwd( 3, 1, x1, 2 )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemyc( 3, 1, x1, 2 )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmean( 3, x1, 2 )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmean.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanors( 3, x1, 2 )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpn( 3, x1, 2 )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpw( 3, x1, 2 )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanwd( 3, x1, 2 )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmean( 4, x1, 2 )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanors( 4, x1, 2 )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanpn( 4, x1, 2 )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanwd( 4, x1, 2 )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsortins( 2, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdev( 3, 1, x1, 2 )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevch( 3, 1, x1, 2 )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevpn( 3, 1, x1, 2 )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevtk( 3, 1, x1, 2 )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevwd( 3, 1, x1, 2 )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevyc( 3, 1.0, x1, 2 )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariance( 3, 1, x1, 2 )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariancepn( 3, 1, x1, 2 )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariance( 3, 1, x1, 2 )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancech( 3, 1, x1, 2 )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancepn( 3, 1, x1, 2 )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancetk( 3, 1, x1, 2 )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancewd( 3, 1, x1, 2 )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarianceyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarianceyc( 3, 1, x1, 2 )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( 4, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsum( 3, 5.0, x1, 2 )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumors( 3, 5.0, x1, 2 )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.gasumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gasumpw( 3, x1, 2 )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.gasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( 3, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfillBy( 3, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansum( 4, x1, 2 )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansum.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn( 4, x1, 2 )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn2( 4, x1, 2 )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumors( 4, x1, 2 )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumpw( 4, x1, 2 )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.grev( 3, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.grev.ndarray( 3, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortins( 2, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortsh( 2, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsum( 3, x1, 2 )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsum.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn( 3, x1, 2 )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn2( 3, x1, 2 )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumors( 3, x1, 2 )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumors.ndarray( 3, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumpw( 3, x1, 2 )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.max( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.max( 3, x1, 2 )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.max.ndarray( 3, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxabs( 3, x1, 2 )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.maxabs.ndarray( 3, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxBy( 3, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxsorted( 3, x1, 2 )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.maxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mean( 3, x1, 2 )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.mean.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn( 3, x1, 2 )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn2( 3, x1, 2 )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanors( 3, x1, 2 )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( 3, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpn( 3, x1, 2 )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpn.ndarray( 3, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpw( 3, x1, 2 )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpw.ndarray( 3, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanwd( 3, x1, 2 )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanwd.ndarray( 3, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mediansorted( 3, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.mediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.min( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.min( 3, x1, 2 )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.min.ndarray( 3, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minabs( 3, x1, 2 )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.minabs.ndarray( 3, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nbase.strided.minBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minBy( 3, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minsorted( 3, x1, 2 )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.minsorted.ndarray( 3, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmax( 3, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmin( 3, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskrange( 3, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmax( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmax( 4, x1, 2 )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmax.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxabs( 4, x1, 2 )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.nanmaxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxBy( 3, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmean( 4, x1, 2 )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmean.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanors( 4, x1, 2 )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanpn( 4, x1, 2 )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanwd( 4, x1, 2 )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmin( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmin( 4, x1, 2 )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmin.ndarray( 4, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanminabs( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanminabs( 4, x1, 2 )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanminabs.ndarray( 4, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nbase.strided.nanminBy( 4, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanminBy( 3, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmax( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmin( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( 5, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanrange( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanrange( 4, x1, 2 )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanrange.ndarray( 4, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { 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x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdev( 4, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevch( 4, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevpn( 4, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevtk( 4, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevwd( 4, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevyc( 4, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariance( 4, 1, x1, 2 )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancech( 4, 1, x1, 2 )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancepn( 3, 1, x1, 2 )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancetk( 4, 1, x1, 2 )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancewd( 4, 1, x1, 2 )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( 4, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvarianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.range( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.range( 3, x1, 2 )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.range.ndarray( 3, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.rangeBy( 3, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumors( 3, 5.0, x1, 2 )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmean( 3, x1, 2 )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmean.ndarray( 3, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmeanors( 3, x1, 2 )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnanmeanors( 3, x1, 2 )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansum( 4, x1, 2 )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssum( 3, x1, 2 )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssumpw( 3, x1, 2 )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smean( 3, x1, 2 )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smean.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn( 3, x1, 2 )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn2( 3, x1, 2 )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanli( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanli( 3, x1, 2 )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanli.ndarray( 3, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanlipw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanlipw( 3, x1, 2 )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanors( 3, x1, 2 )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanors.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpn( 3, x1, 2 )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpw( 3, x1, 2 )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanwd( 3, x1, 2 )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmean( 4, x1, 2 )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmean.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanors( 4, x1, 2 )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanpn( 4, x1, 2 )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanwd( 4, x1, 2 )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn( 4, x1, 2 )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn2( 4, x1, 2 )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdev( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdev( 3, 1, x1, 2 )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevch( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevch( 3, 1, x1, 2 )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevpn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevpn( 3, 1, x1, 2 )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevtk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevtk( 3, 1, x1, 2 )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevwd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevwd( 3, 1, x1, 2 )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevyc( 3, 1, x1, 2 )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdev( 3, 1, x1, 2 )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevch( 3, 1, x1, 2 )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevpn( 3, 1, x1, 2 )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevtk( 3, 1, x1, 2 )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevwd( 3, 1, x1, 2 )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevyc( 3, 1, x1, 2 )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariance( 3, 1, x1, 2 )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancech( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancech( 3, 1, x1, 2 )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancepn( 3, 1, x1, 2 )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancetk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancetk( 3, 1, x1, 2 )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancewd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancewd( 3, 1, x1, 2 )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svarianceyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svarianceyc( 3, 1, x1, 2 )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variance( 3, 1, x1, 2 )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancech( 3, 1, x1, 2 )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancepn( 3, 1, x1, 2 )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancetk( 3, 1, x1, 2 )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancewd( 3, 1, x1, 2 )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.varianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.varianceyc( 3, 1.0, x1, 2 )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar y = base.transpose( x, false )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","BooleanVector":"var arr = BooleanVector()\nvar arr = BooleanVector( 5 )\nvar len = numel( arr )\nvar v = [ true, false, true ];\nvar arr = BooleanVector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = BooleanVector( buf, 0, 4 )\nvar len = numel( arr )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.name":"var str = Complex64.name\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nz = out.get( 1 )\nz = out.get( 2 )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nz = out.get( 1 )\nz = out.get( 2 )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\n","Complex64Matrix":"var arr = Complex64Matrix()\nvar arr = Complex64Matrix( [ 2, 2 ] )\nvar arr = Complex64Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\nvar arr = Complex64Matrix( v )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex64Matrix( buf, 0, [ 8, 1 ] )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex64Matrix( buf, 0, 8, 1 )\n","Complex64Vector":"var arr = Complex64Vector()\nvar arr = Complex64Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar arr = Complex64Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Complex64Vector( buf, 0, 2 )\nvar len = numel( arr )\n","Complex128.name":"var str = Complex128.name\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n","Complex128Matrix":"var arr = Complex128Matrix()\nvar arr = Complex128Matrix( [ 2, 2 ] )\nvar arr = Complex128Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\nvar arr = Complex128Matrix( v )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex128Matrix( buf, 0, [ 4, 1 ] )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex128Matrix( buf, 0, 4, 1 )\n","Complex128Vector":"var arr = Complex128Vector()\nvar arr = Complex128Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar arr = Complex128Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex128Vector( buf, 0, 2 )\nvar len = numel( arr )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataType":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.name":"DataType.name\n","DataType.prototype.alignment":"var dt = new DataType( 'float64' );\ndt.alignment\n","DataType.prototype.byteLength":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.prototype.byteOrder":"var dt = new DataType( 'float64' );\ndt.byteOrder\n","DataType.prototype.char":"var dt = new DataType( 'float64' );\ndt.char\n","DataType.prototype.description":"var dt = new DataType( 'float64' );\ndt.description\n","DataType.prototype.enum":"var dt = new DataType( 'float64' );\ndt.enum\n","DataType.prototype.value":"var dt = new DataType( 'float64' );\ndt.value\n","DataType.prototype.toJSON":"var dt = new DataType( 'float64' );\ndt.toJSON()\n","DataType.prototype.toString":"var dt = new DataType( 'float64' );\ndt.toString()\n","DataType.prototype.valueOf":"var dt = new DataType( 'float64' );\ndt.valueOf()\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj1 = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj1, 'a.b.c', 'beep' )\nvar obj2 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\nobj2\nvar obj3 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\nobj3\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","falses":"var arr = falses( [ 2, 2 ] )\n","falsesLike":"var opts = { 'dtype': 'generic' };\nvar x = ndempty( [ 2, 2 ], opts )\nvar y = falsesLike( x )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","Float16Array":"var arr = new Float16Array()\nvar arr = new Float16Array( 5 )\nvar len = arr.length\nvar buf = new Float64Array( [ 0.5, 0.5, 0.5 ] )\nvar arr = new Float16Array( buf )\nvar len = arr.length\nvar arr = new Float16Array( [ 0.5, 0.5, 0.5 ] )\nvar len = arr.length\nvar buf = new ArrayBuffer( 8 );\nvar arr1 = new Float16Array( buf )\nvar len = arr1.length\nvar arr2 = new Float16Array( buf, 2 )\nlen = arr2.length\nvar arr3 = new Float16Array( buf, 2, 2 )\nlen = arr3.length\n","Float16Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Float16Array.from( [ 1.0, -1.0 ], clbkFcn )\nvar len = arr.length\nvar v = arr[ 0 ]\nv = arr[ 1 ]\n","Float16Array.of":"var arr = Float16Array.of( 1.0, -1.0 )\nvar len = arr.length\nvar v = arr[ 0 ]\nv = arr[ 1 ]\n","Float16Array.BYTES_PER_ELEMENT":"var nbytes = Float16Array.BYTES_PER_ELEMENT\n","Float16Array.name":"var str = Float16Array.name\n","Float16Array.prototype.buffer":"var arr = new Float16Array( 2 )\nvar buf = arr.buffer\n","Float16Array.prototype.byteLength":"var arr = new Float16Array( 5 )\nvar nbytes = arr.byteLength\n","Float16Array.prototype.byteOffset":"var arr = new Float16Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 20 );\narr = new Float16Array( buf, 10 )\noffset = arr.byteOffset\n","Float16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float16Array( 5 )\narr.BYTES_PER_ELEMENT\n","Float16Array.prototype.length":"var arr = new Float16Array( 5 )\nvar len = arr.length\n","Float16Array.prototype.at":"var arr = new Float16Array( [ 10.0, 20.0, 30.0 ] )\nvar v = arr.at( 0 )\nv = arr.at( -1 )\n","Float16Array.prototype.copyWithin":"var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\narr.copyWithin( 0, 3 )\nvar v = arr[ 0 ]\nv = arr[ 1 ]\n","Float16Array.prototype.entries":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Float16Array.prototype.every":"function predicate( v ) { return ( v > 0.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0 ] )\nvar bool = arr.every( predicate )\n","Float16Array.prototype.fill":"var arr = new Float16Array( 3 )\narr.fill( 2.0 );\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.filter":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out[ 0 ]\nv = out[ 1 ]\n","Float16Array.prototype.find":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar v = arr.find( predicate )\n","Float16Array.prototype.findIndex":"function predicate( v ) { return ( v > 2.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Float16Array.prototype.findLast":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar v = arr.findLast( predicate )\n","Float16Array.prototype.findLastIndex":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Float16Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\narr.forEach( clbk );\nstr\n","Float16Array.prototype.includes":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar bool = arr.includes( 3.0 )\nbool = arr.includes( 3.0, 3 )\n","Float16Array.prototype.indexOf":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( 2.0, 2 )\n","Float16Array.prototype.join":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","Float16Array.prototype.keys":"var arr = new Float16Array( [ 1.0, 2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Float16Array.prototype.lastIndexOf":"var arr = new Float16Array( [ 1.0, 2.0, 3.0, 1.0 ] )\nvar idx = arr.lastIndexOf( 1.0 )\nidx = arr.lastIndexOf( 1.0, 2 )\n","Float16Array.prototype.map":"function clbk( v ) { return v * 2.0; };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.map( clbk )\nvar v = out[ 0 ]\nv = out[ 1 ]\nv = out[ 2 ]\n","Float16Array.prototype.reduce":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nfunction reducerFn( acc, v ) { return acc + v; };\nvar v = arr.reduce( reducerFn, 0.0 )\n","Float16Array.prototype.reduceRight":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nfunction reducerFn( acc, v ) { return acc + v; };\nvar v = arr.reduceRight( reducerFn, 0.0 )\n","Float16Array.prototype.reverse":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\narr.reverse();\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.set":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\narr.set( [ 4.0, 5.0 ], 1 );\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.slice":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out[ 0 ]\nv = out[ 1 ]\n","Float16Array.prototype.some":"function predicate( v ) { return ( v > 2.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar bool = arr.some( predicate )\n","Float16Array.prototype.sort":"function compare( a, b ) { return a - b; };\nvar arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\narr.sort( compare );\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.subarray":"var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out[ 0 ]\nv = out[ 1 ]\n","Float16Array.prototype.toLocaleString":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar str = arr.toLocaleString()\n","Float16Array.prototype.toReversed":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.toReversed()\nvar v = out[ 0 ]\nv = out[ 1 ]\nv = out[ 2 ]\n","Float16Array.prototype.toSorted":"function compare( a, b ) { return a - b; };\nvar arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\nvar out = arr.toSorted( compare );\nvar v = out[ 0 ]\nv = out[ 1 ]\nv = out[ 2 ]\n","Float16Array.prototype.toString":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar str = arr.toString()\n","Float16Array.prototype.values":"var arr = new Float16Array( [ 1.0, 2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Float16Array.prototype.with":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.with( 1, 4.0 )\nvar v = out[ 1 ]\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Float32Matrix":"var arr = Float32Matrix()\nvar arr = Float32Matrix( [ 2, 2 ] )\nvar arr = Float32Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\nvar arr = Float32Matrix( v )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float32Matrix( buf, 0, [ 8, 1 ] )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float32Matrix( buf, 0, 4, 1 )\n","Float32Vector":"var arr = Float32Vector()\nvar arr = Float32Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0 ];\nvar arr = Float32Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float32Vector( buf, 0, 4 )\nvar len = numel( arr )\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Float64Matrix":"var arr = Float64Matrix()\nvar arr = Float64Matrix( [ 2, 2 ] )\nvar arr = Float64Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\nvar arr = Float64Matrix( v )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float64Matrix( buf, 0, [ 4, 1 ] )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float64Matrix( buf, 0, 4, 1 )\n","Float64Vector":"var arr = Float64Vector()\nvar arr = Float64Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0 ];\nvar arr = Float64Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float64Vector( buf, 0, 2 )\nvar len = numel( arr )\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServerFactory":"var boot = httpServerFactory()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\nboot = httpServerFactory( onRequest )\nvar opts = { 'port': 7331 };\nboot = httpServerFactory( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Int8Vector":"var arr = Int8Vector()\nvar arr = Int8Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Int8Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int8Vector( buf, 0, 4 )\nvar len = numel( arr )\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Int16Vector":"var arr = Int16Vector()\nvar arr = Int16Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Int16Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int16Vector( buf, 0, 4 )\nvar len = numel( arr )\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Int32Matrix":"var arr = Int32Matrix()\nvar arr = Int32Matrix( [ 2, 2 ] )\nvar arr = Int32Matrix( 2, 2 )\nvar v = [ [ 1, 2 ], [ 3, 4 ] ];\nvar arr = Int32Matrix( v )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Matrix( buf, 0, [ 8, 1 ] )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Matrix( buf, 0, 8, 1 )\n","Int32Vector":"var arr = Int32Vector()\nvar arr = Int32Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Int32Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Vector( buf, 0, 4 )\nvar len = numel( arr )\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var opts = { 'dtype': 'complex128' };\nvar M = ndzeros( [ 2, 2 ], opts );\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var opts = { 'dtype': 'complex128' };\nvar M = ndzeros( [ 2, 2 ], opts );\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var opts = { 'dtype': 'complex128' };\nvar M = ndzeros( [ 4 ], opts );\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isEqualDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isEqualDateObject( d1, d2 )\nd1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nd2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nbool = isEqualDateObject( d1, d2 )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isStruct":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStruct( new S() )\nbool = isStruct( [ 1, 2, 3, 4 ] )\nbool = isStruct( 3.14 )\nbool = isStruct( {} )\n","isStructConstructorLike":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStructConstructorLike( S )\nbool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\nbool = isStructConstructorLike( 3.14 )\nbool = isStructConstructorLike( {} )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","ltrimN":"var out = ltrimN( ' abc ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","matrix":"var arr = matrix()\nvar sh = ndarrayShape( arr )\narr = matrix( 'float32' )\nvar arr = matrix( [ 2, 2 ] )\narr = matrix( [ 2, 2 ], 'float32' )\nvar arr = matrix( 2, 2 )\narr = matrix( 2, 2, 'float32' )\nvar v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\nvar arr = matrix( v, 'float32' )\nvar buf = new ArrayBuffer( 32 );\nvar arr = matrix( buf, 0, [ 2, 2 ], 'float32' )\nvar buf = new ArrayBuffer( 32 );\nvar arr = matrix( buf, 0, 2, 2, 'float32' )\n","matrix.factory":"var f = matrix.factory( 'float32' );\nvar arr = f( [ 2, 2 ] )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar rivers = data.rivers\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDataTypes.binary":"var dt = ndarrayDataTypes.binary\n","ndarrayDataTypes.boolean":"var dt = ndarrayDataTypes.boolean\n","ndarrayDataTypes.complex32":"var dt = ndarrayDataTypes.complex32\n","ndarrayDataTypes.complex64":"var dt = ndarrayDataTypes.complex64\n","ndarrayDataTypes.complex128":"var dt = ndarrayDataTypes.complex128\n","ndarrayDataTypes.float16":"var dt = ndarrayDataTypes.float16\n","ndarrayDataTypes.float32":"var dt = ndarrayDataTypes.float32\n","ndarrayDataTypes.float64":"var dt = ndarrayDataTypes.float64\n","ndarrayDataTypes.generic":"var dt = ndarrayDataTypes.generic\n","ndarrayDataTypes.int8":"var dt = ndarrayDataTypes.int8\n","ndarrayDataTypes.int16":"var dt = ndarrayDataTypes.int16\n","ndarrayDataTypes.int32":"var dt = ndarrayDataTypes.int32\n","ndarrayDataTypes.uint8":"var dt = ndarrayDataTypes.uint8\n","ndarrayDataTypes.uint8c":"var dt = ndarrayDataTypes.uint8c\n","ndarrayDataTypes.uint16":"var dt = ndarrayDataTypes.uint16\n","ndarrayDataTypes.uint32":"var dt = ndarrayDataTypes.uint32\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\n","ndemptyLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndemptyLike( x )\n","ndfill":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nndfill( x, 10.0 );\nx.get( 0, 0 )\n","ndfillBy":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nfunction fcn() { return 10.0; };\nndfillBy( x, fcn );\nx.get( 0, 0 )\nx.get( 0, 1 )\nx.get( 1, 0 )\nx.get( 1, 1 )\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditer2arrayEach":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditer2arrayEach( nditerRows( x ) );\nvar v = it.next().value\nv = it.next().value\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\n","ndzerosLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndzerosLike( x )\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","noneOwnBy":"function isUnderage( v ) { return ( v < 18 ); };\nvar obj = { 'a': 11, 'b': 12, 'c': 22 };\nvar bool = noneOwnBy( obj, isUnderage )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.arcsine":"var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n","random.arcsine.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.arcsine.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.arcsine.factory":"var fcn = random.arcsine.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.arcsine.PRNG":"var prng = random.arcsine.PRNG;\n","random.arcsine.seed":"var seed = random.arcsine.seed;\n","random.arcsine.seedLength":"var len = random.arcsine.seedLength;\n","random.arcsine.state":"var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.arcsine.state\nout = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\nout = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\nrandom.arcsine.state = state;\nout = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n","random.arcsine.stateLength":"var len = random.arcsine.stateLength;\n","random.arcsine.byteLength":"var sz = random.arcsine.byteLength;\n","random.bernoulli":"var out = random.bernoulli( [ 3, 3 ], 0.5 )\n","random.bernoulli.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.bernoulli.assign( 0.5, out )\nvar bool = ( v === out )\n","random.bernoulli.factory":"var fcn = random.bernoulli.factory();\nvar out = fcn( [ 3, 3 ], 0.5 )\n","random.bernoulli.PRNG":"var prng = random.bernoulli.PRNG;\n","random.bernoulli.seed":"var seed = random.bernoulli.seed;\n","random.bernoulli.seedLength":"var len = random.bernoulli.seedLength;\n","random.bernoulli.state":"var out = random.bernoulli( [ 3, 3 ], 0.5 )\nvar state = random.bernoulli.state\nout = random.bernoulli( [ 3, 3 ], 0.5 )\nout = random.bernoulli( [ 3, 3 ], 0.5 )\nrandom.bernoulli.state = state;\nout = random.bernoulli( [ 3, 3 ], 0.5 )\n","random.bernoulli.stateLength":"var len = random.bernoulli.stateLength;\n","random.bernoulli.byteLength":"var sz = random.bernoulli.byteLength;\n","random.beta":"var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n","random.beta.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.beta.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.beta.factory":"var fcn = random.beta.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.beta.PRNG":"var prng = random.beta.PRNG;\n","random.beta.seed":"var seed = random.beta.seed;\n","random.beta.seedLength":"var len = random.beta.seedLength;\n","random.beta.state":"var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.beta.state\nout = random.beta( [ 3, 3 ], 2.0, 5.0 )\nout = random.beta( [ 3, 3 ], 2.0, 5.0 )\nrandom.beta.state = state;\nout = random.beta( [ 3, 3 ], 2.0, 5.0 )\n","random.beta.stateLength":"var len = random.beta.stateLength;\n","random.beta.byteLength":"var sz = random.beta.byteLength;\n","random.betaprime":"var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n","random.betaprime.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.betaprime.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.betaprime.factory":"var fcn = random.betaprime.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.betaprime.PRNG":"var prng = random.betaprime.PRNG;\n","random.betaprime.seed":"var seed = random.betaprime.seed;\n","random.betaprime.seedLength":"var len = random.betaprime.seedLength;\n","random.betaprime.state":"var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.betaprime.state\nout = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\nout = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\nrandom.betaprime.state = state;\nout = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n","random.betaprime.stateLength":"var len = random.betaprime.stateLength;\n","random.betaprime.byteLength":"var sz = random.betaprime.byteLength;\n","random.binomial":"var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n","random.binomial.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.binomial.assign( 17, 0.5, out )\nvar bool = ( v === out )\n","random.binomial.factory":"var fcn = random.binomial.factory();\nvar out = fcn( [ 3, 3 ], 17, 0.5 )\n","random.binomial.PRNG":"var prng = random.binomial.PRNG;\n","random.binomial.seed":"var seed = random.binomial.seed;\n","random.binomial.seedLength":"var len = random.binomial.seedLength;\n","random.binomial.state":"var out = random.binomial( [ 3, 3 ], 17, 0.5 )\nvar state = random.binomial.state\nout = random.binomial( [ 3, 3 ], 17, 0.5 )\nout = random.binomial( [ 3, 3 ], 17, 0.5 )\nrandom.binomial.state = state;\nout = random.binomial( [ 3, 3 ], 17, 0.5 )\n","random.binomial.stateLength":"var len = random.binomial.stateLength;\n","random.binomial.byteLength":"var sz = random.binomial.byteLength;\n","random.cauchy":"var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n","random.cauchy.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.cauchy.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.cauchy.factory":"var fcn = random.cauchy.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.cauchy.PRNG":"var prng = random.cauchy.PRNG;\n","random.cauchy.seed":"var seed = random.cauchy.seed;\n","random.cauchy.seedLength":"var len = random.cauchy.seedLength;\n","random.cauchy.state":"var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.cauchy.state\nout = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\nout = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\nrandom.cauchy.state = state;\nout = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n","random.cauchy.stateLength":"var len = random.cauchy.stateLength;\n","random.cauchy.byteLength":"var sz = random.cauchy.byteLength;\n","random.chi":"var out = random.chi( [ 3, 3 ], 2.0 )\n","random.chi.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.chi.assign( 2.0, out )\nvar bool = ( v === out )\n","random.chi.factory":"var fcn = random.chi.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.chi.PRNG":"var prng = random.chi.PRNG;\n","random.chi.seed":"var seed = random.chi.seed;\n","random.chi.seedLength":"var len = random.chi.seedLength;\n","random.chi.state":"var out = random.chi( [ 3, 3 ], 2.0 )\nvar state = random.chi.state\nout = random.chi( [ 3, 3 ], 2.0 )\nout = random.chi( [ 3, 3 ], 2.0 )\nrandom.chi.state = state;\nout = random.chi( [ 3, 3 ], 2.0 )\n","random.chi.stateLength":"var len = random.chi.stateLength;\n","random.chi.byteLength":"var sz = random.chi.byteLength;\n","random.chisquare":"var out = random.chisquare( [ 3, 3 ], 2.0 )\n","random.chisquare.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.chisquare.assign( 2.0, out )\nvar bool = ( v === out )\n","random.chisquare.factory":"var fcn = random.chisquare.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.chisquare.PRNG":"var prng = random.chisquare.PRNG;\n","random.chisquare.seed":"var seed = random.chisquare.seed;\n","random.chisquare.seedLength":"var len = random.chisquare.seedLength;\n","random.chisquare.state":"var out = random.chisquare( [ 3, 3 ], 2.0 )\nvar state = random.chisquare.state\nout = random.chisquare( [ 3, 3 ], 2.0 )\nout = random.chisquare( [ 3, 3 ], 2.0 )\nrandom.chisquare.state = state;\nout = random.chisquare( [ 3, 3 ], 2.0 )\n","random.chisquare.stateLength":"var len = random.chisquare.stateLength;\n","random.chisquare.byteLength":"var sz = random.chisquare.byteLength;\n","random.cosine":"var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n","random.cosine.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.cosine.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.cosine.factory":"var fcn = random.cosine.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.cosine.PRNG":"var prng = random.cosine.PRNG;\n","random.cosine.seed":"var seed = random.cosine.seed;\n","random.cosine.seedLength":"var len = random.cosine.seedLength;\n","random.cosine.state":"var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.cosine.state\nout = random.cosine( [ 3, 3 ], 2.0, 5.0 )\nout = random.cosine( [ 3, 3 ], 2.0, 5.0 )\nrandom.cosine.state = state;\nout = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n","random.cosine.stateLength":"var len = random.cosine.stateLength;\n","random.cosine.byteLength":"var sz = random.cosine.byteLength;\n","random.discreteUniform":"var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n","random.discreteUniform.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.discreteUniform.assign( -10, 10, out )\nvar bool = ( v === out )\n","random.discreteUniform.factory":"var fcn = random.discreteUniform.factory();\nvar out = fcn( [ 3, 3 ], -10, 10 )\n","random.discreteUniform.PRNG":"var prng = random.discreteUniform.PRNG;\n","random.discreteUniform.seed":"var seed = random.discreteUniform.seed;\n","random.discreteUniform.seedLength":"var len = random.discreteUniform.seedLength;\n","random.discreteUniform.state":"var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\nvar state = random.discreteUniform.state\nout = random.discreteUniform( [ 3, 3 ], -10, 10 )\nout = random.discreteUniform( [ 3, 3 ], -10, 10 )\nrandom.discreteUniform.state = state;\nout = random.discreteUniform( [ 3, 3 ], -10, 10 )\n","random.discreteUniform.stateLength":"var len = random.discreteUniform.stateLength;\n","random.discreteUniform.byteLength":"var sz = random.discreteUniform.byteLength;\n","random.erlang":"var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n","random.erlang.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.erlang.assign( 2, 5.0, out )\nvar bool = ( v === out )\n","random.erlang.factory":"var fcn = random.erlang.factory();\nvar out = fcn( [ 3, 3 ], 2, 5.0 )\n","random.erlang.PRNG":"var prng = random.erlang.PRNG;\n","random.erlang.seed":"var seed = random.erlang.seed;\n","random.erlang.seedLength":"var len = random.erlang.seedLength;\n","random.erlang.state":"var out = random.erlang( [ 3, 3 ], 2, 5.0 )\nvar state = random.erlang.state\nout = random.erlang( [ 3, 3 ], 2, 5.0 )\nout = random.erlang( [ 3, 3 ], 2, 5.0 )\nrandom.erlang.state = state;\nout = random.erlang( [ 3, 3 ], 2, 5.0 )\n","random.erlang.stateLength":"var len = random.erlang.stateLength;\n","random.erlang.byteLength":"var sz = random.erlang.byteLength;\n","random.exponential":"var out = random.exponential( [ 3, 3 ], 2.0 )\n","random.exponential.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.exponential.assign( 2.0, out )\nvar bool = ( v === out )\n","random.exponential.factory":"var fcn = random.exponential.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.exponential.PRNG":"var prng = random.exponential.PRNG;\n","random.exponential.seed":"var seed = random.exponential.seed;\n","random.exponential.seedLength":"var len = random.exponential.seedLength;\n","random.exponential.state":"var out = random.exponential( [ 3, 3 ], 2.0 )\nvar state = random.exponential.state\nout = random.exponential( [ 3, 3 ], 2.0 )\nout = random.exponential( [ 3, 3 ], 2.0 )\nrandom.exponential.state = state;\nout = random.exponential( [ 3, 3 ], 2.0 )\n","random.exponential.stateLength":"var len = random.exponential.stateLength;\n","random.exponential.byteLength":"var sz = random.exponential.byteLength;\n","random.f":"var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n","random.f.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.f.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.f.factory":"var fcn = random.f.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.f.PRNG":"var prng = random.f.PRNG;\n","random.f.seed":"var seed = random.f.seed;\n","random.f.seedLength":"var len = random.f.seedLength;\n","random.f.state":"var out = random.f( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.f.state\nout = random.f( [ 3, 3 ], 2.0, 5.0 )\nout = random.f( [ 3, 3 ], 2.0, 5.0 )\nrandom.f.state = state;\nout = random.f( [ 3, 3 ], 2.0, 5.0 )\n","random.f.stateLength":"var len = random.f.stateLength;\n","random.f.byteLength":"var sz = random.f.byteLength;\n","random.frechet":"var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.frechet.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.frechet.assign( 2.0, 5.0, 3.0, out )\nvar bool = ( v === out )\n","random.frechet.factory":"var fcn = random.frechet.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.frechet.PRNG":"var prng = random.frechet.PRNG;\n","random.frechet.seed":"var seed = random.frechet.seed;\n","random.frechet.seedLength":"var len = random.frechet.seedLength;\n","random.frechet.state":"var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\nvar state = random.frechet.state\nout = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\nout = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\nrandom.frechet.state = state;\nout = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.frechet.stateLength":"var len = random.frechet.stateLength;\n","random.frechet.byteLength":"var sz = random.frechet.byteLength;\n","random.gamma":"var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n","random.gamma.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.gamma.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.gamma.factory":"var fcn = random.gamma.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.gamma.PRNG":"var prng = random.gamma.PRNG;\n","random.gamma.seed":"var seed = random.gamma.seed;\n","random.gamma.seedLength":"var len = random.gamma.seedLength;\n","random.gamma.state":"var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.gamma.state\nout = random.gamma( [ 3, 3 ], 2.0, 5.0 )\nout = random.gamma( [ 3, 3 ], 2.0, 5.0 )\nrandom.gamma.state = state;\nout = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n","random.gamma.stateLength":"var len = random.gamma.stateLength;\n","random.gamma.byteLength":"var sz = random.gamma.byteLength;\n","random.geometric":"var out = random.geometric( [ 3, 3 ], 0.01 )\n","random.geometric.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.geometric.assign( 0.01, out )\nvar bool = ( v === out )\n","random.geometric.factory":"var fcn = random.geometric.factory();\nvar out = fcn( [ 3, 3 ], 0.01 )\n","random.geometric.PRNG":"var prng = random.geometric.PRNG;\n","random.geometric.seed":"var seed = random.geometric.seed;\n","random.geometric.seedLength":"var len = random.geometric.seedLength;\n","random.geometric.state":"var out = random.geometric( [ 3, 3 ], 0.01 )\nvar state = random.geometric.state\nout = random.geometric( [ 3, 3 ], 0.01 )\nout = random.geometric( [ 3, 3 ], 0.01 )\nrandom.geometric.state = state;\nout = random.geometric( [ 3, 3 ], 0.01 )\n","random.geometric.stateLength":"var len = random.geometric.stateLength;\n","random.geometric.byteLength":"var sz = random.geometric.byteLength;\n","random.gumbel":"var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n","random.gumbel.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.gumbel.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.gumbel.factory":"var fcn = random.gumbel.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.gumbel.PRNG":"var prng = random.gumbel.PRNG;\n","random.gumbel.seed":"var seed = random.gumbel.seed;\n","random.gumbel.seedLength":"var len = random.gumbel.seedLength;\n","random.gumbel.state":"var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.gumbel.state\nout = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\nout = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\nrandom.gumbel.state = state;\nout = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n","random.gumbel.stateLength":"var len = random.gumbel.stateLength;\n","random.gumbel.byteLength":"var sz = random.gumbel.byteLength;\n","random.hypergeometric":"var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n","random.hypergeometric.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.hypergeometric.assign( 20, 10, 7, out )\nvar bool = ( v === out )\n","random.hypergeometric.factory":"var fcn = random.hypergeometric.factory();\nvar out = fcn( [ 3, 3 ], 20, 10, 7 )\n","random.hypergeometric.PRNG":"var prng = random.hypergeometric.PRNG;\n","random.hypergeometric.seed":"var seed = random.hypergeometric.seed;\n","random.hypergeometric.seedLength":"var len = random.hypergeometric.seedLength;\n","random.hypergeometric.state":"var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\nvar state = random.hypergeometric.state\nout = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\nout = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\nrandom.hypergeometric.state = state;\nout = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n","random.hypergeometric.stateLength":"var len = random.hypergeometric.stateLength;\n","random.hypergeometric.byteLength":"var sz = random.hypergeometric.byteLength;\n","random.invgamma":"var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n","random.invgamma.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.invgamma.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.invgamma.factory":"var fcn = random.invgamma.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.invgamma.PRNG":"var prng = random.invgamma.PRNG;\n","random.invgamma.seed":"var seed = random.invgamma.seed;\n","random.invgamma.seedLength":"var len = random.invgamma.seedLength;\n","random.invgamma.state":"var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.invgamma.state\nout = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\nout = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\nrandom.invgamma.state = state;\nout = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n","random.invgamma.stateLength":"var len = random.invgamma.stateLength;\n","random.invgamma.byteLength":"var sz = random.invgamma.byteLength;\n","random.kumaraswamy":"var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n","random.kumaraswamy.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.kumaraswamy.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.kumaraswamy.factory":"var fcn = random.kumaraswamy.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.kumaraswamy.PRNG":"var prng = random.kumaraswamy.PRNG;\n","random.kumaraswamy.seed":"var seed = random.kumaraswamy.seed;\n","random.kumaraswamy.seedLength":"var len = random.kumaraswamy.seedLength;\n","random.kumaraswamy.state":"var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.kumaraswamy.state\nout = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\nout = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\nrandom.kumaraswamy.state = state;\nout = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n","random.kumaraswamy.stateLength":"var len = random.kumaraswamy.stateLength;\n","random.kumaraswamy.byteLength":"var sz = random.kumaraswamy.byteLength;\n","random.laplace":"var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n","random.laplace.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.laplace.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.laplace.factory":"var fcn = random.laplace.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.laplace.PRNG":"var prng = random.laplace.PRNG;\n","random.laplace.seed":"var seed = random.laplace.seed;\n","random.laplace.seedLength":"var len = random.laplace.seedLength;\n","random.laplace.state":"var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.laplace.state\nout = random.laplace( [ 3, 3 ], 2.0, 5.0 )\nout = random.laplace( [ 3, 3 ], 2.0, 5.0 )\nrandom.laplace.state = state;\nout = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n","random.laplace.stateLength":"var len = random.laplace.stateLength;\n","random.laplace.byteLength":"var sz = random.laplace.byteLength;\n","random.levy":"var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n","random.levy.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.levy.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.levy.factory":"var fcn = random.levy.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.levy.PRNG":"var prng = random.levy.PRNG;\n","random.levy.seed":"var seed = random.levy.seed;\n","random.levy.seedLength":"var len = random.levy.seedLength;\n","random.levy.state":"var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.levy.state\nout = random.levy( [ 3, 3 ], 2.0, 5.0 )\nout = random.levy( [ 3, 3 ], 2.0, 5.0 )\nrandom.levy.state = state;\nout = random.levy( [ 3, 3 ], 2.0, 5.0 )\n","random.levy.stateLength":"var len = random.levy.stateLength;\n","random.levy.byteLength":"var sz = random.levy.byteLength;\n","random.logistic":"var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n","random.logistic.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.logistic.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.logistic.factory":"var fcn = random.logistic.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.logistic.PRNG":"var prng = random.logistic.PRNG;\n","random.logistic.seed":"var seed = random.logistic.seed;\n","random.logistic.seedLength":"var len = random.logistic.seedLength;\n","random.logistic.state":"var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.logistic.state\nout = random.logistic( [ 3, 3 ], 2.0, 5.0 )\nout = random.logistic( [ 3, 3 ], 2.0, 5.0 )\nrandom.logistic.state = state;\nout = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n","random.logistic.stateLength":"var len = random.logistic.stateLength;\n","random.logistic.byteLength":"var sz = random.logistic.byteLength;\n","random.lognormal":"var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n","random.lognormal.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.lognormal.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.lognormal.factory":"var fcn = random.lognormal.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.lognormal.PRNG":"var prng = random.lognormal.PRNG;\n","random.lognormal.seed":"var seed = random.lognormal.seed;\n","random.lognormal.seedLength":"var len = random.lognormal.seedLength;\n","random.lognormal.state":"var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.lognormal.state\nout = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\nout = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\nrandom.lognormal.state = state;\nout = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n","random.lognormal.stateLength":"var len = random.lognormal.stateLength;\n","random.lognormal.byteLength":"var sz = random.lognormal.byteLength;\n","random.negativeBinomial":"var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n","random.negativeBinomial.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.negativeBinomial.assign( 17, 0.5, out )\nvar bool = ( v === out )\n","random.negativeBinomial.factory":"var fcn = random.negativeBinomial.factory();\nvar out = fcn( [ 3, 3 ], 17, 0.5 )\n","random.negativeBinomial.PRNG":"var prng = random.negativeBinomial.PRNG;\n","random.negativeBinomial.seed":"var seed = random.negativeBinomial.seed;\n","random.negativeBinomial.seedLength":"var len = random.negativeBinomial.seedLength;\n","random.negativeBinomial.state":"var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\nvar state = random.negativeBinomial.state\nout = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\nout = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\nrandom.negativeBinomial.state = state;\nout = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n","random.negativeBinomial.stateLength":"var len = random.negativeBinomial.stateLength;\n","random.negativeBinomial.byteLength":"var sz = random.negativeBinomial.byteLength;\n","random.normal":"var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n","random.normal.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.normal.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.normal.factory":"var fcn = random.normal.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.normal.PRNG":"var prng = random.normal.PRNG;\n","random.normal.seed":"var seed = random.normal.seed;\n","random.normal.seedLength":"var len = random.normal.seedLength;\n","random.normal.state":"var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.normal.state\nout = random.normal( [ 3, 3 ], 2.0, 5.0 )\nout = random.normal( [ 3, 3 ], 2.0, 5.0 )\nrandom.normal.state = state;\nout = random.normal( [ 3, 3 ], 2.0, 5.0 )\n","random.normal.stateLength":"var len = random.normal.stateLength;\n","random.normal.byteLength":"var sz = random.normal.byteLength;\n","random.pareto1":"var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n","random.pareto1.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.pareto1.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.pareto1.factory":"var fcn = random.pareto1.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.pareto1.PRNG":"var prng = random.pareto1.PRNG;\n","random.pareto1.seed":"var seed = random.pareto1.seed;\n","random.pareto1.seedLength":"var len = random.pareto1.seedLength;\n","random.pareto1.state":"var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.pareto1.state\nout = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\nout = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\nrandom.pareto1.state = state;\nout = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n","random.pareto1.stateLength":"var len = random.pareto1.stateLength;\n","random.pareto1.byteLength":"var sz = random.pareto1.byteLength;\n","random.poisson":"var out = random.poisson( [ 3, 3 ], 2.0 )\n","random.poisson.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.poisson.assign( 2.0, out )\nvar bool = ( v === out )\n","random.poisson.factory":"var fcn = random.poisson.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.poisson.PRNG":"var prng = random.poisson.PRNG;\n","random.poisson.seed":"var seed = random.poisson.seed;\n","random.poisson.seedLength":"var len = random.poisson.seedLength;\n","random.poisson.state":"var out = random.poisson( [ 3, 3 ], 2.0 )\nvar state = random.poisson.state\nout = random.poisson( [ 3, 3 ], 2.0 )\nout = random.poisson( [ 3, 3 ], 2.0 )\nrandom.poisson.state = state;\nout = random.poisson( [ 3, 3 ], 2.0 )\n","random.poisson.stateLength":"var len = random.poisson.stateLength;\n","random.poisson.byteLength":"var sz = random.poisson.byteLength;\n","random.rayleigh":"var out = random.rayleigh( [ 3, 3 ], 2.0 )\n","random.rayleigh.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.rayleigh.assign( 2.0, out )\nvar bool = ( v === out )\n","random.rayleigh.factory":"var fcn = random.rayleigh.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.rayleigh.PRNG":"var prng = random.rayleigh.PRNG;\n","random.rayleigh.seed":"var seed = random.rayleigh.seed;\n","random.rayleigh.seedLength":"var len = random.rayleigh.seedLength;\n","random.rayleigh.state":"var out = random.rayleigh( [ 3, 3 ], 2.0 )\nvar state = random.rayleigh.state\nout = random.rayleigh( [ 3, 3 ], 2.0 )\nout = random.rayleigh( [ 3, 3 ], 2.0 )\nrandom.rayleigh.state = state;\nout = random.rayleigh( [ 3, 3 ], 2.0 )\n","random.rayleigh.stateLength":"var len = random.rayleigh.stateLength;\n","random.rayleigh.byteLength":"var sz = random.rayleigh.byteLength;\n","random.t":"var out = random.t( [ 3, 3 ], 2.0 )\n","random.t.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.t.assign( 2.0, out )\nvar bool = ( v === out )\n","random.t.factory":"var fcn = random.t.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.t.PRNG":"var prng = random.t.PRNG;\n","random.t.seed":"var seed = random.t.seed;\n","random.t.seedLength":"var len = random.t.seedLength;\n","random.t.state":"var out = random.t( [ 3, 3 ], 2.0 )\nvar state = random.t.state\nout = random.t( [ 3, 3 ], 2.0 )\nout = random.t( [ 3, 3 ], 2.0 )\nrandom.t.state = state;\nout = random.t( [ 3, 3 ], 2.0 )\n","random.t.stateLength":"var len = random.t.stateLength;\n","random.t.byteLength":"var sz = random.t.byteLength;\n","random.triangular":"var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.triangular.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.triangular.assign( 2.0, 5.0, 3.0, out )\nvar bool = ( v === out )\n","random.triangular.factory":"var fcn = random.triangular.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.triangular.PRNG":"var prng = random.triangular.PRNG;\n","random.triangular.seed":"var seed = random.triangular.seed;\n","random.triangular.seedLength":"var len = random.triangular.seedLength;\n","random.triangular.state":"var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\nvar state = random.triangular.state\nout = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\nout = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\nrandom.triangular.state = state;\nout = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.triangular.stateLength":"var len = random.triangular.stateLength;\n","random.triangular.byteLength":"var sz = random.triangular.byteLength;\n","random.uniform":"var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n","random.uniform.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.uniform.assign( 0.0, 1.0, out )\nvar bool = ( v === out )\n","random.uniform.factory":"var fcn = random.uniform.factory();\nvar out = fcn( [ 3, 3 ], 0.0, 1.0 )\n","random.uniform.PRNG":"var prng = random.uniform.PRNG;\n","random.uniform.seed":"var seed = random.uniform.seed;\n","random.uniform.seedLength":"var len = random.uniform.seedLength;\n","random.uniform.state":"var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\nvar state = random.uniform.state\nout = random.uniform( [ 3, 3 ], 0.0, 1.0 )\nout = random.uniform( [ 3, 3 ], 0.0, 1.0 )\nrandom.uniform.state = state;\nout = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n","random.uniform.stateLength":"var len = random.uniform.stateLength;\n","random.uniform.byteLength":"var sz = random.uniform.byteLength;\n","random.weibull":"var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n","random.weibull.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.weibull.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.weibull.factory":"var fcn = random.weibull.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.weibull.PRNG":"var prng = random.weibull.PRNG;\n","random.weibull.seed":"var seed = random.weibull.seed;\n","random.weibull.seedLength":"var len = random.weibull.seedLength;\n","random.weibull.state":"var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.weibull.state\nout = random.weibull( [ 3, 3 ], 2.0, 5.0 )\nout = random.weibull( [ 3, 3 ], 2.0, 5.0 )\nrandom.weibull.state = state;\nout = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n","random.weibull.stateLength":"var len = random.weibull.stateLength;\n","random.weibull.byteLength":"var sz = random.weibull.byteLength;\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","rtrimN":"var out = rtrimN( ' abc ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","trues":"var arr = trues( [ 2, 2 ] )\n","truesLike":"var opts = { 'dtype': 'generic' };\nvar x = ndempty( [ 2, 2 ], opts )\nvar y = truesLike( x )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedVector":"var arr = Uint8ClampedVector()\nvar arr = Uint8ClampedVector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint8ClampedVector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint8ClampedVector( buf, 0, 4 )\nvar len = numel( arr )\n","Uint8Vector":"var arr = Uint8Vector()\nvar arr = Uint8Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint8Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint8Vector( buf, 0, 4 )\nvar len = numel( arr )\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Vector":"var arr = Uint16Vector()\nvar arr = Uint16Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint16Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint16Vector( buf, 0, 4 )\nvar len = numel( arr )\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Vector":"var arr = Uint32Vector()\nvar arr = Uint32Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint32Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint32Vector( buf, 0, 4 )\nvar len = numel( arr )\n","Uint64":"var x = new Uint64( 5 )\nx.toString()\n","Uint64.name":"var str = Uint64.name\n","Uint64.from":"var v = Uint64.from( [ 1234, 5678 ] )\n","Uint64.of":"var v = Uint64.of( 1234, 5678 )\n","Uint64.BYTES_PER_ELEMENT":"var s = Uint64.BYTES_PER_ELEMENT\n","Uint64.prototype.BYTES_PER_ELEMENT":"var x = new Uint64( 5 )\nvar s = x.BYTES_PER_ELEMENT\n","Uint64.prototype.byteLength":"var x = new Uint64( 5 )\nvar s = x.byteLength\n","Uint64.prototype.hi":"var x = Uint64.from( [ 1234, 5678 ] )\nvar w = x.hi\n","Uint64.prototype.lo":"var x = Uint64.from( [ 1234, 5678 ] )\nvar w = x.lo\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","vector":"var arr = vector()\nvar dt = ndarrayDataType( arr )\narr = vector( 'float32' )\ndt = ndarrayDataType( arr )\nvar arr = vector( 5 )\nvar dt = ndarrayDataType( arr )\nvar len = numel( arr )\narr = vector( 5, 'float32' )\ndt = ndarrayDataType( arr )\nlen = numel( arr )\nvar v = [ 0.5, 0.5, 0.5 ];\nvar arr = vector( v, 'float32' )\nvar dt = ndarrayDataType( arr )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = vector( buf, 0, 4, 'float32' )\nvar dt = ndarrayDataType( arr )\nvar len = numel( arr )\n","vector.factory":"var f = vector.factory( 'float32' );\nvar arr = f()\nvar dt = ndarrayDataType( arr )\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} +{"abs":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar y = abs( x )\n","abs.assign":"var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\nvar x = array( arr );\nvar sh = ndarrayShape( x );\nvar y = ndzeros( sh );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosdf":"var y = base.acosdf( 0.0 )\ny = base.acosdf( FLOAT32_PI / 6.0 )\ny = base.acosdf( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotdf":"var y = base.acotdf( 0.0 )\ny = base.acotdf( FLOAT32_PI/6.0 )\ny = base.acotdf( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( 1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 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)\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v = base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.cadd.assign":"var out = new Float64Array( 2 );\nbase.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cadd.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.caddf.assign":"var out = new Float32Array( 2 );\nbase.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.caddf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.cdiv.assign":"var out = new Float64Array( 2 );\nbase.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n","base.cdiv.strided":"var z1 = new Float64Array( [ -13.0, -1.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n","base.cinvf":"var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmul.assign":"var out = new Float64Array( 2 );\nbase.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmul.strided":"var z1 = new Float64Array( [ 5.0, 3.0 ] );\nvar z2 = new Float64Array( [ -2.0, 1.0 ] );\nvar out = new Float64Array( 2 );\nbase.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cmulf.assign":"var out = new Float32Array( 2 );\nbase.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n","base.cmulf.strided":"var z1 = new Float32Array( [ 5.0, 3.0 ] );\nvar z2 = new Float32Array( [ -2.0, 1.0 ] );\nvar out = new Float32Array( 2 );\nbase.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n i += 1;\n return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n i += 1;\n yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = 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base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 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= base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = 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base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = 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);\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = 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)\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 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4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 0.4 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 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NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.logcdf.factory":"var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 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base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n ~1.791\ny = myQuantile( 0.8 )\n ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = 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0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 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base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toLocaleString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toLocaleString()\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar y = base.ndzerosLike( x )\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeMultiSlice":"var s1 = new MultiSlice( 1, 3, null );\nvar s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\nvar v = s2.data[ 0 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 1 ];\nv.start\nv.stop\nv.step\nv = s2.data[ 2 ];\nv.start\nv.stop\nv.step\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = base.random.arcsine.seed;\n","base.random.arcsine.seedLength":"var len = base.random.arcsine.seedLength;\n","base.random.arcsine.state":"var r = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nvar state = base.random.arcsine.state\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nbase.random.arcsine.state = state;\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\n","base.random.arcsine.stateLength":"var len = base.random.arcsine.stateLength;\n","base.random.arcsine.byteLength":"var sz = base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nvar state = base.random.cauchy.state\nr = 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);\n","base.random.kumaraswamy.factory":"var rand = base.random.kumaraswamy.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.kumaraswamy.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.kumaraswamy.NAME":"var str = base.random.kumaraswamy.NAME\n","base.random.kumaraswamy.PRNG":"var prng = base.random.kumaraswamy.PRNG;\n","base.random.kumaraswamy.seed":"var seed = base.random.kumaraswamy.seed;\n","base.random.kumaraswamy.seedLength":"var len = base.random.kumaraswamy.seedLength;\n","base.random.kumaraswamy.state":"var r = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nvar state = base.random.kumaraswamy.state\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\nbase.random.kumaraswamy.state = state;\nr = base.random.kumaraswamy( 1.5, 1.5 )\nr = base.random.kumaraswamy( 1.5, 1.5 )\n","base.random.kumaraswamy.stateLength":"var len = 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base.random.randi.MAX;\n","base.random.randi.seed":"var seed = base.random.randi.seed;\n","base.random.randi.seedLength":"var len = base.random.randi.seedLength;\n","base.random.randi.state":"var r = base.random.randi()\nr = base.random.randi()\nr = base.random.randi()\nvar state = base.random.randi.state;\nr = base.random.randi()\nr = base.random.randi()\nbase.random.randi.state = state;\nr = base.random.randi()\nr = base.random.randi()\n","base.random.randi.stateLength":"var len = base.random.randi.stateLength;\n","base.random.randi.byteLength":"var sz = base.random.randi.byteLength;\n","base.random.randi.toJSON":"var o = base.random.randi.toJSON()\n","base.random.randn":"var r = base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var 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5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\n","base.random.rayleigh.stateLength":"var len = base.random.rayleigh.stateLength;\n","base.random.rayleigh.byteLength":"var sz = base.random.rayleigh.byteLength;\n","base.random.rayleigh.toJSON":"var o = base.random.rayleigh.toJSON()\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.t.factory":"var rand = base.random.t.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.t.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.t.NAME":"var str = base.random.t.NAME\n","base.random.t.PRNG":"var prng = base.random.t.PRNG;\n","base.random.t.seed":"var seed = base.random.t.seed;\n","base.random.t.seedLength":"var len = base.random.t.seedLength;\n","base.random.t.state":"var r = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nvar state = base.random.t.state\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nbase.random.t.state = state;\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = base.random.t.stateLength;\n","base.random.t.byteLength":"var sz = base.random.t.byteLength;\n","base.random.t.toJSON":"var o = base.random.t.toJSON()\n","base.random.triangular":"var r = base.random.triangular( 2.0, 5.0, 3.33 );\n","base.random.triangular.factory":"var rand = base.random.triangular.factory();\nvar r = rand( 0.0, 1.0, 0.5 );\nr = rand( -2.0, 2.0, 1.0 );\nrand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\nr = rand();\nr = rand();\n","base.random.triangular.NAME":"var str = base.random.triangular.NAME\n","base.random.triangular.PRNG":"var prng = base.random.triangular.PRNG;\n","base.random.triangular.seed":"var seed = base.random.triangular.seed;\n","base.random.triangular.seedLength":"var len = base.random.triangular.seedLength;\n","base.random.triangular.state":"var r = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nvar state = base.random.triangular.state\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = ndarrayShape( x )\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\n","base.sincos.assign":"var out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 )\ny0\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nx\ny\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nx0\ny0\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nx\ny\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nx\ny\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.cuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabsSorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabsSorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabsSorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabsSorted( 3, x1, 2 )\n","base.strided.dmaxabsSorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabsSorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabsSorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxSorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxSorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxSorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxSorted( 3, x1, 2 )\n","base.strided.dmaxSorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxSorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxSorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmean( 3, x1, 2 )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmean.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn( 3, x1, 2 )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeankbn2( 3, x1, 2 )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanli( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanli( 3, x1, 2 )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanli.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanlipw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanlipw( 3, x1, 2 )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanors( 3, x1, 2 )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpn( 3, x1, 2 )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanpw( 3, x1, 2 )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmeanwd( 3, x1, 2 )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dmedianSorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmedianSorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmedianSorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmedianSorted( 3, x1, 2 )\n","base.strided.dmedianSorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmedianSorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmedianSorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasumors( 4, x1, 2 )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmean( 4, x1,2 )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanors( 4, x1, 2 )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpn( 4, x1, 2 )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanpw( 4, x1, 2 )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 4, x1, 2 )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnanstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdev( 3, 1, x1, 2 )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevch( 4, 1, x1, 2 )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevpn( 4, 1, x1, 2 )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevtk( 4, 1, x1, 2 )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevwd( 4, 1, x1, 2 )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanstdevyc( 4, 1, x1, 2 )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariance( 4, 1, x1, 2 )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancech( 4, 1, x1, 2 )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancepn( 4, 1, x1, 2 )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancetk( 4, 1, x1, 2 )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvariancewd( 4, 1, x1, 2 )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanvarianceyc( 4, 1, x1, 2 )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsem( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsem( 3, 1, x1, 2 )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemch( 3, 1, x1, 2 )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsempn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsempn( 3, 1, x1, 2 )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemtk( 3, 1, x1, 2 )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemwd( 3, 1, x1, 2 )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsemyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsemyc( 3, 1, x1, 2 )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmean( 3, x1, 2 )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmean.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanors( 3, x1, 2 )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpn( 3, x1, 2 )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanpw( 3, x1, 2 )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsmeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsmeanwd( 3, x1, 2 )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmean( 4, x1, 2 )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanors( 4, x1, 2 )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanpn( 4, x1, 2 )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnanmeanwd( 4, x1, 2 )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsortins( 2, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdev( 3, 1, x1, 2 )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevch( 3, 1, x1, 2 )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevpn( 3, 1, x1, 2 )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevtk( 3, 1, x1, 2 )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevwd( 3, 1, x1, 2 )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dstdevyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dstdevyc( 3, 1.0, x1, 2 )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariance( 3, 1, x1, 2 )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsvariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsvariancepn( 3, 1, x1, 2 )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariance( 3, 1, x1, 2 )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancech( 3, 1, x1, 2 )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancepn( 3, 1, x1, 2 )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancetk( 3, 1, x1, 2 )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvariancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvariancewd( 3, 1, x1, 2 )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarianceyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarianceyc( 3, 1, x1, 2 )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nbase.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gapx( 4, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsum( 3, 5.0, x1, 2 )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumors( 3, 5.0, x1, 2 )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.gasumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gasumpw( 3, x1, 2 )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.gasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( 3, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gfillBy( 3, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansum( 4, x1, 2 )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansum.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn( 4, x1, 2 )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumkbn2( 4, x1, 2 )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumors( 4, x1, 2 )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnansumpw( 4, x1, 2 )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.grev( 3, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.grev.ndarray( 3, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsorthp( 2, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortins( 2, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( 2, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsortsh( 2, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsum( 3, x1, 2 )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsum.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn( 3, x1, 2 )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumkbn2( 3, x1, 2 )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumors( 3, x1, 2 )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumors.ndarray( 3, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gsumpw( 3, x1, 2 )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.max( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.max( 3, x1, 2 )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.max.ndarray( 3, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxabs( 3, x1, 2 )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.maxabs.ndarray( 3, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxBy( 3, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.maxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.maxsorted( 3, x1, 2 )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.maxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mean( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mean( 3, x1, 2 )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.mean.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn( 3, x1, 2 )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn.ndarray( 3, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meankbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meankbn2( 3, x1, 2 )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanors( 3, x1, 2 )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( 3, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpn( 3, x1, 2 )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpn.ndarray( 3, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanpw( 3, x1, 2 )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanpw.ndarray( 3, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.meanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.meanwd( 3, x1, 2 )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.meanwd.ndarray( 3, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.mediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.mediansorted( 3, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.mediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.min( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.min( 3, x1, 2 )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.min.ndarray( 3, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minabs( 3, x1, 2 )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.minabs.ndarray( 3, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nbase.strided.minBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minBy( 3, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.minsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.minsorted( 3, x1, 2 )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nbase.strided.minsorted.ndarray( 3, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmax( 3, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskmin( 3, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.mskrange( 3, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmax( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmax( 4, x1, 2 )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmax.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxabs( 4, x1, 2 )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.nanmaxBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmaxBy( 3, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmean( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmean( 4, x1, 2 )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmean.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanors( 4, x1, 2 )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanpn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanpn( 4, x1, 2 )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanmeanwd( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmeanwd( 4, x1, 2 )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanmin( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmin( 4, x1, 2 )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanmin.ndarray( 4, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanminabs( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanminabs( 4, x1, 2 )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanminabs.ndarray( 4, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nbase.strided.nanminBy( 4, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanminBy( 3, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmax( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskmin( 4, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\nmask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( 5, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nbase.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanrange( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanrange( 4, x1, 2 )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanrange.ndarray( 4, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nbase.strided.nanrangeBy( 4, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanrangeBy( 3, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdev( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0,NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdev( 4, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevch( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevch( 4, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevpn( 4, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevtk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevtk( 4, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevwd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevwd( 4, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanstdevyc( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanstdevyc( 4, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariance( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariance( 4, 1, x1, 2 )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancech( 4, 1, x1, 2 )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvariancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancepn( 3, 1, x1, 2 )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancetk( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancetk( 4, 1, x1, 2 )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nbase.strided.nanvariancewd( 4, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvariancewd( 4, 1, x1, 2 )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nbase.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( 4, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.nanvarianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.range( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.range( 3, x1, 2 )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.range.ndarray( 3, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( 3, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.rangeBy( 3, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumors( 3, 5.0, x1, 2 )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmean( 3, x1, 2 )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmean.ndarray( 3, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsmeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsmeanors( 3, x1, 2 )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnanmeanors( 3, x1, 2 )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansum( 4, x1, 2 )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssum( 3, x1, 2 )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdssumpw( 3, x1, 2 )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smean( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smean( 3, x1, 2 )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smean.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn( 3, x1, 2 )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn.ndarray( 3, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeankbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeankbn2( 3, x1, 2 )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanli( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanli( 3, x1, 2 )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanli.ndarray( 3, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanlipw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanlipw( 3, x1, 2 )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanors( 3, x1, 2 )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanors.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpn( 3, x1, 2 )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpn.ndarray( 3, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanpw( 3, x1, 2 )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanpw.ndarray( 3, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smeanwd( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smeanwd( 3, x1, 2 )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmean( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmean( 4, x1, 2 )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmean.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmeanors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanors( 4, x1, 2 )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanpn( 4, x1, 2 )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmeanwd( 4, x1, 2 )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn( 4, x1, 2 )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumkbn2( 4, x1, 2 )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdev( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdev( 3, 1, x1, 2 )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevch( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevch( 3, 1, x1, 2 )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevpn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevpn( 3, 1, x1, 2 )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevtk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevtk( 3, 1, x1, 2 )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevwd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevwd( 3, 1, x1, 2 )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sstdevyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sstdevyc( 3, 1, x1, 2 )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdev( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdev( 3, 1, x1, 2 )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevch( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevch( 3, 1, x1, 2 )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevpn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevpn( 3, 1, x1, 2 )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevtk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevtk( 3, 1, x1, 2 )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevwd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevwd( 3, 1, x1, 2 )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.stdevyc( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.stdevyc( 3, 1, x1, 2 )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariance( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariance( 3, 1, x1, 2 )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancech( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancech( 3, 1, x1, 2 )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancepn( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancepn( 3, 1, x1, 2 )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancetk( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancetk( 3, 1, x1, 2 )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svariancewd( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svariancewd( 3, 1, x1, 2 )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.svarianceyc( 3, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.svarianceyc( 3, 1, x1, 2 )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variance( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variance( 3, 1, x1, 2 )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variance.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancech( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancech( 3, 1, x1, 2 )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancepn( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancepn( 3, 1, x1, 2 )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancetk( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancetk( 3, 1, x1, 2 )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.variancewd( 3, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.variancewd( 3, 1, x1, 2 )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.varianceyc( 3, 1.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.varianceyc( 3, 1.0, x1, 2 )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n yield Math.pow( x, exponent );\n exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n exponent += 1;\n return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar y = base.transpose( x, false )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","BooleanVector":"var arr = BooleanVector()\nvar arr = BooleanVector( 5 )\nvar len = numel( arr )\nvar v = [ true, false, true ];\nvar arr = BooleanVector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = BooleanVector( buf, 0, 4 )\nvar len = numel( arr )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.name":"var str = Complex64.name\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nz = out.get( 1 )\nz = out.get( 2 )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nz = out.get( 1 )\nz = out.get( 2 )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\n","Complex64Matrix":"var arr = Complex64Matrix()\nvar arr = Complex64Matrix( [ 2, 2 ] )\nvar arr = Complex64Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\nvar arr = Complex64Matrix( v )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex64Matrix( buf, 0, [ 8, 1 ] )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex64Matrix( buf, 0, 8, 1 )\n","Complex64Vector":"var arr = Complex64Vector()\nvar arr = Complex64Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar arr = Complex64Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Complex64Vector( buf, 0, 2 )\nvar len = numel( arr )\n","Complex128.name":"var str = Complex128.name\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nz = out.get( 1 )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nz = arr.get( 1 )\nz = arr.get( 2 )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n","Complex128Matrix":"var arr = Complex128Matrix()\nvar arr = Complex128Matrix( [ 2, 2 ] )\nvar arr = Complex128Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\nvar arr = Complex128Matrix( v )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex128Matrix( buf, 0, [ 4, 1 ] )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex128Matrix( buf, 0, 4, 1 )\n","Complex128Vector":"var arr = Complex128Vector()\nvar arr = Complex128Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar arr = Complex128Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 64 );\nvar arr = Complex128Vector( buf, 0, 2 )\nvar len = numel( arr )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataType":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.name":"DataType.name\n","DataType.prototype.alignment":"var dt = new DataType( 'float64' );\ndt.alignment\n","DataType.prototype.byteLength":"var dt = new DataType( 'float64' );\ndt.byteLength\n","DataType.prototype.byteOrder":"var dt = new DataType( 'float64' );\ndt.byteOrder\n","DataType.prototype.char":"var dt = new DataType( 'float64' );\ndt.char\n","DataType.prototype.description":"var dt = new DataType( 'float64' );\ndt.description\n","DataType.prototype.enum":"var dt = new DataType( 'float64' );\ndt.enum\n","DataType.prototype.value":"var dt = new DataType( 'float64' );\ndt.value\n","DataType.prototype.toJSON":"var dt = new DataType( 'float64' );\ndt.toJSON()\n","DataType.prototype.toString":"var dt = new DataType( 'float64' );\ndt.toString()\n","DataType.prototype.valueOf":"var dt = new DataType( 'float64' );\ndt.valueOf()\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj1 = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj1, 'a.b.c', 'beep' )\nvar obj2 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\nobj2\nvar obj3 = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\nobj3\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n 'value': 'bar',\n 'writable': false,\n 'configurable': false,\n 'enumerable': true\n },\n 'baz': {\n 'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","falses":"var arr = falses( [ 2, 2 ] )\n","falsesLike":"var opts = { 'dtype': 'generic' };\nvar x = ndempty( [ 2, 2 ], opts )\nvar y = falsesLike( x )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","Float16Array":"var arr = new Float16Array()\nvar arr = new Float16Array( 5 )\nvar len = arr.length\nvar buf = new Float64Array( [ 0.5, 0.5, 0.5 ] )\nvar arr = new Float16Array( buf )\nvar len = arr.length\nvar arr = new Float16Array( [ 0.5, 0.5, 0.5 ] )\nvar len = arr.length\nvar buf = new ArrayBuffer( 8 );\nvar arr1 = new Float16Array( buf )\nvar len = arr1.length\nvar arr2 = new Float16Array( buf, 2 )\nlen = arr2.length\nvar arr3 = new Float16Array( buf, 2, 2 )\nlen = arr3.length\n","Float16Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Float16Array.from( [ 1.0, -1.0 ], clbkFcn )\nvar len = arr.length\nvar v = arr[ 0 ]\nv = arr[ 1 ]\n","Float16Array.of":"var arr = Float16Array.of( 1.0, -1.0 )\nvar len = arr.length\nvar v = arr[ 0 ]\nv = arr[ 1 ]\n","Float16Array.BYTES_PER_ELEMENT":"var nbytes = Float16Array.BYTES_PER_ELEMENT\n","Float16Array.name":"var str = Float16Array.name\n","Float16Array.prototype.buffer":"var arr = new Float16Array( 2 )\nvar buf = arr.buffer\n","Float16Array.prototype.byteLength":"var arr = new Float16Array( 5 )\nvar nbytes = arr.byteLength\n","Float16Array.prototype.byteOffset":"var arr = new Float16Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 20 );\narr = new Float16Array( buf, 10 )\noffset = arr.byteOffset\n","Float16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float16Array( 5 )\narr.BYTES_PER_ELEMENT\n","Float16Array.prototype.length":"var arr = new Float16Array( 5 )\nvar len = arr.length\n","Float16Array.prototype.at":"var arr = new Float16Array( [ 10.0, 20.0, 30.0 ] )\nvar v = arr.at( 0 )\nv = arr.at( -1 )\n","Float16Array.prototype.copyWithin":"var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\narr.copyWithin( 0, 3 )\nvar v = arr[ 0 ]\nv = arr[ 1 ]\n","Float16Array.prototype.entries":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Float16Array.prototype.every":"function predicate( v ) { return ( v > 0.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0 ] )\nvar bool = arr.every( predicate )\n","Float16Array.prototype.fill":"var arr = new Float16Array( 3 )\narr.fill( 2.0 );\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.filter":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out[ 0 ]\nv = out[ 1 ]\n","Float16Array.prototype.find":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar v = arr.find( predicate )\n","Float16Array.prototype.findIndex":"function predicate( v ) { return ( v > 2.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Float16Array.prototype.findLast":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar v = arr.findLast( predicate )\n","Float16Array.prototype.findLastIndex":"function predicate( v ) { return ( v > 1.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Float16Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\narr.forEach( clbk );\nstr\n","Float16Array.prototype.includes":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar bool = arr.includes( 3.0 )\nbool = arr.includes( 3.0, 3 )\n","Float16Array.prototype.indexOf":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( 2.0, 2 )\n","Float16Array.prototype.join":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","Float16Array.prototype.keys":"var arr = new Float16Array( [ 1.0, 2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Float16Array.prototype.lastIndexOf":"var arr = new Float16Array( [ 1.0, 2.0, 3.0, 1.0 ] )\nvar idx = arr.lastIndexOf( 1.0 )\nidx = arr.lastIndexOf( 1.0, 2 )\n","Float16Array.prototype.map":"function clbk( v ) { return v * 2.0; };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.map( clbk )\nvar v = out[ 0 ]\nv = out[ 1 ]\nv = out[ 2 ]\n","Float16Array.prototype.reduce":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nfunction reducerFn( acc, v ) { return acc + v; };\nvar v = arr.reduce( reducerFn, 0.0 )\n","Float16Array.prototype.reduceRight":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nfunction reducerFn( acc, v ) { return acc + v; };\nvar v = arr.reduceRight( reducerFn, 0.0 )\n","Float16Array.prototype.reverse":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\narr.reverse();\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.set":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\narr.set( [ 4.0, 5.0 ], 1 );\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.slice":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out[ 0 ]\nv = out[ 1 ]\n","Float16Array.prototype.some":"function predicate( v ) { return ( v > 2.0 ); };\nvar arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar bool = arr.some( predicate )\n","Float16Array.prototype.sort":"function compare( a, b ) { return a - b; };\nvar arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\narr.sort( compare );\nvar v = arr[ 0 ]\nv = arr[ 1 ]\nv = arr[ 2 ]\n","Float16Array.prototype.subarray":"var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out[ 0 ]\nv = out[ 1 ]\n","Float16Array.prototype.toLocaleString":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar str = arr.toLocaleString()\n","Float16Array.prototype.toReversed":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.toReversed()\nvar v = out[ 0 ]\nv = out[ 1 ]\nv = out[ 2 ]\n","Float16Array.prototype.toSorted":"function compare( a, b ) { return a - b; };\nvar arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\nvar out = arr.toSorted( compare );\nvar v = out[ 0 ]\nv = out[ 1 ]\nv = out[ 2 ]\n","Float16Array.prototype.toString":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar str = arr.toString()\n","Float16Array.prototype.values":"var arr = new Float16Array( [ 1.0, 2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","Float16Array.prototype.with":"var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\nvar out = arr.with( 1, 4.0 )\nvar v = out[ 1 ]\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Float32Matrix":"var arr = Float32Matrix()\nvar arr = Float32Matrix( [ 2, 2 ] )\nvar arr = Float32Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\nvar arr = Float32Matrix( v )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float32Matrix( buf, 0, [ 8, 1 ] )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float32Matrix( buf, 0, 4, 1 )\n","Float32Vector":"var arr = Float32Vector()\nvar arr = Float32Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0 ];\nvar arr = Float32Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float32Vector( buf, 0, 4 )\nvar len = numel( arr )\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Float64Matrix":"var arr = Float64Matrix()\nvar arr = Float64Matrix( [ 2, 2 ] )\nvar arr = Float64Matrix( 2, 2 )\nvar v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\nvar arr = Float64Matrix( v )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float64Matrix( buf, 0, [ 4, 1 ] )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float64Matrix( buf, 0, 4, 1 )\n","Float64Vector":"var arr = Float64Vector()\nvar arr = Float64Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1.0, 2.0, 3.0 ];\nvar arr = Float64Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Float64Vector( buf, 0, 2 )\nvar len = numel( arr )\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServerFactory":"var boot = httpServerFactory()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\nboot = httpServerFactory( onRequest )\nvar opts = { 'port': 7331 };\nboot = httpServerFactory( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Int8Vector":"var arr = Int8Vector()\nvar arr = Int8Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Int8Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int8Vector( buf, 0, 4 )\nvar len = numel( arr )\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Int16Vector":"var arr = Int16Vector()\nvar arr = Int16Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Int16Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int16Vector( buf, 0, 4 )\nvar len = numel( arr )\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Int32Matrix":"var arr = Int32Matrix()\nvar arr = Int32Matrix( [ 2, 2 ] )\nvar arr = Int32Matrix( 2, 2 )\nvar v = [ [ 1, 2 ], [ 3, 4 ] ];\nvar arr = Int32Matrix( v )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Matrix( buf, 0, [ 8, 1 ] )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Matrix( buf, 0, 8, 1 )\n","Int32Vector":"var arr = Int32Vector()\nvar arr = Int32Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Int32Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Int32Vector( buf, 0, 4 )\nvar len = numel( arr )\n","Int64":"var x = new Int64( 5 )\nx.toString()\n","Int64.name":"var str = Int64.name\n","Int64.from":"var v = Int64.from( [ 1234, 5678 ] )\n","Int64.of":"var v = Int64.of( 1234, 5678 )\n","Int64.BYTES_PER_ELEMENT":"var s = Int64.BYTES_PER_ELEMENT\n","Int64.prototype.BYTES_PER_ELEMENT":"var x = new Int64( 5 )\nvar s = x.BYTES_PER_ELEMENT\n","Int64.prototype.byteLength":"var x = new Int64( 5 )\nvar s = x.byteLength\n","Int64.prototype.hi":"var x = Int64.from( [ 1234, 5678 ] )\nvar w = x.hi\n","Int64.prototype.lo":"var x = Int64.from( [ 1234, 5678 ] )\nvar w = x.lo\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( ' ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var opts = { 'dtype': 'complex128' };\nvar M = ndzeros( [ 2, 2 ], opts );\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var opts = { 'dtype': 'complex128' };\nvar M = ndzeros( [ 2, 2 ], opts );\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var opts = { 'dtype': 'complex128' };\nvar M = ndzeros( [ 4 ], opts );\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isEqualDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isEqualDateObject( d1, d2 )\nd1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nd2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nbool = isEqualDateObject( d1, d2 )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n yield idx;\n idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31; // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8; // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isStruct":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStruct( new S() )\nbool = isStruct( [ 1, 2, 3, 4 ] )\nbool = isStruct( 3.14 )\nbool = isStruct( {} )\n","isStructConstructorLike":"var schema = [ { 'name': 'foo', 'type': 'float64' } ];\nvar S = structFactory( schema );\nvar bool = isStructConstructorLike( S )\nbool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\nbool = isStructConstructorLike( 3.14 )\nbool = isStructConstructorLike( {} )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( ' ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n","ltrimN":"var out = ltrimN( ' abc ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","matrix":"var arr = matrix()\nvar sh = ndarrayShape( arr )\narr = matrix( 'float32' )\nvar arr = matrix( [ 2, 2 ] )\narr = matrix( [ 2, 2 ], 'float32' )\nvar arr = matrix( 2, 2 )\narr = matrix( 2, 2, 'float32' )\nvar v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\nvar arr = matrix( v, 'float32' )\nvar buf = new ArrayBuffer( 32 );\nvar arr = matrix( buf, 0, [ 2, 2 ], 'float32' )\nvar buf = new ArrayBuffer( 32 );\nvar arr = matrix( buf, 0, 2, 2, 'float32' )\n","matrix.factory":"var f = matrix.factory( 'float32' );\nvar arr = f( [ 2, 2 ] )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n return b;\n }\n if ( key === 'b' ) {\n return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar rivers = data.rivers\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDataTypes.binary":"var dt = ndarrayDataTypes.binary\n","ndarrayDataTypes.boolean":"var dt = ndarrayDataTypes.boolean\n","ndarrayDataTypes.complex32":"var dt = ndarrayDataTypes.complex32\n","ndarrayDataTypes.complex64":"var dt = ndarrayDataTypes.complex64\n","ndarrayDataTypes.complex128":"var dt = ndarrayDataTypes.complex128\n","ndarrayDataTypes.float16":"var dt = ndarrayDataTypes.float16\n","ndarrayDataTypes.float32":"var dt = ndarrayDataTypes.float32\n","ndarrayDataTypes.float64":"var dt = ndarrayDataTypes.float64\n","ndarrayDataTypes.generic":"var dt = ndarrayDataTypes.generic\n","ndarrayDataTypes.int8":"var dt = ndarrayDataTypes.int8\n","ndarrayDataTypes.int16":"var dt = ndarrayDataTypes.int16\n","ndarrayDataTypes.int32":"var dt = ndarrayDataTypes.int32\n","ndarrayDataTypes.uint8":"var dt = ndarrayDataTypes.uint8\n","ndarrayDataTypes.uint8c":"var dt = ndarrayDataTypes.uint8c\n","ndarrayDataTypes.uint16":"var dt = ndarrayDataTypes.uint16\n","ndarrayDataTypes.uint32":"var dt = ndarrayDataTypes.uint32\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\n","ndemptyLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndemptyLike( x )\n","ndfill":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nndfill( x, 10.0 );\nx.get( 0, 0 )\n","ndfillBy":"var opts = { 'dtype': 'float64' };\nvar x = ndzeros( [ 2, 2 ], opts );\nx.get( 0, 0 )\nfunction fcn() { return 10.0; };\nndfillBy( x, fcn );\nx.get( 0, 0 )\nx.get( 0, 1 )\nx.get( 1, 0 )\nx.get( 1, 1 )\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditer2arrayEach":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditer2arrayEach( nditerRows( x ) );\nvar v = it.next().value\nv = it.next().value\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\n","ndzerosLike":"var x = ndzeros( [ 2, 2 ] )\nvar y = ndzerosLike( x )\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbolsIn( obj )\n","noneOwnBy":"function isUnderage( v ) { return ( v < 18 ); };\nvar obj = { 'a': 11, 'b': 12, 'c': 22 };\nvar bool = noneOwnBy( obj, isUnderage )\n","nonIndexKeys":"function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = nonIndexKeys( obj )\n","noop":"noop();\n","now":"var ts = now()\n","NUM_CPUS":"NUM_CPUS\n","num2words":"var out = num2words( 123 )\nout = num2words( 16.31 )\nout = num2words( 123, { 'lang': 'de' } )\n","Number":"var v = new Number( 5 )\n","numel":"var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n","numelDimension":"var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n","numGraphemeClusters":"var out = numGraphemeClusters( 'beep' )\nout = numGraphemeClusters( '🌷' )\n","Object":"var o = new Object( null )\no = new Object( 5.0 )\no = new Object( 'beep' )\n","Object.assign":"var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n console.error( error.message );\n } else {\n close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.arcsine":"var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n","random.arcsine.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.arcsine.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.arcsine.factory":"var fcn = random.arcsine.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.arcsine.PRNG":"var prng = random.arcsine.PRNG;\n","random.arcsine.seed":"var seed = random.arcsine.seed;\n","random.arcsine.seedLength":"var len = random.arcsine.seedLength;\n","random.arcsine.state":"var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.arcsine.state\nout = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\nout = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\nrandom.arcsine.state = state;\nout = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n","random.arcsine.stateLength":"var len = random.arcsine.stateLength;\n","random.arcsine.byteLength":"var sz = random.arcsine.byteLength;\n","random.bernoulli":"var out = random.bernoulli( [ 3, 3 ], 0.5 )\n","random.bernoulli.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.bernoulli.assign( 0.5, out )\nvar bool = ( v === out )\n","random.bernoulli.factory":"var fcn = random.bernoulli.factory();\nvar out = fcn( [ 3, 3 ], 0.5 )\n","random.bernoulli.PRNG":"var prng = random.bernoulli.PRNG;\n","random.bernoulli.seed":"var seed = random.bernoulli.seed;\n","random.bernoulli.seedLength":"var len = random.bernoulli.seedLength;\n","random.bernoulli.state":"var out = random.bernoulli( [ 3, 3 ], 0.5 )\nvar state = random.bernoulli.state\nout = random.bernoulli( [ 3, 3 ], 0.5 )\nout = random.bernoulli( [ 3, 3 ], 0.5 )\nrandom.bernoulli.state = state;\nout = random.bernoulli( [ 3, 3 ], 0.5 )\n","random.bernoulli.stateLength":"var len = random.bernoulli.stateLength;\n","random.bernoulli.byteLength":"var sz = random.bernoulli.byteLength;\n","random.beta":"var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n","random.beta.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.beta.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.beta.factory":"var fcn = random.beta.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.beta.PRNG":"var prng = random.beta.PRNG;\n","random.beta.seed":"var seed = random.beta.seed;\n","random.beta.seedLength":"var len = random.beta.seedLength;\n","random.beta.state":"var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.beta.state\nout = random.beta( [ 3, 3 ], 2.0, 5.0 )\nout = random.beta( [ 3, 3 ], 2.0, 5.0 )\nrandom.beta.state = state;\nout = random.beta( [ 3, 3 ], 2.0, 5.0 )\n","random.beta.stateLength":"var len = random.beta.stateLength;\n","random.beta.byteLength":"var sz = random.beta.byteLength;\n","random.betaprime":"var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n","random.betaprime.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.betaprime.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.betaprime.factory":"var fcn = random.betaprime.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.betaprime.PRNG":"var prng = random.betaprime.PRNG;\n","random.betaprime.seed":"var seed = random.betaprime.seed;\n","random.betaprime.seedLength":"var len = random.betaprime.seedLength;\n","random.betaprime.state":"var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.betaprime.state\nout = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\nout = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\nrandom.betaprime.state = state;\nout = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n","random.betaprime.stateLength":"var len = random.betaprime.stateLength;\n","random.betaprime.byteLength":"var sz = random.betaprime.byteLength;\n","random.binomial":"var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n","random.binomial.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.binomial.assign( 17, 0.5, out )\nvar bool = ( v === out )\n","random.binomial.factory":"var fcn = random.binomial.factory();\nvar out = fcn( [ 3, 3 ], 17, 0.5 )\n","random.binomial.PRNG":"var prng = random.binomial.PRNG;\n","random.binomial.seed":"var seed = random.binomial.seed;\n","random.binomial.seedLength":"var len = random.binomial.seedLength;\n","random.binomial.state":"var out = random.binomial( [ 3, 3 ], 17, 0.5 )\nvar state = random.binomial.state\nout = random.binomial( [ 3, 3 ], 17, 0.5 )\nout = random.binomial( [ 3, 3 ], 17, 0.5 )\nrandom.binomial.state = state;\nout = random.binomial( [ 3, 3 ], 17, 0.5 )\n","random.binomial.stateLength":"var len = random.binomial.stateLength;\n","random.binomial.byteLength":"var sz = random.binomial.byteLength;\n","random.cauchy":"var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n","random.cauchy.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.cauchy.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.cauchy.factory":"var fcn = random.cauchy.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.cauchy.PRNG":"var prng = random.cauchy.PRNG;\n","random.cauchy.seed":"var seed = random.cauchy.seed;\n","random.cauchy.seedLength":"var len = random.cauchy.seedLength;\n","random.cauchy.state":"var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.cauchy.state\nout = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\nout = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\nrandom.cauchy.state = state;\nout = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n","random.cauchy.stateLength":"var len = random.cauchy.stateLength;\n","random.cauchy.byteLength":"var sz = random.cauchy.byteLength;\n","random.chi":"var out = random.chi( [ 3, 3 ], 2.0 )\n","random.chi.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.chi.assign( 2.0, out )\nvar bool = ( v === out )\n","random.chi.factory":"var fcn = random.chi.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.chi.PRNG":"var prng = random.chi.PRNG;\n","random.chi.seed":"var seed = random.chi.seed;\n","random.chi.seedLength":"var len = random.chi.seedLength;\n","random.chi.state":"var out = random.chi( [ 3, 3 ], 2.0 )\nvar state = random.chi.state\nout = random.chi( [ 3, 3 ], 2.0 )\nout = random.chi( [ 3, 3 ], 2.0 )\nrandom.chi.state = state;\nout = random.chi( [ 3, 3 ], 2.0 )\n","random.chi.stateLength":"var len = random.chi.stateLength;\n","random.chi.byteLength":"var sz = random.chi.byteLength;\n","random.chisquare":"var out = random.chisquare( [ 3, 3 ], 2.0 )\n","random.chisquare.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.chisquare.assign( 2.0, out )\nvar bool = ( v === out )\n","random.chisquare.factory":"var fcn = random.chisquare.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.chisquare.PRNG":"var prng = random.chisquare.PRNG;\n","random.chisquare.seed":"var seed = random.chisquare.seed;\n","random.chisquare.seedLength":"var len = random.chisquare.seedLength;\n","random.chisquare.state":"var out = random.chisquare( [ 3, 3 ], 2.0 )\nvar state = random.chisquare.state\nout = random.chisquare( [ 3, 3 ], 2.0 )\nout = random.chisquare( [ 3, 3 ], 2.0 )\nrandom.chisquare.state = state;\nout = random.chisquare( [ 3, 3 ], 2.0 )\n","random.chisquare.stateLength":"var len = random.chisquare.stateLength;\n","random.chisquare.byteLength":"var sz = random.chisquare.byteLength;\n","random.cosine":"var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n","random.cosine.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.cosine.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.cosine.factory":"var fcn = random.cosine.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.cosine.PRNG":"var prng = random.cosine.PRNG;\n","random.cosine.seed":"var seed = random.cosine.seed;\n","random.cosine.seedLength":"var len = random.cosine.seedLength;\n","random.cosine.state":"var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.cosine.state\nout = random.cosine( [ 3, 3 ], 2.0, 5.0 )\nout = random.cosine( [ 3, 3 ], 2.0, 5.0 )\nrandom.cosine.state = state;\nout = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n","random.cosine.stateLength":"var len = random.cosine.stateLength;\n","random.cosine.byteLength":"var sz = random.cosine.byteLength;\n","random.discreteUniform":"var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n","random.discreteUniform.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.discreteUniform.assign( -10, 10, out )\nvar bool = ( v === out )\n","random.discreteUniform.factory":"var fcn = random.discreteUniform.factory();\nvar out = fcn( [ 3, 3 ], -10, 10 )\n","random.discreteUniform.PRNG":"var prng = random.discreteUniform.PRNG;\n","random.discreteUniform.seed":"var seed = random.discreteUniform.seed;\n","random.discreteUniform.seedLength":"var len = random.discreteUniform.seedLength;\n","random.discreteUniform.state":"var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\nvar state = random.discreteUniform.state\nout = random.discreteUniform( [ 3, 3 ], -10, 10 )\nout = random.discreteUniform( [ 3, 3 ], -10, 10 )\nrandom.discreteUniform.state = state;\nout = random.discreteUniform( [ 3, 3 ], -10, 10 )\n","random.discreteUniform.stateLength":"var len = random.discreteUniform.stateLength;\n","random.discreteUniform.byteLength":"var sz = random.discreteUniform.byteLength;\n","random.erlang":"var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n","random.erlang.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.erlang.assign( 2, 5.0, out )\nvar bool = ( v === out )\n","random.erlang.factory":"var fcn = random.erlang.factory();\nvar out = fcn( [ 3, 3 ], 2, 5.0 )\n","random.erlang.PRNG":"var prng = random.erlang.PRNG;\n","random.erlang.seed":"var seed = random.erlang.seed;\n","random.erlang.seedLength":"var len = random.erlang.seedLength;\n","random.erlang.state":"var out = random.erlang( [ 3, 3 ], 2, 5.0 )\nvar state = random.erlang.state\nout = random.erlang( [ 3, 3 ], 2, 5.0 )\nout = random.erlang( [ 3, 3 ], 2, 5.0 )\nrandom.erlang.state = state;\nout = random.erlang( [ 3, 3 ], 2, 5.0 )\n","random.erlang.stateLength":"var len = random.erlang.stateLength;\n","random.erlang.byteLength":"var sz = random.erlang.byteLength;\n","random.exponential":"var out = random.exponential( [ 3, 3 ], 2.0 )\n","random.exponential.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.exponential.assign( 2.0, out )\nvar bool = ( v === out )\n","random.exponential.factory":"var fcn = random.exponential.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.exponential.PRNG":"var prng = random.exponential.PRNG;\n","random.exponential.seed":"var seed = random.exponential.seed;\n","random.exponential.seedLength":"var len = random.exponential.seedLength;\n","random.exponential.state":"var out = random.exponential( [ 3, 3 ], 2.0 )\nvar state = random.exponential.state\nout = random.exponential( [ 3, 3 ], 2.0 )\nout = random.exponential( [ 3, 3 ], 2.0 )\nrandom.exponential.state = state;\nout = random.exponential( [ 3, 3 ], 2.0 )\n","random.exponential.stateLength":"var len = random.exponential.stateLength;\n","random.exponential.byteLength":"var sz = random.exponential.byteLength;\n","random.f":"var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n","random.f.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.f.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.f.factory":"var fcn = random.f.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.f.PRNG":"var prng = random.f.PRNG;\n","random.f.seed":"var seed = random.f.seed;\n","random.f.seedLength":"var len = random.f.seedLength;\n","random.f.state":"var out = random.f( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.f.state\nout = random.f( [ 3, 3 ], 2.0, 5.0 )\nout = random.f( [ 3, 3 ], 2.0, 5.0 )\nrandom.f.state = state;\nout = random.f( [ 3, 3 ], 2.0, 5.0 )\n","random.f.stateLength":"var len = random.f.stateLength;\n","random.f.byteLength":"var sz = random.f.byteLength;\n","random.frechet":"var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.frechet.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.frechet.assign( 2.0, 5.0, 3.0, out )\nvar bool = ( v === out )\n","random.frechet.factory":"var fcn = random.frechet.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.frechet.PRNG":"var prng = random.frechet.PRNG;\n","random.frechet.seed":"var seed = random.frechet.seed;\n","random.frechet.seedLength":"var len = random.frechet.seedLength;\n","random.frechet.state":"var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\nvar state = random.frechet.state\nout = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\nout = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\nrandom.frechet.state = state;\nout = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.frechet.stateLength":"var len = random.frechet.stateLength;\n","random.frechet.byteLength":"var sz = random.frechet.byteLength;\n","random.gamma":"var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n","random.gamma.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.gamma.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.gamma.factory":"var fcn = random.gamma.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.gamma.PRNG":"var prng = random.gamma.PRNG;\n","random.gamma.seed":"var seed = random.gamma.seed;\n","random.gamma.seedLength":"var len = random.gamma.seedLength;\n","random.gamma.state":"var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.gamma.state\nout = random.gamma( [ 3, 3 ], 2.0, 5.0 )\nout = random.gamma( [ 3, 3 ], 2.0, 5.0 )\nrandom.gamma.state = state;\nout = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n","random.gamma.stateLength":"var len = random.gamma.stateLength;\n","random.gamma.byteLength":"var sz = random.gamma.byteLength;\n","random.geometric":"var out = random.geometric( [ 3, 3 ], 0.01 )\n","random.geometric.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.geometric.assign( 0.01, out )\nvar bool = ( v === out )\n","random.geometric.factory":"var fcn = random.geometric.factory();\nvar out = fcn( [ 3, 3 ], 0.01 )\n","random.geometric.PRNG":"var prng = random.geometric.PRNG;\n","random.geometric.seed":"var seed = random.geometric.seed;\n","random.geometric.seedLength":"var len = random.geometric.seedLength;\n","random.geometric.state":"var out = random.geometric( [ 3, 3 ], 0.01 )\nvar state = random.geometric.state\nout = random.geometric( [ 3, 3 ], 0.01 )\nout = random.geometric( [ 3, 3 ], 0.01 )\nrandom.geometric.state = state;\nout = random.geometric( [ 3, 3 ], 0.01 )\n","random.geometric.stateLength":"var len = random.geometric.stateLength;\n","random.geometric.byteLength":"var sz = random.geometric.byteLength;\n","random.gumbel":"var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n","random.gumbel.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.gumbel.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.gumbel.factory":"var fcn = random.gumbel.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.gumbel.PRNG":"var prng = random.gumbel.PRNG;\n","random.gumbel.seed":"var seed = random.gumbel.seed;\n","random.gumbel.seedLength":"var len = random.gumbel.seedLength;\n","random.gumbel.state":"var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.gumbel.state\nout = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\nout = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\nrandom.gumbel.state = state;\nout = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n","random.gumbel.stateLength":"var len = random.gumbel.stateLength;\n","random.gumbel.byteLength":"var sz = random.gumbel.byteLength;\n","random.hypergeometric":"var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n","random.hypergeometric.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.hypergeometric.assign( 20, 10, 7, out )\nvar bool = ( v === out )\n","random.hypergeometric.factory":"var fcn = random.hypergeometric.factory();\nvar out = fcn( [ 3, 3 ], 20, 10, 7 )\n","random.hypergeometric.PRNG":"var prng = random.hypergeometric.PRNG;\n","random.hypergeometric.seed":"var seed = random.hypergeometric.seed;\n","random.hypergeometric.seedLength":"var len = random.hypergeometric.seedLength;\n","random.hypergeometric.state":"var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\nvar state = random.hypergeometric.state\nout = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\nout = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\nrandom.hypergeometric.state = state;\nout = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n","random.hypergeometric.stateLength":"var len = random.hypergeometric.stateLength;\n","random.hypergeometric.byteLength":"var sz = random.hypergeometric.byteLength;\n","random.invgamma":"var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n","random.invgamma.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.invgamma.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.invgamma.factory":"var fcn = random.invgamma.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.invgamma.PRNG":"var prng = random.invgamma.PRNG;\n","random.invgamma.seed":"var seed = random.invgamma.seed;\n","random.invgamma.seedLength":"var len = random.invgamma.seedLength;\n","random.invgamma.state":"var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.invgamma.state\nout = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\nout = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\nrandom.invgamma.state = state;\nout = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n","random.invgamma.stateLength":"var len = random.invgamma.stateLength;\n","random.invgamma.byteLength":"var sz = random.invgamma.byteLength;\n","random.kumaraswamy":"var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n","random.kumaraswamy.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.kumaraswamy.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.kumaraswamy.factory":"var fcn = random.kumaraswamy.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.kumaraswamy.PRNG":"var prng = random.kumaraswamy.PRNG;\n","random.kumaraswamy.seed":"var seed = random.kumaraswamy.seed;\n","random.kumaraswamy.seedLength":"var len = random.kumaraswamy.seedLength;\n","random.kumaraswamy.state":"var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.kumaraswamy.state\nout = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\nout = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\nrandom.kumaraswamy.state = state;\nout = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n","random.kumaraswamy.stateLength":"var len = random.kumaraswamy.stateLength;\n","random.kumaraswamy.byteLength":"var sz = random.kumaraswamy.byteLength;\n","random.laplace":"var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n","random.laplace.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.laplace.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.laplace.factory":"var fcn = random.laplace.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.laplace.PRNG":"var prng = random.laplace.PRNG;\n","random.laplace.seed":"var seed = random.laplace.seed;\n","random.laplace.seedLength":"var len = random.laplace.seedLength;\n","random.laplace.state":"var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.laplace.state\nout = random.laplace( [ 3, 3 ], 2.0, 5.0 )\nout = random.laplace( [ 3, 3 ], 2.0, 5.0 )\nrandom.laplace.state = state;\nout = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n","random.laplace.stateLength":"var len = random.laplace.stateLength;\n","random.laplace.byteLength":"var sz = random.laplace.byteLength;\n","random.levy":"var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n","random.levy.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.levy.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.levy.factory":"var fcn = random.levy.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.levy.PRNG":"var prng = random.levy.PRNG;\n","random.levy.seed":"var seed = random.levy.seed;\n","random.levy.seedLength":"var len = random.levy.seedLength;\n","random.levy.state":"var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.levy.state\nout = random.levy( [ 3, 3 ], 2.0, 5.0 )\nout = random.levy( [ 3, 3 ], 2.0, 5.0 )\nrandom.levy.state = state;\nout = random.levy( [ 3, 3 ], 2.0, 5.0 )\n","random.levy.stateLength":"var len = random.levy.stateLength;\n","random.levy.byteLength":"var sz = random.levy.byteLength;\n","random.logistic":"var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n","random.logistic.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.logistic.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.logistic.factory":"var fcn = random.logistic.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.logistic.PRNG":"var prng = random.logistic.PRNG;\n","random.logistic.seed":"var seed = random.logistic.seed;\n","random.logistic.seedLength":"var len = random.logistic.seedLength;\n","random.logistic.state":"var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.logistic.state\nout = random.logistic( [ 3, 3 ], 2.0, 5.0 )\nout = random.logistic( [ 3, 3 ], 2.0, 5.0 )\nrandom.logistic.state = state;\nout = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n","random.logistic.stateLength":"var len = random.logistic.stateLength;\n","random.logistic.byteLength":"var sz = random.logistic.byteLength;\n","random.lognormal":"var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n","random.lognormal.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.lognormal.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.lognormal.factory":"var fcn = random.lognormal.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.lognormal.PRNG":"var prng = random.lognormal.PRNG;\n","random.lognormal.seed":"var seed = random.lognormal.seed;\n","random.lognormal.seedLength":"var len = random.lognormal.seedLength;\n","random.lognormal.state":"var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.lognormal.state\nout = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\nout = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\nrandom.lognormal.state = state;\nout = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n","random.lognormal.stateLength":"var len = random.lognormal.stateLength;\n","random.lognormal.byteLength":"var sz = random.lognormal.byteLength;\n","random.negativeBinomial":"var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n","random.negativeBinomial.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.negativeBinomial.assign( 17, 0.5, out )\nvar bool = ( v === out )\n","random.negativeBinomial.factory":"var fcn = random.negativeBinomial.factory();\nvar out = fcn( [ 3, 3 ], 17, 0.5 )\n","random.negativeBinomial.PRNG":"var prng = random.negativeBinomial.PRNG;\n","random.negativeBinomial.seed":"var seed = random.negativeBinomial.seed;\n","random.negativeBinomial.seedLength":"var len = random.negativeBinomial.seedLength;\n","random.negativeBinomial.state":"var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\nvar state = random.negativeBinomial.state\nout = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\nout = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\nrandom.negativeBinomial.state = state;\nout = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n","random.negativeBinomial.stateLength":"var len = random.negativeBinomial.stateLength;\n","random.negativeBinomial.byteLength":"var sz = random.negativeBinomial.byteLength;\n","random.normal":"var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n","random.normal.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.normal.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.normal.factory":"var fcn = random.normal.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.normal.PRNG":"var prng = random.normal.PRNG;\n","random.normal.seed":"var seed = random.normal.seed;\n","random.normal.seedLength":"var len = random.normal.seedLength;\n","random.normal.state":"var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.normal.state\nout = random.normal( [ 3, 3 ], 2.0, 5.0 )\nout = random.normal( [ 3, 3 ], 2.0, 5.0 )\nrandom.normal.state = state;\nout = random.normal( [ 3, 3 ], 2.0, 5.0 )\n","random.normal.stateLength":"var len = random.normal.stateLength;\n","random.normal.byteLength":"var sz = random.normal.byteLength;\n","random.pareto1":"var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n","random.pareto1.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.pareto1.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.pareto1.factory":"var fcn = random.pareto1.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.pareto1.PRNG":"var prng = random.pareto1.PRNG;\n","random.pareto1.seed":"var seed = random.pareto1.seed;\n","random.pareto1.seedLength":"var len = random.pareto1.seedLength;\n","random.pareto1.state":"var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.pareto1.state\nout = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\nout = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\nrandom.pareto1.state = state;\nout = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n","random.pareto1.stateLength":"var len = random.pareto1.stateLength;\n","random.pareto1.byteLength":"var sz = random.pareto1.byteLength;\n","random.poisson":"var out = random.poisson( [ 3, 3 ], 2.0 )\n","random.poisson.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.poisson.assign( 2.0, out )\nvar bool = ( v === out )\n","random.poisson.factory":"var fcn = random.poisson.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.poisson.PRNG":"var prng = random.poisson.PRNG;\n","random.poisson.seed":"var seed = random.poisson.seed;\n","random.poisson.seedLength":"var len = random.poisson.seedLength;\n","random.poisson.state":"var out = random.poisson( [ 3, 3 ], 2.0 )\nvar state = random.poisson.state\nout = random.poisson( [ 3, 3 ], 2.0 )\nout = random.poisson( [ 3, 3 ], 2.0 )\nrandom.poisson.state = state;\nout = random.poisson( [ 3, 3 ], 2.0 )\n","random.poisson.stateLength":"var len = random.poisson.stateLength;\n","random.poisson.byteLength":"var sz = random.poisson.byteLength;\n","random.rayleigh":"var out = random.rayleigh( [ 3, 3 ], 2.0 )\n","random.rayleigh.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.rayleigh.assign( 2.0, out )\nvar bool = ( v === out )\n","random.rayleigh.factory":"var fcn = random.rayleigh.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.rayleigh.PRNG":"var prng = random.rayleigh.PRNG;\n","random.rayleigh.seed":"var seed = random.rayleigh.seed;\n","random.rayleigh.seedLength":"var len = random.rayleigh.seedLength;\n","random.rayleigh.state":"var out = random.rayleigh( [ 3, 3 ], 2.0 )\nvar state = random.rayleigh.state\nout = random.rayleigh( [ 3, 3 ], 2.0 )\nout = random.rayleigh( [ 3, 3 ], 2.0 )\nrandom.rayleigh.state = state;\nout = random.rayleigh( [ 3, 3 ], 2.0 )\n","random.rayleigh.stateLength":"var len = random.rayleigh.stateLength;\n","random.rayleigh.byteLength":"var sz = random.rayleigh.byteLength;\n","random.t":"var out = random.t( [ 3, 3 ], 2.0 )\n","random.t.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.t.assign( 2.0, out )\nvar bool = ( v === out )\n","random.t.factory":"var fcn = random.t.factory();\nvar out = fcn( [ 3, 3 ], 2.0 )\n","random.t.PRNG":"var prng = random.t.PRNG;\n","random.t.seed":"var seed = random.t.seed;\n","random.t.seedLength":"var len = random.t.seedLength;\n","random.t.state":"var out = random.t( [ 3, 3 ], 2.0 )\nvar state = random.t.state\nout = random.t( [ 3, 3 ], 2.0 )\nout = random.t( [ 3, 3 ], 2.0 )\nrandom.t.state = state;\nout = random.t( [ 3, 3 ], 2.0 )\n","random.t.stateLength":"var len = random.t.stateLength;\n","random.t.byteLength":"var sz = random.t.byteLength;\n","random.triangular":"var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.triangular.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.triangular.assign( 2.0, 5.0, 3.0, out )\nvar bool = ( v === out )\n","random.triangular.factory":"var fcn = random.triangular.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.triangular.PRNG":"var prng = random.triangular.PRNG;\n","random.triangular.seed":"var seed = random.triangular.seed;\n","random.triangular.seedLength":"var len = random.triangular.seedLength;\n","random.triangular.state":"var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\nvar state = random.triangular.state\nout = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\nout = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\nrandom.triangular.state = state;\nout = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n","random.triangular.stateLength":"var len = random.triangular.stateLength;\n","random.triangular.byteLength":"var sz = random.triangular.byteLength;\n","random.uniform":"var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n","random.uniform.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.uniform.assign( 0.0, 1.0, out )\nvar bool = ( v === out )\n","random.uniform.factory":"var fcn = random.uniform.factory();\nvar out = fcn( [ 3, 3 ], 0.0, 1.0 )\n","random.uniform.PRNG":"var prng = random.uniform.PRNG;\n","random.uniform.seed":"var seed = random.uniform.seed;\n","random.uniform.seedLength":"var len = random.uniform.seedLength;\n","random.uniform.state":"var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\nvar state = random.uniform.state\nout = random.uniform( [ 3, 3 ], 0.0, 1.0 )\nout = random.uniform( [ 3, 3 ], 0.0, 1.0 )\nrandom.uniform.state = state;\nout = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n","random.uniform.stateLength":"var len = random.uniform.stateLength;\n","random.uniform.byteLength":"var sz = random.uniform.byteLength;\n","random.weibull":"var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n","random.weibull.assign":"var out = ndzeros( [ 3, 3 ] );\nvar v = random.weibull.assign( 2.0, 5.0, out )\nvar bool = ( v === out )\n","random.weibull.factory":"var fcn = random.weibull.factory();\nvar out = fcn( [ 3, 3 ], 2.0, 5.0 )\n","random.weibull.PRNG":"var prng = random.weibull.PRNG;\n","random.weibull.seed":"var seed = random.weibull.seed;\n","random.weibull.seedLength":"var len = random.weibull.seedLength;\n","random.weibull.state":"var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\nvar state = random.weibull.state\nout = random.weibull( [ 3, 3 ], 2.0, 5.0 )\nout = random.weibull( [ 3, 3 ], 2.0, 5.0 )\nrandom.weibull.state = state;\nout = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n","random.weibull.stateLength":"var len = random.weibull.stateLength;\n","random.weibull.byteLength":"var sz = random.weibull.byteLength;\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr = [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n acc.sum += value;\n next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n console.log( path );\n next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n console.error( error.message );\n } else {\n console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","rtrimN":"var out = rtrimN( ' abc ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n console.log( value );\n next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n","trues":"var arr = trues( [ 2, 2 ] )\n","truesLike":"var opts = { 'dtype': 'generic' };\nvar x = ndempty( [ 2, 2 ], opts )\nvar y = truesLike( x )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedVector":"var arr = Uint8ClampedVector()\nvar arr = Uint8ClampedVector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint8ClampedVector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint8ClampedVector( buf, 0, 4 )\nvar len = numel( arr )\n","Uint8Vector":"var arr = Uint8Vector()\nvar arr = Uint8Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint8Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint8Vector( buf, 0, 4 )\nvar len = numel( arr )\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Vector":"var arr = Uint16Vector()\nvar arr = Uint16Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint16Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint16Vector( buf, 0, 4 )\nvar len = numel( arr )\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Vector":"var arr = Uint32Vector()\nvar arr = Uint32Vector( 5 )\nvar len = numel( arr )\nvar v = [ 1, 2, 3 ];\nvar arr = Uint32Vector( v )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = Uint32Vector( buf, 0, 4 )\nvar len = numel( arr )\n","Uint64":"var x = new Uint64( 5 )\nx.toString()\n","Uint64.name":"var str = Uint64.name\n","Uint64.from":"var v = Uint64.from( [ 1234, 5678 ] )\n","Uint64.of":"var v = Uint64.of( 1234, 5678 )\n","Uint64.BYTES_PER_ELEMENT":"var s = Uint64.BYTES_PER_ELEMENT\n","Uint64.prototype.BYTES_PER_ELEMENT":"var x = new Uint64( 5 )\nvar s = x.BYTES_PER_ELEMENT\n","Uint64.prototype.byteLength":"var x = new Uint64( 5 )\nvar s = x.byteLength\n","Uint64.prototype.hi":"var x = Uint64.from( [ 1234, 5678 ] )\nvar w = x.hi\n","Uint64.prototype.lo":"var x = Uint64.from( [ 1234, 5678 ] )\nvar w = x.lo\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","vector":"var arr = vector()\nvar dt = ndarrayDataType( arr )\narr = vector( 'float32' )\ndt = ndarrayDataType( arr )\nvar arr = vector( 5 )\nvar dt = ndarrayDataType( arr )\nvar len = numel( arr )\narr = vector( 5, 'float32' )\ndt = ndarrayDataType( arr )\nlen = numel( arr )\nvar v = [ 0.5, 0.5, 0.5 ];\nvar arr = vector( v, 'float32' )\nvar dt = ndarrayDataType( arr )\nvar len = numel( arr )\nvar buf = new ArrayBuffer( 32 );\nvar arr = vector( buf, 0, 4, 'float32' )\nvar dt = ndarrayDataType( arr )\nvar len = numel( arr )\n","vector.factory":"var f = vector.factory( 'float32' );\nvar arr = f()\nvar dt = ndarrayDataType( arr )\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"} diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv index 071dcc24d86a..1bfca4ecb6b2 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.csv +++ b/lib/node_modules/@stdlib/repl/help/data/data.csv @@ -81,12 +81,12 @@ arrayStream.objectMode,"\narrayStream.objectMode( src[, options] )\n Returns arrayview2iterator,"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n" arrayview2iteratorRight,"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n" aslice,"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n" -AsyncIteratorSymbol,"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n" +AsyncIteratorSymbol,"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n e.g., \n\n See Also\n --------\n Symbol, IteratorSymbol\n" atake,"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aput, aslice\n" azeros,"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n" -azerosLike,"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n" +azerosLike,"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n" azeroTo,"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n" -azeroToLike,"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n" +azeroToLike,"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n" bartlettTest,"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n" base.abs,"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n" base.abs2,"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n" @@ -1780,8 +1780,8 @@ base.strided.dmeanvarpn,"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strid base.strided.dmeanvarpn.ndarray,"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn" base.strided.dmeanwd,"\nbase.strided.dmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n" base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd" -base.strided.dmediansorted,"\nbase.strided.dmediansorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n" -base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted" +base.strided.dmedianSorted,"\nbase.strided.dmedianSorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmedianSorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmedianSorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmedianSorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmedianSorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n" +base.strided.dmedianSorted.ndarray,"\nbase.strided.dmedianSorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted" base.strided.dmidrange,"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n" base.strided.dmidrange.ndarray,"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange" base.strided.dmin,"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n" @@ -2129,8 +2129,8 @@ base.strided.meanpw,"\nbase.strided.meanpw( N, x, strideX )\n Computes the ar base.strided.meanpw.ndarray,"\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw" base.strided.meanwd,"\nbase.strided.meanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n" base.strided.meanwd.ndarray,"\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd" -base.strided.mediansorted,"\nbase.strided.mediansorted( N, x, strideX )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n" -base.strided.mediansorted.ndarray,"\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted" +base.strided.mediansorted,"\nbase.strided.mediansorted( N, x, strideX )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mean, base.strided.smediansorted\n" +base.strided.mediansorted.ndarray,"\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mean, base.strided.smediansorted" base.strided.metaDataProps,"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n\n Parameters\n ----------\n meta: Object\n Function meta data.\n\n meta.nargs: integer\n Total number of arguments (excluding offsets).\n\n meta.nin: integer\n Total number of input arrays.\n\n meta.nout: integer\n Total number of output arrays.\n\n dtypes: ArrayLikeObject\n List of strided array data types.\n\n obj: Object|Function\n Object on which to define properties.\n\n bool: boolean\n Boolean indicating whether the provided object should describe an\n \"ndarray\" function interface.\n\n Returns\n -------\n out: Object|Function\n Object on which properties were defined.\n\n Examples\n --------\n > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n > var dt = [ 'float64', 'float64' ];\n > var obj = {};\n > base.strided.metaDataProps( meta, dt, obj, false );\n > obj.nargs\n 7\n > obj.nin\n 1\n > obj.nout\n 1\n > obj.types\n [...]\n\n" base.strided.min,"\nbase.strided.min( N, x, strideX )\n Computes the minimum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.min( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.min( 3, x1, 2 )\n -2.0\n\n\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n" base.strided.min.ndarray,"\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin" @@ -2327,8 +2327,8 @@ base.strided.smeanpw,"\nbase.strided.smeanpw( N, x, strideX )\n Computes the base.strided.smeanpw.ndarray,"\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean" base.strided.smeanwd,"\nbase.strided.smeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n" base.strided.smeanwd.ndarray,"\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd" -base.strided.smediansorted,"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n" -base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean" +base.strided.smediansorted,"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mediansorted, base.strided.smean\n" +base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mediansorted, base.strided.smean" base.strided.smidrange,"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n" base.strided.smidrange.ndarray,"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange" base.strided.smin,"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n" @@ -3486,6 +3486,15 @@ Int32Array.prototype.toString,"\nInt32Array.prototype.toString()\n Serializes Int32Array.prototype.values,"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray" Int32Matrix,"\nInt32Matrix( [options] )\n Returns a two-dimensional 32-bit signed integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix()\n \n\n\nInt32Matrix( shape[, options] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix( [ 2, 2 ] )\n \n\n\nInt32Matrix( M, N[, options] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix( 2, 2 )\n \n\n\nInt32Matrix( obj[, options] )\n Creates a two-dimensional 32-bit signed integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1, 2 ], [ 3, 4 ] ];\n > var arr = Int32Matrix( v )\n \n\n\nInt32Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Matrix( buf, 0, [ 8, 1 ] )\n \n\n\nInt32Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Matrix( buf, 0, 8, 1 )\n \n\n See Also\n --------\n Float64Matrix, Float32Matrix, Complex128Matrix, Complex64Matrix, matrix, Int32Vector, ndarray\n" Int32Vector,"\nInt32Vector( [options] )\n Returns a one-dimensional signed 32-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Vector()\n \n\n\nInt32Vector( length[, options] )\n Returns a one-dimensional signed 32-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nInt32Vector( obj[, options] )\n Creates a one-dimensional signed 32-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Int32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nInt32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional signed 32-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int8Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, Int32Matrix, ndarray\n" +Int64,"\nInt64( value )\n 64-bit signed integer constructor.\n\n Parameters\n ----------\n value: integer|bigint\n Integer value.\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > x.toString()\n '5'\n\n\nInt64.name\n Constructor name.\n\n Examples\n --------\n > var str = Int64.name\n 'Int64'\n\n\nInt64.from( words )\n Creates a new 64-bit signed integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.from( [ 1234, 5678 ] )\n \n\n\nInt64.of( high, low )\n Creates a new 64-bit signed integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.of( 1234, 5678 )\n \n\n\nInt64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Int64.BYTES_PER_ELEMENT\n 8\n\n\nInt64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8\n\n\nInt64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.byteLength\n 8\n\n\nInt64.prototype.hi\n Returns the high 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234\n\n\nInt64.prototype.lo\n Returns the low 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Uint64\n" +Int64.name,"\nInt64.name\n Constructor name.\n\n Examples\n --------\n > var str = Int64.name\n 'Int64'" +Int64.from,"\nInt64.from( words )\n Creates a new 64-bit signed integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.from( [ 1234, 5678 ] )\n " +Int64.of,"\nInt64.of( high, low )\n Creates a new 64-bit signed integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.of( 1234, 5678 )\n " +Int64.BYTES_PER_ELEMENT,"\nInt64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Int64.BYTES_PER_ELEMENT\n 8" +Int64.prototype.BYTES_PER_ELEMENT,"\nInt64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8" +Int64.prototype.byteLength,"\nInt64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.byteLength\n 8" +Int64.prototype.hi,"\nInt64.prototype.hi\n Returns the high 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234" +Int64.prototype.lo,"\nInt64.prototype.lo\n Returns the low 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Uint64" IS_BIG_ENDIAN,"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n" IS_BROWSER,"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n" IS_DARWIN,"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n" @@ -3878,7 +3887,7 @@ iterator2arrayviewRight,"\niterator2arrayviewRight( iterator, dest[, begin[, end iteratorStream,"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n" iteratorStream.factory,"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );" iteratorStream.objectMode,"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream" -IteratorSymbol,"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n" +IteratorSymbol,"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n e.g., \n\n See Also\n --------\n Symbol\n" iterAvercos,"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n" iterAversin,"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n" iterawgn,"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n" @@ -5057,9 +5066,9 @@ random.beta.seedLength,"\nrandom.beta.seedLength\n Length of generator seed.\ random.beta.state,"\nrandom.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.beta.state\n \n\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n " random.beta.stateLength,"\nrandom.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.beta.stateLength;" random.beta.byteLength,"\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.array.beta, random.strided.beta" -random.betaprime,"\nrandom.betaprime( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a betaprime\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a betaprime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n betaprime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.betaprime.PRNG;\n\n\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.betaprime.seed;\n\n\nrandom.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.betaprime.seedLength;\n\n\nrandom.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.betaprime.state\n \n\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.betaprime.stateLength;\n\n\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime, random.strided.betaprime\n" -random.betaprime.assign,"\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a betaprime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true" -random.betaprime.factory,"\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n betaprime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n " +random.betaprime,"\nrandom.betaprime( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.betaprime.PRNG;\n\n\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.betaprime.seed;\n\n\nrandom.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.betaprime.seedLength;\n\n\nrandom.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.betaprime.state\n \n\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.betaprime.stateLength;\n\n\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime, random.strided.betaprime\n" +random.betaprime.assign,"\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true" +random.betaprime.factory,"\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n " random.betaprime.PRNG,"\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.betaprime.PRNG;" random.betaprime.seed,"\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.betaprime.seed;" random.betaprime.seedLength,"\nrandom.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.betaprime.seedLength;" @@ -5636,7 +5645,7 @@ substringBefore,"\nsubstringBefore( str, search )\n Returns the part of a str substringBeforeLast,"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast" SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n" SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK,"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n" -Symbol,"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n" +Symbol,"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n e.g., \n\n" tabulate,"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n" tabulateBy,"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n" tabulateByAsync,"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n" @@ -5830,7 +5839,7 @@ Uint32Array.prototype.toLocaleString,"\nUint32Array.prototype.toLocaleString( [l Uint32Array.prototype.toString,"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'" Uint32Array.prototype.values,"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray" Uint32Vector,"\nUint32Vector( [options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint32Vector()\n \n\n\nUint32Vector( length[, options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint32Vector( obj[, options] )\n Creates a one-dimensional unsigned 32-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n" -Uint64,"\nUint64( value )\n 64-bit unsigned integer constructor.\n\n Parameters\n ----------\n value: number|bigint\n Integer value.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > x.toString()\n '5'\n\n\nUint64.name\n Constructor name.\n\n Examples\n --------\n > var str = Uint64.name\n 'Uint64'\n\n\nUint64.from( words )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.from( [ 1234, 5678 ] )\n \n\n\nUint64.of( high, low )\n Creates a new 64-bit unsigned integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.of( 1234, 5678 )\n \n\n\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Uint64.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.byteLength\n 8\n\n\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234\n\n\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n Number\n" +Uint64,"\nUint64( value )\n 64-bit unsigned integer constructor.\n\n Parameters\n ----------\n value: integer|bigint\n Integer value.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > x.toString()\n '5'\n\n\nUint64.name\n Constructor name.\n\n Examples\n --------\n > var str = Uint64.name\n 'Uint64'\n\n\nUint64.from( words )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.from( [ 1234, 5678 ] )\n \n\n\nUint64.of( high, low )\n Creates a new 64-bit unsigned integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.of( 1234, 5678 )\n \n\n\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Uint64.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.byteLength\n 8\n\n\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234\n\n\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Int64\n" Uint64.name,"\nUint64.name\n Constructor name.\n\n Examples\n --------\n > var str = Uint64.name\n 'Uint64'" Uint64.from,"\nUint64.from( words )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.from( [ 1234, 5678 ] )\n " Uint64.of,"\nUint64.of( high, low )\n Creates a new 64-bit unsigned integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.of( 1234, 5678 )\n " @@ -5838,7 +5847,7 @@ Uint64.BYTES_PER_ELEMENT,"\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the Uint64.prototype.BYTES_PER_ELEMENT,"\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8" Uint64.prototype.byteLength,"\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.byteLength\n 8" Uint64.prototype.hi,"\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234" -Uint64.prototype.lo,"\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n Number" +Uint64.prototype.lo,"\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Int64" umask,"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - +: enable\n - -: disable\n - =: enable specified and disable unspecified permissions\n\n For example,\n\n - u-w: disable user write permissions\n - u+w: enable user write permissions\n - u=w: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n" uncapitalize,"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n" uncapitalizeKeys,"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n" diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json index fc67c50b68bc..6e06453d57dd 100644 --- a/lib/node_modules/@stdlib/repl/help/data/data.json +++ b/lib/node_modules/@stdlib/repl/help/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x[, options] )\n Computes the absolute value for each element in an ndarray.\n\n The function returns an ndarray having the same shape as the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Output array data type. Must be a real-valued or \"generic\" data type.\n\n options.order: string (optional)\n Output array order. Must be either row-major (C-style) or column-major\n (Fortran-style). By default, the order of the output array is the same\n as the input array.\n\n Returns\n -------\n y: ndarray\n Output array containing element-wise results.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var y = abs( x )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n\n\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of falsy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of falsy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is falsy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of falsy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of falsy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of falsy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: the value of the current property being processed in the object\n - key: the key of the current property being processed in the object\n - object: the input object\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate. It must be non-null.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any value; otherwise, it returns `false`.\n\n Examples\n --------\n > function isNegative(value) { return value < 0 }\n > var obj = { a: 1, b: -2, c: 3, d: 4 }\n > var result = anyInBy(obj, isNegative)\n true\n\n See Also\n --------\n anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return\n value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for one own property; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n > var bool = anyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of truthy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of truthy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is truthy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of truthy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of truthy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of truthy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","aput":"\naput( x, indices, values[, options] )\n Replaces specified elements of an array with provided values.\n\n The function supports broadcasting a `values` array containing a single\n element against an `indices` array containing one or more elements.\n\n The function mutates the input array.\n\n Because each index is only validated at the time of replacing a particular\n element, mutation may occur even when one or more indices are out-of-bounds,\n including when the index mode indicates to raise an exception.\n\n If `indices` is an empty array, the function returns the input array\n unchanged.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n values: ArrayLikeObject\n Values to set. When `indices` contains one or more elements, `values`\n must be broadcast compatible with `indices` (i.e., must have either one\n element or the same number of elements as `indices`).\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aplace, atake\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string|DataType (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n \n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n \n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n ","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n ","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = base.acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianSquare( x )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosd( 0.0 )\n 90.0\n > y = base.acosd( PI/6.0 )\n ~58.43\n > y = base.acosd( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosdf, base.acosh, base.asind, base.atand\n","base.acosdf":"\nbase.acosdf( x )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosdf( 0.0 )\n 90.0\n > y = base.acosdf( FLOAT32_PI / 6.0 )\n ~58.43\n > y = base.acosdf( NaN )\n NaN\n\n See Also\n --------\n base.acosd, base.acosf, base.asindf\n","base.acosf":"\nbase.acosf( x )\n Computes the arccosine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosf( 1.0 )\n 0.0\n > y = base.acosf( 0.707 )\n ~0.7855\n > y = base.acosf( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotd( 0.0 )\n 90.0\n > y = base.acotd( PI/6.0 )\n ~62.36\n > y = base.acotd( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acotdf, base.acoth, base.atand, base.cotd\n","base.acotdf":"\nbase.acotdf( x )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotdf( 0.0 )\n 90.0\n > y = base.acotdf( FLOAT32_PI/6.0 )\n ~62.36\n > y = base.acotdf( NaN )\n NaN\n\n See Also\n --------\n base.acotd, base.acotf\n","base.acotf":"\nbase.acotf( x )\n Computes the inverse cotangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acotf( 2.0 )\n ~0.4636\n > y = base.acotf( 0.0 )\n ~1.5708\n > y = base.acotf( 0.5 )\n ~1.1071\n > y = base.acotf( 1.0 )\n ~0.7854\n > y = base.acotf( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(x-1)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( 1.5 )\n ~0.5236\n > y = base.acovercos( -0.0 )\n ~-1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscd( 0.0 )\n NaN\n > y = base.acscd( PI/6.0 )\n NaN\n > y = base.acscd( 1 )\n 90.0\n > y = base.acscd( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscdf( 0.0 )\n NaN\n > y = base.acscdf( 3.1415927410125732 / 6.0 )\n NaN\n > y = base.acscdf( 1.0 )\n 90.0\n > y = base.acscdf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n Computes the arccosecant of a single-precision floating-point number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acscf( 1.0 )\n ~1.57\n > y = base.acscf( 3.141592653589793 )\n ~0.32\n > y = base.acscf( -3.141592653589793 )\n ~-0.32\n > y = base.acscf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n Returns a filled \"generic\" array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled( 0.0, 3 )\n [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n Returns a filled two-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n Returns a filled three-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n Returns a filled four-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n Returns a filled five-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n Returns a filled \"generic\" array according to a provided callback function.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledBy( 3, clbk )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n Returns a filled n-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afillednd( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledndBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the input array.\n\n If provided an array-like object having a `filter` method , the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.filter( predicate, thisArg )\n\n If provided an array-like object without a `filter` method, the function\n performs a linear scan and always returns a generic array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > function f( v ) { return ( v > 0 ); };\n > var x = [ 1, -2, -3, 4 ];\n > var out = base.afilter( x, f )\n [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n Returns the first element of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: any\n First element.\n\n Examples\n --------\n > var out = base.afirst( [ 1, 2, 3 ] )\n 1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n Flattens an n-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n Flattens a two-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2d( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten2d( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n Flattens a three-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n Flattens a four-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n Flattens a five-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 2, 1 ], [ 4, 3 ] ]\n\n See Also\n --------\n base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 3, 4 ], [ 1, 2 ] ]\n\n See Also\n --------\n base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n Converts a string to alternate case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Alternate-cased string.\n\n Examples\n --------\n > var out = base.altcase( 'Hello World!' )\n 'hElLo wOrLd!'\n > out = base.altcase( 'I am a tiny little teapot' )\n 'i aM A TiNy lItTlE TeApOt'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n Returns a \"generic\" array filled with ones.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones( 3 )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n Returns a two-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones2d( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n Returns a three-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones3d( [ 1, 1, 3 ] )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n Returns a four-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n Returns a five-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n Returns an n-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aonesnd( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.aoneTo( 6 )\n [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n Parameters\n ----------\n args: Array\n Constructor arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var args = [ null, null, null ];\n > var s = new base.args2multislice( args );\n > s.data\n [ null, null, null ]\n > args = [ 10, new Slice( 0, 10, 1 ), null ];\n > s = new base.args2multislice( args );\n > s.data\n [ 10, , null ]\n\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecd( 0.0 )\n NaN\n > y = base.asecd( 2 )\n ~60.0\n > y = base.asecd( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecdf( 2.0 )\n ~60.0\n > y = base.asecdf( 0.0 )\n NaN\n > y = base.asecdf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosdf\n","base.asecf":"\nbase.asecf( x )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asecf( 1.0 )\n 0.0\n > y = base.asecf( 2.0 )\n ~1.0472\n > y = base.asecf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asind( 0.0 )\n 0.0\n > y = base.asind( PI / 6.0 )\n ~31.57\n > y = base.asind( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asindf( 0.0 )\n 0.0\n > y = base.asindf( 3.1415927410125732 / 6.0 )\n ~31.57\n > y = base.asindf( NaN )\n NaN\n\n See Also\n --------\n base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n Computes the arcsine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinf( 0.0 )\n 0.0\n > y = base.asinf( -3.14/6.0 )\n ~-0.551\n > y = base.asinf( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atand":"\nbase.atand( x )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in degrees).\n\n Examples\n --------\n > var y = base.atand( 0.0 )\n 0.0\n > y = base.atand( PI/6.0 )\n ~27.64\n > y = base.atand( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n Computes the arctangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanf( 0.0 )\n 0.0\n > y = base.atanf( -3.14/4.0 )\n ~-0.666\n > y = base.atanf( 3.14/4.0 )\n ~0.666\n > y = base.atanf( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n Returns a zero-filled \"generic\" array.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros( 3 )\n [ 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n Returns a zero-filled two-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros2d( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n Returns a zero-filled three-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros3d( [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n See Also\n --------\n base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n Returns a zero-filled four-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n Returns a zero-filled five-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n Returns a zero-filled n-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azerosnd( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.azeroTo( 6 )\n [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.5\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.cadd.assign":"\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.cadd.strided":"\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.caddf.assign":"\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.caddf.strided":"\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf","base.camelcase":"\nbase.camelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = base.camelcase( 'Hello World!' )\n 'helloWorld'\n > out = base.camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = base.capitalize( 'beep' )\n 'Beep'\n > out = base.capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.56, -3.33 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.cdiv.assign":"\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]","base.cdiv.strided":"\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5, 10 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1, 10 )\n 4.0\n > y = base.ceilsd( 12368.0, 2, 10 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n [ 4.2, -5.5 ]\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n [ 4.0, -5.0 ]\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.55, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = realf( v )\n -1.0\n > var img = imagf( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n [ 0.1, -0.2 ]\n\n See Also\n --------\n base.cdiv, base.cinvf\n","base.cinvf":"\nbase.cinvf( z )\n Computes the inverse of a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n [ ~0.1, ~-0.2 ]\n\n See Also\n --------\n base.cinv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmul.assign":"\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmul.strided":"\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cmulf.assign":"\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmulf.strided":"\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean\n Backward iteration for low surrogates.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = base.codePointAt( 'last man standing', 4, false )\n 32\n > out = base.codePointAt( 'presidential election', 8, true )\n 116\n > out = base.codePointAt( 'अनुच्छेद', 2, false )\n 2369\n > out = base.codePointAt( '🌷', 1, true )\n 127799\n","base.constantcase":"\nbase.constantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = base.constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = base.constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n Computes the cosine of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cosd( 0.0 )\n 1.0\n > y = base.cosd( 90.0 )\n 0.0\n > y = base.cosd( 60.0 )\n ~0.5\n > y = base.cosd( NaN )\n NaN\n\n See Also\n --------\n base.tand\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n Computes the cotangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cotd( 0.0 )\n Infinity\n > y = base.cotd( 90.0 )\n 0.0\n > y = base.cotd( 60.0 )\n ~0.58\n > y = base.cotd( NaN )\n NaN\n\n See Also\n --------\n base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n [ 6.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n [ 5.56, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n Computes the cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.csc( 0.0 )\n Infinity\n > y = base.csc( PI/2.0 )\n ~1.0\n > y = base.csc( -PI/6.0 )\n ~-2.0\n > y = base.csc( NaN )\n NaN\n\n See Also\n --------\n base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n Computes the cosecant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.cscd( 1.0 )\n ~57.30\n > y = base.cscd( PI )\n ~18.25\n > y = base.cscd( -PI )\n ~-18.25\n > y = base.cscd( NaN )\n NaN\n\n See Also\n --------\n base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = base.dotcase( 'Hello World!' )\n 'hello.world'\n > out = base.dotcase( 'I am a tiny little teapot' )\n 'i.am.a.tiny.little.teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an arcsine distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an arcsine distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n Returns the entropy of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.entropy( 0, 1 )\n ~0.693\n > v = base.dists.discreteUniform.entropy( 4, 12 )\n ~2.197\n > v = base.dists.discreteUniform.entropy( 2, 8 )\n ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Fréchet distribution with shape parameter `α`, scale parameter `s`,\n and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a gamma distribution with shape parameter `α` and rate parameter\n `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a gamma distribution with shape parameter `α` and rate parameter `β` at\n a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a geometric distribution with success probability `p` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 0.4 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Gumbel distribution with location parameter `μ` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Gumbel distribution with location parameter `μ` and scale parameter\n `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Laplace distribution with scale parameter `b` and location\n parameter `μ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Laplace distribution with scale parameter `b` and location parameter\n `μ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Lévy distribution with location parameter `μ` and scale\n parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Lévy distribution with location parameter `μ` and scale parameter `c`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a logistic distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a logistic distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with location parameter `μ` and scale\n parameter `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with location\n parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with location\n parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Rayleigh distribution with scale parameter `sigma` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n Evaluates the quantile function for a studentized range distribution.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = quantile( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = quantile( 0.9, 17.0, 2.0 )\n ~0.913\n\n > y = quantile( 0.5, 3.0, 2.0, 2 )\n ~0.01\n\n > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n NaN\n > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.t.logcdf( 2.0, 0.1 )\n ~-0.493\n > y = base.dists.t.logcdf( 1.0, 2.0 )\n ~-0.237\n > y = base.dists.t.logcdf( -1.0, 4.0 )\n ~-1.677\n > y = base.dists.t.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.logcdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.t.logpdf( 0.3, 4.0 )\n ~-1.036\n > y = base.dists.t.logpdf( 2.0, 0.7 )\n ~-2.841\n > y = base.dists.t.logpdf( -1.0, 0.5 )\n ~-2.134\n > y = base.dists.t.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logpdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a uniform distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a uniform distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Weibull distribution with shape parameter `k` and scale\n parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Weibull distribution with shape parameter `k` and scale parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, and is thus\n equivalent to `str.length + len`. Default: str.length.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = base.endsWith( 'beep', 'ep', 4 )\n true\n > bool = base.endsWith( 'Beep', 'op', 4 )\n false\n > bool = base.endsWith( 'Beep', 'ee', 3 )\n true\n > bool = base.endsWith( 'Beep', 'ee', -1 )\n true\n > bool = base.endsWith( 'beep', '', 4 )\n true\n\n See Also\n --------\n base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.floorsd( 3.14159, 1, 10 )\n 3.0\n > y = base.floorsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePointRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster.\n - index: starting grapheme cluster index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n Function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n Generate string from a token array by interpolating values.\n\n Parameters\n ----------\n tokens: Array\n Array of string parts and format identifier objects.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n 'beep boop'\n > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n 'baz 1.00'\n > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n ' 12'\n\n See Also\n --------\n base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n Tokenize a string into an array of string parts and format identifier\n objects.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of string parts and format identifier objects.\n\n Examples\n --------\n > var out = base.formatTokenize( 'Hello %s!' )\n [ 'Hello ', {...}, '!' ]\n > out = base.formatTokenize( '%s %s %d' )\n [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n > out = base.formatTokenize( 'Pi: %.2f' )\n [ 'Pi: ', {...} ]\n\n See Also\n --------\n base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n Computes the sign of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Sign of the gamma function.\n\n Examples\n --------\n > var y = base.gammasgn( 1.0 )\n 1.0\n > y = base.gammasgn( -2.5 )\n -1.0\n > y = base.gammasgn( 0.0 )\n 0.0\n > y = base.gammasgn( NaN )\n NaN\n\n See Also\n --------\n base.gamma","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First number.\n\n b: integer\n Second number.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = base.headercase( 'Hello World!' )\n 'Hello-World'\n > out = base.headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identity\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n Converts an integer to a Slice object.\n\n In strict mode, the function returns an error object if an input value\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n max: integer\n Index upper bound (exclusive).\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s = base.int2slice( -1, 5, false );\n > s.start\n 4\n > s.stop\n 5\n > s.step\n 1\n\n See Also\n --------\n base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invcase":"\nbase.invcase( str )\n Converts a string to inverse case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Inverse-cased string.\n\n Examples\n --------\n > var out = base.invcase( 'Hello World!' )\n 'hELLO wORLD!'\n > out = base.invcase( 'I am A tiny LITTLE teapot' )\n 'i AM a TINY little TEAPOT'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a negative finite number.\n\n Examples\n --------\n > var bool = base.isNegativeFinite( -3.14 )\n true\n > bool = base.isNegativeFinite( -Infinity )\n false\n > bool = base.isNegativeFinite( 2.0 )\n false\n > bool = base.isNegativeFinite( NaN )\n false\n > bool = base.isNegativeFinite( -0.0 )\n false\n\n See Also\n --------\n base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative finite number.\n\n Examples\n --------\n > var out = base.isNonNegativeFinite( 5.0 )\n true\n > out = base.isNonNegativeFinite( 3.14 )\n true\n > out = base.isNonNegativeFinite( 0.0 )\n true\n > out = base.isNonNegativeFinite( Infinity )\n false\n > out = base.isNonNegativeFinite( -3.14 )\n false\n > out = base.isNonNegativeFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = base.isNonPositiveFinite( -3.14 )\n true\n > var bool = base.isNonPositiveFinite( 0.0 )\n true\n > var bool = base.isNonPositiveFinite( -Infinity )\n false\n > var bool = base.isNonPositiveFinite( 3.14 )\n false\n > var bool = base.isNonPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive finite number.\n\n Examples\n --------\n > var bool = base.isPositiveFinite( 5.0 )\n true\n > bool = base.isPositiveFinite( 3.14 )\n true\n > bool = base.isPositiveFinite( 0.0 )\n false\n > bool = base.isPositiveFinite( Infinity )\n false\n > bool = base.isPositiveFinite( -3.14 )\n false\n > bool = base.isPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = base.kebabcase( 'Hello World!' )\n 'hello-world'\n > out = base.kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n\n This function provides a common means for computing logarithms in base e.\n Argument reduction and adding the final term of the polynomial must be done\n by the caller for increased accuracy when different bases are used.\n\n Parameters\n ----------\n f: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var y = base.kernelLog1p( 1.0 )\n ~0.1931\n > y = base.kernelLog1p( 1.4142135623730951 )\n ~0.4672\n > y = base.kernelLog1p( NaN )\n NaN\n\n See Also\n --------\n base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.last":"\nbase.last( str, n )\n Returns the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.last( 'hello', 1 )\n 'o'\n > out = base.last( 'JavaScript', 6 )\n 'Script'\n > out = base.last( 'foo bar', 10 )\n 'foo bar'\n\n See Also\n --------\n base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n Returns the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastCodePoint( 'hello world', 1 )\n 'd'\n > out = base.lastCodePoint( 'JavaScript', 6 )\n 'Script'\n > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n 'द'\n\n See Also\n --------\n base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastGraphemeCluster( 'beep', 1 )\n 'p'\n > out = base.lastGraphemeCluster( 'Boop', 2 )\n 'op'\n > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n 'Script'\n\n See Also\n --------\n base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.leftPad( 'a', 5, ' ' )\n ' a'\n > out = base.leftPad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = base.leftPad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of a double-precision floating-point number.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = base.lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabsn( 3.14, -4.2 )\n 4.2\n > v = base.maxabsn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabsn( 3.14, NaN )\n NaN\n > v = base.maxabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabsn( 3.14, -4.2 )\n 3.14\n > v = base.minabsn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabsn( 3.14, NaN )\n NaN\n > v = base.minabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for both the minimum and\n maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabsn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabsn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabsn( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabsn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for the minimum value and\n negative infinity for the maximum value.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmaxn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxn( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxn( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmaxn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an object with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type. Must be a numeric or \"generic\" data type.\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = base.ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If provided either a non-integer or `n < 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp`\n and assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp`\n and assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice, shape, strict )\n Returns a normalized MultiSlice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n shape: Array\n Maximum slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance (or an error object).\n\n Examples\n --------\n > var s1 = new MultiSlice( 1, 3, null );\n > var s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\n > var v = s2.data[ 0 ];\n > v.start\n 1\n > v.stop\n 2\n > v.step\n 1\n > v = s2.data[ 1 ];\n > v.start\n 3\n > v.stop\n 4\n > v.step\n 1\n > v = s2.data[ 2 ];\n > v.start\n 0\n > v.stop\n 5\n > v.step\n 1\n\n See Also\n --------\n base.normalizeSlice\n","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n Returns a normalized Slice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: Slice\n Input slice object.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s1 = new Slice( 1, 10, 1 );\n > var s2 = base.normalizeSlice( s1, 5, false );\n > s2.start\n 1\n > s2.stop\n 5\n > s2.step\n 1\n > s1 = new Slice( -2, null, -1 );\n > s2 = base.normalizeSlice( s1, 10, false );\n > s2.start\n 8\n > s2.stop\n null\n > s2.step\n -1\n\n See Also\n --------\n base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = base.pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = base.pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = base.percentEncode( '☃' )\n '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative odd integer, the function returns `+Infinity`.\n If `x` is a negative even integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n Converts an angle from radians to degrees (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n 90.0\n > d = base.rad2degf( -3.141592653589793 / 4.0 )\n -45.0\n > d = base.rad2degf( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2degf( 3.141592653589793 / 6.0 )\n 30.000001907348633\n\n See Also\n --------\n base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, random.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, random.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, random.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, random.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta, random.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta, random.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime, random.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime, random.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial, random.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial, random.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy, random.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy, random.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi, random.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi, random.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare, random.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare, random.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine, random.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine, random.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform, random.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform, random.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang, random.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang, random.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential, random.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential, random.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f, random.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f, random.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet, random.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet, random.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma, random.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma, random.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric, random.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric, random.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel, random.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel, random.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric, random.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric, random.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma, random.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma, random.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy, random.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy, random.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace, random.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace, random.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy, random.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy, random.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic, random.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic, random.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal, random.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal, random.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial, random.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial, random.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal, random.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal, random.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1, random.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1, random.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson, random.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson, random.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh, random.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh, random.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t, random.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t, random.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular, random.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular, random.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, random.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, random.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull, random.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull, random.weibull","base.rcbrt":"\nbase.rcbrt( x )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrt( 8.0 )\n 0.5\n > y = base.rcbrt( 1000.0 )\n 0.1\n > y = base.rcbrt( 0.0 )\n Infinity\n > y = base.rcbrt( PINF )\n 0.0\n > y = base.rcbrt( -8.0 )\n -0.5\n > y = base.rcbrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrtf( 8.0 )\n 0.5\n > y = base.rcbrtf( 1000.0 )\n ~0.1\n > y = base.rcbrtf( 0.0 )\n Infinity\n > y = base.rcbrtf( PINF )\n 0.0\n > y = base.rcbrtf( -8.0 )\n -0.5\n > y = base.rcbrtf( NaN )\n NaN\n\n See Also\n --------\n base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n Removes the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirst( 'beep', 1 )\n 'eep'\n > out = base.removeFirst( 'Boop', 1 )\n 'oop'\n > out = base.removeFirst( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n Removes the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstCodePoint( 'beep', 1 )\n 'eep'\n > out = base.removeFirstCodePoint( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstCodePoint( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n 'eep'\n > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n Removes the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLast( 'beep', 1 )\n 'bee'\n > out = base.removeLast( 'Boop', 1 )\n 'Boo'\n > out = base.removeLast( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n Removes the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastCodePoint( 'beep', 1 )\n 'bee'\n > out = base.removeLastCodePoint( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastCodePoint( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n 'bee'\n > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = base.repeat( 'a', 5 )\n 'aaaaa'\n > out = base.repeat( '', 100 )\n ''\n > out = base.repeat( 'beep', 0 )\n ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = base.replace( 'beep', /e/, 'o' )\n 'boep'\n\n See Also\n --------\n base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n Replaces the substring after the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n 'beep foo'\n > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n 'beep bofoo'\n > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n 'Hello Wofoo'\n > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n 'beep boop beepfoo'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n Replaces the substring after the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n 'beep foo'\n > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n 'beep boofoo'\n > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n 'Hellofoo'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n Replaces the substring before the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n 'foo boop'\n > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n 'foooop'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n Replaces the substring before the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n 'foo boop'\n > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n 'fooop'\n > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n 'fooo World!'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n Reverses the UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverse( 'beep' )\n 'peeb'\n > out = base.reverse( 'Boop' )\n 'pooB'\n > out = base.reverse( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n Reverses the Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseCodePoints( 'beep' )\n 'peeb'\n > out = base.reverseCodePoints( 'Boop' )\n 'pooB'\n > out = base.reverseCodePoints( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseGraphemeClusters( 'beep' )\n 'peeb'\n > out = base.reverseGraphemeClusters( 'Boop' )\n 'pooB'\n > out = base.reverseGraphemeClusters( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n Right pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.rightPad( 'a', 5, ' ' )\n 'a '\n > out = base.rightPad( 'beep', 10, 'b' )\n 'beepbbbbbb'\n > out = base.rightPad( 'boop', 12, 'beep' )\n 'boopbeepbeep'\n\n See Also\n --------\n base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string containing constructor arguments.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.sargs2multislice( 'null,null,null' );\n > s.data\n [ null, null, null ]\n > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string|DataType\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = ndarrayShape( x )\n []\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n Computes the secant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Secant.\n\n Examples\n --------\n > var y = base.secd( 1.0 )\n ~1.0\n > y = base.secd( PI )\n ~1.0\n > y = base.secd( -PI )\n ~1.0\n > y = base.secd( NaN )\n NaN\n\n See Also\n --------\n base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n Converts a multidimensional subsequence string to a MultiSlice object.\n\n A multidimensional subsequence string is a comma-separated list of single-\n dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n For example, the following\n\n 2\n :\n 2:\n :10\n 2:10\n ::-1\n 10:2:-1\n :2:\n 2:10:\n 2::2\n :10:2\n :, :, :\n 1, 2, 3\n 0:10, 1:20:2, ::-1\n ...\n :, ..., 2\n\n are all valid multidimensional subsequence strings.\n\n Providing a single nonnegative integer `i` as a single-dimension index\n indexes the same elements as the subsequence `i:i+1`.\n\n Providing a single negative integer `i` as a single-dimension index indexes\n the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n size.\n\n While integers index the same elements as equivalent subsequences, providing\n an integer as a single-dimension index indicates to reduce the number of\n dimensions by one (e.g., if the provided shape corresponds to an array\n having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n In contrast, providing a subsequence indicates to retain a respective\n dimension (e.g., if the provided shape corresponds to an array having rank\n 2, then rank(A) == rank(A[':,:'])).\n\n A multidimensional subsequence string can only contain **one** ellipsis\n ('...') operator. An ellipsis indicates to apply ':' to each dimension\n necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n equals A['1:,:,:,2:5']).\n\n Except in the case of providing a single ellipsis, the number of single-\n dimension indexing expressions must equal the number of dimensions in the\n input shape.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if a single-dimension\n index expression which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n than the provided shape.\n - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n dimensions.\n - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n one ellipsis.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n shape: Array\n Maximum allowed slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n > s.data\n [ ]\n > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n > s.data\n [ 4, , ]\n\n See Also\n --------\n base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if provided a\n subsequence string which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincos.assign":"\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n Converts a Slice object to a subsequence string.\n\n Parameters\n ----------\n slice: Slice\n Input slice.\n\n Returns\n -------\n out: string\n Subsequence string.\n\n Examples\n --------\n > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n '1:10:1'\n > out = base.slice2seq( new Slice( null, 10 ) )\n ':10'\n\n See Also\n --------\n base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n Returns the number of elements in a normalized slice.\n\n Parameters\n ----------\n slice: Slice\n Input normalized slice object.\n\n Returns\n -------\n len: integer\n Number of elements.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > base.sliceLength( s )\n 9\n\n See Also\n --------\n base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceNonReducedDimensions( s )\n [ 2 ]\n\n See Also\n --------\n base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceReducedDimensions( s )\n [ 0, 1 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n Returns the shape of a normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input normalized multi-slice object.\n\n Returns\n -------\n sh: Array\n Slice shape.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > var ms = new MultiSlice( s, s );\n > base.sliceShape( ms )\n [ 9, 9 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = base.snakecase( 'Hello World!' )\n 'hello_world'\n > out = base.snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n Evaluates Spence's function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.startcase":"\nbase.startcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = base.startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = base.startsWith( 'Beep', 'Be', 0 )\n true\n > bool = base.startsWith( 'Beep', 'ep', 0 )\n false\n > bool = base.startsWith( 'Beep', 'ee', 1 )\n true\n > bool = base.startsWith( 'Beep', 'ee', -3 )\n true\n > bool = base.startsWith( 'Beep', '', 0 )\n true\n\n See Also\n --------\n base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n\n Parameters\n ----------\n str: string\n Input string.\n \n p: number\n Probability of capitalization.\n\n Returns\n -------\n out: string\n Sticky-cased string.\n\n Examples\n --------\n > var out = base.stickycase( 'Hello World!' )\n \n\n > out = base.stickycase( 'I am a tiny little teapot' )\n \n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 )\n [ 7.0, 8.0, 3.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf )\n [ 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two single-precision complex floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > x\n [ 0.0, 0.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ]\n > y\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > x0\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision complex floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision complex floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in\n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.dasumpw( 3, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.dasumpw( 3, x1, stride )\n 5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabsSorted":"\nbase.strided.dmaxabsSorted( N, x, strideX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabsSorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabsSorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabsSorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxabsSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxSorted, base.strided.smaxabssorted\n","base.strided.dmaxabsSorted.ndarray":"\nbase.strided.dmaxabsSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxSorted, base.strided.smaxabssorted","base.strided.dmaxSorted":"\nbase.strided.dmaxSorted( N, x, strideX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxSorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxSorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxSorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxSorted.ndarray":"\nbase.strided.dmaxSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxSorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxSorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasum( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasumors( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmean( 4, x1,2 )\n ~-0.3333\n\n\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanpw( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpw( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnanstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancepn( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvarianceyc( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsem( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsem( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemch( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemch( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsempn( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsempn( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemtk( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemtk( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemwd( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemwd( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemyc( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemyc( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed.\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1.0, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevyc( 3, 1.0, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevyc( 3, 1.0, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n\n Parameters\n ----------\n dtype: integer\n Data type enumeration constant.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveEnum( 'float64' )\n \n > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n \n\n See Also\n --------\n base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n Returns the data type string associated with a supported data type value.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveStr( 'float64' )\n 'float64'\n > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n Returns the enumeration constant associated with a strided array data type\n string.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: string\n Data type string.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeStr2Enum( 'float64' )\n \n\n See Also\n --------\n base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( 4, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.gasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, strideX )\n Fills a strided array with a specified scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, strideX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: current array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( 3, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfillBy( 3, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, strideX )\n Reverses a strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.grev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, strideX )\n Multiplies a vector by a scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, strideX )\n Sorts a strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, strideX )\n Sorts a strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, strideX )\n Sorts a strided array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, strideX )\n Computes the sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, strideX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, strideX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, strideX )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, strideX )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, strideX )\n Computes the maximum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.max( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.max( 3, x1, 2 )\n 2.0\n\n\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, strideX )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n 14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, strideX )\n Computes the arithmetic mean of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, strideX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, strideX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, strideX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, strideX )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, strideX )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n\n Parameters\n ----------\n meta: Object\n Function meta data.\n\n meta.nargs: integer\n Total number of arguments (excluding offsets).\n\n meta.nin: integer\n Total number of input arrays.\n\n meta.nout: integer\n Total number of output arrays.\n\n dtypes: ArrayLikeObject\n List of strided array data types.\n\n obj: Object|Function\n Object on which to define properties.\n\n bool: boolean\n Boolean indicating whether the provided object should describe an\n \"ndarray\" function interface.\n\n Returns\n -------\n out: Object|Function\n Object on which properties were defined.\n\n Examples\n --------\n > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n > var dt = [ 'float64', 'float64' ];\n > var obj = {};\n > base.strided.metaDataProps( meta, dt, obj, false );\n > obj.nargs\n 7\n > obj.nin\n 1\n > obj.nout\n 1\n > obj.types\n [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, strideX )\n Computes the minimum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.min( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.min( 3, x1, 2 )\n -2.0\n\n\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, strideX )\n Computes the minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > base.strided.minBy( 3, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, strideX )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n 6\n\n See Also\n --------\n base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, strideX )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmax( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmax( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxabs( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.nanmaxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, strideX )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmin( 4, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmin( 4, x1, 2 )\n -2.0\n\n\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, strideX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminabs( 4, x1, 2 )\n 1.0\n\n\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > base.strided.nanminBy( 4, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmax( 4, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmin( 4, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( 5, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, strideX )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanrange( 4, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrange( 4, x1, 2 )\n 4.0\n\n\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > base.strided.nanrangeBy( 4, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdev( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0,NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdev( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( 4, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvarianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n\n Parameters\n ----------\n x: TypedArray\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: TypedArray\n Typed array view having the same data type as the input array.\n\n Examples\n --------\n > var x = new Float64Array( 10 );\n > var out = base.strided.offsetView( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, strideX )\n Computes the range of a strided array.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a\n typed array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.range( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.range( 3, x1, 2 )\n 4.0\n\n\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( 3, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.rangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n\n Parameters\n ----------\n x: Complex128Array|Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Real-valued floating-point array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n > x = new Complex64Array( 10 );\n > out = base.strided.reinterpretComplex( x, 0 )\n \n > bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n Returns a Float32Array view of a Complex64Array.\n\n Parameters\n ----------\n x: Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex64Array.\n\n Returns\n -------\n out: Float32Array\n Float32Array view.\n\n Examples\n --------\n > var x = new Complex64Array( 10 );\n > var out = base.strided.reinterpretComplex64( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n Returns a Float64Array view of a Complex128Array.\n\n Parameters\n ----------\n x: Complex128Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex128Array.\n\n Returns\n -------\n out: Float64Array\n Float64Array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex128( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnanmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabsSorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabsSorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, strideX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumors( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumors( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, strideX )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves the strided arrays\n are unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, strideX )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided array\n unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, strideX )\n Computes the variance of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, strideX )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, strideX )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.varianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.varianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity )\n [ 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n Parses a string-serialized MultiSlice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n > s.data\n [ null, null, null ]\n > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n Parses a string-serialized Slice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: Slice|null\n Slice instance (or null).\n\n Examples\n --------\n > var s = new base.str2slice( 'Slice(1,10,1)' );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.str2slice( 'Slice(2,5,2)' );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n Computes the tangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tand( 0.0 )\n 0.0\n > y = base.tand( 90.0 )\n Infinity\n > y = base.tand( 60.0 )\n ~1.73\n > y = base.tand( NaN )\n NaN\n\n See Also\n --------\n base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x, writable )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n\n The `writable` parameter only applies to ndarray constructors supporting\n read-only instances.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n writable: boolean\n Boolean indicating whether the returned ndarray should be writable.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ [ 1, 2, 3 ], [ 4, 5, 6 ] ]\n > var y = base.transpose( x, false )\n [ [ 1, 4 ], [ 2, 5 ], [ 3, 6 ] ]\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string\n Custom replacement sequence.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.truncateMiddle( str, 5, '...' )\n 'b...p'\n > out = base.truncateMiddle( str, 5, '|' )\n 'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.truncsd( 3.14159, 1, 10 )\n 3.0\n > y = base.truncsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.umul":"\nbase.umul( x, y )\n Multiples two unsigned 32-bit integers.\n\n The function performs C-like multiplication of two unsigned 32-bit integers,\n including wraparound semantics.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n y: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = base.uncapitalize( 'Beep' )\n 'beep'\n > out = base.uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = base.uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n base.lowercase\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value to the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: log-transformed wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray()\n \n\n\nBooleanArray( length )\n Creates a boolean array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray( booleanarray )\n Creates a boolean array from another boolean array.\n\n Parameters\n ----------\n booleanarray: BooleanArray\n Boolean array from which to generate another boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var arr2 = new BooleanArray( arr1 )\n \n > var len = arr2.length\n 4\n\n\nBooleanArray( typedarray )\n Creates a boolean array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n \n > var arr = new BooleanArray( buf )\n \n > var len = arr.length\n 4\n\n\nBooleanArray( obj )\n Creates a boolean array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var len = arr1.length\n 4\n > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n > len = arr2.length\n 4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n Returns a boolean array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new BooleanArray( buf )\n \n > var len = arr1.length\n 240\n > var arr2 = new BooleanArray( buf, 8 )\n \n > len = arr2.length\n 232\n > var arr3 = new BooleanArray( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n \n\n\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1\n\n\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'\n\n\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false\n\n\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'\n\n\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n ","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanVector":"\nBooleanVector( [options] )\n Returns a one-dimensional boolean ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = BooleanVector()\n \n\n\nBooleanVector( length[, options] )\n Returns a one-dimensional boolean ndarray having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = BooleanVector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nBooleanVector( obj[, options] )\n Creates a one-dimensional boolean ndarray from an array-like object or\n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ true, false, true ];\n > var arr = BooleanVector( v )\n \n > var len = numel( arr )\n 3\n\n\nBooleanVector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional boolean ndarray view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = BooleanVector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, vector, ndarray\n","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Object\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary.\n - phones: manners of articulation for each sound.\n - symbols: complete list of ARPABET symbols used by the dictionary.\n - vp: verbal pronunciations of punctuation marks.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'\n\n\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128\n","Complex64.name":"\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array()\n \n\n\nComplex64Array( length )\n Creates a 64-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex64Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex64Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex64Array( typedarray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex64Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex64Array( obj )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n > var arr2 = new Complex64Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new Complex64Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex64Array( buf, 8 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex64Array( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n\n\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80\n\n\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n [ 3.0, -3.0, 4.0, -4.0, 3.0, -3.0, 4.0, -4.0 ]\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n [ 2.0, 2.0 ]\n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n [ 1.0, -1.0, 2.0, -2.0 ]\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]\n\n\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]\n > var z = out.get( 0 )\n [ 3.0, 3.0 ]\n > z = out.get( 1 )\n [ 2.0, 2.0 ]\n > z = out.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n > z = out.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex64\n Element value.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n > var z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n ","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n [ 3.0, -3.0, 4.0, -4.0, 3.0, -3.0, 4.0, -4.0 ]\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n -3.0\n > var bool = it.next().done\n true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n [ 2.0, 2.0 ]\n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n [ 1.0, -1.0, 2.0, -2.0 ]\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n [ 3.0, -3.0 ]","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n [ 3.0, -3.0 ]","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]\n > var z = out.get( 0 )\n [ 3.0, 3.0 ]\n > z = out.get( 1 )\n [ 2.0, 2.0 ]\n > z = out.get( 2 )\n [ 1.0, 1.0 ]","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n > z = out.get( 2 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex64\n Element value.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n > var z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Matrix":"\nComplex64Matrix( [options] )\n Returns a two-dimensional single-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Matrix()\n \n\n\nComplex64Matrix( shape[, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Matrix( [ 2, 2 ] )\n \n\n\nComplex64Matrix( M, N[, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Matrix( 2, 2 )\n \n\n\nComplex64Matrix( obj[, options] )\n Creates a two-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\n > var arr = Complex64Matrix( v )\n \n\n\nComplex64Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex64Matrix( buf, 0, [ 8, 1 ] )\n \n\n\nComplex64Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex64Matrix( buf, 0, 8, 1 )\n \n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex128Matrix, matrix, Complex64Vector, ndarray\n","Complex64Vector":"\nComplex64Vector( [options] )\n Returns a one-dimensional single-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Vector()\n \n\n\nComplex64Vector( length[, options] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nComplex64Vector( obj[, options] )\n Creates a one-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var arr = Complex64Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nComplex64Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Complex64Vector( buf, 0, 2 )\n \n > var len = numel( arr )\n 2\n\n See Also\n --------\n Complex64Matrix, Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, BooleanVector, vector, ndarray\n","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'\n\n\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64\n","Complex128.name":"\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare )\n [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ]\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n ","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare )\n [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ]","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Matrix":"\nComplex128Matrix( [options] )\n Returns a two-dimensional double-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Matrix()\n \n\n\nComplex128Matrix( shape[, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Matrix( [ 2, 2 ] )\n \n\n\nComplex128Matrix( M, N[, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Matrix( 2, 2 )\n \n\n\nComplex128Matrix( obj[, options] )\n Creates a two-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\n > var arr = Complex128Matrix( v )\n \n\n\nComplex128Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex128Matrix( buf, 0, [ 4, 1 ] )\n \n\n\nComplex128Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex128Matrix( buf, 0, 4, 1 )\n \n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex64Matrix, matrix, Complex128Vector, ndarray\n","Complex128Vector":"\nComplex128Vector( [options] )\n Returns a one-dimensional double-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Vector()\n \n\n\nComplex128Vector( length[, options] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nComplex128Vector( obj[, options] )\n Creates a one-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var arr = Complex128Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nComplex128Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex128Vector( buf, 0, 2 )\n \n > var len = numel( arr )\n 2\n\n See Also\n --------\n Complex128Matrix, Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex64Vector, BooleanVector, vector, ndarray\n","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( value, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `value` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `value` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n value: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\foo\\bar\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\foo\\bar\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n See Also\n --------\n isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n\n Returns\n -------\n out: Array\n List of familiar American-English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataType":"\nDataType( value[, options] )\n Data type constructor.\n\n Parameters\n ----------\n value: any\n Data type value.\n\n options: Object (optional)\n Constructor options.\n\n options.description: string (optional)\n Data type description.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'\n\n\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8\n\n\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'\n\n\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'\n\n\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'\n\n\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n \n\n\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'\n\n\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}\n\n\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'\n\n\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType\n\n","DataType.name":"\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n ","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = ddot( x, y )\n [ -5.0 ]\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj1 = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj1, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > var obj2 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj2\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > var obj3 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\n > obj3\n { 'a': { 'b': { 'c': 'd' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default:\n undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n Interchanges two double-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var o = {a: 1, b: 2, c: 3};\n > var bool = everyInBy( o, positive )\n true\n\n See Also\n --------\n anyInBy, noneInBy, someInBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > var bool = everyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","falses":"\nfalses( shape[, options] )\n Returns an ndarray filled with `false` values and having a specified shape\n and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a boolean or \"generic\" data type. Default:\n 'bool'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = falses( [ 2, 2 ] )\n [ [ false, false ], [ false, false ] ]\n\n See Also\n --------\n array, ndarray, falsesLike, trues\n","falsesLike":"\nfalsesLike( x[, options] )\n Returns an ndarray filled with `false` values and having the same shape and\n data type as a provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a boolean or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var opts = { 'dtype': 'generic' };\n > var x = ndempty( [ 2, 2 ], opts )\n \n > var y = falsesLike( x )\n [ [ false, false ], [ false, false ] ]\n\n See Also\n --------\n array, ndarray, falses, truesLike\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","Float16Array":"\nFloat16Array()\n A 16-bit half-precision floating-point number array.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float16Array()\n \n\n\nFloat16Array( length )\n Creates a half-precision floating-point number array having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var len = arr.length\n 5\n\n\nFloat16Array( typedarray )\n Creates a half-precision floating-point number array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a half-precision floating-point\n number array.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 0.5, 0.5, 0.5 ] )\n \n > var arr = new Float16Array( buf )\n \n > var len = arr.length\n 3\n\n\nFloat16Array( obj )\n Creates a half-precision floating-point number array from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a half-precision\n floating-point number array.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 0.5, 0.5, 0.5 ] )\n \n > var len = arr.length\n 3\n\n\nFloat16Array( buffer[, byteOffset[, length]] )\n Returns a half-precision floating-point number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr1 = new Float16Array( buf )\n \n > var len = arr1.length\n 4\n > var arr2 = new Float16Array( buf, 2 )\n \n > len = arr2.length\n 3\n > var arr3 = new Float16Array( buf, 2, 2 )\n \n > len = arr3.length\n 2\n\n\nFloat16Array.from( src[, clbk[, thisArg]] )\n Creates a new half-precision floating-point number array from an array-like\n object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Float16Array.from( [ 1.0, -1.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n -2.0\n\n\nFloat16Array.of( element0[, element1[, ...elementN]] )\n Creates a new half-precision floating-point number array from a variable\n number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = Float16Array.of( 1.0, -1.0 )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n -1.0\n\n\nFloat16Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Float16Array.BYTES_PER_ELEMENT\n 2\n\n\nFloat16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Float16Array.name\n 'Float16Array'\n\n\nFloat16Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Float16Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nFloat16Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nFloat16Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 20 );\n > arr = new Float16Array( buf, 10 )\n \n > offset = arr.byteOffset\n 10\n\n\nFloat16Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > arr.BYTES_PER_ELEMENT\n 2\n\n\nFloat16Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var len = arr.length\n 5\n\n\nFloat16Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: float|void\n An array element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 10.0, 20.0, 30.0 ] )\n \n > var v = arr.at( 0 )\n 10.0\n > v = arr.at( -1 )\n 30.0\n\n\nFloat16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > arr.copyWithin( 0, 3 )\n \n > var v = arr[ 0 ]\n 4.0\n > v = arr[ 1 ]\n 5.0\n\n\nFloat16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, 1.0 ]\n > v = it.next().value\n [ 1, 2.0 ]\n > v = it.next().value\n [ 2, 3.0 ]\n > var bool = it.next().done\n true\n\n\nFloat16Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 0.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nFloat16Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( 3 )\n \n > arr.fill( 2.0 );\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 2.0\n\n\nFloat16Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0\n\n\nFloat16Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.find( predicate )\n 2.0\n\n\nFloat16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat16Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.findLast( predicate )\n 3.0\n\n\nFloat16Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nFloat16Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1%2%3%'\n\n\nFloat16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.includes( 3.0 )\n true\n > bool = arr.includes( 3.0, 3 )\n false\n\n\nFloat16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.indexOf( 2.0 )\n 1\n > idx = arr.indexOf( 2.0, 2 )\n -1\n\n\nFloat16Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.join()\n '1,2,3'\n > str = arr.join( '|' )\n '1|2|3'\n\n\nFloat16Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nFloat16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 1.0 ] )\n \n > var idx = arr.lastIndexOf( 1.0 )\n 3\n > idx = arr.lastIndexOf( 1.0, 2 )\n 0\n\n\nFloat16Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v * 2.0; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.map( clbk )\n \n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 4.0\n > v = out[ 2 ]\n 6.0\n\n\nFloat16Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduce( reducerFn, 0.0 )\n 6.0\n\n\nFloat16Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduceRight( reducerFn, 0.0 )\n 6.0\n\n\nFloat16Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.reverse();\n > var v = arr[ 0 ]\n 3.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 1.0\n\n\nFloat16Array.prototype.set( arr[, offset] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an offset argument.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.set( [ 4.0, 5.0 ], 1 );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 4.0\n > v = arr[ 2 ]\n 5.0\n\n\nFloat16Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0\n\n\nFloat16Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nFloat16Array.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > arr.sort( compare );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 3.0\n\n\nFloat16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0\n\n\nFloat16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toLocaleString()\n '1,2,3'\n\n\nFloat16Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var v = out[ 0 ]\n 3.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 1.0\n\n\nFloat16Array.prototype.toSorted( [compareFcn] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var v = out[ 0 ]\n 1.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 3.0\n\n\nFloat16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toString()\n '1,2,3'\n\n\nFloat16Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n\nFloat16Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: number\n Element value.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.with( 1, 4.0 )\n \n > var v = out[ 1 ]\n 4.0\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float16Array.from":"\nFloat16Array.from( src[, clbk[, thisArg]] )\n Creates a new half-precision floating-point number array from an array-like\n object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Float16Array.from( [ 1.0, -1.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n -2.0","Float16Array.of":"\nFloat16Array.of( element0[, element1[, ...elementN]] )\n Creates a new half-precision floating-point number array from a variable\n number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = Float16Array.of( 1.0, -1.0 )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n -1.0","Float16Array.BYTES_PER_ELEMENT":"\nFloat16Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Float16Array.BYTES_PER_ELEMENT\n 2","Float16Array.name":"\nFloat16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Float16Array.name\n 'Float16Array'","Float16Array.prototype.buffer":"\nFloat16Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Float16Array( 2 )\n \n > var buf = arr.buffer\n ","Float16Array.prototype.byteLength":"\nFloat16Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var nbytes = arr.byteLength\n 10","Float16Array.prototype.byteOffset":"\nFloat16Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 20 );\n > arr = new Float16Array( buf, 10 )\n \n > offset = arr.byteOffset\n 10","Float16Array.prototype.BYTES_PER_ELEMENT":"\nFloat16Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > arr.BYTES_PER_ELEMENT\n 2","Float16Array.prototype.length":"\nFloat16Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var len = arr.length\n 5","Float16Array.prototype.at":"\nFloat16Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: float|void\n An array element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 10.0, 20.0, 30.0 ] )\n \n > var v = arr.at( 0 )\n 10.0\n > v = arr.at( -1 )\n 30.0","Float16Array.prototype.copyWithin":"\nFloat16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > arr.copyWithin( 0, 3 )\n \n > var v = arr[ 0 ]\n 4.0\n > v = arr[ 1 ]\n 5.0","Float16Array.prototype.entries":"\nFloat16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, 1.0 ]\n > v = it.next().value\n [ 1, 2.0 ]\n > v = it.next().value\n [ 2, 3.0 ]\n > var bool = it.next().done\n true","Float16Array.prototype.every":"\nFloat16Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 0.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Float16Array.prototype.fill":"\nFloat16Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( 3 )\n \n > arr.fill( 2.0 );\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 2.0","Float16Array.prototype.filter":"\nFloat16Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0","Float16Array.prototype.find":"\nFloat16Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.find( predicate )\n 2.0","Float16Array.prototype.findIndex":"\nFloat16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 2","Float16Array.prototype.findLast":"\nFloat16Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.findLast( predicate )\n 3.0","Float16Array.prototype.findLastIndex":"\nFloat16Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","Float16Array.prototype.forEach":"\nFloat16Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1%2%3%'","Float16Array.prototype.includes":"\nFloat16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.includes( 3.0 )\n true\n > bool = arr.includes( 3.0, 3 )\n false","Float16Array.prototype.indexOf":"\nFloat16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.indexOf( 2.0 )\n 1\n > idx = arr.indexOf( 2.0, 2 )\n -1","Float16Array.prototype.join":"\nFloat16Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.join()\n '1,2,3'\n > str = arr.join( '|' )\n '1|2|3'","Float16Array.prototype.keys":"\nFloat16Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Float16Array.prototype.lastIndexOf":"\nFloat16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 1.0 ] )\n \n > var idx = arr.lastIndexOf( 1.0 )\n 3\n > idx = arr.lastIndexOf( 1.0, 2 )\n 0","Float16Array.prototype.map":"\nFloat16Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v * 2.0; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.map( clbk )\n \n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 4.0\n > v = out[ 2 ]\n 6.0","Float16Array.prototype.reduce":"\nFloat16Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduce( reducerFn, 0.0 )\n 6.0","Float16Array.prototype.reduceRight":"\nFloat16Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduceRight( reducerFn, 0.0 )\n 6.0","Float16Array.prototype.reverse":"\nFloat16Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.reverse();\n > var v = arr[ 0 ]\n 3.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 1.0","Float16Array.prototype.set":"\nFloat16Array.prototype.set( arr[, offset] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an offset argument.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.set( [ 4.0, 5.0 ], 1 );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 4.0\n > v = arr[ 2 ]\n 5.0","Float16Array.prototype.slice":"\nFloat16Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0","Float16Array.prototype.some":"\nFloat16Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Float16Array.prototype.sort":"\nFloat16Array.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > arr.sort( compare );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 3.0","Float16Array.prototype.subarray":"\nFloat16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0","Float16Array.prototype.toLocaleString":"\nFloat16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toLocaleString()\n '1,2,3'","Float16Array.prototype.toReversed":"\nFloat16Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var v = out[ 0 ]\n 3.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 1.0","Float16Array.prototype.toSorted":"\nFloat16Array.prototype.toSorted( [compareFcn] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var v = out[ 0 ]\n 1.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 3.0","Float16Array.prototype.toString":"\nFloat16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toString()\n '1,2,3'","Float16Array.prototype.values":"\nFloat16Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true","Float16Array.prototype.with":"\nFloat16Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: number\n Element value.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.with( 1, 4.0 )\n \n > var v = out[ 1 ]\n 4.0\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n\n Examples\n --------\n > FLOAT32_E\n 2.7182817459106445\n\n See Also\n --------\n E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EXPONENT_MASK\n 2139095040\n > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n '01111111100000000000000000000000'\n\n See Also\n --------\n FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_FOURTH_PI\n 7.853981852531433e-1\n\n See Also\n --------\n FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_HALF_LN_TWO\n 0.3465735912322998\n\n See Also\n --------\n HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_HALF_PI\n 1.5707963705062866\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_HALF\n -0.6931471824645996\n\n See Also\n --------\n LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_PI\n 1.1447298526763916\n\n See Also\n --------\n FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TEN\n 2.3025851249694824\n\n See Also\n --------\n FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TWO\n 0.6931471824645996\n\n See Also\n --------\n FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT\n 127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n -127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT\n 38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n -38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_FIBONACCI\n 14930352\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n 10\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n 36\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_LUCAS\n 34\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT\n -126\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n -149\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT\n -37\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n -45\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n\n Examples\n --------\n > FLOAT32_PHI\n 1.6180340051651\n\n See Also\n --------\n PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_PI\n 3.1415927410125732\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGNIFICAND_MASK\n 8388607\n > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n '00000000011111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF\n 0.7071067690849304\n\n See Also\n --------\n SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF_PI\n 1.2533141374588013\n\n See Also\n --------\n SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PHI\n 1.272019624710083\n\n See Also\n --------\n SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PI\n 1.7724539041519165\n\n See Also\n --------\n FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_THREE\n 1.7320507764816284\n\n See Also\n --------\n FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO\n 1.4142135381698608\n\n See Also\n --------\n FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO_PI\n 2.5066282749176025\n\n See Also\n --------\n FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > FLOAT32_TWO_PI\n 6.2831854820251465\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Float32Matrix":"\nFloat32Matrix( [options] )\n Returns a two-dimensional single-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Matrix()\n \n\n\nFloat32Matrix( shape[, options] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Matrix( [ 2, 2 ] )\n \n\n\nFloat32Matrix( M, N[, options] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Matrix( 2, 2 )\n \n\n\nFloat32Matrix( obj[, options] )\n Creates a two-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\n > var arr = Float32Matrix( v )\n \n\n\nFloat32Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float32Matrix( buf, 0, [ 8, 1 ] )\n \n\n\nFloat32Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float32Matrix( buf, 0, 4, 1 )\n \n\n See Also\n --------\n Float64Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, matrix, Float32Vector, ndarray\n","Float32Vector":"\nFloat32Vector( [options] )\n Returns a one-dimensional single-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Vector()\n \n\n\nFloat32Vector( length[, options] )\n Returns a one-dimensional single-precision floating-point ndarray having a\n specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nFloat32Vector( obj[, options] )\n Creates a one-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0 ];\n > var arr = Float32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nFloat32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, Float32Matrix, ndarray\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Float64Matrix":"\nFloat64Matrix( [options] )\n Returns a two-dimensional double-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Matrix()\n \n\n\nFloat64Matrix( shape[, options] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Matrix( [ 2, 2 ] )\n \n\n\nFloat64Matrix( M, N[, options] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Matrix( 2, 2 )\n \n\n\nFloat64Matrix( obj[, options] )\n Creates a two-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\n > var arr = Float64Matrix( v )\n \n\n\nFloat64Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float64Matrix( buf, 0, [ 4, 1 ] )\n \n\n\nFloat64Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float64Matrix( buf, 0, 4, 1 )\n \n\n See Also\n --------\n Float32Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, matrix, Float64Vector, ndarray\n","Float64Vector":"\nFloat64Vector( [options] )\n Returns a one-dimensional double-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Vector()\n \n\n\nFloat64Vector( length[, options] )\n Returns a one-dimensional double-precision floating-point ndarray having a\n specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nFloat64Vector( obj[, options] )\n Creates a one-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0 ];\n > var arr = Float64Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nFloat64Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float64Vector( buf, 0, 2 )\n \n > var len = numel( arr )\n 2\n\n See Also\n --------\n Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, Float64Matrix, ndarray\n","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: starting character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","format":"\nformat( str, ...args )\n Insert supplied variable values into a format string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = format( 'Hello, %s!', 'World' )\n 'Hello, World!'\n\n > out = format( '%s %s', 'Hello', 'World' )\n 'Hello World'\n\n > out = format( 'Pi: %.2f', PI )\n 'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support arrow functions.\n\n Examples\n --------\n > var bool = hasArrowFunctionSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `atob` support.\n\n Examples\n --------\n > var bool = hasAtobSupport()\n \n\n See Also\n --------\n hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `btoa` support.\n\n Examples\n --------\n > var bool = hasBtoaSupport()\n \n\n See Also\n --------\n hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Symbol.toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServerFactory":"\nhttpServerFactory( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n In addition to options documented below, the function supports any options\n supported by `http.createServer`. Which server options are supported depends\n on the Node.js version. Older Node.js versions (e.g., <= v8.12.0) do not\n support an options object when calling `http.createServer`, and, for those\n versions, any options supported by `http.createServer` in later Node.js\n versions are ignored.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n httpServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var boot = httpServerFactory()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > boot = httpServerFactory( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > boot = httpServerFactory( opts )\n \n\n\nboot( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var boot = httpServerFactory();\n > boot( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object.\n - result: either `x` or `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion.\n\n The predicate function callback accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium oreophilum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value.\n - w: weight.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Int8Vector":"\nInt8Vector( [options] )\n Returns a one-dimensional signed 8-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int8Vector()\n \n\n\nInt8Vector( length[, options] )\n Returns a one-dimensional signed 8-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int8Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nInt8Vector( obj[, options] )\n Creates a one-dimensional signed 8-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Int8Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nInt8Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional signed 8-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int8Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Int16Vector":"\nInt16Vector( [options] )\n Returns a one-dimensional signed 16-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int16Vector()\n \n\n\nInt16Vector( length[, options] )\n Returns a one-dimensional signed 16-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int16Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nInt16Vector( obj[, options] )\n Creates a one-dimensional signed 16-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Int16Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nInt16Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional signed 16-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int16Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int8Vector, Int32Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Int32Matrix":"\nInt32Matrix( [options] )\n Returns a two-dimensional 32-bit signed integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix()\n \n\n\nInt32Matrix( shape[, options] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix( [ 2, 2 ] )\n \n\n\nInt32Matrix( M, N[, options] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix( 2, 2 )\n \n\n\nInt32Matrix( obj[, options] )\n Creates a two-dimensional 32-bit signed integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1, 2 ], [ 3, 4 ] ];\n > var arr = Int32Matrix( v )\n \n\n\nInt32Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Matrix( buf, 0, [ 8, 1 ] )\n \n\n\nInt32Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Matrix( buf, 0, 8, 1 )\n \n\n See Also\n --------\n Float64Matrix, Float32Matrix, Complex128Matrix, Complex64Matrix, matrix, Int32Vector, ndarray\n","Int32Vector":"\nInt32Vector( [options] )\n Returns a one-dimensional signed 32-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Vector()\n \n\n\nInt32Vector( length[, options] )\n Returns a one-dimensional signed 32-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nInt32Vector( obj[, options] )\n Creates a one-dimensional signed 32-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Int32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nInt32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional signed 32-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int8Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, Int32Matrix, ndarray\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n\n Examples\n --------\n > IS_DOCKER\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n\n Examples\n --------\n > IS_MOBILE\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n\n Examples\n --------\n > IS_TOUCH_DEVICE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n Tests whether a value is an absolute HTTP(S) URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n Examples\n --------\n > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n true\n > bool = isAbsoluteHttpURI( 'example.com' )\n false\n > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n Tests whether a value is an absolute URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute URI.\n\n Examples\n --------\n > var bool = isAbsoluteURI( 'http://example.com/' )\n true\n > bool = isAbsoluteURI( 'example.com' )\n false\n > bool = isAbsoluteURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n Tests if a value is an arrow function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arrow function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isArrowFunction( beep )\n false\n > bool = isArrowFunction( {} )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n - Object( BigInt() ) (ES11/ES2020)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCamelcase":"\nisCamelcase( value )\n Tests if a value is a camelcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a camelcase string.\n\n Examples\n --------\n > var bool = isCamelcase( 'helloWorld' )\n true\n > bool = isCamelcase( 'hello world' )\n false\n\n See Also\n --------\n isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var opts = { 'dtype': 'complex128' };\n > var M = ndzeros( [ 2, 2 ], opts );\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var opts = { 'dtype': 'complex128' };\n > var M = ndzeros( [ 2, 2 ], opts );\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var opts = { 'dtype': 'complex128' };\n > var M = ndzeros( [ 4 ], opts );\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n Tests if a value is a constantcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a constantcase string.\n\n Examples\n --------\n > var bool = isConstantcase( 'BEEP_BOOP' )\n true\n > bool = isConstantcase( 'BEEP and BOOP' )\n false\n\n See Also\n --------\n isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n Tests if a value is the current year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is the current year.\n\n Examples\n --------\n > var bool = isCurrentYear( new Date() )\n true\n > bool = isCurrentYear( currentYear() )\n true\n > bool = isCurrentYear( 2021 )\n false\n > bool = isCurrentYear( null )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isDomainName":"\nisDomainName( value )\n Tests if a value is a domain name.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a domain name.\n\n Examples\n --------\n > var bool = isDomainName( 'example.com' )\n true\n > bool = isDomainName( 'foo@bar.com' )\n false\n","isDurationString":"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n Tests if two arguments are both generic arrays and have equal values.\n\n The function performs strict equality comparison; thus, the function treats\n `-0` and `+0` as equal and `NaNs` as distinct.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are equal.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isEqualArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isEqualArray( x, y )\n false\n\n See Also\n --------\n isArray, isSameArray\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n\n Parameters\n ----------\n d1: any\n First input value.\n d2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether both values are Date objects corresponding to\n the same date and time.\n\n Examples\n --------\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var bool = isEqualDateObject( d1, d2 )\n true\n > d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n > bool = isEqualDateObject( d1, d2 )\n false\n\n See Also\n --------\n isDateObject, isSameValue\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isKebabcase":"\nisKebabcase( value )\n Tests if a value is a string in kebab case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in kebab case.\n\n Examples\n --------\n > var bool = isKebabcase( 'beep-boop' )\n true\n > bool = isKebabcase( 'BEEP_BOOP' )\n false\n\n See Also\n --------\n isString","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n Tests if a value is an ndarray-like object having a specified data type.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n dtype: any\n Data type value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object having a\n specified data type.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLikeWithDataType( M, 'generic' )\n true\n > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n false\n > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n false\n > bool = isndarrayLikeWithDataType( {}, 'generic' )\n false\n\n See Also\n --------\n isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n Tests if a value is a finite negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite negative number.\n\n Examples\n --------\n > var bool = isNegativeFinite( -5.0 )\n true\n > bool = isNegativeFinite( new Number( -5.0 ) )\n true\n > bool = isNegativeFinite( -3.14 )\n true\n > bool = isNegativeFinite( 5.0 )\n false\n > bool = isNegativeFinite( null )\n false\n > bool = isNegativeFinite( -1.0/0.0 )\n false\n > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n Tests if a value is a nonpositive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = isNonPositiveFinite( -5.0 )\n true\n > bool = isNonPositiveFinite( new Number( -5.0 ) )\n true\n > bool = isNonPositiveFinite( -3.14 )\n true\n > bool = isNonPositiveFinite( 5.0 )\n false\n > bool = isNonPositiveFinite( null )\n false\n\n\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [value] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPascalcase":"\nisPascalcase( value )\n Tests if a value is a string in Pascal case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in Pascal case.\n\n Examples\n --------\n > var bool = isPascalcase( 'HelloWorld' )\n true\n > bool = isPascalcase( 'hello-world' )\n false\n\n See Also\n --------\n isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n Tests if a value is a positive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a positive finite number.\n\n Examples\n --------\n > var bool = isPositiveFinite( 5.0 )\n true\n > bool = isPositiveFinite( new Number( 5.0 ) )\n true\n > bool = isPositiveFinite( 3.14 )\n true\n > bool = isPositiveFinite( -5.0 )\n false\n > var bool = isPositiveFinite( 1.0/0.0 )\n false\n > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n false\n > bool = isPositiveFinite( null )\n false\n\n\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n Tests if a value is a ragged nested array. \n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a ragged nested array.\n\n Examples\n --------\n > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n true\n > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n false\n > bool = isRaggedNestedArray( 'beep' )\n false\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n Tests whether a value is a relative URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is a relative URI.\n\n Examples\n --------\n > var bool = isRelativeURI( '/images/example.png' )\n true\n > bool = isRelativeURI( 'http://www.example.com' )\n false\n > bool = isRelativeURI( null )\n false\n\n See Also\n --------\n isURI","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n Tests if two arguments are both array-like and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArrayLike( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArrayLike( x, y )\n true\n\n See Also\n --------\n isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n Tests if a value is a semantic version string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a provided value is a semantic version\n string.\n\n Examples\n --------\n > var bool = isSemVer( '1.0.0' )\n true\n > bool = isSemVer( '1.0.0-alpha.1' )\n true\n > bool = isSemVer( '0.1' )\n false\n > bool = isSemVer( null )\n false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n Tests if a value is a string in snake case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in snake case.\n\n Examples\n --------\n > var bool = isSnakecase( 'hello_world' )\n true\n > bool = isSnakecase( 'Hello World' )\n false\n\n See Also\n --------\n isString","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n Tests if a value is a startcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is a startcase string.\n\n Examples\n --------\n > var bool = isStartcase( 'Beep Boop' )\n true\n > bool = isStartcase( 'Beep and Boop' )\n false\n\n See Also\n --------\n isString","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isStruct":"\nisStruct( value )\n Tests if a value is a `struct` instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a `struct` instance.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStruct( new S() )\n true\n > bool = isStruct( [ 1, 2, 3, 4 ] )\n false\n > bool = isStruct( 3.14 )\n false\n > bool = isStruct( {} )\n false\n\n See Also\n --------\n isStructConstructorLike, structFactory\n","isStructConstructorLike":"\nisStructConstructorLike( value )\n Tests if a value is struct constructor-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is struct constructor-like.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStructConstructorLike( S )\n true\n > bool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isStructConstructorLike( 3.14 )\n false\n > bool = isStructConstructorLike( {} )\n false\n\n See Also\n --------\n isStruct, structFactory\n","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a built-in typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a built-in typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n Tests if a value is a WebAssembly memory instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a WebAssembly memory instance.\n\n Examples\n --------\n > var bool = isWebAssemblyMemory( {} )\n false\n\n See Also\n --------\n hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n Tests if a string is well-formed.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is well-formed.\n\n Examples\n --------\n > var bool = isWellFormedString( '' )\n true\n\n > bool = isWellFormedString( new String( '' ) )\n true\n\n > bool = isWellFormedString( '\\uDBFF' )\n false\n\n > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n false\n\n > bool = isWellFormedString( [] )\n false\n\n > bool = isWellFormedString( '-5' )\n true\n\n > bool = isWellFormedString( null )\n false\n\n\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false\n\n\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [0,2]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value.\n - index: iterated value index (zero-based).\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value.\n - sprev: previous source iterated value.\n - dprev: previous downstream iterated value.\n - index: source iteration index (zero-based).\n - acc: previous resolved value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterSubtract, iterMultiply\n","iterDoUntilEach":"\niterDoUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoWhileEach, iterUntilEach, iterWhileEach\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1552.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values.\n - index: iteration index (zero-based).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value.\n - index: source iteration index (zero-based).\n - n: iteration index (zero-based).\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value.\n - i: input iteration index (zero-based).\n - n: output (strided) iteration index (zero-based).\n - curr: current stride.\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 64.\n\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant\n object has the next\n iterated value (if one exists) and a\n boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n\n Examples\n --------\n > var it = iterTribonnaciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 0\n\n See Also\n --------\n base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n Returns the last character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = last( 'beep' )\n 'p'\n > out = last( 'Boop', 2 )\n 'op'\n > out = last( 'foo bar', 3 )\n 'bar'\n\n See Also\n --------\n firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n Trims `n` characters from the beginning of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrimN( ' abc ', 2 )\n 'abc '\n > var out = ltrimN( '!!!abc!!!', 2, '!' )\n '!abc!!!'\n\n See Also\n --------\n rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - index: invocation index (starting from zero).\n - next: callback to be invoked upon function completion.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `key`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - key\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - key\n - value\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - key: transformed key.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `value`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - value\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - value\n - key\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - value: transformed value.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","matrix":"\nmatrix( [dtype][, options] )\n Returns a two-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = matrix()\n \n > var sh = ndarrayShape( arr )\n [ 0, 0 ]\n > arr = matrix( 'float32' )\n \n\n\nmatrix( shape[, dtype][, options] )\n Returns a two-dimensional ndarray having a specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = matrix( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > arr = matrix( [ 2, 2 ], 'float32' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n\nmatrix( M, N[, dtype][, options] )\n Returns a two-dimensional ndarray having a specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = matrix( 2, 2 )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > arr = matrix( 2, 2, 'float32' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n\nmatrix( obj[, dtype][, options] )\n Creates a two-dimensional ndarray from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\n > var arr = matrix( v, 'float32' )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n\n\nmatrix( buffer[, byteOffset[, shape]][, dtype][, options] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = matrix( buf, 0, [ 2, 2 ], 'float32' )\n \n\n\nmatrix( buffer[, byteOffset[, M, N]][, dtype][, options] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = matrix( buf, 0, 2, 2, 'float32' )\n \n\n\nmatrix.factory( dtype[, options] )\n Returns a function for creating a two-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a two-dimensional ndarray.\n\n Examples\n --------\n > var f = matrix.factory( 'float32' );\n > var arr = f( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, vector, ndarray\n","matrix.factory":"\nmatrix.factory( dtype[, options] )\n Returns a function for creating a two-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a two-dimensional ndarray.\n\n Examples\n --------\n > var f = matrix.factory( 'float32' );\n > var arr = f( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, vector, ndarray","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size.\n - cities: cities.\n - labels: map labels.\n - temperature: temperature during the army's return from Russia.\n - rivers: river data.\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var rivers = data.rivers\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier).\n - title: chapter title (if available; otherwise, empty).\n - text: chapter text.\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var f = namedtypedtuple( [ 'x', 'y' ] );\n > var p = f( new Float64Array( [ 1.0, -1.0 ] ) );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: ...number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n > p[ 3 ]\n 1.0\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n Converts an ndarray to an object supporting fancy indexing.\n\n An ndarray supporting fancy indexing is an ndarray which supports slicing\n via indexing expressions for both retrieval and assignment.\n\n A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n any mutations to the returned ndarray will affect the underlying input\n ndarray and vice versa.\n\n A fancy ndarray supports indexing using positive and negative integers (both\n numeric literals and strings), Slice and MultiSlice instances, subsequence\n expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n A fancy ndarray supports all properties and methods of the input ndarray,\n and, thus, a fancy ndarray can be consumed by any API which supports\n ndarray-like objects.\n\n For operations returning a new ndarray (e.g., when slicing or invoking an\n instance method), a fancy ndarray returns a new fancy ndarray having the\n same configuration as specified by provided options.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n are repeated (without additional memory allocation) to match the dimensions\n of a target ndarray instance.\n\n When assigning ndarrays to slices, the ndarray on the right-hand-side must\n be broadcast-compatible with dimensions implied by the slice.\n\n Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point ndarrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy ndarrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number ndarray, a fancy\n ndarray will cast the real-valued scalar to a complex number argument having\n an imaginary component equal to zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n out: ndarray\n Output ndarray supporting fancy indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Convert to a fancy ndarray:\n > var arr = ndarray2fancy( x );\n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n Serializes an ndarray as a JSON object.\n\n This function does *not* serialize data outside of the buffer region defined\n by the ndarray view.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2json( arr )\n {...}\n\n See Also\n --------\n array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex32: half-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int8: signed 8-bit integers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - binary: binary.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n [...]\n > out = ndarrayDataTypes( 'floating_point' )\n [...]\n > out = ndarrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n \n\n\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n \n\n\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n \n\n\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n \n\n\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n \n\n\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n \n\n\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n \n\n\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n \n\n\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n \n\n\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n \n\n\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n \n\n\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n \n\n\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n \n\n\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n \n\n\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n \n\n\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n ","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n ","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n ","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n ","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n ","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n ","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n ","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n ","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n ","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n ","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n ","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n ","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n ","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n ","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n ","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n Converts an ndarray-like object to an ndarray.\n\n If provided a read-only ndarray, the function returns a read-only ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray-like object.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarraylike2ndarray( arr )\n \n\n See Also\n --------\n array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndemptyLike( x )\n \n\n See Also\n --------\n ndempty, ndzerosLike\n","ndfill":"\nndfill( x, value )\n Fills an input ndarray with a specified value.\n\n If `value` is a number and `x` has a complex data type, the function fills\n an input ndarray with a complex number whose real component equals the\n provided scalar `value` and whose imaginary component is zero.\n\n The function *mutates* the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n value: any\n Scalar value. Must be able to safely cast to the input ndarray data\n type. Scalar values having floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., a scalar double-precision floating-point number can be\n used to fill a 'float32' input ndarray).\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > ndfill( x, 10.0 );\n > x.get( 0, 0 )\n 10.0\n\n See Also\n --------\n ndfillBy, ndmap, ndzeros\n","ndfillBy":"\nndfillBy( x, fcn[, thisArg] )\n Fills an input ndarray according to a callback function.\n\n The function *mutates* the input ndarray.\n\n The function assumes that each element in the underlying input ndarray data\n buffer has one, and only one, corresponding element in input ndarray view\n (i.e., a provided ndarray is not a broadcasted ndarray view).\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > function fcn() { return 10.0; };\n > ndfillBy( x, fcn );\n > x.get( 0, 0 )\n 10.0\n > x.get( 0, 1 )\n 10.0\n > x.get( 1, 0 )\n 10.0\n > x.get( 1, 1 )\n 10.0\n\n See Also\n --------\n ndfill, ndmap, ndzeros\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v > 2.0; };\n > var y = ndfilter( x, f )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n If a provided callback function returns `undefined`, the function skips the\n respective ndarray element. If the callback function returns a value other\n than `undefined`, the function stores the callback's return value in the\n output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n > var y = ndfilterMap( x, f )\n [ 30.0, 40.0 ]\n\n See Also\n --------\n ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n Invokes a callback function once for each ndarray element.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n > ndforEach( x, f );\n\n See Also\n --------\n ndmap","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n Wraps a provided array as an ndarray index object.\n\n ndarray index instances have no explicit functionality; however, they are\n used by \"fancy\" ndarrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying ndarray are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped ndarray, as the consumer will attempt to resolve an\n instance in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n\n\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n \n\n\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}\n\n\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n \n\n\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'\n\n\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n \n\n\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true\n\n\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'\n\n\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n \n\n\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n \n\n\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n ","ndindex.get":"\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n ","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n ","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n ","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n ","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy","nditer2arrayEach":"\nnditer2arrayEach( iterator )\n Returns an iterator which converts each iterated ndarray to a generic array.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditer2arrayEach( nditerRows( x ) );\n > var v = it.next().value\n [ 1, 2 ]\n > v = it.next().value\n [ 3, 4 ]\n\n See Also\n --------\n ndarray, ndarray2array\n","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n Returns an iterator which iterates over interleaved subarrays.\n\n For input ndarrays supporting read-only views, the function returns\n *read-only* views of interleaved subarrays. As input ndarrays may be\n broadcasted, a view is typically *not* contiguous. As more than one element\n of a returned view may refer to the same memory location, writing to a view\n may affect multiple elements. If you need to write to a subarray, copy the\n subarray before attempting mutation.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n arr: ArrayLike\n Input ndarrays. All ndarrays must be broadcast-compatible. After\n broadcasting, each broadcasted input ndarray must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack after broadcasting.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n options.keepdim: boolean (optional)\n Boolean indicating whether returned views should include the selected\n dimension as a singleton dimension. Including the selected dimension as\n a singleton dimension can be useful when wanting to ensure that returned\n views remain broadcast compatible with the input ndarray. Default:\n false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSelectDimension( x, 0 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `dims.length+1` dimensions.\n\n dims: Array\n Indices of dimensions to stack. If a dimension index is less than zero,\n the index is resolved relative to the last dimension, with the last\n dimension corresponding to the value `-1`. The list of indices must be\n unique and resolve to dimension indices sorted in ascending order.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerStacks( x, [ 1, 2 ] );\n > var v = it.next().value\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSubarrays( x, 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v*10.0; };\n > var y = ndmap( x, f )\n [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v <= 2.0; };\n > var y = ndreject( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a numeric or \"generic\" data type. Default:\n 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a numeric or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n > var bool = noneInBy( obj, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all own properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function isUnderage( v ) { return ( v < 18 ); };\n > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n > var bool = noneOwnBy( obj, isUnderage )\n false\n\n See Also\n --------\n anyOwnBy, everyOwnBy, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n In older JavaScript engines, insertion order is not guaranteed, as object\n key enumeration was not specified according to the ECMAScript specification\n in earlier editions. In practice, however, most older engines use insertion\n order to sort an object's keys, thus allowing for deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number.\n - town: town name.\n - town_id: town identifier.\n - tract: tract identifier.\n - lon: longitude.\n - lat: latitude.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - bh: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - bonferroni: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - by: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - holm: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - hommel: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if the prototype was successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n random.beta, base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n random.beta, base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.binomial, random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.binomial, random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n random.cauchy, base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n random.cauchy, base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n random.cosine, base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n random.cosine, base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, random.discreteUniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, random.discreteUniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n random.erlang, base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n random.erlang, base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n random.f, base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n random.f, base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n random.gamma, base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n random.gamma, base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n random.gumbel, base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n random.gumbel, base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n random.kumaraswamy, base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n random.kumaraswamy, base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n random.laplace, base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n random.laplace, base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n random.levy, base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n random.levy, base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n random.logistic, base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n random.logistic, base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.negativeBinomial, random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.negativeBinomial, random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n random.normal, base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n random.normal, base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t, random.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t, random.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform, random.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform, random.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.beta, base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.beta, base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.cosine, base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.cosine, base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.discreteUniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.discreteUniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.gamma, base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.gamma, base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.normal, base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.normal, base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n random.rayleigh, base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n random.rayleigh, base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n random.t, base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n random.t, base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.uniform, base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.uniform, base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.weibull, base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.weibull, base.random.weibull, random.array.weibull","random.arcsine":"\nrandom.arcsine( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.arcsine.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.arcsine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.arcsine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an arcsine\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.arcsine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.arcsine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.arcsine.PRNG;\n\n\nrandom.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.arcsine.seed;\n\n\nrandom.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.arcsine.seedLength;\n\n\nrandom.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.arcsine.state\n \n\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.arcsine.stateLength;\n\n\nrandom.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine, random.strided.arcsine\n","random.arcsine.assign":"\nrandom.arcsine.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.arcsine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.arcsine.factory":"\nrandom.arcsine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an arcsine\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.arcsine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.arcsine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.arcsine.PRNG":"\nrandom.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.arcsine.PRNG;","random.arcsine.seed":"\nrandom.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.arcsine.seed;","random.arcsine.seedLength":"\nrandom.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.arcsine.seedLength;","random.arcsine.state":"\nrandom.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.arcsine.state\n \n\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n ","random.arcsine.stateLength":"\nrandom.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.arcsine.stateLength;","random.arcsine.byteLength":"\nrandom.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine, random.strided.arcsine","random.bernoulli":"\nrandom.bernoulli( shape, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n\nrandom.bernoulli.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.bernoulli.assign( 0.5, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.bernoulli.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.bernoulli` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.bernoulli.factory();\n > var out = fcn( [ 3, 3 ], 0.5 )\n \n\n\nrandom.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.bernoulli.PRNG;\n\n\nrandom.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.bernoulli.seed;\n\n\nrandom.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.bernoulli.seedLength;\n\n\nrandom.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.bernoulli.state\n \n\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Set the state:\n > random.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n\nrandom.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.bernoulli.stateLength;\n\n\nrandom.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli, random.strided.bernoulli\n","random.bernoulli.assign":"\nrandom.bernoulli.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.bernoulli.assign( 0.5, out )\n \n > var bool = ( v === out )\n true","random.bernoulli.factory":"\nrandom.bernoulli.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.bernoulli` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.bernoulli.factory();\n > var out = fcn( [ 3, 3 ], 0.5 )\n ","random.bernoulli.PRNG":"\nrandom.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.bernoulli.PRNG;","random.bernoulli.seed":"\nrandom.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.bernoulli.seed;","random.bernoulli.seedLength":"\nrandom.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.bernoulli.seedLength;","random.bernoulli.state":"\nrandom.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.bernoulli.state\n \n\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Set the state:\n > random.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n ","random.bernoulli.stateLength":"\nrandom.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.bernoulli.stateLength;","random.bernoulli.byteLength":"\nrandom.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli, random.strided.bernoulli","random.beta":"\nrandom.beta( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.beta.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.beta.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.beta.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a beta\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.beta` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.beta.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.beta.PRNG;\n\n\nrandom.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.beta.seed;\n\n\nrandom.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.beta.seedLength;\n\n\nrandom.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.beta.state\n \n\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.beta.stateLength;\n\n\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.array.beta, random.strided.beta\n","random.beta.assign":"\nrandom.beta.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.beta.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.beta.factory":"\nrandom.beta.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a beta\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.beta` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.beta.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.beta.PRNG":"\nrandom.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.beta.PRNG;","random.beta.seed":"\nrandom.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.beta.seed;","random.beta.seedLength":"\nrandom.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.beta.seedLength;","random.beta.state":"\nrandom.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.beta.state\n \n\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n ","random.beta.stateLength":"\nrandom.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.beta.stateLength;","random.beta.byteLength":"\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.array.beta, random.strided.beta","random.betaprime":"\nrandom.betaprime( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a betaprime\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a betaprime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n betaprime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.betaprime.PRNG;\n\n\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.betaprime.seed;\n\n\nrandom.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.betaprime.seedLength;\n\n\nrandom.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.betaprime.state\n \n\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.betaprime.stateLength;\n\n\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime, random.strided.betaprime\n","random.betaprime.assign":"\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a betaprime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.betaprime.factory":"\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n betaprime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.betaprime.PRNG":"\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.betaprime.PRNG;","random.betaprime.seed":"\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.betaprime.seed;","random.betaprime.seedLength":"\nrandom.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.betaprime.seedLength;","random.betaprime.state":"\nrandom.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.betaprime.state\n \n\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n ","random.betaprime.stateLength":"\nrandom.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.betaprime.stateLength;","random.betaprime.byteLength":"\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime, random.strided.betaprime","random.binomial":"\nrandom.binomial( shape, n, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n n: number|ndarray\n Number of trials. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.binomial.assign( n, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n n: number|ndarray\n Number of trials. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.binomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.binomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a binomial\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.binomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.binomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.binomial.PRNG;\n\n\nrandom.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.binomial.seed;\n\n\nrandom.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.binomial.seedLength;\n\n\nrandom.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.binomial.state\n \n\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.binomial.stateLength;\n\n\nrandom.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.binomial.byteLength;\n\n See Also\n --------\n base.random.binomial, random.array.binomial\n","random.binomial.assign":"\nrandom.binomial.assign( n, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n n: number|ndarray\n Number of trials. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.binomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true","random.binomial.factory":"\nrandom.binomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a binomial\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.binomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.binomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n ","random.binomial.PRNG":"\nrandom.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.binomial.PRNG;","random.binomial.seed":"\nrandom.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.binomial.seed;","random.binomial.seedLength":"\nrandom.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.binomial.seedLength;","random.binomial.state":"\nrandom.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.binomial.state\n \n\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n ","random.binomial.stateLength":"\nrandom.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.binomial.stateLength;","random.binomial.byteLength":"\nrandom.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.binomial.byteLength;\n\n See Also\n --------\n base.random.binomial, random.array.binomial","random.cauchy":"\nrandom.cauchy( shape, x0, gamma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n x0: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n gamma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cauchy.assign( x0, gamma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n gamma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cauchy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.cauchy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Cauchy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cauchy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cauchy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cauchy.PRNG;\n\n\nrandom.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cauchy.seed;\n\n\nrandom.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cauchy.seedLength;\n\n\nrandom.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cauchy.state\n \n\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cauchy.stateLength;\n\n\nrandom.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy, random.array.cauchy\n","random.cauchy.assign":"\nrandom.cauchy.assign( x0, gamma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n gamma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cauchy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.cauchy.factory":"\nrandom.cauchy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Cauchy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cauchy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cauchy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.cauchy.PRNG":"\nrandom.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cauchy.PRNG;","random.cauchy.seed":"\nrandom.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cauchy.seed;","random.cauchy.seedLength":"\nrandom.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cauchy.seedLength;","random.cauchy.state":"\nrandom.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cauchy.state\n \n\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n ","random.cauchy.stateLength":"\nrandom.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cauchy.stateLength;","random.cauchy.byteLength":"\nrandom.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy, random.array.cauchy","random.chi":"\nrandom.chi( shape, k[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.chi( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chi.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chi.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.chi.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chi` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chi.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chi.PRNG;\n\n\nrandom.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chi.seed;\n\n\nrandom.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chi.seedLength;\n\n\nrandom.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chi.state\n \n\n > out = random.chi( [ 3, 3 ], 2.0 )\n \n > out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.chi( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chi.stateLength;\n\n\nrandom.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi, random.strided.chi\n","random.chi.assign":"\nrandom.chi.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chi.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.chi.factory":"\nrandom.chi.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chi` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chi.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.chi.PRNG":"\nrandom.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chi.PRNG;","random.chi.seed":"\nrandom.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chi.seed;","random.chi.seedLength":"\nrandom.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chi.seedLength;","random.chi.state":"\nrandom.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chi.state\n \n\n > out = random.chi( [ 3, 3 ], 2.0 )\n \n > out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.chi( [ 3, 3 ], 2.0 )\n ","random.chi.stateLength":"\nrandom.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chi.stateLength;","random.chi.byteLength":"\nrandom.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi, random.strided.chi","random.chisquare":"\nrandom.chisquare( shape, k[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chisquare.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chisquare.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.chisquare.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi-\n square distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chisquare` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chisquare.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chisquare.PRNG;\n\n\nrandom.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chisquare.seed;\n\n\nrandom.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chisquare.seedLength;\n\n\nrandom.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chisquare.state\n \n\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chisquare.stateLength;\n\n\nrandom.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare, random.strided.chisquare\n","random.chisquare.assign":"\nrandom.chisquare.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chisquare.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.chisquare.factory":"\nrandom.chisquare.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi-\n square distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chisquare` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chisquare.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.chisquare.PRNG":"\nrandom.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chisquare.PRNG;","random.chisquare.seed":"\nrandom.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chisquare.seed;","random.chisquare.seedLength":"\nrandom.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chisquare.seedLength;","random.chisquare.state":"\nrandom.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chisquare.state\n \n\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n ","random.chisquare.stateLength":"\nrandom.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chisquare.stateLength;","random.chisquare.byteLength":"\nrandom.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare, random.strided.chisquare","random.cosine":"\nrandom.cosine( shape, mu, s[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a raised\n cosine distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cosine.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cosine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.cosine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cosine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cosine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cosine.PRNG;\n\n\nrandom.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cosine.seed;\n\n\nrandom.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cosine.seedLength;\n\n\nrandom.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cosine.state\n \n\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cosine.stateLength;\n\n\nrandom.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.array.cosine, random.strided.cosine\n","random.cosine.assign":"\nrandom.cosine.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cosine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.cosine.factory":"\nrandom.cosine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cosine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cosine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.cosine.PRNG":"\nrandom.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cosine.PRNG;","random.cosine.seed":"\nrandom.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cosine.seed;","random.cosine.seedLength":"\nrandom.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cosine.seedLength;","random.cosine.state":"\nrandom.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cosine.state\n \n\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n ","random.cosine.stateLength":"\nrandom.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cosine.stateLength;","random.cosine.byteLength":"\nrandom.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.array.cosine, random.strided.cosine","random.discreteUniform":"\nrandom.discreteUniform( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n\nrandom.discreteUniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.discreteUniform.assign( -10, 10, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.discreteUniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.discreteUniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.discreteUniform.factory();\n > var out = fcn( [ 3, 3 ], -10, 10 )\n \n\n\nrandom.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.discreteUniform.PRNG;\n\n\nrandom.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.discreteUniform.seed;\n\n\nrandom.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.discreteUniform.seedLength;\n\n\nrandom.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.discreteUniform.state\n \n\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Set the state:\n > random.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n\nrandom.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.discreteUniform.stateLength;\n\n\nrandom.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.discreteUniform.byteLength;\n\n See Also\n --------\n random.uniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.discreteUniform\n","random.discreteUniform.assign":"\nrandom.discreteUniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.discreteUniform.assign( -10, 10, out )\n \n > var bool = ( v === out )\n true","random.discreteUniform.factory":"\nrandom.discreteUniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.discreteUniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.discreteUniform.factory();\n > var out = fcn( [ 3, 3 ], -10, 10 )\n ","random.discreteUniform.PRNG":"\nrandom.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.discreteUniform.PRNG;","random.discreteUniform.seed":"\nrandom.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.discreteUniform.seed;","random.discreteUniform.seedLength":"\nrandom.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.discreteUniform.seedLength;","random.discreteUniform.state":"\nrandom.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.discreteUniform.state\n \n\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Set the state:\n > random.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n ","random.discreteUniform.stateLength":"\nrandom.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.discreteUniform.stateLength;","random.discreteUniform.byteLength":"\nrandom.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.discreteUniform.byteLength;\n\n See Also\n --------\n random.uniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.discreteUniform","random.erlang":"\nrandom.erlang( shape, k, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n\nrandom.erlang.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.erlang.assign( 2, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.erlang.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.erlang` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.erlang.factory();\n > var out = fcn( [ 3, 3 ], 2, 5.0 )\n \n\n\nrandom.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.erlang.PRNG;\n\n\nrandom.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.erlang.seed;\n\n\nrandom.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.erlang.seedLength;\n\n\nrandom.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.erlang.state\n \n\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Set the state:\n > random.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n\nrandom.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.erlang.stateLength;\n\n\nrandom.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang, random.array.erlang\n","random.erlang.assign":"\nrandom.erlang.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.erlang.assign( 2, 5.0, out )\n \n > var bool = ( v === out )\n true","random.erlang.factory":"\nrandom.erlang.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.erlang` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.erlang.factory();\n > var out = fcn( [ 3, 3 ], 2, 5.0 )\n ","random.erlang.PRNG":"\nrandom.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.erlang.PRNG;","random.erlang.seed":"\nrandom.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.erlang.seed;","random.erlang.seedLength":"\nrandom.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.erlang.seedLength;","random.erlang.state":"\nrandom.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.erlang.state\n \n\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Set the state:\n > random.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n ","random.erlang.stateLength":"\nrandom.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.erlang.stateLength;","random.erlang.byteLength":"\nrandom.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang, random.array.erlang","random.exponential":"\nrandom.exponential( shape, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n\nrandom.exponential.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.exponential.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.exponential.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.exponential` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.exponential.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.exponential.PRNG;\n\n\nrandom.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.exponential.seed;\n\n\nrandom.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.exponential.seedLength;\n\n\nrandom.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.exponential.state\n \n\n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n\nrandom.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.exponential.stateLength;\n\n\nrandom.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential, random.strided.exponential\n","random.exponential.assign":"\nrandom.exponential.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.exponential.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.exponential.factory":"\nrandom.exponential.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.exponential` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.exponential.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.exponential.PRNG":"\nrandom.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.exponential.PRNG;","random.exponential.seed":"\nrandom.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.exponential.seed;","random.exponential.seedLength":"\nrandom.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.exponential.seedLength;","random.exponential.state":"\nrandom.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.exponential.state\n \n\n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.exponential( [ 3, 3 ], 2.0 )\n ","random.exponential.stateLength":"\nrandom.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.exponential.stateLength;","random.exponential.byteLength":"\nrandom.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential, random.strided.exponential","random.f":"\nrandom.f( shape, d1, d2[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n d1: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n d2: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.f.assign( d1, d2, out )\n Fills an ndarray with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n d2: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.f.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.f.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an F\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.f` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.f.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.f.PRNG;\n\n\nrandom.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.f.seed;\n\n\nrandom.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.f.seedLength;\n\n\nrandom.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.f.state\n \n\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.f.state = state;\n\n // Regenerate a previous array:\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.f.stateLength;\n\n\nrandom.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.f.byteLength;\n\n See Also\n --------\n base.random.f, random.array.f\n","random.f.assign":"\nrandom.f.assign( d1, d2, out )\n Fills an ndarray with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n d2: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.f.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.f.factory":"\nrandom.f.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an F\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.f` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.f.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.f.PRNG":"\nrandom.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.f.PRNG;","random.f.seed":"\nrandom.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.f.seed;","random.f.seedLength":"\nrandom.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.f.seedLength;","random.f.state":"\nrandom.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.f.state\n \n\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.f.state = state;\n\n // Regenerate a previous array:\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n ","random.f.stateLength":"\nrandom.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.f.stateLength;","random.f.byteLength":"\nrandom.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.f.byteLength;\n\n See Also\n --------\n base.random.f, random.array.f","random.frechet":"\nrandom.frechet( shape, alpha, s, m[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n m: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.frechet.assign( alpha, s, m, out )\n Fills an ndarray with pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n m: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.frechet.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.frechet.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.frechet` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.frechet.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.frechet.PRNG;\n\n\nrandom.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.frechet.seed;\n\n\nrandom.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.frechet.seedLength;\n\n\nrandom.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.frechet.state\n \n\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.frechet.stateLength;\n\n\nrandom.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.array.frechet\n","random.frechet.assign":"\nrandom.frechet.assign( alpha, s, m, out )\n Fills an ndarray with pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n m: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.frechet.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true","random.frechet.factory":"\nrandom.frechet.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.frechet` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.frechet.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.frechet.PRNG":"\nrandom.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.frechet.PRNG;","random.frechet.seed":"\nrandom.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.frechet.seed;","random.frechet.seedLength":"\nrandom.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.frechet.seedLength;","random.frechet.state":"\nrandom.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.frechet.state\n \n\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.frechet.stateLength":"\nrandom.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.frechet.stateLength;","random.frechet.byteLength":"\nrandom.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.array.frechet","random.gamma":"\nrandom.gamma( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n beta: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.gamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gamma.PRNG;\n\n\nrandom.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gamma.seed;\n\n\nrandom.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gamma.seedLength;\n\n\nrandom.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gamma.state\n \n\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gamma.stateLength;\n\n\nrandom.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.array.gamma, random.strided.gamma\n","random.gamma.assign":"\nrandom.gamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.gamma.factory":"\nrandom.gamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.gamma.PRNG":"\nrandom.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gamma.PRNG;","random.gamma.seed":"\nrandom.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gamma.seed;","random.gamma.seedLength":"\nrandom.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gamma.seedLength;","random.gamma.state":"\nrandom.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gamma.state\n \n\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n ","random.gamma.stateLength":"\nrandom.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gamma.stateLength;","random.gamma.byteLength":"\nrandom.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.array.gamma, random.strided.gamma","random.geometric":"\nrandom.geometric( shape, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n\nrandom.geometric.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.geometric.assign( 0.01, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.geometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.geometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.geometric.factory();\n > var out = fcn( [ 3, 3 ], 0.01 )\n \n\n\nrandom.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.geometric.PRNG;\n\n\nrandom.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.geometric.seed;\n\n\nrandom.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.geometric.seedLength;\n\n\nrandom.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.geometric.state\n \n\n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Set the state:\n > random.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n\nrandom.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.geometric.stateLength;\n\n\nrandom.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric, random.strided.geometric\n","random.geometric.assign":"\nrandom.geometric.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.geometric.assign( 0.01, out )\n \n > var bool = ( v === out )\n true","random.geometric.factory":"\nrandom.geometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.geometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.geometric.factory();\n > var out = fcn( [ 3, 3 ], 0.01 )\n ","random.geometric.PRNG":"\nrandom.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.geometric.PRNG;","random.geometric.seed":"\nrandom.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.geometric.seed;","random.geometric.seedLength":"\nrandom.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.geometric.seedLength;","random.geometric.state":"\nrandom.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.geometric.state\n \n\n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Set the state:\n > random.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.geometric( [ 3, 3 ], 0.01 )\n ","random.geometric.stateLength":"\nrandom.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.geometric.stateLength;","random.geometric.byteLength":"\nrandom.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric, random.strided.geometric","random.gumbel":"\nrandom.gumbel( shape, mu, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gumbel.assign( mu, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gumbel.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.gumbel.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gumbel` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gumbel.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gumbel.PRNG;\n\n\nrandom.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gumbel.seed;\n\n\nrandom.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gumbel.seedLength;\n\n\nrandom.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gumbel.state\n \n\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gumbel.stateLength;\n\n\nrandom.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel, random.array.gumbel\n","random.gumbel.assign":"\nrandom.gumbel.assign( mu, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gumbel.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.gumbel.factory":"\nrandom.gumbel.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gumbel` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gumbel.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.gumbel.PRNG":"\nrandom.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gumbel.PRNG;","random.gumbel.seed":"\nrandom.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gumbel.seed;","random.gumbel.seedLength":"\nrandom.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gumbel.seedLength;","random.gumbel.state":"\nrandom.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gumbel.state\n \n\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n ","random.gumbel.stateLength":"\nrandom.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gumbel.stateLength;","random.gumbel.byteLength":"\nrandom.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel, random.array.gumbel","random.hypergeometric":"\nrandom.hypergeometric( shape, N, K, n[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n N: number|ndarray\n Population size. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n K: number|ndarray\n Subpopulation size. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n n: number|ndarray\n Number of draws. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n\nrandom.hypergeometric.assign( N, K, n, out )\n Fills an ndarray with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number|ndarray\n Population size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n K: number|ndarray\n Subpopulation size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n n: number|ndarray\n Number of draws. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.hypergeometric.assign( 20, 10, 7, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.hypergeometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.hypergeometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.hypergeometric.factory();\n > var out = fcn( [ 3, 3 ], 20, 10, 7 )\n \n\n\nrandom.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.hypergeometric.PRNG;\n\n\nrandom.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.hypergeometric.seed;\n\n\nrandom.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.hypergeometric.seedLength;\n\n\nrandom.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.hypergeometric.state\n \n\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Set the state:\n > random.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n\nrandom.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.hypergeometric.stateLength;\n\n\nrandom.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.array.hypergeometric\n","random.hypergeometric.assign":"\nrandom.hypergeometric.assign( N, K, n, out )\n Fills an ndarray with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number|ndarray\n Population size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n K: number|ndarray\n Subpopulation size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n n: number|ndarray\n Number of draws. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.hypergeometric.assign( 20, 10, 7, out )\n \n > var bool = ( v === out )\n true","random.hypergeometric.factory":"\nrandom.hypergeometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.hypergeometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.hypergeometric.factory();\n > var out = fcn( [ 3, 3 ], 20, 10, 7 )\n ","random.hypergeometric.PRNG":"\nrandom.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.hypergeometric.PRNG;","random.hypergeometric.seed":"\nrandom.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.hypergeometric.seed;","random.hypergeometric.seedLength":"\nrandom.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.hypergeometric.seedLength;","random.hypergeometric.state":"\nrandom.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.hypergeometric.state\n \n\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Set the state:\n > random.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n ","random.hypergeometric.stateLength":"\nrandom.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.hypergeometric.stateLength;","random.hypergeometric.byteLength":"\nrandom.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.array.hypergeometric","random.invgamma":"\nrandom.invgamma( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an inverse\n gamma distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.invgamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.invgamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.invgamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an inverse\n gamma distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.invgamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.invgamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.invgamma.PRNG;\n\n\nrandom.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.invgamma.seed;\n\n\nrandom.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.invgamma.seedLength;\n\n\nrandom.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.invgamma.state\n \n\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.invgamma.stateLength;\n\n\nrandom.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma, random.strided.invgamma\n","random.invgamma.assign":"\nrandom.invgamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.invgamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.invgamma.factory":"\nrandom.invgamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an inverse\n gamma distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.invgamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.invgamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.invgamma.PRNG":"\nrandom.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.invgamma.PRNG;","random.invgamma.seed":"\nrandom.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.invgamma.seed;","random.invgamma.seedLength":"\nrandom.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.invgamma.seedLength;","random.invgamma.state":"\nrandom.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.invgamma.state\n \n\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n ","random.invgamma.stateLength":"\nrandom.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.invgamma.stateLength;","random.invgamma.byteLength":"\nrandom.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma, random.strided.invgamma","random.kumaraswamy":"\nrandom.kumaraswamy( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.kumaraswamy.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.kumaraswamy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.kumaraswamy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Kumaraswamy distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.kumaraswamy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.kumaraswamy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.kumaraswamy.PRNG;\n\n\nrandom.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.kumaraswamy.seed;\n\n\nrandom.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.kumaraswamy.seedLength;\n\n\nrandom.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.kumaraswamy.state\n \n\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.kumaraswamy.stateLength;\n\n\nrandom.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy, random.array.kumaraswamy\n","random.kumaraswamy.assign":"\nrandom.kumaraswamy.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.kumaraswamy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.kumaraswamy.factory":"\nrandom.kumaraswamy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Kumaraswamy distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.kumaraswamy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.kumaraswamy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.kumaraswamy.PRNG":"\nrandom.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.kumaraswamy.PRNG;","random.kumaraswamy.seed":"\nrandom.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.kumaraswamy.seed;","random.kumaraswamy.seedLength":"\nrandom.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.kumaraswamy.seedLength;","random.kumaraswamy.state":"\nrandom.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.kumaraswamy.state\n \n\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n ","random.kumaraswamy.stateLength":"\nrandom.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.kumaraswamy.stateLength;","random.kumaraswamy.byteLength":"\nrandom.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy, random.array.kumaraswamy","random.laplace":"\nrandom.laplace( shape, mu, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n b: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.laplace.assign( mu, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n b: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.laplace.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.laplace.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.laplace` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.laplace.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.laplace.PRNG;\n\n\nrandom.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.laplace.seed;\n\n\nrandom.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.laplace.seedLength;\n\n\nrandom.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.laplace.state\n \n\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.laplace.stateLength;\n\n\nrandom.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace, random.array.laplace\n","random.laplace.assign":"\nrandom.laplace.assign( mu, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n b: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.laplace.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.laplace.factory":"\nrandom.laplace.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.laplace` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.laplace.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.laplace.PRNG":"\nrandom.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.laplace.PRNG;","random.laplace.seed":"\nrandom.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.laplace.seed;","random.laplace.seedLength":"\nrandom.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.laplace.seedLength;","random.laplace.state":"\nrandom.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.laplace.state\n \n\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n ","random.laplace.stateLength":"\nrandom.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.laplace.stateLength;","random.laplace.byteLength":"\nrandom.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace, random.array.laplace","random.levy":"\nrandom.levy( shape, mu, c[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n c: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.levy.assign( mu, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.levy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.levy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.levy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.levy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.levy.PRNG;\n\n\nrandom.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.levy.seed;\n\n\nrandom.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.levy.seedLength;\n\n\nrandom.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.levy.state\n \n\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.levy.stateLength;\n\n\nrandom.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.levy.byteLength;\n\n See Also\n --------\n base.random.levy, random.array.levy\n","random.levy.assign":"\nrandom.levy.assign( mu, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.levy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.levy.factory":"\nrandom.levy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.levy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.levy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.levy.PRNG":"\nrandom.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.levy.PRNG;","random.levy.seed":"\nrandom.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.levy.seed;","random.levy.seedLength":"\nrandom.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.levy.seedLength;","random.levy.state":"\nrandom.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.levy.state\n \n\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n ","random.levy.stateLength":"\nrandom.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.levy.stateLength;","random.levy.byteLength":"\nrandom.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.levy.byteLength;\n\n See Also\n --------\n base.random.levy, random.array.levy","random.logistic":"\nrandom.logistic( shape, mu, s[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.logistic.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.logistic.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.logistic.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a logistic\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.logistic` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.logistic.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.logistic.PRNG;\n\n\nrandom.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.logistic.seed;\n\n\nrandom.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.logistic.seedLength;\n\n\nrandom.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.logistic.state\n \n\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.logistic.stateLength;\n\n\nrandom.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic, random.array.logistic\n","random.logistic.assign":"\nrandom.logistic.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.logistic.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.logistic.factory":"\nrandom.logistic.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a logistic\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.logistic` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.logistic.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.logistic.PRNG":"\nrandom.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.logistic.PRNG;","random.logistic.seed":"\nrandom.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.logistic.seed;","random.logistic.seedLength":"\nrandom.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.logistic.seedLength;","random.logistic.state":"\nrandom.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.logistic.state\n \n\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n ","random.logistic.stateLength":"\nrandom.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.logistic.stateLength;","random.logistic.byteLength":"\nrandom.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic, random.array.logistic","random.lognormal":"\nrandom.lognormal( shape, mu, sigma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.lognormal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.lognormal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.lognormal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.lognormal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.lognormal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.lognormal.PRNG;\n\n\nrandom.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.lognormal.seed;\n\n\nrandom.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.lognormal.seedLength;\n\n\nrandom.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.lognormal.state\n \n\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.lognormal.stateLength;\n\n\nrandom.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal, random.strided.lognormal\n","random.lognormal.assign":"\nrandom.lognormal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.lognormal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.lognormal.factory":"\nrandom.lognormal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.lognormal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.lognormal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.lognormal.PRNG":"\nrandom.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.lognormal.PRNG;","random.lognormal.seed":"\nrandom.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.lognormal.seed;","random.lognormal.seedLength":"\nrandom.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.lognormal.seedLength;","random.lognormal.state":"\nrandom.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.lognormal.state\n \n\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n ","random.lognormal.stateLength":"\nrandom.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.lognormal.stateLength;","random.lognormal.byteLength":"\nrandom.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal, random.strided.lognormal","random.negativeBinomial":"\nrandom.negativeBinomial( shape, r, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n r: number|ndarray\n Number of successes until experiment is stopped. If an ndarray, must be\n broadcast compatible with the specified array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.negativeBinomial.assign( r, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number|ndarray\n Number of successes until experiment is stopped. If an ndarray, must be\n broadcast compatible with the provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.negativeBinomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.negativeBinomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a negative\n binomial distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.negativeBinomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.negativeBinomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.negativeBinomial.PRNG;\n\n\nrandom.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.negativeBinomial.seed;\n\n\nrandom.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.negativeBinomial.seedLength;\n\n\nrandom.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.negativeBinomial.state\n \n\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.negativeBinomial.stateLength;\n\n\nrandom.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.negativeBinomial.byteLength;\n\n See Also\n --------\n base.random.negativeBinomial, random.array.negativeBinomial\n","random.negativeBinomial.assign":"\nrandom.negativeBinomial.assign( r, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number|ndarray\n Number of successes until experiment is stopped. If an ndarray, must be\n broadcast compatible with the provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.negativeBinomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true","random.negativeBinomial.factory":"\nrandom.negativeBinomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a negative\n binomial distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.negativeBinomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.negativeBinomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n ","random.negativeBinomial.PRNG":"\nrandom.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.negativeBinomial.PRNG;","random.negativeBinomial.seed":"\nrandom.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.negativeBinomial.seed;","random.negativeBinomial.seedLength":"\nrandom.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.negativeBinomial.seedLength;","random.negativeBinomial.state":"\nrandom.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.negativeBinomial.state\n \n\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n ","random.negativeBinomial.stateLength":"\nrandom.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.negativeBinomial.stateLength;","random.negativeBinomial.byteLength":"\nrandom.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.negativeBinomial.byteLength;\n\n See Also\n --------\n base.random.negativeBinomial, random.array.negativeBinomial","random.normal":"\nrandom.normal( shape, mu, sigma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n sigma: number|ndarray\n Standard deviation. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.normal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n sigma: number|ndarray\n Standard deviation. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.normal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.normal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a normal\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.normal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.normal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.normal.PRNG;\n\n\nrandom.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.normal.seed;\n\n\nrandom.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.normal.seedLength;\n\n\nrandom.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.normal.state\n \n\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.normal.stateLength;\n\n\nrandom.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.array.normal, random.strided.normal\n","random.normal.assign":"\nrandom.normal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n sigma: number|ndarray\n Standard deviation. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.normal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.normal.factory":"\nrandom.normal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a normal\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.normal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.normal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.normal.PRNG":"\nrandom.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.normal.PRNG;","random.normal.seed":"\nrandom.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.normal.seed;","random.normal.seedLength":"\nrandom.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.normal.seedLength;","random.normal.state":"\nrandom.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.normal.state\n \n\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n ","random.normal.stateLength":"\nrandom.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.normal.stateLength;","random.normal.byteLength":"\nrandom.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.array.normal, random.strided.normal","random.pareto1":"\nrandom.pareto1( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.pareto1.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.pareto1.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.pareto1.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.pareto1` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.pareto1.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.pareto1.PRNG;\n\n\nrandom.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.pareto1.seed;\n\n\nrandom.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.pareto1.seedLength;\n\n\nrandom.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.pareto1.state\n \n\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.pareto1.stateLength;\n\n\nrandom.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.array.pareto1\n","random.pareto1.assign":"\nrandom.pareto1.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.pareto1.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.pareto1.factory":"\nrandom.pareto1.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.pareto1` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.pareto1.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.pareto1.PRNG":"\nrandom.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.pareto1.PRNG;","random.pareto1.seed":"\nrandom.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.pareto1.seed;","random.pareto1.seedLength":"\nrandom.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.pareto1.seedLength;","random.pareto1.state":"\nrandom.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.pareto1.state\n \n\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n ","random.pareto1.stateLength":"\nrandom.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.pareto1.stateLength;","random.pareto1.byteLength":"\nrandom.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.array.pareto1","random.poisson":"\nrandom.poisson( shape, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n lambda: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n\nrandom.poisson.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.poisson.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.poisson.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.poisson` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.poisson.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.poisson.PRNG;\n\n\nrandom.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.poisson.seed;\n\n\nrandom.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.poisson.seedLength;\n\n\nrandom.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.poisson.state\n \n\n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n\nrandom.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.poisson.stateLength;\n\n\nrandom.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson, random.strided.poisson\n","random.poisson.assign":"\nrandom.poisson.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.poisson.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.poisson.factory":"\nrandom.poisson.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.poisson` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.poisson.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.poisson.PRNG":"\nrandom.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.poisson.PRNG;","random.poisson.seed":"\nrandom.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.poisson.seed;","random.poisson.seedLength":"\nrandom.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.poisson.seedLength;","random.poisson.state":"\nrandom.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.poisson.state\n \n\n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.poisson( [ 3, 3 ], 2.0 )\n ","random.poisson.stateLength":"\nrandom.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.poisson.stateLength;","random.poisson.byteLength":"\nrandom.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson, random.strided.poisson","random.rayleigh":"\nrandom.rayleigh( shape, sigma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n\nrandom.rayleigh.assign( sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.rayleigh.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.rayleigh.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.rayleigh` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.rayleigh.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.rayleigh.PRNG;\n\n\nrandom.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.rayleigh.seed;\n\n\nrandom.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.rayleigh.seedLength;\n\n\nrandom.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.rayleigh.state\n \n\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n\nrandom.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.rayleigh.stateLength;\n\n\nrandom.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh, random.strided.rayleigh\n","random.rayleigh.assign":"\nrandom.rayleigh.assign( sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.rayleigh.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.rayleigh.factory":"\nrandom.rayleigh.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.rayleigh` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.rayleigh.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.rayleigh.PRNG":"\nrandom.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.rayleigh.PRNG;","random.rayleigh.seed":"\nrandom.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.rayleigh.seed;","random.rayleigh.seedLength":"\nrandom.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.rayleigh.seedLength;","random.rayleigh.state":"\nrandom.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.rayleigh.state\n \n\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n ","random.rayleigh.stateLength":"\nrandom.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.rayleigh.stateLength;","random.rayleigh.byteLength":"\nrandom.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh, random.strided.rayleigh","random.t":"\nrandom.t( shape, v[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Student's t-\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n v: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.t( [ 3, 3 ], 2.0 )\n \n\n\nrandom.t.assign( v, out )\n Fills an ndarray with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n Parameters\n ----------\n v: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.t.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.t.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Student's t-distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.t` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.t.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.t.PRNG;\n\n\nrandom.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.t.seed;\n\n\nrandom.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.t.seedLength;\n\n\nrandom.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.t.state\n \n\n > out = random.t( [ 3, 3 ], 2.0 )\n \n > out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.t.state = state;\n\n // Regenerate a previous array:\n > out = random.t( [ 3, 3 ], 2.0 )\n \n\n\nrandom.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.t.stateLength;\n\n\nrandom.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t, random.strided.t\n","random.t.assign":"\nrandom.t.assign( v, out )\n Fills an ndarray with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n Parameters\n ----------\n v: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.t.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.t.factory":"\nrandom.t.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Student's t-distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.t` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.t.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.t.PRNG":"\nrandom.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.t.PRNG;","random.t.seed":"\nrandom.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.t.seed;","random.t.seedLength":"\nrandom.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.t.seedLength;","random.t.state":"\nrandom.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.t.state\n \n\n > out = random.t( [ 3, 3 ], 2.0 )\n \n > out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.t.state = state;\n\n // Regenerate a previous array:\n > out = random.t( [ 3, 3 ], 2.0 )\n ","random.t.stateLength":"\nrandom.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.t.stateLength;","random.t.byteLength":"\nrandom.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t, random.strided.t","random.triangular":"\nrandom.triangular( shape, a, b, c[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n c: number|ndarray\n Mode. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.triangular.assign( a, b, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Mode. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.triangular.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.triangular.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.triangular` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.triangular.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.triangular.PRNG;\n\n\nrandom.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.triangular.seed;\n\n\nrandom.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.triangular.seedLength;\n\n\nrandom.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.triangular.state\n \n\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.triangular.stateLength;\n\n\nrandom.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.array.triangular\n","random.triangular.assign":"\nrandom.triangular.assign( a, b, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Mode. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.triangular.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true","random.triangular.factory":"\nrandom.triangular.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.triangular` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.triangular.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.triangular.PRNG":"\nrandom.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.triangular.PRNG;","random.triangular.seed":"\nrandom.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.triangular.seed;","random.triangular.seedLength":"\nrandom.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.triangular.seedLength;","random.triangular.state":"\nrandom.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.triangular.state\n \n\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.triangular.stateLength":"\nrandom.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.triangular.stateLength;","random.triangular.byteLength":"\nrandom.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.array.triangular","random.uniform":"\nrandom.uniform( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support (inclusive). If an ndarray, must be broadcast compatible\n with the specified array shape.\n\n b: number|ndarray\n Maximum support (exclusive). If an ndarray, must be broadcast compatible\n with the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n\nrandom.uniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support (inclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n b: number|ndarray\n Maximum support (exclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.uniform.assign( 0.0, 1.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.uniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.uniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.uniform.factory();\n > var out = fcn( [ 3, 3 ], 0.0, 1.0 )\n \n\n\nrandom.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.uniform.PRNG;\n\n\nrandom.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.uniform.seed;\n\n\nrandom.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.uniform.seedLength;\n\n\nrandom.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Get a copy of the current state:\n > var state = random.uniform.state\n \n\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Set the state:\n > random.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n\nrandom.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.uniform.stateLength;\n\n\nrandom.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.uniform.byteLength;\n\n See Also\n --------\n random.discreteUniform, base.random.uniform, random.array.uniform, random.strided.uniform\n","random.uniform.assign":"\nrandom.uniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support (inclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n b: number|ndarray\n Maximum support (exclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.uniform.assign( 0.0, 1.0, out )\n \n > var bool = ( v === out )\n true","random.uniform.factory":"\nrandom.uniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.uniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.uniform.factory();\n > var out = fcn( [ 3, 3 ], 0.0, 1.0 )\n ","random.uniform.PRNG":"\nrandom.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.uniform.PRNG;","random.uniform.seed":"\nrandom.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.uniform.seed;","random.uniform.seedLength":"\nrandom.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.uniform.seedLength;","random.uniform.state":"\nrandom.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Get a copy of the current state:\n > var state = random.uniform.state\n \n\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Set the state:\n > random.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n ","random.uniform.stateLength":"\nrandom.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.uniform.stateLength;","random.uniform.byteLength":"\nrandom.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.uniform.byteLength;\n\n See Also\n --------\n random.discreteUniform, base.random.uniform, random.array.uniform, random.strided.uniform","random.weibull":"\nrandom.weibull( shape, k, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n lambda: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.weibull.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.weibull.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.weibull.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Weibull\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.weibull` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.weibull.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.weibull.PRNG;\n\n\nrandom.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.weibull.seed;\n\n\nrandom.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.weibull.seedLength;\n\n\nrandom.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.weibull.state\n \n\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.weibull.stateLength;\n\n\nrandom.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.array.weibull, random.strided.weibull\n","random.weibull.assign":"\nrandom.weibull.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.weibull.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.weibull.factory":"\nrandom.weibull.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Weibull\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.weibull` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.weibull.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.weibull.PRNG":"\nrandom.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.weibull.PRNG;","random.weibull.seed":"\nrandom.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.weibull.seed;","random.weibull.seedLength":"\nrandom.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.weibull.seedLength;","random.weibull.state":"\nrandom.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.weibull.state\n \n\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n ","random.weibull.stateLength":"\nrandom.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.weibull.stateLength;","random.weibull.byteLength":"\nrandom.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.array.weibull, random.strided.weibull","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path.\n - data: file contents as either a Buffer or string.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n The regular expression captures the following groups:\n\n 1. The days component.\n 2. The hours component.\n 3. The minutes component.\n 4. The seconds component.\n 5. The milliseconds component.\n\n Returns\n -------\n re: RegExp: Regular expression\n Regular expression to match a duration string.\n\n Examples\n --------\n > var RE = reDurationString();\n > var parts = RE.exec( '3d2ms' )\n [...]\n > parts = RE.exec( '4h3m20s' )\n [...]\n\n\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n \n replacement: string\n Replacement string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = replaceBefore( str, ' ', 'foo' )\n 'foo boop'\n > out = replaceBefore( str, 'o', 'foo' )\n 'foooop'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\[A\\-Z\\]\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - path: a resolved path.\n - next: a callback to be invoked after processing a resolved path.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer).\n - data: buffer data as an array of integers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n - re: real component (number).\n - im: imaginary component (number).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp).\n - pattern: regular expression pattern.\n - flags: regular expression flags.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n - data: typed array data as an array of numbers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n Trims `n` characters from the end of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrimN( ' abc ', 2 )\n ' abc'\n > var out = rtrimN( '!!!abc!!!', 2, '!' )\n '!!!abc!'\n\n See Also\n --------\n ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = sdot( x, y )\n [ -5.0 ]\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","sentencize":"\nsentencize( str )\n Splits a string into an array of sentences.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of sentences.\n\n Examples\n --------\n > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello Mrs. Maple, could you call me back?' ]\n\n > out = sentencize( 'Hello World! How are you?' )\n [ 'Hello World!', 'How are you?' ]\n\n See Also\n --------\n tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - complex128: 128-bit complex numbers.\n - complex64: 64-bit complex numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection value.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object contains at least `n`\n successful properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n > var bool = someInBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object's own properties satisfy a\n predicate for at least `n` properties; otherwise, the function\n returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n > var bool = someOwnBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year.\n - name: President name.\n - party: the President's political party.\n - text: speech text.\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group).\n - group: message group.\n - checksum: object containing checksum info.\n - text: message text (including headers).\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages).\n - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n - spam-1: spam e-mails (500 messages).\n - spam-2: spam e-mails collected at a later date (1396 messages).\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5).\n - value: checksum value.\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n Interchanges two single-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.356, ~0.786 ]\n > y0\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy( 2, x, 2, y, -1, clbk )\n [ ~1.317, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.567, ~0.962 ]\n > y0\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy( 2, x, 2, y, -1, clbk )\n [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~-0.588 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy( 2, x, 2, y, -1, clbk )\n [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n [ -Infinity, ~-0.255 ]\n > y0\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n [ ~-0.524, ~-1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 13.0, 14.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 17.0, 16.0 ]\n > z0\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n [ 0.0, ~3.142, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.094, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n [ ~3.142, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.047, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy( 2, x, 2, y, -1, clbk )\n [ ~1.571, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.253, ~-0.524 ]\n > y0\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy( 2, x, 2, y, -1, clbk )\n [ ~1.444, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-1.444, 0.0 ]\n > y0\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy( 2, x, 2, y, -1, clbk )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.896, ~-0.464 ]\n > y0\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy( 2, x, 2, y, -1, clbk )\n [ Infinity, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.255, ~-0.549 ]\n > y0\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By( 2, x, 2, y, -1, clbk )\n [ ~0.998, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n [ ~0.984, ~0.765 ]\n > y0\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By( 2, x, 2, y, -1, clbk )\n [ ~0.05, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n [ ~0.124, ~0.44 ]\n > y0\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By( 2, x, 2, y, -1, clbk )\n [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n [ ~-0.932, ~0.088 ]\n > y0\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By( 2, x, 2, y, -1, clbk )\n [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n [ ~-2.704, ~-0.781 ]\n > y0\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy( 2, x, 2, y, -1, clbk )\n [ 1.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n [ 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy( 2, x, 2, y, -1, clbk )\n [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.839, ~-1.0 ]\n > y0\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - bool: boolean values.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 12.0, 33.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 52.0, 28.0 ]\n > z0\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy( 2, x, 2, y, -1, clbk )\n [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.544, ~0.002 ]\n > y0\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n [ ~11.045, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~7.071, 1.0 ]\n > y0\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 4.0, 5.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 8.0, 7.0 ]\n > z0\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","trues":"\ntrues( shape[, options] )\n Returns an ndarray filled with `true` values and having a specified shape\n and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a boolean or \"generic\" data type. Default:\n 'bool'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = trues( [ 2, 2 ] )\n [ [ true, true ], [ true, true ] ]\n\n See Also\n --------\n array, ndarray, falses, truesLike\n","truesLike":"\ntruesLike( x[, options] )\n Returns an ndarray filled with `true` values and having the same shape and\n data type as a provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a boolean or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var opts = { 'dtype': 'generic' };\n > var x = ndempty( [ 2, 2 ], opts )\n \n > var y = truesLike( x )\n [ [ true, true ], [ true, true ] ]\n\n See Also\n --------\n array, ndarray, falsesLike, trues\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - result: function result.\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object.\n - result: either the result of `x` or the provided argument `y`.\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`.\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > var arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Float16Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n - BooleanArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type.\n - data: typed array data as a generic array.\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n \n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n \n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n ","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n ","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","Uint8ClampedVector":"\nUint8ClampedVector( [options] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8ClampedVector()\n \n\n\nUint8ClampedVector( length[, options] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray having a\n specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8ClampedVector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint8ClampedVector( obj[, options] )\n Creates a one-dimensional clamped unsigned 8-bit integer ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint8ClampedVector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint8ClampedVector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint8ClampedVector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","Uint8Vector":"\nUint8Vector( [options] )\n Returns a one-dimensional unsigned 8-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8Vector()\n \n\n\nUint8Vector( length[, options] )\n Returns a one-dimensional unsigned 8-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint8Vector( obj[, options] )\n Creates a one-dimensional unsigned 8-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint8Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint8Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint8Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","Uint16Vector":"\nUint16Vector( [options] )\n Returns a one-dimensional unsigned 16-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint16Vector()\n \n\n\nUint16Vector( length[, options] )\n Returns a one-dimensional unsigned 16-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint16Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint16Vector( obj[, options] )\n Creates a one-dimensional unsigned 16-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint16Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint16Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional unsigned 16-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint16Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint8Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","Uint32Vector":"\nUint32Vector( [options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint32Vector()\n \n\n\nUint32Vector( length[, options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint32Vector( obj[, options] )\n Creates a one-dimensional unsigned 32-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","Uint64":"\nUint64( value )\n 64-bit unsigned integer constructor.\n\n Parameters\n ----------\n value: number|bigint\n Integer value.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > x.toString()\n '5'\n\n\nUint64.name\n Constructor name.\n\n Examples\n --------\n > var str = Uint64.name\n 'Uint64'\n\n\nUint64.from( words )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.from( [ 1234, 5678 ] )\n \n\n\nUint64.of( high, low )\n Creates a new 64-bit unsigned integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.of( 1234, 5678 )\n \n\n\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Uint64.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.byteLength\n 8\n\n\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234\n\n\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n Number\n","Uint64.name":"\nUint64.name\n Constructor name.\n\n Examples\n --------\n > var str = Uint64.name\n 'Uint64'","Uint64.from":"\nUint64.from( words )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.from( [ 1234, 5678 ] )\n ","Uint64.of":"\nUint64.of( high, low )\n Creates a new 64-bit unsigned integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.of( 1234, 5678 )\n ","Uint64.BYTES_PER_ELEMENT":"\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Uint64.BYTES_PER_ELEMENT\n 8","Uint64.prototype.BYTES_PER_ELEMENT":"\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8","Uint64.prototype.byteLength":"\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.byteLength\n 8","Uint64.prototype.hi":"\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234","Uint64.prototype.lo":"\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n Number","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - +: enable\n - -: disable\n - =: enable specified and disable unspecified permissions\n\n For example,\n\n - u-w: disable user write permissions\n - u+w: enable user write permissions\n - u=w: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","vector":"\nvector( [dtype][, options] )\n Returns a one-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = vector()\n \n > var dt = ndarrayDataType( arr )\n 'float64'\n > arr = vector( 'float32' )\n \n > dt = ndarrayDataType( arr )\n 'float32'\n\n\nvector( length[, dtype][, options] )\n Returns a one-dimensional ndarray having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = vector( 5 )\n \n > var dt = ndarrayDataType( arr )\n 'float64'\n > var len = numel( arr )\n 5\n > arr = vector( 5, 'float32' )\n \n > dt = ndarrayDataType( arr )\n 'float32'\n > len = numel( arr )\n 5\n\n\nvector( obj[, dtype][, options] )\n Creates a one-dimensional ndarray from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 0.5, 0.5, 0.5 ];\n > var arr = vector( v, 'float32' )\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n > var len = numel( arr )\n 3\n\n\nvector( buffer[, byteOffset[, length]][, dtype][, options] )\n Returns a one-dimensional ndarray view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = vector( buf, 0, 4, 'float32' )\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n > var len = numel( arr )\n 4\n\n\nvector.factory( dtype[, options] )\n Returns a function for creating a one-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a one-dimensional ndarray.\n\n Examples\n --------\n > var f = vector.factory( 'float32' );\n > var arr = f()\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, matrix, ndarray\n","vector.factory":"\nvector.factory( dtype[, options] )\n Returns a function for creating a one-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a one-dimensional ndarray.\n\n Examples\n --------\n > var f = vector.factory( 'float32' );\n > var arr = f()\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, matrix, ndarray","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n WebAssembly memory constructor.\n\n Parameters\n ----------\n descriptor: Object\n Memory descriptor object.\n\n descriptor.initial: integer\n Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.maximum: integer (optional)\n Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.shared: boolean (optional)\n Boolean indicating whether the memory is shared. Default: false.\n\n Returns\n -------\n out: Memory\n WebAssembly memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n \n\n\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n \n\n\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n \n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n ","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n ","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} +{"abs":"\nabs( x[, options] )\n Computes the absolute value for each element in an ndarray.\n\n The function returns an ndarray having the same shape as the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Output array data type. Must be a real-valued or \"generic\" data type.\n\n options.order: string (optional)\n Output array order. Must be either row-major (C-style) or column-major\n (Fortran-style). By default, the order of the output array is the same\n as the input array.\n\n Returns\n -------\n y: ndarray\n Output array containing element-wise results.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var y = abs( x )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n\n\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true\n\n","abs.assign":"\nabs.assign( x, y )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array. Must have a numeric or \"generic\" data type.\n\n y: ndarray\n Output array.\n\n Returns\n -------\n y: ndarray\n Output array.\n\n Examples\n --------\n > var arr = [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ];\n > var x = array( arr );\n > var sh = ndarrayShape( x );\n > var y = ndzeros( sh );\n > var out = abs.assign( x, y )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n > var bool = ( out === y )\n true","acartesianPower":"\nacartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var out = acartesianSquare( [ 1, 2 ] )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n Generates an acronym for a given string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.stopwords: Array (optional)\n Array of custom stop words.\n\n Returns\n -------\n out: string\n Acronym for the given string.\n\n Examples\n --------\n > var out = acronym( 'the quick brown fox' )\n 'QBF'\n > out = acronym( 'Hard-boiled eggs' )\n 'HBE'\n","aempty":"\naempty( length[, dtype] )\n Creates an uninitialized array having a specified length.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aempty( 2 )\n \n > arr = aempty( 2, 'float32' )\n \n\n See Also\n --------\n aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n\n In browser environments, the function always returns zero-filled arrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled array.\n\n In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n is *not* initialized. Memory contents are unknown and may contain\n *sensitive* data.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var arr = aemptyLike( x )\n \n > arr = aemptyLike( x, 'float32' )\n \n\n See Also\n --------\n aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n\n The returned list contains 1468 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list is an earlier version of AFINN-111.\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_96()\n [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_111\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n\n The returned list contains 2477 English words (and phrases) rated for\n valence. Negative words have a negative valence [-5,0). Positive words have\n a positive valence (0,5]. Neutral words have a valence of 0.\n\n A few notes:\n\n - The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n - All words are lowercase.\n - Words may contain numbers; e.g., \"n00b\".\n - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n - Words may contain apostrophes; e.g., \"can't stand\".\n - Words may contain diaeresis; e.g., \"naïve\".\n - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n Returns\n -------\n out: Array\n List of English words and their valence.\n\n Examples\n --------\n > var list = AFINN_111()\n [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n References\n ----------\n - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n 718:93–98. CEUR Workshop Proceedings. .\n\n * If you use the list for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n value: any\n Fill value.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = afull( 2, 1.0 )\n [ 1.0, 1.0 ]\n > arr = afull( 2, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n Returns a filled array having the same length and data type as a provided\n input array.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = afullLike( x, 1.0 )\n [ 1.0, 1.0 ]\n > y = afullLike( x, 1.0, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n Returns the package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Package name.\n\n Examples\n --------\n > var v = alias2pkg( 'base.sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n Returns aliases related to a specified alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: Array|null\n Related aliases.\n\n Examples\n --------\n > var v = alias2related( 'base.sin' )\n [...]\n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n Returns the standalone package name associated with a provided alias.\n\n Parameters\n ----------\n alias: string\n Alias.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = alias2standalone( 'base.sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n Returns a list of standard library aliases.\n\n Parameters\n ----------\n namespace: string (optional)\n Namespace filter.\n\n Returns\n -------\n out: Array\n List of aliases.\n\n Examples\n --------\n > var o = aliases()\n [...]\n > o = aliases( '@stdlib/math/base/special' )\n [...]\n\n See Also\n --------\n alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n Allocates a buffer having a specified number of bytes.\n\n The underlying memory of returned buffers is not initialized. Memory\n contents are unknown and may contain sensitive data.\n\n When the size is less than half a buffer pool size, memory is allocated from\n the buffer pool for faster allocation of Buffer instances.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = allocUnsafe( 100 )\n \n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is truthy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of falsy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of falsy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is falsy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of falsy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of falsy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of falsy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n Returns a new array by applying a mask to a provided input array.\n\n If a mask array element is falsy, the corresponding element in `x` is\n included in the output array; otherwise, the corresponding element in `x` is\n \"masked\" and thus excluded from the output array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n mask: Array|TypedArray|Object\n Mask array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n [ 1, 3 ]\n\n See Also\n --------\n amskfilter\n","anans":"\nanans( length[, dtype] )\n Returns an array filled with NaNs and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754)\n - float32: single-precision floating-point numbers (IEEE 754)\n - complex128: double-precision complex floating-point numbers\n - complex64: single-precision complex floating-point numbers\n - generic: generic JavaScript values\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = anans( 2 )\n [ NaN, NaN ]\n > arr = anans( 2, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = anansLike( x )\n [ NaN, NaN ]\n > y = anansLike( x, 'float32' )\n [ NaN, NaN ]\n\n See Also\n --------\n afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n Performs a one-way analysis of variance.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n factor: Array\n Array of treatments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.means: Object\n Group means alongside sample sizes and standard errors.\n\n out.treatment: Object\n Treatment results.\n\n out.treatment.df: number\n Treatment degrees of freedom.\n\n out.treatment.ss: number\n Treatment sum of squares.\n\n out.treatment.ms: number\n Treatment mean sum of squares.\n\n out.error: Object\n Error results.\n\n out.error.df: number\n Error degrees of freedom.\n\n out.error.ss: number\n Error sum of squares.\n\n out.error.ms: number\n Error mean sum of squares.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n > var f = [\n ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ... ];\n > var out = anova1( x, f )\n {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n\n Anscombe's quartet is a set of 4 datasets which all have nearly identical\n simple statistical properties but vary considerably when graphed. Anscombe\n created the datasets to demonstrate why graphical data exploration should\n precede statistical data analysis and to show the effect of outliers on\n statistical properties.\n\n Returns\n -------\n out: Array\n Anscombe's quartet.\n\n Examples\n --------\n > var d = ANSCOMBES_QUARTET()\n [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n References\n ----------\n - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n Ltd.]: 17–21. .\n\n","any":"\nany( collection )\n Tests whether at least one element in a collection is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an element is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 1 ];\n > var bool = any( arr )\n true\n\n See Also\n --------\n anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4, -1 ];\n > var bool = anyBy( arr, negative )\n true\n\n See Also\n --------\n anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > anyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any element; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, 2, 3, 4 ];\n > var bool = anyByRight( arr, negative )\n true\n\n See Also\n --------\n anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > anyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = anyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: the value of the current property being processed in the object\n - key: the key of the current property being processed in the object\n - object: the input object\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate. It must be non-null.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns `true` for\n any value; otherwise, it returns `false`.\n\n Examples\n --------\n > function isNegative(value) { return value < 0 }\n > var obj = { a: 1, b: -2, c: 3, d: 4 }\n > var result = anyInBy(obj, isNegative)\n true\n\n See Also\n --------\n anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return\n value.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for one own property; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n > var bool = anyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n Returns an array filled with ones and having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aones( 2 )\n [ 1.0, 1.0 ]\n > arr = aones( 2, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = aonesLike( x )\n [ 1.0, 1.0 ]\n > y = aonesLike( x, 'float32' )\n [ 1.0, 1.0 ]\n\n See Also\n --------\n afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneTo( 2 )\n [ 1.0, 2.0 ]\n > arr = aoneTo( 2, 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = aoneToLike( [ 0, 0 ] )\n [ 1, 2 ]\n > arr = aoneToLike( [ 0, 0 ], 'float32' )\n [ 1.0, 2.0 ]\n\n See Also\n --------\n afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n Apéry's constant.\n\n Examples\n --------\n > APERY\n 1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n\n In broadcasting modes, the function supports broadcasting a values array\n containing a single element against the number of truthy values in the mask\n array.\n\n In repeat mode, the function supports recycling elements in a values array\n to satisfy the number of truthy values in the mask array.\n\n The function mutates the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n mask: ArrayLikeObject\n Mask array. If a mask array element is truthy, the corresponding element\n in `x` is *replaced*; otherwise, the corresponding element in `x` is\n \"masked\" and thus left unchanged.\n\n values: ArrayLikeObject\n Values to set.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n String specifying behavior when the number of values to set does not\n equal the number of truthy mask values. The function supports the\n following modes:\n\n - 'strict': specifies that the function must raise an exception when the\n number of values does not *exactly* equal the number of truthy mask\n values.\n - 'non_strict': specifies that the function must raise an exception when\n the function is provided insufficient values to satisfy the mask array.\n - 'strict_broadcast': specifies that the function must broadcast a\n single-element values array and otherwise raise an exception when the\n number of values does not **exactly** equal the number of truthy mask\n values.\n - 'broadcast': specifies that the function must broadcast a single-\n element values array and otherwise raise an exception when the function\n is provided insufficient values to satisfy the mask array.\n - 'repeat': specifies that the function must reuse provided values when\n replacing elements in `x` in order to satisfy the mask array.\n\n Default: 'repeat'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n Adds the elements of one collection to the end of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = append( arr, [ 6.0, 7.0 ] )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = append( arr, [ 3.0, 4.0 ] )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = append( arr, [ 1.0, 2.0 ] )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n prepend, push\n","aput":"\naput( x, indices, values[, options] )\n Replaces specified elements of an array with provided values.\n\n The function supports broadcasting a `values` array containing a single\n element against an `indices` array containing one or more elements.\n\n The function mutates the input array.\n\n Because each index is only validated at the time of replacing a particular\n element, mutation may occur even when one or more indices are out-of-bounds,\n including when the index mode indicates to raise an exception.\n\n If `indices` is an empty array, the function returns the input array\n unchanged.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n values: ArrayLikeObject\n Values to set. When `indices` contains one or more elements, `values`\n must be broadcast compatible with `indices` (i.e., must have either one\n element or the same number of elements as `indices`).\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: ArrayLikeObject\n Input array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n [ 1, 20, 3, 40 ]\n > var bool = ( out === x )\n true\n\n See Also\n --------\n amskput, aplace, atake\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n\n Current possible values:\n\n - arm\n - arm64\n - ia32\n - mips\n - mipsel\n - ppc\n - ppc64\n - s390\n - s390x\n - x32\n - x64\n\n Examples\n --------\n > ARCH\n \n\n See Also\n --------\n PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n Returns a function which always returns a specified argument.\n\n The input argument corresponds to the zero-based index of the argument to\n return.\n\n Parameters\n ----------\n idx: integer\n Argument index to return (zero-based).\n\n Returns\n -------\n out: Function\n Argument function.\n\n Examples\n --------\n > var argn = argumentFunction( 1 );\n > var v = argn( 3.14, -3.14, 0.0 )\n -3.14\n > v = argn( -1.0, -0.0, 1.0 )\n -0.0\n > v = argn( 'beep', 'boop', 'bop' )\n 'boop'\n > v = argn( 'beep' )\n undefined\n\n See Also\n --------\n constantFunction, identity\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n\n The first element is the absolute pathname of the executable that started\n the calling process.\n\n The second element is the path of the executed file.\n\n Any additional elements are additional command-line arguments.\n\n In browser environments, the array is empty.\n\n Examples\n --------\n > var execPath = ARGV[ 0 ]\n e.g., /usr/local/bin/node\n\n See Also\n --------\n ENV\n","array":"\narray( [buffer,] [options] )\n Returns a multidimensional array.\n\n Parameters\n ----------\n buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source.\n\n options: Object (optional)\n Options.\n\n options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n Data source. If provided along with a `buffer` argument, the argument\n takes precedence.\n\n options.dtype: string|DataType (optional)\n Underlying storage data type. If not specified and a data source is\n provided, the data type is inferred from the provided data source. If an\n input data source is not of the same type, this option specifies the\n data type to which to cast the input data. For non-ndarray generic array\n data sources, the function casts generic array data elements to the\n default data type. In order to prevent this cast, the `dtype` option\n must be explicitly set to `'generic'`. Any time a cast is required, the\n `copy` option is set to `true`, as memory must be copied from the data\n source to an output data buffer. Default: 'float64'.\n\n options.order: string (optional)\n Specifies the memory layout of the data source as either row-major (C-\n style) or column-major (Fortran-style). The option may be one of the\n following values:\n\n - 'row-major': the order of the returned array is row-major.\n - 'column-major': the order of the returned array is column-major.\n - 'any': if a data source is column-major and not row-major, the order\n of the returned array is column-major; otherwise, the order of the\n returned array is row-major.\n - 'same': the order of the returned array matches the order of an input\n data source.\n\n Note that specifying an order which differs from the order of a\n provided data source does *not* entail a conversion from one memory\n layout to another. In short, this option is descriptive, not\n prescriptive. Default: 'row-major'.\n\n options.shape: Array (optional)\n Array shape (dimensions). If a shape is not specified, the function\n attempts to infer a shape based on a provided data source. For example,\n if provided a nested array, the function resolves nested array\n dimensions. If provided a multidimensional array data source, the\n function uses the array's associated shape. For most use cases, such\n inference suffices. For the remaining use cases, specifying a shape is\n necessary. For example, provide a shape to create a multidimensional\n array view over a linear data buffer, ignoring any existing shape meta\n data associated with a provided data source.\n\n options.flatten: boolean (optional)\n Boolean indicating whether to automatically flatten generic array data\n sources. If an array shape is not specified, the shape is inferred from\n the dimensions of nested arrays prior to flattening. If a use case\n requires partial flattening, partially flatten prior to invoking this\n function and set the option value to `false` to prevent further\n flattening during invocation. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to (shallow) copy source data to a new data\n buffer. The function does *not* perform a deep copy. To prevent\n undesired shared changes in state for generic arrays containing objects,\n perform a deep copy prior to invoking this function. Default: false.\n\n options.ndmin: integer (optional)\n Specifies the minimum number of dimensions. If an array shape has fewer\n dimensions than required by `ndmin`, the function prepends singleton\n dimensions to the array shape in order to satisfy the dimensions\n requirement. Default: 0.\n\n options.casting: string (optional)\n Specifies the casting rule used to determine acceptable casts. The\n option may be one of the following values:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers\n and floats).\n\n Default: 'safe'.\n\n options.codegen: boolean (optional)\n Boolean indicating whether to use code generation. Code generation can\n boost performance, but may be problematic in browser contexts enforcing\n a strict content security policy (CSP). Default: true.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. The\n option may be one of the following values:\n\n - 'throw': an ndarray instance throws an error when an index exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative indices and\n throws an error when an index exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around indices exceeding array\n dimensions using modulo arithmetic.\n - 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index.\n\n Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to\n\n - 'throw': an ndarray instance throws an error when a subscript exceeds\n array dimensions.\n - 'normalize': an ndarray instance normalizes negative subscripts and\n throws an error when a subscript exceeds array dimensions.\n - 'wrap': an ndarray instance wraps around subscripts exceeding array\n dimensions using modulo arithmetic.\n - 'clamp': an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index.\n\n If the number of modes is fewer than the number of dimensions, the\n function recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Multidimensional array.\n\n Examples\n --------\n // Create a 2x2 matrix:\n > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n See Also\n --------\n ndarray\n","array2buffer":"\narray2buffer( arr )\n Allocates a buffer using an octet array.\n\n Parameters\n ----------\n arr: Array\n Array (or array-like object) of octets from which to copy.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n Converts an array to an object supporting fancy indexing.\n\n An array supporting fancy indexing is an array which supports slicing via\n indexing expressions for both retrieval and assignment.\n\n A fancy array shares the *same* data as the provided input array. Hence, any\n mutations to the returned array will affect the underlying input array and\n vice versa.\n\n For operations returning a new array (e.g., when slicing or invoking an\n instance method), a fancy array returns a new fancy array having the same\n configuration as specified by provided options.\n\n A fancy array supports indexing using positive and negative integers (both\n numeric literals and strings), Slice instances, subsequence expressions,\n mask arrays, boolean arrays, and integer arrays.\n\n A fancy array supports all properties and methods of the input array, and,\n thus, a fancy array can be consumed by any API which supports array-like\n objects.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on array views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use (e.g., in the\n REPL) and scripting. For performance critical applications, prefer\n equivalent functional APIs supporting array-like objects.\n\n Fancy arrays support broadcasting in which assigned scalars and single-\n element arrays are repeated (without additional memory allocation) to match\n the length of a target array instance.\n\n Fancy array broadcasting follows the same rules as for ndarrays.\n\n Consequently, when assigning arrays to slices, the array on the right-hand-\n side must be broadcast-compatible with number of elements in the slice.\n\n Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point arrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy arrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number array (e.g.,\n Complex128Array or Complex64Array), a fancy array will cast the real-valued\n scalar to a complex number argument having an imaginary component equal to\n zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array supporting fancy indexing.\n\n Examples\n --------\n > var y = array2fancy( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving array index objects. Must have a 'get' method which\n accepts a single argument: a string identifier associated with an array\n index. If an array index associated with a provided identifier exists,\n the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index array.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - dtype: the data type of the underlying array.\n\n If an array index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ArrayIndex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an array to an object supporting fancy indexing.\n\n Examples\n --------\n > var f = array2fancy.factory();\n > var y = f( [ 1, 2, 3, 4 ] );\n > y[ '1::2' ]\n [ 2, 4 ]\n > y[ '::-1' ]\n [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n Wraps a provided array as an array index object.\n\n For documentation and usage, see `ArrayIndex`.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n See Also\n --------\n aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n Returns an array buffer having a specified number of bytes.\n\n Buffer contents are initialized to 0.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: ArrayBuffer\n An array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n\n\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1\n\n\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true\n\n\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > ArrayBuffer.length\n 1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n Returns a boolean indicating if provided an array buffer view.\n\n Parameters\n ----------\n arr: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input argument is a buffer view.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > ArrayBuffer.isView( arr )\n true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > buf.byteLength\n 5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of an array buffer to a new array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: ArrayBuffer\n A new array buffer whose contents have been copied from the calling\n array buffer.\n\n Examples\n --------\n > var b1 = new ArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n Allocates a buffer from an ArrayBuffer.\n\n The behavior of this function varies across Node.js versions due to changes\n in the underlying Node.js APIs:\n\n - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n returns a view of an ArrayBuffer without copying the underlying memory.\n - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n Buffer which is not an ArrayBuffer view.\n - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n the underlying memory.\n\n Parameters\n ----------\n buf: ArrayBuffer\n Input array buffer.\n\n byteOffset: integer (optional)\n Index offset specifying the location of the first byte.\n\n length: integer (optional)\n Number of bytes to expose from the underlying ArrayBuffer.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var ab = new ArrayBuffer( 10 )\n \n > var buf = arraybuffer2buffer( ab )\n \n > var len = buf.length\n 10\n > buf = arraybuffer2buffer( ab, 2, 6 )\n \n > len = buf.length\n 6\n\n See Also\n --------\n Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n Returns an array constructor.\n\n The function returns constructors for the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = arrayCtors( 'float64' )\n \n > ctor = arrayCtors( 'float' )\n null\n\n See Also\n --------\n typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n Returns the data type of an array.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n array: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var arr = new Float64Array( 10 );\n > var dt = arrayDataType( arr )\n 'float64'\n > dt = arrayDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n Returns a list of array data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of array data types.\n\n Examples\n --------\n > var out = arrayDataTypes()\n [...]\n > out = arrayDataTypes( 'floating_point' )\n [...]\n > out = arrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n See Also\n --------\n typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n Wraps a provided array as an array index object.\n\n Array index instances have no explicit functionality; however, they are used\n by \"fancy\" arrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying array are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped array, as the consumer will attempt to resolve an instance\n in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ArrayIndex\n ArrayIndex instance.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n \n\n\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}\n\n\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'\n\n\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n \n\n\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true\n\n\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n \n\n\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n \n\n\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.free( idx.id )\n ","ArrayIndex.get":"\nArrayIndex.get( id )\n Returns the array associated with the instance having a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing array data.\n\n out.data: Array|TypedArray|Object\n The underlying array associated with the provided identifier.\n\n out.type: string\n The type of array index.\n\n out.dtype: string\n The data type of the underlying array.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > ArrayIndex.get( idx.id )\n {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Array data.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.data\n [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.dtype\n 'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.id\n ","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an array index is actively cached.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.isCached\n true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n\n Returns\n -------\n out: string\n Array index type.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.type\n ","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toString()\n ","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n > idx.toJSON()\n { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n See Also\n --------\n array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n Array data type.\n\n Examples\n --------\n > var dt = arrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = arrayMinDataType( 3 )\n 'uint8'\n > dt = arrayMinDataType( -3 )\n 'int8'\n > dt = arrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type value.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be cast.\n\n Examples\n --------\n > var out = arrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n Returns the next larger array data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: string (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = arrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n Array data type.\n\n dtype2: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = arrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = arraySafeCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n\n If not provided an array data type, the function returns a casting table.\n\n If provided an unrecognized array data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n Array data type.\n\n Returns\n -------\n out: Object|Array|null\n Array data types to which a data type can be safely cast or cast within\n the same \"kind\".\n\n Examples\n --------\n > var out = arraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n Determines array dimensions.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Array shape.\n\n Examples\n --------\n > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ 2, 3 ]\n\n See Also\n --------\n ndarray\n","arrayStream":"\narrayStream( src[, options] )\n Creates a readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = arrayStream( [ 1, 2, 3 ] );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: src.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n Returns a shallow copy of a portion of an array.\n\n If provided an array-like object having a `slice` method, the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.slice( start, end )\n\n If provided an array-like object without a `slice` method, the function\n copies input array elements to a new generic array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n start: integer (optional)\n Starting index (inclusive). Default: 0.\n\n end: integer (optional)\n Ending index (exclusive). Default: x.length.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = aslice( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1 )\n [ 2, 3, 4 ]\n > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n [ 2, 3 ]\n\n See Also\n --------\n atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n\n This symbol specifies the default async iterator for an object.\n\n The symbol is only supported in ES2018+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = AsyncIteratorSymbol\n e.g., \n\n See Also\n --------\n Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n Takes elements from an array.\n\n If `indices` is an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n indices: ArrayLikeObject\n List of element indices.\n\n options: Object (optional)\n Function options.\n\n options.mode: string (optional)\n Specifies how to handle an index outside the interval [0, max], where\n `max` is the maximum possible array index. If equal to 'throw', the\n function throws an error. If equal to 'normalize', the function throws\n an error if provided an out-of-bounds normalized index. If equal to\n 'wrap', the function wraps around an index using modulo arithmetic. If\n equal to 'clamp', the function sets an index to either 0 (minimum index)\n or the maximum index. Default: 'normalize'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1, 2, 3, 4 ];\n > var y = atake( x, [ 1, 3 ] )\n [ 2, 4 ]\n\n See Also\n --------\n aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n Returns a zero-filled array having a specified length.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeros( 2 )\n [ 0.0, 0.0 ]\n > arr = azeros( 2, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var x = new Float64Array( 2 );\n > var y = azerosLike( x )\n [ 0.0, 0.0 ]\n > y = azerosLike( x, 'float32' )\n [ 0.0, 0.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n The default array data type is `float64`.\n\n If `n` is equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: integer\n Number of elements.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroTo( 2 )\n [ 0.0, 1.0 ]\n > arr = azeroTo( 2, 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - float16: half-precision floating-point numbers (IEEE 754).\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - generic: generic JavaScript values.\n\n Parameters\n ----------\n x: TypedArray|Array\n Input array.\n\n dtype: string (optional)\n Data type. If not provided, the output array data type is inferred from\n the input array.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = azeroToLike( [ 0, 0 ] )\n [ 0, 1 ]\n > arr = azeroToLike( [ 0, 0 ], 'float32' )\n [ 0.0, 1.0 ]\n\n See Also\n --------\n aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n Computes Bartlett’s test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = bartlettTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = bartlettTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n Computes the absolute value of a double-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.abs( -1.0 )\n 1.0\n > y = base.abs( 2.0 )\n 2.0\n > y = base.abs( 0.0 )\n 0.0\n > y = base.abs( -0.0 )\n 0.0\n > y = base.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2( -1.0 )\n 1.0\n > y = base.abs2( 2.0 )\n 4.0\n > y = base.abs2( 0.0 )\n 0.0\n > y = base.abs2( -0.0 )\n 0.0\n > y = base.abs2( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.abs2f( -1.0 )\n 1.0\n > y = base.abs2f( 2.0 )\n 4.0\n > y = base.abs2f( 0.0 )\n 0.0\n > y = base.abs2f( -0.0 )\n 0.0\n > y = base.abs2f( NaN )\n NaN\n\n See Also\n --------\n base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n Computes the absolute difference.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Absolute difference.\n\n Examples\n --------\n > var d = base.absdiff( 2.0, 5.0 )\n 3.0\n > d = base.absdiff( -1.0, 3.14 )\n ~4.14\n > d = base.absdiff( 10.1, -2.05 )\n ~12.15\n > d = base.absdiff( -0.0, 0.0 )\n +0.0\n > d = base.absdiff( NaN, 5.0 )\n NaN\n > d = base.absdiff( PINF, NINF )\n Infinity\n > d = base.absdiff( PINF, PINF )\n NaN\n\n See Also\n --------\n base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n Computes the absolute value of a single-precision floating-point number `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.absf( -1.0 )\n 1.0\n > y = base.absf( 2.0 )\n 2.0\n > y = base.absf( 0.0 )\n 0.0\n > y = base.absf( -0.0 )\n 0.0\n > y = base.absf( NaN )\n NaN\n\n See Also\n --------\n base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n Returns the Cartesian power.\n\n If provided an empty array, the function returns an empty array.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n n: integer\n Power.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianPower( x, 2 )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n Returns the Cartesian product.\n\n If provided one or more empty arrays, the function returns an empty array.\n\n Parameters\n ----------\n x1: ArrayLikeObject\n First input array.\n\n x2: ArrayLikeObject\n Second input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x1 = [ 1, 2 ];\n > var x2 = [ 3, 4 ];\n > var out = base.acartesianProduct( x1, x2 )\n [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n See Also\n --------\n acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n Returns the Cartesian square.\n\n If provided an empty array, the function returns an empty array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: Array\n Cartesian product.\n\n Examples\n --------\n > var x = [ 1, 2 ];\n > var out = base.acartesianSquare( x )\n [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n See Also\n --------\n acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n Compute the arccosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acos( 1.0 )\n 0.0\n > y = base.acos( 0.707 )\n ~0.7855\n > y = base.acos( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosd( 0.0 )\n 90.0\n > y = base.acosd( PI/6.0 )\n ~58.43\n > y = base.acosd( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosdf, base.acosh, base.asind, base.atand\n","base.acosdf":"\nbase.acosdf( x )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in degrees).\n\n Examples\n --------\n > var y = base.acosdf( 0.0 )\n 90.0\n > y = base.acosdf( FLOAT32_PI / 6.0 )\n ~58.43\n > y = base.acosdf( NaN )\n NaN\n\n See Also\n --------\n base.acosd, base.acosf, base.asindf\n","base.acosf":"\nbase.acosf( x )\n Computes the arccosine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosine (in radians).\n\n Examples\n --------\n > var y = base.acosf( 1.0 )\n 0.0\n > y = base.acosf( 0.707 )\n ~0.7855\n > y = base.acosf( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n\n If `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosine.\n\n Examples\n --------\n > var y = base.acosh( 1.0 )\n 0.0\n > y = base.acosh( 2.0 )\n ~1.317\n > y = base.acosh( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n Computes the inverse cotangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acot( 2.0 )\n ~0.4636\n > y = base.acot( 0.0 )\n ~1.5708\n > y = base.acot( 0.5 )\n ~1.1071\n > y = base.acot( 1.0 )\n ~0.7854\n > y = base.acot( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotd( 0.0 )\n 90.0\n > y = base.acotd( PI/6.0 )\n ~62.36\n > y = base.acotd( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acotdf, base.acoth, base.atand, base.cotd\n","base.acotdf":"\nbase.acotdf( x )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccotangent (in degrees).\n\n Examples\n --------\n > var y = base.acotdf( 0.0 )\n 90.0\n > y = base.acotdf( FLOAT32_PI/6.0 )\n ~62.36\n > y = base.acotdf( NaN )\n NaN\n\n See Also\n --------\n base.acotd, base.acotf\n","base.acotf":"\nbase.acotf( x )\n Computes the inverse cotangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse cotangent (in radians).\n\n Examples\n --------\n > var y = base.acotf( 2.0 )\n ~0.4636\n > y = base.acotf( 0.0 )\n ~1.5708\n > y = base.acotf( 0.5 )\n ~1.1071\n > y = base.acotf( 1.0 )\n ~0.7854\n > y = base.acotf( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n\n The domain of the inverse hyperbolic cotangent is the union of the intervals\n (-inf,-1] and [1,inf).\n\n If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.acoth( 2.0 )\n ~0.5493\n > y = base.acoth( 0.0 )\n NaN\n > y = base.acoth( 0.5 )\n NaN\n > y = base.acoth( 1.0 )\n Infinity\n > y = base.acoth( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n Computes the inverse coversed cosine.\n\n The inverse coversed cosine is defined as `asin(x-1)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed cosine.\n\n Examples\n --------\n > var y = base.acovercos( 1.5 )\n ~0.5236\n > y = base.acovercos( -0.0 )\n ~-1.5708\n\n See Also\n --------\n base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n Computes the inverse coversed sine.\n\n The inverse coversed sine is defined as `asin(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse coversed sine.\n\n Examples\n --------\n > var y = base.acoversin( 1.5 )\n ~-0.5236\n > y = base.acoversin( 0.0 )\n ~1.5708\n\n See Also\n --------\n base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n Computes the arccosecant of a number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acsc( 1.0 )\n ~1.57\n > y = base.acsc( PI )\n ~0.32\n > y = base.acsc( -PI )\n ~-0.32\n > y = base.acsc( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscd( 0.0 )\n NaN\n > y = base.acscd( PI/6.0 )\n NaN\n > y = base.acscd( 1 )\n 90.0\n > y = base.acscd( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in degrees).\n\n Examples\n --------\n > var y = base.acscdf( 0.0 )\n NaN\n > y = base.acscdf( 3.1415927410125732 / 6.0 )\n NaN\n > y = base.acscdf( 1.0 )\n 90.0\n > y = base.acscdf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n Computes the arccosecant of a single-precision floating-point number.\n\n If `|x| < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arccosecant (in radians).\n\n Examples\n --------\n > var y = base.acscf( 1.0 )\n ~1.57\n > y = base.acscf( 3.141592653589793 )\n ~0.32\n > y = base.acscf( -3.141592653589793 )\n ~-0.32\n > y = base.acscf( NaN )\n NaN\n\n See Also\n --------\n base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n Computes the hyperbolic arccosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arccosecant.\n\n Examples\n --------\n > var y = base.acsch( 0.0 )\n Infinity\n > y = base.acsch( -1.0 )\n ~-0.881\n > y = base.acsch( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.add( -1.0, 5.0 )\n 4.0\n > v = base.add( 2.0, 5.0 )\n 7.0\n > v = base.add( 0.0, 5.0 )\n 5.0\n > v = base.add( -0.0, 0.0 )\n 0.0\n > v = base.add( NaN, NaN )\n NaN\n\n See Also\n --------\n base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n Computes the sum of three double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add3( -1.0, 5.0, 2.0 )\n 6.0\n > v = base.add3( 2.0, 5.0, 2.0 )\n 9.0\n > v = base.add3( 0.0, 5.0, 2.0 )\n 7.0\n > v = base.add3( -0.0, 0.0, -0.0 )\n 0.0\n > v = base.add3( NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n Computes the sum of four double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n 3.0\n > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n 6.0\n > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n 4.0\n > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n 0.0\n > v = base.add4( NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n Computes the sum of five double-precision floating-point numbers.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n z: number\n Third input value.\n\n w: number\n Fourth input value.\n\n u: number\n Fifth input value.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n 7.0\n > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n 10.0\n > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n 8.0\n > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n 0.0\n > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n NaN\n\n See Also\n --------\n base.add\n","base.addf":"\nbase.addf( x, y )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Sum.\n\n Examples\n --------\n > var v = base.addf( -1.0, 5.0 )\n 4.0\n > v = base.addf( 2.0, 5.0 )\n 7.0\n > v = base.addf( 0.0, 5.0 )\n 5.0\n > v = base.addf( -0.0, 0.0 )\n 0.0\n > v = base.addf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n Returns a filled \"generic\" array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled( 0.0, 3 )\n [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n Returns a filled two-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n Returns a filled three-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n Returns a filled four-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n Returns a filled five-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n Returns a filled \"generic\" array according to a provided callback function.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledBy( 3, clbk )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n Returns a filled n-dimensional nested array.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afillednd( 0.0, [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n\n The callback function is provided one argument:\n\n - indices: current array element indices.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var out = base.afilledndBy( [ 1, 3 ], clbk )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the input array.\n\n If provided an array-like object having a `filter` method , the function\n defers execution to that method and assumes that the method has the\n following signature:\n\n x.filter( predicate, thisArg )\n\n If provided an array-like object without a `filter` method, the function\n performs a linear scan and always returns a generic array.\n\n Parameters\n ----------\n x: Array|TypedArray|Object\n Input array.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > function f( v ) { return ( v > 0 ); };\n > var x = [ 1, -2, -3, 4 ];\n > var out = base.afilter( x, f )\n [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n Returns the first element of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n Returns\n -------\n out: any\n First element.\n\n Examples\n --------\n > var out = base.afirst( [ 1, 2, 3 ] )\n 1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n Flattens an n-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n Flattens a two-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2d( x, [ 2, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten2d( x, [ 2, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n Flattens a three-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n Flattens a four-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n Flattens a five-dimensional nested array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n [ 1, 2, 3, 4 ]\n > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colexicographic: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n [ 1, 2, 3, 4 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n > out\n [ 1, 3, 2, 4 ]\n\n See Also\n --------\n base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n [ 2, 4, 6, 8 ]\n > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n\n The function assumes that all nested arrays have the same length (i.e., the\n input array is *not* a ragged array).\n\n The callback function is provided the following arguments:\n\n - value: nested array element.\n - indices: element indices (in lexicographic order).\n - arr: the input array.\n\n Parameters\n ----------\n x: Array\n Input array.\n\n shape: Array\n Array shape.\n\n colex: boolean\n Specifies whether to flatten array values in colexicographic order.\n\n out: Collection\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > function fcn( v ) { return v * 2; };\n > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n > var out = [ 0, 0, 0, 0 ];\n > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n [ 2, 4, 6, 8 ]\n > var bool = ( v === out )\n true\n > out = [ 0, 0, 0, 0 ];\n > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n > out\n [ 2, 6, 4, 8 ]\n\n See Also\n --------\n base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 2, 1 ], [ 4, 3 ] ]\n\n See Also\n --------\n base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n See Also\n --------\n base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ [ 3, 4 ], [ 1, 2 ] ]\n\n See Also\n --------\n base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n\n The function does *not* perform a deep copy of nested array elements.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Input nested array.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n See Also\n --------\n base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n Computes the inverse half-value versed cosine.\n\n The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed cosine.\n\n Examples\n --------\n > var y = base.ahavercos( 0.5 )\n ~1.5708\n > y = base.ahavercos( 0.0 )\n ~3.1416\n\n See Also\n --------\n base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n Computes the inverse half-value versed sine.\n\n The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse half-value versed sine.\n\n Examples\n --------\n > var y = base.ahaversin( 0.5 )\n ~1.5708\n > y = base.ahaversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n Converts a string to alternate case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Alternate-cased string.\n\n Examples\n --------\n > var out = base.altcase( 'Hello World!' )\n 'hElLo wOrLd!'\n > out = base.altcase( 'I am a tiny little teapot' )\n 'i aM A TiNy lItTlE TeApOt'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n Returns a \"generic\" array filled with ones.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones( 3 )\n [ 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n Returns a two-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones2d( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n Returns a three-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones3d( [ 1, 1, 3 ] )\n [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n See Also\n --------\n base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n Returns a four-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n See Also\n --------\n base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n Returns a five-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n Returns an n-dimensional nested array filled with ones.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.aonesnd( [ 1, 3 ] )\n [ [ 1.0, 1.0, 1.0 ] ]\n\n See Also\n --------\n base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.aoneTo( 6 )\n [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.aoneTo.assign( out, -1, out.length-1 );\n > out\n [ 6, 5, 4, 3, 2, 1 ]\n\n See Also\n --------\n base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n Parameters\n ----------\n args: Array\n Constructor arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var args = [ null, null, null ];\n > var s = new base.args2multislice( args );\n > s.data\n [ null, null, null ]\n > args = [ 10, new Slice( 0, 10, 1 ), null ];\n > s = new base.args2multislice( args );\n > s.data\n [ 10, , null ]\n\n","base.asec":"\nbase.asec( x )\n Computes the inverse (arc) secant of a number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asec( 1.0 )\n 0.0\n > y = base.asec( 2.0 )\n ~1.0472\n > y = base.asec( NaN )\n NaN\n\n See Also\n --------\n base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecd( 0.0 )\n NaN\n > y = base.asecd( 2 )\n ~60.0\n > y = base.asecd( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n\n If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsecant (in degrees).\n\n Examples\n --------\n > var y = base.asecdf( 2.0 )\n ~60.0\n > y = base.asecdf( 0.0 )\n NaN\n > y = base.asecdf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosdf\n","base.asecf":"\nbase.asecf( x )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n\n If `x > -1` and `x < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse (arc) secant.\n\n Examples\n --------\n > var y = base.asecf( 1.0 )\n 0.0\n > y = base.asecf( 2.0 )\n ~1.0472\n > y = base.asecf( NaN )\n NaN\n\n See Also\n --------\n base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n Computes the hyperbolic arcsecant of a number.\n\n If `x < 0` or `x > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsecant.\n\n Examples\n --------\n > var y = base.asech( 1.0 )\n 0.0\n > y = base.asech( 0.5 )\n ~1.317\n > y = base.asech( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asec, base.acoth\n","base.asin":"\nbase.asin( x )\n Computes the arcsine of a double-precision floating-point number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asin( 0.0 )\n 0.0\n > y = base.asin( -PI/6.0 )\n ~-0.551\n > y = base.asin( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asind( 0.0 )\n 0.0\n > y = base.asind( PI / 6.0 )\n ~31.57\n > y = base.asind( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in degrees).\n\n Examples\n --------\n > var y = base.asindf( 0.0 )\n 0.0\n > y = base.asindf( 3.1415927410125732 / 6.0 )\n ~31.57\n > y = base.asindf( NaN )\n NaN\n\n See Also\n --------\n base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n Computes the arcsine of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arcsine (in radians).\n\n Examples\n --------\n > var y = base.asinf( 0.0 )\n 0.0\n > y = base.asinf( -3.14/6.0 )\n ~-0.551\n > y = base.asinf( NaN )\n NaN\n\n See Also\n --------\n base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arcsine.\n\n Examples\n --------\n > var y = base.asinh( 0.0 )\n 0.0\n > y = base.asinh( 2.0 )\n ~1.444\n > y = base.asinh( -2.0 )\n ~-1.444\n > y = base.asinh( NaN )\n NaN\n > y = base.asinh( NINF )\n -Infinity\n > y = base.asinh( PINF )\n Infinity\n\n See Also\n --------\n base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n Computes the arctangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atan( 0.0 )\n ~0.0\n > y = base.atan( -PI/2.0 )\n ~-1.004\n > y = base.atan( PI/2.0 )\n ~1.004\n > y = base.atan( NaN )\n NaN\n\n See Also\n --------\n base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n\n Parameters\n ----------\n y: number\n Coordinate along y-axis.\n\n x: number\n Coordinate along x-axis.\n\n Returns\n -------\n out: number\n Angle (in radians).\n\n Examples\n --------\n > var v = base.atan2( 2.0, 2.0 )\n ~0.785\n > v = base.atan2( 6.0, 2.0 )\n ~1.249\n > v = base.atan2( -1.0, -1.0 )\n ~-2.356\n > v = base.atan2( 3.0, 0.0 )\n ~1.571\n > v = base.atan2( -2.0, 0.0 )\n ~-1.571\n > v = base.atan2( 0.0, 0.0 )\n 0.0\n > v = base.atan2( 3.0, NaN )\n NaN\n > v = base.atan2( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.atan\n","base.atand":"\nbase.atand( x )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in degrees).\n\n Examples\n --------\n > var y = base.atand( 0.0 )\n 0.0\n > y = base.atand( PI/6.0 )\n ~27.64\n > y = base.atand( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n Computes the arctangent of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Arctangent (in radians).\n\n Examples\n --------\n > var y = base.atanf( 0.0 )\n 0.0\n > y = base.atanf( -3.14/4.0 )\n ~-0.666\n > y = base.atanf( 3.14/4.0 )\n ~0.666\n > y = base.atanf( NaN )\n NaN\n\n See Also\n --------\n base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n\n If `|x| > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic arctangent.\n\n Examples\n --------\n > var y = base.atanh( 0.0 )\n 0.0\n > y = base.atanh( 0.9 )\n ~1.472\n > y = base.atanh( 1.0 )\n Infinity\n > y = base.atanh( -1.0 )\n -Infinity\n > y = base.atanh( NaN )\n NaN\n\n See Also\n --------\n base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n Computes the inverse versed cosine.\n\n The inverse versed cosine is defined as `acos(1+x)`.\n\n If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed cosine.\n\n Examples\n --------\n > var y = base.avercos( -1.5 )\n ~2.0944\n > y = base.avercos( -0.0 )\n 0.0\n\n See Also\n --------\n base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n Computes the inverse versed sine.\n\n The inverse versed sine is defined as `acos(1-x)`.\n\n If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Inverse versed sine.\n\n Examples\n --------\n > var y = base.aversin( 1.5 )\n ~2.0944\n > y = base.aversin( 0.0 )\n 0.0\n\n See Also\n --------\n base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n Returns a zero-filled \"generic\" array.\n\n Parameters\n ----------\n len: integer\n Array length.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros( 3 )\n [ 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n Returns a zero-filled two-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros2d( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n Returns a zero-filled three-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros3d( [ 1, 1, 3 ] )\n [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n See Also\n --------\n base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n Returns a zero-filled four-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n Returns a zero-filled five-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n See Also\n --------\n base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n Returns a zero-filled n-dimensional nested array.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n Returns\n -------\n out: Array\n Output array.\n\n Examples\n --------\n > var out = base.azerosnd( [ 1, 3 ] )\n [ [ 0.0, 0.0, 0.0 ] ]\n\n See Also\n --------\n base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n\n If `n` is a non-integer value greater than zero, the function returns an\n array having `ceil(n)` elements.\n\n If `n` is less than or equal to zero, the function returns an empty array.\n\n Parameters\n ----------\n n: number\n Number of elements.\n\n Returns\n -------\n out: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = base.azeroTo( 6 )\n [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n\n Parameters\n ----------\n out: ArrayLikeObject\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > base.azeroTo.assign( out, -1, out.length-1 );\n > out\n [ 5, 4, 3, 2, 1, 0 ]\n\n See Also\n --------\n base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n Computes the nth Bernoulli number.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Bernoulli number.\n\n Examples\n --------\n > var y = base.bernoulli( 0 )\n 1.0\n > y = base.bernoulli( 1 )\n 0.5\n > y = base.bernoulli( 2 )\n ~0.167\n > y = base.bernoulli( 3 )\n 0.0\n > y = base.bernoulli( 4 )\n ~-0.033\n > y = base.bernoulli( 5 )\n 0.0\n > y = base.bernoulli( 20 )\n ~-529.124\n > y = base.bernoulli( 260 )\n -Infinity\n > y = base.bernoulli( 262 )\n Infinity\n > y = base.bernoulli( NaN )\n NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n Computes the Bessel function of the first kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj0( 0.0 )\n 1.0\n > y = base.besselj0( 1.0 )\n ~0.765\n > y = base.besselj0( PINF )\n 0.0\n > y = base.besselj0( NINF )\n 0.0\n > y = base.besselj0( NaN )\n NaN\n\n See Also\n --------\n base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n Computes the Bessel function of the first kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.besselj1( 0.0 )\n 0.0\n > y = base.besselj1( 1.0 )\n ~0.440\n > y = base.besselj1( PINF )\n 0.0\n > y = base.besselj1( NINF )\n 0.0\n > y = base.besselj1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n Computes the Bessel function of the second kind of order zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely0( 0.0 )\n -Infinity\n > y = base.bessely0( 1.0 )\n ~0.088\n > y = base.bessely0( -1.0 )\n NaN\n > y = base.bessely0( PINF )\n 0.0\n > y = base.bessely0( NINF )\n NaN\n > y = base.bessely0( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n Computes the Bessel function of the second kind of order one.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.bessely1( 0.0 )\n -Infinity\n > y = base.bessely1( 1.0 )\n ~-0.781\n > y = base.bessely1( -1.0 )\n NaN\n > y = base.bessely1( PINF )\n 0.0\n > y = base.bessely1( NINF )\n NaN\n > y = base.bessely1( NaN )\n NaN\n\n See Also\n --------\n base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n Evaluates the beta function.\n\n Parameters\n ----------\n x: number\n First function parameter (nonnegative).\n\n y: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Evaluated beta function.\n\n Examples\n --------\n > var v = base.beta( 0.0, 0.5 )\n Infinity\n > v = base.beta( 1.0, 1.0 )\n 1.0\n > v = base.beta( -1.0, 2.0 )\n NaN\n > v = base.beta( 5.0, 0.2 )\n ~3.382\n > v = base.beta( 4.0, 1.0 )\n 0.25\n > v = base.beta( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n Computes the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betainc( 0.5, 2.0, 2.0 )\n 0.5\n > y = base.betainc( 0.5, 2.0, 2.0, false )\n ~0.083\n > y = base.betainc( 0.2, 1.0, 2.0 )\n 0.36\n > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n 0.64\n > y = base.betainc( NaN, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.8, NaN, 1.0 )\n NaN\n > y = base.betainc( 0.8, 1.0, NaN )\n NaN\n > y = base.betainc( 1.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betainc( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betainc( 0.5, 2.0, -2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n Computes the inverse of the lower incomplete beta function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second and third arguments are `a` and `b`,\n respectively.\n\n By default, the function inverts the lower regularized incomplete beta\n function. To invert the upper function, set the `upper` argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete beta function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n ~0.327\n > y = base.betaincinv( 0.4, 3.0, 3.0 )\n ~0.446\n > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n ~0.554\n > y = base.betaincinv( 0.4, 1.0, 6.0 )\n ~0.082\n > y = base.betaincinv( 0.8, 1.0, 6.0 )\n ~0.235\n > y = base.betaincinv( NaN, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, NaN, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, 1.0, NaN )\n NaN\n > y = base.betaincinv( 1.2, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( -0.5, 1.0, 1.0 )\n NaN\n > y = base.betaincinv( 0.5, -2.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 0.0, 2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, -2.0 )\n NaN\n > y = base.betaincinv( 0.5, 2.0, 0.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n Evaluates the natural logarithm of the beta function.\n\n Parameters\n ----------\n a: number\n First function parameter (nonnegative).\n\n b: number\n Second function parameter (nonnegative).\n\n Returns\n -------\n out: number\n Natural logarithm of the beta function.\n\n Examples\n --------\n > var v = base.betaln( 0.0, 0.0 )\n Infinity\n > v = base.betaln( 1.0, 1.0 )\n 0.0\n > v = base.betaln( -1.0, 2.0 )\n NaN\n > v = base.betaln( 5.0, 0.2 )\n ~1.218\n > v = base.betaln( 4.0, 1.0 )\n ~-1.386\n > v = base.betaln( NaN, 2.0 )\n NaN\n\n See Also\n --------\n base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n Evaluates Binet's formula extended to real numbers.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function result.\n\n Examples\n --------\n > var y = base.binet( 0.0 )\n 0.0\n > y = base.binet( 1.0 )\n 1.0\n > y = base.binet( 2.0 )\n 1.0\n > y = base.binet( 3.0 )\n 2.0\n > y = base.binet( 4.0 )\n 3.0\n > y = base.binet( 5.0 )\n ~5.0\n > y = base.binet( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n Computes the binomial coefficient of two integers.\n\n If `k < 0`, the function returns `0`.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = base.binomcoef( 8, 2 )\n 28\n > v = base.binomcoef( 0, 0 )\n 1\n > v = base.binomcoef( -4, 2 )\n 10\n > v = base.binomcoef( 5, 3 )\n 10\n > v = base.binomcoef( NaN, 3 )\n NaN\n > v = base.binomcoef( 5, NaN )\n NaN\n > v = base.binomcoef( NaN, NaN )\n NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n Computes the natural logarithm of the binomial coefficient of two integers.\n\n If `k < 0`, the function returns negative infinity.\n\n The function returns `NaN` for non-integer `n` or `k`.\n\n Parameters\n ----------\n n: integer\n First input value.\n\n k: integer\n Second input value.\n\n Returns\n -------\n out: number\n Natural logarithm of the binomial coefficient.\n\n Examples\n --------\n > var v = base.binomcoefln( 8, 2 )\n ~3.332\n > v = base.binomcoefln( 0, 0 )\n 0.0\n > v = base.binomcoefln( -4, 2 )\n ~2.303\n > v = base.binomcoefln( 88, 3 )\n ~11.606\n > v = base.binomcoefln( NaN, 3 )\n NaN\n > v = base.binomcoefln( 5, NaN )\n NaN\n > v = base.binomcoefln( NaN, NaN )\n NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n Computes a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox( 1.0, 2.5 )\n 0.0\n > v = base.boxcox( 4.0, 2.5 )\n 12.4\n > v = base.boxcox( 10.0, 2.5 )\n ~126.0911\n > v = base.boxcox( 2.0, 0.0 )\n ~0.6931\n > v = base.boxcox( -1.0, 2.5 )\n NaN\n > v = base.boxcox( 0.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n Computes a one-parameter Box-Cox transformation of 1+x.\n\n Parameters\n ----------\n x: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1p( 1.0, 2.5 )\n ~1.8627\n > v = base.boxcox1p( 4.0, 2.5 )\n ~21.9607\n > v = base.boxcox1p( 10.0, 2.5 )\n ~160.1246\n > v = base.boxcox1p( 2.0, 0.0 )\n ~1.0986\n > v = base.boxcox1p( -1.0, 2.5 )\n -0.4\n > v = base.boxcox1p( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1p( -1.0, -1.0 )\n -Infinity\n\n See Also\n --------\n base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcox1pinv( 1.0, 2.5 )\n ~0.6505\n > v = base.boxcox1pinv( 4.0, 2.5 )\n ~1.6095\n > v = base.boxcox1pinv( 10.0, 2.5 )\n ~2.6812\n > v = base.boxcox1pinv( 2.0, 0.0 )\n ~6.3891\n > v = base.boxcox1pinv( -1.0, 2.5 )\n NaN\n > v = base.boxcox1pinv( 0.0, -1.0 )\n 0.0\n > v = base.boxcox1pinv( 1.0, NaN )\n NaN\n > v = base.boxcox1pinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n Computes the inverse of a one-parameter Box-Cox transformation.\n\n Parameters\n ----------\n y: number\n Input value.\n\n lambda: number\n Power parameter.\n\n Returns\n -------\n b: number\n Function value.\n\n Examples\n --------\n > var v = base.boxcoxinv( 1.0, 2.5 )\n ~1.6505\n > v = base.boxcoxinv( 4.0, 2.5 )\n ~2.6095\n > v = base.boxcoxinv( 10.0, 2.5 )\n ~3.6812\n > v = base.boxcoxinv( 2.0, 0.0 )\n ~7.3891\n > v = base.boxcoxinv( -1.0, 2.5 )\n NaN\n > v = base.boxcoxinv( 0.0, -1.0 )\n 1.0\n > v = base.boxcoxinv( 1.0, NaN )\n NaN\n > v = base.boxcoxinv( NaN, 3.1 )\n NaN\n\n See Also\n --------\n base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n Computes the absolute value of a double-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Squared absolute value.\n\n Examples\n --------\n > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n 34.0\n\n See Also\n --------\n base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n Computes the absolute value of a single-precision complex floating-point\n number.\n\n The absolute value of a complex number is its distance from zero.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n y: number\n Absolute value.\n\n Examples\n --------\n > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n ~5.831\n\n See Also\n --------\n base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n Adds two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var out = base.cadd( z, z )\n \n > var re = real( out )\n 10.0\n > var im = imag( out )\n 6.0\n\n\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub\n","base.cadd.assign":"\nbase.cadd.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cadd.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.cadd.strided":"\nbase.cadd.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cadd.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cdiv, base.cmul, base.csub","base.caddf":"\nbase.caddf( z1, z2 )\n Adds two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var out = base.caddf( z, z )\n \n > var re = realf( out )\n 10.0\n > var im = imagf( out )\n 6.0\n\n\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf\n","base.caddf.assign":"\nbase.caddf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.caddf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ 3.0, 4.0 ]","base.caddf.strided":"\nbase.caddf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.caddf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n base.cadd, base.cmulf, base.csubf","base.camelcase":"\nbase.camelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = base.camelcase( 'Hello World!' )\n 'helloWorld'\n > out = base.camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = base.capitalize( 'beep' )\n 'Beep'\n > out = base.capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n Computes the cube root of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrt( 64.0 )\n 4.0\n > y = base.cbrt( 27.0 )\n 3.0\n > y = base.cbrt( 0.0 )\n 0.0\n > y = base.cbrt( -0.0 )\n -0.0\n > y = base.cbrt( -9.0 )\n ~-2.08\n > y = base.cbrt( NaN )\n NaN\n\n See Also\n --------\n base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n Computes the cube root of a single-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cube root.\n\n Examples\n --------\n > var y = base.cbrtf( 64.0 )\n 4.0\n > y = base.cbrtf( 27.0 )\n 3.0\n > y = base.cbrtf( 0.0 )\n 0.0\n > y = base.cbrtf( -0.0 )\n -0.0\n > y = base.cbrtf( -9.0 )\n ~-2.08\n > y = base.cbrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n [ -1.0, 3.0 ]\n\n See Also\n --------\n base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Real and imaginary components.\n\n Examples\n --------\n > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.56, -3.33 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n Divides two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( -13.0, -1.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var y = base.cdiv( z1, z2 )\n \n > var re = real( y )\n 5.0\n > var im = imag( y )\n 3.0\n\n\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.cdiv.assign":"\nbase.cdiv.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cdiv.assign( -13.0, -1.0, -2.0, 1.0, out, 1, 0 )\n [ 5.0, 3.0 ]","base.cdiv.strided":"\nbase.cdiv.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ -13.0, -1.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cdiv.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cadd, base.cmul, base.csub","base.ceil":"\nbase.ceil( x )\n Rounds a double-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil( 3.14 )\n 4.0\n > y = base.ceil( -4.2 )\n -4.0\n > y = base.ceil( -4.6 )\n -4.0\n > y = base.ceil( 9.5 )\n 10.0\n > y = base.ceil( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil2( 3.14 )\n 4.0\n > y = base.ceil2( -4.2 )\n -4.0\n > y = base.ceil2( -4.6 )\n -4.0\n > y = base.ceil2( 9.5 )\n 16.0\n > y = base.ceil2( 13.0 )\n 16.0\n > y = base.ceil2( -13.0 )\n -8.0\n > y = base.ceil2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceil10( 3.14 )\n 10.0\n > y = base.ceil10( -4.2 )\n -1.0\n > y = base.ceil10( -4.6 )\n -1.0\n > y = base.ceil10( 9.5 )\n 10.0\n > y = base.ceil10( 13.0 )\n 100.0\n > y = base.ceil10( -13.0 )\n -10.0\n > y = base.ceil10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.ceilb( 3.14159, -4, 10 )\n 3.1416\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.ceilb( 3.14159, 0, 2 )\n 4.0\n\n // Round to nearest multiple of two toward positive infinity:\n > y = base.ceilb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n Rounds a single-precision floating-point number toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilf( 3.14 )\n 4.0\n > y = base.ceilf( -4.2 )\n -4.0\n > y = base.ceilf( -4.6 )\n -4.0\n > y = base.ceilf( 9.5 )\n 10.0\n > y = base.ceilf( -0.0 )\n -0.0\n\n See Also\n --------\n base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.ceiln( 3.14159, -2 )\n 3.15\n\n // If `n = 0`, standard round toward positive infinity behavior:\n > y = base.ceiln( 3.14159, 0 )\n 4.0\n\n // Round to nearest thousand:\n > y = base.ceiln( 12368.0, 3 )\n 13000.0\n\n\n See Also\n --------\n base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.ceilsd( 3.14159, 5, 10 )\n 3.1416\n > y = base.ceilsd( 3.14159, 1, 10 )\n 4.0\n > y = base.ceilsd( 12368.0, 2, 10 )\n 13000.0\n > y = base.ceilsd( 0.0313, 2, 2 )\n 0.046875\n\n See Also\n --------\n base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex number.\n\n Examples\n --------\n > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n [ 1.0, 0.0 ]\n > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n [ ~0.540, ~0.841 ]\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n [ 4.2, -5.5 ]\n\n See Also\n --------\n base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n y: number\n Number from which to derive the sign.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n [ 4.0, -5.0 ]\n\n See Also\n --------\n base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n z: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n [ 5.55, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex128\n Input value.\n\n Returns\n -------\n v: Complex128\n Input value.\n\n Examples\n --------\n > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n \n > var re = real( v )\n -1.0\n > var img = imag( v )\n 2.0\n\n See Also\n --------\n base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n\n Parameters\n ----------\n z: Complex64\n Input value.\n\n Returns\n -------\n v: Complex64\n Input value.\n\n Examples\n --------\n > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n \n > var re = realf( v )\n -1.0\n > var img = imagf( v )\n 2.0\n\n See Also\n --------\n base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n Computes the inverse of a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n [ 0.1, -0.2 ]\n\n See Also\n --------\n base.cdiv, base.cinvf\n","base.cinvf":"\nbase.cinvf( z )\n Computes the inverse of a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var v = base.cinvf( new Complex64( 2.0, 4.0 ) )\n [ ~0.1, ~-0.2 ]\n\n See Also\n --------\n base.cinv\n","base.clamp":"\nbase.clamp( v, min, max )\n Restricts a double-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clamp( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clamp( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clamp( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clamp( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clamp( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n Restricts a single-precision floating-point number to a specified range.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to restrict.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Restricted value.\n\n Examples\n --------\n > var y = base.clampf( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.clampf( -3.14, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 3.14, 0.0, 3.0 )\n 3.0\n > y = base.clampf( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.clampf( 0.0, -3.14, -0.0 )\n -0.0\n > y = base.clampf( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n Multiplies two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.cmul( z1, z2 )\n \n > var re = real( out )\n -13.0\n > var im = imag( out )\n -1.0\n\n\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub\n","base.cmul.assign":"\nbase.cmul.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > base.cmul.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmul.strided":"\nbase.cmul.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float64Array( [ 5.0, 3.0 ] );\n > var z2 = new Float64Array( [ -2.0, 1.0 ] );\n > var out = new Float64Array( 2 );\n > base.cmul.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.cadd, base.cdiv, base.csub","base.cmulf":"\nbase.cmulf( z1, z2 )\n Multiplies two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.cmulf( z1, z2 )\n \n > var re = realf( out )\n -13.0\n > var im = imagf( out )\n -1.0\n\n\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf\n","base.cmulf.assign":"\nbase.cmulf.assign( re1, im1, re2, im2, out, strideOut, offsetOut )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n\n Parameters\n ----------\n re1: number\n Real component of the first complex number.\n\n im1: number\n Imaginary component of the first complex number.\n\n re2: number\n Real component of the second complex number.\n\n im2: number\n Imaginary component of the second complex number.\n\n out: ArrayLikeObject\n Output array.\n\n strideOut: integer\n Stride length.\n\n offsetOut: integer\n Starting index.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = new Float32Array( 2 );\n > base.cmulf.assign( 5.0, 3.0, -2.0, 1.0, out, 1, 0 )\n [ -13.0, -1.0 ]","base.cmulf.strided":"\nbase.cmulf.strided( z1, sz1, oz1, z2, sz2, oz2, out, so, oo )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n\n Parameters\n ----------\n z1: ArrayLikeObject\n First complex number view.\n\n sz1: integer\n Stride length for `z1`.\n\n oz1: integer\n Starting index for `z1`.\n\n z2: ArrayLikeObject\n Second complex number view.\n\n sz2: integer\n Stride length for `z2`.\n\n oz2: integer\n Starting index for `z2`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Stride length for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var z1 = new Float32Array( [ 5.0, 3.0 ] );\n > var z2 = new Float32Array( [ -2.0, 1.0 ] );\n > var out = new Float32Array( 2 );\n > base.cmulf.strided( z1, 1, 0, z2, 1, 0, out, 1, 0 )\n [ -13.0, -1.0 ]\n\n See Also\n --------\n base.caddf, base.cmul, base.csubf","base.cneg":"\nbase.cneg( z )\n Negates a double-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z = new Complex128( -4.2, 5.5 )\n \n > var v = base.cneg( z )\n \n > var re = real( v )\n 4.2\n > var im = imag( v )\n -5.5\n\n See Also\n --------\n base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n Negates a single-precision complex floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z = new Complex64( -4.0, 5.0 )\n \n > var v = base.cnegf( z )\n \n > var re = realf( v )\n 4.0\n > var im = imagf( v )\n -5.0\n\n See Also\n --------\n base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean\n Backward iteration for low surrogates.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = base.codePointAt( 'last man standing', 4, false )\n 32\n > out = base.codePointAt( 'presidential election', 8, true )\n 116\n > out = base.codePointAt( 'अनुच्छेद', 2, false )\n 2369\n > out = base.codePointAt( '🌷', 1, true )\n 127799\n","base.constantcase":"\nbase.constantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = base.constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = base.constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n\n `generator` can be either a function which returns an array with two\n elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n By default, the function computes\n\n a1\n ---------------\n b1 + a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n To evaluate\n\n b0 +\t a1\n ---------------\n b1 +\t a2\n ----------\n b2 + a3\n -----\n b3 + ...\n\n set the `keep` option to `true`.\n\n Parameters\n ----------\n generator: Function\n Function returning terms of continued fraction expansion.\n\n options: Object (optional)\n Options.\n\n options.maxIter: integer (optional)\n Maximum number of iterations. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n current term times the tolerance. Default: `2.22e-16`.\n\n options.keep: boolean (optional)\n Boolean indicating whether to keep the `b0` term in the continued\n fraction. Default: `false`.\n\n Returns\n -------\n out: number\n Value of continued fraction.\n\n Examples\n --------\n // Continued fraction for (e-1)^(-1):\n > function closure() {\n ... var i = 0;\n ... return function() {\n ... i += 1;\n ... return [ i, i ];\n ... };\n ... };\n > var gen = closure();\n > var out = base.continuedFraction( gen )\n ~0.582\n\n // Using an ES6 generator:\n > function* generator() {\n ... var i = 0;\n ... while ( true ) {\n ... i += 1;\n ... yield [ i, i ];\n ... }\n ... };\n > gen = generator();\n > out = base.continuedFraction( gen )\n ~0.582\n\n // Set options:\n > out = base.continuedFraction( generator(), { 'keep': true } )\n ~1.718\n > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n ~0.582\n > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysign( -3.14, 10.0 )\n 3.14\n > z = base.copysign( 3.14, -1.0 )\n -3.14\n > z = base.copysign( 1.0, -0.0 )\n -1.0\n > z = base.copysign( -3.14, -0.0 )\n -3.14\n > z = base.copysign( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.copysignf( -3.0, 10.0 )\n 3.0\n > z = base.copysignf( 3.0, -1.0 )\n -3.0\n > z = base.copysignf( 1.0, -0.0 )\n -1.0\n > z = base.copysignf( -3.0, -0.0 )\n -3.0\n > z = base.copysignf( -0.0, 1.0 )\n 0.0\n\n See Also\n --------\n base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n Computes the cosine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cos( 0.0 )\n 1.0\n > y = base.cos( PI/4.0 )\n ~0.707\n > y = base.cos( -PI/6.0 )\n ~0.866\n > y = base.cos( NaN )\n NaN\n\n See Also\n --------\n base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n Computes the cosine of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosine.\n\n Examples\n --------\n > var y = base.cosd( 0.0 )\n 1.0\n > y = base.cosd( 90.0 )\n 0.0\n > y = base.cosd( 60.0 )\n ~0.5\n > y = base.cosd( NaN )\n NaN\n\n See Also\n --------\n base.tand\n","base.cosh":"\nbase.cosh( x )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cosine.\n\n Examples\n --------\n > var y = base.cosh( 0.0 )\n 1.0\n > y = base.cosh( 2.0 )\n ~3.762\n > y = base.cosh( -2.0 )\n ~3.762\n > y = base.cosh( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n Computes the cosine of a number minus one.\n\n This function should be used instead of manually calculating `cos(x)-1` when\n `x` is near unity.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosine minus one.\n\n Examples\n --------\n > var y = base.cosm1( 0.0 )\n 0.0\n > y = base.cosm1( PI/4.0 )\n ~-0.293\n > y = base.cosm1( -PI/6.0 )\n ~-0.134\n > y = base.cosm1( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cospi":"\nbase.cospi( x )\n Computes the value of `cos(πx)`.\n\n This function computes `cos(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.cospi( 0.0 )\n 1.0\n > y = base.cospi( 0.5 )\n 0.0\n > y = base.cospi( 0.1 )\n ~0.951\n > y = base.cospi( NaN )\n NaN\n\n See Also\n --------\n base.cos\n","base.cot":"\nbase.cot( x )\n Computes the cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cot( 0.0 )\n Infinity\n > y = base.cot( -PI/4.0 )\n ~-1.0\n > y = base.cot( PI/4.0 )\n ~1.0\n > y = base.cot( NaN )\n NaN\n\n See Also\n --------\n base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n Computes the cotangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cotangent.\n\n Examples\n --------\n > var y = base.cotd( 0.0 )\n Infinity\n > y = base.cotd( 90.0 )\n 0.0\n > y = base.cotd( 60.0 )\n ~0.58\n > y = base.cotd( NaN )\n NaN\n\n See Also\n --------\n base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n Computes the hyperbolic cotangent of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic cotangent.\n\n Examples\n --------\n > var y = base.coth( 0.0 )\n Infinity\n > y = base.coth( -0.0 )\n -Infinity\n > y = base.coth( 2.0 )\n ~1.0373\n > y = base.coth( -2.0 )\n ~-1.0373\n > y = base.coth( +Infinity )\n ~1\n > y = base.coth( -Infinity )\n ~-1\n > y = base.coth( NaN )\n NaN\n\n See Also\n --------\n base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n Computes the coversed cosine.\n\n The coversed cosine is defined as `1 + sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed cosine.\n\n Examples\n --------\n > var y = base.covercos( 3.14 )\n ~1.0016\n > y = base.covercos( -4.2 )\n ~1.8716\n > y = base.covercos( -4.6 )\n ~1.9937\n > y = base.covercos( 9.5 )\n ~0.9248\n > y = base.covercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n Computes the coversed sine.\n\n The coversed sine is defined as `1 - sin(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Coversed sine.\n\n Examples\n --------\n > var y = base.coversin( 3.14 )\n ~0.9984\n > y = base.coversin( -4.2 )\n ~0.1284\n > y = base.coversin( -4.6 )\n ~0.0063\n > y = base.coversin( 9.5 )\n ~1.0752\n > y = base.coversin( -0.0 )\n 1.0\n\n See Also\n --------\n base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n\n The argument of a complex number, also known as the phase, is the angle of\n the radius extending from the origin to the complex number plotted in the\n complex plane and the positive real axis.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n phi: number\n Argument.\n\n Examples\n --------\n > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n ~0.5404\n\n See Also\n --------\n base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Array\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n out: Array|TypedArray|Object\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Absolute value and phase, respectively.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n [ ~5.83, ~0.5404 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Rounded complex number.\n\n Examples\n --------\n > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n [ 6.0, 3.0 ]\n\n See Also\n --------\n base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n [ 5.56, -3.34 ]\n\n See Also\n --------\n base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n Computes the cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.csc( 0.0 )\n Infinity\n > y = base.csc( PI/2.0 )\n ~1.0\n > y = base.csc( -PI/6.0 )\n ~-2.0\n > y = base.csc( NaN )\n NaN\n\n See Also\n --------\n base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n Computes the cosecant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Cosecant.\n\n Examples\n --------\n > var y = base.cscd( 1.0 )\n ~57.30\n > y = base.cscd( PI )\n ~18.25\n > y = base.cscd( -PI )\n ~-18.25\n > y = base.cscd( NaN )\n NaN\n\n See Also\n --------\n base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n Computes the hyperbolic cosecant of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Hyperbolic cosecant.\n\n Examples\n --------\n > var y = base.csch( +0.0 )\n +Infinity\n > var y = base.csch( -0.0 )\n -Infinity\n > var y = base.csch( +Infinity )\n +0.0\n > var y = base.csch( -Infinity )\n -0.0\n > y = base.csch( 2.0 )\n ~0.2757\n > y = base.csch( -2.0 )\n ~-0.2757\n > y = base.csch( NaN )\n NaN\n\n See Also\n --------\n base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n [ -0.6069136033622302, 0.79476781392673 ]\n\n See Also\n --------\n base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n Subtracts two double-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex128\n Complex number.\n\n z2: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Result.\n\n Examples\n --------\n > var z1 = new Complex128( 5.0, 3.0 )\n \n > var z2 = new Complex128( -2.0, 1.0 )\n \n > var out = base.csub( z1, z2 )\n \n > var re = real( out )\n 7.0\n > var im = imag( out )\n 2.0\n\n See Also\n --------\n base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n Subtracts two single-precision complex floating-point numbers.\n\n Parameters\n ----------\n z1: Complex64\n Complex number.\n\n z2: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Result.\n\n Examples\n --------\n > var z1 = new Complex64( 5.0, 3.0 )\n \n > var z2 = new Complex64( -2.0, 1.0 )\n \n > var out = base.csubf( z1, z2 )\n \n > var re = realf( out )\n 7.0\n > var im = imagf( out )\n 2.0\n\n See Also\n --------\n base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n Converts an angle from degrees to radians.\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2rad( 90.0 )\n ~1.571\n > r = base.deg2rad( -45.0 )\n ~-0.785\n > r = base.deg2rad( NaN )\n NaN\n\n See Also\n --------\n base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n Converts an angle from degrees to radians (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in degrees.\n\n Returns\n -------\n r: number\n Angle in radians.\n\n Examples\n --------\n > var r = base.deg2radf( 90.0 )\n ~1.571\n > r = base.deg2radf( -45.0 )\n ~-0.785\n > r = base.deg2radf( NaN )\n NaN\n\n See Also\n --------\n base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n Evaluates the digamma function.\n\n If `x` is zero or a negative integer, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.digamma( -2.5 )\n ~1.103\n > y = base.digamma( 1.0 )\n ~-0.577\n > y = base.digamma( 10.0 )\n ~2.252\n > y = base.digamma( NaN )\n NaN\n > y = base.digamma( -1.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n Evaluates the Dirac delta function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.diracDelta( 3.14 )\n 0.0\n > y = base.diracDelta( 0.0 )\n Infinity\n\n See Also\n --------\n base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n Divides two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.div( -1.0, 5.0 )\n -0.2\n > v = base.div( 2.0, 5.0 )\n 0.4\n > v = base.div( 0.0, 5.0 )\n 0.0\n > v = base.div( -0.0, 5.0 )\n -0.0\n > v = base.div( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n Divides two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value (dividend).\n\n y: number\n Second input value (divisor).\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.divf( -1.0, 5.0 )\n ~-0.2\n > v = base.divf( 2.0, 5.0 )\n ~0.4\n > v = base.divf( 0.0, 5.0 )\n 0.0\n > v = base.divf( -0.0, 5.0 )\n -0.0\n > v = base.divf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = base.dotcase( 'Hello World!' )\n 'hello.world'\n > out = base.dotcase( 'I am a tiny little teapot' )\n 'i.am.a.tiny.little.teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n Returns an arcsine distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be less than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n arcsine: Object\n Distribution instance.\n\n arcsine.a: number\n Minimum support. If set, the value must be less than `b`.\n\n arcsine.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n arcsine.entropy: number\n Read-only property which returns the differential entropy.\n\n arcsine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n arcsine.mean: number\n Read-only property which returns the expected value.\n\n arcsine.median: number\n Read-only property which returns the median.\n\n arcsine.mode: number\n Read-only property which returns the mode.\n\n arcsine.skewness: number\n Read-only property which returns the skewness.\n\n arcsine.stdev: number\n Read-only property which returns the standard deviation.\n\n arcsine.variance: number\n Read-only property which returns the variance.\n\n arcsine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n arcsine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n arcsine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n arcsine.pdf: Function\n Evaluates the probability density function (PDF).\n\n arcsine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n > arcsine.a\n 0.0\n > arcsine.b\n 1.0\n > arcsine.entropy\n ~-0.242\n > arcsine.kurtosis\n -1.5\n > arcsine.mean\n 0.5\n > arcsine.median\n 0.5\n > arcsine.mode\n 0.0\n > arcsine.skewness\n 0.0\n > arcsine.stdev\n ~0.354\n > arcsine.variance\n 0.125\n > arcsine.cdf( 0.8 )\n ~0.705\n > arcsine.logcdf( 0.8 )\n ~-0.35\n > arcsine.logpdf( 0.4 )\n ~-0.431\n > arcsine.pdf( 0.8 )\n ~0.796\n > arcsine.quantile( 0.8 )\n ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n ~0.795\n > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n ~0.333\n > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n ~0.144\n > y = mycdf( 8.0 )\n ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n Returns the differential entropy of an arcsine distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n ~-0.242\n > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n ~1.838\n > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n Returns the excess kurtosis of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n -1.5\n > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an arcsine distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n ~-0.229\n > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n ~-1.1\n > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-1.941\n > y = mylogcdf( 8.0 )\n ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an arcsine distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n ~-1.838\n > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n ~-0.308\n > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n Infinity\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n Returns the expected value of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n Returns the median of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.arcsine.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.arcsine.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n Returns the mode of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.mode( 4.0, 12.0 )\n 4.0\n > v = base.dists.arcsine.mode( 2.0, 8.0 )\n 2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n ~0.159\n > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n ~0.735\n > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n Infinity\n > y = myPDF( 5.0 )\n 0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n ~0.905\n > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n ~5.0\n\n > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n Returns the skewness of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n Returns the standard deviation of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n ~0.354\n > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n Returns the variance of an arcsine distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n ~0.125\n > v = base.dists.arcsine.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.arcsine.variance( 2.0, 8.0 )\n ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n Returns a Bernoulli distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n bernoulli: Object\n Distribution instance.\n\n bernoulli.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n bernoulli.entropy: number\n Read-only property which returns the differential entropy.\n\n bernoulli.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n bernoulli.mean: number\n Read-only property which returns the expected value.\n\n bernoulli.median: number\n Read-only property which returns the median.\n\n bernoulli.skewness: number\n Read-only property which returns the skewness.\n\n bernoulli.stdev: number\n Read-only property which returns the standard deviation.\n\n bernoulli.variance: number\n Read-only property which returns the variance.\n\n bernoulli.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n bernoulli.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n bernoulli.pmf: Function\n Evaluates the probability mass function (PMF).\n\n bernoulli.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n > bernoulli.p\n 0.6\n > bernoulli.entropy\n ~0.673\n > bernoulli.kurtosis\n ~-1.833\n > bernoulli.mean\n 0.6\n > bernoulli.median\n 1.0\n > bernoulli.skewness\n ~-0.408\n > bernoulli.stdev\n ~0.49\n > bernoulli.variance\n ~0.24\n > bernoulli.cdf( 0.5 )\n 0.4\n > bernoulli.mgf( 3.0 )\n ~12.451\n > bernoulli.pmf( 0.0 )\n 0.4\n > bernoulli.quantile( 0.7 )\n 1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n 0.5\n > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n 0.9\n > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n 0.0\n > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n 1.0\n > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.bernoulli.cdf( 0.0, NaN )\n NaN\n // Invalid probability:\n > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 1.0\n > y = mycdf( 0.7 )\n 0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.bernoulli.entropy( 0.1 )\n ~0.325\n > v = base.dists.bernoulli.entropy( 0.5 )\n ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.bernoulli.kurtosis( 0.1 )\n ~5.111\n > v = base.dists.bernoulli.kurtosis( 0.5 )\n -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mean( 0.1 )\n 0.1\n > v = base.dists.bernoulli.mean( 0.5 )\n 0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n Returns the median of a Bernoulli distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.bernoulli.median( 0.1 )\n 0\n > v = base.dists.bernoulli.median( 0.8 )\n 1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n ~1.111\n > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n ~1.246\n > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n\n For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n `0` for `p = 0.5`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.bernoulli.mode( 0.1 )\n 0\n > v = base.dists.bernoulli.mode( 0.8 )\n 1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n 0.3\n > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n 0.3\n > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.bernoulli.pmf( 0.0, NaN )\n NaN\n > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n > var y = mypmf( 1.0 )\n 0.5\n > y = mypmf( 0.0 )\n 0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n 1\n > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n 0\n > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n 0\n\n > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 1\n > y = myquantile( 1.0 )\n 1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.bernoulli.skewness( 0.1 )\n ~2.667\n > v = base.dists.bernoulli.skewness( 0.5 )\n 0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.bernoulli.stdev( 0.1 )\n ~0.3\n > v = base.dists.bernoulli.stdev( 0.5 )\n 0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.bernoulli.variance( 0.1 )\n ~0.09\n > v = base.dists.bernoulli.variance( 0.5 )\n 0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n Returns a beta distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n beta: Object\n Distribution instance.\n\n beta.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n beta.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n beta.entropy: number\n Read-only property which returns the differential entropy.\n\n beta.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n beta.mean: number\n Read-only property which returns the expected value.\n\n beta.median: number\n Read-only property which returns the median.\n\n beta.mode: number\n Read-only property which returns the mode.\n\n beta.skewness: number\n Read-only property which returns the skewness.\n\n beta.stdev: number\n Read-only property which returns the standard deviation.\n\n beta.variance: number\n Read-only property which returns the variance.\n\n beta.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n beta.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n beta.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n beta.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n beta.pdf: Function\n Evaluates the probability density function (PDF).\n\n beta.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n > beta.alpha\n 1.0\n > beta.beta\n 1.0\n > beta.entropy\n 0.0\n > beta.kurtosis\n -1.2\n > beta.mean\n 0.5\n > beta.median\n 0.5\n > beta.mode\n NaN\n > beta.skewness\n 0.0\n > beta.stdev\n ~0.289\n > beta.variance\n ~0.0833\n > beta.cdf( 0.8 )\n 0.8\n > beta.logcdf( 0.8 )\n ~-0.223\n > beta.logpdf( 1.0 )\n 0.0\n > beta.mgf( 3.14 )\n ~7.0394\n > beta.pdf( 1.0 )\n 1.0\n > beta.quantile( 0.8 )\n 0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n ~0.813\n > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n ~0.104\n > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n ~0.967\n > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.705\n > y = mycdf( 0.3 )\n ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n Returns the differential entropy of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.beta.entropy( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.entropy( 4.0, 12.0 )\n ~-0.869\n > v = base.dists.beta.entropy( 8.0, 2.0 )\n ~-0.795\n\n > v = base.dists.beta.entropy( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.entropy( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.entropy( 2.0, NaN )\n NaN\n > v = base.dists.beta.entropy( NaN, 2.0 )\n NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n Returns the excess kurtosis of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n -1.2\n > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n ~0.082\n > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n ~0.490\n\n > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.beta.kurtosis( NaN, 2.0 )\n NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n ~-0.208\n > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n ~-2.263\n > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n ~-0.034\n > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.35\n > y = mylogcdf( 0.3 )\n ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n ~0.223\n > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n ~-0.041\n > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n ~-0.556\n > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-0.228\n > y = mylogpdf( 0.3 )\n ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n Returns the expected value of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.beta.mean( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.mean( 4.0, 12.0 )\n 0.25\n > v = base.dists.beta.mean( 8.0, 2.0 )\n 0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n Returns the median of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.beta.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.beta.median( 4.0, 12.0 )\n ~0.239\n > v = base.dists.beta.median( 8.0, 2.0 )\n ~0.820\n\n > v = base.dists.beta.median( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.median( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.median( 2.0, NaN )\n NaN\n > v = base.dists.beta.median( NaN, 2.0 )\n NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n ~1.297\n > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n ~1.186\n > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n ~5.575\n > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n ~0.676\n\n > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n NaN\n\n > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n NaN\n > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n > var y = myMGF( 0.8 )\n ~1.552\n > y = myMGF( 0.3 )\n ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n Returns the mode of a beta distribution.\n\n If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.beta.mode( 4.0, 12.0 )\n ~0.214\n > v = base.dists.beta.mode( 8.0, 2.0 )\n ~0.875\n > v = base.dists.beta.mode( 1.0, 1.0 )\n NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n 1.25\n > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n ~0.96\n > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n ~0.573\n > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.796\n > y = mypdf( 0.3 )\n ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n ~0.894\n > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n ~0.686\n > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n > y = myquantile( 0.8 )\n ~0.713\n > y = myquantile( 0.4 )\n ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n Returns the skewness of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.beta.skewness( 1.0, 1.0 )\n 0.0\n > v = base.dists.beta.skewness( 4.0, 12.0 )\n ~0.529\n > v = base.dists.beta.skewness( 8.0, 2.0 )\n ~-0.829\n\n > v = base.dists.beta.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.skewness( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.skewness( 2.0, NaN )\n NaN\n > v = base.dists.beta.skewness( NaN, 2.0 )\n NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n Returns the standard deviation of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.beta.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.beta.stdev( 4.0, 12.0 )\n ~0.105\n > v = base.dists.beta.stdev( 8.0, 2.0 )\n ~0.121\n\n > v = base.dists.beta.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.stdev( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.stdev( 2.0, NaN )\n NaN\n > v = base.dists.beta.stdev( NaN, 2.0 )\n NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n Returns the variance of a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.beta.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.beta.variance( 4.0, 12.0 )\n ~0.011\n > v = base.dists.beta.variance( 8.0, 2.0 )\n ~0.015\n\n > v = base.dists.beta.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.beta.variance( -0.1, 1.0 )\n NaN\n\n > v = base.dists.beta.variance( 2.0, NaN )\n NaN\n > v = base.dists.beta.variance( NaN, 2.0 )\n NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n Returns a beta prime distribution object.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n betaprime: Object\n Distribution instance.\n\n betaprime.alpha: number\n First shape parameter. If set, the value must be greater than `0`.\n\n betaprime.beta: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n betaprime.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n betaprime.mean: number\n Read-only property which returns the expected value.\n\n betaprime.mode: number\n Read-only property which returns the mode.\n\n betaprime.skewness: number\n Read-only property which returns the skewness.\n\n betaprime.stdev: number\n Read-only property which returns the standard deviation.\n\n betaprime.variance: number\n Read-only property which returns the variance.\n\n betaprime.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n betaprime.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n betaprime.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n betaprime.pdf: Function\n Evaluates the probability density function (PDF).\n\n betaprime.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n > betaprime.alpha\n 6.0\n > betaprime.beta\n 5.0\n > betaprime.kurtosis\n 44.4\n > betaprime.mean\n 1.5\n > betaprime.mode\n ~0.833\n > betaprime.skewness\n ~3.578\n > betaprime.stdev\n ~1.118\n > betaprime.variance\n 1.25\n > betaprime.cdf( 0.8 )\n ~0.25\n > betaprime.logcdf( 0.8 )\n ~-1.387\n > betaprime.logpdf( 1.0 )\n ~-0.486\n > betaprime.pdf( 1.0 )\n ~0.615\n > betaprime.quantile( 0.8 )\n ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n ~0.333\n > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n ~0.539\n > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n ~0.074\n > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n ~0.38\n > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n > var y = mycdf( 0.8 )\n ~0.465\n > y = mycdf( 0.3 )\n ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n Returns the excess kurtosis of a beta prime distribution.\n\n If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n ~26.143\n > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n ~5.764\n > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n ~19.962\n\n > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n NaN\n\n > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n ~-1.099\n > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n ~-0.618\n > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n ~-2.603\n > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n ~-0.968\n > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n > var y = mylogcdf( 0.8 )\n ~-0.767\n > y = mylogcdf( 0.3 )\n ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n ~-0.811\n > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n ~-0.13\n > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n ~-0.547\n > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n ~-0.43\n > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n fcn: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n > var y = mylogpdf( 0.8 )\n ~-1.62\n > y = mylogpdf( 0.3 )\n ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n Returns the expected value of a beta prime distribution.\n\n If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n 1.0\n > v = base.dists.betaprime.mean( 4.0, 12.0 )\n ~0.364\n > v = base.dists.betaprime.mean( 8.0, 2.0 )\n 8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n Returns the mode of a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n 0.0\n > v = base.dists.betaprime.mode( 4.0, 12.0 )\n ~0.231\n > v = base.dists.betaprime.mode( 8.0, 2.0 )\n ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n ~0.444\n > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n ~0.878\n > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n ~0.579\n > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n ~0.65\n > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n > var y = mypdf( 0.8 )\n ~0.198\n > y = mypdf( 0.3 )\n ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value (probability).\n\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n ~8.472\n > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n ~2.187\n > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n > y = myQuantile( 0.8 )\n ~2.483\n > y = myQuantile( 0.4 )\n ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n Returns the skewness of a beta prime distribution.\n\n If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n ~6.261\n > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n ~1.724\n > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n ~5.729\n\n > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n NaN\n > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n NaN\n\n > v = base.dists.betaprime.skewness( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.skewness( NaN, 4.0 )\n NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n Returns the standard deviation of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n ~1.491\n > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n ~0.223\n > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n ~8.219\n\n > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.stdev( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.stdev( NaN, 3.0 )\n NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n Returns the variance of a beta prime distribution.\n\n If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n ~2.222\n > v = base.dists.betaprime.variance( 4.0, 12.0 )\n ~0.05\n > v = base.dists.betaprime.variance( 8.0, 2.5 )\n ~67.556\n\n > v = base.dists.betaprime.variance( 8.0, 1.0 )\n NaN\n > v = base.dists.betaprime.variance( 1.0, -0.1 )\n NaN\n > v = base.dists.betaprime.variance( -0.1, 3.0 )\n NaN\n\n > v = base.dists.betaprime.variance( 2.0, NaN )\n NaN\n > v = base.dists.betaprime.variance( NaN, 3.0 )\n NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n Returns a binomial distribution object.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials. Must be a positive integer. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n binomial: Object\n Distribution instance.\n\n binomial.n: number\n Number of trials. If set, the value must be a positive integer.\n\n binomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n binomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n binomial.mean: number\n Read-only property which returns the expected value.\n\n binomial.median: number\n Read-only property which returns the median.\n\n binomial.mode: number\n Read-only property which returns the mode.\n\n binomial.skewness: number\n Read-only property which returns the skewness.\n\n binomial.stdev: number\n Read-only property which returns the standard deviation.\n\n binomial.variance: number\n Read-only property which returns the variance.\n\n binomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n binomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n binomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n binomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n binomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n > binomial.n\n 8.0\n > binomial.p\n 0.5\n > binomial.kurtosis\n -0.25\n > binomial.mean\n 4.0\n > binomial.median\n 4.0\n > binomial.mode\n 4.0\n > binomial.skewness\n 0.0\n > binomial.stdev\n ~1.414\n > binomial.variance\n 2.0\n > binomial.cdf( 2.9 )\n ~0.145\n > binomial.logpmf( 3.0 )\n ~-1.52\n > binomial.mgf( 0.2 )\n ~2.316\n > binomial.pmf( 3.0 )\n ~0.219\n > binomial.quantile( 0.8 )\n 5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n ~0.411\n > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n 1.0\n > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n ~0.834\n > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n > var y = mycdf( 3.0 )\n ~0.172\n > y = mycdf( 1.0 )\n ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n Returns the entropy of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.binomial.entropy( 100, 0.1 )\n ~2.511\n > v = base.dists.binomial.entropy( 20, 0.5 )\n ~2.223\n > v = base.dists.binomial.entropy( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.entropy( 20, 1.1 )\n NaN\n > v = base.dists.binomial.entropy( 20, NaN )\n NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n Returns the excess kurtosis of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n ~0.051\n > v = base.dists.binomial.kurtosis( 20, 0.5 )\n ~-0.1\n > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, 1.1 )\n NaN\n > v = base.dists.binomial.kurtosis( 20, NaN )\n NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n ~-1.583\n > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n -Infinity\n > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n ~-1.606\n > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n ~-5.108\n > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.144\n > y = mylogpmf( 5.0 )\n ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n Returns the expected value of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.binomial.mean( 100, 0.1 )\n 10.0\n > v = base.dists.binomial.mean( 20, 0.5 )\n 10.0\n > v = base.dists.binomial.mean( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mean( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mean( 20, NaN )\n NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n Returns the median of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.binomial.median( 100, 0.1 )\n 10\n > v = base.dists.binomial.median( 20, 0.5 )\n 10\n > v = base.dists.binomial.median( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.median( 20, 1.1 )\n NaN\n > v = base.dists.binomial.median( 20, NaN )\n NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n ~11.471\n > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n ~4.798e+29\n > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n ~99.338\n > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n 1.0\n\n > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n NaN\n\n > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n > var y = myMGF( 0.3 )\n ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n Returns the mode of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.binomial.mode( 100, 0.1 )\n 10\n > v = base.dists.binomial.mode( 20, 0.5 )\n 10\n > v = base.dists.binomial.mode( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.mode( 20, 1.1 )\n NaN\n > v = base.dists.binomial.mode( 20, NaN )\n NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n ~0.205\n > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n 0.0\n > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n ~0.201\n > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n ~0.006\n > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n > var y = mypmf( 3.0 )\n ~0.117\n > y = mypmf( 5.0 )\n ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n 3\n > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n 5\n > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n 4\n > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n 0\n > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n 10\n\n > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n\n > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n NaN\n > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n > var y = myquantile( 0.1 )\n 3\n > y = myquantile( 0.9 )\n 7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n Returns the skewness of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.binomial.skewness( 100, 0.1 )\n ~0.267\n > v = base.dists.binomial.skewness( 20, 0.5 )\n 0.0\n > v = base.dists.binomial.skewness( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.skewness( 20, 1.1 )\n NaN\n > v = base.dists.binomial.skewness( 20, NaN )\n NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n Returns the standard deviation of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.binomial.stdev( 100, 0.1 )\n 3.0\n > v = base.dists.binomial.stdev( 20, 0.5 )\n ~2.236\n > v = base.dists.binomial.stdev( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.stdev( 20, 1.1 )\n NaN\n > v = base.dists.binomial.stdev( 20, NaN )\n NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n Returns the variance of a binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a number of trials `n` which is not a nonnegative integer, the\n function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.binomial.variance( 100, 0.1 )\n 9\n > v = base.dists.binomial.variance( 20, 0.5 )\n 5\n > v = base.dists.binomial.variance( 10.3, 0.5 )\n NaN\n > v = base.dists.binomial.variance( 20, 1.1 )\n NaN\n > v = base.dists.binomial.variance( 20, NaN )\n NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n Returns a Cauchy distribution object.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter. Default: `0.0`.\n\n Ɣ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cauchy: Object\n Distribution instance.\n\n cauchy.x0: number\n Location parameter.\n\n cauchy.gamma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cauchy.entropy: number\n Read-only property which returns the differential entropy.\n\n cauchy.median: number\n Read-only property which returns the median.\n\n cauchy.mode: number\n Read-only property which returns the mode.\n\n cauchy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cauchy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cauchy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cauchy.pdf: Function\n Evaluates the probability density function (PDF).\n\n cauchy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n > cauchy.x0\n 0.0\n > cauchy.gamma\n 1.0\n > cauchy.entropy\n ~2.531\n > cauchy.median\n 0.0\n > cauchy.mode\n 0.0\n > cauchy.cdf( 0.8 )\n ~0.715\n > cauchy.logcdf( 1.0 )\n ~-0.288\n > cauchy.logpdf( 1.0 )\n ~-1.838\n > cauchy.pdf( 1.0 )\n ~0.159\n > cauchy.quantile( 0.8 )\n ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n ~0.852\n > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n ~0.648\n > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n 0.25\n > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n > var y = myCDF( 1.0 )\n ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n Returns the differential entropy of a Cauchy distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n ~4.477\n > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n ~1.838\n > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n ~-0.16\n > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n ~-0.435\n > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n ~-1.386\n > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n NaN\n > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of CDF.\n\n Examples\n --------\n > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n > var y = mylogCDF( 1.0 )\n ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Natural logarithm of PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n ~-1.838\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n ~-3.457\n > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n ~-2.349\n > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n Returns the median of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.cauchy.median( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.median( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.median( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n Returns the mode of a Cauchy distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n 10.0\n > v = base.dists.cauchy.mode( 7.0, 0.5 )\n 7.0\n > v = base.dists.cauchy.mode( 10.3, -0.5 )\n NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n ~0.159\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n ~0.0315\n > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n ~0.095\n > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n ~0.547\n > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n ~12.753\n > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n ~3.845\n\n > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chi.cdf( 2.0, 3.0 )\n ~0.739\n > y = base.dists.chi.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chi.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chi.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chi.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chi.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chi.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.954\n > y = mycdf( 1.2 )\n ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n Returns a chi distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chi: Object\n Distribution instance.\n\n chi.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chi.entropy: number\n Read-only property which returns the differential entropy.\n\n chi.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chi.mean: number\n Read-only property which returns the expected value.\n\n chi.mode: number\n Read-only property which returns the mode.\n\n chi.skewness: number\n Read-only property which returns the skewness.\n\n chi.stdev: number\n Read-only property which returns the standard deviation.\n\n chi.variance: number\n Read-only property which returns the variance.\n\n chi.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chi.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n chi.pdf: Function\n Evaluates the probability density function (PDF).\n\n chi.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chi = base.dists.chi.Chi( 6.0 );\n > chi.k\n 6.0\n > chi.entropy\n ~1.04\n > chi.kurtosis\n ~0.025\n > chi.mean\n ~2.35\n > chi.mode\n ~2.236\n > chi.skewness\n ~0.318\n > chi.stdev\n ~0.691\n > chi.variance\n ~0.478\n > chi.cdf( 1.0 )\n ~0.014\n > chi.logpdf( 1.5 )\n ~-1.177\n > chi.pdf( 1.5 )\n ~0.308\n > chi.quantile( 0.5 )\n ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n Returns the differential entropy of a chi distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chi.entropy( 11.0 )\n ~1.056\n > v = base.dists.chi.entropy( 1.5 )\n ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n Returns the excess kurtosis of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chi.kurtosis( 9.0 )\n ~0.011\n > v = base.dists.chi.kurtosis( 1.5 )\n ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n ~-4.35\n > y = base.dists.chi.logpdf( 0.7, 0.7 )\n ~-0.622\n > y = base.dists.chi.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n > var y = mylogPDF( 3.0 )\n ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n Returns the expected value of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chi.mean( 11.0 )\n ~3.242\n > v = base.dists.chi.mean( 4.5 )\n ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n Returns the mode of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 1`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chi.mode( 11.0 )\n ~3.162\n > v = base.dists.chi.mode( 1.5 )\n ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chi.pdf( 0.3, 4.0 )\n ~0.013\n > y = base.dists.chi.pdf( 0.7, 0.7 )\n ~0.537\n > y = base.dists.chi.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chi.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chi.quantile( 0.8, 1.0 )\n ~1.282\n > y = base.dists.chi.quantile( 0.5, 4.0 )\n ~1.832\n > y = base.dists.chi.quantile( 0.8, 0.1 )\n ~0.116\n > y = base.dists.chi.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chi.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chi.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chi.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chi.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chi.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chi.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.845\n > y = myquantile( 0.7 )\n ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n Returns the skewness of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chi.skewness( 11.0 )\n ~0.225\n > v = base.dists.chi.skewness( 1.5 )\n ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n Returns the standard deviation of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chi.stdev( 11.0 )\n ~0.699\n > v = base.dists.chi.stdev( 1.5 )\n ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n Returns the variance of a chi distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chi.variance( 11.0 )\n ~0.488\n > v = base.dists.chi.variance( 1.5 )\n ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n ~0.428\n > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n ~0.846\n > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.chisquare.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.cdf( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n 1.0\n > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n 0.0\n\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n > var y = mycdf( 2.0 )\n ~0.843\n > y = mycdf( 1.2 )\n ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n Returns a chi-squared distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n chisquare: Object\n Distribution instance.\n\n chisquare.k: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n chisquare.entropy: number\n Read-only property which returns the differential entropy.\n\n chisquare.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n chisquare.mean: number\n Read-only property which returns the expected value.\n\n chisquare.median: number\n Read-only property which returns the median.\n\n chisquare.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n chisquare.mode: number\n Read-only property which returns the mode.\n\n chisquare.skewness: number\n Read-only property which returns the skewness.\n\n chisquare.stdev: number\n Read-only property which returns the standard deviation.\n\n chisquare.variance: number\n Read-only property which returns the variance.\n\n chisquare.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n chisquare.pdf: Function\n Evaluates the probability density function (PDF).\n\n chisquare.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n > chisquare.k\n 6.0\n > chisquare.entropy\n ~2.541\n > chisquare.kurtosis\n 2.0\n > chisquare.mean\n 6.0\n > chisquare.median\n ~5.348\n > chisquare.mode\n 4.0\n > chisquare.skewness\n ~1.155\n > chisquare.stdev\n ~3.464\n > chisquare.variance\n 12.0\n > chisquare.cdf( 3.0 )\n ~0.191\n > chisquare.mgf( 0.2 )\n ~4.63\n > chisquare.pdf( 1.5 )\n ~0.066\n > chisquare.quantile( 0.5 )\n ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n Returns the differential entropy of a chi-squared distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.chisquare.entropy( 11.0 )\n ~2.901\n > v = base.dists.chisquare.entropy( 1.5 )\n ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n Returns the excess kurtosis of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.chisquare.kurtosis( 9.0 )\n ~1.333\n > v = base.dists.chisquare.kurtosis( 1.5 )\n 8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n ~-2.74\n > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n ~-1.295\n > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n > var y = myLogPDF( 3.0 )\n ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n Returns the expected value of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.chisquare.mean( 11.0 )\n 11.0\n > v = base.dists.chisquare.mean( 4.5 )\n 4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n Returns the median of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var k = base.dists.chisquare.median( 9.0 )\n ~8.343\n > k = base.dists.chisquare.median( 2.0 )\n ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.chisquare.mgf( 0.4, 2 )\n ~5.0\n > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n ~0.0642\n > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n 1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n > var y = mymgf( 0.2 )\n ~1.291\n > y = mymgf( 0.4 )\n ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n Returns the mode of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.chisquare.mode( 11.0 )\n 9.0\n > v = base.dists.chisquare.mode( 1.5 )\n 0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n ~0.065\n > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n ~0.274\n > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, NaN )\n NaN\n > y = base.dists.chisquare.pdf( NaN, 2.0 )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n > var y = myPDF( 3.0 )\n ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n ~1.642\n > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n ~3.357\n > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n ~0.014\n > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n NaN\n > y = base.dists.chisquare.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.chisquare.quantile( 0.0, NaN )\n NaN\n\n // Negative degrees of freedom:\n > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n NaN\n\n // Degenerate distribution when `k = 0`:\n > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n 0.0\n > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n > var y = myquantile( 0.3 )\n ~0.713\n > y = myquantile( 0.7 )\n ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n Returns the skewness of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.chisquare.skewness( 11.0 )\n ~0.853\n > v = base.dists.chisquare.skewness( 1.5 )\n ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n Returns the standard deviation of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.chisquare.stdev( 11.0 )\n ~4.69\n > v = base.dists.chisquare.stdev( 1.5 )\n ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n Returns the variance of a chi-squared distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `k < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.chisquare.variance( 11.0 )\n 22.0\n > v = base.dists.chisquare.variance( 1.5 )\n 3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n ~0.971\n > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n ~0.196\n\n > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.9 )\n ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n Returns a raised cosine distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n cosine: Object\n Distribution instance.\n\n cosine.mu: number\n Location parameter.\n\n cosine.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n cosine.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n cosine.mean: number\n Read-only property which returns the expected value.\n\n cosine.median: number\n Read-only property which returns the median.\n\n cosine.mode: number\n Read-only property which returns the mode.\n\n cosine.skewness: number\n Read-only property which returns the skewness.\n\n cosine.stdev: number\n Read-only property which returns the standard deviation.\n\n cosine.variance: number\n Read-only property which returns the variance.\n\n cosine.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n cosine.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n cosine.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n cosine.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n cosine.pdf: Function\n Evaluates the probability density function (PDF).\n\n cosine.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n > cosine.mu\n -2.0\n > cosine.s\n 3.0\n > cosine.kurtosis\n ~-0.594\n > cosine.mean\n -2.0\n > cosine.median\n -2.0\n > cosine.mode\n -2.0\n > cosine.skewness\n 0.0\n > cosine.stdev\n ~1.085\n > cosine.variance\n ~1.176\n > cosine.cdf( 0.5 )\n ~0.996\n > cosine.logcdf( 0.5 )\n ~-0.004\n > cosine.logpdf( -1.0 )\n ~-1.386\n > cosine.mgf( 0.2 )\n ~0.686\n > cosine.pdf( -2.0 )\n ~0.333\n > cosine.quantile( 0.9 )\n ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n ~-0.594\n > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n ~-0.029\n > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n ~-1.632\n\n > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.9 )\n ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n ~-2.485\n > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n ~-3.307\n > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.cosine.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mean( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mean( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.cosine.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.median( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.median( 0.0, NaN )\n NaN\n > y = base.dists.cosine.median( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n ~7.234\n > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n ~1.606e+47\n\n > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n NaN\n > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n > var y = mymgf( 1.9 )\n ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.cosine.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.cosine.mode( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.mode( 0.0, NaN )\n NaN\n > y = base.dists.cosine.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n ~0.083\n > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n ~0.048\n > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n > var y = myPDF( 2.0 )\n ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n ~0.327\n > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n ~4.0\n\n > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.3 )\n ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.cosine.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.cosine.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.skewness( 0.0, NaN )\n NaN\n > y = base.dists.cosine.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n ~0.362\n > y = base.dists.cosine.stdev( 4.0, 2.0 )\n ~0.723\n > y = base.dists.cosine.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.stdev( 0.0, NaN )\n NaN\n > y = base.dists.cosine.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.cosine.variance( 0.0, 1.0 )\n ~0.131\n > y = base.dists.cosine.variance( 4.0, 2.0 )\n ~0.523\n > y = base.dists.cosine.variance( NaN, 1.0 )\n NaN\n > y = base.dists.cosine.variance( 0.0, NaN )\n NaN\n > y = base.dists.cosine.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.cdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n > var y = myCDF( 3.0 )\n 0.0\n > y = myCDF( 6.0 )\n 1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n Returns a degenerate distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Constant value of distribution.\n\n Returns\n -------\n degenerate: Object\n Distribution instance.\n\n degenerate.mu: number\n Constant value of distribution.\n\n degenerate.entropy: number\n Read-only property which returns the differential entropy.\n\n degenerate.mean: number\n Read-only property which returns the expected value.\n\n degenerate.median: number\n Read-only property which returns the median.\n\n degenerate.stdev: number\n Read-only property which returns the standard deviation.\n\n degenerate.variance: number\n Read-only property which returns the variance.\n\n degenerate.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n degenerate.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n degenerate.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n degenerate.logpmf: Function\n Evaluates the natural logarithm of the probability mass function\n (PMF).\n\n degenerate.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n degenerate.pmf: Function\n Evaluates the probability mass function (PMF).\n\n degenerate.pdf: Function\n Evaluates the probability density function (PDF).\n\n degenerate.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n > degenerate.mu\n 2.0\n > degenerate.entropy\n 0.0\n > degenerate.mean\n 2.0\n > degenerate.mode\n 2.0\n > degenerate.median\n 2.0\n > degenerate.stdev\n 0.0\n > degenerate.variance\n 0.0\n > degenerate.cdf( 0.5 )\n 0.0\n > degenerate.logcdf( 2.5 )\n 0.0\n > degenerate.logpdf( 0.5 )\n -Infinity\n > degenerate.logpmf( 2.5 )\n -Infinity\n > degenerate.mgf( 0.2 )\n ~1.492\n > degenerate.pdf( 2.0 )\n +Infinity\n > degenerate.pmf( 2.0 )\n 1.0\n > degenerate.quantile( 0.7 )\n 2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.degenerate.entropy( 20.0 )\n 0.0\n > v = base.dists.degenerate.entropy( -10.0 )\n 0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the CDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n 0\n > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logcdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logcdf: Function\n Function to evaluate the natural logarithm of cumulative distribution\n function (logCDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n > var y = mylogcdf( 3.0 )\n -Infinity\n > y = mylogcdf( 6.0 )\n 0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Natural logarithm of the PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpdf: Function\n Function to evaluate the natural logarithm of the PDF.\n\n Examples\n --------\n > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n > var y = mylogPDF( 10.0 )\n Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n -Infinity\n > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.logpmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n > var y = mylogPMF( 10.0 )\n 0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.degenerate.mean( 20.0 )\n 20.0\n > v = base.dists.degenerate.mean( -10.0 )\n -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n Returns the median of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.degenerate.median( 20.0 )\n 20.0\n > v = base.dists.degenerate.median( -10.0 )\n -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n ~2.718\n > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n ~403.429\n > y = base.dists.degenerate.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.mgf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n > var y = myMGF( 0.1 )\n ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n Returns the mode of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.degenerate.mode( 20.0 )\n 20.0\n > v = base.dists.degenerate.mode( -10.0 )\n -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n Infinity\n > y = base.dists.degenerate.pdf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n > var y = myPDF( 10.0 )\n Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n 0.0\n > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n 1.0\n > y = base.dists.degenerate.pmf( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.pmf( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n > var y = myPMF( 10.0 )\n 1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n 2.0\n > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n 4.0\n > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( NaN, 0.0 )\n NaN\n > y = base.dists.degenerate.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.degenerate.stdev( 20.0 )\n 0.0\n > v = base.dists.degenerate.stdev( -10.0 )\n 0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n Returns the variance of a degenerate distribution with constant value `μ`.\n\n Parameters\n ----------\n μ: number\n Constant value of distribution.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.degenerate.variance( 20.0 )\n 0.0\n > v = base.dists.degenerate.variance( -10.0 )\n 0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n ~0.909\n > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n ~0.333\n > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n 1.0\n > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n > var y = mycdf( 0.5 )\n ~0.091\n > y = mycdf( 8.0 )\n ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n Returns a discrete uniform distribution object.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n b: integer (optional)\n Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n Returns\n -------\n discreteUniform: Object\n Distribution instance.\n\n discreteUniform.a: integer\n Minimum support. If set, the value must be an integer smaller than or\n equal to `b`.\n\n discreteUniform.b: integer\n Maximum support. If set, the value must be an integer greater than or\n equal to `a`.\n\n discreteUniform.entropy: number\n Read-only property which returns the entropy.\n\n discreteUniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n discreteUniform.mean: number\n Read-only property which returns the expected value.\n\n discreteUniform.median: number\n Read-only property which returns the median.\n\n discreteUniform.skewness: number\n Read-only property which returns the skewness.\n\n discreteUniform.stdev: number\n Read-only property which returns the standard deviation.\n\n discreteUniform.variance: number\n Read-only property which returns the variance.\n\n discreteUniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n discreteUniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n discreteUniform.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n discreteUniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n discreteUniform.pmf: Function\n Evaluates the probability mass function (PMF).\n\n discreteUniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n > discreteUniform.a\n -2\n > discreteUniform.b\n 2\n > discreteUniform.entropy\n ~1.609\n > discreteUniform.kurtosis\n -1.3\n > discreteUniform.mean\n 0.0\n > discreteUniform.median\n 0.0\n > discreteUniform.skewness\n 0.0\n > discreteUniform.stdev\n ~1.414\n > discreteUniform.variance\n 2.0\n > discreteUniform.cdf( 0.8 )\n 0.6\n > discreteUniform.logcdf( 0.5 )\n ~-0.511\n > discreteUniform.logpmf( 1.0 )\n ~-1.609\n > discreteUniform.mgf( 0.8 )\n ~1.766\n > discreteUniform.pmf( 0.0 )\n 0.2\n > discreteUniform.quantile( 0.8 )\n 2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n Returns the entropy of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.entropy( 0, 1 )\n ~0.693\n > v = base.dists.discreteUniform.entropy( 4, 12 )\n ~2.197\n > v = base.dists.discreteUniform.entropy( 2, 8 )\n ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n Returns the excess kurtosis of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n -2.0\n > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n ~-1.23\n > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n ~-0.095\n > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n ~-1.099\n > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n 0.0\n > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n > var y = myLogCDF( 0.5 )\n ~-2.398\n > y = myLogCDF( 8.0 )\n ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n ~-1.609\n > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n -Infinity\n > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n ~-2.197\n > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n > var y = myLogPMF( 7.0 )\n ~-0.693\n > y = myLogPMF( 5.0 )\n -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n Returns the expected value of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.mean( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.mean( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.mean( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n Returns the median of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.median( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.median( 4, 12 )\n 8.0\n > v = base.dists.discreteUniform.median( 2, 8 )\n 5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n ~689.475\n > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n ~0.697\n > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n ~4.195\n > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n NaN\n > y = base.dists.discreteUniform.mgf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n > var y = mymgf( 0.1 )\n ~1.918\n > y = mymgf( 1.1 )\n ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n ~0.2\n > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n 0.0\n > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n ~0.111\n > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n NaN\n > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n > var y = myPMF( 7.0 )\n 0.5\n > y = myPMF( 5.0 )\n 0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n If provided `a > b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n 1\n > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n 5\n\n > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n NaN\n > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n NaN\n\n > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n NaN\n > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n NaN\n\n > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n > var y = myQuantile( 0.8 )\n 4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n Returns the skewness of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.skewness( -2, 2 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 4, 12 )\n 0.0\n > v = base.dists.discreteUniform.skewness( 2, 8 )\n 0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n Returns the standard deviation of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.stdev( 0, 1 )\n ~0.5\n > v = base.dists.discreteUniform.stdev( 4, 12 )\n ~2.582\n > v = base.dists.discreteUniform.stdev( 2, 8 )\n 2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n Returns the variance of a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.discreteUniform.variance( 0, 1 )\n ~0.25\n > v = base.dists.discreteUniform.variance( 4, 12 )\n ~6.667\n > v = base.dists.discreteUniform.variance( 2, 8 )\n 4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n ~0.865\n > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n ~0.323\n > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n 1.0\n > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n NaN\n > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n NaN\n > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n > var y = mycdf( 6.0 )\n ~0.801\n > y = mycdf( 2.0 )\n ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n Returns the differential entropy of an Erlang distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.erlang.entropy( 1, 1.0 )\n ~1.0\n > v = base.dists.erlang.entropy( 4, 12.0 )\n ~-0.462\n > v = base.dists.erlang.entropy( 8, 2.0 )\n ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n Returns an Erlang distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be a positive integer. Default: `1.0`.\n\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n erlang: Object\n Distribution instance.\n\n erlang.k: number\n Shape parameter. If set, the value must be a positive integer.\n\n erlang.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n erlang.entropy: number\n Read-only property which returns the differential entropy.\n\n erlang.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n erlang.mean: number\n Read-only property which returns the expected value.\n\n erlang.mode: number\n Read-only property which returns the mode.\n\n erlang.skewness: number\n Read-only property which returns the skewness.\n\n erlang.stdev: number\n Read-only property which returns the standard deviation.\n\n erlang.variance: number\n Read-only property which returns the variance.\n\n erlang.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n erlang.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n erlang.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n erlang.pdf: Function\n Evaluates the probability density function (PDF).\n\n erlang.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n > erlang.k\n 6\n > erlang.lambda\n 5.0\n > erlang.entropy\n ~0.647\n > erlang.kurtosis\n 1.0\n > erlang.mean\n 1.2\n > erlang.mode\n 1.0\n > erlang.skewness\n ~0.816\n > erlang.stdev\n ~0.49\n > erlang.variance\n 0.24\n > erlang.cdf( 3.0 )\n ~0.997\n > erlang.logpdf( 3.0 )\n ~-4.638\n > erlang.mgf( -0.5 )\n ~0.564\n > erlang.pdf( 3.0 )\n ~0.01\n > erlang.quantile( 0.8 )\n ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n Returns the excess kurtosis of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n 6.0\n > v = base.dists.erlang.kurtosis( 4, 12.0 )\n 1.5\n > v = base.dists.erlang.kurtosis( 8, 2.0 )\n 0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n ~-0.1\n > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n ~-0.111\n > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n > y = myLogPDF( 7.0 )\n ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n Returns the expected value of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.erlang.mean( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.mean( 4, 12.0 )\n ~0.333\n > v = base.dists.erlang.mean( 8, 2.0 )\n 4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n ~1.429\n > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n ~9.0\n > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n ~0.444\n\n > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n NaN\n\n > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n NaN\n > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n > var y = myMGF( 0.2 )\n ~2.778\n > y = myMGF( -0.5 )\n 0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n Returns the mode of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.erlang.mode( 1, 1.0 )\n 0.0\n > v = base.dists.erlang.mode( 4, 12.0 )\n 0.25\n > v = base.dists.erlang.mode( 8, 2.0 )\n 3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n ~0.905\n > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n ~0.895\n > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n NaN\n > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n Infinity\n > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n NaN\n > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n > y = myPDF( 7.0 )\n ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n If provided a non-positive number for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n ~2.994\n > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n ~1.836\n\n > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n NaN\n\n > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n NaN\n\n // Non-integer shape parameter:\n > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n NaN\n // Non-positive shape parameter:\n > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n > var y = myQuantile( 0.4 )\n ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n Returns the skewness of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.erlang.skewness( 1, 1.0 )\n 2.0\n > v = base.dists.erlang.skewness( 4, 12.0 )\n 1.0\n > v = base.dists.erlang.skewness( 8, 2.0 )\n ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n Returns the standard deviation of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.erlang.stdev( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.stdev( 4, 12.0 )\n ~0.167\n > v = base.dists.erlang.stdev( 8, 2.0 )\n ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n Returns the variance of an Erlang distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `k`, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.erlang.variance( 1, 1.0 )\n 1.0\n > v = base.dists.erlang.variance( 4, 12.0 )\n ~0.028\n > v = base.dists.erlang.variance( 8, 2.0 )\n 2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n ~0.181\n > y = base.dists.exponential.cdf( 1.0, 2.0 )\n ~0.865\n > y = base.dists.exponential.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.exponential.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.cdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.cdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n > var y = myCDF( 3.0 )\n ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n Returns the differential entropy of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.exponential.entropy( 11.0 )\n ~-1.398\n > v = base.dists.exponential.entropy( 4.5 )\n ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n Returns an exponential distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n exponential: Object\n Distribution instance.\n\n exponential.lambda: number\n Rate parameter. If set, the value must be greater than `0`.\n\n exponential.entropy: number\n Read-only property which returns the differential entropy.\n\n exponential.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n exponential.mean: number\n Read-only property which returns the expected value.\n\n exponential.median: number\n Read-only property which returns the median.\n\n exponential.mode: number\n Read-only property which returns the mode.\n\n exponential.skewness: number\n Read-only property which returns the skewness.\n\n exponential.stdev: number\n Read-only property which returns the standard deviation.\n\n exponential.variance: number\n Read-only property which returns the variance.\n\n exponential.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n exponential.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n exponential.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n exponential.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n exponential.pdf: Function\n Evaluates the probability density function (PDF).\n\n exponential.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var exponential = base.dists.exponential.Exponential( 6.0 );\n > exponential.lambda\n 6.0\n > exponential.entropy\n ~-0.792\n > exponential.kurtosis\n 6.0\n > exponential.mean\n ~0.167\n > exponential.median\n ~0.116\n > exponential.mode\n 0.0\n > exponential.skewness\n 2.0\n > exponential.stdev\n ~0.167\n > exponential.variance\n ~0.028\n > exponential.cdf( 1.0 )\n ~0.998\n > exponential.logcdf( 1.0 )\n ~-0.002\n > exponential.logpdf( 1.5 )\n ~-7.208\n > exponential.mgf( -0.5 )\n ~0.923\n > exponential.pdf( 1.5 )\n ~0.001\n > exponential.quantile( 0.5 )\n ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n Returns the excess kurtosis of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.exponential.kurtosis( 11.0 )\n 6.0\n > v = base.dists.exponential.kurtosis( 4.5 )\n 6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n ~-1.708\n > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n ~-0.145\n > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.exponential.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.logcdf( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n > var y = mylogCDF( 3.0 )\n ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n ~0.186\n > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n ~-1.757\n > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.exponential.logpdf( 0, NaN )\n NaN\n > y = base.dists.exponential.logpdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n > var y = mylogpdf( 3.0 )\n ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n Returns the expected value of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.exponential.mean( 11.0 )\n ~0.091\n > v = base.dists.exponential.mean( 4.5 )\n ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n Returns the median of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.exponential.median( 11.0 )\n ~0.063\n > v = base.dists.exponential.median( 4.5 )\n ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n 3.0\n > v = base.dists.exponential.mgf( 0.4, 1.2 )\n 1.5\n > v = base.dists.exponential.mgf( 0.8, 1.6 )\n 2.0\n > v = base.dists.exponential.mgf( 4.0, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( NaN, 3.0 )\n NaN\n > v = base.dists.exponential.mgf( 2.0, NaN )\n NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n mg: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n > var y = myMGF( 3.0 )\n 4.0\n > y = myMGF( 0.5 )\n ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n Returns the mode of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.exponential.mode( 11.0 )\n 0.0\n > v = base.dists.exponential.mode( 4.5 )\n 0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n ~1.205\n > y = base.dists.exponential.pdf( 2.0, 0.7 )\n ~0.173\n > y = base.dists.exponential.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.exponential.pdf( 0, NaN )\n NaN\n > y = base.dists.exponential.pdf( NaN, 2.0 )\n NaN\n\n // Negative rate:\n > y = base.dists.exponential.pdf( 2.0, -1.0 )\n NaN\n\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n > var y = myPDF( 3.0 )\n ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n ~1.609\n > y = base.dists.exponential.quantile( 0.5, 4.0 )\n ~0.173\n > y = base.dists.exponential.quantile( 0.5, 0.1 )\n ~6.931\n\n > y = base.dists.exponential.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.exponential.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.exponential.quantile( 0.0, NaN )\n NaN\n\n // Negative rate parameter:\n > y = base.dists.exponential.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~1.277\n > y = myQuantile( 1.0 )\n Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n Returns the skewness of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.exponential.skewness( 11.0 )\n 2.0\n > v = base.dists.exponential.skewness( 4.5 )\n 2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n Returns the standard deviation of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.exponential.stdev( 9.0 )\n ~0.11\n > v = base.dists.exponential.stdev( 1.0 )\n 1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n Returns the variance of an exponential distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.exponential.variance( 9.0 )\n ~0.012\n > v = base.dists.exponential.variance( 1.0 )\n 1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n ~0.608\n > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n ~0.737\n > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n 1.0\n > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n NaN\n > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n NaN\n\n > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n NaN\n > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n ~0.906\n > y = myCDF( 8.0 )\n ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n Returns the differential entropy of an F distribution (in nats).\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.f.entropy( 3.0, 7.0 )\n ~1.298\n > v = base.dists.f.entropy( 4.0, 12.0 )\n ~1.12\n > v = base.dists.f.entropy( 8.0, 2.0 )\n ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n Returns an F distribution object.\n\n Parameters\n ----------\n d1: number (optional)\n Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n d2: number (optional)\n Denominator degrees of freedom. Must be greater than `0`.\n Default: `1.0`.\n\n Returns\n -------\n f: Object\n Distribution instance.\n\n f.d1: number\n Numerator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.d2: number\n Denominator degrees of freedom. If set, the value must be greater than\n `0`.\n\n f.entropy: number\n Read-only property which returns the differential entropy.\n\n f.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n f.mean: number\n Read-only property which returns the expected value.\n\n f.mode: number\n Read-only property which returns the mode.\n\n f.skewness: number\n Read-only property which returns the skewness.\n\n f.stdev: number\n Read-only property which returns the standard deviation.\n\n f.variance: number\n Read-only property which returns the variance.\n\n f.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n f.pdf: Function\n Evaluates the probability density function (PDF).\n\n f.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var f = base.dists.f.F( 6.0, 9.0 );\n > f.d1\n 6.0\n > f.d2\n 9.0\n > f.entropy\n ~1.134\n > f.kurtosis\n ~104.564\n > f.mean\n ~1.286\n > f.mode\n ~0.545\n > f.skewness\n ~4.535\n > f.stdev\n ~1.197\n > f.variance\n ~1.433\n > f.cdf( 3.0 )\n ~0.932\n > f.pdf( 2.5 )\n ~0.095\n > f.quantile( 0.8 )\n ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n Returns the excess kurtosis of an F distribution.\n\n If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n ~124.667\n > v = base.dists.f.kurtosis( 4.0, 12.0 )\n ~26.143\n > v = base.dists.f.kurtosis( 8.0, 9.0 )\n ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n Returns the expected value of an F distribution.\n\n If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.f.mean( 3.0, 5.0 )\n ~1.667\n > v = base.dists.f.mean( 4.0, 12.0 )\n ~1.2\n > v = base.dists.f.mean( 8.0, 4.0 )\n 2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n Returns the mode of an F distribution.\n\n If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.f.mode( 3.0, 5.0 )\n ~0.238\n > v = base.dists.f.mode( 4.0, 12.0 )\n ~0.429\n > v = base.dists.f.mode( 8.0, 4.0 )\n 0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n ~0.057\n > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n ~0.915\n > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n NaN\n > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n ~0.004\n > y = myPDF( 2.0 )\n ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n ~9.472\n > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n ~1.207\n\n > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~0.527\n > y = myQuantile( 0.8 )\n ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n Returns the skewness of an F distribution.\n\n If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.f.skewness( 3.0, 7.0 )\n 11.0\n > v = base.dists.f.skewness( 4.0, 12.0 )\n ~3.207\n > v = base.dists.f.skewness( 8.0, 7.0 )\n ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n Returns the standard deviation of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.f.stdev( 3.0, 5.0 )\n ~3.333\n > v = base.dists.f.stdev( 4.0, 12.0 )\n ~1.122\n > v = base.dists.f.stdev( 8.0, 5.0 )\n ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n Returns the variance of an F distribution.\n\n If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Numerator degrees of freedom.\n\n d2: number\n Denominator degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.f.variance( 3.0, 5.0 )\n ~11.111\n > v = base.dists.f.variance( 4.0, 12.0 )\n ~1.26\n > v = base.dists.f.variance( 8.0, 5.0 )\n ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n ~0.914\n > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n ~0.105\n > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n ~0.018\n > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n > var y = myCDF( 10.0 )\n ~0.806\n > y = myCDF( 7.0 )\n ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n ~2.154\n > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n ~1.028\n > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n Returns a Fréchet distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n m: number (optional)\n Location parameter. Default: `0.0`.\n\n Returns\n -------\n frechet: Object\n Distribution instance.\n\n frechet.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n frechet.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n frechet.m: number\n Location parameter.\n\n frechet.entropy: number\n Read-only property which returns the differential entropy.\n\n frechet.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n frechet.mean: number\n Read-only property which returns the expected value.\n\n frechet.median: number\n Read-only property which returns the median.\n\n frechet.mode: number\n Read-only property which returns the mode.\n\n frechet.skewness: number\n Read-only property which returns the skewness.\n\n frechet.stdev: number\n Read-only property which returns the standard deviation.\n\n frechet.variance: number\n Read-only property which returns the variance.\n\n frechet.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n frechet.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n frechet.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n frechet.pdf: Function\n Evaluates the probability density function (PDF).\n\n frechet.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n > frechet.alpha\n 1.0\n > frechet.s\n 1.0\n > frechet.m\n 0.0\n > frechet.entropy\n ~2.154\n > frechet.kurtosis\n Infinity\n > frechet.mean\n Infinity\n > frechet.median\n ~1.443\n > frechet.mode\n 0.5\n > frechet.skewness\n Infinity\n > frechet.stdev\n Infinity\n > frechet.variance\n Infinity\n > frechet.cdf( 0.8 )\n ~0.287\n > frechet.logcdf( 0.8 )\n -1.25\n > frechet.logpdf( 0.8 )\n ~-0.804\n > frechet.pdf( 0.8 )\n ~0.448\n > frechet.quantile( 0.8 )\n ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 4` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n ~45.092\n > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n ~45.092\n > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n ~-0.09\n > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n ~-2.25\n > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n -4.0\n > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.216\n > y = mylogcdf( 7.0 )\n ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Fréchet distribution with shape parameter `α`, scale parameter `s`,\n and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n ~-2.72\n > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n ~-1.901\n > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n ~-0.307\n > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n > var y = mylogPDF( 10.0 )\n ~-3.812\n > y = mylogPDF( 2.0 )\n ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 1` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n ~3.451\n > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n ~3.192\n > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n ~-0.808\n > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n ~5.163\n > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n ~2.891\n > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n ~-1.109\n > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n ~1.222\n > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n > var y = myPDF( 10.0 )\n ~0.933\n > y = myPDF( 2.0 )\n ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n ~4.963\n > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n ~5.56\n > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n ~6.491\n > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n NaN\n > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~5.402\n > y = myQuantile( 0.2 )\n ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 3` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n ~5.605\n > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n ~5.605\n > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n ~1.041\n > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n ~1.041\n > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n\n If provided `0 < α <= 2` and `s > 0`, the function returns positive\n infinity.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n ~1.083\n > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n ~1.083\n > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n Infinity\n > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n NaN\n > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n ~0.323\n > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0` when `α = 0.0`:\n > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n 1.0\n > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 6.0 )\n ~0.801\n > y = myCDF( 2.0 )\n ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n Returns the differential entropy of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.entropy( 4.0, 12.0 )\n ~-0.462\n > v = base.dists.gamma.entropy( 8.0, 2.0 )\n ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n Returns a gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gamma: Object\n Distribution instance.\n\n gamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n gamma.beta: number\n Rate parameter. If set, the value must be greater than `0`.\n\n gamma.entropy: number\n Read-only property which returns the differential entropy.\n\n gamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gamma.mean: number\n Read-only property which returns the expected value.\n\n gamma.mode: number\n Read-only property which returns the mode.\n\n gamma.skewness: number\n Read-only property which returns the skewness.\n\n gamma.stdev: number\n Read-only property which returns the standard deviation.\n\n gamma.variance: number\n Read-only property which returns the variance.\n\n gamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gamma.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gamma.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n gamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n > gamma.alpha\n 6.0\n > gamma.beta\n 5.0\n > gamma.entropy\n ~0.647\n > gamma.kurtosis\n 1.0\n > gamma.mean\n 1.2\n > gamma.mode\n 1.0\n > gamma.skewness\n ~0.816\n > gamma.stdev\n ~0.49\n > gamma.variance\n 0.24\n > gamma.cdf( 0.8 )\n ~0.215\n > gamma.logcdf( 0.8 )\n ~-1.538\n > gamma.logpdf( 1.0 )\n ~-0.131\n > gamma.mgf( -0.5 )\n ~0.564\n > gamma.pdf( 1.0 )\n ~0.877\n > gamma.quantile( 0.8 )\n ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n Returns the excess kurtosis of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n 1.5\n > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n 0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a gamma distribution with shape parameter `α` and rate parameter\n `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n ~-0.047\n > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n ~-2.352\n > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n > var y = mylogCDF( 2.0 )\n ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a gamma distribution with shape parameter `α` and rate parameter `β` at\n a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.919\n > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n -Infinity\n > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n Returns the expected value of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.gamma.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.mean( 4.0, 12.0 )\n ~0.333\n > v = base.dists.gamma.mean( 8.0, 2.0 )\n 4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n ~1.414\n > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n ~1.111\n > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n ~0.198\n\n > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n NaN\n > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n > var y = myMGF( 1.0 )\n ~27.0\n > y = myMGF( 0.5 )\n ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n Returns the mode of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.gamma.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.gamma.mode( 4.0, 12.0 )\n 0.25\n > v = base.dists.gamma.mode( 8.0, 2.0 )\n 3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n ~0.054\n > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n ~2.994\n > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n ~1.836\n\n > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n // Non-positive rate parameter:\n > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `0.0` when `α = 0.0`:\n > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n 0.0\n > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n 0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~1.497\n > y = myQuantile( 0.4 )\n ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n Returns the skewness of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.gamma.skewness( 4.0, 12.0 )\n 1.0\n > v = base.dists.gamma.skewness( 8.0, 2.0 )\n ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n Returns the standard deviation of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.stdev( 4.0, 12.0 )\n ~0.167\n > v = base.dists.gamma.stdev( 8.0, 2.0 )\n ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n Returns the variance of a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.gamma.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.gamma.variance( 4.0, 12.0 )\n ~0.028\n > v = base.dists.gamma.variance( 8.0, 2.0 )\n 2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n 0.875\n > y = base.dists.geometric.cdf( 2.0, 0.1 )\n ~0.271\n > y = base.dists.geometric.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.geometric.cdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.cdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.cdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n 0.9375\n > y = mycdf( 1.0 )\n 0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.geometric.entropy( 0.1 )\n ~3.251\n > v = base.dists.geometric.entropy( 0.5 )\n ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n Returns a geometric distribution object.\n\n Parameters\n ----------\n p: number (optional)\n Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n Returns\n -------\n geometric: Object\n Distribution instance.\n\n geometric.p: number\n Success probability. If set, the value must be between `0` and `1`.\n\n geometric.entropy: number\n Read-only property which returns the differential entropy.\n\n geometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n geometric.mean: number\n Read-only property which returns the expected value.\n\n geometric.median: number\n Read-only property which returns the median.\n\n geometric.mode: number\n Read-only property which returns the mode.\n\n geometric.skewness: number\n Read-only property which returns the skewness.\n\n geometric.stdev: number\n Read-only property which returns the standard deviation.\n\n geometric.variance: number\n Read-only property which returns the variance.\n\n geometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n geometric.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n geometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n geometric.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n geometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n geometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var geometric = base.dists.geometric.Geometric( 0.6 );\n > geometric.p\n 0.6\n > geometric.entropy\n ~1.122\n > geometric.kurtosis\n ~6.9\n > geometric.mean\n ~0.667\n > geometric.median\n 0.0\n > geometric.mode\n 0.0\n > geometric.skewness\n ~2.214\n > geometric.stdev\n ~1.054\n > geometric.variance\n ~1.111\n > geometric.cdf( 3.0 )\n ~0.974\n > geometric.logcdf( 3.0 )\n ~-0.026\n > geometric.logpmf( 4.0 )\n ~-4.176\n > geometric.mgf( 0.5 )\n ~2.905\n > geometric.pmf( 2.0 )\n ~0.096\n > geometric.quantile( 0.7 )\n 1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.geometric.kurtosis( 0.1 )\n ~6.011\n > v = base.dists.geometric.kurtosis( 0.5 )\n 6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a geometric distribution with success probability `p` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n ~-0.134\n > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n ~-1.306\n > y = base.dists.geometric.logcdf( -1.0, 0.4 )\n -Infinity\n > y = base.dists.geometric.logcdf( NaN, 0.5 )\n NaN\n > y = base.dists.geometric.logcdf( 0.0, NaN )\n NaN\n // Invalid probability\n > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.065\n > y = mylogcdf( 1.0 )\n ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n ~-2.631\n > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n ~-2.765\n > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.geometric.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.logpmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n > var y = mylogpmf( 3.0 )\n ~-2.773\n > y = mylogpmf( 1.0 )\n ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.geometric.mean( 0.1 )\n 9.0\n > v = base.dists.geometric.mean( 0.5 )\n 1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n Returns the median of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.geometric.median( 0.1 )\n 6\n > v = base.dists.geometric.median( 0.5 )\n 0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `t >= -ln(1-p)`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n ~1.569\n > y = base.dists.geometric.mgf( 0.4, 0.5 )\n ~2.936\n // Case: t >= -ln(1-p)\n > y = base.dists.geometric.mgf( 0.8, 0.5 )\n NaN\n > y = base.dists.geometric.mgf( NaN, 0.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.mgf( -2.0, -1.0 )\n NaN\n > y = base.dists.geometric.mgf( 0.2, 2.0 )\n NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n > var y = mymgf( -0.2 )\n ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n Returns the mode of a geometric distribution with success probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.geometric.mode( 0.1 )\n 0\n > v = base.dists.geometric.mode( 0.5 )\n 0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n ~0.072\n > y = base.dists.geometric.pmf( 2.0, 0.7 )\n ~0.063\n > y = base.dists.geometric.pmf( -1.0, 0.5 )\n 0.0\n > y = base.dists.geometric.pmf( 0.0, NaN )\n NaN\n > y = base.dists.geometric.pmf( NaN, 0.5 )\n NaN\n // Invalid success probability:\n > y = base.dists.geometric.pmf( 2.0, 1.5 )\n NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n > var y = mypmf( 3.0 )\n 0.0625\n > y = mypmf( 1.0 )\n 0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n\n If `r < 0` or `r > 1`, the function returns `NaN`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Input probability.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n 3\n > y = base.dists.geometric.quantile( 0.5, 0.4 )\n 1\n > y = base.dists.geometric.quantile( 0.9, 0.1 )\n 21\n\n > y = base.dists.geometric.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.geometric.quantile( NaN, 0.8 )\n NaN\n > y = base.dists.geometric.quantile( 0.4, NaN )\n NaN\n\n > y = base.dists.geometric.quantile( 0.5, -1.0 )\n NaN\n > y = base.dists.geometric.quantile( 0.5, 1.5 )\n NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n > var y = myquantile( 0.4 )\n 0\n > y = myquantile( 0.8 )\n 3\n > y = myquantile( 1.0 )\n Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.geometric.skewness( 0.1 )\n ~2.003\n > v = base.dists.geometric.skewness( 0.5 )\n ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.geometric.stdev( 0.1 )\n ~9.487\n > v = base.dists.geometric.stdev( 0.5 )\n ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n Returns the variance of a geometric distribution with success probability\n `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.geometric.variance( 0.1 )\n ~90.0\n > v = base.dists.geometric.variance( 0.5 )\n 2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n ~0.965\n > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n ~0.143\n > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.933\n > y = myCDF( 2.0 )\n ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n ~1.577\n > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n ~2.27\n > y = base.dists.gumbel.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n Returns a Gumbel distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n gumbel: Object\n Distribution instance.\n\n gumbel.mu: number\n Location parameter.\n\n gumbel.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n gumbel.entropy: number\n Read-only property which returns the differential entropy.\n\n gumbel.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n gumbel.mean: number\n Read-only property which returns the expected value.\n\n gumbel.median: number\n Read-only property which returns the median.\n\n gumbel.mode: number\n Read-only property which returns the mode.\n\n gumbel.skewness: number\n Read-only property which returns the skewness.\n\n gumbel.stdev: number\n Read-only property which returns the standard deviation.\n\n gumbel.variance: number\n Read-only property which returns the variance.\n\n gumbel.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n gumbel.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n gumbel.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n gumbel.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n gumbel.pdf: Function\n Evaluates the probability density function (PDF).\n\n gumbel.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n > gumbel.mu\n -2.0\n > gumbel.beta\n 3.0\n > gumbel.entropy\n ~2.676\n > gumbel.kurtosis\n 2.4\n > gumbel.mean\n ~-0.268\n > gumbel.median\n ~-0.9\n > gumbel.mode\n -2.0\n > gumbel.skewness\n ~1.14\n > gumbel.stdev\n ~3.848\n > gumbel.variance\n ~14.804\n > gumbel.cdf( 0.8 )\n ~0.675\n > gumbel.logcdf( 0.8 )\n ~-0.393\n > gumbel.logpdf( 1.0 )\n ~-2.466\n > gumbel.mgf( 0.2 )\n ~1.487\n > gumbel.pdf( 1.0 )\n ~0.085\n > gumbel.quantile( 0.8 )\n ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n 2.4\n > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Gumbel distribution with location parameter `μ` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n ~-0.036\n > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n ~-1.948\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n ~-1.0\n > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n > var y = myLCDF( 10.0 )\n ~-0.069\n > y = myLCDF( 2.0 )\n ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Gumbel distribution with location parameter `μ` and scale parameter\n `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n ~-1.693\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n ~-1\n > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n ~-2.411\n > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-1.693\n > y = mylogpdf( 12.0 )\n ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n ~0.577\n > y = base.dists.gumbel.mean( 4.0, 2.0 )\n ~5.154\n > y = base.dists.gumbel.mean( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mean( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.gumbel.median( 0.0, 1.0 )\n ~0.367\n > y = base.dists.gumbel.median( 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.median( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.median( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.median( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n 6.0\n > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n ~1.298\n\n > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n NaN\n\n // Case: `t >= 1/beta`\n > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n NaN\n\n // Non-positive scale parameter:\n > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n > var y = myMGF( -1.5 )\n ~52.343\n > y = myMGF( -1.0 )\n 6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.gumbel.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.gumbel.mode( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.mode( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n ~0.184\n > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n ~0.368\n > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n ~0.09\n > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.184\n > y = myPDF( 12.0 )\n ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n ~1.5\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n ~4.733\n > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n ~5.466\n\n > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~8.733\n > y = myQuantile( 0.7 )\n ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n ~1.14\n > y = base.dists.gumbel.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n ~1.283\n > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n ~2.565\n > y = base.dists.gumbel.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n ~1.645\n > y = base.dists.gumbel.variance( 4.0, 2.0 )\n ~6.58\n > y = base.dists.gumbel.variance( NaN, 1.0 )\n NaN\n > y = base.dists.gumbel.variance( 0.0, NaN )\n NaN\n > y = base.dists.gumbel.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceeds population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n ~0.786\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n 1.0\n > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n ~0.214\n\n > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n > var y = myCDF( 4.0 )\n ~0.891\n > y = myCDF( 1.0 )\n ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n Returns a hypergeometric distribution object.\n\n Parameters\n ----------\n N: integer (optional)\n Population size. Must be a nonnegative integer larger than or equal to\n `K` and `n`.\n\n K: integer (optional)\n Subpopulation size. Must be a nonnegative integer smaller than or equal\n to `N`.\n\n n: integer (optional)\n Number of draws. Must be a nonnegative integer smaller than or equal to\n `N`.\n\n Returns\n -------\n hypergeometric: Object\n Distribution instance.\n\n hypergeometric.N: number\n Population size. If set, the value must be a nonnegative integer larger\n than or equal to `K` and `n`.\n\n hypergeometric.K: number\n Subpopulation size. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.n: number\n Number of draws. If set, the value must be a nonnegative integer\n smaller than or equal to `N`.\n\n hypergeometric.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n hypergeometric.mean: number\n Read-only property which returns the expected value.\n\n hypergeometric.mode: number\n Read-only property which returns the mode.\n\n hypergeometric.skewness: number\n Read-only property which returns the skewness.\n\n hypergeometric.stdev: number\n Read-only property which returns the standard deviation.\n\n hypergeometric.variance: number\n Read-only property which returns the variance.\n\n hypergeometric.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n hypergeometric.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n hypergeometric.pmf: Function\n Evaluates the probability mass function (PMF).\n\n hypergeometric.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n > hypergeometric.N\n 100.0\n > hypergeometric.K\n 70.0\n > hypergeometric.n\n 20.0\n > hypergeometric.kurtosis\n ~-0.063\n > hypergeometric.mean\n 14.0\n > hypergeometric.mode\n 14.0\n > hypergeometric.skewness\n ~-0.133\n > hypergeometric.stdev\n ~1.842\n > hypergeometric.variance\n ~3.394\n > hypergeometric.cdf( 2.9 )\n ~0.0\n > hypergeometric.logpmf( 10 )\n ~-3.806\n > hypergeometric.pmf( 10 )\n ~0.022\n > hypergeometric.quantile( 0.8 )\n 16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n Returns the excess kurtosis of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or subpopulation size `K` exceed population size\n `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n ~-0.326\n > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K`, or draws `n`\n which is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n ~-0.56\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n ~-1.54\n > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n -Infinity\n\n > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n > var y = mylogPMF( 4.0 )\n ~-1.079\n > y = mylogPMF( 1.0 )\n ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n Returns the expected value of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n 2.75\n > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n Returns the mode of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n 3\n > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n 1\n\n > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n ~0.571\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n ~0.214\n > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n 0.0\n\n > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n NaN\n\n > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n NaN\n > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n > var y = myPMF( 4.0 )\n ~0.34\n > y = myPMF( 1.0 )\n ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n 5\n > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n 15\n > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n 1\n > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n 0\n > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n 20\n\n > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n NaN\n > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n > var y = myQuantile( 0.2 )\n 1\n > y = myQuantile( 0.9 )\n 4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n Returns the skewness of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n ~-0.258\n > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n 0.0\n\n > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n Returns the standard deviation of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n ~0.829\n > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n 0.5\n\n > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n Returns the variance of a hypergeometric distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a population size `N`, subpopulation size `K` or draws `n` which\n is not a nonnegative integer, the function returns `NaN`.\n\n If the number of draws `n` or the subpopulation size `K` exceed population\n size `N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n ~0.688\n > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n 0.25\n\n > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n NaN\n > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n NaN\n\n > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n NaN\n > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n ~0.607\n > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n ~0.986\n > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n > var y = myCDF( 0.5 )\n ~0.736\n > y = myCDF( 2.0 )\n ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n Returns the differential entropy of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n ~2.154\n > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n ~1.996\n > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n Returns an inverse gamma distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n invgamma: Object\n Distribution instance.\n\n invgamma.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n invgamma.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n invgamma.entropy: number\n Read-only property which returns the differential entropy.\n\n invgamma.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n invgamma.mean: number\n Read-only property which returns the expected value.\n\n invgamma.mode: number\n Read-only property which returns the mode.\n\n invgamma.skewness: number\n Read-only property which returns the skewness.\n\n invgamma.stdev: number\n Read-only property which returns the standard deviation.\n\n invgamma.variance: number\n Read-only property which returns the variance.\n\n invgamma.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n invgamma.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n invgamma.pdf: Function\n Evaluates the probability density function (PDF).\n\n invgamma.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n > invgamma.alpha\n 6.0\n > invgamma.beta\n 5.0\n > invgamma.entropy\n ~0.454\n > invgamma.kurtosis\n 19.0\n > invgamma.mean\n 1.0\n > invgamma.mode\n ~0.714\n > invgamma.skewness\n ~2.667\n > invgamma.stdev\n 0.5\n > invgamma.variance\n 0.25\n > invgamma.cdf( 0.8 )\n ~0.406\n > invgamma.pdf( 1.0 )\n ~0.877\n > invgamma.logpdf( 1.0 )\n ~-0.131\n > invgamma.quantile( 0.8 )\n ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n Returns the excess kurtosis of an inverse gamma distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n 12.0\n > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n 19.0\n > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n ~-2.112\n > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n ~-1.781\n > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 2.0 )\n ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n Returns the expected value of an inverse gamma distribution.\n\n If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n 4.0\n > v = base.dists.invgamma.mean( 8.0, 2.0 )\n ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n Returns the mode of an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n 0.5\n > v = base.dists.invgamma.mode( 4.0, 12.0 )\n 2.4\n > v = base.dists.invgamma.mode( 8.0, 2.0 )\n ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n ~0.121\n > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n ~0.168\n > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n NaN\n\n // Negative shape parameter:\n > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 2.0 )\n ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n ~1.213\n > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n ~0.545\n > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n NaN\n\n // Non-positive shape parameter:\n > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n NaN\n\n // Non-positive rate parameter:\n > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n > var y = myQuantile( 0.8 )\n ~2.426\n > y = myQuantile( 0.4 )\n ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n Returns the skewness of an inverse gamma distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n ~5.657\n > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n Returns the standard deviation of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n ~1.01\n > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n ~2.828\n > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n Returns the variance of an inverse gamma distribution.\n\n If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n ~1.021\n > v = base.dists.invgamma.variance( 4.0, 12.0 )\n 8.0\n > v = base.dists.invgamma.variance( 8.0, 2.0 )\n ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n ~0.5\n > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n ~0.684\n > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n ~0.078\n > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n ~0.878\n > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n > var y = mycdf( 0.8 )\n ~0.894\n > y = mycdf( 0.3 )\n ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n Returns a Kumaraswamy's double bounded distribution object.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n b: number (optional)\n Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n kumaraswamy: Object\n Distribution instance.\n\n kumaraswamy.a: number\n First shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.b: number\n Second shape parameter. If set, the value must be greater than `0`.\n\n kumaraswamy.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n kumaraswamy.mean: number\n Read-only property which returns the expected value.\n\n kumaraswamy.mode: number\n Read-only property which returns the mode.\n\n kumaraswamy.skewness: number\n Read-only property which returns the skewness.\n\n kumaraswamy.stdev: number\n Read-only property which returns the standard deviation.\n\n kumaraswamy.variance: number\n Read-only property which returns the variance.\n\n kumaraswamy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n kumaraswamy.pdf: Function\n Evaluates the probability density function (PDF).\n\n kumaraswamy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n > kumaraswamy.a\n 6.0\n > kumaraswamy.b\n 5.0\n > kumaraswamy.kurtosis\n ~3.194\n > kumaraswamy.mean\n ~0.696\n > kumaraswamy.mode\n ~0.746\n > kumaraswamy.skewness\n ~-0.605\n > kumaraswamy.stdev\n ~0.126\n > kumaraswamy.variance\n ~0.016\n > kumaraswamy.cdf( 0.8 )\n ~0.781\n > kumaraswamy.pdf( 1.0 )\n ~0.0\n > kumaraswamy.quantile( 0.8 )\n ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n ~1.8\n > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n ~2.704\n > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n ~-0.38\n > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n ~-2.546\n > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n ~-0.13\n > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n > var y = mylogcdf( 0.8 )\n ~-0.112\n > y = mylogcdf( 0.3 )\n ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n 0.0\n > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n ~0.523\n > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n ~-0.264\n > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n ~0.522\n > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n -Infinity\n > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n > var y = mylogpdf( 0.8 )\n ~-0.582\n > y = mylogpdf( 0.3 )\n ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mean.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n ~0.512\n > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n ~0.481\n > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n Returns the median of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n 0.5\n > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n ~0.487\n > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n ~0.543\n > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n ~0.503\n > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n 1.0\n > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n ~1.688\n > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n ~0.768\n > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n ~1.686\n > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n 0.0\n > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n > var y = mypdf( 0.8 )\n ~0.559\n > y = mypdf( 0.3 )\n ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n 0.5\n > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n ~0.399\n > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n ~0.325\n > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n ~0.759\n\n > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n > var y = myQuantile( 0.8 )\n ~0.64\n > y = myQuantile( 0.3 )\n ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n ~1.154e-15\n > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n ~-0.201\n > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n ~0.289\n > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n ~0.13\n > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n ~0.083\n > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n ~0.017\n > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n ~0.932\n > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n ~0.094\n > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.965\n > y = myCDF( 2.0 )\n 0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n ~1.693\n > y = base.dists.laplace.entropy( 4.0, 2.0 )\n ~2.386\n > y = base.dists.laplace.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.entropy( 0.0, NaN )\n NaN\n > y = base.dists.laplace.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n 3.0\n > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n Returns a Laplace distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n b: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n laplace: Object\n Distribution instance.\n\n laplace.mu: number\n Location parameter.\n\n laplace.b: number\n Scale parameter. If set, the value must be greater than `0`.\n\n laplace.entropy: number\n Read-only property which returns the differential entropy.\n\n laplace.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n laplace.mean: number\n Read-only property which returns the expected value.\n\n laplace.median: number\n Read-only property which returns the median.\n\n laplace.mode: number\n Read-only property which returns the mode.\n\n laplace.skewness: number\n Read-only property which returns the skewness.\n\n laplace.stdev: number\n Read-only property which returns the standard deviation.\n\n laplace.variance: number\n Read-only property which returns the variance.\n\n laplace.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n laplace.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n laplace.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n laplace.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n laplace.pdf: Function\n Evaluates the probability density function (PDF).\n\n laplace.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n > laplace.mu\n -2.0\n > laplace.b\n 3.0\n > laplace.entropy\n ~2.792\n > laplace.kurtosis\n 3.0\n > laplace.mean\n -2.0\n > laplace.median\n -2.0\n > laplace.mode\n -2.0\n > laplace.skewness\n 0.0\n > laplace.stdev\n ~4.243\n > laplace.variance\n 18.0\n > laplace.cdf( 0.8 )\n ~0.803\n > laplace.logcdf( 0.8 )\n ~-0.219\n > laplace.logpdf( 1.0 )\n ~-2.792\n > laplace.mgf( 0.2 )\n ~1.047\n > laplace.pdf( 2.0 )\n ~0.044\n > laplace.quantile( 0.9 )\n ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Laplace distribution with scale parameter `b` and location\n parameter `μ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n ~-0.07\n > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n ~-2.36\n > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.035\n > y = mylogcdf( 2.0 )\n ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Laplace distribution with scale parameter `b` and location parameter\n `μ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n ~-2.693\n > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n ~-2.792\n > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n ~-1.958\n > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.laplace.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mean( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mean( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.laplace.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.median( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.median( 0.0, NaN )\n NaN\n > y = base.dists.laplace.median( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n ~1.333\n > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n ~0.019\n > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n NaN\n > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n NaN\n > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n > var y = mymgf( 0.2 )\n ~2.649\n > y = mymgf( 0.4 )\n ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.laplace.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.laplace.mode( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.mode( 0.0, NaN )\n NaN\n > y = base.dists.laplace.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n ~0.068\n > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n ~0.061\n > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n ~0.141\n > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n ~0.916\n > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n 4.0\n\n > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n > y = myQuantile( 0.8 )\n ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.laplace.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.laplace.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.skewness( 0.0, NaN )\n NaN\n > y = base.dists.laplace.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n ~1.414\n > y = base.dists.laplace.stdev( 4.0, 2.0 )\n ~2.828\n > y = base.dists.laplace.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.stdev( 0.0, NaN )\n NaN\n > y = base.dists.laplace.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.laplace.variance( 0.0, 1.0 )\n 2.0\n > y = base.dists.laplace.variance( 4.0, 2.0 )\n 8.0\n > y = base.dists.laplace.variance( NaN, 1.0 )\n NaN\n > y = base.dists.laplace.variance( 0.0, NaN )\n NaN\n > y = base.dists.laplace.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n ~0.48\n > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n ~0.221\n > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n 0.0\n > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n > var y = myCDF( 10.0 )\n ~0.54\n > y = myCDF( 2.0 )\n 0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.levy.entropy( 0.0, 1.0 )\n ~3.324\n > y = base.dists.levy.entropy( 4.0, 2.0 )\n ~4.018\n > y = base.dists.levy.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.levy.entropy( 0.0, NaN )\n NaN\n > y = base.dists.levy.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n Returns a Lévy distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n c: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n levy: Object\n Distribution instance.\n\n levy.mu: number\n Location parameter.\n\n levy.c: number\n Scale parameter. If set, the value must be greater than `0`.\n\n levy.entropy: number\n Read-only property which returns the differential entropy.\n\n levy.mean: number\n Read-only property which returns the expected value.\n\n levy.median: number\n Read-only property which returns the median.\n\n levy.mode: number\n Read-only property which returns the mode.\n\n levy.stdev: number\n Read-only property which returns the standard deviation.\n\n levy.variance: number\n Read-only property which returns the variance.\n\n levy.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n levy.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n levy.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n levy.pdf: Function\n Evaluates the probability density function (PDF).\n\n levy.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n > levy.mu\n -2.0\n > levy.c\n 3.0\n > levy.entropy\n ~4.423\n > levy.mean\n Infinity\n > levy.median\n ~4.594\n > levy.mode\n -1.0\n > levy.stdev\n Infinity\n > levy.variance\n Infinity\n > levy.cdf( 0.8 )\n ~0.3\n > levy.logcdf( 0.8 )\n ~-1.2\n > levy.logpdf( 1.0 )\n ~-2.518\n > levy.pdf( 1.0 )\n ~0.081\n > levy.quantile( 0.8 )\n ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Lévy distribution with location parameter `μ` and scale\n parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n ~-0.735\n > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n ~-1.51\n > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n -Infinity\n > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.616\n > y = mylogcdf( 2.0 )\n -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Lévy distribution with location parameter `μ` and scale parameter `c`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n ~-2.209\n > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n > var y = mylogPDF( 11.0 )\n ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.levy.mean( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.mean( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.mean( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mean( 0.0, NaN )\n NaN\n > y = base.dists.levy.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.levy.median( 0.0, 1.0 )\n ~2.198\n > y = base.dists.levy.median( 4.0, 3.0 )\n ~10.594\n > y = base.dists.levy.median( NaN, 1.0 )\n NaN\n > y = base.dists.levy.median( 0.0, NaN )\n NaN\n > y = base.dists.levy.median( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.levy.mode( 0.0, 1.0 )\n ~0.333\n > y = base.dists.levy.mode( 4.0, 3.0 )\n 5.0\n > y = base.dists.levy.mode( NaN, 1.0 )\n NaN\n > y = base.dists.levy.mode( 0.0, NaN )\n NaN\n > y = base.dists.levy.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n ~0.11\n > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 11.0 )\n ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n ~15.58\n > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n ~8.396\n\n > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.levy.stdev( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.stdev( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.levy.stdev( 0.0, NaN )\n NaN\n > y = base.dists.levy.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.levy.variance( 0.0, 1.0 )\n Infinity\n > y = base.dists.levy.variance( 4.0, 3.0 )\n Infinity\n > y = base.dists.levy.variance( NaN, 1.0 )\n NaN\n > y = base.dists.levy.variance( 0.0, NaN )\n NaN\n > y = base.dists.levy.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n ~0.881\n > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n ~0.159\n\n > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `s = 0.0`:\n > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n > var y = mycdf( 1.0 )\n ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n 2.0\n > y = base.dists.logistic.entropy( 4.0, 2.0 )\n ~2.693\n > y = base.dists.logistic.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.entropy( 0.0, NaN )\n NaN\n > y = base.dists.logistic.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n 1.2\n > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a logistic distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n ~-0.127\n > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n ~-1.84\n > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n > var y = mylogcdf( 1.0 )\n ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n Returns a logistic distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n s: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n logistic: Object\n Distribution instance.\n\n logistic.mu: number\n Location parameter.\n\n logistic.s: number\n Scale parameter. If set, the value must be greater than `0`.\n\n logistic.entropy: number\n Read-only property which returns the differential entropy.\n\n logistic.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n logistic.mean: number\n Read-only property which returns the expected value.\n\n logistic.median: number\n Read-only property which returns the median.\n\n logistic.mode: number\n Read-only property which returns the mode.\n\n logistic.skewness: number\n Read-only property which returns the skewness.\n\n logistic.stdev: number\n Read-only property which returns the standard deviation.\n\n logistic.variance: number\n Read-only property which returns the variance.\n\n logistic.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n logistic.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n logistic.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n logistic.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n logistic.pdf: Function\n Evaluates the probability density function (PDF).\n\n logistic.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n > logistic.mu\n -2.0\n > logistic.s\n 3.0\n > logistic.entropy\n ~3.1\n > logistic.kurtosis\n 1.2\n > logistic.mean\n -2.0\n > logistic.median\n -2.0\n > logistic.mode\n -2.0\n > logistic.skewness\n 0.0\n > logistic.stdev\n ~5.441\n > logistic.variance\n ~29.609\n > logistic.cdf( 0.8 )\n ~0.718\n > logistic.logcdf( 0.8 )\n ~-0.332\n > logistic.logpdf( 2.0 )\n ~-2.9\n > logistic.mgf( 0.2 )\n ~1.329\n > logistic.pdf( 2.0 )\n ~0.055\n > logistic.quantile( 0.9 )\n ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a logistic distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n ~-2.254\n > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n ~-3.351\n > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution at `s = 0.0`:\n > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n > var y = mylogpdf( 10.0 )\n ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.logistic.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mean( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mean( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.logistic.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.median( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.median( 0.0, NaN )\n NaN\n > y = base.dists.logistic.median( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n ~9.15\n > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n ~1.971\n > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n ~1.921\n > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n Infinity\n > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n > var y = mymgf( 0.5 )\n ~164.846\n > y = mymgf( 2.0 )\n Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.logistic.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.logistic.mode( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.mode( 0.0, NaN )\n NaN\n > y = base.dists.logistic.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n ~0.105\n > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n ~0.035\n > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n 0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n ~1.386\n > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.logistic.skewness( 4.0, 2.0 )\n 0.0\n > y = base.dists.logistic.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.skewness( 0.0, NaN )\n NaN\n > y = base.dists.logistic.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n ~1.814\n > y = base.dists.logistic.stdev( 4.0, 2.0 )\n ~3.628\n > y = base.dists.logistic.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.stdev( 0.0, NaN )\n NaN\n > y = base.dists.logistic.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.logistic.variance( 0.0, 1.0 )\n ~3.29\n > y = base.dists.logistic.variance( 4.0, 2.0 )\n ~13.159\n > y = base.dists.logistic.variance( NaN, 1.0 )\n NaN\n > y = base.dists.logistic.variance( 0.0, NaN )\n NaN\n > y = base.dists.logistic.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n ~0.756\n > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n ~0.003\n\n > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n > var y = myCDF( 1.0 )\n ~0.023\n > y = myCDF( 4.0 )\n ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n ~7.112\n > y = base.dists.lognormal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n ~110.936\n > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n ~9220556.977\n > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n Returns a lognormal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter. Default: `0.0`.\n\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n lognormal: Object\n Distribution instance.\n\n lognormal.mu: number\n Location parameter.\n\n lognormal.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n lognormal.entropy: number\n Read-only property which returns the differential entropy.\n\n lognormal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n lognormal.mean: number\n Read-only property which returns the expected value.\n\n lognormal.median: number\n Read-only property which returns the median.\n\n lognormal.mode: number\n Read-only property which returns the mode.\n\n lognormal.skewness: number\n Read-only property which returns the skewness.\n\n lognormal.stdev: number\n Read-only property which returns the standard deviation.\n\n lognormal.variance: number\n Read-only property which returns the variance.\n\n lognormal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n lognormal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n lognormal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n lognormal.pdf: Function\n Evaluates the probability density function (PDF).\n\n lognormal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n > lognormal.mu\n -2.0\n > lognormal.sigma\n 3.0\n > lognormal.entropy\n ~0.518\n > lognormal.kurtosis\n 4312295840576300\n > lognormal.mean\n ~12.182\n > lognormal.median\n ~0.135\n > lognormal.mode\n ~0.0\n > lognormal.skewness\n ~729551.383\n > lognormal.stdev\n ~1096.565\n > lognormal.variance\n ~1202455.871\n > lognormal.cdf( 0.8 )\n ~0.723\n > lognormal.logcdf( 0.8 )\n ~-4.334\n > lognormal.logpdf( 2.0 )\n ~-3.114\n > lognormal.pdf( 2.0 )\n ~0.044\n > lognormal.quantile( 0.9 )\n ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with location parameter `μ` and scale\n parameter `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.2799\n > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n ~-1.442\n > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with location\n parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with location\n parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n ~-1.852\n > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n ~-0.919\n > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n ~-5.419\n > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n > var y = mylogPDF( 10.0 )\n ~-4.275\n > y = mylogPDF( 2.0 )\n ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n ~1.649\n > y = base.dists.lognormal.mean( 4.0, 2.0 )\n ~403.429\n > y = base.dists.lognormal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mean( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.lognormal.median( 0.0, 1.0 )\n 1.0\n > y = base.dists.lognormal.median( 5.0, 2.0 )\n ~148.413\n > y = base.dists.lognormal.median( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.median( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n ~0.368\n > y = base.dists.lognormal.mode( 5.0, 2.0 )\n ~2.718\n > y = base.dists.lognormal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.mode( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n ~0.157\n > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n ~0.399\n > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n ~0.004\n > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.014\n > y = myPDF( 2.0 )\n ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n ~2.32\n > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n ~54.598\n > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Non-positive scale parameter `σ`:\n > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n NaN\n > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n > var y = myQuantile( 0.2 )\n ~10.143\n > y = myQuantile( 0.8 )\n ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n ~6.185\n > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n ~414.359\n > y = base.dists.lognormal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n ~2.161\n > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n ~2953.533\n > y = base.dists.lognormal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n ~4.671\n > y = base.dists.lognormal.variance( 4.0, 2.0 )\n ~8723355.729\n > y = base.dists.lognormal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.lognormal.variance( 0.0, NaN )\n NaN\n > y = base.dists.lognormal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n ~0.617\n > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n ~0.622\n > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n ~0.034\n > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n ~0.859\n > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n ~0.131\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n > var y = myCDF( 3.0 )\n ~0.046\n > y = myCDF( 11.0 )\n ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n Returns the excess kurtosis of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Kurtosis.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n ~0.061\n > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n ~-1.853\n > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n ~-2.818\n > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n ~-4.115\n > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n ~-1.054\n > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n ~-3.292\n > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n ~-2.976\n\n > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n > var y = mylogPMF( 3.0 )\n ~-3.617\n > y = mylogPMF( 5.0 )\n ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n Returns the expected value of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n 400\n > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n 20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n ~267.839\n > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n ~9.347\n > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n ~42822.023\n\n > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n NaN\n\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n > var y = myMGF( 0.2 )\n ~4.696\n > y = myMGF( 0.4 )\n ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n Returns the mode of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n 396\n > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n 19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n Returns a negative binomial distribution object.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped. Must be a positive\n number. Default: `1`.\n\n p: number (optional)\n Success probability. Must be a number between `0` and `1`. Default:\n `0.5`.\n\n Returns\n -------\n nbinomial: Object\n Distribution instance.\n\n nbinomial.r: number\n Number of trials. If set, the value must be a positive number.\n\n nbinomial.p: number\n Success probability. If set, the value must be a number between `0` and\n `1`.\n\n nbinomial.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n nbinomial.mean: number\n Read-only property which returns the expected value.\n\n nbinomial.mode: number\n Read-only property which returns the mode.\n\n nbinomial.skewness: number\n Read-only property which returns the skewness.\n\n nbinomial.stdev: number\n Read-only property which returns the standard deviation.\n\n nbinomial.variance: number\n Read-only property which returns the variance.\n\n nbinomial.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n nbinomial.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n nbinomial.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n nbinomial.pmf: Function\n Evaluates the probability mass function (PMF).\n\n nbinomial.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n > nbinomial.r\n 8.0\n > nbinomial.p\n 0.5\n > nbinomial.kurtosis\n 0.8125\n > nbinomial.mean\n 8.0\n > nbinomial.mode\n 7.0\n > nbinomial.skewness\n 0.75\n > nbinomial.stdev\n 4.0\n > nbinomial.variance\n 16.0\n > nbinomial.cdf( 2.9 )\n ~0.055\n > nbinomial.logpmf( 3.0 )\n ~-2.837\n > nbinomial.mgf( 0.2 )\n ~36.675\n > nbinomial.pmf( 3.0 )\n ~0.059\n > nbinomial.quantile( 0.8 )\n 11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n ~0.157\n > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n ~0.06\n > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n ~0.016\n > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n ~0.349\n > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n ~0.037\n > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n ~0.051\n\n > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n > var y = myPMF( 3.0 )\n ~0.027\n > y = myPMF( 5.0 )\n ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n\n If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n k: number\n Input probability.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n 106\n > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n 8\n > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n 14\n > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n 0\n\n > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n 12\n > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n 10\n\n > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n NaN\n\n > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n NaN\n > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n > var y = myQuantile( 0.1 )\n 5\n > y = myQuantile( 0.9 )\n 16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n Returns the skewness of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n ~0.201\n > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n Returns the standard deviation of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n ~44.721\n > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n Returns the variance of a negative binomial distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a `r` which is not a positive number, the function returns\n `NaN`.\n\n If provided a success probability `p` outside of `[0,1]`, the function\n returns `NaN`.\n\n Parameters\n ----------\n r: integer\n Number of failures until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n 2000.0\n > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n 40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n ~0.977\n > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n 0.5\n > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n ~0.006\n > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n 1.0\n > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n 1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 10.0 )\n 0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var y = base.dists.normal.entropy( 0.0, 1.0 )\n ~1.419\n > y = base.dists.normal.entropy( 4.0, 3.0 )\n ~2.518\n > y = base.dists.normal.entropy( NaN, 1.0 )\n NaN\n > y = base.dists.normal.entropy( 0.0, NaN )\n NaN\n > y = base.dists.normal.entropy( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.kurtosis( NaN, 1.0 )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, NaN )\n NaN\n > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logcdf.\n\n Examples\n --------\n > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n ~-0.023\n > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n ~-5.082\n > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n 0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n > var y = mylogcdf( 10.0 )\n ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n ~-2.919\n > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n ~-4.737\n > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n -Infinity\n > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n > var y = myLogPDF( 10.0 )\n ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var y = base.dists.normal.mean( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mean( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mean( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mean( 0.0, NaN )\n NaN\n > y = base.dists.normal.mean( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var y = base.dists.normal.median( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.median( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.median( NaN, 1.0 )\n NaN\n > y = base.dists.normal.median( 0.0, NaN )\n NaN\n > y = base.dists.normal.median( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n ~7.389\n > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n ~0.1353\n > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n > var y = myMGF( 1.0 )\n ~403.429\n > y = myMGF( 0.5 )\n ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var y = base.dists.normal.mode( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.mode( 4.0, 2.0 )\n 4.0\n > y = base.dists.normal.mode( NaN, 1.0 )\n NaN\n > y = base.dists.normal.mode( 0.0, NaN )\n NaN\n > y = base.dists.normal.mode( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n Returns a normal distribution object.\n\n Parameters\n ----------\n μ: number (optional)\n Mean parameter. Default: `0.0`.\n\n σ: number (optional)\n Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n normal: Object\n Distribution instance.\n\n normal.mu: number\n Mean parameter.\n\n normal.sigma: number\n Standard deviation. If set, the value must be greater than `0`.\n\n normal.entropy: number\n Read-only property which returns the differential entropy.\n\n normal.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n normal.mean: number\n Read-only property which returns the expected value.\n\n normal.median: number\n Read-only property which returns the median.\n\n normal.mode: number\n Read-only property which returns the mode.\n\n normal.skewness: number\n Read-only property which returns the skewness.\n\n normal.stdev: number\n Read-only property which returns the standard deviation.\n\n normal.variance: number\n Read-only property which returns the variance.\n\n normal.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n normal.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n normal.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n normal.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n normal.pdf: Function\n Evaluates the probability density function (PDF).\n\n normal.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n > normal.mu\n -2.0\n > normal.sigma\n 3.0\n > normal.entropy\n ~2.518\n > normal.kurtosis\n 0.0\n > normal.mean\n -2.0\n > normal.median\n -2.0\n > normal.mode\n -2.0\n > normal.skewness\n 0.0\n > normal.stdev\n 3.0\n > normal.variance\n 9.0\n > normal.cdf( 0.8 )\n ~0.825\n > normal.logcdf( 0.8 )\n ~-0.193\n > normal.logpdf( 2.0 )\n ~-2.9\n > normal.mgf( 0.2 )\n ~0.803\n > normal.pdf( 2.0 )\n ~0.055\n > normal.quantile( 0.9 )\n ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n ~0.054\n > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n ~0.009\n > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n 0.0\n > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n > var y = myPDF( 10.0 )\n ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n ~0.842\n > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n 4\n\n > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n NaN\n\n // Negative standard deviation:\n > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n NaN\n\n // Degenerate distribution centered at `μ` when `σ = 0.0`:\n > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n 8.0\n > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n 8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n > var y = myQuantile( 0.5 )\n 10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var y = base.dists.normal.skewness( 0.0, 1.0 )\n 0.0\n > y = base.dists.normal.skewness( 4.0, 3.0 )\n 0.0\n > y = base.dists.normal.skewness( NaN, 1.0 )\n NaN\n > y = base.dists.normal.skewness( 0.0, NaN )\n NaN\n > y = base.dists.normal.skewness( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var y = base.dists.normal.stdev( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.stdev( 4.0, 3.0 )\n 3.0\n > y = base.dists.normal.stdev( NaN, 1.0 )\n NaN\n > y = base.dists.normal.stdev( 0.0, NaN )\n NaN\n > y = base.dists.normal.stdev( 0.0, 0.0 )\n NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var y = base.dists.normal.variance( 0.0, 1.0 )\n 1.0\n > y = base.dists.normal.variance( 4.0, 3.0 )\n 9.0\n > y = base.dists.normal.variance( NaN, 1.0 )\n NaN\n > y = base.dists.normal.variance( 0.0, NaN )\n NaN\n > y = base.dists.normal.variance( 0.0, 0.0 )\n NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n 0.5\n > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n ~0.36\n > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n 0.75\n > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n 1.0\n\n > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n > var y = myCDF( 3.0 )\n ~0.983\n > y = myCDF( 2.5 )\n ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n ~2.473\n > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n ~2.349\n > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n ~70.8\n > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n ~146.444\n > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n ~-0.693\n > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n ~-1.022\n > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n ~-0.288\n > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n > var y = mylogCDF( 3.0 )\n ~-0.017\n > y = mylogCDF( 2.5 )\n ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n ~-2.773\n > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n ~-3.689\n > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n ~-1.561\n > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n ~-5.238\n > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n -Infinity\n\n > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n > var y = mylogPDF( 0.8 )\n ~-0.705\n > y = mylogPDF( 2.0 )\n ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n Returns the expected value of a Pareto (Type I) distribution.\n\n If `0 < α <= 1`, the function returns `Infinity`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.mean( 4.0, 12.0 )\n 16.0\n > v = base.dists.pareto1.mean( 8.0, 2.0 )\n ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n Returns the median of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.pareto1.median( 0.8, 1.0 )\n ~2.378\n > v = base.dists.pareto1.median( 4.0, 12.0 )\n ~14.27\n > v = base.dists.pareto1.median( 8.0, 2.0 )\n ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n Returns the mode of a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n 1.0\n > v = base.dists.pareto1.mode( 4.0, 12.0 )\n 12.0\n > v = base.dists.pareto1.mode( 8.0, 2.0 )\n 2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n Returns a Pareto (Type I) distribution object.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n β: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n pareto1: Object\n Distribution instance.\n\n pareto1.alpha: number\n Shape parameter. If set, the value must be greater than `0`.\n\n pareto1.beta: number\n Scale parameter. If set, the value must be greater than `0`.\n\n pareto1.entropy: number\n Read-only property which returns the differential entropy.\n\n pareto1.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n pareto1.mean: number\n Read-only property which returns the expected value.\n\n pareto1.median: number\n Read-only property which returns the median.\n\n pareto1.mode: number\n Read-only property which returns the mode.\n\n pareto1.skewness: number\n Read-only property which returns the skewness.\n\n pareto1.variance: number\n Read-only property which returns the variance.\n\n pareto1.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n pareto1.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF).\n\n pareto1.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (logPDF).\n\n pareto1.pdf: Function\n Evaluates the probability density function (PDF).\n\n pareto1.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n > pareto1.alpha\n 6.0\n > pareto1.beta\n 5.0\n > pareto1.entropy\n ~0.984\n > pareto1.kurtosis\n ~35.667\n > pareto1.mean\n 6.0\n > pareto1.median\n ~5.612\n > pareto1.mode\n 5.0\n > pareto1.skewness\n ~3.81\n > pareto1.variance\n 1.5\n > pareto1.cdf( 7.0 )\n ~0.867\n > pareto1.logcdf( 7.0 )\n ~-0.142\n > pareto1.logpdf( 5.0 )\n ~0.182\n > pareto1.pdf( 5.0 )\n 1.2\n > pareto1.quantile( 0.8 )\n ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n ~0.063\n > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n 0.025\n > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n ~0.21\n > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n ~0.005\n > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n 0.0\n\n > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n NaN\n\n > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n > var y = myPDF( 0.8 )\n ~0.494\n > y = myPDF( 2.0 )\n ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n ~2.236\n > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n ~50.0\n > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n ~11.111\n\n > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n NaN\n\n > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n NaN\n > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n > var y = myQuantile( 0.5 )\n ~0.66\n > y = myQuantile( 0.8 )\n ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n Returns the skewness of a Pareto (Type I) distribution.\n\n If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n ~11.784\n > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n ~7.071\n > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n Returns the standard deviation of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n ~5.657\n > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n Returns the variance of a Pareto (Type I) distribution.\n\n If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n Infinity\n > v = base.dists.pareto1.variance( 4.0, 12.0 )\n 32.0\n > v = base.dists.pareto1.variance( 8.0, 2.0 )\n ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n ~0.986\n > y = base.dists.poisson.cdf( 2.0, 10.0 )\n ~0.003\n > y = base.dists.poisson.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.poisson.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.poisson.cdf( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.poisson.cdf( 10.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n > var y = mycdf( 3.0 )\n ~0.265\n > y = mycdf( 8.0 )\n ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n Returns the entropy of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.poisson.entropy( 11.0 )\n ~2.61\n > v = base.dists.poisson.entropy( 4.5 )\n ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n Returns the excess kurtosis of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.poisson.kurtosis( 11.0 )\n ~0.091\n > v = base.dists.poisson.kurtosis( 4.5 )\n ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated logPMF.\n\n Examples\n --------\n > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n ~-1.784\n > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n ~-1.901\n > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.logpmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n -Infinity\n > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n 0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n logpmf: Function\n Logarithm of probability mass function (PMF).\n\n Examples\n --------\n > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n > var y = mylogpmf( 3.0 )\n ~-2.792\n > y = mylogpmf( 1.0 )\n ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n Returns the expected value of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.poisson.mean( 11.0 )\n 11.0\n > v = base.dists.poisson.mean( 4.5 )\n 4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n Returns the median of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Median.\n\n Examples\n --------\n > var v = base.dists.poisson.median( 11.0 )\n 11\n > v = base.dists.poisson.median( 4.5 )\n 4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n ~13.163\n > y = base.dists.poisson.mgf( 0.5, 0.5 )\n ~1.383\n > y = base.dists.poisson.mgf( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.mgf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.mgf( -2.0, -1.0 )\n NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n > var y = myMGF( 0.1 )\n ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n Returns the mode of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: integer\n Mode.\n\n Examples\n --------\n > var v = base.dists.poisson.mode( 11.0 )\n 11\n > v = base.dists.poisson.mode( 4.5 )\n 4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated PMF.\n\n Examples\n --------\n > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n ~0.168\n > y = base.dists.poisson.pmf( 1.0, 3.0 )\n ~0.149\n > y = base.dists.poisson.pmf( -1.0, 2.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, NaN )\n NaN\n > y = base.dists.poisson.pmf( NaN, 0.5 )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.pmf( 2.0, -0.5 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.pmf( 2.0, 0.0 )\n 0.0\n > y = base.dists.poisson.pmf( 0.0, 0.0 )\n 1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n pmf: Function\n Probability mass function (PMF).\n\n Examples\n --------\n > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n > var y = mypmf( 3.0 )\n ~0.061\n > y = mypmf( 1.0 )\n ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n Returns a Poisson distribution object.\n\n Parameters\n ----------\n λ: number (optional)\n Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n poisson: Object\n Distribution instance.\n\n poisson.lambda: number\n Mean parameter. If set, the value must be greater than `0`.\n\n poisson.entropy: number\n Read-only property which returns the differential entropy.\n\n poisson.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n poisson.mean: number\n Read-only property which returns the expected value.\n\n poisson.median: number\n Read-only property which returns the median.\n\n poisson.mode: number\n Read-only property which returns the mode.\n\n poisson.skewness: number\n Read-only property which returns the skewness.\n\n poisson.stdev: number\n Read-only property which returns the standard deviation.\n\n poisson.variance: number\n Read-only property which returns the variance.\n\n poisson.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n poisson.logpmf: Function\n Evaluates the natural logarithm of the probability mass function (PMF).\n\n poisson.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n poisson.pmf: Function\n Evaluates the probability mass function (PMF).\n\n poisson.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var poisson = base.dists.poisson.Poisson( 6.0 );\n > poisson.lambda\n 6.0\n > poisson.entropy\n ~2.3\n > poisson.kurtosis\n ~0.167\n > poisson.mean\n 6.0\n > poisson.median\n 6.0\n > poisson.mode\n 6.0\n > poisson.skewness\n ~0.408\n > poisson.stdev\n ~2.449\n > poisson.variance\n 6.0\n > poisson.cdf( 4.0 )\n ~0.285\n > poisson.logpmf( 2.0 )\n ~-3.11\n > poisson.mgf( 0.5 )\n ~49.025\n > poisson.pmf( 2.0 )\n ~0.045\n > poisson.quantile( 0.5 )\n 6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n 2\n > y = base.dists.poisson.quantile( 0.9, 4.0 )\n 7\n > y = base.dists.poisson.quantile( 0.1, 200.0 )\n 182\n\n > y = base.dists.poisson.quantile( 1.1, 0.0 )\n NaN\n > y = base.dists.poisson.quantile( -0.2, 0.0 )\n NaN\n\n > y = base.dists.poisson.quantile( NaN, 0.5 )\n NaN\n > y = base.dists.poisson.quantile( 0.0, NaN )\n NaN\n\n // Negative mean parameter:\n > y = base.dists.poisson.quantile( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution at `λ = 0`:\n > y = base.dists.poisson.quantile( 0.1, 0.0 )\n 0.0\n > y = base.dists.poisson.quantile( 0.9, 0.0 )\n 0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n 0.0\n > y = myQuantile( 1.0 )\n Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n Returns the skewness of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.poisson.skewness( 11.0 )\n ~0.302\n > v = base.dists.poisson.skewness( 4.5 )\n ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n Returns the standard deviation of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.poisson.stdev( 11.0 )\n ~3.317\n > v = base.dists.poisson.stdev( 4.5 )\n ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n Returns the variance of a Poisson distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `λ`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.poisson.variance( 11.0 )\n 11.0\n > v = base.dists.poisson.variance( 4.5 )\n 4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n ~0.199\n > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n ~0.118\n > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.cdf( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n 1.0\n > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n 1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n > var y = myCDF( 1.0 )\n ~0.865\n > y = myCDF( 0.5 )\n ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n Returns the differential entropy of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.rayleigh.entropy( 11.0 )\n ~3.34\n > v = base.dists.rayleigh.entropy( 4.5 )\n ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n Returns the excess kurtosis of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.rayleigh.kurtosis( 11.0 )\n ~0.245\n > v = base.dists.rayleigh.kurtosis( 4.5 )\n ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Rayleigh distribution with scale parameter `sigma` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n ~-1.613\n > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n ~-2.141\n > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n -Infinity\n > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n > var y = mylogcdf( 1.0 )\n ~-0.145\n > y = mylogcdf( 0.5 )\n ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n ~-1.249\n > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n ~-1.986\n > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n -Infinity\n > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n NaN\n // Negative scale parameter:\n > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n > var y = mylogpdf( 6.0 )\n ~-2.106\n > y = mylogpdf( 4.0 )\n ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n Returns the expected value of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mean( 11.0 )\n ~13.786\n > v = base.dists.rayleigh.mean( 4.5 )\n ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n Returns the median of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.rayleigh.median( 11.0 )\n ~12.952\n > v = base.dists.rayleigh.median( 4.5 )\n ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n ~678.508\n > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n ~38.65\n > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n ~-0.947\n > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.mgf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n > var y = myMGF( 1.0 )\n ~2.715\n > y = myMGF( 0.5 )\n ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n Returns the mode of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.rayleigh.mode( 11.0 )\n 11.0\n > v = base.dists.rayleigh.mode( 4.5 )\n 4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n ~0.287\n > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n ~0.137\n > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, NaN )\n NaN\n > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n NaN\n\n // Degenerate distribution when `sigma = 0.0`:\n > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n 0.0\n > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n Infinity\n > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n 0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n > var y = myPDF( 6.0 )\n ~0.122\n > y = myPDF( 4.0 )\n ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `sigma`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n sigma: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n ~1.794\n > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n ~4.71\n\n > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n NaN\n\n > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.rayleigh.quantile( 0.0, NaN )\n NaN\n\n // Negative scale parameter:\n > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n > var y = myQuantile( 0.4 )\n ~0.404\n > y = myQuantile( 1.0 )\n Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n Returns a Rayleigh distribution object.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n rayleigh: Object\n Distribution instance.\n\n rayleigh.sigma: number\n Scale parameter. If set, the value must be greater than `0`.\n\n rayleigh.entropy: number\n Read-only property which returns the differential entropy.\n\n rayleigh.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n rayleigh.mean: number\n Read-only property which returns the expected value.\n\n rayleigh.median: number\n Read-only property which returns the median.\n\n rayleigh.mode: number\n Read-only property which returns the mode.\n\n rayleigh.skewness: number\n Read-only property which returns the skewness.\n\n rayleigh.stdev: number\n Read-only property which returns the standard deviation.\n\n rayleigh.variance: number\n Read-only property which returns the variance.\n\n rayleigh.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n rayleigh.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n rayleigh.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n rayleigh.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n rayleigh.pdf: Function\n Evaluates the probability density function (PDF).\n\n rayleigh.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n > rayleigh.sigma\n 6.0\n > rayleigh.entropy\n ~2.734\n > rayleigh.kurtosis\n ~0.245\n > rayleigh.mean\n ~7.52\n > rayleigh.median\n ~7.064\n > rayleigh.mode\n 6.0\n > rayleigh.skewness\n ~0.631\n > rayleigh.stdev\n ~3.931\n > rayleigh.variance\n ~15.451\n > rayleigh.cdf( 1.0 )\n ~0.014\n > rayleigh.logcdf( 1.0 )\n ~-4.284\n > rayleigh.logpdf( 1.5 )\n ~-3.209\n > rayleigh.mgf( -0.5 )\n ~-0.91\n > rayleigh.pdf( 1.5 )\n ~0.04\n > rayleigh.quantile( 0.5 )\n ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n Returns the skewness of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.rayleigh.skewness( 11.0 )\n ~0.631\n > v = base.dists.rayleigh.skewness( 4.5 )\n ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n Returns the standard deviation of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.rayleigh.stdev( 9.0 )\n ~5.896\n > v = base.dists.rayleigh.stdev( 4.5 )\n ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n Returns the variance of a Rayleigh distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `σ < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.rayleigh.variance( 9.0 )\n ~34.765\n > v = base.dists.rayleigh.variance( 4.5 )\n ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.signrank.cdf( 3, 7 )\n ~0.039\n > y = base.dists.signrank.cdf( 1.8, 3 )\n ~0.375\n > y = base.dists.signrank.cdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.cdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.cdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.signrank.cdf.factory( 8 );\n > var y = myCDF( 5.7 )\n ~0.055\n > y = myCDF( 2.2 )\n ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a negative value for `x`, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.signrank.pdf( 3, 7 )\n ~0.0156\n > y = base.dists.signrank.pdf( 1.8, 3 )\n 0.0\n > y = base.dists.signrank.pdf( -1.0, 40 )\n 0.0\n > y = base.dists.signrank.pdf( NaN, 10 )\n NaN\n > y = base.dists.signrank.pdf( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.signrank.pdf.factory( 8 );\n > var y = myPDF( 6.0 )\n ~0.0156\n > y = myPDF( 2.0 )\n ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If not provided a positive integer for `n`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n n: integer\n Number of observations.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.signrank.quantile( 0.8, 5 )\n 11\n > y = base.dists.signrank.quantile( 0.5, 4 )\n 5\n\n > y = base.dists.signrank.quantile( 1.1, 5 )\n NaN\n > y = base.dists.signrank.quantile( -0.2, 5 )\n NaN\n\n > y = base.dists.signrank.quantile( NaN, 5 )\n NaN\n > y = base.dists.signrank.quantile( 0.0, NaN )\n NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n\n Parameters\n ----------\n n: integer\n Number of observations.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n > var y = myQuantile( 0.4 )\n 16\n > y = myQuantile( 1.0 )\n 36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n\n Parameters\n ----------\n r: number\n Number of samples.\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n > var y = mycdf( 3.0 )\n ~0.712\n > y = mycdf( 1.0 )\n ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n Evaluates the quantile function for a studentized range distribution.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = quantile( 0.5, 3.0, 2.0 )\n ~0.0644\n\n > y = quantile( 0.9, 17.0, 2.0 )\n ~0.913\n\n > y = quantile( 0.5, 3.0, 2.0, 2 )\n ~0.01\n\n > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n NaN\n > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n NaN\n\n > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n\n Parameters\n ----------\n r: number\n Sample size for range (same for each group).\n\n v: number\n Degrees of freedom.\n\n nranges: integer\n Number of groups whose maximum range is considered. Default: 1.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = quantile.factory( 3.0, 3.0 );\n > var y = myQuantile( 0.5 )\n ~1.791\n\n > y = myQuantile( 0.8 )\n ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.t.cdf( 2.0, 0.1 )\n ~0.611\n > y = base.dists.t.cdf( 1.0, 2.0 )\n ~0.789\n > y = base.dists.t.cdf( -1.0, 4.0 )\n ~0.187\n > y = base.dists.t.cdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.cdf( 0.0, NaN )\n NaN\n > y = base.dists.t.cdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.t.cdf.factory( 0.5 );\n > var y = mycdf( 3.0 )\n ~0.816\n > y = mycdf( 1.0 )\n ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n Returns the differential entropy of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.t.entropy( 11.0 )\n ~1.512\n > v = base.dists.t.entropy( 4.5 )\n ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n Returns the excess kurtosis of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 2`, the function returns `NaN`.\n\n If provided `2 < v <= 4`, the function returns positive infinity.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.t.kurtosis( 11.0 )\n ~0.857\n > v = base.dists.t.kurtosis( 4.5 )\n 12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.t.logcdf( 2.0, 0.1 )\n ~-0.493\n > y = base.dists.t.logcdf( 1.0, 2.0 )\n ~-0.237\n > y = base.dists.t.logcdf( -1.0, 4.0 )\n ~-1.677\n > y = base.dists.t.logcdf( NaN, 1.0 )\n NaN\n > y = base.dists.t.logcdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logcdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n > var y = mylogcdf( 3.0 )\n ~-0.203\n > y = mylogcdf( 1.0 )\n ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.t.logpdf( 0.3, 4.0 )\n ~-1.036\n > y = base.dists.t.logpdf( 2.0, 0.7 )\n ~-2.841\n > y = base.dists.t.logpdf( -1.0, 0.5 )\n ~-2.134\n > y = base.dists.t.logpdf( 0.0, NaN )\n NaN\n > y = base.dists.t.logpdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.logpdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n > var y = mylogPDF( 1.0 )\n ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n Returns the expected value of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.t.mean( 11.0 )\n 0.0\n > v = base.dists.t.mean( 4.5 )\n 0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n Returns the median of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.t.median( 11.0 )\n 0.0\n > v = base.dists.t.median( 4.5 )\n 0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n Returns the mode of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v < 0`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.t.mode( 11.0 )\n 0.0\n > v = base.dists.t.mode( 4.5 )\n 0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.t.pdf( 0.3, 4.0 )\n ~0.355\n > y = base.dists.t.pdf( 2.0, 0.7 )\n ~0.058\n > y = base.dists.t.pdf( -1.0, 0.5 )\n ~0.118\n > y = base.dists.t.pdf( 0.0, NaN )\n NaN\n > y = base.dists.t.pdf( NaN, 2.0 )\n NaN\n > y = base.dists.t.pdf( 2.0, -1.0 )\n NaN\n\n\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.t.pdf.factory( 3.0 );\n > var y = myPDF( 1.0 )\n ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `v`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.t.quantile( 0.8, 1.0 )\n ~1.376\n > y = base.dists.t.quantile( 0.1, 1.0 )\n ~-3.078\n > y = base.dists.t.quantile( 0.5, 0.1 )\n 0.0\n\n > y = base.dists.t.quantile( -0.2, 0.1 )\n NaN\n\n > y = base.dists.t.quantile( NaN, 1.0 )\n NaN\n > y = base.dists.t.quantile( 0.0, NaN )\n NaN\n\n > y = base.dists.t.quantile( 0.5, -1.0 )\n NaN\n\n\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n > var y = myQuantile( 0.2 )\n ~-0.941\n > y = myQuantile( 0.9 )\n ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n Returns the skewness of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `v <= 3`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.t.skewness( 11.0 )\n 0.0\n > v = base.dists.t.skewness( 4.5 )\n 0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n Returns the standard deviation of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.t.stdev( 9.0 )\n ~1.134\n > v = base.dists.t.stdev( 4.5 )\n ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n Returns a Student's t distribution object.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n t: Object\n Distribution instance.\n\n t.v: number\n Degrees of freedom. If set, the value must be greater than `0`.\n\n t.entropy: number\n Read-only property which returns the differential entropy.\n\n t.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n t.mean: number\n Read-only property which returns the expected value.\n\n t.median: number\n Read-only property which returns the median.\n\n t.mode: number\n Read-only property which returns the mode.\n\n t.skewness: number\n Read-only property which returns the skewness.\n\n t.stdev: number\n Read-only property which returns the standard deviation.\n\n t.variance: number\n Read-only property which returns the variance.\n\n t.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n t.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n t.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n t.pdf: Function\n Evaluates the probability density function (PDF).\n\n t.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var t = base.dists.t.T( 6.0 );\n > t.v\n 6.0\n > t.entropy\n ~1.592\n > t.kurtosis\n 3.0\n > t.mean\n 0.0\n > t.median\n 0.0\n > t.mode\n 0.0\n > t.skewness\n 0.0\n > t.stdev\n ~1.225\n > t.variance\n 1.5\n > t.cdf( 1.0 )\n ~0.822\n > t.logcdf( 1.0 )\n ~-0.196\n > t.logpdf( 1.5 )\n ~-2.075\n > t.pdf( 1.5 )\n ~0.126\n > t.quantile( 0.8 )\n ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n Returns the variance of a Student's t distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `1 < v <= 2`, the function returns positive infinity.\n\n If provided `v <= 1`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.t.variance( 9.0 )\n ~1.286\n > v = base.dists.t.variance( 4.5 )\n ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n 0.875\n > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n 0.75\n > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.278\n > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n > var y = mycdf( 0.5 )\n 0.0125\n > y = mycdf( 8.0 )\n 0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n Returns the differential entropy of a triangular distribution (in nats).\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n ~-0.193\n > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n ~1.886\n > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n Returns the excess kurtosis of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n -0.6\n > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n -0.6\n > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.134\n > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n ~-0.288\n > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n ~-1.281\n > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n cdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n > var y = mylogcdf( 0.5 )\n ~-4.382\n > y = mylogcdf( 8.0 )\n ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n ~-0.693\n > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n 0.0\n > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n ~-2.89\n > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n -Infinity\n > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n > var y = mylogpdf( 2.0 )\n ~-2.526\n > y = mylogpdf( 12.0 )\n -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n Returns the expected value of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n ~0.6\n > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n 7.0\n > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n Returns the median of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n ~0.632\n > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n ~6.708\n > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n ~1.021\n > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n ~1.111\n > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n ~24.334\n > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n ~1.381\n > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n > var y = mymgf( -1.0 )\n ~0.3996\n > y = mymgf( 2.0 )\n ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n Returns the mode of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n 0.8\n > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n 5.0\n > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n 5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n 0.5\n > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n 1.0\n > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n ~0.056\n > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n 0.0\n > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n NaN\n > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n > var y = mypdf( 2.0 )\n 0.08\n > y = mypdf( 12.0 )\n 0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n ~0.553\n > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n ~-0.452\n > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n -14.0\n > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n ~11.056\n\n > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n NaN\n > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n NaN\n\n > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n NaN\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n NaN\n\n > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n > var y = myquantile( 0.4 )\n ~2.658\n > y = myquantile( 0.8 )\n ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n Returns the skewness of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n ~-0.476\n > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n ~0.532\n > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n 0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n Returns the standard deviation of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n ~0.216\n > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n ~1.78\n > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n Returns a triangular distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n c: number (optional)\n Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n Returns\n -------\n triangular: Object\n Distribution instance.\n\n triangular.a: number\n Minimum support. If set, the value must be smaller or equal to `b` and\n `c`.\n\n triangular.b: number\n Maximum support. If set, the value must be greater than or equal to `a`\n and `c`.\n\n triangular.c: number\n Mode. If set, the value must be greater than or equal to `a` and smaller\n than or equal to `b`.\n\n triangular.entropy: number\n Read-only property which returns the differential entropy.\n\n triangular.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n triangular.mean: number\n Read-only property which returns the expected value.\n\n triangular.median: number\n Read-only property which returns the median.\n\n triangular.mode: number\n Read-only property which returns the mode.\n\n triangular.skewness: number\n Read-only property which returns the skewness.\n\n triangular.stdev: number\n Read-only property which returns the standard deviation.\n\n triangular.variance: number\n Read-only property which returns the variance.\n\n triangular.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n triangular.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n triangular.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n triangular.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n triangular.pdf: Function\n Evaluates the probability density function (PDF).\n\n triangular.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n > triangular.a\n 0.0\n > triangular.b\n 1.0\n > triangular.c\n 0.5\n > triangular.entropy\n ~-0.193\n > triangular.kurtosis\n -0.6\n > triangular.mean\n 0.5\n > triangular.median\n 0.5\n > triangular.mode\n 0.5\n > triangular.skewness\n 0.0\n > triangular.stdev\n ~0.204\n > triangular.variance\n ~0.042\n > triangular.cdf( 0.8 )\n 0.92\n > triangular.logcdf( 0.8 )\n ~-0.083\n > triangular.logpdf( 0.8 )\n ~-0.223\n > triangular.mgf( 0.8 )\n ~1.512\n > triangular.pdf( 0.8 )\n ~0.8\n > triangular.quantile( 0.8 )\n ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n Returns the variance of a triangular distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n ~0.047\n > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n ~3.167\n > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n 0.9\n > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n 0.25\n > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n 1.0\n > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n > var y = mycdf( 0.5 )\n 0.05\n > y = mycdf( 8.0 )\n 0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n Returns the differential entropy of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Differential entropy.\n\n Examples\n --------\n > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.entropy( 4.0, 12.0 )\n ~2.079\n > v = base.dists.uniform.entropy( 2.0, 8.0 )\n ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n Returns the excess kurtosis of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n -1.2\n > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a uniform distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n ~-0.105\n > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n ~-1.386\n > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n 0.0\n > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logcdf: Function\n Logarithm of Cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n > var y = mylogcdf( 0.5 )\n ~-2.996\n > y = mylogcdf( 8.0 )\n ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a uniform distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n ~-1.386\n > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n -Infinity\n > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n 0.0\n > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -Infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n > var y = mylogPDF( 7.0 )\n 0.0\n > y = mylogPDF( 5.0 )\n -Infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n Returns the expected value of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.uniform.mean( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.mean( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.mean( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n Returns the median of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.uniform.median( 0.0, 1.0 )\n 0.5\n > v = base.dists.uniform.median( 4.0, 12.0 )\n 8.0\n > v = base.dists.uniform.median( 2.0, 8.0 )\n 5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n t: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n ~372.495\n > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n ~0.688\n > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n ~3.195\n > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n NaN\n > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n > var y = mymgf( 0.1 )\n ~1.916\n > y = mymgf( 1.1 )\n ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n 0.25\n > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n 0.0\n > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n 1.0\n > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n > var y = myPDF( 7.0 )\n 1.0\n > y = myPDF( 5.0 )\n 0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n 0.8\n > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n 5.0\n\n > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n NaN\n\n > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n > var y = myQuantile( 0.8 )\n 3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n Returns the skewness of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n 0.0\n > v = base.dists.uniform.skewness( 4.0, 12.0 )\n 0.0\n > v = base.dists.uniform.skewness( 2.0, 8.0 )\n 0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n Returns the standard deviation of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n ~0.289\n > v = base.dists.uniform.stdev( 4.0, 12.0 )\n ~2.309\n > v = base.dists.uniform.stdev( 2.0, 8.0 )\n ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n Returns a uniform distribution object.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n b: number (optional)\n Maximum support. Must be greater than `a`. Default: `1.0`.\n\n Returns\n -------\n uniform: Object\n Distribution instance.\n\n uniform.a: number\n Minimum support. If set, the value must be smaller than `b`.\n\n uniform.b: number\n Maximum support. If set, the value must be greater than `a`.\n\n uniform.entropy: number\n Read-only property which returns the differential entropy.\n\n uniform.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n uniform.mean: number\n Read-only property which returns the expected value.\n\n uniform.median: number\n Read-only property which returns the median.\n\n uniform.skewness: number\n Read-only property which returns the skewness.\n\n uniform.stdev: number\n Read-only property which returns the standard deviation.\n\n uniform.variance: number\n Read-only property which returns the variance.\n\n uniform.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n uniform.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n uniform.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n uniform.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n uniform.pdf: Function\n Evaluates the probability density function (PDF).\n\n uniform.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n > uniform.a\n 0.0\n > uniform.b\n 1.0\n > uniform.entropy\n 0.0\n > uniform.kurtosis\n -1.2\n > uniform.mean\n 0.5\n > uniform.median\n 0.5\n > uniform.skewness\n 0.0\n > uniform.stdev\n ~0.289\n > uniform.variance\n ~0.083\n > uniform.cdf( 0.8 )\n 0.8\n > uniform.logcdf( 0.5 )\n ~-0.693\n > uniform.logpdf( 1.0 )\n ~-0.0\n > uniform.mgf( 0.8 )\n ~1.532\n > uniform.pdf( 0.8 )\n 1.0\n > uniform.quantile( 0.8 )\n 0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n Returns the variance of a uniform distribution.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `a >= b`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.uniform.variance( 0.0, 1.0 )\n ~0.083\n > v = base.dists.uniform.variance( 4.0, 12.0 )\n ~5.333\n > v = base.dists.uniform.variance( 2.0, 8.0 )\n 3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated CDF.\n\n Examples\n --------\n > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n ~0.865\n > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n 1.0\n > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n cdf: Function\n Cumulative distribution function (CDF).\n\n Examples\n --------\n > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n > var y = myCDF( 12.0 )\n ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n Returns the differential entropy of a Weibull distribution (in nats).\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Entropy.\n\n Examples\n --------\n > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.entropy( 4.0, 12.0 )\n ~2.532\n > v = base.dists.weibull.entropy( 8.0, 2.0 )\n ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n Returns the excess kurtosis of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Excess kurtosis.\n\n Examples\n --------\n > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n 6.0\n > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n ~-0.252\n > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Weibull distribution with shape parameter `k` and scale\n parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logCDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n ~-0.145\n > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logcdf: Function\n Logarithm of cumulative distribution function (CDF).\n\n Examples\n --------\n > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n > var y = mylogcdf( 12.0 )\n ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Weibull distribution with shape parameter `k` and scale parameter `λ`\n at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated logPDF.\n\n Examples\n --------\n > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n ~-3.307\n > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n ~-0.1\n > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n -Infinity\n > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n logpdf: Function\n Logarithm of probability density function (PDF).\n\n Examples\n --------\n > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n > y = mylofpdf( 7.0 )\n ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n Returns the expected value of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Expected value.\n\n Examples\n --------\n > var v = base.dists.weibull.mean( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.mean( 4.0, 12.0 )\n ~10.877\n > v = base.dists.weibull.mean( 8.0, 2.0 )\n ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n Returns the median of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Median.\n\n Examples\n --------\n > var v = base.dists.weibull.median( 1.0, 1.0 )\n ~0.693\n > v = base.dists.weibull.median( 4.0, 12.0 )\n ~10.949\n > v = base.dists.weibull.median( 8.0, 2.0 )\n ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated MGF.\n\n Examples\n --------\n > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n ~2.0\n > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n ~0.019\n\n > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n NaN\n\n > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n NaN\n > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n mgf: Function\n Moment-generating function (MGF).\n\n Examples\n --------\n > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n > var y = myMGF( 0.8 )\n ~3150.149\n > y = myMGF( 0.08 )\n ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n Returns the mode of a Weibull distribution.\n\n If `0 < k <= 1`, the function returns `0.0`.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Mode.\n\n Examples\n --------\n > var v = base.dists.weibull.mode( 1.0, 1.0 )\n 0.0\n > v = base.dists.weibull.mode( 4.0, 12.0 )\n ~11.167\n > v = base.dists.weibull.mode( 8.0, 2.0 )\n ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated PDF.\n\n Examples\n --------\n > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n ~0.037\n > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n ~0.905\n > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n 0.0\n > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n NaN\n > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n pdf: Function\n Probability density function (PDF).\n\n Examples\n --------\n > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n > var y = myPDF( 7.0 )\n ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input probability.\n\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Evaluated quantile function.\n\n Examples\n --------\n > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n ~1.609\n > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n ~3.33\n\n > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n NaN\n\n > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n NaN\n > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n NaN\n\n > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n quantile: Function\n Quantile function.\n\n Examples\n --------\n > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n > var y = myQuantile( 0.4 )\n ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n Returns the skewness of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Skewness.\n\n Examples\n --------\n > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n 2.0\n > v = base.dists.weibull.skewness( 4.0, 12.0 )\n ~-0.087\n > v = base.dists.weibull.skewness( 8.0, 2.0 )\n ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n Returns the standard deviation of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Standard deviation.\n\n Examples\n --------\n > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.stdev( 4.0, 12.0 )\n ~3.051\n > v = base.dists.weibull.stdev( 8.0, 2.0 )\n ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n Returns the variance of a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n out: number\n Variance.\n\n Examples\n --------\n > var v = base.dists.weibull.variance( 1.0, 1.0 )\n 1.0\n > v = base.dists.weibull.variance( 4.0, 12.0 )\n ~9.311\n > v = base.dists.weibull.variance( 8.0, 2.0 )\n ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n Returns a Weibull distribution object.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n λ: number (optional)\n Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n Returns\n -------\n weibull: Object\n Distribution instance.\n\n weibull.k: number\n Shape parameter. If set, the value must be greater than `0`.\n\n weibull.lambda: number\n Scale parameter. If set, the value must be greater than `0`.\n\n weibull.entropy: number\n Read-only property which returns the differential entropy.\n\n weibull.kurtosis: number\n Read-only property which returns the excess kurtosis.\n\n weibull.mean: number\n Read-only property which returns the expected value.\n\n weibull.median: number\n Read-only property which returns the median.\n\n weibull.mode: number\n Read-only property which returns the mode.\n\n weibull.skewness: number\n Read-only property which returns the skewness.\n\n weibull.stdev: number\n Read-only property which returns the standard deviation.\n\n weibull.variance: number\n Read-only property which returns the variance.\n\n weibull.cdf: Function\n Evaluates the cumulative distribution function (CDF).\n\n weibull.logcdf: Function\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF).\n\n weibull.logpdf: Function\n Evaluates the natural logarithm of the probability density function\n (PDF).\n\n weibull.mgf: Function\n Evaluates the moment-generating function (MGF).\n\n weibull.pdf: Function\n Evaluates the probability density function (PDF).\n\n weibull.quantile: Function\n Evaluates the quantile function at probability `p`.\n\n Examples\n --------\n > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n > weibull.k\n 6.0\n > weibull.lambda\n 5.0\n > weibull.entropy\n ~1.299\n > weibull.kurtosis\n ~0.035\n > weibull.mean\n ~4.639\n > weibull.median\n ~4.704\n > weibull.mode\n ~4.85\n > weibull.skewness\n ~-0.373\n > weibull.stdev\n ~0.899\n > weibull.variance\n ~0.808\n > weibull.cdf( 3.0 )\n ~0.046\n > weibull.logcdf( 3.0 )\n ~-3.088\n > weibull.logpdf( 1.0 )\n ~-7.865\n > weibull.mgf( -0.5 )\n ~0.075\n > weibull.pdf( 3.0 )\n ~0.089\n > weibull.quantile( 0.8 )\n ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n Computes the complete elliptic integral of the second kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipe( 0.5 )\n ~1.351\n > y = base.ellipe( -1.0 )\n ~1.910\n > y = base.ellipe( 2.0 )\n NaN\n > y = base.ellipe( PINF )\n NaN\n > y = base.ellipe( NINF )\n NaN\n > y = base.ellipe( NaN )\n NaN\n\n See Also\n --------\n base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: Array\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var v = base.ellipj( 0.3, 0.5 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > v = base.ellipj( 0.0, 0.0 )\n [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n > v = base.ellipj( Infinity, 1.0 )\n [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n > v = base.ellipj( 0.0, -2.0)\n [ ~0.0, ~1.0, ~1.0, NaN ]\n > v = base.ellipj( NaN, NaN )\n [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true\n\n\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293\n\n\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956\n\n\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978\n\n\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Jacobi elliptic functions and Jacobi amplitude.\n\n Examples\n --------\n > var out = new Float64Array( 4 );\n > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n > var bool = ( v === out )\n true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n Computes the Jacobi elliptic function sn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function sn.\n\n Examples\n --------\n > var v = base.ellipj.sn( 0.3, 0.5 )\n ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n Computes the Jacobi elliptic functions cn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function cn.\n\n Examples\n --------\n > var v = base.ellipj.cn( 0.3, 0.5 )\n ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n Computes the Jacobi elliptic function dn.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function dn.\n\n Examples\n --------\n > var v = base.ellipj.dn( 0.3, 0.5 )\n ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n Computes the Jacobi amplitude am.\n\n Parameters\n ----------\n u: number\n Input value.\n\n m: number\n Modulus m, equivalent to k².\n\n Returns\n -------\n out: number\n Jacobi elliptic function am.\n\n Examples\n --------\n > var v = base.ellipj.am( 0.3, 0.5 )\n ~0.298\n\n See Also\n --------\n base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n Computes the complete elliptic integral of the first kind.\n\n Parameters\n ----------\n m: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ellipk( 0.5 )\n ~1.854\n > y = base.ellipk( -1.0 )\n ~1.311\n > y = base.ellipk( 2.0 )\n NaN\n > y = base.ellipk( PINF )\n NaN\n > y = base.ellipk( NINF )\n NaN\n > y = base.ellipk( NaN )\n NaN\n\n See Also\n --------\n base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, and is thus\n equivalent to `str.length + len`. Default: str.length.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = base.endsWith( 'beep', 'ep', 4 )\n true\n > bool = base.endsWith( 'Beep', 'op', 4 )\n false\n > bool = base.endsWith( 'Beep', 'ee', 3 )\n true\n > bool = base.endsWith( 'Beep', 'ee', -1 )\n true\n > bool = base.endsWith( 'beep', '', 4 )\n true\n\n See Also\n --------\n base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If computing the relative difference in units of epsilon will result in\n overflow, the function returns the maximum double-precision floating-point\n number.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference in units of double-precision floating-point epsilon.\n\n Examples\n --------\n > var d = base.epsdiff( 12.15, 12.149999999999999 )\n ~0.658\n > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n ~64761.512\n\n // Custom scale function:\n > function scale( x, y ) { return ( x > y ) ? y : x; };\n > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n ~44\n\n See Also\n --------\n base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n Evaluates the error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erf( 2.0 )\n ~0.9953\n > y = base.erf( -1.0 )\n ~-0.8427\n > y = base.erf( -0.0 )\n -0.0\n > y = base.erf( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n Evaluates the complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfc( 2.0 )\n ~0.0047\n > y = base.erfc( -1.0 )\n ~1.8427\n > y = base.erfc( 0.0 )\n 1.0\n > y = base.erfc( PINF )\n 0.0\n > y = base.erfc( NINF )\n 2.0\n > y = base.erfc( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n Evaluates the inverse complementary error function.\n\n The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcinv( 0.5 )\n ~0.4769\n > y = base.erfcinv( 0.8 )\n ~0.1791\n > y = base.erfcinv( 0.0 )\n Infinity\n > y = base.erfcinv( 2.0 )\n -Infinity\n > y = base.erfcinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n Evaluates the scaled complementary error function.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfcx( 1.0 )\n ~0.4276\n > y = base.erfcx( -1.0 )\n ~5.01\n > y = base.erfcx( 0.0 )\n 1.0\n > y = base.erfcx( NaN )\n NaN\n\n See Also\n --------\n base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n Evaluates the inverse error function.\n\n If `|x| > 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.erfinv( 0.5 )\n ~0.4769\n > y = base.erfinv( 0.8 )\n ~0.9062\n > y = base.erfinv( 0.0 )\n 0.0\n > y = base.erfinv( -0.0 )\n -0.0\n > y = base.erfinv( -1.0 )\n -Infinity\n > y = base.erfinv( 1.0 )\n Infinity\n > y = base.erfinv( NaN )\n NaN\n\n See Also\n --------\n base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.eta( 0.0 )\n 0.5\n > y = base.eta( -1.0 )\n 0.25\n > y = base.eta( 1.0 )\n ~0.6931\n > y = base.eta( 3.14 )\n ~0.9096\n > y = base.eta( NaN )\n NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n out: number\n Evaluated polynomial.\n\n Examples\n --------\n > var arr = [ 3.0, 2.0, 1.0 ];\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = base.evalpoly( arr, 10.0 )\n 123.0\n\n\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n c: Array\n Polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a polynomial.\n\n Examples\n --------\n > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n // 3*10^0 + 2*10^1 + 1*10^2\n > var v = f( 10.0 )\n 123.0\n\n // 3*5^0 + 2*5^1 + 1*5^2\n > v = f( 5.0 )\n 38.0\n\n See Also\n --------\n base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n\n A rational function `f(x)` is defined as\n\n P(x)\n f(x) = ----\n Q(x)\n\n where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n For polynomials of different degree, the coefficient array for the lower\n degree polynomial should be padded with zeros.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n x: number\n Value at which to evaluate the rational function.\n\n Returns\n -------\n out: number\n Evaluated rational function.\n\n Examples\n --------\n // 2x^3 + 4x^2 - 5x^1 - 6x^0\n > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n // 0.5x^1 + 3x^0\n > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n // Evaluate the rational function:\n > var v = base.evalrational( P, Q, 6.0 )\n 90.0\n\n\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n\n Parameters\n ----------\n P: Array\n Numerator polynomial coefficients sorted in ascending degree.\n\n Q: Array\n Denominator polynomial coefficients sorted in ascending degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a rational function.\n\n Examples\n --------\n > var P = [ 20.0, 8.0, 3.0 ];\n > var Q = [ 10.0, 9.0, 1.0 ];\n > var f = base.evalrational.factory( P, Q );\n\n // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n > var v = f( 10.0 )\n 2.0\n\n // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n > v = f( 2.0 )\n 1.5\n\n See Also\n --------\n base.evalpoly","base.exp":"\nbase.exp( x )\n Evaluates the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp( 4.0 )\n ~54.5982\n > y = base.exp( -9.0 )\n ~1.234e-4\n > y = base.exp( 0.0 )\n 1.0\n > y = base.exp( NaN )\n NaN\n\n See Also\n --------\n base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n Evaluates the base 2 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp2( 3.0 )\n 8.0\n > y = base.exp2( -9.0 )\n ~0.002\n > y = base.exp2( 0.0 )\n 1.0\n > y = base.exp2( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n Evaluates the base 10 exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.exp10( 3.0 )\n 1000\n > y = base.exp10( -9.0 )\n 1.0e-9\n > y = base.exp10( 0.0 )\n 1.0\n > y = base.exp10( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n Evaluates the standard logistic function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expit( 0.0 )\n 0.5\n > y = base.expit( 1.0 )\n ~0.731\n > y = base.expit( -1.0 )\n ~0.269\n > y = base.expit( Infinity )\n 1.0\n > y = base.expit( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1( 0.2 )\n ~0.221\n > y = base.expm1( -9.0 )\n ~-1.0\n > y = base.expm1( 0.0 )\n 0.0\n > y = base.expm1( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n Relative error exponential.\n\n When `x` is near zero,\n\n e^x - 1\n\n can suffer catastrophic cancellation (i.e., significant loss of precision).\n This function avoids the loss of precision when `x` is near zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.expm1rel( 0.0 )\n 1.0\n > y = base.expm1rel( 1.0 )\n ~1.718\n > y = base.expm1rel( -1.0 )\n ~0.632\n > y = base.expm1rel( NaN )\n NaN\n\t\n See Also\n --------\n base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponent( 3.14e-307 )\n -1019\n > exponent = base.exponent( -3.14 )\n 1\n > exponent = base.exponent( 0.0 )\n -1023\n > exponent = base.exponent( NaN )\n 1024\n\n See Also\n --------\n base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unbiased exponent.\n\n Examples\n --------\n > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n 114\n > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n -112\n > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n 1\n > exponent = base.exponentf( 0.0 )\n -127\n > exponent = base.exponentf( NaN )\n 128\n\n See Also\n --------\n base.exponent\n","base.factorial":"\nbase.factorial( x )\n Evaluates the factorial of `x`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Factorial.\n\n Examples\n --------\n > var y = base.factorial( 3.0 )\n 6.0\n > y = base.factorial( -1.5 )\n ~-3.545\n > y = base.factorial( -0.5 )\n ~1.772\n > y = base.factorial( 0.5 )\n ~0.886\n > y = base.factorial( -10.0 )\n NaN\n > y = base.factorial( 171.0 )\n Infinity\n > y = base.factorial( NaN )\n NaN\n\n See Also\n --------\n base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n Evaluates the double factorial of `n`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: number\n Input value.\n\n Returns\n -------\n y: number\n Double factorial.\n\n Examples\n --------\n > var y = base.factorial2( 3 )\n 3\n > y = base.factorial2( 5 )\n 15\n > y = base.factorial2( 6 )\n 48\n > y = base.factorial2( 301 )\n Infinity\n > y = base.factorial2( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n Evaluates the natural logarithm of the factorial of `x`.\n\n For input values other than negative integers, the function returns\n\n ln( x! ) = ln( Γ(x+1) )\n\n where `Γ` is the Gamma function. For negative integers, the function returns\n `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the factorial of `x`.\n\n Examples\n --------\n > var y = base.factorialln( 3.0 )\n ~1.792\n > y = base.factorialln( 2.4 )\n ~1.092\n > y = base.factorialln( -1.0 )\n NaN\n > y = base.factorialln( -1.5 )\n ~1.266\n > y = base.factorialln( NaN )\n NaN\n\n See Also\n --------\n base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n Computes the falling factorial of `x` and `n`.\n\n If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.fallingFactorial( 0.9, 5 )\n ~0.644\n > v = base.fallingFactorial( -9.0, 3 )\n -990.0\n > v = base.fallingFactorial( 0.0, 2 )\n 0.0\n > v = base.fallingFactorial( 3.0, -2 )\n NaN\n\n See Also\n --------\n base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n Computes the nth Fibonacci number.\n\n Fibonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2}\n\n with seed values F_0 = 0 and F_1 = 1.\n\n If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Fibonacci number.\n\n Examples\n --------\n > var y = base.fibonacci( 0 )\n 0\n > y = base.fibonacci( 1 )\n 1\n > y = base.fibonacci( 2 )\n 1\n > y = base.fibonacci( 3 )\n 2\n > y = base.fibonacci( 4 )\n 3\n > y = base.fibonacci( 79 )\n NaN\n > y = base.fibonacci( NaN )\n NaN\n\n See Also\n --------\n base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n Computes the Fibonacci number index.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n F: integer\n Fibonacci number.\n\n Returns\n -------\n n: number\n Fibonacci number index.\n\n Examples\n --------\n > var n = base.fibonacciIndex( 2 )\n 3\n > n = base.fibonacciIndex( 3 )\n 4\n > n = base.fibonacciIndex( 5 )\n 5\n > n = base.fibonacciIndex( NaN )\n NaN\n > n = base.fibonacciIndex( 1 )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n Evaluates a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Fibonacci polynomial.\n\n Returns\n -------\n out: number\n Evaluated Fibonacci polynomial.\n\n Examples\n --------\n // 2^4 + 3*2^2 + 1\n > var v = base.fibpoly( 5, 2.0 )\n 29.0\n\n\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n Returns a function for evaluating a Fibonacci polynomial.\n\n Parameters\n ----------\n n: integer\n Fibonacci polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Fibonacci polynomial.\n\n Examples\n --------\n > var polyval = base.fibpoly.factory( 5 );\n\n // 1^4 + 3*1^2 + 1\n > var v = polyval( 1.0 )\n 5.0\n\n // 2^4 + 3*2^2 + 1\n > v = polyval( 2.0 )\n 29.0\n\n See Also\n --------\n base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n Returns the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodePoint( 'beep', 1 )\n 'b'\n > out = base.firstCodePoint( 'Boop', 1 )\n 'B'\n > out = base.firstCodePoint( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n Returns the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstCodeUnit( 'beep', 1 )\n 'b'\n > out = base.firstCodeUnit( 'Boop', 1 )\n 'B'\n > out = base.firstCodeUnit( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.firstGraphemeCluster( 'beep', 1 )\n 'b'\n > out = base.firstGraphemeCluster( 'Boop', 1 )\n 'B'\n > out = base.firstGraphemeCluster( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n or `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsign( -3.0, 10.0 )\n -3.0\n > z = base.flipsign( -3.0, -1.0 )\n 3.0\n > z = base.flipsign( 1.0, -0.0 )\n -1.0\n > z = base.flipsign( -3.0, -0.0 )\n 3.0\n > z = base.flipsign( -0.0, 1.0 )\n -0.0\n > z = base.flipsign( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n\n The function only returns `-x` when `y` is a negative number.\n\n According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n `0`. In which case, `NaN` may not correspond to just one but many binary\n representations. Accordingly, care should be taken to ensure that `y` is not\n `NaN`; otherwise, behavior may be indeterminate.\n\n Parameters\n ----------\n x: number\n Number from which to derive a magnitude.\n\n y: number\n Number from which to derive a sign.\n\n Returns\n -------\n z: number\n Single-precision floating-point number.\n\n Examples\n --------\n > var z = base.flipsignf( -3.0, 10.0 )\n -3.0\n > z = base.flipsignf( -3.0, -1.0 )\n 3.0\n > z = base.flipsignf( 1.0, -0.0 )\n -1.0\n > z = base.flipsignf( -3.0, -0.0 )\n 3.0\n > z = base.flipsignf( -0.0, 1.0 )\n -0.0\n > z = base.flipsignf( 0.0, -1.0 )\n -0.0\n\n See Also\n --------\n base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n 0\n > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n -3\n > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToInt32( FLOAT32_PINF )\n 0\n > y = base.float32ToInt32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n 0\n > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n 3\n > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n 4294967293\n > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n 0\n > y = base.float32ToUint32( FLOAT32_PINF )\n 0\n > y = base.float32ToUint32( FLOAT32_NINF )\n 0\n\n See Also\n --------\n base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: float\n Nearest single-precision floating-point number.\n\n Examples\n --------\n > var y = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToInt32( 4294967295.0 )\n -1\n > y = base.float64ToInt32( 3.14 )\n 3\n > y = base.float64ToInt32( -3.14 )\n -3\n > y = base.float64ToInt32( NaN )\n 0\n > y = base.float64ToInt32( PINF )\n 0\n > y = base.float64ToInt32( NINF )\n 0\n\n See Also\n --------\n base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n Returns\n -------\n out: Uint8Array\n Byte array.\n\n Examples\n --------\n > var y = base.float64ToInt64Bytes( 4294967297.0 )\n \n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n\n This function assumes that the input value is less than the maximum safe\n double-precision floating-point integer plus one (i.e., `2**53`).\n\n Parameters\n ----------\n x: integer\n Integer-valued double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Uint8Array( 16 );\n > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n \n\n See Also\n --------\n base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.float64ToUint32( 4294967297.0 )\n 1\n > y = base.float64ToUint32( 3.14 )\n 3\n > y = base.float64ToUint32( -3.14 )\n 4294967293\n > y = base.float64ToUint32( NaN )\n 0\n > y = base.float64ToUint32( PINF )\n 0\n > y = base.float64ToUint32( NINF )\n 0\n\n See Also\n --------\n base.float64ToInt32","base.floor":"\nbase.floor( x )\n Rounds a double-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor( 3.14 )\n 3.0\n > y = base.floor( -4.2 )\n -5.0\n > y = base.floor( -4.6 )\n -5.0\n > y = base.floor( 9.5 )\n 9.0\n > y = base.floor( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor2( 3.14 )\n 2.0\n > y = base.floor2( -4.2 )\n -8.0\n > y = base.floor2( -4.6 )\n -8.0\n > y = base.floor2( 9.5 )\n 8.0\n > y = base.floor2( 13.0 )\n 8.0\n > y = base.floor2( -13.0 )\n -16.0\n > y = base.floor2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floor10( 3.14 )\n 1.0\n > y = base.floor10( -4.2 )\n -10.0\n > y = base.floor10( -4.6 )\n -10.0\n > y = base.floor10( 9.5 )\n 1.0\n > y = base.floor10( 13.0 )\n 10.0\n > y = base.floor10( -13.0 )\n -100.0\n > y = base.floor10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.floorb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward negative infinity:\n > y = base.floorb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n Rounds a single-precision floating-point number toward negative infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorf( 3.14 )\n 3.0\n > y = base.floorf( -4.2 )\n -5.0\n > y = base.floorf( -4.6 )\n -5.0\n > y = base.floorf( 9.5 )\n 9.0\n > y = base.floorf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.floorn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round toward negative infinity behavior:\n > y = base.floorn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.floorn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.floorsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.floorsd( 3.14159, 1, 10 )\n 3.0\n > y = base.floorsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.floorsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePoint( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: code point.\n - index: starting code point index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each Unicode code point in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachCodePointRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: grapheme cluster.\n - index: starting grapheme cluster index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n The function to invoke for each grapheme cluster in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachGraphemeCluster( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n clbk: Function\n Function to invoke for each UTF-16 code unit in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > base.forEachRight( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n Generate string from a token array by interpolating values.\n\n Parameters\n ----------\n tokens: Array\n Array of string parts and format identifier objects.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n 'beep boop'\n > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n 'baz 1.00'\n > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n ' 12'\n\n See Also\n --------\n base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n Tokenize a string into an array of string parts and format identifier\n objects.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of string parts and format identifier objects.\n\n Examples\n --------\n > var out = base.formatTokenize( 'Hello %s!' )\n [ 'Hello ', {...}, '!' ]\n > out = base.formatTokenize( '%s %s %d' )\n [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n > out = base.formatTokenize( 'Pi: %.2f' )\n [ 'Pi: ', {...} ]\n\n See Also\n --------\n base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n Computes the Fresnel integrals S(x) and C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n S(x) and C(x).\n\n Examples\n --------\n > var y = base.fresnel( 0.0 )\n [ ~0.0, ~0.0 ]\n > y = base.fresnel( 1.0 )\n [ ~0.438, ~0.780 ]\n > y = base.fresnel( PINF )\n [ ~0.5, ~0.5 ]\n > y = base.fresnel( NINF )\n [ ~-0.5, ~-0.5 ]\n > y = base.fresnel( NaN )\n [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Destination array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n S(x) and C(x).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~0.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n Computes the Fresnel integral C(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n C(x).\n\n Examples\n --------\n > var y = base.fresnelc( 0.0 )\n ~0.0\n > y = base.fresnelc( 1.0 )\n ~0.780\n > y = base.fresnelc( PINF )\n ~0.5\n > y = base.fresnelc( NINF )\n ~-0.5\n > y = base.fresnelc( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n Computes the Fresnel integral S(x).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n S(x).\n\n Examples\n --------\n > var y = base.fresnels( 0.0 )\n ~0.0\n > y = base.fresnels( 1.0 )\n ~0.438\n > y = base.fresnels( PINF )\n ~0.5\n > y = base.fresnels( NINF )\n ~-0.5\n > y = base.fresnels( NaN )\n NaN\n\n See Also\n --------\n base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = base.frexp( 4.0 )\n [ 0.5, 3 ]\n > out = base.frexp( 0.0 )\n [ 0.0, 0 ]\n > out = base.frexp( -0.0 )\n [ -0.0, 0 ]\n > out = base.frexp( NaN )\n [ NaN, 0 ]\n > out = base.frexp( PINF )\n [ Infinity, 0 ]\n > out = base.frexp( NINF )\n [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n\n The first element of the returned array is the normalized fraction and the\n second is the exponent. The normalized fraction and exponent satisfy the\n relation\n\n x = frac * 2^exp\n\n If provided positive or negative zero, `NaN`, or positive or negative\n infinity, the function returns a two-element array containing the input\n value and an exponent equal to zero.\n\n For all other numeric input values, the absolute value of the normalized\n fraction resides on the interval [0.5,1).\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array\n A normalized fraction and an exponent.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.frexp.assign( 4.0, out, 1, 0 )\n [ 0.5, 3 ]\n > var bool = ( y === out )\n true\n\n See Also\n --------\n base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n Creates a double-precision floating-point number from a literal bit\n representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var bstr;\n > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n > var val = base.fromBinaryString( bstr )\n 4.0\n > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n > val = base.fromBinaryString( bstr )\n 3.141592653589793\n > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n > val = base.fromBinaryString( bstr )\n -1.0e308\n\n // The function handles subnormals:\n > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n > val = base.fromBinaryString( bstr )\n -3.14e-320\n > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n > val = base.fromBinaryString( bstr )\n 5.0e-324\n\n // The function handles special values:\n > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n 0.0\n > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -0.0\n > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n NaN\n > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n Infinity\n > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n > val = base.fromBinaryString( bstr )\n -Infinity\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var bstr = '01000000100000000000000000000000';\n > var val = base.fromBinaryStringf( bstr )\n 4.0\n > bstr = '01000000010010010000111111011011';\n > val = base.fromBinaryStringf( bstr )\n ~3.14\n > bstr = '11111111011011000011101000110011';\n > val = base.fromBinaryStringf( bstr )\n ~-3.14e+38\n\n // The function handles subnormals:\n > bstr = '10000000000000000000000000010110';\n > val = base.fromBinaryStringf( bstr )\n ~-3.08e-44\n > bstr = '00000000000000000000000000000001';\n > val = base.fromBinaryStringf( bstr )\n ~1.40e-45\n\n // The function handles special values:\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n 0.0\n > bstr = '10000000000000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -0.0\n > bstr = '01111111110000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n NaN\n > bstr = '01111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n Infinity\n > bstr = '11111111100000000000000000000000';\n > val = base.fromBinaryStringf( bstr )\n -Infinity\n\n See Also\n --------\n base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n Creates an unsigned 8-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 8-bit integer.\n\n Examples\n --------\n > var bstr = '01010101';\n > var val = base.fromBinaryStringUint8( bstr )\n 85\n > bstr = '00000000';\n > val = base.fromBinaryStringUint8( bstr )\n 0\n > bstr = '00000010';\n > val = base.fromBinaryStringUint8( bstr )\n 2\n > bstr = '11111111';\n > val = base.fromBinaryStringUint8( bstr )\n 255\n\n See Also\n --------\n base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n Creates an unsigned 16-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 16-bit integer.\n\n Examples\n --------\n > var bstr = '0101010101010101';\n > var val = base.fromBinaryStringUint16( bstr )\n 21845\n > bstr = '0000000000000000';\n > val = base.fromBinaryStringUint16( bstr )\n 0\n > bstr = '0000000000000010';\n > val = base.fromBinaryStringUint16( bstr )\n 2\n > bstr = '1111111111111111';\n > val = base.fromBinaryStringUint16( bstr )\n 65535\n\n See Also\n --------\n base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n Creates an unsigned 32-bit integer from a literal bit representation.\n\n Parameters\n ----------\n bstr: string\n Literal bit representation.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var bstr = '01010101010101010101010101010101';\n > var val = base.fromBinaryStringUint32( bstr )\n 1431655765\n > bstr = '00000000000000000000000000000000';\n > val = base.fromBinaryStringUint32( bstr )\n 0\n > bstr = '00000000000000000000000000000010';\n > val = base.fromBinaryStringUint32( bstr )\n 2\n > bstr = '11111111111111111111111111111111';\n > val = base.fromBinaryStringUint32( bstr )\n 4294967295\n\n See Also\n --------\n base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n\n The function assumes host byte order (endianness).\n\n Parameters\n ----------\n bytes: Array|TypedArray|Object\n Byte array.\n\n stride: integer\n Index stride.\n\n offset: integer\n Index offset.\n\n Returns\n -------\n out: number\n Number.\n\n Examples\n --------\n > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n > var y = base.fromInt64Bytes( bytes, 1, 0 )\n -1.0\n\n See Also\n --------\n base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n\n Parameters\n ----------\n word: integer\n Unsigned integer.\n\n Returns\n -------\n out: float\n Single-precision floating-point number.\n\n Examples\n --------\n > var word = 1068180177; // => 0 01111111 01010110010001011010001\n > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n 1.3370000123977661\n\n See Also\n --------\n base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n Parameters\n ----------\n high: integer\n Higher order word (unsigned 32-bit integer).\n\n low: integer\n Lower order word (unsigned 32-bit integer).\n\n Returns\n -------\n out: number\n Double-precision floating-point number.\n\n Examples\n --------\n > var v = base.fromWords( 1774486211, 2479577218 )\n 3.14e201\n > v = base.fromWords( 3221823995, 1413754136 )\n -3.141592653589793\n > v = base.fromWords( 0, 0 )\n 0.0\n > v = base.fromWords( 2147483648, 0 )\n -0.0\n > v = base.fromWords( 2146959360, 0 )\n NaN\n > v = base.fromWords( 2146435072, 0 )\n Infinity\n > v = base.fromWords( 4293918720, 0 )\n -Infinity\n\n See Also\n --------\n base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n Evaluates the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma( 4.0 )\n 6.0\n > y = base.gamma( -1.5 )\n ~2.363\n > y = base.gamma( -0.5 )\n ~-3.545\n > y = base.gamma( 0.5 )\n ~1.772\n > y = base.gamma( 0.0 )\n Infinity\n > y = base.gamma( -0.0 )\n -Infinity\n > y = base.gamma( NaN )\n NaN\n\n See Also\n --------\n base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gamma1pm1( 0.2 )\n ~-0.082\n > y = base.gamma1pm1( -6.7 )\n ~-0.991\n > y = base.gamma1pm1( 0.0 )\n 0.0\n > y = base.gamma1pm1( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n Computes the ratio of two gamma functions.\n\n The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n Parameters\n ----------\n z: number\n First gamma parameter.\n\n delta: number\n Difference.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n ~0.042\n > y = base.gammaDeltaRatio( 4.0, 0.5 )\n ~0.516\n > y = base.gammaDeltaRatio( 100.0, 0.0 )\n 1.0\n > y = base.gammaDeltaRatio( NaN, 3.0 )\n NaN\n > y = base.gammaDeltaRatio( 5.0, NaN )\n NaN\n > y = base.gammaDeltaRatio( NaN, NaN )\n NaN\n\n See Also\n --------\n base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n Computes the regularized incomplete gamma function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete gamma functions, respectively.\n\n If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n s: number\n Second function parameter.\n\n regularized: boolean (optional)\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete gamma function. Default: `true`.\n\n upper: boolean (optional)\n Boolean indicating whether the function should return the upper tail of\n the incomplete gamma function. Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammainc( 6.0, 2.0 )\n ~0.9826\n > y = base.gammainc( 1.0, 2.0, true, true )\n ~0.7358\n > y = base.gammainc( 7.0, 5.0 )\n ~0.8270\n > y = base.gammainc( 7.0, 5.0, false )\n ~19.8482\n > y = base.gammainc( NaN, 2.0 )\n NaN\n > y = base.gammainc( 6.0, NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n Computes the inverse of the lower incomplete gamma function.\n\n In contrast to a more commonly used definition, the first argument is the\n probability `p` and the second argument is the scale factor `a`.\n\n By default, the function inverts the lower regularized incomplete gamma\n function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n argument to `true`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Probability.\n\n a: number\n Scale parameter.\n\n upper: boolean (optional)\n Boolean indicating if the function should invert the upper tail of the\n incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n Default: `false`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.gammaincinv( 0.5, 2.0 )\n ~1.678\n > y = base.gammaincinv( 0.1, 10.0 )\n ~6.221\n > y = base.gammaincinv( 0.75, 3.0 )\n ~3.92\n > y = base.gammaincinv( 0.75, 3.0, true )\n ~1.727\n > y = base.gammaincinv( 0.75, NaN )\n NaN\n > y = base.gammaincinv( NaN, 3.0 )\n NaN\n\n See Also\n --------\n base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n Calculates the Lanczos sum for the approximation of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSum( 4.0 )\n ~950.366\n > y = base.gammaLanczosSum( -1.5 )\n ~1373366.245\n > y = base.gammaLanczosSum( -0.5 )\n ~-699841.735\n > y = base.gammaLanczosSum( 0.5 )\n ~96074.186\n > y = base.gammaLanczosSum( 0.0 )\n Infinity\n > y = base.gammaLanczosSum( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Scaled Lanczos sum.\n\n Examples\n --------\n > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n ~0.018\n > y = base.gammaLanczosSumExpGScaled( -1.5 )\n ~25.337\n > y = base.gammaLanczosSumExpGScaled( -0.5 )\n ~-12.911\n > y = base.gammaLanczosSumExpGScaled( 0.5 )\n ~1.772\n > y = base.gammaLanczosSumExpGScaled( 0.0 )\n Infinity\n > y = base.gammaLanczosSumExpGScaled( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n Evaluates the natural logarithm of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Natural logarithm of the gamma function.\n\n Examples\n --------\n > var y = base.gammaln( 1.0 )\n 0.0\n > y = base.gammaln( 2.0 )\n 0.0\n > y = base.gammaln( 4.0 )\n ~1.792\n > y = base.gammaln( -0.5 )\n ~1.266\n > y = base.gammaln( 0.5 )\n ~0.572\n > y = base.gammaln( 0.0 )\n Infinity\n > y = base.gammaln( NaN )\n NaN\n\n See Also\n --------\n base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n Computes the sign of the gamma function.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Sign of the gamma function.\n\n Examples\n --------\n > var y = base.gammasgn( 1.0 )\n 1.0\n > y = base.gammasgn( -2.5 )\n -1.0\n > y = base.gammasgn( 0.0 )\n 0.0\n > y = base.gammasgn( NaN )\n NaN\n\n See Also\n --------\n base.gamma","base.gcd":"\nbase.gcd( a, b )\n Computes the greatest common divisor (gcd).\n\n If both `a` and `b` are `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First number.\n\n b: integer\n Second number.\n\n Returns\n -------\n out: integer\n Greatest common divisor.\n\n Examples\n --------\n > var v = base.gcd( 48, 18 )\n 6\n\n See Also\n --------\n base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Higher order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getHighWord( 3.14e201 )\n 1774486211\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: integer\n Lower order word (unsigned 32-bit integer).\n\n Examples\n --------\n > var w = base.getLowWord( 3.14e201 )\n 2479577218\n\n See Also\n --------\n base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n Computes the half-value coversed cosine.\n\n The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed cosine.\n\n Examples\n --------\n > var y = base.hacovercos( 3.14 )\n ~0.5008\n > y = base.hacovercos( -4.2 )\n ~0.9358\n > y = base.hacovercos( -4.6 )\n ~0.9968\n > y = base.hacovercos( 9.5 )\n ~0.4624\n > y = base.hacovercos( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n Computes the half-value coversed sine.\n\n The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value coversed sine.\n\n Examples\n --------\n > var y = base.hacoversin( 3.14 )\n ~0.4992\n > y = base.hacoversin( -4.2 )\n ~0.0642\n > y = base.hacoversin( -4.6 )\n ~0.0032\n > y = base.hacoversin( 9.5 )\n ~0.538\n > y = base.hacoversin( -0.0 )\n 0.5\n\n See Also\n --------\n base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n Computes the half-value versed cosine.\n\n The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed cosine.\n\n Examples\n --------\n > var y = base.havercos( 3.14 )\n ~0.0\n > y = base.havercos( -4.2 )\n ~0.2549\n > y = base.havercos( -4.6 )\n ~0.4439\n > y = base.havercos( 9.5 )\n ~0.0014\n > y = base.havercos( -0.0 )\n 1.0\n\n See Also\n --------\n base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n Computes the half-value versed sine.\n\n The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Half-value versed sine.\n\n Examples\n --------\n > var y = base.haversin( 3.14 )\n ~1.0\n > y = base.haversin( -4.2 )\n ~0.7451\n > y = base.haversin( -4.6 )\n ~0.5561\n > y = base.haversin( 9.5 )\n ~0.9986\n > y = base.haversin( -0.0 )\n 0.0\n\n See Also\n --------\n base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = base.headercase( 'Hello World!' )\n 'Hello-World'\n > out = base.headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n Evaluates the Heaviside function.\n\n The `continuity` parameter may be one of the following:\n\n - 'half-maximum': if `x == 0`, the function returns `0.5`.\n - 'left-continuous': if `x == 0`, the function returns `0`.\n - 'right-continuous': if `x == 0`, the function returns `1`.\n\n By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n discontinuous).\n\n Parameters\n ----------\n x: number\n Input value.\n\n continuity: string (optional)\n Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n returns `NaN`.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.heaviside( 3.14 )\n 1.0\n > y = base.heaviside( -3.14 )\n 0.0\n > y = base.heaviside( 0.0 )\n NaN\n > y = base.heaviside( 0.0, 'half-maximum' )\n 0.5\n > y = base.heaviside( 0.0, 'left-continuous' )\n 0.0\n > y = base.heaviside( 0.0, 'right-continuous' )\n 1.0\n\n See Also\n --------\n base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n Evaluates a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.hermitepoly( 1, 0.5 )\n 1.0\n > y = base.hermitepoly( -1, 0.5 )\n NaN\n > y = base.hermitepoly( 0, 0.5 )\n 1.0\n > y = base.hermitepoly( 2, 0.5 )\n -1.0\n\n\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n Returns a function for evaluating a physicist's Hermite polynomial.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a physicist's Hermite polynomial.\n\n Examples\n --------\n > var polyval = base.hermitepoly.factory( 2 );\n > var v = polyval( 0.5 )\n -1.0\n\n See Also\n --------\n base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n Computes the hypotenuse avoiding overflow and underflow.\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypot( -5.0, 12.0 )\n 13.0\n > h = base.hypot( NaN, 12.0 )\n NaN\n > h = base.hypot( -0.0, -0.0 )\n 0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n If either argument is `NaN` and the other argument is not `+-Infinity`,\n the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = base.hypotf( -5.0, 12.0 )\n 13.0\n > h = base.hypotf( NaN, 12.0 )\n NaN\n > h = base.hypotf( -0.0, -0.0 )\n 0.0\n\n See Also\n --------\n base.hypot\n","base.identity":"\nbase.identity( x )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identity( -1.0 )\n -1.0\n > y = base.identity( 2.0 )\n 2.0\n > y = base.identity( 0.0 )\n 0.0\n > y = base.identity( -0.0 )\n -0.0\n > y = base.identity( NaN )\n NaN\n\n See Also\n --------\n base.identityf\n","base.identityf":"\nbase.identityf( x )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Input value.\n\n Examples\n --------\n > var y = base.identityf( -1.0 )\n -1.0\n > y = base.identityf( 2.0 )\n 2.0\n > y = base.identityf( 0.0 )\n 0.0\n > y = base.identityf( -0.0 )\n -0.0\n > y = base.identityf( NaN )\n NaN\n\n See Also\n --------\n base.identity\n","base.imul":"\nbase.imul( a, b )\n Performs C-like multiplication of two signed 32-bit integers.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.imul( -10|0, 4|0 )\n -40\n\n See Also\n --------\n base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.imuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Signed 32-bit integer.\n\n b: integer\n Signed 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n Converts an integer to a Slice object.\n\n In strict mode, the function returns an error object if an input value\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n max: integer\n Index upper bound (exclusive).\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s = base.int2slice( -1, 5, false );\n > s.start\n 4\n > s.stop\n 5\n > s.step\n 1\n\n See Also\n --------\n base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n 4294967264\n > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n 3\n\n See Also\n --------\n base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.inv( -1.0 )\n -1.0\n > y = base.inv( 2.0 )\n 0.5\n > y = base.inv( 0.0 )\n Infinity\n > y = base.inv( -0.0 )\n -Infinity\n > y = base.inv( NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.invcase":"\nbase.invcase( str )\n Converts a string to inverse case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Inverse-cased string.\n\n Examples\n --------\n > var out = base.invcase( 'Hello World!' )\n 'hELLO wORLD!'\n > out = base.invcase( 'I am A tiny LITTLE teapot' )\n 'i AM a TINY little TEAPOT'\n\n See Also\n --------\n base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n\n The multiplicative inverse is defined as `1/x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Multiplicative inverse.\n\n Examples\n --------\n > var y = base.invf( -1.0 )\n -1.0\n > y = base.invf( 2.0 )\n 0.5\n > y = base.invf( 0.0 )\n Infinity\n > y = base.invf( -0.0 )\n -Infinity\n > y = base.invf( NaN )\n NaN\n\n See Also\n --------\n base.inv\n","base.isComposite":"\nbase.isComposite( x )\n Tests if a number is composite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a composite number.\n\n Examples\n --------\n > var bool = base.isComposite( 10.0 )\n true\n > bool = base.isComposite( 11.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n Tests if two numbers are coprime.\n\n Parameters\n ----------\n a: number\n First value.\n\n b: number\n Second value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the values are coprime.\n\n Examples\n --------\n > var bool = base.isCoprime( 14.0, 15.0 )\n true\n > bool = base.isCoprime( 14.0, 21.0 )\n false\n\n See Also\n --------\n base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n Tests if a finite numeric value is an even number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEven( 5.0 )\n false\n > bool = base.isEven( -2.0 )\n true\n > bool = base.isEven( 0.0 )\n true\n > bool = base.isEven( NaN )\n false\n\n See Also\n --------\n base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n Tests if a 32-bit integer is even.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an even number.\n\n Examples\n --------\n > var bool = base.isEvenInt32( 5 )\n false\n > bool = base.isEvenInt32( -2 )\n true\n > bool = base.isEvenInt32( 0 )\n true\n\n See Also\n --------\n base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n Tests if a double-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinite( 5.0 )\n true\n > bool = base.isFinite( -2.0e64 )\n true\n > bool = base.isFinite( PINF )\n false\n > bool = base.isFinite( NINF )\n false\n\n See Also\n --------\n base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n Tests if a single-precision floating-point numeric value is finite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is finite.\n\n Examples\n --------\n > var bool = base.isFinitef( 5.0 )\n true\n > bool = base.isFinitef( -1.0e38 )\n true\n > bool = base.isFinitef( FLOAT32_PINF )\n false\n > bool = base.isFinitef( FLOAT32_NINF )\n false\n\n See Also\n --------\n base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n Tests if a double-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinite( PINF )\n true\n > bool = base.isInfinite( NINF )\n true\n > bool = base.isInfinite( 5.0 )\n false\n > bool = base.isInfinite( NaN )\n false\n\n See Also\n --------\n base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n Tests if a single-precision floating-point numeric value is infinite.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is infinite.\n\n Examples\n --------\n > var bool = base.isInfinitef( FLOAT32_PINF )\n true\n > bool = base.isInfinitef( FLOAT32_NINF )\n true\n > bool = base.isInfinitef( 5.0 )\n false\n > bool = base.isInfinitef( NaN )\n false\n\n See Also\n --------\n base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n Tests if a finite double-precision floating-point number is an integer.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an integer.\n\n Examples\n --------\n > var bool = base.isInteger( 1.0 )\n true\n > bool = base.isInteger( 3.14 )\n false\n\n","base.isnan":"\nbase.isnan( x )\n Tests if a double-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnan( NaN )\n true\n > bool = base.isnan( 7.0 )\n false\n\n See Also\n --------\n base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n Tests if a single-precision floating-point numeric value is `NaN`.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is `NaN`.\n\n Examples\n --------\n > var bool = base.isnanf( NaN )\n true\n > bool = base.isnanf( 7.0 )\n false\n\n See Also\n --------\n base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a negative finite number.\n\n Examples\n --------\n > var bool = base.isNegativeFinite( -3.14 )\n true\n > bool = base.isNegativeFinite( -Infinity )\n false\n > bool = base.isNegativeFinite( 2.0 )\n false\n > bool = base.isNegativeFinite( NaN )\n false\n > bool = base.isNegativeFinite( -0.0 )\n false\n\n See Also\n --------\n base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a negative integer.\n\n Examples\n --------\n > var bool = base.isNegativeInteger( -1.0 )\n true\n > bool = base.isNegativeInteger( 0.0 )\n false\n > bool = base.isNegativeInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n Tests if a double-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZero( -0.0 )\n true\n > bool = base.isNegativeZero( 0.0 )\n false\n\n See Also\n --------\n base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n Tests if a single-precision floating-point numeric value is negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is negative zero.\n\n Examples\n --------\n > var bool = base.isNegativeZerof( -0.0 )\n true\n > bool = base.isNegativeZerof( 0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative finite number.\n\n Examples\n --------\n > var out = base.isNonNegativeFinite( 5.0 )\n true\n > out = base.isNonNegativeFinite( 3.14 )\n true\n > out = base.isNonNegativeFinite( 0.0 )\n true\n > out = base.isNonNegativeFinite( Infinity )\n false\n > out = base.isNonNegativeFinite( -3.14 )\n false\n > out = base.isNonNegativeFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonnegative integer.\n\n Examples\n --------\n > var bool = base.isNonNegativeInteger( 1.0 )\n true\n > bool = base.isNonNegativeInteger( 0.0 )\n true\n > bool = base.isNonNegativeInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether the value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = base.isNonPositiveFinite( -3.14 )\n true\n > var bool = base.isNonPositiveFinite( 0.0 )\n true\n > var bool = base.isNonPositiveFinite( -Infinity )\n false\n > var bool = base.isNonPositiveFinite( 3.14 )\n false\n > var bool = base.isNonPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n\n The function assumes a finite number. If provided negative infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n The function does not distinguish between positive and negative zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a nonpositive integer.\n\n Examples\n --------\n > var bool = base.isNonPositiveInteger( -1.0 )\n true\n > bool = base.isNonPositiveInteger( 0.0 )\n true\n > bool = base.isNonPositiveInteger( 10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n Tests if a finite numeric value is an odd number.\n\n The function assumes a finite number. If provided positive or negative\n infinity, the function will return `true`, when, in fact, the result is\n undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOdd( 5.0 )\n true\n > bool = base.isOdd( -2.0 )\n false\n > bool = base.isOdd( 0.0 )\n false\n > bool = base.isOdd( NaN )\n false\n\n See Also\n --------\n base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n Tests if a 32-bit integer is odd.\n\n Parameters\n ----------\n x: integer\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is an odd number.\n\n Examples\n --------\n > var bool = base.isOddInt32( 5 )\n true\n > bool = base.isOddInt32( -2 )\n false\n > bool = base.isOddInt32( 0 )\n false\n\n See Also\n --------\n base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive finite number.\n\n Examples\n --------\n > var bool = base.isPositiveFinite( 5.0 )\n true\n > bool = base.isPositiveFinite( 3.14 )\n true\n > bool = base.isPositiveFinite( 0.0 )\n false\n > bool = base.isPositiveFinite( Infinity )\n false\n > bool = base.isPositiveFinite( -3.14 )\n false\n > bool = base.isPositiveFinite( NaN )\n false\n\n See Also\n --------\n base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n\n The function assumes a finite number. If provided positive infinity, the\n function will return `true`, when, in fact, the result is undefined.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a positive integer.\n\n Examples\n --------\n > var bool = base.isPositiveInteger( 1.0 )\n true\n > bool = base.isPositiveInteger( 0.0 )\n false\n > bool = base.isPositiveInteger( -10.0 )\n false\n\n See Also\n --------\n base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n Tests if a double-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZero( 0.0 )\n true\n > bool = base.isPositiveZero( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n Tests if a single-precision floating-point numeric value is positive zero.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is positive zero.\n\n Examples\n --------\n > var bool = base.isPositiveZerof( 0.0 )\n true\n > bool = base.isPositiveZerof( -0.0 )\n false\n\n See Also\n --------\n base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n Tests whether an unsigned integer is a power of 2.\n\n Parameters\n ----------\n x: integer\n Unsigned integer.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a power of 2.\n\n Examples\n --------\n > var bool = base.isPow2Uint32( 2 )\n true\n > bool = base.isPow2Uint32( 5 )\n false\n\n","base.isPrime":"\nbase.isPrime( x )\n Tests if a number is prime.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a prime number.\n\n Examples\n --------\n > var bool = base.isPrime( 11.0 )\n true\n > bool = base.isPrime( 3.14 )\n false\n\n See Also\n --------\n base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n Tests if a double-precision floating-point number value is a probability.\n\n A probability is defined as a number on the closed interval [0,1].\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a probability.\n\n Examples\n --------\n > var bool = base.isProbability( 0.5 )\n true\n > bool = base.isProbability( 3.14 )\n false\n > bool = base.isProbability( NaN )\n false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n Tests if a finite double-precision floating-point number is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the value is a safe integer.\n\n Examples\n --------\n > var bool = base.isSafeInteger( 1.0 )\n true\n > bool = base.isSafeInteger( 2.0e200 )\n false\n > bool = base.isSafeInteger( 3.14 )\n false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = base.kebabcase( 'Hello World!' )\n 'hello-world'\n > out = base.kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n [ ~1.277, ~0.926 ]\n > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n Computes the kernel function for the regularized incomplete beta function.\n\n The `regularized` and `upper` parameters specify whether to evaluate the\n non-regularized and/or upper incomplete beta functions, respectively.\n\n If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n a: number\n Second function parameter.\n\n b: number\n Third function parameter.\n\n regularized: boolean\n Boolean indicating whether the function should evaluate the regularized\n or non-regularized incomplete beta function.\n\n upper: boolean\n Boolean indicating whether the function should return the upper tail of\n the incomplete beta function.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Function value and first derivative.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n [ 0.64, 1.6 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n Computes the inverse of the lower incomplete beta function.\n\n Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n Parameters\n ----------\n a: number\n First function parameter (a positive number).\n\n b: number\n Second function parameter (a positive number).\n\n p: number\n Probability.\n\n q: number\n Probability equal to `1-p`.\n\n Returns\n -------\n out: Array\n Two-element array holding function value `y` and `1-y`.\n\n Examples\n --------\n > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n [ ~0.327, ~0.673 ]\n > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n [ ~0.446, ~0.554 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n [ ~0.082, ~0.918 ]\n > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n [ ~0.235, ~0.765 ]\n\n See Also\n --------\n base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Cosine.\n\n Examples\n --------\n > var out = base.kernelCos( 0.0, 0.0 )\n ~1.0\n > out = base.kernelCos( PI/6.0, 0.0 )\n ~0.866\n > out = base.kernelCos( 0.785, -1.144e-17 )\n ~0.707\n > out = base.kernelCos( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n\n This function provides a common means for computing logarithms in base e.\n Argument reduction and adding the final term of the polynomial must be done\n by the caller for increased accuracy when different bases are used.\n\n Parameters\n ----------\n f: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var y = base.kernelLog1p( 1.0 )\n ~0.1931\n > y = base.kernelLog1p( 1.4142135623730951 )\n ~0.4672\n > y = base.kernelLog1p( NaN )\n NaN\n\n See Also\n --------\n base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n For increased accuracy, the number for which the cosine should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n Returns\n -------\n out: number\n Sine.\n\n Examples\n --------\n > var y = base.kernelSin( 0.0, 0.0 )\n ~0.0\n > y = base.kernelSin( PI/6.0, 0.0 )\n ~0.5\n > y = base.kernelSin( 0.619, 9.279e-18 )\n ~0.58\n\n > y = base.kernelSin( NaN, 0.0 )\n NaN\n > y = base.kernelSin( 2.0, NaN )\n NaN\n > y = base.kernelSin( NaN, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n\n For increased accuracy, the number for which the tangent should be evaluated\n can be supplied as a double-double number (i.e., a non-evaluated sum of two\n double-precision floating-point numbers `x` and `y`).\n\n The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n y: number\n Tail of `x`.\n\n k: integer\n If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n returns the negative inverse `-1/tan(x+y)`.\n\n Returns\n -------\n out: number\n Tangent.\n\n Examples\n --------\n > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n ~1.0\n > out = base.kernelTan( PI/4.0, 0.0, -1 )\n ~-1.0\n > out = base.kernelTan( PI/6.0, 0.0, 1 )\n ~0.577\n > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n ~0.783\n\n > out = base.kernelTan( NaN, 0.0, 1 )\n NaN\n > out = base.kernelTan( 3.0, NaN, 1 )\n NaN\n > out = base.kernelTan( 3.0, 0.0, NaN )\n NaN\n\n See Also\n --------\n base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n Evaluates the Kronecker delta.\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDelta( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDelta( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n Evaluates the Kronecker delta (single-precision).\n\n If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n Parameters\n ----------\n i: number\n Input value.\n\n j: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n 0.0\n > y = base.kroneckerDeltaf( 3.14, 3.14 )\n 1.0\n\n See Also\n --------\n base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n\n Parameters\n ----------\n x: integer\n Signed 32-bit integer.\n\n Returns\n -------\n out: integer\n Absolute value.\n\n Examples\n --------\n > var v = base.labs( -1|0 )\n 1\n > v = base.labs( 2|0 )\n 2\n > v = base.labs( 0|0 )\n 0\n\n See Also\n --------\n base.abs\n","base.last":"\nbase.last( str, n )\n Returns the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.last( 'hello', 1 )\n 'o'\n > out = base.last( 'JavaScript', 6 )\n 'Script'\n > out = base.last( 'foo bar', 10 )\n 'foo bar'\n\n See Also\n --------\n base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n Returns the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastCodePoint( 'hello world', 1 )\n 'd'\n > out = base.lastCodePoint( 'JavaScript', 6 )\n 'Script'\n > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n 'द'\n\n See Also\n --------\n base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to return.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.lastGraphemeCluster( 'beep', 1 )\n 'p'\n > out = base.lastGraphemeCluster( 'Boop', 2 )\n 'op'\n > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n 'Script'\n\n See Also\n --------\n base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n Computes the least common multiple (lcm).\n\n If either `a` or `b` is `0`, the function returns `0`.\n\n Both `a` and `b` must have integer values; otherwise, the function returns\n `NaN`.\n\n Parameters\n ----------\n a: integer\n First integer.\n\n b: integer\n Second integer.\n\n Returns\n -------\n out: integer\n Least common multiple.\n\n Examples\n --------\n > var v = base.lcm( 21, 6 )\n 42\n\n See Also\n --------\n base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n\n If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n infinity, the function returns a value equal to `frac`.\n\n Parameters\n ----------\n frac: number\n Fraction.\n\n exp: number\n Exponent.\n\n Returns\n -------\n out: number\n Double-precision floating-point number equal to `frac * 2^exp`.\n\n Examples\n --------\n > var x = base.ldexp( 0.5, 3 )\n 4.0\n > x = base.ldexp( 4.0, -2 )\n 1.0\n > x = base.ldexp( 0.0, 20 )\n 0.0\n > x = base.ldexp( -0.0, 39 )\n -0.0\n > x = base.ldexp( NaN, -101 )\n NaN\n > x = base.ldexp( PINF, 11 )\n Infinity\n > x = base.ldexp( NINF, -118 )\n -Infinity\n\n See Also\n --------\n base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.leftPad( 'a', 5, ' ' )\n ' a'\n > out = base.leftPad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = base.leftPad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.leftTrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n Evaluates the natural logarithm of a double-precision floating-point number.\n\n For negative numbers, the natural logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ln( 4.0 )\n ~1.386\n > y = base.ln( 0.0 )\n -Infinity\n > y = base.ln( PINF )\n Infinity\n > y = base.ln( NaN )\n NaN\n > y = base.ln( -4.0 )\n NaN\n\n See Also\n --------\n base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n Computes the base `b` logarithm of a double-precision floating-point number.\n\n For negative `b` or `x`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n b: number\n Base.\n\n Returns\n -------\n y: number\n Logarithm (base `b`).\n\n Examples\n --------\n > var y = base.log( 100.0, 10.0 )\n 2.0\n > y = base.log( 16.0, 2.0 )\n 4.0\n > y = base.log( 5.0, 1.0 )\n Infinity\n > y = base.log( NaN, 2.0 )\n NaN\n > y = base.log( 1.0, NaN )\n NaN\n > y = base.log( -4.0, 2.0 )\n NaN\n > y = base.log( 4.0, -2.0 )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1mexp( -10.0 )\n ~-0.00005\n > y = base.log1mexp( 0.0 )\n -Infinity\n > y = base.log1mexp( 5.0 )\n ~-0.00676\n > y = base.log1mexp( 10.0 )\n ~-0.00005\n > y = base.log1mexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n Evaluates the natural logarithm of `1+x`.\n\n For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n defined for negative numbers.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1p( 4.0 )\n ~1.609\n > y = base.log1p( -1.0 )\n -Infinity\n > y = base.log1p( 0.0 )\n 0.0\n > y = base.log1p( -0.0 )\n -0.0\n > y = base.log1p( -2.0 )\n NaN\n > y = base.log1p( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n Evaluates the natural logarithm of `1+exp(x)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log1pexp( -10.0 )\n ~0.000045\n > y = base.log1pexp( 0.0 )\n ~0.693147\n > y = base.log1pexp( 5.0 )\n ~5.006715\n > y = base.log1pexp( 34.0 )\n 34.0\n > y = base.log1pexp( NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n Evaluates `ln(1+x) - x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > base.log1pmx( 1.1 )\n ~-0.358\n > base.log1pmx( 0.99 )\n ~-0.302\n > base.log1pmx( -0.99 )\n ~-3.615\n > base.log1pmx( -1.1 )\n NaN\n > base.log1pmx( NaN )\n NaN\n\n See Also\n --------\n base.ln, base.log1p","base.log2":"\nbase.log2( x )\n Evaluates the binary logarithm (base two).\n\n For negative numbers, the binary logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log2( 4.0 )\n 2.0\n > y = base.log2( 8.0 )\n 3.0\n > y = base.log2( 0.0 )\n -Infinity\n > y = base.log2( PINF )\n Infinity\n > y = base.log2( NaN )\n NaN\n > y = base.log2( -4.0 )\n NaN\n\n See Also\n --------\n base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n Evaluates the common logarithm (base 10).\n\n For negative numbers, the common logarithm is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.log10( 100.0 )\n 2.0\n > y = base.log10( 8.0 )\n ~0.903\n > y = base.log10( 0.0 )\n -Infinity\n > y = base.log10( PINF )\n Infinity\n > y = base.log10( NaN )\n NaN\n > y = base.log10( -4.0 )\n NaN\n\n See Also\n --------\n base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n v: number\n Function value.\n\n Examples\n --------\n > var v = base.logaddexp( 90.0, 90.0 )\n ~90.6931\n > v = base.logaddexp( -20.0, 90.0 )\n 90.0\n > v = base.logaddexp( 0.0, -100.0 )\n ~3.7201e-44\n > v = base.logaddexp( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n Evaluates the logit function.\n\n Let `p` be the probability of some event. The logit function is defined as\n the logarithm of the odds `p / (1-p)`.\n\n If `p < 0` or `p > 1`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.logit( 0.2 )\n ~-1.386\n > y = base.logit( 0.9 )\n ~2.197\n > y = base.logit( -4.0 )\n NaN\n > y = base.logit( 1.5 )\n NaN\n > y = base.logit( NaN )\n NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = base.lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n Computes the nth Lucas number.\n\n Lucas numbers follow the recurrence relation\n\n L_n = L_{n-1} + L_{n-2}\n\n with seed values L_0 = 2 and L_1 = 1.\n\n If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n numbers cannot be accurately represented due to limitations of double-\n precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Lucas number.\n\n Examples\n --------\n > var y = base.lucas( 0 )\n 2\n > y = base.lucas( 1 )\n 1\n > y = base.lucas( 2 )\n 3\n > y = base.lucas( 3 )\n 4\n > y = base.lucas( 4 )\n 7\n > y = base.lucas( 77 )\n NaN\n > y = base.lucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n Evaluates a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n x: number\n Value at which to evaluate the Lucas polynomial.\n\n Returns\n -------\n out: number\n Evaluated Lucas polynomial.\n\n Examples\n --------\n // 2^5 + 5*2^3 + 5*2\n > var v = base.lucaspoly( 5, 2.0 )\n 82.0\n\n\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n Returns a function for evaluating a Lucas polynomial.\n\n Parameters\n ----------\n n: integer\n Lucas polynomial to evaluate.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a Lucas polynomial.\n\n Examples\n --------\n > var polyval = base.lucaspoly.factory( 5 );\n\n // 1^5 + 5*1^2 + 5\n > var v = polyval( 1.0 )\n 11.0\n\n // 2^5 + 5*2^3 + 5*2\n > v = polyval( 2.0 )\n 82.0\n\n See Also\n --------\n base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.max( 3.14, 4.2 )\n 4.2\n > v = base.max( 3.14, NaN )\n NaN\n > v = base.max( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabs( 3.14, -4.2 )\n 4.2\n > v = base.maxabs( 3.14, NaN )\n NaN\n > v = base.maxabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n Returns the maximum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n the absolute value of `-infinity`).\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n > var v = base.maxabsn( 3.14, -4.2 )\n 4.2\n > v = base.maxabsn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxabsn( 3.14, NaN )\n NaN\n > v = base.maxabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n Returns the maximum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), negative infinity is the\n least upper bound. Similar to zero being the identity element for the sum of\n an empty set and to one being the identity element for the product of an\n empty set, negative infinity is the identity element for the maximum, and\n thus, if not provided any arguments, the function returns negative infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = base.maxn( 3.14, 4.2 )\n 4.2\n > v = base.maxn( 5.9, 3.14, 4.2 )\n 5.9\n > v = base.maxn( 3.14, NaN )\n NaN\n > v = base.maxn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.min( 3.14, 4.2 )\n 3.14\n > v = base.min( 3.14, NaN )\n NaN\n > v = base.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabs( 3.14, -4.2 )\n 3.14\n > v = base.minabs( 3.14, NaN )\n NaN\n > v = base.minabs( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n Returns the minimum absolute value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest upper bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n > var v = base.minabsn( 3.14, -4.2 )\n 3.14\n > v = base.minabsn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minabsn( 3.14, NaN )\n NaN\n > v = base.minabsn( +0.0, -0.0 )\n +0.0\n\n See Also\n --------\n base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmax( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmax( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmax( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabs( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabs( -5.9, 3.14)\n [ 3.14, 5.9 ]\n > v = base.minmaxabs( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabs( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for both the minimum and\n maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var v = base.minmaxabsn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxabsn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxabsn( +0.0, -0.0 )\n [ 0.0, 0.0 ]\n > v = base.minmaxabsn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum absolute values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum absolute values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum absolute values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n [ 3.14, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n Returns the minimum and maximum values.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound and negative infinity is the least upper bound. Similar\n to zero being the identity element for the sum of an empty set and to one\n being the identity element for the product of an empty set, positive\n infinity is the identity element for the minimum and negative infinity is\n the identity element for the maximum, and thus, if not provided any\n arguments, the function returns positive infinity for the minimum value and\n negative infinity for the maximum value.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: Array\n Minimum and maximum values.\n\n Examples\n --------\n > var v = base.minmaxn( 3.14, 4.2 )\n [ 3.14, 4.2 ]\n > v = base.minmaxn( 5.9, 3.14, 4.2 )\n [ 3.14, 5.9 ]\n > v = base.minmaxn( 3.14, NaN )\n [ NaN, NaN ]\n > v = base.minmaxn( +0.0, -0.0 )\n [ -0.0, +0.0 ]\n > v = base.minmaxn( 3.14 )\n [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n\n If any argument is `NaN`, the function returns `NaN` for both the minimum\n and maximum values.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n out: Array|TypedArray|Object\n Output object.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Minimum and maximum values.\n\n Examples\n --------\n > var out = [ 0.0, 0.0 ];\n > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n [ -1.5, 3.14 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n Returns the minimum value.\n\n If any argument is `NaN`, the function returns `NaN`.\n\n When an empty set is considered a subset of the extended reals (all real\n numbers, including positive and negative infinity), positive infinity is the\n greatest lower bound. Similar to zero being the identity element for the sum\n of an empty set and to one being the identity element for the product of an\n empty set, positive infinity is the identity element for the minimum, and\n thus, if not provided any arguments, the function returns positive infinity.\n\n Parameters\n ----------\n x: number (optional)\n First number.\n\n y: number (optional)\n Second number.\n\n args: ...number (optional)\n Numbers.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = base.minn( 3.14, 4.2 )\n 3.14\n > v = base.minn( 5.9, 3.14, 4.2 )\n 3.14\n > v = base.minn( 3.14, NaN )\n NaN\n > v = base.minn( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Integral and fractional parts.\n\n Examples\n --------\n > var parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( 3.14 )\n [ 3.0, 0.14000000000000012 ]\n > parts = base.modf( +0.0 )\n [ +0.0, +0.0 ]\n > parts = base.modf( -0.0 )\n [ -0.0, -0.0 ]\n > parts = base.modf( PINF )\n [ Infinity, +0.0 ]\n > parts = base.modf( NINF )\n [ -Infinity, -0.0 ]\n > parts = base.modf( NaN )\n [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Integral and fractional parts.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var parts = base.modf.assign( 3.14, out, 1, 0 )\n [ 3.0, 0.14000000000000012 ]\n > var bool = ( parts === out )\n true","base.mul":"\nbase.mul( x, y )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mul( -1.0, 5.0 )\n -5.0\n > v = base.mul( 2.0, 5.0 )\n 10.0\n > v = base.mul( 0.0, 5.0 )\n 0.0\n > v = base.mul( -0.0, 0.0 )\n -0.0\n > v = base.mul( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.mulf( -1.0, 5.0 )\n -5.0\n > v = base.mulf( 2.0, 5.0 )\n 10.0\n > v = base.mulf( 0.0, 5.0 )\n 0.0\n > v = base.mulf( -0.0, 0.0 )\n -0.0\n > v = base.mulf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40 );\n > arr.get( 1, 1 )\n 40\n\n // Set an element using a linear index:\n > arr.iset( 3, 99 );\n > arr.get( 1, 1 )\n 99\n\n\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'\n\n\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales[, options]] )\n Serializes an ndarray as a locale-aware string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n Configuration options.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toLocaleString()\n '...'","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n\n Each provided \"ndarray\" should be an object with the following properties:\n\n - dtype: data type.\n - data: data buffer.\n - shape: dimensions.\n - strides: stride lengths.\n - offset: index offset.\n - order: specifies whether an ndarray is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one input ndarray and one output ndarray.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n // Define ndarray data and meta data...\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dtype = 'float64';\n > var shape = [ 2, 2 ];\n > var sx = [ 2, 1 ];\n > var sy = [ 2, 1 ];\n > var ox = 0;\n > var oy = 0;\n > var order = 'row-major';\n\n // Using ndarrays...\n > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using minimal ndarray-like objects...\n > x = {\n ... 'dtype': dtype,\n ... 'data': xbuf,\n ... 'shape': shape,\n ... 'strides': sx,\n ... 'offset': ox,\n ... 'order': order\n ... };\n > y = {\n ... 'dtype': dtype,\n ... 'data': ybuf,\n ... 'shape': shape,\n ... 'strides': sy,\n ... 'offset': oy,\n ... 'order': order\n ... };\n > base.ndarrayUnary( [ x, y ], base.abs );\n > y.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type. Must be a numeric or \"generic\" data type.\n\n shape: ArrayLikeObject\n Array shape.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n Along with data type, shape, and order, the function infers the \"class\" of\n the returned ndarray from the provided ndarray. For example, if provided a\n \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n ndarray, the function returns a non-base ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = base.ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n Computes the nth negaFibonacci number.\n\n The negaFibonacci numbers follow the recurrence relation\n\n F_{n-2} = F_{n} - F_{n-1}\n\n with seed values F_0 = 0 and F_{-1} = 1.\n\n If `|n|` is greater than `78`, the function returns `NaN` as larger\n negaFibonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaFibonacci number.\n\n Examples\n --------\n > var y = base.negafibonacci( 0 )\n 0\n > y = base.negafibonacci( -1 )\n 1\n > y = base.negafibonacci( -2 )\n -1\n > y = base.negafibonacci( -3 )\n 2\n > y = base.negafibonacci( -4 )\n -3\n > y = base.negafibonacci( -79 )\n NaN\n > y = base.negafibonacci( -80 )\n NaN\n > y = base.negafibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n Computes the nth negaLucas number.\n\n The negaLucas numbers follow the recurrence relation\n\n L_{n-2} = L_{n} - L_{n-1}\n\n with seed values L_0 = 2 and L_{-1} = -1.\n\n If `|n|` is greater than `76`, the function returns `NaN` as larger\n negaLucas numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a non-positive integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n NegaLucas number.\n\n Examples\n --------\n > var y = base.negalucas( 0 )\n 2\n > y = base.negalucas( -1 )\n -1\n > y = base.negalucas( -2 )\n 3\n > y = base.negalucas( -3 )\n -4\n > y = base.negalucas( -4 )\n 7\n > y = base.negalucas( -77 )\n NaN\n > y = base.negalucas( -78 )\n NaN\n > y = base.negalucas( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n Computes the nth non-Fibonacci number.\n\n If provided either a non-integer or `n < 1`, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: number\n Non-Fibonacci number.\n\n Examples\n --------\n > var v = base.nonfibonacci( 1 )\n 4\n > v = base.nonfibonacci( 2 )\n 6\n > v = base.nonfibonacci( 3 )\n 7\n > v = base.nonfibonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalize( 3.14e-319 )\n [ 1.4141234400356668e-303, -52 ]\n > var y = out[ 0 ];\n > var exponent = out[ 1 ];\n > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n true\n\n // Special cases:\n > out = base.normalize( 0.0 )\n [ 0.0, 0 ];\n > out = base.normalize( PINF )\n [ Infinity, 0 ]\n > out = base.normalize( NINF )\n [ -Infinity, 0 ]\n > out = base.normalize( NaN )\n [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Output array.\n\n Examples\n --------\n > var out = new Float64Array( 2 )\n > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n [ 1.4141234400356668e-303, -52 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.normalizef","base.normalizef":"\nbase.normalizef( x )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: Array\n An array containing `y` and `exp`.\n\n Examples\n --------\n > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n [ 1.1754943508222875e-38, -23 ]\n > var y = out[ 0 ];\n > var exp = out[ 1 ];\n > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n true\n\n // Special cases:\n > out = base.normalizef( FLOAT32_PINF )\n [ Infinity, 0 ]\n > out = base.normalizef( FLOAT32_NINF )\n [ -Infinity, 0 ]\n > out = base.normalizef( NaN )\n [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp`\n and assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp`\n and assigns results to a provided output array.\n\n The first element of the returned array corresponds to `y` and the second to\n `exp`.\n\n While the function accepts higher precision floating-point numbers, beware\n that providing such numbers can be a source of subtle bugs as the relation\n `x = y * 2^exp` may not hold.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n An array containing `y` and `exp`.\n\n Examples\n --------\n > out = new Float32Array( 2 );\n > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n [ 1.1754943508222875e-38, -23.0 ]\n > bool = ( v === out )\n true\n\n See Also\n --------\n base.normalize","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice, shape, strict )\n Returns a normalized MultiSlice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n shape: Array\n Maximum slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance (or an error object).\n\n Examples\n --------\n > var s1 = new MultiSlice( 1, 3, null );\n > var s2 = base.normalizeMultiSlice( s1, [ 5, 5, 5 ], false );\n > var v = s2.data[ 0 ];\n > v.start\n 1\n > v.stop\n 2\n > v.step\n 1\n > v = s2.data[ 1 ];\n > v.start\n 3\n > v.stop\n 4\n > v.step\n 1\n > v = s2.data[ 2 ];\n > v.start\n 0\n > v.stop\n 5\n > v.step\n 1\n\n See Also\n --------\n base.normalizeSlice\n","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n Returns a normalized Slice object.\n\n In strict mode, the function returns an error object if an input slice\n exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n Parameters\n ----------\n slice: Slice\n Input slice object.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance (or an error object).\n\n Examples\n --------\n > var s1 = new Slice( 1, 10, 1 );\n > var s2 = base.normalizeSlice( s1, 5, false );\n > s2.start\n 1\n > s2.stop\n 5\n > s2.step\n 1\n > s1 = new Slice( -2, null, -1 );\n > s2 = base.normalizeSlice( s1, 10, false );\n > s2.start\n 8\n > s2.stop\n null\n > s2.step\n -1\n\n See Also\n --------\n base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n x: number\n Value at which to evaluate the polynomial.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.normhermitepoly( 1, 0.5 )\n 0.5\n > y = base.normhermitepoly( -1, 0.5 )\n NaN\n > y = base.normhermitepoly( 0, 0.5 )\n 1.0\n > y = base.normhermitepoly( 2, 0.5 )\n -0.75\n\n\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n\n Parameters\n ----------\n n: integer\n Nonnegative polynomial degree.\n\n Returns\n -------\n fcn: Function\n Function for evaluating a normalized Hermite polynomial.\n\n Examples\n --------\n > var f = base.normhermitepoly.factory( 2 );\n > var v = f( 0.5 )\n -0.75\n\n See Also\n --------\n base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = base.pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = base.pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdiff( 5.9, 3.14 )\n 2.76\n > v = base.pdiff( 3.14, 4.2 )\n 0.0\n > v = base.pdiff( 3.14, NaN )\n NaN\n > v = base.pdiff( -0.0, +0.0 )\n +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Positive difference.\n\n Examples\n --------\n > var v = base.pdifff( 5.9, 3.15 )\n 2.75\n > v = base.pdifff( 3.14, 4.2 )\n 0.0\n > v = base.pdifff( 3.14, NaN )\n NaN\n > v = base.pdifff( -0.0, +0.0 )\n +0.0\n\n See Also\n --------\n base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = base.percentEncode( '☃' )\n '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n\n If `n` is not a nonnegative integer, the function returns `NaN`.\n\n If `x` is zero or a negative odd integer, the function returns `+Infinity`.\n If `x` is a negative even integer, the function returns `NaN`.\n\n If provided `NaN` as either parameter, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Derivative order.\n\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.polygamma( 3, 1.2 )\n ~3.245\n > v = base.polygamma( 5, 1.2 )\n ~41.39\n > v = base.polygamma( 3, -4.9 )\n ~60014.239\n > v = base.polygamma( -1, 5.3 )\n NaN\n > v = base.polygamma( 2, -1.0 )\n Infinity\n\n See Also\n --------\n base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n Evaluates the exponential function `bˣ`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.pow( 2.0, 3.0 )\n 8.0\n > y = base.pow( 4.0, 0.5 )\n 2.0\n > y = base.pow( 100.0, 0.0 )\n 1.0\n > y = base.pow( PI, 5.0 )\n ~306.0197\n > y = base.pow( PI, -0.2 )\n ~0.7954\n > y = base.pow( NaN, 3.0 )\n NaN\n > y = base.pow( 5.0, NaN )\n NaN\n > y = base.pow( NaN, NaN )\n NaN\n\n See Also\n --------\n base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n Evaluates `bˣ - 1`.\n\n When `b` is close to `1` and/or `x` is small, this function is more accurate\n than naively computing `bˣ` and subtracting `1`.\n\n Parameters\n ----------\n b: number\n Base.\n\n x: number\n Exponent.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.powm1( 2.0, 3.0 )\n 7.0\n > y = base.powm1( 4.0, 0.5 )\n 1.0\n > y = base.powm1( 0.0, 100.0 )\n -1.0\n > y = base.powm1( 100.0, 0.0 )\n 0.0\n > y = base.powm1( 0.0, 0.0 )\n 0.0\n > y = base.powm1( PI, 5.0 )\n ~305.0197\n > y = base.powm1( NaN, 3.0 )\n NaN\n > y = base.powm1( 5.0, NaN )\n NaN\n\n See Also\n --------\n base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n Converts an angle from radians to degrees.\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2deg( PI/2.0 )\n 90.0\n > d = base.rad2deg( -PI/4.0 )\n -45.0\n > d = base.rad2deg( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2deg( PI/6.0 )\n 29.999999999999996\n\n See Also\n --------\n base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n Converts an angle from radians to degrees (single-precision).\n\n Parameters\n ----------\n x: number\n Angle in radians.\n\n Returns\n -------\n d: number\n Angle in degrees.\n\n Examples\n --------\n > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n 90.0\n > d = base.rad2degf( -3.141592653589793 / 4.0 )\n -45.0\n > d = base.rad2degf( NaN )\n NaN\n\n // Due to finite precision, canonical values may not be returned:\n > d = base.rad2degf( 3.141592653589793 / 6.0 )\n 30.000001907348633\n\n See Also\n --------\n base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n Evaluates the ramp function.\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.ramp( 3.14 )\n 3.14\n > y = base.ramp( -3.14 )\n 0.0\n\n See Also\n --------\n base.heaviside\n","base.rampf":"\nbase.rampf( x )\n Evaluates the ramp function (single-precision).\n\n If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.rampf( 3.14 )\n 3.14\n > y = base.rampf( -3.14 )\n 0.0\n\n See Also\n --------\n base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n Returns a pseudorandom number drawn from an arcsine distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 5.0 )\n \n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n \n\n\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'\n\n\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, random.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.arcsine.factory();\n > var r = rand( 0.0, 1.0 )\n \n > r = rand( -2.0, 2.0 )\n \n\n // Provide `a` and `b`:\n > rand = base.random.arcsine.factory( 0.0, 1.0 );\n > r = rand()\n \n > r = rand()\n ","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.arcsine.NAME\n 'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.arcsine.state\n \n\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n \n\n // Set the state:\n > base.random.arcsine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.arcsine( 2.0, 4.0 )\n \n > r = base.random.arcsine( 2.0, 4.0 )\n ","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.arcsine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, random.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, random.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.bernoulli.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.bernoulli.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.bernoulli.NAME\n 'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.bernoulli.state\n \n\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n \n\n // Set the state:\n > base.random.bernoulli.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.bernoulli( 0.3 )\n \n > r = base.random.bernoulli( 0.3 )\n ","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.bernoulli.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, random.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n Returns a pseudorandom number drawn from a beta distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'\n\n\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta, random.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.beta.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.beta.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.beta.NAME\n 'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.beta.state\n \n\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.beta.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.beta( 2.0, 5.0 )\n \n > r = base.random.beta( 2.0, 5.0 )\n ","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.beta.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.beta, random.iterators.beta, random.streams.beta, random.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n Returns a pseudorandom number drawn from a beta prime distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'\n\n\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime, random.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.betaprime.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.betaprime.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.betaprime.NAME\n 'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.betaprime.state\n \n\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.betaprime.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.betaprime( 2.0, 5.0 )\n \n > r = base.random.betaprime( 2.0, 5.0 )\n ","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.betaprime.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.betaprime, random.iterators.betaprime, random.streams.betaprime, random.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n Returns a pseudorandom number drawn from a binomial distribution.\n\n If `n` is not a positive integer or `p` is not a probability, the function\n returns `NaN`.\n\n If `n` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'\n\n\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial, random.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided `n` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `n` and `p`, the returned PRNG requires that both `n` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.binomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `n` and `p`:\n > rand = base.random.binomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.binomial.NAME\n 'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Get a copy of the current state:\n > var state = base.random.binomial.state\n \n\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n \n\n // Set the state:\n > base.random.binomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.binomial( 20, 0.8 )\n \n > r = base.random.binomial( 20, 0.8 )\n ","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.binomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.binomial, random.iterators.binomial, random.streams.binomial, random.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'\n\n\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.boxMuller.factory();\n > r = rand();\n > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.boxMuller.NAME\n 'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Get a copy of the current state:\n > var state = base.random.boxMuller.state\n \n\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n \n\n // Set the state:\n > base.random.boxMuller.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.boxMuller()\n \n > r = base.random.boxMuller()\n ","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.boxMuller.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n\n If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'\n\n\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy, random.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n `Ɣ` be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n Ɣ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cauchy.factory();\n > var r = rand( 0.0, 1.5 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `x0` and `Ɣ`:\n > rand = base.random.cauchy.factory( 0.0, 1.5 );\n > r = rand();\n > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cauchy.NAME\n 'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cauchy.state\n \n\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cauchy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cauchy( 2.0, 5.0 )\n \n > r = base.random.cauchy( 2.0, 5.0 )\n ","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cauchy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cauchy, random.iterators.cauchy, random.streams.cauchy, random.cauchy","base.random.chi":"\nbase.random.chi( k )\n Returns a pseudorandom number drawn from a chi distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'\n\n\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi, random.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chi.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chi.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chi.NAME\n 'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chi.state\n \n\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n \n\n // Set the state:\n > base.random.chi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chi( 2 )\n \n > r = base.random.chi( 2 )\n ","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chi, random.iterators.chi, random.streams.chi, random.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n Returns a pseudorandom number drawn from a chi-square distribution.\n\n If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'\n\n\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare, random.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided `k`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `k`, the returned PRNG requires that `k` be provided at each\n invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.chisquare.factory();\n > var r = rand( 5 );\n > r = rand( 3.14 );\n\n // Provide `k`:\n > rand = base.random.chisquare.factory( 3 );\n > r = rand();\n > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.chisquare.NAME\n 'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Get a copy of the current state:\n > var state = base.random.chisquare.state\n \n\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n \n\n // Set the state:\n > base.random.chisquare.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.chisquare( 2 )\n \n > r = base.random.chisquare( 2 )\n ","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.chisquare.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.chisquare, random.iterators.chisquare, random.streams.chisquare, random.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'\n\n\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine, random.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.cosine.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.cosine.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.cosine.NAME\n 'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.cosine.state\n \n\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.cosine.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.cosine( 2.0, 5.0 )\n \n > r = base.random.cosine( 2.0, 5.0 )\n ","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.cosine.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.cosine, random.iterators.cosine, random.streams.cosine, random.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n If `a > b`, the function returns `NaN`.\n\n If `a` or `b` is not an integer value, the function returns `NaN`.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();\n\n\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform, random.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.discreteUniform.factory();\n > var r = rand( 0, 10 );\n > r = rand( -20, 20 );\n\n // Provide `a` and `b`:\n > rand = base.random.discreteUniform.factory( 0, 10 );\n > r = rand();\n > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.discreteUniform.NAME\n 'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Get a copy of the current state:\n > var state = base.random.discreteUniform.state\n \n\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n \n\n // Set the state:\n > base.random.discreteUniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.discreteUniform( 2, 50 )\n \n > r = base.random.discreteUniform( 2, 50 )\n ","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.discreteUniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform, random.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n Returns a pseudorandom number drawn from an Erlang distribution.\n\n If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'\n\n\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang, random.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: integer (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.erlang.factory();\n > var r = rand( 2, 1.0 );\n > r = rand( 4, 3.14 );\n\n // Provide `k` and `λ`:\n > rand = base.random.erlang.factory( 2, 1.5 );\n > r = rand();\n > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.erlang.NAME\n 'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.erlang.state\n \n\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n \n\n // Set the state:\n > base.random.erlang.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.erlang( 2, 5.0 )\n \n > r = base.random.erlang( 2, 5.0 )\n ","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.erlang.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.erlang, random.iterators.erlang, random.streams.erlang, random.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n Returns a pseudorandom number drawn from an exponential distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'\n\n\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential, random.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.exponential.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.exponential.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.exponential.NAME\n 'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Get a copy of the current state:\n > var state = base.random.exponential.state\n \n\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n \n\n // Set the state:\n > base.random.exponential.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.exponential( 7.9 )\n \n > r = base.random.exponential( 7.9 )\n ","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.exponential.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.exponential, random.iterators.exponential, random.streams.exponential, random.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n Returns a pseudorandom number drawn from an F distribution.\n\n If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'\n\n\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f, random.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n\n If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n `d2` be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.f.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.0, 3.14 );\n\n // Provide `d1` and `d2`:\n > rand = base.random.f.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.f.NAME\n 'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.f.state\n \n\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.f.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.f( 1.5, 1.5 )\n \n > r = base.random.f( 1.5, 1.5 )\n ","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.f.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.f, random.iterators.f, random.streams.f, random.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n\n If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'\n\n\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet, random.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n and `m` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.frechet.factory();\n > var r = rand( 1.0, 1.0, 0.5 );\n > r = rand( 2.0, 2.0, 1.0 );\n\n // Provide `α`, `s`, and `m`:\n > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.frechet.NAME\n 'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.frechet.state\n \n\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.frechet.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n \n > r = base.random.frechet( 1.0, 1.0, 0.5 )\n ","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.frechet.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.frechet, random.iterators.frechet, random.streams.frechet, random.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n Returns a pseudorandom number drawn from a gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'\n\n\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma, random.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.gamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gamma.NAME\n 'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gamma.state\n \n\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gamma( 2.0, 5.0 )\n \n > r = base.random.gamma( 2.0, 5.0 )\n ","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gamma, random.iterators.gamma, random.streams.gamma, random.gamma","base.random.geometric":"\nbase.random.geometric( p )\n Returns a pseudorandom number drawn from a geometric distribution.\n\n If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();\n\n\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'\n\n\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric, random.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided `p`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `p`, the returned PRNG requires that `p` be provided at each\n invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.geometric.factory();\n > var r = rand( 0.3 );\n > r = rand( 0.59 );\n\n // Provide `p`:\n > rand = base.random.geometric.factory( 0.3 );\n > r = rand();\n > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.geometric.NAME\n 'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.geometric.state\n \n\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n \n\n // Set the state:\n > base.random.geometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.geometric( 0.3 )\n \n > r = base.random.geometric( 0.3 )\n ","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.geometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.geometric, random.iterators.geometric, random.streams.geometric, random.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n\n If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'\n\n\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel, random.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided `μ` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.gumbel.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `β`:\n > rand = base.random.gumbel.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.gumbel.NAME\n 'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.gumbel.state\n \n\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.gumbel.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.gumbel( 2.0, 5.0 )\n \n > r = base.random.gumbel( 2.0, 5.0 )\n ","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.gumbel.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.gumbel, random.iterators.gumbel, random.streams.gumbel, random.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n returns `NaN`.\n\n If `n > N` or `K > N`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();\n\n\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric, random.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n and `n` be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.hypergeometric.factory();\n > var r = rand( 20, 10, 15 );\n > r = rand( 20, 10, 7 );\n\n // Provide `N`, `K`, and `n`:\n > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n > r = rand();\n > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.hypergeometric.NAME\n 'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Get a copy of the current state:\n > var state = base.random.hypergeometric.state\n \n\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n \n\n // Set the state:\n > base.random.hypergeometric.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.hypergeometric( 20, 10, 15 )\n \n > r = base.random.hypergeometric( 20, 10, 15 )\n ","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.hypergeometric.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric, random.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.improvedZiggurat.factory();\n > r = rand();\n > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.improvedZiggurat.NAME\n 'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Get a copy of the current state:\n > var state = base.random.improvedZiggurat.state\n \n\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n \n\n // Set the state:\n > base.random.improvedZiggurat.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.improvedZiggurat()\n \n > r = base.random.improvedZiggurat()\n ","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.improvedZiggurat.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'\n\n\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma, random.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.invgamma.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 3.14, 2.25 );\n\n // Provide `α` and `β`:\n > rand = base.random.invgamma.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.invgamma.NAME\n 'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.invgamma.state\n \n\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.invgamma.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.invgamma( 2.0, 5.0 )\n \n > r = base.random.invgamma( 2.0, 5.0 )\n ","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.invgamma.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.invgamma, random.iterators.invgamma, random.streams.invgamma, random.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n\n If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy, random.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.kumaraswamy.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `a` and `b`:\n > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.kumaraswamy.NAME\n 'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.kumaraswamy.state\n \n\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n\n // Set the state:\n > base.random.kumaraswamy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.kumaraswamy( 1.5, 1.5 )\n \n > r = base.random.kumaraswamy( 1.5, 1.5 )\n ","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.kumaraswamy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy, random.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n Returns a pseudorandom number drawn from a Laplace distribution.\n\n If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'\n\n\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace, random.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n\n If provided `μ` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.laplace.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.laplace.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.laplace.NAME\n 'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.laplace.state\n \n\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.laplace.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.laplace( 2.0, 5.0 )\n \n > r = base.random.laplace( 2.0, 5.0 )\n ","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.laplace.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.laplace, random.iterators.laplace, random.streams.laplace, random.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n Returns a pseudorandom number drawn from a Lévy distribution.\n\n If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'\n\n\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy, random.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided `μ` and `c`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n `c` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.levy.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `b`:\n > rand = base.random.levy.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.levy.NAME\n 'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.levy.state\n \n\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.levy.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.levy( 2.0, 5.0 )\n \n > r = base.random.levy( 2.0, 5.0 )\n ","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.levy.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.levy, random.iterators.levy, random.streams.levy, random.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n Returns a pseudorandom number drawn from a logistic distribution.\n\n If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'\n\n\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic, random.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided `μ` and `s`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n `s` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.logistic.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `s`:\n > rand = base.random.logistic.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.logistic.NAME\n 'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.logistic.state\n \n\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.logistic.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.logistic( 2.0, 5.0 )\n \n > r = base.random.logistic( 2.0, 5.0 )\n ","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.logistic.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.logistic, random.iterators.logistic, random.streams.logistic, random.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n Returns a pseudorandom number drawn from a lognormal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'\n\n\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal, random.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.lognormal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.lognormal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.lognormal.NAME\n 'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.lognormal.state\n \n\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.lognormal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.lognormal( 2.0, 5.0 )\n \n > r = base.random.lognormal( 2.0, 5.0 )\n ","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.lognormal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.lognormal, random.iterators.lognormal, random.streams.lognormal, random.lognormal","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838\n\n\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'\n\n\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1\n\n\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646\n\n\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG).\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstd.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstd.factory( { 'seed': 1234 } );\n > r = rand()\n 20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstd.NAME\n 'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MIN\n 1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstd.MAX\n 2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstd()\n \n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Get the current state:\n > var state = base.random.minstd.state\n \n\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n \n\n // Set the state:\n > base.random.minstd.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstd()\n \n > r = base.random.minstd()\n ","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstd.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654\n\n\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1\n\n\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646\n\n\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.minstdShuffle.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n > r = rand()\n 1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.minstdShuffle.NAME\n 'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MIN\n 1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.minstdShuffle.MAX\n 2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Get a copy of the current state:\n > var state = base.random.minstdShuffle.state\n \n\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n \n\n // Set the state:\n > base.random.minstdShuffle.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.minstdShuffle()\n \n > r = base.random.minstdShuffle()\n ","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.minstdShuffle.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775\n\n\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'\n\n\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0\n\n\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295\n\n\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.mt19937.factory();\n > r = rand();\n > r = rand();\n\n // Provide a seed:\n > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n > r = rand()\n 822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.mt19937.NAME\n 'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MIN\n 0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n\n Examples\n --------\n > var v = base.random.mt19937.MAX\n 4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Get a copy of the current state:\n > var state = base.random.mt19937.state\n \n\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n \n\n // Set the state:\n > base.random.mt19937.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.mt19937()\n \n > r = base.random.mt19937()\n ","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.mt19937.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n\n If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n If `r` or `p` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial, random.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided `r` and `p`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `r` and `p`, the returned PRNG requires that both `r` and\n `p` be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.negativeBinomial.factory();\n > var r = rand( 20, 0.3 );\n > r = rand( 10, 0.77 );\n\n // Provide `r` and `p`:\n > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n > r = rand();\n > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.negativeBinomial.NAME\n 'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Get a copy of the current state:\n > var state = base.random.negativeBinomial.state\n \n\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n \n\n // Set the state:\n > base.random.negativeBinomial.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.negativeBinomial( 20, 0.3 )\n \n > r = base.random.negativeBinomial( 20, 0.3 )\n ","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.negativeBinomial.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial, random.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n Returns a pseudorandom number drawn from a normal distribution.\n\n If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'\n\n\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal, random.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n\n If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n `σ` be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.normal.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `μ` and `σ`:\n > rand = base.random.normal.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.normal.NAME\n 'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.normal.state\n \n\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.normal.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.normal( 2.0, 5.0 )\n \n > r = base.random.normal( 2.0, 5.0 )\n ","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n\n Examples\n --------\n > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.normal.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.normal, random.iterators.normal, random.streams.normal, random.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n If `α` or `β` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1, random.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided `α` and `β`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `α` and `β`, the returned PRNG requires that both `α` and\n `β` be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.pareto1.factory();\n > var r = rand( 1.5, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `α` and `β`:\n > rand = base.random.pareto1.factory( 1.5, 1.5 );\n > r = rand();\n > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.pareto1.NAME\n 'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.pareto1.state\n \n\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.pareto1.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.pareto1( 2.0, 5.0 )\n \n > r = base.random.pareto1( 2.0, 5.0 )\n ","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.pareto1.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.pareto1, random.iterators.pareto1, random.streams.pareto1, random.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n Returns a pseudorandom number drawn from a Poisson distribution.\n\n If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'\n\n\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson, random.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided `λ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.poisson.factory();\n > var r = rand( 4.0 );\n > r = rand( 3.14 );\n\n // Provide `λ`:\n > rand = base.random.poisson.factory( 10.0 );\n > r = rand();\n > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.poisson.NAME\n 'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.poisson.state\n \n\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n \n\n // Set the state:\n > base.random.poisson.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.poisson( 10.0 )\n \n > r = base.random.poisson( 10.0 )\n ","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.poisson.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.poisson, random.iterators.poisson, random.streams.poisson, random.poisson","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();\n\n\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'\n\n\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var randi = base.random.randi.factory();\n > var r = randi();\n > r = randi();\n\n // Specify alternative PRNG:\n > randi = base.random.randi.factory({ 'name': 'minstd' });\n > r = randi();\n > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randi.NAME\n 'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randi()\n \n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Get a copy of the current state:\n > var state = base.random.randi.state;\n\n > r = base.random.randi()\n \n > r = base.random.randi()\n \n\n // Set the state:\n > base.random.randi.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randi()\n \n > r = base.random.randi()\n ","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randi.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'\n\n\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG) that samples\n from a standard normal distribution. The following PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randn.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n > r = rand();\n > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randn.NAME\n 'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randn()\n \n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Get a copy of the current state:\n > var state = base.random.randn.state;\n\n > r = base.random.randn()\n \n > r = base.random.randn()\n \n\n // Set the state:\n > base.random.randn.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randn()\n \n > r = base.random.randn()\n ","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randn.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either use the `factory`\n method to explicitly specify a PRNG via the `name` option or use an\n underlying PRNG directly.\n\n Returns\n -------\n r: number\n Pseudorandom number on the interval `[0,1)`.\n\n Examples\n --------\n > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();\n\n\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'\n\n\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of the underlying pseudorandom number generator (PRNG). The\n following PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underlying PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.randu.factory();\n > var r = rand();\n > r = rand();\n\n // Specify alternative PRNG:\n > var rand = base.random.randu.factory({ 'name': 'minstd' });\n > r = rand();\n > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.randu.NAME\n 'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n\n Examples\n --------\n > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.randu()\n \n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Get a copy of the current state:\n > var state = base.random.randu.state;\n\n > r = base.random.randu()\n \n > r = base.random.randu()\n \n\n // Set the state:\n > base.random.randu.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.randu()\n \n > r = base.random.randu()\n ","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.randu.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh, random.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided `σ`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.rayleigh.factory();\n > var r = rand( 5.0 );\n > r = rand( 10.0 );\n\n // Provide `σ`:\n > rand = base.random.rayleigh.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.rayleigh.NAME\n 'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.rayleigh.state\n \n\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n \n\n // Set the state:\n > base.random.rayleigh.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.rayleigh( 5.0 )\n \n > r = base.random.rayleigh( 5.0 )\n ","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.rayleigh.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh, random.rayleigh","base.random.t":"\nbase.random.t( v )\n Returns a pseudorandom number drawn from a Student's t distribution.\n\n If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'\n\n\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t, random.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided `v`, the returned PRNG returns random variates drawn from the\n specified distribution.\n\n If not provided `v`, the returned PRNG requires that `v` be provided at each\n invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.t.factory();\n > var r = rand( 5.0 );\n > r = rand( 3.14 );\n\n // Provide `v`:\n > rand = base.random.t.factory( 5.0 );\n > r = rand();\n > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.t.NAME\n 't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.t.state\n \n\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n \n\n // Set the state:\n > base.random.t.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.t( 10.0 )\n \n > r = base.random.t( 10.0 )\n ","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.t.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.t, random.iterators.t, random.streams.t, random.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n Returns a pseudorandom number drawn from a triangular distribution.\n\n If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n Returns\n -------\n r: integer\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'\n\n\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular, random.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n drawn from the specified distribution.\n\n If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n and `c` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.triangular.factory();\n > var r = rand( 0.0, 1.0, 0.5 );\n > r = rand( -2.0, 2.0, 1.0 );\n\n // Provide `a`, `b`, and `c`:\n > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n > r = rand();\n > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.triangular.NAME\n 'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = base.random.triangular.state\n \n\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n\n // Set the state:\n > base.random.triangular.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n \n > r = base.random.triangular( 0.0, 1.0, 0.5 )\n ","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.triangular.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.triangular, random.iterators.triangular, random.streams.triangular, random.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n If `a >= b`, the function returns `NaN`.\n\n If `a` or `b` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n a: number\n Minimum support (inclusive).\n\n b: number\n Maximum support (exclusive).\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();\n\n\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'\n\n\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, random.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n\n If provided `a` and `b`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `a` and `b`, the returned PRNG requires that both `a` and\n `b` be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support (inclusive).\n\n b: number (optional)\n Maximum support (exclusive).\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.uniform.factory();\n > var r = rand( 0.0, 1.0 );\n > r = rand( -2.0, 2.0 );\n\n // Provide `a` and `b`:\n > rand = base.random.uniform.factory( 0.0, 1.0 );\n > r = rand();\n > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.uniform.NAME\n 'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.uniform.state\n \n\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.uniform.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.uniform( 2.0, 5.0 )\n \n > r = base.random.uniform( 2.0, 5.0 )\n ","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.uniform.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.uniform, random.iterators.uniform, random.streams.uniform, random.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n Returns a pseudorandom number drawn from a Weibull distribution.\n\n If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Scale parameter.\n\n Returns\n -------\n r: number\n Pseudorandom number.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();\n\n\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'\n\n\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull, random.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided `k` and `λ`, the returned PRNG returns random variates drawn\n from the specified distribution.\n\n If not provided `k` and `λ`, the returned PRNG requires that both\n `k` and `λ` be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n rand: Function\n Pseudorandom number generator (PRNG).\n\n Examples\n --------\n // Basic usage:\n > var rand = base.random.weibull.factory();\n > var r = rand( 0.1, 1.5 );\n > r = rand( 2.0, 3.14 );\n\n // Provide `λ` and `k`:\n > rand = base.random.weibull.factory( 0.1, 1.5 );\n > r = rand();\n > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n\n Examples\n --------\n > var str = base.random.weibull.NAME\n 'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n\n Examples\n --------\n > var r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = base.random.weibull.state\n \n\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n \n\n // Set the state:\n > base.random.weibull.state = state;\n\n // Replay the last two pseudorandom numbers:\n > r = base.random.weibull( 2.0, 5.0 )\n \n > r = base.random.weibull( 2.0, 5.0 )\n ","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var o = base.random.weibull.toJSON()\n { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n See Also\n --------\n random.array.weibull, random.iterators.weibull, random.streams.weibull, random.weibull","base.rcbrt":"\nbase.rcbrt( x )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrt( 8.0 )\n 0.5\n > y = base.rcbrt( 1000.0 )\n 0.1\n > y = base.rcbrt( 0.0 )\n Infinity\n > y = base.rcbrt( PINF )\n 0.0\n > y = base.rcbrt( -8.0 )\n -0.5\n > y = base.rcbrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal cube root.\n\n Examples\n --------\n > var y = base.rcbrtf( 8.0 )\n 0.5\n > y = base.rcbrtf( 1000.0 )\n ~0.1\n > y = base.rcbrtf( 0.0 )\n Infinity\n > y = base.rcbrtf( PINF )\n 0.0\n > y = base.rcbrtf( -8.0 )\n -0.5\n > y = base.rcbrtf( NaN )\n NaN\n\n See Also\n --------\n base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n Computes the relative difference of two real numbers.\n\n By default, the function scales the absolute difference by dividing the\n absolute difference by the maximum absolute value of `x` and `y`. To scale\n by a different function, specify a scale function name.\n\n The following `scale` functions are supported:\n\n - 'max-abs': maximum absolute value of `x` and `y` (default).\n - 'max': maximum value of `x` and `y`.\n - 'min-abs': minimum absolute value of `x` and `y`.\n - 'min': minimum value of `x` and `y`.\n - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n - 'mean': arithmetic mean of `x` and `y`.\n - 'x': `x` (*noncommutative*).\n - 'y': `y` (*noncommutative*).\n\n To use a custom scale function, provide a function which accepts two numeric\n arguments `x` and `y`.\n\n If the absolute difference of `x` and `y` is `0`, the relative difference is\n always `0`.\n\n If `|x| = |y| = infinity`, the function returns `NaN`.\n\n If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n If a `scale` function returns `0`, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n scale: string|Function (optional)\n Scale function. Default: `'max-abs'`.\n\n Returns\n -------\n out: number\n Relative difference.\n\n Examples\n --------\n > var d = base.reldiff( 2.0, 5.0 )\n 0.6\n > d = base.reldiff( -1.0, 3.14 )\n ~1.318\n > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'max' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'min' )\n 3.5\n > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n 2.0\n > d = base.reldiff( -2.0, 5.0, 'mean' )\n ~4.667\n > d = base.reldiff( -2.0, 5.0, 'x' )\n 3.5\n > d = base.reldiff( 5.0, -2.0, 'x' )\n 1.4\n > d = base.reldiff( -2.0, 5.0, 'y' )\n 1.4\n > d = base.reldiff( 5.0, -2.0, 'y' )\n 3.5\n\n // Custom scale function:\n > function scale( x, y ) {\n ... var s;\n ...\n ... x = base.abs( x );\n ... y = base.abs( y );\n ...\n ... // Maximum absolute value:\n ... s = (x < y ) ? y : x;\n ...\n ... // Scale in units of epsilon:\n ... return s * EPS;\n ... };\n > d = base.reldiff( 12.15, 12.149999999999999, scale )\n ~0.658\n\n See Also\n --------\n base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n Removes the first `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirst( 'beep', 1 )\n 'eep'\n > out = base.removeFirst( 'Boop', 1 )\n 'oop'\n > out = base.removeFirst( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n Removes the first `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstCodePoint( 'beep', 1 )\n 'eep'\n > out = base.removeFirstCodePoint( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstCodePoint( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n 'eep'\n > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n 'oop'\n > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n 'ar'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n Removes the last `n` UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of UTF-16 code units to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLast( 'beep', 1 )\n 'bee'\n > out = base.removeLast( 'Boop', 1 )\n 'Boo'\n > out = base.removeLast( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n Removes the last `n` Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of Unicode code points to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastCodePoint( 'beep', 1 )\n 'bee'\n > out = base.removeLastCodePoint( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastCodePoint( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of grapheme clusters to remove.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n 'bee'\n > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n 'Boo'\n > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n 'fo'\n\n See Also\n --------\n base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n Computes `x - nπ/2 = r`.\n\n The function returns `n` and stores the remainder `r` as the two numbers\n `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n For input values larger than `2^20 * π/2` in magnitude, the function only\n returns the last three binary digits of `n` and not the full result.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: Array|TypedArray|Object\n Remainder elements.\n\n Returns\n -------\n n: integer\n Factor of `π/2`.\n\n Examples\n --------\n > var y = [ 0.0, 0.0 ];\n > var n = base.rempio2( 128.0, y )\n 81\n > var y1 = y[ 0 ]\n ~0.765\n > var y2 = y[ 1 ]\n ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = base.repeat( 'a', 5 )\n 'aaaaa'\n > out = base.repeat( '', 100 )\n ''\n > out = base.repeat( 'beep', 0 )\n ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = base.replace( 'beep', /e/, 'o' )\n 'boep'\n\n See Also\n --------\n base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n Replaces the substring after the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n 'beep foo'\n > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n 'beep bofoo'\n > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n 'Hello Wofoo'\n > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n 'beep boop beepfoo'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n Replaces the substring after the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n 'beep foo'\n > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n 'beep boofoo'\n > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n 'Hellofoo'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n Replaces the substring before the first occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n 'foo boop'\n > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n 'foooop'\n\n See Also\n --------\n base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n Replaces the substring before the last occurrence of a specified search\n string.\n\n If unable to find a search string, the function returns the input string\n unchanged.\n\n The function scans an input string from the starting index to the beginning\n of the string (i.e., backward).\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n replacement: string\n Replacement string.\n\n fromIndex: integer\n Starting index (inclusive). If less than zero, the starting index is\n resolved relative to the last string character, with the last string\n character corresponding to `fromIndex = -1`.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n 'foo boop'\n > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n 'fooop'\n > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n 'fooo World!'\n\n See Also\n --------\n base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n Reverses the UTF-16 code units of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverse( 'beep' )\n 'peeb'\n > out = base.reverse( 'Boop' )\n 'pooB'\n > out = base.reverse( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n Reverses the Unicode code points of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseCodePoints( 'beep' )\n 'peeb'\n > out = base.reverseCodePoints( 'Boop' )\n 'pooB'\n > out = base.reverseCodePoints( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = base.reverseGraphemeClusters( 'beep' )\n 'peeb'\n > out = base.reverseGraphemeClusters( 'Boop' )\n 'pooB'\n > out = base.reverseGraphemeClusters( 'foo bar' )\n 'rab oof'\n\n See Also\n --------\n base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n Right pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string\n String used to pad.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = base.rightPad( 'a', 5, ' ' )\n 'a '\n > out = base.rightPad( 'beep', 10, 'b' )\n 'beepbbbbbb'\n > out = base.rightPad( 'boop', 12, 'beep' )\n 'boopbeepbeep'\n\n See Also\n --------\n base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.rightTrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n Computes the rising factorial of `x` and `n`.\n\n If provided a non-integer for `n`, the function returns `NaN`.\n\n If provided `NaN` as any argument, the function returns `NaN`.\n\n Parameters\n ----------\n x: number\n First function parameter.\n\n n: integer\n Second function parameter.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var v = base.risingFactorial( 0.9, 5 )\n ~94.766\n > v = base.risingFactorial( -9.0, 3 )\n -504.0\n > v = base.risingFactorial( 0.0, 2 )\n 0.0\n > v = base.risingFactorial( 3.0, -2 )\n 0.5\n\n See Also\n --------\n base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n Performs a bitwise rotation to the left.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 2147483649;\n > var bStr = base.toBinaryStringUint32( x )\n '10000000000000000000000000000001'\n > var y = base.rotl32( x, 10 )\n 1536\n > bstr = base.toBinaryStringUint32( y )\n '00000000000000000000011000000000'\n\n See Also\n --------\n base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n Performs a bitwise rotation to the right.\n\n If `shift = 0`, the function returns `x`.\n\n If `shift >= 32`, the function only considers the five least significant\n bits of `shift` (i.e., `shift % 32`).\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n shift: integer\n Number of bits to shift.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var x = 1;\n > var bStr = base.toBinaryStringUint32( x )\n '00000000000000000000000000000001'\n > var y = base.rotr32( x, 10 )\n 4194304\n > bstr = base.toBinaryStringUint32( y )\n '00000000010000000000000000000000'\n\n See Also\n --------\n base.rotl32\n","base.round":"\nbase.round( x )\n Rounds a numeric value to the nearest integer.\n\n Ties are rounded toward positive infinity.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round( 3.14 )\n 3.0\n > y = base.round( -4.2 )\n -4.0\n > y = base.round( -4.6 )\n -5.0\n > y = base.round( 9.5 )\n 10.0\n > y = base.round( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n Rounds a numeric value to the nearest power of two on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round2( 3.14 )\n 4.0\n > y = base.round2( -4.2 )\n -4.0\n > y = base.round2( -4.6 )\n -4.0\n > y = base.round2( 9.5 )\n 8.0\n > y = base.round2( 13.0 )\n 16.0\n > y = base.round2( -13.0 )\n -16.0\n > y = base.round2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.round10( 3.14 )\n 1.0\n > y = base.round10( -4.2 )\n -1.0\n > y = base.round10( -4.6 )\n -1.0\n > y = base.round10( 9.5 )\n 10.0\n > y = base.round10( 13.0 )\n 10.0\n > y = base.round10( -13.0 )\n -10.0\n > y = base.round10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundb( 3.14159, -2, 10 )\n 3.14\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.roundb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two:\n > y = base.roundb( 5.0, 1, 2 )\n 6.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n`.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 2 decimal places:\n > var y = base.roundn( 3.14159, -2 )\n 3.14\n\n // If `n = 0`, standard round behavior:\n > y = base.roundn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.roundn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer (optional)\n Base. Must be greater than 0. Default: 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.roundsd( 3.14159, 3 )\n 3.14\n > y = base.roundsd( 3.14159, 1 )\n 3.0\n > y = base.roundsd( 12368.0, 2 )\n 12000.0\n > y = base.roundsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrt( 4.0 )\n 0.5\n > y = base.rsqrt( 100.0 )\n 0.1\n > y = base.rsqrt( 0.0 )\n Infinity\n > y = base.rsqrt( Infinity )\n 0.0\n > y = base.rsqrt( -4.0 )\n NaN\n > y = base.rsqrt( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the reciprocal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Reciprocal square root.\n\n Examples\n --------\n > var y = base.rsqrtf( 4.0 )\n 0.5\n > y = base.rsqrtf( 0.0 )\n Infinity\n > y = base.rsqrtf( Infinity )\n 0.0\n > y = base.rsqrtf( -4.0 )\n NaN\n > y = base.rsqrtf( NaN )\n NaN\n\n See Also\n --------\n base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string containing constructor arguments.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.sargs2multislice( 'null,null,null' );\n > s.data\n [ null, null, null ]\n > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string|DataType\n Data type.\n\n order: string\n Memory layout (either 'row-major' or 'column-major').\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n \n > var sh = ndarrayShape( x )\n []\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n Computes the secant of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Secant.\n\n Examples\n --------\n > var y = base.secd( 1.0 )\n ~1.0\n > y = base.secd( PI )\n ~1.0\n > y = base.secd( -PI )\n ~1.0\n > y = base.secd( NaN )\n NaN\n\n See Also\n --------\n base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n Converts a multidimensional subsequence string to a MultiSlice object.\n\n A multidimensional subsequence string is a comma-separated list of single-\n dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n For example, the following\n\n 2\n :\n 2:\n :10\n 2:10\n ::-1\n 10:2:-1\n :2:\n 2:10:\n 2::2\n :10:2\n :, :, :\n 1, 2, 3\n 0:10, 1:20:2, ::-1\n ...\n :, ..., 2\n\n are all valid multidimensional subsequence strings.\n\n Providing a single nonnegative integer `i` as a single-dimension index\n indexes the same elements as the subsequence `i:i+1`.\n\n Providing a single negative integer `i` as a single-dimension index indexes\n the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n size.\n\n While integers index the same elements as equivalent subsequences, providing\n an integer as a single-dimension index indicates to reduce the number of\n dimensions by one (e.g., if the provided shape corresponds to an array\n having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n In contrast, providing a subsequence indicates to retain a respective\n dimension (e.g., if the provided shape corresponds to an array having rank\n 2, then rank(A) == rank(A[':,:'])).\n\n A multidimensional subsequence string can only contain **one** ellipsis\n ('...') operator. An ellipsis indicates to apply ':' to each dimension\n necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n equals A['1:,:,:,2:5']).\n\n Except in the case of providing a single ellipsis, the number of single-\n dimension indexing expressions must equal the number of dimensions in the\n input shape.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if a single-dimension\n index expression which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n than the provided shape.\n - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n dimensions.\n - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n one ellipsis.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n shape: Array\n Maximum allowed slice shape.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: MultiSlice|Object\n MultiSlice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n > s.data\n [ ]\n > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n > s.data\n [ 4, , ]\n\n See Also\n --------\n base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n The function returns an error object if provided an invalid subsequence\n string.\n\n In strict mode, the function returns an error object if provided a\n subsequence string which exceeds index bounds.\n\n A returned error object is a plain object having the following properties:\n\n - code: error code.\n\n A returned error object may have one of the following error codes:\n\n - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n increment.\n - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n exceeding index bounds.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice|Object\n Slice instance or an error object.\n\n Examples\n --------\n > var s = new base.seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n high: integer\n Unsigned 32-bit integer to replace the higher order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same lower order word as `x`.\n\n Examples\n --------\n // Set the higher order bits of `+infinity` to return `1`:\n > var high = 1072693248 >>> 0;\n > var y = base.setHighWord( PINF, high )\n 1.0\n\n See Also\n --------\n base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n\n Setting the lower order bits of `NaN` or positive or negative infinity will\n return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n all ones and whose fraction can be any bit sequence except all zeros.\n Positive and negative infinity are defined as doubles with an exponent bit\n sequence equal to all ones and a fraction equal to all zeros. Hence,\n changing the less significant bits of positive and negative infinity\n converts each value to `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n low: integer\n Unsigned 32-bit integer to replace the lower order word of `x`.\n\n Returns\n -------\n out: number\n Double having the same higher order word as `x`.\n\n Examples\n --------\n > var low = 5 >>> 0;\n > var x = 3.14e201;\n > var y = base.setLowWord( x, low )\n 3.139998651394392e+201\n\n // Special cases:\n > var low = 12345678;\n > var y = base.setLowWord( PINF, low )\n NaN\n > y = base.setLowWord( NINF, low )\n NaN\n > y = base.setLowWord( NaN, low )\n NaN\n\n See Also\n --------\n base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n Computes the sine and cosine integrals.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: Array\n Sine and cosine integrals.\n\n Examples\n --------\n > var y = base.sici( 3.0 )\n [ ~1.849, ~0.12 ]\n > y = base.sici( 0.0 )\n [ 0.0, -Infinity ]\n > y = base.sici( -9.0 )\n [ ~-1.665, ~0.055 ]\n > y = base.sici( NaN )\n [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Sine and cosine integrals.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var y = base.sici.assign( 3.0, out, 1, 0 )\n [ ~1.849, ~0.12 ]\n > var bool = ( y === out )\n true","base.signbit":"\nbase.signbit( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbit( 4.0 )\n false\n > bool = base.signbit( -9.14e-34 )\n true\n > bool = base.signbit( 0.0 )\n false\n > bool = base.signbit( -0.0 )\n true\n\n See Also\n --------\n base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if sign bit is on or off.\n\n Examples\n --------\n > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n false\n > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n true\n > bool = base.signbitf( 0.0 )\n false\n > bool = base.signbitf( -0.0 )\n true\n\n See Also\n --------\n base.signbit\n","base.significandf":"\nbase.significandf( x )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Significand.\n\n Examples\n --------\n > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n 4293751\n > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n 5288021\n > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n 4781507\n > s = base.significandf( 0.0 )\n 0\n > s = base.significandf( NaN )\n 4194304\n\n","base.signum":"\nbase.signum( x )\n Evaluates the signum function for a double-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signum( -5.0 )\n -1.0\n > sign = base.signum( 5.0 )\n 1.0\n > sign = base.signum( -0.0 )\n -0.0\n > sign = base.signum( 0.0 )\n 0.0\n > sign = base.signum( NaN )\n NaN\n\n","base.signumf":"\nbase.signumf( x )\n Evaluates the signum function for a single-precision floating-point number.\n\n Value | Sign\n ----- | -----\n x > 0 | +1\n x < 0 | -1\n 0 | 0\n -0 | -0\n NaN | NaN\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n sign: number\n Function value.\n\n Examples\n --------\n > var sign = base.signumf( -5.0 )\n -1.0\n > sign = base.signumf( 5.0 )\n 1.0\n > sign = base.signumf( -0.0 )\n -0.0\n > sign = base.signumf( 0.0 )\n 0.0\n > sign = base.signumf( NaN )\n NaN\n\n See Also\n --------\n base.signum\n","base.sin":"\nbase.sin( x )\n Computes the sine of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Sine.\n\n Examples\n --------\n > var y = base.sin( 0.0 )\n ~0.0\n > y = base.sin( PI/2.0 )\n ~1.0\n > y = base.sin( -PI/6.0 )\n ~-0.5\n > y = base.sin( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n Computes the normalized cardinal sine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Cardinal sine.\n\n Examples\n --------\n > var y = base.sinc( 0.5 )\n ~0.637\n > y = base.sinc( -1.2 )\n ~-0.156\n > y = base.sinc( 0.0 )\n 1.0\n > y = base.sinc( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.sincos":"\nbase.sincos( x )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: Array\n Sine and cosine.\n\n Examples\n --------\n > var y = base.sincos( 0.0 )\n [ ~0.0, ~1.0 ]\n > y = base.sincos( PI/2.0 )\n [ ~1.0, ~0.0 ]\n > y = base.sincos( -PI/6.0 )\n [ ~-0.5, ~0.866 ]\n > y = base.sincos( NaN )\n [ NaN, NaN ]\n\n\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincos.assign":"\nbase.sincos.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Sine and cosine.\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincos.assign( 0.0, out, 1, 0 )\n [ ~0.0, ~1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n Simultaneously computes the sine and cosine of a number times π.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: Array\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var y = base.sincospi( 0.0 )\n [ 0.0, 1.0 ]\n > y = base.sincospi( 0.5 )\n [ 1.0, 0.0 ]\n > y = base.sincospi( 0.1 )\n [ ~0.309, ~0.951 ]\n > y = base.sincospi( NaN )\n [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n\n Parameters\n ----------\n x: number\n Input value.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Two-element array containing sin(πx) and cos(πx).\n\n Examples\n --------\n > var out = new Float64Array( 2 );\n > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n [ 0.0, 1.0 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n Computes the hyperbolic sine of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic sine.\n\n Examples\n --------\n > var y = base.sinh( 0.0 )\n 0.0\n > y = base.sinh( 2.0 )\n ~3.627\n > y = base.sinh( -2.0 )\n ~-3.627\n > y = base.sinh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n Computes the value of `sin(πx)`.\n\n The function computes `sin(πx)` more accurately than the obvious approach,\n especially for large `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.sinpi( 0.0 )\n 0.0\n > y = base.sinpi( 0.5 )\n 1.0\n > y = base.sinpi( 0.9 )\n ~0.309\n > y = base.sinpi( NaN )\n NaN\n\n See Also\n --------\n base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n Converts a Slice object to a subsequence string.\n\n Parameters\n ----------\n slice: Slice\n Input slice.\n\n Returns\n -------\n out: string\n Subsequence string.\n\n Examples\n --------\n > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n '1:10:1'\n > out = base.slice2seq( new Slice( null, 10 ) )\n ':10'\n\n See Also\n --------\n base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n Returns the number of elements in a normalized slice.\n\n Parameters\n ----------\n slice: Slice\n Input normalized slice object.\n\n Returns\n -------\n len: integer\n Number of elements.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > base.sliceLength( s )\n 9\n\n See Also\n --------\n base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceNonReducedDimensions( s )\n [ 2 ]\n\n See Also\n --------\n base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input slice object.\n\n Returns\n -------\n out: Array\n Dimension indices.\n\n Examples\n --------\n > var s = new MultiSlice( 1, 3, null );\n > var out = base.sliceReducedDimensions( s )\n [ 0, 1 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n Returns the shape of a normalized multi-slice.\n\n Parameters\n ----------\n slice: MultiSlice\n Input normalized multi-slice object.\n\n Returns\n -------\n sh: Array\n Slice shape.\n\n Examples\n --------\n > var s = new Slice( 1, 10, 1 );\n > var ms = new MultiSlice( s, s );\n > base.sliceShape( ms )\n [ 9, 9 ]\n\n See Also\n --------\n base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = base.snakecase( 'Hello World!' )\n 'hello_world'\n > out = base.snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n Evaluates Spence's function, which is also known as the dilogarithm.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.spence( 3.0 )\n ~-1.437\n > y = base.spence( 0.0 )\n ~1.645\n > y = base.spence( -9.0 )\n NaN\n > y = base.spence( NaN )\n NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n Computes the principal square root of a double-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrt( 4.0 )\n 2.0\n > y = base.sqrt( 9.0 )\n 3.0\n > y = base.sqrt( 0.0 )\n 0.0\n > y = base.sqrt( -4.0 )\n NaN\n > y = base.sqrt( NaN )\n NaN\n\n See Also\n --------\n base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n Computes the principal square root of `1+x` minus one.\n\n This function is more accurate than the obvious approach for small `x`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Square root of `1+x` minus one.\n\n Examples\n --------\n > var y = base.sqrt1pm1( 3.0 )\n 1.0\n > y = base.sqrt1pm1( 0.5 )\n ~0.225\n > y = base.sqrt1pm1( 0.02 )\n ~0.01\n > y = base.sqrt1pm1( -0.5 )\n ~-0.293\n > y = base.sqrt1pm1( -1.1 )\n NaN\n > y = base.sqrt1pm1( NaN )\n NaN\n\n See Also\n --------\n base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n Computes the principal square root of a single-precision floating-point\n number.\n\n For `x < 0`, the principal square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root.\n\n Examples\n --------\n > var y = base.sqrtf( 4.0 )\n 2.0\n > y = base.sqrtf( 9.0 )\n 3.0\n > y = base.sqrtf( 0.0 )\n 0.0\n > y = base.sqrtf( -4.0 )\n NaN\n > y = base.sqrtf( NaN )\n NaN\n\n See Also\n --------\n base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n\n For `x < 0`, the square root is not defined.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Principal square root of the product of π and the input value.\n\n Examples\n --------\n > var y = base.sqrtpi( 4.0 )\n ~3.5449\n > y = base.sqrtpi( 10.0 )\n ~5.60499\n > y = base.sqrtpi( 0.0 )\n 0.0\n > y = base.sqrtpi( -4.0 )\n NaN\n > y = base.sqrtpi( NaN )\n NaN\n\n See Also\n --------\n base.sqrt","base.startcase":"\nbase.startcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = base.startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = base.startsWith( 'Beep', 'Be', 0 )\n true\n > bool = base.startsWith( 'Beep', 'ep', 0 )\n false\n > bool = base.startsWith( 'Beep', 'ee', 1 )\n true\n > bool = base.startsWith( 'Beep', 'ee', -3 )\n true\n > bool = base.startsWith( 'Beep', '', 0 )\n true\n\n See Also\n --------\n base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n\n Parameters\n ----------\n str: string\n Input string.\n \n p: number\n Probability of capitalization.\n\n Returns\n -------\n out: string\n Sticky-cased string.\n\n Examples\n --------\n > var out = base.stickycase( 'Hello World!' )\n \n\n > out = base.stickycase( 'I am a tiny little teapot' )\n \n See Also\n --------\n base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary( [ x, y, z ], shape, strides, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing two strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Binary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > function f( x, y ) { return x + y; };\n > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n > z\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n Generates a list of binary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of `3` (i.e.,\n every `3` elements define a binary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first two elements are the input data types and the\n third element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the first input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the second input argument.\n\n dtypes3: ArrayLike\n List of supported data types for the output value.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing binary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n [...]\n\n See Also\n --------\n base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n Assigns callbacks to binary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing binary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n > var t = {\n ... 'default': base.add,\n ... 'complex64': base.caddf,\n ... 'complex128': base.cadd\n ... };\n > var out = base.strided.binarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy( 2, x, -2, y, 1 )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.ccopy( 2, x1, -2, y1, 1 )\n [ 7.0, 8.0, 3.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex64Array( x.length );\n > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Complex64Array( xbuf );\n > var y0 = new Complex64Array( x0.length );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf )\n [ 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex64Array( xbuf );\n > var y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( xbuf );\n > y = new Complex64Array( x.length );\n > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n Interchanges two single-precision complex floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap( x.length, x, 1, y, 1 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap( 2, x, -2, y, 1 );\n > x\n [ 0.0, 0.0, 3.0, 4.0, 0.0, 0.0, 7.0, 8.0 ]\n > y\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using typed array views:\n > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.cswap( 2, x1, -2, y1, 1 );\n > x0\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision complex floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision complex floating-point vectors using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Complex64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n > x\n [ 6.0, 7.0, 8.0, 9.0 ]\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n > x\n [ 1.0, 2.0, 0.0, 0.0, 5.0, 6.0, 0.0, 0.0 ]\n > y\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.cuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.cuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n 14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in\n the strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.dasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.dasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var stride = 2;\n > base.strided.dasumpw( 3, x, stride )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.dasumpw( 3, x1, stride )\n 5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dcbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float64Array( x.length );\n > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n Computes the dot product of two double-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( x.length, x, 1, y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv( N, x, 2, y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabsSorted":"\nbase.strided.dmaxabsSorted( N, x, strideX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabsSorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxabsSorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxabsSorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxabsSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxSorted, base.strided.smaxabssorted\n","base.strided.dmaxabsSorted.ndarray":"\nbase.strided.dmaxabsSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxabsSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dmaxSorted, base.strided.smaxabssorted","base.strided.dmaxSorted":"\nbase.strided.dmaxSorted( N, x, strideX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxSorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmaxSorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmaxSorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dmaxSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxSorted.ndarray":"\nbase.strided.dmaxSorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmaxSorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdev.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and standard deviation equal to\n `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~2.0817 ]\n\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanstdevpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~2.0817 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvar.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn( 3, 1, x1, 2, out, 1 )\n [ ~0.3333, ~4.3333 ]\n\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n c: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > out = new Float64Array( 2 );\n > base.strided.dmeanvarpn.ndarray( 3, 1, x, 2, 1, out, 1, 0 )\n [ ~0.3333, ~4.3333 ]\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmedianSorted":"\nbase.strided.dmedianSorted( N, x, strideX )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmedianSorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmedianSorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmedianSorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dmedianSorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmedianSorted.ndarray":"\nbase.strided.dmedianSorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dmedianSorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n Computes the mid-range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.dmin( N, x1, stride )\n -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxSorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmaxSorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ -0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float64Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float64Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float64Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasum( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors( 4, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanasumors( 4, x1, 2 )\n 5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanasumors.ndarray( 4, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmean( 4, x1,2 )\n ~-0.3333\n\n\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmeanpw( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanpw( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanpw.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.dnanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.dnanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnanstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnanstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, NaN, -2.0, 2.0 ] );\n > base.strided.dnanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancepn( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancepn.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnanvarianceyc( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dnanvarianceyc.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n Computes the L2-norm of a double-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( x.length, x, 1, y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp( N, x, 2, y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n Computes the range of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.drange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.drange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.drange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.drange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n Reverses a double-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.drev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.drev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.drev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( x.length, x, 1, y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt( N, x, 2, y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.drsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n dot: number\n Dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsem( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsem( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsem.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemch( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemch( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemch.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsempn( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsempn( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsempn.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemtk( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemtk( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemtk.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemwd( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemwd( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemwd.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, strideX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc( x.length, 1, x, 1 )\n ~1.20185\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsemyc( 3, 1, x, 2 )\n ~1.20185\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsemyc( 3, 1, x1, 2 )\n ~1.20185\n\n\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Standard error of the mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n ~1.20185\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsemyc.ndarray( 3, 1, x, 2, 1 )\n ~1.20185\n\n See Also\n --------\n base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed.\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsmeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsmeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsmeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Float64Array\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Float64Array\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > var out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > out = new Float64Array( 2 );\n > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, strideX )\n Sorts a double-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n Sorts a double-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh( N, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsortsh( N, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float64Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float64Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dsqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssum.ndarray(3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc( x.length, 1.0, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dstdevyc( 3, 1.0, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dstdevyc( 3, 1.0, x1, 2 )\n ~2.0817\n\n\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dstdevyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dstdevyc.ndarray( 3, 1.0, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, strideX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dsvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dsvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dsvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n Interchanges two double-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.dswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.dtrunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float64Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n\n Parameters\n ----------\n dtype: integer\n Data type enumeration constant.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveEnum( 'float64' )\n \n > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n \n\n See Also\n --------\n base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n Returns the data type string associated with a supported data type value.\n\n Parameters\n ----------\n dtype: any\n Data type value.\n\n Returns\n -------\n out: string|null\n Data type string.\n\n Examples\n --------\n > var out = base.strided.dtypeResolveStr( 'float64' )\n 'float64'\n > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n 'float64'\n\n See Also\n --------\n base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n Returns the enumeration constant associated with a strided array data type\n string.\n\n Downstream consumers of this function should *not* rely on specific integer\n values (e.g., `INT8 == 0`). Instead, the function should be used in an\n opaque manner.\n\n Parameters\n ----------\n dtype: string\n Data type string.\n\n Returns\n -------\n out: integer|null\n Enumeration constant.\n\n Examples\n --------\n > var out = base.strided.dtypeStr2Enum( 'float64' )\n \n\n See Also\n --------\n base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.dvarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarm( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarm.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarm.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmpn( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmpn.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmpn.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, correction, mean, x, strideX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk( x.length, 1, 1.0/3.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.dvarmtk( 3, 1, 1.0/3.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, correction, mean, x, strideX, offsetX )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n mean: number\n Mean.\n\n x: Float64Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.dvarmtk.ndarray( x.length, 1, 1.0/3.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n > base.strided.dvarmtk.ndarray( 3, 1, 1.0/3.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 5.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gapx( 4, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, 0.0, 4.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and `stride` parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum( x.length, x, 1 )\n 19.0\n\n // Sum every other value:\n > s = base.strided.gasum( 3, x, 2 )\n 10.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.gasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: number\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n 19.0\n\n // Sum the last three elements:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.gasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.gasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Array|TypedArray\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied into\n `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float64Array( x0.length );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gcusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > var y = [ 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.gcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n Computes the dot product of two vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, strideX )\n Fills a strided array with a specified scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: any\n Scalar constant.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, strideX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: current array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback return value is used as the fill value for the current array\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( x.length, x, 1, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy( 3, x, 2, fill )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gfillBy( 3, x1, 2, fill )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > function fill() { return 5.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gfillBy.ndarray( 3, x, 2, 1, fill )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns a sum equal to `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n [ 1.0, 3 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x, 2, out, 1 )\n [ 1.0, 3 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn( 4, x1, 2, out, 1 )\n [ 1.0, 3 ]\n\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on a starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n out: Array|TypedArray\n Output array.\n\n strideOut: integer\n Stride length for `out`.\n\n offsetOut: integer\n Starting index for `out`.\n\n Returns\n -------\n out: Array|TypedArray\n Output array whose first element is the sum and whose second element is\n the number of non-NaN elements.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > var out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n [ 1.0, 3 ]\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n > out = [ 0.0, 0 ];\n > base.strided.gnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n [ 1.0, 3 ]\n\n See Also\n --------\n base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumors( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, strideX )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.gnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n Computes the L2-norm of a vector.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n Returns\n -------\n out: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gnrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gnrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a vector using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n nrm2: number\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, strideX )\n Reverses a strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.grev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, strideX, offsetX )\n Reverses a strided array in-place using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: ArrayLikeObject\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.grev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.grev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, strideX )\n Multiplies a vector by a scalar constant.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.gscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, strideX, offsetX )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, 0.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Array|TypedArray\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 1.0, 2.0, 3.0 ];\n > base.strided.gsort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, strideX )\n Sorts a strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using heapsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, strideX )\n Sorts a strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, strideX )\n Sorts a strided array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, strideX, offsetX )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Array|TypedArray\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > base.strided.gsortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, strideX )\n Computes the sum of strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, strideX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, strideX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, strideX )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, strideX )\n Computes the sum of strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.gsumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.gsumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.gsumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n Interchanges vectors `x` and `y`.\n\n The `N` and stride parameters determine how values from `x` are swapped with\n values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.gswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: ArrayLikeObject\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: ArrayLikeObject\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n [ 8.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n [ -4.0, 0.0 ]\n > z0\n [ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply to callback return values.\n\n clbk: Function\n Callback function which returns an array-like object containing two\n values.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n [ 4.0, -2.0, 10.0, -4.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 1.0, 1.0, 2.0, 2.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n [ 0.0, -4.0, 0.0, 0.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, strideX )\n Computes the maximum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.max( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.max( 3, x1, 2 )\n 2.0\n\n\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.max.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.max.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.maxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.maxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, strideX )\n Computes the maximum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.maxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.maxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.maxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n 14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, strideX )\n Computes the arithmetic mean of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.mean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.mean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.mean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, strideX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, strideX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, strideX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > var N = base.floor( x.length / 2 );\n > base.strided.meanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n\n The `N` and stride parameters determine which elements are accessed at\n runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, strideX )\n Computes the arithmetic mean of a strided array using pairwise summation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.meanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.meanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, 2.0 ];\n > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.meanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, strideX )\n Computes the median value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.mediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.mediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.mediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n\n Parameters\n ----------\n meta: Object\n Function meta data.\n\n meta.nargs: integer\n Total number of arguments (excluding offsets).\n\n meta.nin: integer\n Total number of input arrays.\n\n meta.nout: integer\n Total number of output arrays.\n\n dtypes: ArrayLikeObject\n List of strided array data types.\n\n obj: Object|Function\n Object on which to define properties.\n\n bool: boolean\n Boolean indicating whether the provided object should describe an\n \"ndarray\" function interface.\n\n Returns\n -------\n out: Object|Function\n Object on which properties were defined.\n\n Examples\n --------\n > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n > var dt = [ 'float64', 'float64' ];\n > var obj = {};\n > base.strided.metaDataProps( meta, dt, obj, false );\n > obj.nargs\n 7\n > obj.nin\n 1\n > obj.nout\n 1\n > obj.types\n [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, strideX )\n Computes the minimum value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.min( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.min( 3, x1, 2 )\n -2.0\n\n\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.min.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.min.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, strideX )\n Computes the minimum absolute value of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.minabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n > base.strided.minBy( 3, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.minBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, strideX )\n Computes the minimum value of a sorted strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.minsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.minsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, 2.0, 3.0 ];\n > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n > base.strided.minsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n idx: integer\n Minimum accessible index.\n\n Examples\n --------\n > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n 6\n\n See Also\n --------\n base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n > var mask = [ 0, 0, 1, 0 ];\n > base.strided.mskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.mskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n > var mask = [ 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.mskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array, a strided mask\n array, and one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1 ];\n > var offsets = [ 0, 0, 0 ];\n > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n\n The function returns a strided array having a stride length of three (i.e.,\n every three elements define a masked unary interface signature).\n\n For each signature (i.e., set of three consecutive non-overlapping strided\n array elements), the first element is the input data type, the second\n element is the mask data type, and the last element is the return data type.\n\n All signatures follow type promotion rules.\n\n The mask array data type is always `uint8`.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing masked unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing masked unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, strideX )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmax( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmax( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmax.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs( 4, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxabs( 4, x1, 2 )\n 2.0\n\n\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmaxabs.ndarray( 4, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, strideX, clbk[, thisArg] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy( x.length, x, 1, accessor )\n 8.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.nanmaxBy( 3, x, 2, accessor )\n 8.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmaxBy( 3, x1, 2, accessor )\n -4.0\n\n\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n 8.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanmaxBy.ndarray( 3, x, 2, 1, accessor )\n -4.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x =[ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, strideX )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanmin( 4, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmin( 4, x1, 2 )\n -2.0\n\n\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanmin.ndarray( 4, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, strideX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminabs( 4, x1, 2 )\n 1.0\n\n\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanminabs.ndarray( 4, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, strideX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `NaN`.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy( x.length, x, 1, accessor )\n -10.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n > base.strided.nanminBy( 4, x, 2, accessor )\n -4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanminBy( 3, x1, 2, accessor )\n -12.0\n\n\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index of `x`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n -10.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanminBy.ndarray( 3, x, 2, 1, accessor )\n -12.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmax( 4, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmax( 4, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskmin( 4, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskmin( 4, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0, NaN, NaN ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1, 0, 0 ];\n > base.strided.nanmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n > var mask = [ 0, 0, 1, 0, 0 ];\n > base.strided.nanmskrange( 5, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Array|TypedArray\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n > var mask = [ 0, 0, 0, 1, 0 ];\n > base.strided.nanmskrange.ndarray( 5, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n > base.strided.nanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, strideX )\n Computes the range of a strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanrange( 4, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrange( 4, x1, 2 )\n 4.0\n\n\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanrange.ndarray( 4, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function returns `NaN`, the value is ignored.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n > base.strided.nanrangeBy( 4, x, 2, accessor )\n 14.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanrangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.nanrangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdev( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0,NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdev( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdev.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevch( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevch( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevch.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevpn( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevpn.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevtk( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevtk( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevtk.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevwd( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevwd( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevwd.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanstdevyc( 4, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanstdevyc( 4, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanstdevyc.ndarray( 4, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariance( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariance( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariance.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancech( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancech.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancetk( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancetk( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancetk.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n > base.strided.nanvariancewd( 4, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvariancewd( 4, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n > base.strided.nanvariancewd.ndarray( 4, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, strideX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc( 4, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.nanvarianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.nanvarianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, NaN, 2.0 ];\n > base.strided.nanvarianceyc.ndarray( 4, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.nanvarianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n output array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary( [ x ], shape, strides, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride length for the strided output\n array.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting index (i.e., index offset) for\n the strided output array.\n\n fcn: Function\n Nullary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1 ];\n > var offsets = [ 0 ];\n > var fcn = constantFunction( 3.0 );\n > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n > x\n [ 3.0, 3.0, 3.0, 3.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n\n Parameters\n ----------\n x: TypedArray\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: TypedArray\n Typed array view having the same data type as the input array.\n\n Examples\n --------\n > var x = new Float64Array( 10 );\n > var out = base.strided.offsetView( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing four strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quaternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w ) { return x + y + z + w; };\n > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n > u\n [ 4.0, 8.0, 12.0, 16.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing five strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Quinary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n > v\n [ 5.0, 10.0, 15.0, 20.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, strideX )\n Computes the range of a strided array.\n\n The `N` and stride parameters determine which elements in the strided\n array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a\n typed array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.range( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.range( 3, x1, 2 )\n 4.0\n\n\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, strideX, offsetX )\n Computes the range of a strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.range.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.range.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, strideX, clbk[, thisArg] )\n Computes the range of a strided array via a callback function.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - aidx: array index.\n - sidx: strided index (offset + aidx*stride).\n - array: the input array.\n\n The callback function should return a numeric value.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( x.length, x, 1, accessor )\n 18.0\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy( 3, x, 2, accessor )\n 12.0\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.rangeBy( 3, x1, 2, accessor )\n 8.0\n\n\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > function accessor( v ) { return v * 2.0; };\n > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n 18.0\n\n // Using an index offset:\n > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n > base.strided.rangeBy.ndarray( 3, x, 2, 1, accessor )\n 8.0\n\n See Also\n --------\n base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n\n Parameters\n ----------\n x: Complex128Array|Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the input array.\n\n Returns\n -------\n out: Float64Array|Float32Array\n Real-valued floating-point array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n > x = new Complex64Array( 10 );\n > out = base.strided.reinterpretComplex( x, 0 )\n \n > bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n Returns a Float32Array view of a Complex64Array.\n\n Parameters\n ----------\n x: Complex64Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex64Array.\n\n Returns\n -------\n out: Float32Array\n Float32Array view.\n\n Examples\n --------\n > var x = new Complex64Array( 10 );\n > var out = base.strided.reinterpretComplex64( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n Returns a Float64Array view of a Complex128Array.\n\n Parameters\n ----------\n x: Complex128Array\n Input array.\n\n offset: integer\n Starting index of the view relative to the Complex128Array.\n\n Returns\n -------\n out: Float64Array\n Float64Array view.\n\n Examples\n --------\n > var x = new Complex128Array( 10 );\n > var out = base.strided.reinterpretComplex128( x, 0 )\n \n > var bool = ( out.buffer === x.buffer )\n true\n\n See Also\n --------\n base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs( N, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( x.length, x, 1, y, 1 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2( N, x, 2, y, -1 )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sabs2( N, x1, -2, y1, 1 )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, strideX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns the strided array unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( x.length, 5.0, x, 1 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx( 3, 5.0, x, 2 )\n [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapx( 3, 5.0, x1, 2 )\n [ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n > x0\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumors( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumors( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n Computes the sum of the absolute values.\n\n The sum of absolute values corresponds to the *L1* norm.\n\n The `N` and stride parameters determine which elements in `x` are used to\n compute the sum.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum( x.length, x, 1 )\n 15.0\n\n // Sum every other value:\n > s = base.strided.sasum( 3, x, 2 )\n 9.0\n\n // Use view offset; e.g., starting at 2nd element:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > s = base.strided.sasum( 3, x1, 2 )\n 12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n Computes the sum of absolute values using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n sum: float\n Sum of absolute values.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n 15.0\n\n // Sum the last three elements:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n 15.0\n\n See Also\n --------\n base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, strideX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw( x.length, x, 1 )\n 5.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sasumpw( 3, x, 2 )\n 5.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sasumpw( 3, x1, 2 )\n 5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n 5.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n 5.0\n\n See Also\n --------\n base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n [ 40.0, 31.0, 22.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > var alpha = 5.0;\n > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( x.length, x, 1, y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt( N, x, 2, y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.scbrt( N, x1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( x.length, x, 1, y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil( N, x, 2, y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sceil( N, x1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n Copies values from `x` into `y`.\n\n The `N` and stride parameters determine how values from `x` are copied\n into `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scopy( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Copies values from `x` into `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax( 3, x, 2, y, 2 )\n [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumax( 3, x1, 2, y1, 1 )\n [ -2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumaxabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin( x.length, x, 1, y, 1 )\n [ 1.0, -2.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin( 3, x, 2, y, 2 )\n [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scumin( 3, x1, 2, y1, 1 )\n [ -2.0, -2.0, -2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, -2.0, -2.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n See Also\n --------\n base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs( x.length, x, 1, y, 1 )\n [ 1.0, 1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs( 3, x, 2, y, 2 )\n [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scuminabs( 3, x1, 2, y1, 1 )\n [ 2.0, 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n See Also\n --------\n base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n See Also\n --------\n base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `y` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n [ 1.0, -1.0, 1.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var y0 = new Float32Array( x0.length );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n [ -2.0, 0.0, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sum: number\n Initial sum.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Output array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > var y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n [ 1.0, -1.0, 1.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > y = new Float32Array( x.length );\n > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n See Also\n --------\n base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad( N, x, 2, y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot( 3, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: float\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, strideX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n 16.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n 16.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n 14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Scalar constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n 16.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n 14.0\n\n See Also\n --------\n base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns the provided scalar constant.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n 9.0\n\n // Using view offsets:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n 128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing based on a starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n scalar: number\n Scalar constant added to dot product.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n out: number\n The dot product.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n -5.0\n\n // Strides:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n 9.0\n\n // Using offset indices:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n 128.0\n\n References\n ----------\n - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n NY, USA: Association for Computing Machinery: 324–25.\n doi:10.1145/355841.355848.\n\n See Also\n --------\n base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdsmeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdsmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.sdsnanmean( N, x, stride )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.sdsnanmean( N, x1, stride )\n ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnanmeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.sdsnanmeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdsnansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sdssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sdssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( x.length, 5.0, x, 1 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill( 3, 5.0, x, 2 )\n [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sfill( 3, 5.0, x1, 2 )\n [ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n > x0\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n See Also\n --------\n base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( x.length, x, 1, y, 1 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor( N, x, 2, y, -1 )\n [ 3.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sfloor( N, x1, -2, y1, 1 )\n [ 4.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ -2.0, 1.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 1.0 ]\n\n See Also\n --------\n base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( x.length, x, 1, y, 1 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv( N, x, 2, y, -1 )\n [ 0.5, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sinv( N, x1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n [ 3.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n [ 7.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n [ 0.0, 6.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.smax.ndarray( N, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxabssorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxabssorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabsSorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxabsSorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted( x.length, x, 1 )\n 3.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smaxsorted( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smaxsorted( 3, x1, 2 )\n 3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dmaxSorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smean( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smean( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smean.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeankbn2( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeankbn2( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeankbn2.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanli( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanli( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanli.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanlipw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanlipw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanlipw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanors( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanors( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanors.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpn( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpn( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpn.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanpw( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanpw( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanpw.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smeanwd( 3, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smeanwd( 3, x1, 2 )\n ~-0.3333\n\n\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smeanwd.ndarray( 3, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, strideX )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smediansorted( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smediansorted( 3, x1, 2 )\n 2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Index increment.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Median value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmedianSorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n Computes the mid-range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange( x.length, x, 1 )\n 0.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smidrange( 3, x, 2 )\n 0.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smidrange( 3, x1, 2 )\n 0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Mid-range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n 0.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n 0.0\n\n See Also\n --------\n base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.smin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.smin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.smin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.smin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, strideX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n\n The input strided array must be sorted in either strictly ascending or\n descending order.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sminsorted( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sminsorted( 3, x1, 2 )\n -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Sorted input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n [ 5.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 1.0, 0.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 5.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 4.0, 1.0, 0.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 1.0, 0.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 2.0, 3.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n [ ~1.047, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, ~0.524, 0.0, ~1.047 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.047, ~0.524 ]\n\n See Also\n --------\n base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n [ 0.0, ~-0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ ~-0.05, -1.0, 0.0, 0.25 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n [ 0.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n [ 0.0, 0.0, 4.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n [ 0.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n [ 0.0, 6.0 ]\n > z0\n [ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float32Array\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n z: Float32Array\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n fcn: Function\n Binary function to apply.\n\n Returns\n -------\n z: Float32Array\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n [ 2.0, 4.0, 0.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n [ 0.0, 0.0, 7.0, 0.0 ]\n\n See Also\n --------\n base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n > base.strided.smskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ Infinity, 0.5, 0.0, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 0.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n m: Uint8Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and stride parameters:\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n m: Float32Array\n Mask array.\n\n sm: integer\n Index increment for `m`.\n\n om: integer\n Starting index for `m`.\n\n y: Float32Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmax( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmax( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmax( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmaxabs( x.length, x, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmaxabs( 3, x, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmaxabs( 3, x1, 2 )\n 2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Maximum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmean( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmean( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmean.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmeanors( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanors( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanors.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanpn( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanpn.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, strideX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd( x.length, x, 1 )\n ~0.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd( 4, x, 2 )\n ~0.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmeanwd( 4, x1, 2 )\n ~-0.3333\n\n\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, strideX, offsetX )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: float\n The arithmetic mean.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n ~0.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snanmeanwd.ndarray( 4, x, 2, 1 )\n ~-0.3333\n\n See Also\n --------\n base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanmin( x.length, x, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanmin( 3, x, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmin( 3, x1, 2 )\n -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanminabs( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanminabs( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanminabs( 3, x1, 2 )\n 1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Minimum absolute value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n 1.0\n\n See Also\n --------\n base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n 2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax( 3, x, 2, mask, 2 )\n 2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmax( 3, x1, 2, mask1, 2 )\n 2.0\n\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride lengt for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride lengt for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 2.0\n\n See Also\n --------\n base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n -2.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin( 3, x, 2, mask, 2 )\n -2.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskmin( 3, x1, 2, mask1, 2 )\n -2.0\n\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n offsetMask: integer\n Starting index for `mask`.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n -2.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n -2.0\n\n See Also\n --------\n base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce offsets, use a typed\n array views.\n\n If a `mask` array element is `0`, the corresponding element in `x` is\n considered valid and included in computation.\n\n If a `mask` array element is `1`, the corresponding element in `x` is\n considered invalid/missing and excluded from computation.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange( 3, x, 2, mask, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanmskrange( 3, x1, 2, mask1, 2 )\n 4.0\n\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n mask: Uint8Array\n Mask array.\n\n strideMask: integer\n Index increment for `mask`.\n\n offsetMask: integer\n Stride length for `mask`.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n > base.strided.snanmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanrange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n > base.strided.snanrange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snanrange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdev( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdev( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevch( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevch( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevpn( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevpn( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevtk( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevtk( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevwd( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevwd( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > var stride = 2;\n > base.strided.snanstdevyc( N, 1, x, stride )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > stride = 2;\n > base.strided.snanstdevyc( N, 1, x1, stride )\n ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansum( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansum( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansum.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumkbn2( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > var stride = 2;\n > base.strided.snansumors( 4, x, stride )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > stride = 2;\n > base.strided.snansumors( 4, x1, stride )\n -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw( 4, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snansumpw( 4, x1, 2 )\n -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariance( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancech( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancepn( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancetk( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvariancewd( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n If every indexed element is `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > N = base.floor( x0.length / 2 );\n > base.strided.snanvarianceyc( N, 1, x1, 2 )\n ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `n - c` where `c` corresponds to the\n provided degrees of freedom adjustment and `n` corresponds to the number\n of non-`NaN` indexed elements. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n Computes the L2-norm of a single-precision floating-point vector.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0` the function returns `0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2( x.length, x, 1 )\n 3.0\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.snrm2( 3, x, 2 )\n 3.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.snrm2( 3, x1, 2 )\n 3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment.\n\n offset: integer\n Starting index.\n\n Returns\n -------\n out: float\n The L2-norm.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n 3.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n 3.0\n\n See Also\n --------\n base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp( N, x, 2, y, -1 )\n [ 0.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.sramp( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n Computes the range of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange( x.length, x, 1 )\n 4.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.srange( 3, x, 2 )\n 4.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srange( 3, x1, 2 )\n 4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Range.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.srange.ndarray( x.length, x, 1, 0 )\n 4.0\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.srange.ndarray( 3, x, 2, 1 )\n 4.0\n\n See Also\n --------\n base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, strideX )\n Reverses a single-precision floating-point strided array in-place.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( x.length, x, 1 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev( 3, x, 2 )\n [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.srev( 3, x1, 2 )\n [ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n > x0\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, strideX, offsetX )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.srev.ndarray( x.length, x, 1, 0 )\n [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.srev.ndarray( 3, x, 2, 1 )\n [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n See Also\n --------\n base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( x.length, x, 1, y, 1 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt( N, x, 2, y, -1 )\n [ ~0.333, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.srsqrt( N, x1, -2, y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0`, the function returns `x` unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( x.length, 5.0, x, 1 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal( 3, 5.0, x, 2 )\n [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sscal( 3, 5.0, x1, 2 )\n [ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n > x0\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: number\n Constant.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n See Also\n --------\n base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n\n The `N` and `stride` parameters determine which elements in the strided\n arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves the strided arrays\n are unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Stride length for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n x: Float32Array\n First input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided arrays are sorted *in-place* (i.e., the input strided\n arrays are *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n > y\n [ 2.0, 1.0, 0.0, 3.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y0\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index of `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index of `y`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n > y\n [ 3.0, 1.0, 0.0, 2.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n > y\n [ 0.0, 3.0, 2.0, 1.0 ]\n\n See Also\n --------\n base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, strideX )\n Sorts a single-precision floating-point strided array using heapsort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns the strided array\n unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssorthp( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, strideX, offsetX )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts the strided array in\n decreasing order. If `order > 0`, the function sorts the strided array\n in increasing order.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n x: Float32Array\n Output array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n Sorts a single-precision floating-point strided array using insertion sort.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^2).\n\n The algorithm is efficient for *small* strided arrays (typically N <= 20)\n and is particularly efficient for sorting strided arrays which are already\n substantially sorted.\n\n The algorithm is *stable*, meaning that the algorithm does *not* change the\n order of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortins( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n Sorts a single-precision floating-point strided array using Shellsort.\n\n The `N` and `stride` parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n sorted after `+0`.\n\n The algorithm sorts `NaN` values to the end. When sorted in increasing\n order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n values are sorted first.\n\n The algorithm has space complexity O(1) and worst case time complexity\n O(N^(4/3)).\n\n The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n The algorithm is *unstable*, meaning that the algorithm may change the order\n of strided array elements which are equal or equivalent (e.g., `NaN`\n values).\n\n The input strided array is sorted *in-place* (i.e., the input strided array\n is *mutated*).\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( x.length, 1, x, 1 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh( 2, -1, x, 2 )\n [ 3.0, -2.0, 1.0, -4.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssortsh( 2, 1, x1, 2 )\n [ -4.0, 3.0, -2.0 ]\n > x0\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n order: number\n Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n If `order > 0`, the function sorts `x` in increasing order.\n\n x: Float32Array\n Input array.\n\n stride: integer\n Index increment for `x`.\n\n offset: integer\n Starting index of `x`.\n\n Returns\n -------\n x: Float32Array\n Input array `x`.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n [ -4.0, -2.0, 1.0, 3.0 ]\n\n // Using an index offset:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n [ 1.0, -4.0, 3.0, -2.0 ]\n\n See Also\n --------\n base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( x.length, x, 1, y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt( N, x, 2, y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.ssqrt( N, x1, -2, y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.sstdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, strideX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.sstdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.sstdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.sstdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssum( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssum( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssum.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumkbn2( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumkbn2( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a starting\n index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumors( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumors( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `0.0`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw( x.length, x, 1 )\n 1.0\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.ssumpw( 3, x, 2 )\n 1.0\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.ssumpw( 3, x1, 2 )\n -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n Sum.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n 1.0\n\n // Using offset parameter:\n > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n -1.0\n\n See Also\n --------\n base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n Interchanges two single-precision floating-point vectors.\n\n The `N` and stride parameters determine how values from `x` are swapped\n with values from `y`.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the vectors are unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap( 3, x, -2, y, 1 )\n [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n // Using typed array views:\n > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n > base.strided.sswap( 3, x1, -2, y1, 1 )\n [ 6.0, 4.0, 2.0 ]\n > y0\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n First input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Second input array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Second input array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, strideX )\n Computes the standard deviation of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdev( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdev( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdev.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevch( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevch( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevch.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevpn( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevpn( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevpn.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevtk( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevtk( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevtk.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, strideX )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevwd( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevwd( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevwd.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, strideX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc( x.length, 1, x, 1 )\n ~2.0817\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.stdevyc( 3, 1, x, 2 )\n ~2.0817\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.stdevyc( 3, 1, x1, 2 )\n ~2.0817\n\n\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the standard deviation according to `N - c` where `c` corresponds to\n the provided degrees of freedom adjustment. When computing the standard\n deviation of a population, setting this parameter to `0` is the standard\n choice (i.e., the provided array contains data constituting an entire\n population). When computing the corrected sample standard deviation,\n setting this parameter to `1` is the standard choice (i.e., the provided\n array contains data sampled from a larger population; this is commonly\n referred to as Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The standard deviation.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n ~2.0817\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.stdevyc.ndarray( 3, 1, x, 2, 1 )\n ~2.0817\n\n See Also\n --------\n base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( x.length, x, 1, y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > var N = base.floor( x.length / 2 );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc( N, x, 2, y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > N = base.floor( x0.length / 2 );\n > base.strided.strunc( N, x1, -2, y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Float32Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: Float32Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var N = base.floor( x.length / 2 );\n > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n\n The `N` and stride parameters determine which elements in `x` are accessed\n at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride Length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svariancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svariancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svariancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, strideX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n > base.strided.svarianceyc( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.svarianceyc( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Float32Array\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > base.strided.svarianceyc.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing three strided input arrays and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Ternary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1, 1, 1 ];\n > var offsets = [ 0, 0, 0, 0 ];\n > function f( x, y, z ) { return x + y + z; };\n > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n > w\n [ 3.0, 6.0, 9.0, 12.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n\n The `shape` and `strides` parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > base.strided.unary( [ x, y ], shape, strides, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsets` parameter supports indexing semantics based on\n starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary callback.\n\n Examples\n --------\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var shape = [ x.length ];\n > var strides = [ 1, 1 ];\n > var offsets = [ 0, 0 ];\n > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.binary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n\n The shape and stride parameters determine which elements in the strided\n input and output arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using shape and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n > y\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > sh = [ 2 ];\n > st = [ -2, 1 ];\n > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n > y1\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offsest parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n arrays: ArrayLikeObject\n Array-like object containing one strided input array and one strided\n output array.\n\n shape: ArrayLikeObject\n Array-like object containing a single element, the number of indexed\n elements.\n\n strides: ArrayLikeObject\n Array-like object containing the stride lengths for the strided input\n and output arrays.\n\n offsets: ArrayLikeObject\n Array-like object containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n fcn: Function\n Unary function to apply to callback return values.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > var sh = [ x.length ];\n > var st = [ 1, 1 ];\n > var o = [ 0, 0 ];\n > function clbk( v ) { return v * 2.0; };\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > sh = [ 2 ];\n > st = [ 2, -1 ];\n > o = [ 1, y.length-1 ];\n > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n > y\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n Generates a list of unary interface signatures from strided array data\n types.\n\n The function returns a strided array having a stride length of two (i.e.,\n every two elements define a unary interface signature).\n\n For each signature (i.e., set of two consecutive non-overlapping strided\n array elements), the first element is the input data type and the second\n element is the return data type.\n\n All signatures follow type promotion rules.\n\n Parameters\n ----------\n dtypes1: ArrayLike\n List of supported data types for the input argument.\n\n dtypes2: ArrayLike\n List of supported data types for the output argument.\n\n options: Object (optional)\n Options.\n\n options.enums: boolean (optional)\n Boolean flag indicating whether to return signatures as a list of data\n type enumeration constants. Default: false.\n\n Returns\n -------\n out: Array\n Strided array containing unary interface signatures.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var out = base.strided.unaryDtypeSignatures( dt, dt )\n [...]\n\n See Also\n --------\n base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n Assigns callbacks to unary interfaces according to type promotion rules.\n\n Parameters\n ----------\n table: Object\n Object mapping callbacks to data types.\n\n table.default: Function\n Default callback.\n\n table.complex64: Function\n Callback to be invoked when input arrays promote to single-precision\n complex floating-point numbers.\n\n table.complex128: Function\n Callback to be invoked when input arrays promote to double precision\n complex floating-point numbers.\n\n signatures: ArrayLike\n Strided array containing unary interface signatures.\n\n Returns\n -------\n out: Array\n List of callbacks, one per signature.\n\n Examples\n --------\n > var dt = strided.dataTypes();\n > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n > var t = {\n ... 'default': base.identity,\n ... 'complex64': base.cidentityf,\n ... 'complex128': base.cidentity\n ... };\n > var out = base.strided.unarySignatureCallbacks( t, sigs )\n [...]\n\n See Also\n --------\n base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, strideX )\n Computes the variance of a strided array.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variance( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variance( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variance.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancech( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancech( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancech.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, strideX )\n Computes the variance of a strided array using a two-pass algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancepn( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancepn( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancepn.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancetk( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancetk( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancetk.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, strideX )\n Computes the variance of a strided array using Welford's algorithm.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd( x.length, 1, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.variancewd( 3, 1, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.variancewd( 3, 1, x1, 2 )\n ~4.3333\n\n\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offset` parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length.\n\n offsetX: integer\n Starting index.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.variancewd.ndarray( 3, 1, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, strideX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n\n The `N` and stride parameters determine which elements in the strided array\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use a typed\n array view.\n\n If `N <= 0`, the function returns `NaN`.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc( x.length, 1.0, x, 1 )\n ~4.3333\n\n // Using `N` and stride parameters:\n > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n > base.strided.varianceyc( 3, 1.0, x, 2 )\n ~4.3333\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > base.strided.varianceyc( 3, 1.0, x1, 2 )\n ~4.3333\n\n\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, strideX, offsetX )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameter supports indexing semantics based on a\n starting index.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n correction: number\n Degrees of freedom adjustment. Setting this parameter to a value other\n than `0` has the effect of adjusting the divisor during the calculation\n of the variance according to `N - c` where `c` corresponds to the\n provided degrees of freedom adjustment. When computing the variance of a\n population, setting this parameter to `0` is the standard choice (i.e.,\n the provided array contains data constituting an entire population).\n When computing the unbiased sample variance, setting this parameter to\n `1` is the standard choice (i.e., the provided array contains data\n sampled from a larger population; this is commonly referred to as\n Bessel's correction).\n\n x: Array|TypedArray\n Input array.\n\n strideX: integer\n Stride length for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n Returns\n -------\n out: number\n The variance.\n\n Examples\n --------\n // Standard Usage:\n > var x = [ 1.0, -2.0, 2.0 ];\n > base.strided.varianceyc.ndarray( x.length, 1.0, x, 1, 0 )\n ~4.3333\n\n // Using offset parameter:\n > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n > base.strided.varianceyc.ndarray( 3, 1.0, x, 2, 1 )\n ~4.3333\n\n See Also\n --------\n base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = new Complex128Array( x.length );\n > base.strided.zmap( 2, x, 2, y, -1, base.cidentity )\n [ 5.0, 6.0, 1.0, 2.0, 0.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Complex128Array( xbuf );\n > var y0 = new Complex128Array( x0.length );\n > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity )\n [ 7.0, 8.0, 3.0, 4.0 ]\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Complex128Array\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n y: Complex128Array\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n fcn: Function\n Unary function to apply.\n\n Returns\n -------\n y: Complex128Array\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n > var x = new Complex128Array( xbuf );\n > var y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ]\n\n // Advanced indexing:\n > x = new Complex128Array( xbuf );\n > y = new Complex128Array( x.length );\n > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity )\n [ 0.0, 0.0, 0.0, 0.0, 7.0, 8.0, 3.0, 4.0 ]\n\n See Also\n --------\n base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n Parses a string-serialized MultiSlice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: MultiSlice|null\n MultiSlice instance (or null).\n\n Examples\n --------\n > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n > s.data\n [ null, null, null ]\n > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n > s.data\n [ 10, , null ]\n\n See Also\n --------\n base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n Parses a string-serialized Slice object.\n\n The function returns `null` if provided an invalid string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n s: Slice|null\n Slice instance (or null).\n\n Examples\n --------\n > var s = new base.str2slice( 'Slice(1,10,1)' );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new base.str2slice( 'Slice(2,5,2)' );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.sub( -1.0, 5.0 )\n -6.0\n > v = base.sub( 2.0, 5.0 )\n -3.0\n > v = base.sub( 0.0, 5.0 )\n -5.0\n > v = base.sub( -0.0, 0.0 )\n -0.0\n > v = base.sub( NaN, NaN )\n NaN\n\n See Also\n --------\n base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n\n Parameters\n ----------\n x: number\n First input value.\n\n y: number\n Second input value.\n\n Returns\n -------\n z: number\n Result.\n\n Examples\n --------\n > var v = base.subf( -1.0, 5.0 )\n -6.0\n > v = base.subf( 2.0, 5.0 )\n -3.0\n > v = base.subf( 0.0, 5.0 )\n -5.0\n > v = base.subf( -0.0, 0.0 )\n -0.0\n > v = base.subf( NaN, NaN )\n NaN\n\n See Also\n --------\n base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n Sum the elements of the series given by the supplied function.\n\n Parameters\n ----------\n generator: Function\n Series function.\n\n options: Object (optional)\n Options.\n\n options.maxTerms: integer (optional)\n Maximum number of terms to be added. Default: `1000000`.\n\n options.tolerance: number (optional)\n Further terms are only added as long as the next term is greater than\n the current term times the tolerance. Default: `2.22e-16`.\n\n options.initialValue: number (optional)\n Initial value of the resulting sum. Default: `0`.\n\n Returns\n -------\n out: number\n Sum of series terms.\n\n Examples\n --------\n // Using an ES6 generator function:\n > function* geometricSeriesGenerator( x ) {\n ... var exponent = 0;\n ... while ( true ) {\n ... yield Math.pow( x, exponent );\n ... exponent += 1;\n ... }\n ... };\n > var gen = geometricSeriesGenerator( 0.9 );\n > var out = base.sumSeries( gen )\n 10\n\n // Using a closure:\n > function geometricSeriesClosure( x ) {\n ... var exponent = -1;\n ... return function() {\n ... exponent += 1;\n ... return Math.pow( x, exponent );\n ... };\n ... };\n > gen = geometricSeriesClosure( 0.9 );\n > out = base.sumSeries( gen )\n 10\n\n // Setting an initial value for the sum:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n 3\n // Changing the maximum number of terms to be summed:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n ~1.998 // Infinite sum is 2\n\n // Adjusting the used tolerance:\n > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n ~1.998\n\n","base.tan":"\nbase.tan( x )\n Computes the tangent of a number.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tan( 0.0 )\n ~0.0\n > y = base.tan( -PI/4.0 )\n ~-1.0\n > y = base.tan( PI/4.0 )\n ~1.0\n > y = base.tan( NaN )\n NaN\n\n See Also\n --------\n base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n Computes the tangent of an angle measured in degrees.\n\n Parameters\n ----------\n x: number\n Input value (in degrees).\n\n Returns\n -------\n y: number\n Tangent.\n\n Examples\n --------\n > var y = base.tand( 0.0 )\n 0.0\n > y = base.tand( 90.0 )\n Infinity\n > y = base.tand( 60.0 )\n ~1.73\n > y = base.tand( NaN )\n NaN\n\n See Also\n --------\n base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Hyperbolic tangent.\n\n Examples\n --------\n > var y = base.tanh( 0.0 )\n 0.0\n > var y = base.tanh( -0.0 )\n -0.0\n > y = base.tanh( 2.0 )\n ~0.964\n > y = base.tanh( -2.0 )\n ~-0.964\n > y = base.tanh( NaN )\n NaN\n\n See Also\n --------\n base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n bstr: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryString( 4.0 )\n '0100000000010000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PI )\n '0100000000001001001000011111101101010100010001000010110100011000'\n > str = base.toBinaryString( -1.0e308 )\n '1111111111100001110011001111001110000101111010111100100010100000'\n > str = base.toBinaryString( -3.14e-320 )\n '1000000000000000000000000000000000000000000000000001100011010011'\n > str = base.toBinaryString( 5.0e-324 )\n '0000000000000000000000000000000000000000000000000000000000000001'\n > str = base.toBinaryString( 0.0 )\n '0000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( -0.0 )\n '1000000000000000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NaN )\n '0111111111111000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( PINF )\n '0111111111110000000000000000000000000000000000000000000000000000'\n > str = base.toBinaryString( NINF )\n '1111111111110000000000000000000000000000000000000000000000000000'\n\n See Also\n --------\n base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n '01000000100000000000000000000000'\n > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n '01000000010010010000111111011011'\n > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n '11111110100101100111011010011001'\n > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n '10000000001000100011000100001011'\n > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringf( 0.0 )\n '00000000000000000000000000000000'\n > str = base.toBinaryStringf( -0.0 )\n '10000000000000000000000000000000'\n > str = base.toBinaryStringf( NaN )\n '01111111110000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_PINF )\n '01111111100000000000000000000000'\n > str = base.toBinaryStringf( FLOAT32_NINF )\n '11111111100000000000000000000000'\n\n See Also\n --------\n base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 8-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 8-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned 8-bit\n integers. Accordingly, care should be taken to ensure that only nonnegative\n integer values less than `256` (`2^8`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint8Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint8( a[ 0 ] )\n '00000001'\n > str = base.toBinaryStringUint8( a[ 1 ] )\n '00000100'\n > str = base.toBinaryStringUint8( a[ 2 ] )\n '00001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 16-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 16-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 16-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `65536` (`2^16`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint16Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint16( a[ 0 ] )\n '0000000000000001'\n > str = base.toBinaryStringUint16( a[ 1 ] )\n '0000000000000100'\n > str = base.toBinaryStringUint16( a[ 2 ] )\n '0000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n\n Except for typed arrays, JavaScript does not provide native user support for\n unsigned 32-bit integers. According to the ECMAScript standard, `number`\n values correspond to double-precision floating-point numbers. While this\n function is intended for unsigned 32-bit integers, the function will accept\n floating-point values and represent the values as if they are unsigned\n 32-bit integers. Accordingly, care should be taken to ensure that only\n nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n Parameters\n ----------\n x: integer\n Input value.\n\n Returns\n -------\n str: string\n Bit representation.\n\n Examples\n --------\n > var a = new Uint32Array( [ 1, 4, 9 ] );\n > var str = base.toBinaryStringUint32( a[ 0 ] )\n '00000000000000000000000000000001'\n > str = base.toBinaryStringUint32( a[ 1 ] )\n '00000000000000000000000000000100'\n > str = base.toBinaryStringUint32( a[ 2 ] )\n '00000000000000000000000000001001'\n\n See Also\n --------\n base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n\n Parameters\n ----------\n x: float\n Single-precision floating-point number.\n\n Returns\n -------\n out: integer\n Unsigned 32-bit integer.\n\n Examples\n --------\n > var f32 = base.float64ToFloat32( 1.337 )\n 1.3370000123977661\n > var w = base.toWordf( f32 )\n 1068180177\n\n See Also\n --------\n base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n Returns\n -------\n out: Array\n Higher and lower order words.\n\n Examples\n --------\n > var w = base.toWords( 3.14e201 )\n [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n\n When provided a destination object, the function returns an array with two\n elements: a higher order word and a lower order word, respectively. The\n lower order word contains the less significant bits, while the higher order\n word contains the more significant bits and includes the exponent and sign.\n\n Parameters\n ----------\n x: number\n Double-precision floating-point number.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Higher and lower order words.\n\n Examples\n --------\n > var out = new Uint32Array( 2 );\n > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n [ 1774486211, 2479577218 ]\n > var bool = ( w === out )\n true\n\n See Also\n --------\n base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x, writable )\n Transposes a matrix (or a stack of matrices).\n\n The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n to the original ndarray will mutate the returned ndarray and vice versa.\n\n The `writable` parameter only applies to ndarray constructors supporting\n read-only instances.\n\n If provided an ndarray with fewer than two dimensions, the function raises\n an exception.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n writable: boolean\n Boolean indicating whether the returned ndarray should be writable.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n [ [ 1, 2, 3 ], [ 4, 5, 6 ] ]\n > var y = base.transpose( x, false )\n [ [ 1, 4 ], [ 2, 5 ], [ 3, 6 ] ]\n\n See Also\n --------\n ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n Computes the nth Tribonacci number.\n\n Tribonacci numbers follow the recurrence relation\n\n F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n If `n` is greater than `63`, the function returns `NaN`, as larger\n Tribonacci numbers cannot be accurately represented due to limitations of\n double-precision floating-point format.\n\n If not provided a nonnegative integer value, the function returns `NaN`.\n\n If provided `NaN`, the function returns `NaN`.\n\n Parameters\n ----------\n n: integer\n Input value.\n\n Returns\n -------\n y: integer\n Tribonacci number.\n\n Examples\n --------\n > var y = base.tribonacci( 0 )\n 0\n > y = base.tribonacci( 1 )\n 0\n > y = base.tribonacci( 2 )\n 1\n > y = base.tribonacci( 3 )\n 1\n > y = base.tribonacci( 4 )\n 2\n > y = base.tribonacci( 64 )\n NaN\n > y = base.tribonacci( NaN )\n NaN\n\n See Also\n --------\n base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n Evaluates the trigamma function.\n\n If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n If provided `NaN`, the `function` returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.trigamma( -2.5 )\n ~9.539\n > y = base.trigamma( 1.0 )\n ~1.645\n > y = base.trigamma( 10.0 )\n ~0.105\n > y = base.trigamma( NaN )\n NaN\n > y = base.trigamma( -1.0 )\n NaN\n\n See Also\n --------\n base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = base.trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n Rounds a double-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc( 3.14 )\n 3.0\n > y = base.trunc( -4.2 )\n -4.0\n > y = base.trunc( -4.6 )\n -4.0\n > y = base.trunc( 9.5 )\n 9.0\n > y = base.trunc( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n Rounds a numeric value to the nearest power of two toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc2( 3.14 )\n 2.0\n > y = base.trunc2( -4.2 )\n -4.0\n > y = base.trunc2( -4.6 )\n -4.0\n > y = base.trunc2( 9.5 )\n 8.0\n > y = base.trunc2( 13.0 )\n 8.0\n > y = base.trunc2( -13.0 )\n -8.0\n > y = base.trunc2( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n Rounds a numeric value to the nearest power of ten toward zero.\n\n The function may not return accurate results for subnormals due to a general\n loss in precision.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.trunc10( 3.14 )\n 1.0\n > y = base.trunc10( -4.2 )\n -1.0\n > y = base.trunc10( -4.6 )\n -1.0\n > y = base.trunc10( 9.5 )\n 1.0\n > y = base.trunc10( 13.0 )\n 10.0\n > y = base.trunc10( -13.0 )\n -10.0\n > y = base.trunc10( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string\n Custom replacement sequence.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = base.truncateMiddle( str, 5, '...' )\n 'b...p'\n > out = base.truncateMiddle( str, 5, '|' )\n 'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n Due to floating-point rounding error, rounding may not be exact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power.\n\n b: integer\n Base.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncb( 3.14159, -4, 10 )\n 3.1415\n\n // If `n = 0` or `b = 1`, standard round behavior:\n > y = base.truncb( 3.14159, 0, 2 )\n 3.0\n\n // Round to nearest multiple of two toward zero:\n > y = base.truncb( 5.0, 1, 2 )\n 4.0\n\n See Also\n --------\n base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n Rounds a single-precision floating-point number toward zero.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncf( 3.14 )\n 3.0\n > y = base.truncf( -4.2 )\n -4.0\n > y = base.truncf( -4.6 )\n -4.0\n > y = base.truncf( 9.5 )\n 9.0\n > y = base.truncf( -0.0 )\n -0.0\n\n See Also\n --------\n base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n When operating on floating-point numbers in bases other than `2`, rounding\n to specified digits can be inexact.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Integer power of 10.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n // Round to 4 decimal places:\n > var y = base.truncn( 3.14159, -4 )\n 3.1415\n\n // If `n = 0`, standard round behavior:\n > y = base.truncn( 3.14159, 0 )\n 3.0\n\n // Round to nearest thousand:\n > y = base.truncn( 12368.0, 3 )\n 12000.0\n\n\n See Also\n --------\n base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n\n Parameters\n ----------\n x: number\n Input value.\n\n n: integer\n Number of significant figures. Must be greater than 0.\n\n b: integer\n Base. Must be greater than 0.\n\n Returns\n -------\n y: number\n Rounded value.\n\n Examples\n --------\n > var y = base.truncsd( 3.14159, 5, 10 )\n 3.1415\n > y = base.truncsd( 3.14159, 1, 10 )\n 3.0\n > y = base.truncsd( 12368.0, 2, 10 )\n 12000.0\n > y = base.truncsd( 0.0313, 2, 2 )\n 0.03125\n\n See Also\n --------\n base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Signed 32-bit integer.\n\n Examples\n --------\n > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n -1\n > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n 3\n\n","base.umul":"\nbase.umul( x, y )\n Multiples two unsigned 32-bit integers.\n\n The function performs C-like multiplication of two unsigned 32-bit integers,\n including wraparound semantics.\n\n Parameters\n ----------\n x: integer\n Unsigned 32-bit integer.\n\n y: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: integer\n Product.\n\n Examples\n --------\n > var v = base.umul( 10>>>0, 4>>>0 )\n 40\n\n See Also\n --------\n base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n Returns\n -------\n out: Array\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var v = base.umuldw( 1, 10 )\n [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n\n When computing the product of 32-bit integer values in double-precision\n floating-point format (the default JavaScript numeric data type), computing\n the double word product is necessary in order to avoid exceeding the maximum\n safe double-precision floating-point integer value.\n\n Parameters\n ----------\n a: integer\n Unsigned 32-bit integer.\n\n b: integer\n Unsigned 32-bit integer.\n\n out: Array|TypedArray|Object\n Output array.\n\n stride: integer\n Output array stride.\n\n offset: integer\n Output array index offset.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Double word product (in big endian order; i.e., the first element\n corresponds to the most significant bits and the second element to the\n least significant bits).\n\n Examples\n --------\n > var out = [ 0, 0 ];\n > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n [ 0, 10 ]\n > var bool = ( v === out )\n true\n\n See Also\n --------\n base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = base.uncapitalize( 'Beep' )\n 'beep'\n > out = base.uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = base.uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n base.lowercase\n","base.vercos":"\nbase.vercos( x )\n Computes the versed cosine.\n\n The versed cosine is defined as `1 + cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed cosine.\n\n Examples\n --------\n > var y = base.vercos( 3.14 )\n ~0.0\n > y = base.vercos( -4.2 )\n ~0.5097\n > y = base.vercos( -4.6 )\n ~0.8878\n > y = base.vercos( 9.5 )\n ~0.0028\n > y = base.vercos( -0.0 )\n 2.0\n\n See Also\n --------\n base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n Computes the versed sine.\n\n The versed sine is defined as `1 - cos(x)`.\n\n Parameters\n ----------\n x: number\n Input value (in radians).\n\n Returns\n -------\n y: number\n Versed sine.\n\n Examples\n --------\n > var y = base.versin( 3.14 )\n ~2.0\n > y = base.versin( -4.2 )\n ~1.490\n > y = base.versin( -4.6 )\n ~1.112\n > y = base.versin( 9.5 )\n ~1.997\n > y = base.versin( -0.0 )\n 0.0\n\n See Also\n --------\n base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n Wraps a value to the half-open interval `[min,max)`.\n\n The function does not distinguish between positive and negative zero. Where\n appropriate, the function returns positive zero.\n\n If provided `NaN` for any argument, the function returns `NaN`.\n\n Parameters\n ----------\n v: number\n Value to wrap.\n\n min: number\n Minimum value.\n\n max: number\n Maximum value.\n\n Returns\n -------\n y: number\n Wrapped value.\n\n Examples\n --------\n > var y = base.wrap( 3.14, 0.0, 5.0 )\n 3.14\n > y = base.wrap( -3.14, 0.0, 5.0 )\n ~1.86\n > y = base.wrap( 3.14, 0.0, 3.0 )\n ~0.14\n > y = base.wrap( -0.0, 0.0, 5.0 )\n 0.0\n > y = base.wrap( 0.0, -3.14, -0.0 )\n -3.14\n > y = base.wrap( NaN, 0.0, 5.0 )\n NaN\n\n See Also\n --------\n base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlog1py( 3.0, 2.0 )\n ~3.296\n > out = base.xlog1py( 1.5, 5.9 )\n ~2.897\n > out = base.xlog1py( 0.9, 1.0 )\n ~0.624\n > out = base.xlog1py( 1.0, 0.0 )\n 0.0\n > out = base.xlog1py( 0.0, -2.0 )\n 0.0\n > out = base.xlog1py( 1.5, NaN )\n NaN\n > out = base.xlog1py( 0.0, NaN )\n NaN\n > out = base.xlog1py( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n y: number\n Input value.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var out = base.xlogy( 3.0, 2.0 )\n ~2.079\n > out = base.xlogy( 1.5, 5.9 )\n ~2.662\n > out = base.xlogy( 0.9, 1.0 )\n 0.0\n > out = base.xlogy( 0.0, -2.0 )\n 0.0\n > out = base.xlogy( 1.5, NaN )\n NaN\n > out = base.xlogy( 0.0, NaN )\n NaN\n > out = base.xlogy( NaN, 2.3 )\n NaN\n\n See Also\n --------\n base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n Parameters\n ----------\n s: number\n Input value.\n\n Returns\n -------\n y: number\n Function value.\n\n Examples\n --------\n > var y = base.zeta( 1.1 )\n ~10.584\n > y = base.zeta( -4.0 )\n 0.0\n > y = base.zeta( 70.0 )\n 1.0\n > y = base.zeta( 0.5 )\n ~-1.46\n > y = base.zeta( NaN )\n NaN\n\n // Evaluate at a pole:\n > y = base.zeta( 1.0 )\n NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n\n Each array element has the following eleven fields:\n\n - education: number of years of education.\n - south: indicator variable for southern region (1 if a person lives in the\n South; 0 if a person does not live in the South).\n - gender: gender of the person.\n - experience: number of years of work experience.\n - union: indicator variable for union membership (1 if union member; 0 if\n not a union member).\n - wage: log-transformed wage (in dollars per hour).\n - age: age (in years).\n - race: ethnicity/race (white, hispanic, and other).\n - occupation: occupational category (management, sales, clerical, service,\n professional, and other).\n - sector: sector (other, manufacturing, or construction).\n - married: marital status (0 if unmarried; 1 if married).\n\n Based on residual plots, wages were log-transformed to stabilize the\n variance.\n\n Returns\n -------\n out: Array\n CPS data.\n\n Examples\n --------\n > var data = BERNDT_CPS_WAGES_1985()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n Splits values into two groups.\n\n If an element in `filter` is truthy, then the corresponding element in the\n input collection belongs to the first group; otherwise, the collection\n element belongs to the second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n filter: Array|TypedArray|Object\n A collection indicating which group an element in the input collection\n belongs to. If an element in `filter` is truthy, the corresponding\n element in `collection` belongs to the first group; otherwise, the\n collection element belongs to the second group. If provided an object,\n the object must be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var f = [ true, true, false, true ];\n > var out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n > f = [ 1, 1, 0, 1 ];\n > out = bifurcate( collection, f )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > f = [ true, true, false, true ];\n > var opts = { 'returns': 'indices' };\n > out = bifurcate( collection, opts, f )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = bifurcate( collection, opts, f )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n See Also\n --------\n bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If a predicate function returns a truthy value, a collection value is\n placed in the first group; otherwise, a collection value is placed in the\n second group.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = bifurcateBy( collection, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ 0, 1, 3 ], [ 2 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateBy( collection, opts, predicate )\n [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an predicate function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If a predicate function calls the `next` callback with a truthy group value,\n a collection value is placed in the first group; otherwise, a collection\n value is placed in the second group.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n [ [ 1000, 3000 ], [ 2500 ] ]\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ 2, 0 ], [ 1 ] ]\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > bifurcateByAsync( arr, opts, predicate, done )\n 1000\n 2500\n 3000\n [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n // Limit number of concurrent invocations:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n // Process sequentially:\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > bifurcateByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n Returns a function which splits values into two groups according to an\n predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n Predicate function indicating which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which splits values into two groups.\n\n Examples\n --------\n > function predicate( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = bifurcateByAsync.factory( opts, predicate );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n [ [ 3000, 1000 ], [ 2500 ] ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n [ [ 2000, 1000 ], [ 1500 ] ]\n\n See Also\n --------\n bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object with no prototype, the function returns an empty\n array.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var out = bifurcateIn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateIn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n Splits values into two groups according to a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n If a predicate function returns a truthy value, a value is placed in the\n first group; otherwise, a value is placed in the second group.\n\n If provided an empty object, the function returns an empty array.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n predicate: Function\n Predicate function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Array|Array\n Group results.\n\n Examples\n --------\n > function predicate( v ) { return v[ 0 ] === 'b'; };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = bifurcateOwn( obj, predicate )\n [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = bifurcateOwn( obj, opts, predicate )\n [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n See Also\n --------\n bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n Returns a BigInt.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support BigInts.\n\n Parameters\n ----------\n value: integer|string\n Value of the BigInt.\n\n Returns\n -------\n out: BigInt\n BigInt.\n\n Examples\n --------\n > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: (number|Array)\n Number of successes or two-element array with successes and failures.\n\n n: Array (optional)\n Total number of observations.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.p: number (optional)\n Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Sample proportion.\n\n out.ci: Array\n 1-alpha confidence interval for the success probability.\n\n out.nullValue: number\n Assumed success probability under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var out = binomialTest( 682, 925 )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( [ 682, 925 - 682 ] )\n {\n 'pValue': ~3.544e-49,\n 'statistic': ~0.737\n // ...\n }\n\n > out = binomialTest( 21, 40, {\n ... 'p': 0.4,\n ... 'alternative': 'greater'\n ... })\n {\n 'pValue': ~0.074,\n 'statistic': 0.525\n // ...\n }\n\n","Boolean":"\nBoolean( value )\n Returns a boolean.\n\n When invoked without `new`,\n\n - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n string, the function returns `false`.\n - if provided any other value, including an empty object, an empty array,\n the string `'false'`, or a `Boolean` object (including a `Boolean` object\n whose value is `false`), the function returns `true`.\n\n When invoked with `new`, the constructor returns a `Boolean` object, which\n is an object wrapper for a primitive boolean value. The value of the\n returned `Boolean` object follows the same conversion semantics as when the\n constructor is invoked without `new`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: boolean|Boolean\n Boolean primitive or object.\n\n Examples\n --------\n > var b = new Boolean( null )\n \n > b = Boolean( null )\n false\n > b = Boolean( [] )\n true\n\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'\n\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n\n Returns\n -------\n out: string\n String representation.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.toString()\n 'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n\n Returns\n -------\n out: boolean\n Boolean primitive.\n\n Examples\n --------\n > var b = new Boolean( true )\n \n > b.valueOf()\n true","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray()\n \n\n\nBooleanArray( length )\n Creates a boolean array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray( booleanarray )\n Creates a boolean array from another boolean array.\n\n Parameters\n ----------\n booleanarray: BooleanArray\n Boolean array from which to generate another boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var arr2 = new BooleanArray( arr1 )\n \n > var len = arr2.length\n 4\n\n\nBooleanArray( typedarray )\n Creates a boolean array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n \n > var arr = new BooleanArray( buf )\n \n > var len = arr.length\n 4\n\n\nBooleanArray( obj )\n Creates a boolean array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a boolean array.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new BooleanArray( [ true, false, false, true ] )\n \n > var len = arr1.length\n 4\n > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n > len = arr2.length\n 4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n Returns a boolean array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new BooleanArray( buf )\n \n > var len = arr1.length\n 240\n > var arr2 = new BooleanArray( buf, 8 )\n \n > len = arr2.length\n 232\n > var arr3 = new BooleanArray( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n \n\n\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1\n\n\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10\n\n\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1\n\n\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'\n\n\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false\n\n\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true\n\n\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false\n\n\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'\n\n\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true\n\n\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n Creates a new boolean array from an array-like object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > function map( v ) { return !v };\n > var src = [ true, false ];\n > var arr = BooleanArray.from( src, map )\n \n > var len = arr.length\n 2\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n Creates a new boolean array from a variable number of arguments.\n\n Parameters\n ----------\n element0: bool\n Array element.\n\n element1: bool (optional)\n Array element.\n\n elementN: ...bool (optional)\n Array elements.\n\n Returns\n -------\n out: BooleanArray\n A typed array.\n\n Examples\n --------\n > var arr = BooleanArray.of( true, false, false, true )\n \n > var len = arr.length\n 4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n 1","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = BooleanArray.name\n 'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > var buf = arr.buffer\n ","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var nbytes = arr.byteLength\n 10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new BooleanArray( buf, 64 )\n \n > offset = arr.byteOffset\n 64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > var len = arr.length\n 10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n An array element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > var v = arr.at( 1 )\n false\n > v = arr.at( -1 )\n true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, true ]\n > v = it.next().value\n [ 1, false ]\n > v = it.next().value\n [ 2, true ]\n > var bool = it.next().done\n true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, true, true ] )\n \n > var bool = arr.every( predicate )\n true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: boolean\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( 3 )\n \n > arr.fill( true );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v === true ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.find( predicate )\n true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findIndex( predicate )\n 0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var v = arr.findLast( predicate )\n true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new BooleanArray( [ true, false, false, true ] )\n \n > arr.forEach( clbk );\n > str\n '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: boolean|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new BooleanArray( 10 )\n \n > arr.set( true, 0 );\n > var v = arr.get( 0 )\n true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var bool = arr.includes( true )\n true\n > bool = arr.includes( false, 3 )\n false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, true, true ] )\n \n > var idx = arr.indexOf( true )\n 0\n > idx = arr.indexOf( false, 3 )\n -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.join()\n 'true,false,true'\n > str = arr.join( '|' )\n 'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: boolean\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, true, true, false, true ] )\n \n > var idx = arr.lastIndexOf( false )\n 3\n > idx = arr.lastIndexOf( false, 2 )\n -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: BooleanArray\n A new typed array.\n\n Examples\n --------\n > function invert( v ) { return !v; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.map( invert )\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduce( reducer )\n false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > function reducer( acc, v ) { return ( acc && v ); };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.reduceRight( reducer )\n false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > arr.reverse();\n > var v = arr.get( 0 )\n false\n > v = arr.get( 1 )\n false\n > v = arr.get( 2 )\n true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n truthy and falsy values.\n\n Parameters\n ----------\n v: bool|BooleanArray|ArrayLikeObject\n Boolean value or Boolean value array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new BooleanArray( 2 )\n \n > arr.set( false );\n > var v = arr.get( 0 )\n false\n > arr.set( true, 1 );\n > v = arr.get( 1 )\n true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 4\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return v === true; };\n > var arr = new BooleanArray( [ false, true, false ] )\n \n > var bool = arr.some( predicate )\n true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > arr.sort( compare );\n > var v = arr.get( 0 )\n true\n > v = arr.get( 1 )\n true\n > v = arr.get( 2 )\n false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: BooleanArray\n New typed array view.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true, false, true ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toLocaleString()\n 'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, false ] )\n \n > var out = arr.toReversed()\n \n > var v = out.get( 0 )\n false\n > v = out.get( 1 )\n false\n > v = out.get( 2 )\n true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first boolean value for comparison.\n - b: second boolean value for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a === true ? -1 : 1; };\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.toSorted( compare );\n > var v = out.get( 0 )\n true\n > v = out.get( 1 )\n true\n > v = out.get( 2 )\n false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n out: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var str = arr.toString()\n 'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false ] )\n \n > var it = arr.values();\n > var v = it.next().value\n true\n > v = it.next().value\n false\n > var bool = it.next().done\n true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: boolean\n Element value.\n\n Returns\n -------\n out: BooleanArray\n New typed array.\n\n Examples\n --------\n > var arr = new BooleanArray( [ true, false, true ] )\n \n > var out = arr.with( 0, false )\n \n > var v = out.get( 0 )\n false\n\n\n See Also\n --------\n ArrayBuffer","BooleanVector":"\nBooleanVector( [options] )\n Returns a one-dimensional boolean ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = BooleanVector()\n \n\n\nBooleanVector( length[, options] )\n Returns a one-dimensional boolean ndarray having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = BooleanVector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nBooleanVector( obj[, options] )\n Creates a one-dimensional boolean ndarray from an array-like object or\n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ true, false, true ];\n > var arr = BooleanVector( v )\n \n > var len = numel( arr )\n 3\n\n\nBooleanVector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional boolean ndarray view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = BooleanVector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, vector, ndarray\n","broadcastArray":"\nbroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape.\n\n The returned array is a read-only view on the input array data buffer. The\n view is typically *not* contiguous. As more than one element of a returned\n view may refer to the same memory location, writing to the input array may\n affect multiple elements. If you need to write to the input array, copy the\n input array before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n The function always returns a new ndarray instance even if the input ndarray\n shape and the desired shape are the same.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = broadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n The returned arrays are read-only views on their respective underlying\n array data buffers. The views are typically **not** contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input array, copy the array before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n The function always returns new ndarray instances even if an input ndarray\n and the broadcasted shape are the same.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = broadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n Buffer constructor.\n\n\nBuffer( size )\n Allocates a buffer having a specified number of bytes.\n\n Parameters\n ----------\n size: integer\n Number of bytes to allocate.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 4 )\n \n\n\nBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n > var b2 = new Buffer( b1 )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n Allocates a buffer using an array of octets.\n\n Parameters\n ----------\n array: Array\n Array of octets.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( [ 1, 2, 3, 4 ] )\n [ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = new Buffer( 'beep boop' )\n \n\n\nTODO: add methods and properties\n\n\n See Also\n --------\n ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n Returns a JSON representation of a buffer.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n out.type: string\n Value type. The assigned value is always \"Buffer\".\n\n out.data: Array\n Buffer data.\n\n Examples\n --------\n > var buf = new allocUnsafe( 2 );\n > buf[ 0 ] = 1;\n > buf[ 1 ] = 2;\n > var json = buffer2json( buf )\n { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n See Also\n --------\n typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'mixed-endian'\n - 'unknown'\n\n Examples\n --------\n > BYTE_ORDER\n \n\n See Also\n --------\n IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n Converts a string to camel case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Camel-cased string.\n\n Examples\n --------\n > var out = camelcase( 'Hello World!' )\n 'helloWorld'\n > out = camelcase( 'beep boop' )\n 'beepBoop'\n\n See Also\n --------\n constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n Capitalizes the first character in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Capitalized string.\n\n Examples\n --------\n > var out = capitalize( 'beep' )\n 'Beep'\n > out = capitalize( 'Boop' )\n 'Boop'\n\n See Also\n --------\n uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n Converts the first letter of each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'aa': 1, 'bb': 2 };\n > var out = capitalizeKeys( obj )\n { 'Aa': 1, 'Bb': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n Catalan's constant.\n\n Examples\n --------\n > CATALAN\n 0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n\n Examples\n --------\n > CBRT_EPS\n 0.0000060554544523933395\n\n See Also\n --------\n EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n\n All birth data by race before 1980 are based on race of the child. Starting\n in 1980, birth data by race are based on race of the mother. Birth data are\n used to calculate infant mortality rate.\n\n Returns\n -------\n out: Object\n Infant mortality data.\n\n Examples\n --------\n > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n Changes the current working directory.\n\n If unable to set the current working directory (e.g., due to a non-existent\n path), the function returns an error; otherwise, the function returns\n `null`.\n\n Parameters\n ----------\n path: string\n Desired working directory.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = chdir( '/path/to/current/working/directory' )\n\n See Also\n --------\n cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n Performs a chi-square goodness-of-fit test.\n\n A chi-square goodness-of-fit test is computed for the null hypothesis that\n the values of `x` come from the discrete probability distribution specified\n by `y`.\n\n The second argument can either be expected frequencies, population\n probabilities summing to one, or a discrete probability distribution name to\n test against.\n\n When providing a discrete probability distribution name, distribution\n parameters *must* be supplied as additional arguments.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n By default, the p-value is computed using a chi-square distribution with\n `k-1` degrees of freedom, where `k` is the length of `x`.\n\n If provided distribution arguments are estimated (e.g., via maximum\n likelihood estimation), the degrees of freedom should be corrected. Set the\n `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n freedom adjustment.\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five.\n\n Instead of relying on chi-square approximation to calculate the p-value, one\n can use Monte Carlo simulation. When the `simulate` option is `true`, the\n simulation is performed by re-sampling from the discrete probability\n distribution specified by `y`.\n\n Parameters\n ----------\n x: ndarray|Array|TypedArray\n Observation frequencies.\n\n y: ndarray|Array|TypedArray|string\n Expected frequencies, population probabilities, or a discrete\n probability distribution name.\n\n args: ...number (optional)\n Distribution parameters. Distribution parameters will be passed to a\n probability mass function (PMF) as arguments.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.ddof: number (optional)\n Delta degrees of freedom adjustment. Default: 0.\n\n options.simulate: boolean (optional)\n Boolean indicating whether to calculate p-values by Monte Carlo\n simulation. The simulation is performed by re-sampling from the discrete\n distribution specified by `y`. Default: false.\n\n options.iterations: number (optional)\n Number of Monte Carlo iterations. Default: 500.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number|null\n Degrees of freedom.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n // Provide expected probabilities...\n > var x = [ 89, 37, 30, 28, 2 ];\n > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > var out = chi2gof( x, p );\n > var o = out.toJSON()\n { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.01 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Calculate the test p-value via Monte Carlo simulation...\n > x = [ 89, 37, 30, 28, 2 ];\n > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n > opts = { 'simulate': true, 'iterations': 1000 };\n > out = chi2gof( x, p, opts );\n > out.toString()\n\n // Verify that data comes from Poisson distribution...\n > var lambda = 3.0;\n > var rpois = base.random.poisson.factory( lambda );\n > var len = 400;\n > x = [];\n > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n // Generate a frequency table...\n > var freqs = new Int32Array( len );\n > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n > out = chi2gof( freqs, 'poisson', lambda );\n > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n Performs a chi-square independence test.\n\n For a two-way contingency table, the function computes a chi-square\n independence test for the null hypothesis that the joint distribution of the\n cell counts is the product of the row and column marginals (i.e. that the\n row and column variables are independent).\n\n The chi-square approximation may be incorrect if the observed or expected\n frequencies in each category are too small. Common practice is to require\n frequencies greater than five. The Yates' continuity correction is enabled\n by default for 2x2 tables to account for this, although it tends to\n over-correct.\n\n The function returns an object containing the test statistic, p-value, and\n decision.\n\n Parameters\n ----------\n x: ndarray|Array>\n Two-way table of observed frequencies.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Significance level of the hypothesis test. Must be on the interval\n [0,1]. Default: 0.05.\n\n options.correct: boolean (optional)\n Boolean indicating whether to use Yates' continuity correction when\n provided a 2x2 contingency table. Default: true.\n\n Returns\n -------\n out: Object\n Test results object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n Test p-value.\n\n out.statistic: number\n Test statistic.\n\n out.df: number\n Degrees of freedom.\n\n out.expected: ndarray\n Expected frequencies.\n\n out.method: string\n Test name.\n\n out.toString: Function\n Serializes results as formatted output.\n\n out.toJSON: Function\n Serializes results as JSON.\n\n Examples\n --------\n > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n > var out = chi2test( x );\n > var o = out.toJSON()\n { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Set significance level...\n > var opts = { 'alpha': 0.1 };\n > out = chi2test( x, opts );\n > o = out.toJSON()\n { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n > out.toString()\n\n // Disable Yates' continuity correction (primarily used with small counts):\n > opts = { 'correct': false };\n > out = chi2test( x, opts );\n > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, an iterator iterates over elements\n from right-to-left. Default: 1.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Source value.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n options.dir: integer (optional)\n Iteration direction. If set to `-1`, a stream iterates over elements\n from right-to-left. Default: 1.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 15 };\n > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n Circular buffer constructor.\n\n Parameters\n ----------\n buffer: integer|ArrayLike\n Buffer size or an array-like object to use as the underlying buffer.\n\n Returns\n -------\n buf: Object\n Circular buffer data structure.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.length\n 3\n > b.count\n 3\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0\n\n\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2\n\n\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true\n\n\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3\n\n\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'\n\n\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n\n Returns\n -------\n out: Object\n Circular buffer instance.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.count\n 3\n > b.clear();\n > b.count\n 0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n\n Returns\n -------\n out: integer\n Number of elements currently in the buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.count\n 0\n > b.push( 'foo' );\n > b.count\n 1\n > b.push( 'bar' );\n > b.count\n 2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a circular buffer is full.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.full\n false\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.full\n true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n Returns an iterator for iterating over a circular buffer.\n\n A returned iterator does not iterate over partially full buffers.\n\n Parameters\n ----------\n niters: integer (optional)\n Number of iterations. Default: infinity.\n\n Returns\n -------\n out: Iterator\n Iterator.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var it = b.iterator( b.length );\n > var v = it.next().value\n 'bar'\n > v = it.next().value\n 'beep'\n > v = it.next().value\n 'boop'\n > var bool = it.next().done\n true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n\n Returns\n -------\n out: integer\n Buffer length.\n\n Examples\n --------\n > var b = CircularBuffer( [ 0, 0, 0 ] );\n > var len = b.length\n 3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n Adds a value to a circular buffer.\n\n Parameters\n ----------\n value: any\n Value to add.\n\n Returns\n -------\n out: any\n Removed element (or undefined).\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' )\n undefined\n > b.push( 'bar' )\n undefined\n > b.push( 'beep' )\n undefined\n > b.push( 'boop' )\n 'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n\n Returns\n -------\n out: Array\n Circular buffer values.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var vals = b.toArray()\n [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n\n Returns\n -------\n out: Object\n Serialized circular buffer.\n\n Examples\n --------\n > var b = CircularBuffer( 3 );\n > b.push( 'foo' );\n > b.push( 'bar' );\n > b.push( 'beep' );\n > b.push( 'boop' );\n > var o = b.toJSON()\n {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n See Also\n --------\n FIFO, Stack","close":"\nclose( fd, clbk )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n clbk: Function\n Callback to invoke upon closing a file descriptor.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n Synchronously closes a file descriptor.\n\n Parameters\n ----------\n fd: integer\n File descriptor.\n\n Returns\n -------\n out: Error|void\n If an error occurs, an error object; otherwise, undefined.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.js', 'r+' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n Data includes the following:\n\n - dict: the main pronouncing dictionary.\n - phones: manners of articulation for each sound.\n - symbols: complete list of ARPABET symbols used by the dictionary.\n - vp: verbal pronunciations of punctuation marks.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n CMUdict dataset.\n\n Examples\n --------\n > var data = CMUDICT();\n > var dict = data.dict\n {...}\n > var phones = data.phones\n {...}\n > var symbols = data.symbols\n [...]\n > var vp = data.vp\n {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n Returns a Unicode code point from a string at a specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n idx: integer\n Position. If less than `0`, the string position is determined relative\n to the end of the input string.\n\n backward: boolean (optional)\n Backward iteration for low surrogates. Default: false.\n\n Returns\n -------\n out: integer\n Unicode code point.\n\n Examples\n --------\n > var out = codePointAt( 'last man standing', 4 )\n 32\n > out = codePointAt( 'presidential election', 8, true )\n 116\n > out = codePointAt( 'अनुच्छेद', 2 )\n 2369\n > out = codePointAt( '🌷', 1, true )\n 127799\n\n See Also\n --------\n fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n Returns the common own property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys of objects.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeys( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n Returns the common own and inherited property names of two or more objects.\n\n Parameters\n ----------\n obj1: any\n First object.\n\n obj2: any\n Second object.\n\n obj: ...any (optional)\n Additional objects.\n\n Returns\n -------\n out: Array\n Common keys.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > var keys = commonKeysIn( obj1, obj2 )\n [ 'a', 'b' ]\n\n See Also\n --------\n commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n Creates a complex number.\n\n The function supports the following data types:\n\n - float64\n - float32\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n z: Complex\n Complex number.\n\n Examples\n --------\n > var z = complex( 5.0, 3.0, 'float64' )\n \n > z = complex( 5.0, 3.0, 'float32' )\n \n\n See Also\n --------\n Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n 64-bit complex number constructor.\n\n Both the real and imaginary components are stored as single-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex64\n 64-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > z.re\n 5.0\n > z.im\n 3.0\n\n\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'\n\n\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4\n\n\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128\n","Complex64.name":"\nComplex64.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex64.name\n 'Complex64'","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex64.BYTES_PER_ELEMENT\n 4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 )\n \n > var s = z.byteLength\n 8\n\n See Also\n --------\n complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX64_NAN\n \n\n See Also\n --------\n COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n\n Examples\n --------\n > COMPLEX64_NUM_BYTES\n 8\n\n See Also\n --------\n COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX64_ZERO\n \n\n See Also\n --------\n COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array()\n \n\n\nComplex64Array( length )\n Creates a 64-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex64Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex64Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex64Array( typedarray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex64Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex64Array( obj )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n > var arr2 = new Complex64Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 240 );\n > var arr1 = new Complex64Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex64Array( buf, 8 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex64Array( buf, 8, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n\n\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80\n\n\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8\n\n\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n [ 3.0, -3.0, 4.0, -4.0, 3.0, -3.0, 4.0, -4.0 ]\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n -3.0\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n [ 2.0, 2.0 ]\n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n [ 1.0, -1.0, 2.0, -2.0 ]\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]\n\n\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]\n > var z = out.get( 0 )\n [ 3.0, 3.0 ]\n > z = out.get( 1 )\n [ 2.0, 2.0 ]\n > z = out.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n > z = out.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true\n\n\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex64\n Element value.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n > var z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Complex64Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex64( 1.0, -1.0 );\n > var z2 = new Complex64( 2.0, -2.0 );\n > arr = Complex64Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n 8","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex64Array.name\n 'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > var buf = arr.buffer\n ","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var nbytes = arr.byteLength\n 80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex64Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 240 );\n > arr = new Complex64Array( buf, 64 )\n \n > offset = arr.byteOffset\n 64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex64Array( 10 )\n \n > var len = arr.length\n 10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n [ 3.0, -3.0, 4.0, -4.0, 3.0, -3.0, 4.0, -4.0 ]\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n -3.0\n > var bool = it.next().done\n true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex64\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( 3 )\n \n > arr.fill( new Complex64( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n [ 2.0, 2.0 ]\n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex64|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex64\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n 0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex64Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n [ 1.0, -1.0, 2.0, -2.0 ]\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.caddf )\n [ 3.0, -3.0 ]","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.caddf )\n [ 3.0, -3.0 ]","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex64|Complex64Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex64Array( 2 )\n \n > arr.set( new Complex64( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex64Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]\n > var z = out.get( 0 )\n [ 3.0, 3.0 ]\n > z = out.get( 1 )\n [ 2.0, 2.0 ]\n > z = out.get( 2 )\n [ 1.0, 1.0 ]","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n > z = out.get( 2 )\n [ 3.0, -3.0 ]","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex64\n Element value.\n\n Returns\n -------\n out: Complex64Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n > var z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex128Array, complex, Complex64","Complex64Matrix":"\nComplex64Matrix( [options] )\n Returns a two-dimensional single-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Matrix()\n \n\n\nComplex64Matrix( shape[, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Matrix( [ 2, 2 ] )\n \n\n\nComplex64Matrix( M, N[, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Matrix( 2, 2 )\n \n\n\nComplex64Matrix( obj[, options] )\n Creates a two-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\n > var arr = Complex64Matrix( v )\n \n\n\nComplex64Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex64Matrix( buf, 0, [ 8, 1 ] )\n \n\n\nComplex64Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex64Matrix( buf, 0, 8, 1 )\n \n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex128Matrix, matrix, Complex64Vector, ndarray\n","Complex64Vector":"\nComplex64Vector( [options] )\n Returns a one-dimensional single-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Vector()\n \n\n\nComplex64Vector( length[, options] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex64Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nComplex64Vector( obj[, options] )\n Creates a one-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var arr = Complex64Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nComplex64Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Complex64Vector( buf, 0, 2 )\n \n > var len = numel( arr )\n 2\n\n See Also\n --------\n Complex64Matrix, Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, BooleanVector, vector, ndarray\n","Complex128":"\nComplex128( real, imag )\n 128-bit complex number constructor.\n\n Both the real and imaginary components are stored as double-precision\n floating-point numbers.\n\n Parameters\n ----------\n real: number\n Real component.\n\n imag: number\n Imaginary component.\n\n Returns\n -------\n z: Complex128\n 128-bit complex number.\n\n z.re: number\n Read-only property returning the real component.\n\n z.im: number\n Read-only property returning the imaginary component.\n\n\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'\n\n\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8\n\n\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64\n","Complex128.name":"\nComplex128.name\n Constructor name.\n\n Examples\n --------\n > var str = Complex128.name\n 'Complex128'","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n v: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var s = Complex128.BYTES_PER_ELEMENT\n 8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n\n Returns\n -------\n s: integer\n Size (in bytes) of each component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.BYTES_PER_ELEMENT\n 8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n\n Returns\n -------\n len: integer\n Length (in bytes) of a complex number.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 )\n \n > var s = z.byteLength\n 16\n\n See Also\n --------\n complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n\n Examples\n --------\n > COMPLEX128_NAN\n \n\n See Also\n --------\n COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n\n Examples\n --------\n > COMPLEX128_NUM_BYTES\n 16\n\n See Also\n --------\n COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n\n Examples\n --------\n > COMPLEX128_ZERO\n \n\n See Also\n --------\n COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array()\n \n\n\nComplex128Array( length )\n Creates a 128-bit complex number array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array( complexarray )\n Creates a 64-bit complex number array from another complex number array.\n\n Parameters\n ----------\n complexarray: Complex128Array\n Complex array from which to generate another complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr2 = new Complex128Array( arr1 )\n \n > var len = arr2.length\n 2\n\n\nComplex128Array( typedarray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var arr = new Complex128Array( buf )\n \n > var len = arr.length\n 2\n\n\nComplex128Array( obj )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a complex array.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var len = arr1.length\n 2\n > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n > var arr2 = new Complex128Array( buf )\n \n > len = arr2.length\n 2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 480 );\n > var arr1 = new Complex128Array( buf )\n \n > var len = arr1.length\n 30\n > var arr2 = new Complex128Array( buf, 16 )\n \n > len = arr2.length\n 29\n > var arr3 = new Complex128Array( buf, 16, 20 )\n \n > len = arr3.length\n 20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160\n\n\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16\n\n\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10\n\n\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1\n\n\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]\n\n\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare )\n [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ]\n\n\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true\n\n\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 2.0, -2.0 ]","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n\n Parameters\n ----------\n element0: number|ComplexLike\n Array element.\n\n element1: number |ComplexLike(optional)\n Array element.\n\n elementN: ...number|ComplexLike (optional)\n Array elements.\n\n Returns\n -------\n out: Complex128Array\n A typed array.\n\n Examples\n --------\n > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n \n > var len = arr.length\n 2\n > var z1 = new Complex128( 1.0, -1.0 );\n > var z2 = new Complex128( 2.0, -2.0 );\n > arr = Complex128Array.of( z1, z2 )\n \n > len = arr.length\n 2\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n 16","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Complex128Array.name\n 'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > var buf = arr.buffer\n ","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var nbytes = arr.byteLength\n 160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 480 );\n > arr = new Complex128Array( buf, 128 )\n \n > offset = arr.byteOffset\n 128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > arr.BYTES_PER_ELEMENT\n 16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Complex128Array( 10 )\n \n > var len = arr.length\n 10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n An array element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.at( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > arr.copyWithin( 0, 2 )\n \n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, [ 1.0, -1.0 ] ]\n > v = it.next().value\n [ 1, [ 2.0, -2.0 ] ]\n > v = it.next().value\n [ 2, [ 3.0, -3.0 ] ]\n > var bool = it.next().done\n true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) > 0.0 ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: Complex128\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( 3 )\n \n > arr.fill( new Complex128( 1.0, 1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, 1.0 ]\n > z = arr.get( 1 )\n [ 1.0, 1.0 ]\n > z = arr.get( 2 )\n [ 1.0, 1.0 ]","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 1\n > var z = out.get( 0 )\n [ 2.0, 2.0 ]","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.find( predicate )\n [ 1.0, 1.0 ]","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var z = arr.findLast( predicate )\n [ 2.0, 2.0 ]","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n Returns an array element located at integer position (index) `i`.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: Complex128|void\n Array element or `undefined`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n true\n > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n 2\n > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var str = arr.join()\n '1 - 1i,2 - 2i'\n > str = arr.join( '/' )\n '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: Complex128\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n 3\n > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n 0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Complex128Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v; };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.map( clbk )\n \n > var z = out.get( 0 )\n [ 1.0, -1.0 ]\n > z = out.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduce( base.cadd )\n [ 3.0, -3.0 ]","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var z = arr.reduceRight( base.cadd )\n [ 3.0, -3.0 ]","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > arr.reverse();\n > var z = arr.get( 0 )\n [ 3.0, -3.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 1.0, -1.0 ]","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an index argument `i`.\n\n To set one or more array elements, provide an array-like object containing\n either complex numbers or interleaved real and imaginary components.\n\n Parameters\n ----------\n z: Complex128|Complex128Array|ArrayLikeObject\n Complex number or complex number array.\n\n i: integer (optional)\n Array index at which to start setting elements. Default: 0.\n\n Examples\n --------\n > var arr = new Complex128Array( 2 )\n \n > arr.set( new Complex128( 1.0, -1.0 ) );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var z = out.get( 0 )\n [ 2.0, -2.0 ]\n > z = out.get( 1 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > arr.sort( compare );\n > var z = arr.get( 0 )\n [ 1.0, -1.0 ]\n > z = arr.get( 1 )\n [ 2.0, -2.0 ]\n > z = arr.get( 2 )\n [ 3.0, -3.0 ]","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Complex128Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n [ 2.0, -2.0, 3.0, -3.0 ]\n > var len = out.length\n 2","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n \n > var str = arr.toLocaleString()\n '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n \n > var out = arr.toReversed()\n [ 3.0, 3.0, 2.0, 2.0, 1.0, 1.0 ]","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function\n Comparison function.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n \n > var out = arr.toSorted( compare )\n [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ]","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n \n > var str = arr.toString()\n '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n [ 1.0, -1.0 ]\n > v = it.next().value\n [ 2.0, -2.0 ]\n > var bool = it.next().done\n true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: Complex128\n Element value.\n\n Returns\n -------\n out: Complex128Array\n New typed array.\n\n Examples\n --------\n > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n \n > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n [ 1.0, -1.0, 3.0, -3.0 ]\n\n\n See Also\n --------\n Complex64Array, complex, Complex128","Complex128Matrix":"\nComplex128Matrix( [options] )\n Returns a two-dimensional double-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Matrix()\n \n\n\nComplex128Matrix( shape[, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Matrix( [ 2, 2 ] )\n \n\n\nComplex128Matrix( M, N[, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Matrix( 2, 2 )\n \n\n\nComplex128Matrix( obj[, options] )\n Creates a two-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0, 3.0, 4.0 ], [ 5.0, 6.0, 7.0, 8.0 ] ];\n > var arr = Complex128Matrix( v )\n \n\n\nComplex128Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex128Matrix( buf, 0, [ 4, 1 ] )\n \n\n\nComplex128Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex128Matrix( buf, 0, 4, 1 )\n \n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex64Matrix, matrix, Complex128Vector, ndarray\n","Complex128Vector":"\nComplex128Vector( [options] )\n Returns a one-dimensional double-precision complex floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Vector()\n \n\n\nComplex128Vector( length[, options] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Complex128Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nComplex128Vector( obj[, options] )\n Creates a one-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var arr = Complex128Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nComplex128Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = Complex128Vector( buf, 0, 2 )\n \n > var len = numel( arr )\n 2\n\n See Also\n --------\n Complex128Matrix, Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex64Vector, BooleanVector, vector, ndarray\n","complexarray":"\ncomplexarray( [dtype] )\n Creates a complex typed array.\n\n The function supports the following data types:\n\n - complex128: double-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n\n The default typed array data type is `complex128`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray()\n \n > arr = complexarray( 'complex64' )\n \n\n\ncomplexarray( length[, dtype] )\n Returns a complex number typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr = complexarray( 5 )\n \n > arr = complexarray( 5, 'complex64' )\n \n\n\ncomplexarray( complexarray[, dtype] )\n Creates a complex number typed array from another complex number typed\n array.\n\n Parameters\n ----------\n complexarray: ComplexArray\n Complex number typed array from which to generate another complex number\n typed array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( obj[, dtype] )\n Creates a complex number typed array from an array-like object or iterable.\n\n If an array-like object contains interleaved real and imaginary components,\n the array-like object must have a length which is a multiple of two.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n > var arr2 = complexarray( arr1, 'complex64' )\n \n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a complex number typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first array element.\n Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'complex128'.\n\n Returns\n -------\n out: ComplexArray\n A complex number typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 64 );\n > var arr = complexarray( buf, 0, 8, 'complex64' )\n \n\n See Also\n --------\n typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n Returns a complex typed array constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision floating-point complex numbers.\n - complex128: double-precision floating-point complex numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Complex typed array constructor.\n\n Examples\n --------\n > var ctor = complexarrayCtors( 'complex64' )\n \n > ctor = complexarrayCtors( 'float32' )\n null\n\n See Also\n --------\n arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n\n Returns\n -------\n out: Array\n List of complex typed array data types.\n\n Examples\n --------\n > var out = complexarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n Returns a complex number constructor.\n\n The function returns constructors for the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Constructor.\n\n Examples\n --------\n > var ctor = complexCtors( 'complex128' )\n \n > ctor = complexCtors( 'complex' )\n null\n\n See Also\n --------\n complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n Returns the data type of a complex number object.\n\n If provided an argument having an unknown or unsupported type, the function\n returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string|null\n Data type.\n\n Examples\n --------\n > var v = new Complex128( 1.0, 2.0 );\n > var dt = complexDataType( v )\n 'complex128'\n > dt = complexDataType( 'beep' )\n null\n\n See Also\n --------\n arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n\n The output array contains the following data types:\n\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n\n Returns\n -------\n out: Array\n List of complex number data types.\n\n Examples\n --------\n > var out = complexDataTypes()\n \n\n See Also\n --------\n complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: string (optional)\n Data type.\n\n dtype2: string (optional)\n Data type.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = complexPromotionRules( 'complex128', 'complex64' )\n 'complex128'\n\n See Also\n --------\n arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as an argument\n to the next function. The result of the leftmost function is the result\n of the whole.\n\n Notes:\n\n - Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n - The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x ) {\n ... return 2 * x;\n ... }\n > function b( x ) {\n ... return x + 3;\n ... }\n > function c( x ) {\n ... return x / 5;\n ... }\n > var f = compose( c, b, a );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n Function composition.\n\n Returns a composite function. Starting from the right, the composite\n function evaluates each function and passes the result as the first argument\n of the next function. The result of the leftmost function is the result\n of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a composed function calls the `next` callback with a truthy `error`\n argument, the composite function suspends execution and immediately calls\n the `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the rightmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n f: ...Function\n Functions to compose.\n\n Returns\n -------\n out: Function\n Composite function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = composeAsync( c, b, a );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n compose\n","configdir":"\nconfigdir( [p] )\n Returns a directory for user-specific configuration files.\n\n On Windows platforms, the function first checks for a `LOCALAPPDATA`\n environment variable before checking for an `APPDATA` environment variable.\n This means that machine specific user configuration files have precedence\n over roaming user configuration files.\n\n On non-Windows platforms, if the function is unable to locate the current\n user's `home` directory, the function returns `null`. Similarly, on Windows\n platforms, if the function is unable to locate an application data\n directory, the function also returns `null`.\n\n Parameters\n ----------\n p: string (optional)\n Path to append to a base directory.\n\n Returns\n -------\n out: string|null\n Directory.\n\n Examples\n --------\n > var dir = configdir()\n e.g., '/Users//Library/Preferences'\n > dir = configdir( 'appname/config' )\n e.g., '/Users//Library/Preferences/appname/config'\n\n See Also\n --------\n homedir, tmpdir\n","conj":"\nconj( z )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Complex128\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conj( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n imag, real, reim\n","conjf":"\nconjf( z )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Complex64\n Complex conjugate.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > z.toString()\n '5 + 3i'\n > var v = conjf( z );\n > v.toString()\n '5 - 3i'\n\n See Also\n --------\n conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n Converts a string to constant case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Constant-cased string.\n\n Examples\n --------\n > var out = constantcase( 'Hello World!' )\n 'HELLO_WORLD'\n > out = constantcase( 'I am a tiny little teapot' )\n 'I_AM_A_TINY_LITTLE_TEAPOT'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n Creates a function which always returns the same value.\n\n Notes:\n\n - When provided an object reference, the returned `function` always returns\n the same reference.\n\n Parameters\n ----------\n val: any\n Value to always return.\n\n Returns\n -------\n out: Function\n Constant function.\n\n Examples\n --------\n > var fcn = constantFunction( 3.14 );\n > var v = fcn()\n 3.14\n > v = fcn()\n 3.14\n > v = fcn()\n 3.14\n\n See Also\n --------\n argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n Returns a readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream( 'beep', opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n Returns a function for creating readable streams which always stream the\n same value.\n\n If provided a value to stream, the returned function returns readable always\n streams the provided value.\n\n If not provided a value to stream, the returned function requires that a\n value be provided at each invocation.\n\n If provided only one argument and that argument is an object (either empty\n or not containing any recognized options properties), the function treats\n the argument as a value to be streamed, not as an options argument.\n\n Parameters\n ----------\n value: string|Buffer|Uint8Array|any (optional)\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n\n In object mode, `null` is a reserved value. If provided `null`, the\n returned stream will prematurely end.\n\n Parameters\n ----------\n value: any\n Value to stream.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = constantStream.objectMode( 3.14, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n Determines the name of a value's constructor.\n\n Parameters\n ----------\n val: any\n Input value.\n\n Returns\n -------\n out: string\n Name of a value's constructor.\n\n Examples\n --------\n > var v = constructorName( 'a' )\n 'String'\n > v = constructorName( {} )\n 'Object'\n > v = constructorName( true )\n 'Boolean'\n\n See Also\n --------\n functionName\n","contains":"\ncontains( value, searchValue[, position] )\n Tests if an array-like value contains a search value.\n\n When `value` is a string, the function checks whether the characters of the\n search string are found in the input string. The search is case-sensitive.\n\n When `value` is an array-like object, the function checks whether the input\n array contains an element strictly equal to the specified search value.\n\n For strings, this function is modeled after `String.prototype.includes`,\n part of the ECMAScript 6 specification. This function is different from a\n call to `String.prototype.includes.call` insofar as type-checking is\n performed for all arguments.\n\n The function does distinguish between positive and negative zero.\n\n If `position < 0`, the search is performed for the entire input array or\n string.\n\n\n Parameters\n ----------\n value: ArrayLike\n Input value.\n\n searchValue: any\n Value to search for.\n\n position: integer (optional)\n Position at which to start searching for `searchValue`. Default: `0`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an input value contains another value.\n\n Examples\n --------\n > var bool = contains( 'Hello World', 'World' )\n true\n > bool = contains( 'Hello World', 'world' )\n false\n > bool = contains( [ 1, 2, 3, 4 ], 2 )\n true\n > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n true\n\n // Supply a position:\n > bool = contains( 'Hello World', 'Hello', 6 )\n false\n > bool = contains( [ true, NaN, false ], true, 1 )\n false\n\n","convertArray":"\nconvertArray( arr, dtype )\n Converts an input array to an array of a different data type.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Array to convert.\n\n dtype: string\n Output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n > var out = convertArray( arr, 'float32' )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n Converts an input array to the same data type as a second input array.\n\n Parameters\n ----------\n x: ArrayLikeObject\n Array to convert.\n\n y: Array|TypedArray\n Array having desired output data type.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = new Float32Array( 0 );\n > var out = convertArraySame( x, y )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n convertArray\n","convertPath":"\nconvertPath( from, to )\n Converts between POSIX and Windows paths.\n\n Parameters\n ----------\n from: string\n Input path.\n\n to: string\n Output path convention: 'win32', 'mixed', or 'posix'.\n\n Returns\n -------\n out: string\n Converted path.\n\n Examples\n --------\n > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n 'c:\\foo\\bar\\beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n 'c:/foo/bar/beep.c'\n > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n 'C:\\\\foo\\bar\\beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n 'C:/foo/bar/beep.c'\n > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n Copy or deep clone a value to an arbitrary depth.\n\n The implementation can handle circular references.\n\n If a `Number`, `String`, or `Boolean` object is encountered, the value is\n cloned as a primitive. This behavior is intentional.\n\n For objects, the implementation only copies enumerable keys and their\n associated property descriptors.\n\n The implementation only checks whether basic `Objects`, `Arrays`, and class\n instances are extensible, sealed, and/or frozen.\n\n Functions are not cloned; their reference is copied.\n\n The implementation supports custom error types which are `Error` instances\n (e.g., ES2015 subclasses).\n\n Support for copying class instances is inherently fragile. Any instances\n with privileged access to variables (e.g., within closures) cannot be\n cloned. This stated, basic copying of class instances is supported. Provided\n an environment which supports ES5, the implementation is greedy and performs\n a deep clone of any arbitrary class instance and its properties. The\n implementation assumes that the concept of `level` applies only to the class\n instance reference, but not to its internal state.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n level: integer (optional)\n Copy depth. Default: Infinity.\n\n Returns\n -------\n out: any\n Value copy.\n\n Examples\n --------\n > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > var out = copy( value )\n [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n > var bool = ( value[ 0 ].c === out[ 0 ].c )\n false\n\n // Set the `level` option to limit the copy depth:\n > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n > out = copy( value, 1 );\n > bool = ( value[ 0 ] === out[ 0 ] )\n true\n > bool = ( value[ 0 ].c === out[ 0 ].c )\n true\n\n\n See Also\n --------\n merge\n","copyBuffer":"\ncopyBuffer( buffer )\n Copies buffer data to a new Buffer instance.\n\n Parameters\n ----------\n buffer: Buffer\n Buffer to copy from.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n > var b2 = copyBuffer( b1 )\n [ 1, 2, 3, 4 ]\n\n See Also\n --------\n allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = countBy( collection, indicator )\n { 'b': 3, 'other': 1 }\n\n See Also\n --------\n group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function and returns group counts.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"even\": 2, \"odd\": 1 }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > countByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A function which groups values and returns group counts.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = countByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"even\": 2, \"odd\": 1 }\n > arr = [ 2000, 1500, 1000, 500 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 500\n { \"even\": 2, \"odd\": 2 }\n\n See Also\n --------\n countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n Returns the current year.\n\n Returns\n -------\n out: integer\n Current year.\n\n Examples\n --------\n > var y = currentYear()\n \n\n See Also\n --------\n isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curry( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curry( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curry( obj.greet, obj );\n > var str = f( 'Hello' )( 'there' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n\n Until return value resolution, each invocation returns a new partially\n applied curry function.\n\n This function applies arguments starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Function to curry.\n\n arity: integer (optional)\n Number of parameters. Default: `fcn.length`.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Curry function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var f = curryRight( add );\n > var sum = f( 2 )( 3 )\n 5\n\n // Supply arity:\n > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n > f = curryRight( add, 2 );\n > sum = f( 2 )( 3 )\n 5\n\n // Provide function context:\n > var obj = {\n ... 'name': 'Ada',\n ... 'greet': function greet( word1, word2 ) {\n ... return word1 + ' ' + word2 + ', ' + this.name + '!'\n ... }\n ... };\n > f = curryRight( obj.greet, obj );\n > var str = f( 'there' )( 'Hello' )\n 'Hello there, Ada!'\n\n See Also\n --------\n curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n Returns the current working directory.\n\n Returns\n -------\n path: string\n Current working directory of the process.\n\n Examples\n --------\n > var dir = cwd()\n '/path/to/current/working/directory'\n\n See Also\n --------\n chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n\n Returns\n -------\n out: Array\n List of familiar American-English words.\n\n Examples\n --------\n > var list = DALE_CHALL_NEW()\n [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n References\n ----------\n - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n the new Dale-Chall readability formula*. Brookline Books.\n .\n\n","datasets":"\ndatasets( name[, options] )\n Returns a dataset.\n\n The function forwards provided options to the dataset interface specified\n by `name`.\n\n Parameters\n ----------\n name: string\n Dataset name.\n\n options: Object (optional)\n Function options.\n\n Returns\n -------\n out: any\n Dataset.\n\n Examples\n --------\n > var out = datasets( 'MONTH_NAMES_EN' )\n [ 'January', 'February', ... ]\n > var opts = { 'data': 'cities' };\n > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n [ {...}, {...}, ... ]\n\n","DataType":"\nDataType( value[, options] )\n Data type constructor.\n\n Parameters\n ----------\n value: any\n Data type value.\n\n options: Object (optional)\n Constructor options.\n\n options.description: string (optional)\n Data type description.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'\n\n\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8\n\n\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8\n\n\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'\n\n\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'\n\n\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'\n\n\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n \n\n\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'\n\n\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}\n\n\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'\n\n\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType\n\n","DataType.name":"\nDataType.name\n Constructor name.\n\n Returns\n -------\n out: string\n Constructor name.\n\n Examples\n --------\n > DataType.name\n 'DataType'","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n\n If a data type does not have a known alignment, the returned value is -1.\n\n Returns\n -------\n out: integer\n Alignment (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.alignment\n 8","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n\n If a data type does not have a known size, the returned value is -1.\n\n Returns\n -------\n out: integer\n Byte length (in bytes).\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteLength\n 8","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n\n May be one of the following values:\n\n - host: host platform byte order.\n - little-endian: little-endian byte order.\n - big-endian: big-endian byte order.\n\n Returns\n -------\n out: string\n Byte order.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.byteOrder\n 'host'","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n\n If a data type does not have a corresponding single letter character\n abbreviation, the returned value is an empty string.\n\n Returns\n -------\n out: string\n Single letter character abbreviation.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.char\n 'd'","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n\n If a data type does not have an associated description, the returned value\n is an empty string.\n\n Returns\n -------\n out: string\n Description.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.description\n '...'","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n\n If a data type does not have a corresponding known enumeration constant, the\n returned value is -1.\n\n Returns\n -------\n out: integer\n Enumeration constant.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.enum\n ","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n\n Returns\n -------\n out: any\n Data type value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.value\n 'float64'","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toJSON()\n {...}","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n\n Returns\n -------\n out: string\n Serialized string.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.toString()\n 'float64'","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n\n This method returns the same value as `#.toString()`.\n\n Returns\n -------\n out: string\n Primitive value.\n\n Examples\n --------\n > var dt = new DataType( 'float64' );\n > dt.valueOf()\n 'float64'\n\n See Also\n --------\n ndarray, ndarrayDataType","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n Returns a data view representing a provided array buffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer|SharedArrayBuffer\n Array buffer.\n\n byteOffset: integer (optional)\n Offset (in bytes) to the first byte in the array buffer for the new view\n to reference. Default: 0.\n\n byteLength: integer (optional)\n Number of elements in the byte array. If not provided, the view's length\n will equal the buffer's length.\n\n Returns\n -------\n out: DataView\n A data view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 )\n \n > var dv = new DataView( buf )\n \n\n\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true\n\n\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5\n\n\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2\n\n\nTODO: document properties/methods\n\n\n See Also\n --------\n ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n\n Examples\n --------\n > var buf1 = new ArrayBuffer( 5 );\n > var dv = new DataView( buf1 );\n > var buf2 = dv.buffer\n \n > var b = ( buf1 === buf2 )\n true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf );\n > dv.byteLength\n 5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 5 );\n > var dv = new DataView( buf, 2 );\n > dv.byteLength\n 3\n > dv.byteOffset\n 2","datespace":"\ndatespace( start, stop[, length][ , options] )\n Generates an array of linearly spaced dates.\n\n Parameters\n ----------\n start: number\n Start time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n stop: number\n Stop time as either a `Date` object, Unix timestamp, JavaScript\n timestamp, or date string.\n\n length: integer (optional)\n Length of output array. Default: `100`.\n\n options: Object (optional)\n Options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded:\n [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n Returns\n -------\n arr: Array\n Array of dates.\n\n Examples\n --------\n > var stop = '2014-12-02T07:00:54.973Z';\n > var start = new Date( stop ) - 60000;\n > var arr = datespace( start, stop, 6 )\n [...]\n\n // Equivalent of Math.ceil():\n > var opts = { 'round': 'ceil' };\n > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n [...]\n\n See Also\n --------\n linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n Returns the day of the quarter.\n\n By default, the function returns the day of the quarter for the current date\n (according to local time). To determine the day of the quarter for a\n particular day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the quarter.\n\n Examples\n --------\n > var day = dayOfQuarter()\n \n > day = dayOfQuarter( new Date() )\n \n > day = dayOfQuarter( 12, 31, 2017 )\n 92\n\n // Other ways to supply month:\n > day = dayOfQuarter( 'dec', 31, 2017 )\n 92\n > day = dayOfQuarter( 'december', 31, 2017 )\n 92\n\n See Also\n --------\n dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n Returns the day of the year.\n\n By default, the function returns the day of the year for the current date\n (according to local time). To determine the day of the year for a particular\n day, provide `month`, `day`, and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function also accepts a `Date` object.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n day: integer (optional)\n Day.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Day of the year.\n\n Examples\n --------\n > var day = dayOfYear()\n \n > day = dayOfYear( new Date() )\n \n > day = dayOfYear( 12, 31, 2016 )\n 366\n\n // Other ways to supply month:\n > day = dayOfYear( 'dec', 31, 2016 )\n 366\n > day = dayOfYear( 'december', 31, 2016 )\n 366\n\n See Also\n --------\n dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n Returns the number of days in a month.\n\n By default, the function returns the number of days in the current month\n of the current year (according to local time). To determine the number of\n days for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|integer|Date (optional)\n Month (or `Date`).\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Days in a month.\n\n Examples\n --------\n > var num = daysInMonth()\n \n > num = daysInMonth( 2 )\n \n > num = daysInMonth( 2, 2016 )\n 29\n > num = daysInMonth( 2, 2017 )\n 28\n\n // Other ways to supply month:\n > num = daysInMonth( 'feb', 2016 )\n 29\n > num = daysInMonth( 'february', 2016 )\n 29\n\n See Also\n --------\n daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n Returns the number of days in a year according to the Gregorian calendar.\n\n By default, the function returns the number of days in the current year\n (according to local time). To determine the number of days for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of days in a year.\n\n Examples\n --------\n > var num = daysInYear()\n \n > num = daysInYear( 2016 )\n 366\n > num = daysInYear( 2017 )\n 365\n\n See Also\n --------\n daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n Computes the dot product of two double-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = ddot( x, y )\n [ -5.0 ]\n\n See Also\n --------\n base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n Returns a writable stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > var s = debugSinkStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n Returns a transform stream for debugging stream pipelines.\n\n If the `DEBUG` environment variable is not set, no data is logged.\n\n Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n environment variable can be used to filter debuggers.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = debugStream( { 'name': 'foo' } );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( name[, clbk] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Debug namespace.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function (optional)\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = debugStream.objectMode( { 'name': 'foo' } );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n\n Decorators are intended to be transparent, meaning that, when interfacing\n with an API, the decorated API should have the same signature (i.e., number\n of parameters) as the decorated function.\n\n Thus, a typical value for `arity` is `fcn.length`. This function does not\n require equality, however, and the `arity` argument is allowed to diverge\n from that of the decorated function. Specifying a differing `arity` does\n *not* affect function evaluation behavior, as the returned function passes\n all provided arguments to the decorated function.\n\n If the `after` function returns `undefined`, the returned decorator returns\n the return value of the decorated function `fcn`; otherwise, the returned\n decorator returns the return value of `after`.\n\n The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n the maximum arity of the returned function is `10`). For an arity greater\n than `10`, the returned function has an arity equal to `0`. While this\n violates strict notions of a decorator, for all practical purposes, this is\n unlikely to be an issue, as the vast majority of functions have fewer than\n `10` parameters and the need for explicitly checking function length is\n relatively uncommon.\n\n Common use cases for decorating a function with additional actions *after*\n invocation include logging, capturing invocation statistics, and validating\n return values.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n\n Code generation may be problematic in browser contexts enforcing a strict\n content security policy] (CSP). If running in or targeting an environment\n with a CSP, avoid using code generation.\n\n For non-native functions, the function supports returning a decorator whose\n API exactly matches the API of the decorated function, including function\n length and parameter names.\n\n For native functions, due to how native functions serialize to strings, the\n function generates placeholder parameter names, which are unlikely to match\n the canonical parameter names. Using placeholder parameter names ensures\n that the length of the decorator (i.e., number of parameters) matches the\n decorated function and, except in scenarios involving function source code\n inspection, will not affect runtime behavior.\n\n Parameters\n ----------\n fcn: Function\n Function to decorate.\n\n arity: integer\n Number of parameters.\n\n after: Function\n Function with which to invoke the return value of the decorated\n function.\n\n thisArg: any (optional)\n Evaluation context for `after`.\n\n Returns\n -------\n out: Function\n Decorator function.\n\n Examples\n --------\n > function f( v ) { return -v; };\n > var fcn = decorateAfter.factory( base.abs, 1, f );\n > var v = fcn( -5 )\n -5\n > v = fcn( 5 )\n -5","deepEqual":"\ndeepEqual( a, b )\n Tests for deep equality between two values.\n\n Parameters\n ----------\n a: any\n First comparison value.\n\n b: any\n Second comparison value.\n\n Returns\n -------\n out: boolean\n Boolean indicating if `a` is deep equal to `b`.\n\n Examples\n --------\n > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n true\n\n > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n false\n\n > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n false\n\n See Also\n --------\n isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n Returns a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: any\n Nested property value.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a.b.c' )\n 'd'\n\n // Specify a custom separator via the `sep` option:\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n 'd'\n\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n Creates a reusable deep get function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep get factory.\n\n Examples\n --------\n > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var val = dget( obj )\n 'd'\n\n See Also\n --------\n deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path.\n\n The function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepHasOwnProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path.\n\n The returned function tests for \"own\" properties and will return `false` for\n inherited properties.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Key path array elements are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var obj = { 'a': new Foo() };\n > var bool = deepHasProp( obj, 'a.b.c' )\n true\n\n // Specify a custom separator via the `sep` option:\n > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n true\n\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Function which tests whether an object contains a nested key path.\n\n Examples\n --------\n > function Foo() { return this; };\n > Foo.prototype.b = { 'c': 'd' };\n > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n > var obj = { 'a': new Foo() };\n > var bool = has( obj )\n true\n\n See Also\n --------\n deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n Extracts a nested property value from each element of an object array.\n\n If a key path does not exist, the function sets the plucked value as\n `undefined`.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. Default:\n true.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': { 'b': { 'c': 1 } } },\n ... { 'a': { 'b': { 'c': 2 } } }\n ... ];\n > var out = deepPluck( arr, 'a.b.c' )\n [ 1, 2 ]\n > arr = [\n ... { 'a': [ 0, 1, 2 ] },\n ... { 'a': [ 3, 4, 5 ] }\n ... ];\n > out = deepPluck( arr, [ 'a', 1 ] )\n [ 1, 4 ]\n\n See Also\n --------\n deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n Sets a nested property value.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n path: string|Array\n Key path.\n\n value: any\n Value to set.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if the property was successfully set.\n\n Examples\n --------\n > var obj1 = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = deepSet( obj1, 'a.b.c', 'beep' )\n true\n\n // Specify an alternative separator via the sep option:\n > var obj2 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj2, 'a/b/c', 'beep', { 'sep': '/' } );\n > obj2\n { 'a': { 'b': { 'c': 'beep' } } }\n\n // To create a key path which does not exist, set the create option to true:\n > var obj3 = { 'a': { 'b': { 'c': 'd' } } };\n > bool = deepSet( obj3, 'a.e.c', 'boop', { 'create': true } );\n > obj3\n { 'a': { 'b': { 'c': 'd' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n Creates a reusable deep set function.\n\n Parameters\n ----------\n path: string|Array\n Key path.\n\n options: Object (optional)\n Options.\n\n options.create: boolean (optional)\n Boolean indicating whether to create a path if the key path does not\n already exist. Default: false.\n\n options.sep: string (optional)\n Key path separator. Default: '.'.\n\n Returns\n -------\n out: Function\n Deep set function.\n\n Examples\n --------\n > var dset = deepSet.factory( 'a/b/c', {\n ... 'create': true,\n ... 'sep': '/'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var bool = dset( obj, 'beep' )\n true\n > obj\n { 'a': { 'b': { 'c': 'beep' } } }\n\n See Also\n --------\n deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n Defines a memoized object property.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() {\n ... return 'bar';\n ... };\n > defineMemoizedProperty( obj, 'foo', {\n ... 'configurable': false,\n ... 'enumerable': true,\n ... 'writable': false,\n ... 'value': foo\n ... });\n > obj.foo\n 'bar'\n\n See Also\n --------\n setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n Defines (and/or modifies) object properties.\n\n The second argument is an object whose own enumerable property values are\n descriptors for the properties to be defined or modified.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n A property descriptor has the following optional properties:\n\n - configurable: boolean indicating if property descriptor can be changed and\n if the property can be deleted from the provided object. Default: false.\n\n - enumerable: boolean indicating if the property shows up when enumerating\n object properties. Default: false.\n\n - writable: boolean indicating if the value associated with the property can\n be changed with an assignment operator. Default: false.\n\n - value: property value.\n\n - get: function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used as\n the property value. Default: undefined.\n\n - set: function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called with\n one argument (the value being assigned to the property) and with the `this`\n context set to the object through which the property is assigned. Default:\n undefined.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the properties.\n\n properties: Object\n Object with property descriptors.\n\n Returns\n -------\n obj: Object\n Object on which properties were defined (and/or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperties( obj, {\n ... 'foo': {\n ... 'value': 'bar',\n ... 'writable': false,\n ... 'configurable': false,\n ... 'enumerable': true\n ... },\n ... 'baz': {\n ... 'value': 13\n ... }\n ... });\n > obj.foo\n 'bar'\n > obj.baz\n 13\n\n See Also\n --------\n defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n Defines (or modifies) an object property.\n\n Property descriptors come in two flavors: data descriptors and accessor\n descriptors. A data descriptor is a property that has a value, which may or\n may not be writable. An accessor descriptor is a property described by a\n getter-setter function pair. A descriptor must be one of these two flavors\n and cannot be both.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n descriptor: Object\n Property descriptor.\n\n descriptor.configurable: boolean (optional)\n Boolean indicating if property descriptor can be changed and if the\n property can be deleted from the provided object. Default: false.\n\n descriptor.enumerable: boolean (optional)\n Boolean indicating if the property shows up when enumerating object\n properties. Default: false.\n\n descriptor.writable: boolean (optional)\n Boolean indicating if the value associated with the property can be\n changed with an assignment operator. Default: false.\n\n descriptor.value: any (optional)\n Property value.\n\n descriptor.get: Function|void (optional)\n Function which serves as a getter for the property, or, if no getter,\n undefined. When the property is accessed, a getter function is called\n without arguments and with the `this` context set to the object through\n which the property is accessed (which may not be the object on which the\n property is defined due to inheritance). The return value will be used\n as the property value. Default: undefined.\n\n descriptor.set: Function|void (optional)\n Function which serves as a setter for the property, or, if no setter,\n undefined. When assigning a property value, a setter function is called\n with one argument (the value being assigned to the property) and with\n the `this` context set to the object through which the property is\n assigned. Default: undefined.\n\n Returns\n -------\n obj: Object\n Object on which the property was defined (or modified).\n\n Examples\n --------\n > var obj = {};\n > defineProperty( obj, 'foo', {\n ... 'value': 'bar',\n ... 'enumerable': true,\n ... 'writable': false\n ... });\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n Returns a directory name.\n\n Parameters\n ----------\n path: string\n Path.\n\n Returns\n -------\n out: string\n Directory name.\n\n Examples\n --------\n > var dir = dirname( './foo/bar/index.js' )\n './foo/bar'\n\n See Also\n --------\n extname\n","dotcase":"\ndotcase( str )\n Converts a string to dot case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Dot-cased string.\n\n Examples\n --------\n > var out = dotcase( 'Hello World!' )\n 'hello.world'\n > out = dotcase( 'beep boop' )\n 'beep.boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n\n Returns\n -------\n list: Object\n Doubly linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the first list node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node. For its third argument, the\n method accepts a location: 'before' or 'after'. Default: 'after'.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation. For its sole argument, the method accepts a\n direction: 'forward' or 'reverse'. Default: 'forward'.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = DoublyLinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doUntil( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doUntilAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doUntilEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doUntilEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > doWhile( beep, predicate )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from one).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function continues invoking `fcn`;\n otherwise, the function invokes the `done` callback.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n The function to invoke.\n\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > doWhileAsync( fcn, predicate, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > doWhileEach( arr, logger, predicate )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n 4: NaN\n\n See Also\n --------\n doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n If provided an empty collection, both `value` and `index` are `undefined`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > doWhileEachRight( arr, logger, predicate )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n 1: NaN\n\n See Also\n --------\n doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n Interchanges two double-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float64' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > dswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.dswap, gswap, sswap\n","E":"\nE\n Euler's number.\n\n Examples\n --------\n > E\n 2.718281828459045\n\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n\n Returns\n -------\n out: Array\n Emoji database.\n\n Examples\n --------\n > var data = EMOJI()\n [ {...}, ... ]\n\n See Also\n --------\n EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n\n Returns\n -------\n out: Object\n An object mapping emoji codes to pictographs.\n\n Examples\n --------\n > var out = EMOJI_CODE_PICTO()\n\n See Also\n --------\n EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n\n Returns\n -------\n out: Object\n An object mapping emoji pictographs to codes.\n\n Examples\n --------\n > var out = EMOJI_PICTO_CODE()\n\n See Also\n --------\n EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n Returns an \"empty\" readable stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = emptyStream();\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n Returns a function for creating empty readable streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true };\n > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = emptyStream.objectMode();\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n constantStream","endsWith":"\nendsWith( str, search[, len] )\n Tests if a string ends with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n len: integer (optional)\n Substring length. Restricts the search to a substring within the input\n string beginning from the leftmost character. If provided a negative\n value, `len` indicates to ignore the last `len` characters, returning\n the same output as `str.length + len`. Default: `str.length`.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string ends with the characters of another\n string.\n\n Examples\n --------\n > var bool = endsWith( 'beep', 'ep' )\n true\n > bool = endsWith( 'Beep', 'op' )\n false\n > bool = endsWith( 'Beep', 'ee', 3 )\n true\n > bool = endsWith( 'Beep', 'ee', -1 )\n true\n > bool = endsWith( 'beep', '' )\n true\n\n See Also\n --------\n startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n Returns an array of an object's own enumerable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = enumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = enumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n Returns an array of an object's own enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = enumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n An object containing the user environment.\n\n Examples\n --------\n > var user = ENV.USER\n \n\n See Also\n --------\n ARGV\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n\n Examples\n --------\n > EPS\n 2.220446049250313e-16\n\n See Also\n --------\n FLOAT32_EPS\n","error2json":"\nerror2json( error )\n Returns a JSON representation of an error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n The JSON object is guaranteed to have the following properties:\n\n - type: error type.\n - message: error message.\n\n The only standardized cross-platform property is `message`. Depending on the\n platform, the following properties *may* be present:\n\n - name: error name.\n - stack: stack trace.\n - code: error code (Node.js system errors).\n - errno: error code string (Node.js system errors).\n - syscall: string representing the failed system call (Node.js system\n errors).\n\n The function also serializes all enumerable properties.\n\n The implementation supports custom error types and sets the `type` field to\n the closest built-in error type.\n\n Parameters\n ----------\n error: Error\n Error to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var err = new Error( 'beep' );\n > var json = error2json( err )\n \n\n See Also\n --------\n reviveError\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n\n Examples\n --------\n > EULERGAMMA\n 0.5772156649015329\n\n","every":"\nevery( collection )\n Tests whether all elements in a collection are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 1, 1, 1, 1, 1 ];\n > var bool = every( arr )\n true\n\n See Also\n --------\n any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyBy( arr, positive )\n true\n\n See Also\n --------\n anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > everyByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = everyByRight( arr, positive )\n true\n\n See Also\n --------\n anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-truthy `result`\n value and calls the `done` callback with `null` as the first argument and\n `false` as the second argument.\n\n If all elements succeed, the function calls the `done` callback with `null`\n as the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > everyByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, true );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = everyByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var o = {a: 1, b: 2, c: 3};\n > var bool = everyInBy( o, positive )\n true\n\n See Also\n --------\n anyInBy, noneInBy, someInBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a non-truthy return\n value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a truthy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > var bool = everyOwnBy( obj, positive )\n true\n\n See Also\n --------\n anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n Alias for `eval` global.\n\n A reference to `eval` is treated differently by the compiler. For example,\n when evaluating code containing block-scoped declarations (e.g., `let`,\n `const`, `function`, `class`), the compiler may throw an `error` complaining\n that block-scoped declarations are not yet supported outside of\n `strict mode`. One possible workaround is to include `\"use strict\";` in the\n evaluated code.\n\n Parameters\n ----------\n str: string\n Code to evaluate.\n\n Returns\n -------\n out: any\n Returned value if applicable.\n\n Examples\n --------\n > var v = evil( '5*4*3*2*1' )\n 120\n\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n\n Examples\n --------\n > EXEC_PATH\n \n\n","exists":"\nexists( path, clbk )\n Asynchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n clbk: Function\n Callback to invoke after testing for path existence. A callback may\n accept a single argument, a boolean indicating whether a path exists, or\n two arguments, an error argument and a boolean, matching the error-first\n callback convention used in most asynchronous Node.js APIs.\n\n Examples\n --------\n > function done( error, bool ) { console.log( bool ); };\n > exists( './beep/boop', done );\n\n\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir\n","exists.sync":"\nexists.sync( path )\n Synchronously tests whether a path exists on the filesystem.\n\n Parameters\n ----------\n path: string|Buffer\n Path to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether the path exists.\n\n Examples\n --------\n > var bool = exists.sync( './beep/boop' )\n \n\n See Also\n --------\n readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n Expands acronyms in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded acronyms.\n\n Examples\n --------\n > var str = 'LOL, this is fun. I am ROFL.';\n > var out = expandAcronyms( str )\n 'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n > str = 'brb, I need to check my mail. thx!';\n > out = expandAcronyms( str )\n 'be right back, I need to check my mail. thanks!'\n\n See Also\n --------\n expandContractions\n","expandContractions":"\nexpandContractions( str )\n Expands all contractions to their formal equivalents.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with expanded contractions.\n\n Examples\n --------\n > var str = 'I won\\'t be able to get y\\'all out of this one.';\n > var out = expandContractions( str )\n 'I will not be able to get you all out of this one.'\n\n > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n > out = expandContractions( str )\n 'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n Returns a filename extension.\n\n Parameters\n ----------\n filename: string\n Filename.\n\n Returns\n -------\n ext: string\n Filename extension.\n\n Examples\n --------\n > var ext = extname( 'index.js' )\n '.js'\n\n See Also\n --------\n dirname\n","falses":"\nfalses( shape[, options] )\n Returns an ndarray filled with `false` values and having a specified shape\n and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a boolean or \"generic\" data type. Default:\n 'bool'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = falses( [ 2, 2 ] )\n [ [ false, false ], [ false, false ] ]\n\n See Also\n --------\n array, ndarray, falsesLike, trues\n","falsesLike":"\nfalsesLike( x[, options] )\n Returns an ndarray filled with `false` values and having the same shape and\n data type as a provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a boolean or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var opts = { 'dtype': 'generic' };\n > var x = ndempty( [ 2, 2 ], opts )\n \n > var y = falsesLike( x )\n [ [ false, false ], [ false, false ] ]\n\n See Also\n --------\n array, ndarray, falses, truesLike\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns a FancyArray instance.\n\n A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n A FancyArray is an ndarray instance and supports all ndarray options,\n attributes, and methods. A FancyArray can be consumed by any API which\n supports ndarray instances.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: FancyArray\n FancyArray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: FancyArray\n FancyArray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n Computes an absolute value.\n\n This implementation is not IEEE 754 compliant. If provided `-0`, the\n function returns `-0`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Absolute value.\n\n Examples\n --------\n > var v = fastmath.abs( -1.0 )\n 1.0\n > v = fastmath.abs( 2.0 )\n 2.0\n > v = fastmath.abs( 0.0 )\n 0.0\n > v = fastmath.abs( -0.0 )\n -0.0\n > v = fastmath.abs( NaN )\n NaN\n\n See Also\n --------\n base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n Computes the hyperbolic arccosine of a number.\n\n The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n will return `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arccosine (in radians).\n\n Examples\n --------\n > var v = fastmath.acosh( 1.0 )\n 0.0\n > v = fastmath.acosh( 2.0 )\n ~1.317\n > v = fastmath.acosh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.acosh( 1.0e308 )\n Infinity\n\n See Also\n --------\n base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n The algorithm computes only an approximation.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.ampbm( 5.0, 12.0 )\n ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n\n Parameters\n ----------\n alpha: number\n Alpha.\n\n beta: number\n Beta.\n\n nonnegative: boolean (optional)\n Boolean indicating whether input values are always nonnegative.\n\n ints: boolean (optional)\n Boolean indicating whether input values are always 32-bit integers.\n\n Returns\n -------\n fcn: Function\n Function to compute a hypotenuse.\n\n Examples\n --------\n > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n \n\n See Also\n --------\n base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n Computes the hyperbolic arcsine of a number.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arcsine (in radians).\n\n Examples\n --------\n > var v = fastmath.asinh( 0.0 )\n 0.0\n > v = fastmath.asinh( 2.0 )\n ~1.444\n > v = fastmath.asinh( -2.0 )\n ~-1.444\n > v = fastmath.asinh( NaN )\n NaN\n\n // The function overflows for large `x`:\n > v = fastmath.asinh( 1.0e200 )\n Infinity\n\n // The function underflows for small `x`:\n > v = fastmath.asinh( 1.0e-50 )\n 0.0\n\n See Also\n --------\n base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n Computes the hyperbolic arctangent of a number.\n\n The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n returns `NaN`.\n\n Parameters\n ----------\n x: number\n Input value.\n\n Returns\n -------\n out: number\n Hyperbolic arctangent (in radians).\n\n Examples\n --------\n > var v = fastmath.atanh( 0.0 )\n 0.0\n > v = fastmath.atanh( 0.9 )\n ~1.472\n > v = fastmath.atanh( 1.0 )\n Infinity\n > v = fastmath.atanh( -1.0 )\n -Infinity\n > v = fastmath.atanh( NaN )\n NaN\n\n // The function underflows for small `x`:\n > v = fastmath.atanh( 1.0e-17 )\n 0.0\n\n See Also\n --------\n base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n Computes the hypotenuse.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Hypotenuse.\n\n Examples\n --------\n > var h = fastmath.hypot( -5.0, 12.0 )\n 13.0\n\n // For a sufficiently large `x` and/or `y`, the function overflows:\n > h = fastmath.hypot( 1.0e154, 1.0e154 )\n Infinity\n\n // For sufficiently small `x` and/or `y`, the function underflows:\n > h = fastmath.hypot( 1e-200, 1.0e-200 )\n 0.0\n\n See Also\n --------\n base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n\n This function provides a performance boost when requiring only approximate\n computations for integer arguments.\n\n For high-precision applications, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer binary logarithm (base two).\n\n Examples\n --------\n > var v = fastmath.log2Uint32( 4 >>> 0 )\n 2\n > v = fastmath.log2Uint32( 8 >>> 0 )\n 3\n > v = fastmath.log2Uint32( 9 >>> 0 )\n 3\n\n See Also\n --------\n base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n Returns the maximum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var v = fastmath.max( 3.14, 4.2 )\n 4.2\n > v = fastmath.max( 3.14, NaN )\n NaN\n > v = fastmath.max( NaN, 3.14 )\n 3.14\n > v = fastmath.max( -0.0, +0.0 )\n +0.0\n > v = fastmath.max( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.max\n","fastmath.min":"\nfastmath.min( x, y )\n Returns the minimum value.\n\n The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n Parameters\n ----------\n x: number\n First number.\n\n y: number\n Second number.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var v = fastmath.min( 3.14, 4.2 )\n 3.14\n > v = fastmath.min( 3.14, NaN )\n NaN\n > v = fastmath.min( NaN, 3.14 )\n 3.14\n > v = fastmath.min( -0.0, +0.0 )\n +0.0\n > v = fastmath.min( +0.0, -0.0 )\n -0.0\n\n See Also\n --------\n base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n\n This function is not recommended for high-precision applications due to\n error accumulation.\n\n If provided a negative exponent, the function first computes the reciprocal\n of the base and then evaluates the exponential function. This can introduce\n significant error.\n\n Parameters\n ----------\n x: number\n Base.\n\n y: integer\n Signed 32-bit integer exponent.\n\n Returns\n -------\n out: number\n Function value.\n\n Examples\n --------\n > var v = fastmath.powint( 2.0, 3 )\n 8.0\n > v = fastmath.powint( 3.14, 0 )\n 1.0\n > v = fastmath.powint( 2.0, -2 )\n 0.25\n > v = fastmath.powint( 0.0, 0 )\n 1.0\n > v = fastmath.powint( -3.14, 1 )\n -3.14\n > v = fastmath.powint( NaN, 0 )\n NaN\n\n See Also\n --------\n base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n Prefer hardware `sqrt` over a software implementation.\n\n When using a software `sqrt`, this function provides a performance boost\n when an application requires only approximate computations for integer\n arguments.\n\n For applications requiring high-precision, this function is never suitable.\n\n Parameters\n ----------\n x: uinteger\n Input value.\n\n Returns\n -------\n out: uinteger\n Integer square root.\n\n Examples\n --------\n > var v = fastmath.sqrtUint32( 9 >>> 0 )\n 3\n > v = fastmath.sqrtUint32( 2 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 3 >>> 0 )\n 1\n > v = fastmath.sqrtUint32( 0 >>> 0 )\n 0\n\n See Also\n --------\n base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common female first names.\n\n Examples\n --------\n > var list = FEMALE_FIRST_NAMES_EN()\n [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. \"Moby Word II.\" .\n\n See Also\n --------\n MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n\n Returns\n -------\n queue: Object\n First-in-first-out queue.\n\n queue.clear: Function\n Clears the queue.\n\n queue.first: Function\n Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.iterator: Function\n Returns an iterator for iterating over a queue. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from queue mutation during\n iteration, a returned iterator **always** iterates over a queue\n \"snapshot\", which is defined as the list of queue elements at the time\n of the method's invocation.\n\n queue.last: Function\n Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n If the queue is empty, the returned value is `undefined`.\n\n queue.length: integer\n Queue length.\n\n queue.pop: Function\n Removes and returns the current \"first-out\" value from the queue. If the\n queue is empty, the returned value is `undefined`.\n\n queue.push: Function\n Adds a value to the queue.\n\n queue.toArray: Function\n Returns an array of queue values.\n\n queue.toJSON: Function\n Serializes a queue as JSON.\n\n Examples\n --------\n > var q = FIFO();\n > q.push( 'foo' ).push( 'bar' );\n > q.length\n 2\n > q.pop()\n 'foo'\n > q.length\n 1\n > q.pop()\n 'bar'\n > q.length\n 0\n\n See Also\n --------\n Stack\n","filledarray":"\nfilledarray( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray()\n \n > arr = filledarray( 'float32' )\n \n\n\nfilledarray( value, length[, dtype] )\n Returns a filled array having a specified length.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarray( 1.0, 5 )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarray( 1, 5, 'int32' )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n Creates a filled array from another array (or array-like object).\n\n Parameters\n ----------\n value: any\n Fill value.\n\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n Creates a filled array from an iterable.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarray( 1.0, arr1, 'float32' )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n Returns a filled typed array view of an ArrayBuffer.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n value: any\n Fill value.\n\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n Creates a filled array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr = filledarrayBy()\n \n > arr = filledarrayBy( 'float32' )\n \n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\n Parameters\n ----------\n length: integer\n Array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > function clbk() { return 1.0; };\n > var arr = filledarrayBy( 5, clbk )\n [ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n > arr = filledarrayBy( 5, 'int32', clbk )\n [ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\n Parameters\n ----------\n array: ArrayLikeObject\n Array from which to generate another array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n [ 2.0, 2.0, 2.0 ]\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\n Parameters\n ----------\n iterable: Iterable\n Iterable from which to generate an array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray|Array\n Output array.\n\n Examples\n --------\n > var arr1 = iterConstant( 3.0, {'iter': 3} );\n > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n\n The 'generic' array data type is *not* supported.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n [ 1.0, 1.0, 1.0, 1.0 ]\n\n See Also\n --------\n filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a truthy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v !== 2 ); };\n > var bar = filterArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n Finds elements in an array-like object that satisfy a test condition.\n\n Parameters\n ----------\n arr: Array|TypedArray|string\n Object from which elements will be tested.\n\n options: Object (optional)\n Options.\n\n options.k: integer (optional)\n Limits the number of returned elements. The sign determines the\n direction in which to search. If set to a negative integer, the function\n searches from last element to first element. Default: arr.length.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'indices'.\n\n clbk: Function\n Function invoked for each array element. If the return value is truthy,\n the value is considered to have satisfied the test condition.\n\n Returns\n -------\n out: Array\n Array of indices, element values, or arrays of index-value pairs.\n\n Examples\n --------\n > var data = [ 30, 20, 50, 60, 10 ];\n > function condition( val ) { return val > 20; };\n > var vals = find( data, condition )\n [ 0, 2, 3 ]\n\n // Limit number of results:\n > data = [ 30, 20, 50, 60, 10 ];\n > var opts = { 'k': 2, 'returns': 'values' };\n > vals = find( data, opts, condition )\n [ 30, 50 ]\n\n // Return both indices and values as index-value pairs:\n > data = [ 30, 20, 50, 60, 10 ];\n > opts = { 'k': -2, 'returns': '*' };\n > vals = find( data, opts, condition )\n [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n Returns the first character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = firstChar( 'beep' )\n 'b'\n > out = firstChar( 'Boop', 1 )\n 'B'\n > out = firstChar( 'foo bar', 5 )\n 'foo b'\n\n See Also\n --------\n removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Returns\n -------\n out: Array\n FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n\n Examples\n --------\n > var data = FIVETHIRTYEIGHT_FFQ()\n [ {...}, ... ]\n\n References\n ----------\n - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n Nutrition.\" .\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n Flattens an array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n out: Array\n Flattened array.\n\n Examples\n --------\n > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > var out = flattenArray( arr )\n [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Set the maximum depth:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2 } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n true\n\n // Deep copy:\n > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n false\n\n\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n Returns a function for flattening arrays having specified dimensions.\n\n The returned function does not validate that input arrays actually have the\n specified dimensions.\n\n Parameters\n ----------\n dims: ArrayLike\n Dimensions.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy array elements. Default: false.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenArray.factory( [ 2, 2 ], {\n ... 'copy': false\n ... });\n > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n [ 1, 2, 3, 4 ]\n > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n [ 5, 6, 7, 8 ]\n\n See Also\n --------\n flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n Flattens an object.\n\n Parameters\n ----------\n obj: ObjectLike\n Object to flatten.\n\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n out: ObjectLike\n Flattened object.\n\n Examples\n --------\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flattenObject( obj )\n { 'a.b.c': 'd' }\n\n // Set the `depth` option to flatten to a specified depth:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'depth': 1 } )\n { 'a.b': { 'c': 'd' } }\n > var bool = ( obj.a.b === out[ 'a.b' ] )\n true\n\n // Set the `delimiter` option:\n > obj = { 'a': { 'b': { 'c': 'd' } } };\n > out = flattenObject( obj, { 'delimiter': '-|-' } )\n { 'a-|-b-|-c': 'd' }\n\n // Flatten arrays:\n > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n > out = flattenObject( obj, { 'flattenArrays': true } )\n { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n Returns a function to flatten an object.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.depth: integer (optional)\n Maximum depth to flatten.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy. Default: false.\n\n options.flattenArrays: boolean (optional)\n Boolean indicating whether to flatten arrays. Default: false.\n\n options.delimiter: string (optional)\n Key path delimiter. Default: '.'.\n\n Returns\n -------\n fcn: Function\n Flatten function.\n\n Examples\n --------\n > var flatten = flattenObject.factory({\n ... 'depth': 1,\n ... 'copy': true,\n ... 'delimiter': '|'\n ... });\n > var obj = { 'a': { 'b': { 'c': 'd' } } };\n > var out = flatten( obj )\n { 'a|b': { 'c': 'd' } }\n\n See Also\n --------\n flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n Computes the Fligner-Killeen test for equal variances.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = flignerTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = flignerTest( arr, { 'groups': groups } )\n\n See Also\n --------\n bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n\n Possible values:\n\n - 'little-endian'\n - 'big-endian'\n - 'unknown'\n\n Examples\n --------\n > FLOAT_WORD_ORDER\n \n\n See Also\n --------\n BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_CBRT_EPS\n 0.09921256574801247\n\n See Also\n --------\n FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_EPS\n 0.0009765625\n\n See Also\n --------\n FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT16_EXPONENT_BIAS\n 15\n\n See Also\n --------\n FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_MAX\n 65504.0\n\n See Also\n --------\n FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n\n The maximum safe half-precision floating-point integer is given by\n `2^11 - 1`.\n\n Examples\n --------\n > FLOAT16_MAX_SAFE_INTEGER\n 2047\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n\n The minimum safe half-precision floating-point integer is given by\n `-(2^11 - 1)`.\n\n Examples\n --------\n > FLOAT16_MIN_SAFE_INTEGER\n -2047\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT16_NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_NUM_BYTES\n 2\n\n See Also\n --------\n FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT16_PINF\n Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n\n The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT16_PRECISION\n 11\n\n See Also\n --------\n FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_NORMAL\n 6.103515625e-5\n\n See Also\n --------\n FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n\n Examples\n --------\n > FLOAT16_SMALLEST_SUBNORMAL\n 5.960464477539063e-8\n\n See Also\n --------\n FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT16_SQRT_EPS\n 0.03125\n\n See Also\n --------\n FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","Float16Array":"\nFloat16Array()\n A 16-bit half-precision floating-point number array.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float16Array()\n \n\n\nFloat16Array( length )\n Creates a half-precision floating-point number array having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var len = arr.length\n 5\n\n\nFloat16Array( typedarray )\n Creates a half-precision floating-point number array from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a half-precision floating-point\n number array.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var buf = new Float64Array( [ 0.5, 0.5, 0.5 ] )\n \n > var arr = new Float16Array( buf )\n \n > var len = arr.length\n 3\n\n\nFloat16Array( obj )\n Creates a half-precision floating-point number array from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a half-precision\n floating-point number array.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 0.5, 0.5, 0.5 ] )\n \n > var len = arr.length\n 3\n\n\nFloat16Array( buffer[, byteOffset[, length]] )\n Returns a half-precision floating-point number array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr1 = new Float16Array( buf )\n \n > var len = arr1.length\n 4\n > var arr2 = new Float16Array( buf, 2 )\n \n > len = arr2.length\n 3\n > var arr3 = new Float16Array( buf, 2, 2 )\n \n > len = arr3.length\n 2\n\n\nFloat16Array.from( src[, clbk[, thisArg]] )\n Creates a new half-precision floating-point number array from an array-like\n object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Float16Array.from( [ 1.0, -1.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n -2.0\n\n\nFloat16Array.of( element0[, element1[, ...elementN]] )\n Creates a new half-precision floating-point number array from a variable\n number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = Float16Array.of( 1.0, -1.0 )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n -1.0\n\n\nFloat16Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Float16Array.BYTES_PER_ELEMENT\n 2\n\n\nFloat16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Float16Array.name\n 'Float16Array'\n\n\nFloat16Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Float16Array( 2 )\n \n > var buf = arr.buffer\n \n\n\nFloat16Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var nbytes = arr.byteLength\n 10\n\n\nFloat16Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 20 );\n > arr = new Float16Array( buf, 10 )\n \n > offset = arr.byteOffset\n 10\n\n\nFloat16Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > arr.BYTES_PER_ELEMENT\n 2\n\n\nFloat16Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var len = arr.length\n 5\n\n\nFloat16Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: float|void\n An array element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 10.0, 20.0, 30.0 ] )\n \n > var v = arr.at( 0 )\n 10.0\n > v = arr.at( -1 )\n 30.0\n\n\nFloat16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > arr.copyWithin( 0, 3 )\n \n > var v = arr[ 0 ]\n 4.0\n > v = arr[ 1 ]\n 5.0\n\n\nFloat16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, 1.0 ]\n > v = it.next().value\n [ 1, 2.0 ]\n > v = it.next().value\n [ 2, 3.0 ]\n > var bool = it.next().done\n true\n\n\nFloat16Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 0.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var bool = arr.every( predicate )\n true\n\n\nFloat16Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( 3 )\n \n > arr.fill( 2.0 );\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 2.0\n\n\nFloat16Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0\n\n\nFloat16Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.find( predicate )\n 2.0\n\n\nFloat16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat16Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.findLast( predicate )\n 3.0\n\n\nFloat16Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2\n\n\nFloat16Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1%2%3%'\n\n\nFloat16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.includes( 3.0 )\n true\n > bool = arr.includes( 3.0, 3 )\n false\n\n\nFloat16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.indexOf( 2.0 )\n 1\n > idx = arr.indexOf( 2.0, 2 )\n -1\n\n\nFloat16Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.join()\n '1,2,3'\n > str = arr.join( '|' )\n '1|2|3'\n\n\nFloat16Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true\n\n\nFloat16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 1.0 ] )\n \n > var idx = arr.lastIndexOf( 1.0 )\n 3\n > idx = arr.lastIndexOf( 1.0, 2 )\n 0\n\n\nFloat16Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v * 2.0; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.map( clbk )\n \n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 4.0\n > v = out[ 2 ]\n 6.0\n\n\nFloat16Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduce( reducerFn, 0.0 )\n 6.0\n\n\nFloat16Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduceRight( reducerFn, 0.0 )\n 6.0\n\n\nFloat16Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.reverse();\n > var v = arr[ 0 ]\n 3.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 1.0\n\n\nFloat16Array.prototype.set( arr[, offset] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an offset argument.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.set( [ 4.0, 5.0 ], 1 );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 4.0\n > v = arr[ 2 ]\n 5.0\n\n\nFloat16Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0\n\n\nFloat16Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.some( predicate )\n true\n\n\nFloat16Array.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > arr.sort( compare );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 3.0\n\n\nFloat16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0\n\n\nFloat16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toLocaleString()\n '1,2,3'\n\n\nFloat16Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var v = out[ 0 ]\n 3.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 1.0\n\n\nFloat16Array.prototype.toSorted( [compareFcn] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var v = out[ 0 ]\n 1.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 3.0\n\n\nFloat16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toString()\n '1,2,3'\n\n\nFloat16Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n\nFloat16Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: number\n Element value.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.with( 1, 4.0 )\n \n > var v = out[ 1 ]\n 4.0\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float16Array.from":"\nFloat16Array.from( src[, clbk[, thisArg]] )\n Creates a new half-precision floating-point number array from an array-like\n object or an iterable.\n\n A callback function is provided two arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n clbk: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > function clbkFcn( v ) { return v * 2.0 };\n > var arr = Float16Array.from( [ 1.0, -1.0 ], clbkFcn )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n -2.0","Float16Array.of":"\nFloat16Array.of( element0[, element1[, ...elementN]] )\n Creates a new half-precision floating-point number array from a variable\n number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float16Array\n A typed array.\n\n Examples\n --------\n > var arr = Float16Array.of( 1.0, -1.0 )\n \n > var len = arr.length\n 2\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n -1.0","Float16Array.BYTES_PER_ELEMENT":"\nFloat16Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n\n Examples\n --------\n > var nbytes = Float16Array.BYTES_PER_ELEMENT\n 2","Float16Array.name":"\nFloat16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > var str = Float16Array.name\n 'Float16Array'","Float16Array.prototype.buffer":"\nFloat16Array.prototype.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var arr = new Float16Array( 2 )\n \n > var buf = arr.buffer\n ","Float16Array.prototype.byteLength":"\nFloat16Array.prototype.byteLength\n Length of the array in bytes.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var nbytes = arr.byteLength\n 10","Float16Array.prototype.byteOffset":"\nFloat16Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var offset = arr.byteOffset\n 0\n > var buf = new ArrayBuffer( 20 );\n > arr = new Float16Array( buf, 10 )\n \n > offset = arr.byteOffset\n 10","Float16Array.prototype.BYTES_PER_ELEMENT":"\nFloat16Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > arr.BYTES_PER_ELEMENT\n 2","Float16Array.prototype.length":"\nFloat16Array.prototype.length\n The number of array elements.\n\n Examples\n --------\n > var arr = new Float16Array( 5 )\n \n > var len = arr.length\n 5","Float16Array.prototype.at":"\nFloat16Array.prototype.at( i )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n\n If provided an index outside the array index range, the method returns\n `undefined`.\n\n Parameters\n ----------\n i: integer\n Element index.\n\n Returns\n -------\n out: float|void\n An array element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 10.0, 20.0, 30.0 ] )\n \n > var v = arr.at( 0 )\n 10.0\n > v = arr.at( -1 )\n 30.0","Float16Array.prototype.copyWithin":"\nFloat16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > arr.copyWithin( 0, 3 )\n \n > var v = arr[ 0 ]\n 4.0\n > v = arr[ 1 ]\n 5.0","Float16Array.prototype.entries":"\nFloat16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var it = arr.entries();\n > var v = it.next().value\n [ 0, 1.0 ]\n > v = it.next().value\n [ 1, 2.0 ]\n > v = it.next().value\n [ 2, 3.0 ]\n > var bool = it.next().done\n true","Float16Array.prototype.every":"\nFloat16Array.prototype.every( predicate[, thisArg] )\n Returns a boolean indicating whether all elements in the array pass a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all elements pass the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 0.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var bool = arr.every( predicate )\n true","Float16Array.prototype.fill":"\nFloat16Array.prototype.fill( value[, start[, end]] )\n Returns a modified typed array filled with a fill value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( 3 )\n \n > arr.fill( 2.0 );\n > var v = arr[ 0 ]\n 2.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 2.0","Float16Array.prototype.filter":"\nFloat16Array.prototype.filter( predicate[, thisArg] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.filter( predicate )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0","Float16Array.prototype.find":"\nFloat16Array.prototype.find( predicate[, thisArg] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.find( predicate )\n 2.0","Float16Array.prototype.findIndex":"\nFloat16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findIndex( predicate )\n 2","Float16Array.prototype.findLast":"\nFloat16Array.prototype.findLast( predicate[, thisArg] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: number|void\n Array element or `undefined`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var v = arr.findLast( predicate )\n 3.0","Float16Array.prototype.findLastIndex":"\nFloat16Array.prototype.findLastIndex( predicate[, thisArg] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 1.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.findLastIndex( predicate )\n 2","Float16Array.prototype.forEach":"\nFloat16Array.prototype.forEach( clbk[, thisArg] )\n Invokes a function once for each array element.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n clbk: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Execution context.\n\n Examples\n --------\n > var str = '%';\n > function clbk( v ) { str += v.toString() + '%'; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.forEach( clbk );\n > str\n '%1%2%3%'","Float16Array.prototype.includes":"\nFloat16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a provided value.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.includes( 3.0 )\n true\n > bool = arr.includes( 3.0, 3 )\n false","Float16Array.prototype.indexOf":"\nFloat16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var idx = arr.indexOf( 2.0 )\n 1\n > idx = arr.indexOf( 2.0, 2 )\n -1","Float16Array.prototype.join":"\nFloat16Array.prototype.join( [separator] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n\n Parameters\n ----------\n separator: string (optional)\n Separator string. Default: ','.\n\n Returns\n -------\n out: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.join()\n '1,2,3'\n > str = arr.join( '|' )\n '1|2|3'","Float16Array.prototype.keys":"\nFloat16Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array index keys.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.keys();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().done\n true","Float16Array.prototype.lastIndexOf":"\nFloat16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the last index at which a given element can be found.\n\n If method does not find a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index at which to start the search. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: out.length-1.\n\n Returns\n -------\n out: integer\n Array index or `-1`.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 1.0 ] )\n \n > var idx = arr.lastIndexOf( 1.0 )\n 3\n > idx = arr.lastIndexOf( 1.0, 2 )\n 0","Float16Array.prototype.map":"\nFloat16Array.prototype.map( clbk[, thisArg] )\n Returns a new array with each element being the result of a provided\n callback function.\n\n A callback function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n clbk: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n out: Float16Array\n A new typed array.\n\n Examples\n --------\n > function clbk( v ) { return v * 2.0; };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.map( clbk )\n \n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 4.0\n > v = out[ 2 ]\n 6.0","Float16Array.prototype.reduce":"\nFloat16Array.prototype.reduce( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduce( reducerFn, 0.0 )\n 6.0","Float16Array.prototype.reduceRight":"\nFloat16Array.prototype.reduceRight( reducerFn[, initialValue] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n\n A reducer function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n reducerFn: Function\n Function to apply to each array element.\n\n initialValue: any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > function reducerFn( acc, v ) { return acc + v; };\n > var v = arr.reduceRight( reducerFn, 0.0 )\n 6.0","Float16Array.prototype.reverse":"\nFloat16Array.prototype.reverse()\n Reverses the array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.reverse();\n > var v = arr[ 0 ]\n 3.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 1.0","Float16Array.prototype.set":"\nFloat16Array.prototype.set( arr[, offset] )\n Sets one or more array elements.\n\n If provided a single argument, the method sets array elements starting at\n position (index) `i = 0`. To set elements starting elsewhere in the array,\n provide an offset argument.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > arr.set( [ 4.0, 5.0 ], 1 );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 4.0\n > v = arr[ 2 ]\n 5.0","Float16Array.prototype.slice":"\nFloat16Array.prototype.slice( [start[, end]] )\n Copies a portion of a typed array to a new typed array.\n\n Parameters\n ----------\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.slice( 1 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0","Float16Array.prototype.some":"\nFloat16Array.prototype.some( predicate[, thisArg] )\n Returns a boolean indicating whether at least one element passes a test.\n\n A predicate function is provided the following arguments:\n\n - value: current array element.\n - index: current array element index.\n - arr: the array on which the method was called.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one element passes the test.\n\n Examples\n --------\n > function predicate( v ) { return ( v > 2.0 ); };\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var bool = arr.some( predicate )\n true","Float16Array.prototype.sort":"\nFloat16Array.prototype.sort( [compareFunction] )\n Sorts an array in-place.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n Modified array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > arr.sort( compare );\n > var v = arr[ 0 ]\n 1.0\n > v = arr[ 1 ]\n 2.0\n > v = arr[ 2 ]\n 3.0","Float16Array.prototype.subarray":"\nFloat16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float16Array\n New typed array view.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] )\n \n > var out = arr.subarray( 1, 3 )\n \n > var len = out.length\n 2\n > var v = out[ 0 ]\n 2.0\n > v = out[ 1 ]\n 3.0","Float16Array.prototype.toLocaleString":"\nFloat16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n Locale identifier(s).\n\n options: Object (optional)\n An object containing serialization options.\n\n Returns\n -------\n str: string\n Local-specific string.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toLocaleString()\n '1,2,3'","Float16Array.prototype.toReversed":"\nFloat16Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.toReversed()\n \n > var v = out[ 0 ]\n 3.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 1.0","Float16Array.prototype.toSorted":"\nFloat16Array.prototype.toSorted( [compareFcn] )\n Returns a new typed array containing the elements in sorted order.\n\n A comparison function determines the order of the array elements. The\n function is provided two arguments:\n\n - a: first element for comparison.\n - b: second element for comparison.\n\n The function should return a value less than zero if `a` comes before `b`,\n a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n are equivalent.\n\n Parameters\n ----------\n compareFcn: Function (optional)\n Comparison function.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > function compare( a, b ) { return a - b; };\n > var arr = new Float16Array( [ 2.0, 3.0, 1.0 ] )\n \n > var out = arr.toSorted( compare );\n > var v = out[ 0 ]\n 1.0\n > v = out[ 1 ]\n 2.0\n > v = out[ 2 ]\n 3.0","Float16Array.prototype.toString":"\nFloat16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n String serialization of the array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var str = arr.toString()\n '1,2,3'","Float16Array.prototype.values":"\nFloat16Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n\n Returns\n -------\n iterator: Iterator\n Iterator for iterating over array values.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0 ] )\n \n > var it = arr.values();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true","Float16Array.prototype.with":"\nFloat16Array.prototype.with( index, value )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n\n Parameters\n ----------\n index: integer\n Element index.\n\n value: number\n Element value.\n\n Returns\n -------\n out: Float16Array\n New typed array.\n\n Examples\n --------\n > var arr = new Float16Array( [ 1.0, 2.0, 3.0 ] )\n \n > var out = arr.with( 1, 4.0 )\n \n > var v = out[ 1 ]\n 4.0\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_CBRT_EPS\n 0.004921566694974899\n\n See Also\n --------\n FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n\n Examples\n --------\n > FLOAT32_E\n 2.7182817459106445\n\n See Also\n --------\n E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EPS\n 1.1920928955078125e-7\n\n See Also\n --------\n EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT32_EXPONENT_BIAS\n 127\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_EXPONENT_MASK\n 2139095040\n > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n '01111111100000000000000000000000'\n\n See Also\n --------\n FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_FOURTH_PI\n 7.853981852531433e-1\n\n See Also\n --------\n FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_HALF_LN_TWO\n 0.3465735912322998\n\n See Also\n --------\n HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_HALF_PI\n 1.5707963705062866\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_HALF\n -0.6931471824645996\n\n See Also\n --------\n LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_PI\n 1.1447298526763916\n\n See Also\n --------\n FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TEN\n 2.3025851249694824\n\n See Also\n --------\n FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_LN_TWO\n 0.6931471824645996\n\n See Also\n --------\n FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX\n 3.4028234663852886e+38\n\n See Also\n --------\n FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT\n 127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n -127\n\n See Also\n --------\n FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT\n 38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n -38\n\n See Also\n --------\n FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_FIBONACCI\n 14930352\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n\n The maximum safe single-precision floating-point integer is given by\n `2^24 - 1`.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_INTEGER\n 16777215\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n 10\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n 36\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT32_MAX_SAFE_NTH_LUCAS\n 34\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT\n -126\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n -149\n\n See Also\n --------\n FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT\n -37\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n -45\n\n See Also\n --------\n FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n\n The minimum safe single-precision floating-point integer is given by\n `-(2^24 - 1)`.\n\n Examples\n --------\n > FLOAT32_MIN_SAFE_INTEGER\n -16777215\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n\n Examples\n --------\n > FLOAT32_NAN\n NaN\n\n See Also\n --------\n NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n\n Examples\n --------\n > FLOAT32_NINF\n -Infinity\n\n See Also\n --------\n FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_NUM_BYTES\n 4\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n\n Examples\n --------\n > FLOAT32_PHI\n 1.6180340051651\n\n See Also\n --------\n PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n\n Examples\n --------\n > FLOAT32_PI\n 3.1415927410125732\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n\n Examples\n --------\n > FLOAT32_PINF\n Infinity\n\n See Also\n --------\n FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n\n The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT32_PRECISION\n 24\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SIGNIFICAND_MASK\n 8388607\n > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n '00000000011111111111111111111111'\n\n See Also\n --------\n FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_NORMAL\n 1.1754943508222875e-38\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SMALLEST_SUBNORMAL\n 1.401298464324817e-45\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n\n Examples\n --------\n > FLOAT32_SQRT_EPS\n 0.0003452669770922512\n\n See Also\n --------\n FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF\n 0.7071067690849304\n\n See Also\n --------\n SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_HALF_PI\n 1.2533141374588013\n\n See Also\n --------\n SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PHI\n 1.272019624710083\n\n See Also\n --------\n SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_PI\n 1.7724539041519165\n\n See Also\n --------\n FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_THREE\n 1.7320507764816284\n\n See Also\n --------\n FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO\n 1.4142135381698608\n\n See Also\n --------\n FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT32_SQRT_TWO_PI\n 2.5066282749176025\n\n See Also\n --------\n FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > FLOAT32_TWO_PI\n 6.2831854820251465\n\n See Also\n --------\n FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array()\n \n\n\nFloat32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float32Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Float32Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'\n\n\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n \n\n\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20\n\n\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr = Float32Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float32Array.BYTES_PER_ELEMENT\n 4","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float32Array.name\n 'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.buffer\n ","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteLength\n 20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.byteOffset\n 0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float32Array( 5 );\n > arr.length\n 5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float32Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Float32Matrix":"\nFloat32Matrix( [options] )\n Returns a two-dimensional single-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Matrix()\n \n\n\nFloat32Matrix( shape[, options] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Matrix( [ 2, 2 ] )\n \n\n\nFloat32Matrix( M, N[, options] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Matrix( 2, 2 )\n \n\n\nFloat32Matrix( obj[, options] )\n Creates a two-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\n > var arr = Float32Matrix( v )\n \n\n\nFloat32Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float32Matrix( buf, 0, [ 8, 1 ] )\n \n\n\nFloat32Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float32Matrix( buf, 0, 4, 1 )\n \n\n See Also\n --------\n Float64Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, matrix, Float32Vector, ndarray\n","Float32Vector":"\nFloat32Vector( [options] )\n Returns a one-dimensional single-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Vector()\n \n\n\nFloat32Vector( length[, options] )\n Returns a one-dimensional single-precision floating-point ndarray having a\n specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nFloat32Vector( obj[, options] )\n Creates a one-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0 ];\n > var arr = Float32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nFloat32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, Float32Matrix, ndarray\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n\n Examples\n --------\n > FLOAT64_EXPONENT_BIAS\n 1023\n\n See Also\n --------\n FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_ABS_MASK\n 2147483647\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n '01111111111111111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_EXPONENT_MASK\n 2146435072\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n '01111111111100000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGN_MASK\n 2147483648\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n '10000000000000000000000000000000'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n 1048575\n > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n '00000000000011111111111111111111'\n\n See Also\n --------\n FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX\n 1.7976931348623157e+308\n\n See Also\n --------\n FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT\n 1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n -1023\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT\n 308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_MAX_LN\n 709.782712893384\n\n See Also\n --------\n FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_FIBONACCI\n 8944394323791464\n\n See Also\n --------\n FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n\n The maximum safe double-precision floating-point integer is given by\n `2^53 - 1`.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_INTEGER\n 9007199254740991\n\n See Also\n --------\n FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_LUCAS\n 7639424778862807\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n 78\n\n See Also\n --------\n FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n\n Examples\n --------\n > FLOAT64_MAX_SAFE_NTH_LUCAS\n 76\n\n See Also\n --------\n FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT\n -1022\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n -1074\n\n See Also\n --------\n FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT\n -308\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n\n Examples\n --------\n > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n -324\n\n See Also\n --------\n FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n\n Examples\n --------\n > FLOAT64_MIN_LN\n -708.3964185322641\n\n See Also\n --------\n FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n\n The minimum safe double-precision floating-point integer is given by\n `-(2^53 - 1)`.\n\n Examples\n --------\n > FLOAT64_MIN_SAFE_INTEGER\n -9007199254740991\n\n See Also\n --------\n FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_NUM_BYTES\n 8\n\n See Also\n --------\n FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n\n The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n Examples\n --------\n > FLOAT64_PRECISION\n 53\n\n See Also\n --------\n FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_NORMAL\n 2.2250738585072014e-308\n\n See Also\n --------\n FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n\n Examples\n --------\n > FLOAT64_SMALLEST_SUBNORMAL\n 4.940656458412465e-324\n\n See Also\n --------\n FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array()\n \n\n\nFloat64Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = new Float64Array( arr1 )\n [ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = new Float64Array( buf, 0, 4 )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'\n\n\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n \n\n\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40\n\n\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8\n\n\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0\n\n\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2\n\n\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0\n\n\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'\n\n\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2.0; };\n > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n [ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr = Float64Array.of( 2.0, -2.0 )\n [ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Float64Array.BYTES_PER_ELEMENT\n 8","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Float64Array.name\n 'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.buffer\n ","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteLength\n 40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.byteOffset\n 0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Float64Array( 5 );\n > arr.length\n 5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 2.0\n > arr[ 4 ]\n -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1.0 ]\n > it.next().value\n [ 1, -1.0 ]\n > it.next().done\n true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > arr.every( predicate )\n false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > arr.fill( 2.0 );\n > arr[ 0 ]\n 2.0\n > arr[ 1 ]\n 2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = arr.find( predicate )\n -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = arr.findIndex( predicate )\n 2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var bool = arr.includes( 2.0 )\n false\n > bool = arr.includes( -1.0 )\n true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var idx = arr.indexOf( 2.0 )\n -1\n > idx = arr.indexOf( -1.0 )\n 2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.join( '|' )\n '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = arr.lastIndexOf( 2.0 )\n -1\n > idx = arr.lastIndexOf( 0.0 )\n 3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var arr2 = arr1.map( fcn )\n [ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0.0 )\n 2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0.0 )\n 2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n \n > arr.reverse()\n [ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > arr.set( [ -2.0, 2.0 ], 1 );\n > arr[ 1 ]\n -2.0\n > arr[ 2 ]\n 2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 0.0\n > arr2[ 1 ]\n -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > arr.some( predicate )\n true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Float64Array\n Modified array.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > arr.sort()\n [ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Float64Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toLocaleString()\n '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n > arr.toString()\n '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Float64Array( [ 1.0, -1.0 ] );\n > it = arr.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float16Array, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Float64Matrix":"\nFloat64Matrix( [options] )\n Returns a two-dimensional double-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Matrix()\n \n\n\nFloat64Matrix( shape[, options] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Matrix( [ 2, 2 ] )\n \n\n\nFloat64Matrix( M, N[, options] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Matrix( 2, 2 )\n \n\n\nFloat64Matrix( obj[, options] )\n Creates a two-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\n > var arr = Float64Matrix( v )\n \n\n\nFloat64Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float64Matrix( buf, 0, [ 4, 1 ] )\n \n\n\nFloat64Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float64Matrix( buf, 0, 4, 1 )\n \n\n See Also\n --------\n Float32Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, matrix, Float64Vector, ndarray\n","Float64Vector":"\nFloat64Vector( [options] )\n Returns a one-dimensional double-precision floating-point ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Vector()\n \n\n\nFloat64Vector( length[, options] )\n Returns a one-dimensional double-precision floating-point ndarray having a\n specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Float64Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nFloat64Vector( obj[, options] )\n Creates a one-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1.0, 2.0, 3.0 ];\n > var arr = Float64Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nFloat64Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Float64Vector( buf, 0, 2 )\n \n > var len = numel( arr )\n 2\n\n See Also\n --------\n Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, Float64Matrix, ndarray\n","forEach":"\nforEach( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEach( arr, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > forEachAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n Invokes a function for each character in a string.\n\n When invoked, the provided function is provided three arguments:\n\n - value: character.\n - index: starting character index.\n - str: input string.\n\n Parameters\n ----------\n str: string\n Input string over which to iterate.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters over which to iterate. The following modes are\n supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n clbk: Function\n The function to invoke for each character in the input string.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: string\n Input string.\n\n Examples\n --------\n > var n = 0;\n > function fcn() { n += 1; };\n > forEachChar( 'hello world!', fcn );\n > n\n 12\n\n See Also\n --------\n forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4 ];\n > forEachRight( arr, logger )\n 3: 4\n 2: 3\n 1: 2\n 0: 1\n\n See Also\n --------\n forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, onDuration, done )\n 1000\n 2500\n 3000\n Done.\n\n // Limit number of concurrent invocations:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 2500\n 3000\n 1000\n Done.\n\n // Process sequentially:\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > forEachRightAsync( arr, opts, onDuration, done )\n 3000\n 2500\n 1000\n Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function onDuration( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next();\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = forEachRightAsync.factory( opts, onDuration );\n > function done( error ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Done.' );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n Done.\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n Done.\n\n See Also\n --------\n forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > function Foo() { return this; };\n > Foo.prototype.beep = 'boop';\n > var obj = new Foo();\n > forIn( obj, logger )\n beep: boop\n\n See Also\n --------\n forEach, forOwn\n","format":"\nformat( str, ...args )\n Insert supplied variable values into a format string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n args: ...any\n Variable values.\n\n Returns\n -------\n out: string\n Formatted string.\n\n Examples\n --------\n > var out = format( 'Hello, %s!', 'World' )\n 'Hello, World!'\n\n > out = format( '%s %s', 'Hello', 'World' )\n 'Hello World'\n\n > out = format( 'Pi: %.2f', PI )\n 'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n Invokes a function for each own enumerable property of an object.\n\n When invoked, the function is provided three arguments:\n\n - value: object property value.\n - key: object property.\n - obj: the input object.\n\n To terminate iteration before visiting all properties, the provided function\n must explicitly return `false`.\n\n The function determines the list of own enumerable properties *before*\n invoking the provided function. Hence, any modifications made to the input\n object *after* calling this function (such as adding and removing\n properties) will *not* affect the list of visited properties.\n\n Property iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Input object, including arrays, typed arrays, and other collections.\n\n fcn: Function\n The function to invoke for each own enumerable property.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Input object.\n\n Examples\n --------\n > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n > forOwn( obj, logger )\n a: 1\n b: 2\n c: 3\n d: 4\n\n See Also\n --------\n forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n\n Examples\n --------\n > FOURTH_PI\n 7.85398163397448309616e-1\n\n See Also\n --------\n PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n\n Examples\n --------\n > FOURTH_ROOT_EPS\n 0.0001220703125\n\n See Also\n --------\n EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n\n Each array element has the following fields:\n\n - date: collection date (month/day/year; e.g., 01/01/1980).\n - all_workers: wage rates for hourly and non-hourly workers.\n - hourly_workers: wage rates for hourly workers.\n - non_hourly_workers: wage rates for non-hourly workers.\n - less_than_high_school: wage rates for workers with less than a high school\n education.\n - high_school: wage rates for workers with a high school education.\n - some_college: wage rates for workers with some college education.\n - college: wage rates for workers with a college education.\n - construction: wage rates for workers in the construction industry.\n - finance: wage rates for workers in the finance industry.\n - manufacturing: wage rates for workers in the manufacturing industry.\n\n Returns\n -------\n out: Array\n Wage rates.\n\n Examples\n --------\n > var data = FRB_SF_WAGE_RIGIDITY()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" .\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n Creates a string from a sequence of Unicode code points.\n\n In addition to multiple arguments, the function also supports providing an\n array-like object as a single argument containing a sequence of Unicode code\n points.\n\n Parameters\n ----------\n pt: ...integer\n Sequence of Unicode code points.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = fromCodePoint( 9731 )\n '☃'\n > out = fromCodePoint( [ 9731 ] )\n '☃'\n > out = fromCodePoint( 97, 98, 99 )\n 'abc'\n > out = fromCodePoint( [ 97, 98, 99 ] )\n 'abc'\n\n See Also\n --------\n codePointAt\n","Function":"\nFunction( [...argNames,] body )\n Returns a Function object.\n\n Argument names must be strings corresponding to valid JavaScript parameters\n (i.e., a plain identifier, or, in environments supporting such parameters, a\n rest parameter or destructured parameter, optionally with a default).\n\n Parameters\n ----------\n argNames: ...any (optional)\n Parameter names.\n\n body: string\n Function body.\n\n Returns\n -------\n fcn: Function\n Function object.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f( 1, 2 )\n 3\n\n\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3\n\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3\n\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3\n\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2\n\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'\n\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: Array\n Array of arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.apply( null, [ 1, 2 ] )\n 3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n Calls a function with a given `this` value and arguments provided\n individually.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n out: any\n Function return value.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.call( null, 1, 2 )\n 3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n\n Parameters\n ----------\n thisArg: any\n Value to use as `this` when executing the function.\n\n args: ...any\n Arguments to pass to the function.\n\n Returns\n -------\n fcn: Function\n Bound function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > var g = f.bind( null, 1 );\n > g( 2 )\n 3","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.toString()\n 'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.length\n 2","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name\n 'anonymous'\n\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.name = 'add';\n > f.name\n 'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n\n Examples\n --------\n > var f = new Function( 'x', 'y', 'return x + y' );\n > f.prototype\n {}","function2string":"\nfunction2string( fcn )\n Returns a string representing the source code of a provided function.\n\n If called on built-in functions, functions created by `Function#bind()`, or\n other non-JavaScript functions, the function returns a \"native\" function\n string similar to the following:\n\n \"function foo() { [native code] }\"\n\n For intrinsic object methods and functions, `foo` is the initial name of the\n function.\n\n If called on a function created by the `Function` constructor, the function\n returns the source code of a synthesized function declaration having the\n name \"anonymous\" and using the provided parameters and function body.\n\n Starting in ES2018, the ECMAScript specification requires that the returned\n string contain the exact same source code as it was declared, including any\n whitespace and/or comments. If the host is unable to access the source code,\n the specification requires that the returned string be the native function\n string.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n String representing the function's source code.\n\n Examples\n --------\n > function2string( base.erf )\n \n\n See Also\n --------\n Function\n","functionName":"\nfunctionName( fcn )\n Returns the name of a function.\n\n If provided an anonymous function, the function returns an empty `string` or\n the string `\"anonymous\"`.\n\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n Returns\n -------\n out: string\n Function name.\n\n Examples\n --------\n > var v = functionName( String )\n 'String'\n > v = functionName( function foo(){} )\n 'foo'\n > v = functionName( function(){} )\n '' || 'anonymous'\n\n See Also\n --------\n constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as an argument to the next function. The result of the\n rightmost function is the result of the whole.\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as unary functions.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x ) { return 2 * x; };\n > function b( x ) { return x + 3; };\n > function c( x ) { return x / 5; };\n > var f = functionSequence( a, b, c );\n > var z = f( 6 )\n 3\n\n See Also\n --------\n compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n Returns a pipeline function.\n\n Starting from the left, the pipeline function evaluates each function and\n passes the result as the first argument of the next function. The result of\n the rightmost function is the result of the whole.\n\n The last argument for each provided function is a `next` callback which\n should be invoked upon function completion. The callback accepts two\n arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the pipeline function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Only the leftmost function is explicitly permitted to accept multiple\n arguments. All other functions are evaluated as binary functions.\n\n The function will throw if provided fewer than two input arguments.\n\n Parameters\n ----------\n fcn: ...Function\n Functions to evaluate in sequential order.\n\n Returns\n -------\n out: Function\n Pipeline function.\n\n Examples\n --------\n > function a( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, 2*x );\n ... }\n ... };\n > function b( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x+3 );\n ... }\n ... };\n > function c( x, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, x/5 );\n ... }\n ... };\n > var f = functionSequenceAsync( a, b, c );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > f( 6, done )\n 3\n\n See Also\n --------\n composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n Examples\n --------\n > GAMMA_LANCZOS_G\n 10.900511\n\n","gdot":"\ngdot( x, y )\n Computes the dot product of two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n If provided empty vectors, the function returns `0.0`.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n dot: number\n The dot product.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gdot( x, y )\n -5.0\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gdot( x, y )\n -5.0\n\n See Also\n --------\n base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n\n The function only returns an effective group identity on POSIX platforms.\n For all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric group identity.\n\n Examples\n --------\n > var gid = getegid()\n\n See Also\n --------\n geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n\n The function only returns an effective user identity on POSIX platforms. For\n all other platforms (e.g., Windows and Android), the function returns\n `null`.\n\n Returns\n -------\n id: integer|null\n Effective numeric user identity.\n\n Examples\n --------\n > var uid = geteuid()\n\n See Also\n --------\n getegid, getgid, getuid\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n\n The function only returns a group identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric group identity.\n\n Examples\n --------\n > var gid = getgid()\n\n See Also\n --------\n getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n Returns the global object.\n\n Parameters\n ----------\n codegen: boolean (optional)\n Boolean indicating whether to use code generation to resolve the global\n object. Code generation is the *most* reliable means for resolving the\n global object; however, using code generation may violate content\n security policies (CSPs). Default: false.\n\n Returns\n -------\n global: Object\n Global object.\n\n Examples\n --------\n > var g = getGlobal()\n {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n Returns the prototype of a provided object.\n\n In contrast to the native `Object.getPrototypeOf`, this function does not\n throw when provided `null` or `undefined`. Instead, similar to when provided\n any value with *no* inherited properties, the function returns `null`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object|null\n Prototype.\n\n Examples\n --------\n > var proto = getPrototypeOf( {} )\n {}\n\n See Also\n --------\n isPrototypeOf\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n\n The function only returns a user identity on POSIX platforms. For all other\n platforms (e.g., Windows and Android), the function returns `null`.\n\n Returns\n -------\n id: integer|null\n Numeric user identity.\n\n Examples\n --------\n > var uid = getuid()\n\n See Also\n --------\n getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n\n Examples\n --------\n > GLAISHER\n 1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iterator( '🌷🍕' );\n > var v = it.next().value\n '🌷'\n > v = it.next().value\n '🍕'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n\n When invoked, an input function is provided three arguments:\n\n - value: grapheme cluster.\n - index: iterated value index.\n - src: source string.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke a string's `@@iterator` method, regardless of whether this method is\n defined. To convert a string to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: string\n String from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n > var v = it.next().value\n '🍕'\n > v = it.next().value\n '🌷'\n > var bool = it.next().done\n true\n\n See Also\n --------\n array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n Groups values as arrays associated with distinct keys.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n groups: Array|TypedArray|Object\n A collection defining which group an element in the input collection\n belongs to. Each value in `groups` should resolve to a value which can\n be serialized as an object key. If provided an object, the object must\n be array-like (excluding strings and functions).\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var groups = [ 'b', 'b', 'f', 'b' ];\n > var out = group( collection, groups )\n { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n > groups = [ 1, 1, 2, 1 ];\n > out = group( collection, groups )\n { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n // Output group results as indices:\n > groups = [ 'b', 'b', 'f', 'b' ];\n > var opts = { 'returns': 'indices' };\n > out = group( collection, opts, groups )\n { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n // Output group results as index-element pairs:\n > opts = { 'returns': '*' };\n > out = group( collection, opts, groups )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n See Also\n --------\n bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty collection, the function returns an empty object.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to group. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n > var out = groupBy( collection, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > out = groupBy( collection, opts, indicator )\n { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n See Also\n --------\n bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n Groups values according to an indicator function.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty object as the second argument.\n\n The `group` returned by an indicator function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n // Output group results as indices:\n > var opts = { 'returns': 'indices' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n // Output group results as index-value pairs:\n > opts = { 'returns': '*' };\n > groupByAsync( arr, opts, indicator, done )\n 1000\n 2500\n 3000\n { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > groupByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n Returns a function which groups values according to an indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.returns: string (optional)\n If `values`, values are returned; if `indices`, indices are returned; if\n `*`, both indices and values are returned. Default: 'values'.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying which group an element in the input\n collection belongs to.\n\n Returns\n -------\n out: Function\n A group-by function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = groupByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n See Also\n --------\n bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object with no prototype, the function returns an empty\n object.\n\n The function iterates over an object's own and inherited properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n > Foo.prototype = Object.create( null );\n > Foo.prototype.c = 'foo';\n > Foo.prototype.d = 'bar';\n > var obj = new Foo();\n > var out = groupIn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupIn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n Group values according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: object value.\n - key: object key.\n\n The value returned by an indicator function should be a value which can be\n serialized as an object key.\n\n If provided an empty object, the function returns an empty object.\n\n The function iterates over an object's own properties.\n\n Key iteration order is *not* guaranteed, and, thus, result order is *not*\n guaranteed.\n\n Parameters\n ----------\n obj: Object|Array|TypedArray\n Input object to group.\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n options.returns: string (optional)\n If `values`, values are returned; if `keys`, keys are returned; if `*`,\n both keys and values are returned. Default: 'values'.\n\n indicator: Function\n Indicator function indicating which group a value in the input object\n belongs to.\n\n Returns\n -------\n out: Object\n Group results.\n\n Examples\n --------\n > function indicator( v ) {\n ... if ( v[ 0 ] === 'b' ) {\n ... return 'b';\n ... }\n ... return 'other';\n ... };\n > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n > var out = groupOwn( obj, indicator )\n { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n // Output group results as keys:\n > var opts = { 'returns': 'keys' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n // Output group results as key-value pairs:\n > opts = { 'returns': '*' };\n > out = groupOwn( obj, opts, indicator )\n { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n See Also\n --------\n bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n Interchanges two vectors.\n\n In general, for best performance, especially for large vectors, provide\n 1-dimensional ndarrays whose underlying data type is either 'float64' or\n 'float32'.\n\n Parameters\n ----------\n x: ndarray|ArrayLikeObject\n First input array.\n\n y: ndarray|ArrayLikeObject\n Second input array.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n // Using ndarrays...\n > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > gswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n // Using array-like objects...\n > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n > gswap( x, y );\n > x\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n\n Examples\n --------\n > HALF_LN2\n 3.46573590279972654709e-01\n\n See Also\n --------\n LN2\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n\n Examples\n --------\n > HALF_PI\n 1.5707963267948966\n\n See Also\n --------\n PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 14 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n Additionally, as documented by Gilley and Pace (1996), the dataset contains\n eight miscoded median values.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 15 attributes:\n\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n - lstat: percent lower status of the population.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred. Harrison and Rubinfeld do not, however, mention any\n censoring.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `ArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasArrayBufferSupport()\n \n\n See Also\n --------\n hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support arrow functions.\n\n Examples\n --------\n > var bool = hasArrowFunctionSupport()\n \n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `async`/`await` support.\n\n Examples\n --------\n > var bool = hasAsyncAwaitSupport()\n \n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.asyncIterator`\n support.\n\n Examples\n --------\n > var bool = hasAsyncIteratorSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `atob` support.\n\n Examples\n --------\n > var bool = hasAtobSupport()\n \n\n See Also\n --------\n hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigInt64Array` support.\n\n Examples\n --------\n > var bool = hasBigInt64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `BigInt` support.\n\n Examples\n --------\n > var bool = hasBigIntSupport()\n \n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `BigUint64Array` support.\n\n Examples\n --------\n > var bool = hasBigUint64ArraySupport()\n \n\n See Also\n --------\n hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `btoa` support.\n\n Examples\n --------\n > var bool = hasBtoaSupport()\n \n\n See Also\n --------\n hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `class` support.\n\n Examples\n --------\n > var bool = hasClassSupport()\n \n\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `DataView` support.\n\n Examples\n --------\n > var bool = hasDataViewSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperties`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertiesSupport()\n \n\n See Also\n --------\n hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Object.defineProperty`\n support.\n\n Examples\n --------\n > var bool = hasDefinePropertySupport()\n \n\n See Also\n --------\n hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float32Array` support.\n\n Examples\n --------\n > var bool = hasFloat32ArraySupport()\n \n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Float64Array` support.\n\n Examples\n --------\n > var bool = hasFloat64ArraySupport()\n \n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has function `name` support.\n\n Examples\n --------\n > var bool = hasFunctionNameSupport()\n \n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment support generator functions.\n\n Examples\n --------\n > var bool = hasGeneratorSupport()\n \n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `globalThis` support.\n\n Examples\n --------\n > var bool = hasGlobalThisSupport()\n \n\n See Also\n --------\n getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int8Array` support.\n\n Examples\n --------\n > var bool = hasInt8ArraySupport()\n \n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int16Array` support.\n\n Examples\n --------\n > var bool = hasInt16ArraySupport()\n \n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Int32Array` support.\n\n Examples\n --------\n > var bool = hasInt32ArraySupport()\n \n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol.iterator`\n support.\n\n Examples\n --------\n > var bool = hasIteratorSymbolSupport()\n \n\n See Also\n --------\n hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Map` support.\n\n Examples\n --------\n > var bool = hasMapSupport()\n \n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Buffer` support.\n\n Examples\n --------\n > var bool = hasNodeBufferSupport()\n \n\n","hasOwnProp":"\nhasOwnProp( value, property )\n Tests if an object has a specified property.\n\n In contrast to the native `Object.prototype.hasOwnProperty`, this function\n does not throw when provided `null` or `undefined`. Instead, the function\n returns `false`.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasOwnProp( beep, 'boop' )\n true\n > bool = hasOwnProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp\n","hasProp":"\nhasProp( value, property )\n Tests if an object has a specified property, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = hasProp( beep, 'boop' )\n true\n > bool = hasProp( beep, 'toString' )\n true\n > bool = hasProp( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Proxy` support.\n\n Examples\n --------\n > var bool = hasProxySupport()\n \n\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Set` support.\n\n Examples\n --------\n > var bool = hasSetSupport()\n \n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n Examples\n --------\n > var bool = hasSharedArrayBufferSupport()\n \n\n See Also\n --------\n hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native `Symbol` support.\n\n Examples\n --------\n > var bool = hasSymbolSupport()\n \n\n See Also\n --------\n hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Symbol.toStringTag` support.\n\n Examples\n --------\n > var bool = hasToStringTagSupport()\n \n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8Array` support.\n\n Examples\n --------\n > var bool = hasUint8ArraySupport()\n \n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n Examples\n --------\n > var bool = hasUint8ClampedArraySupport()\n \n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint16Array` support.\n\n Examples\n --------\n > var bool = hasUint16ArraySupport()\n \n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `Uint32Array` support.\n\n Examples\n --------\n > var bool = hasUint32ArraySupport()\n \n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n Parameters\n ----------\n str: string\n Input string.\n\n pos: integer\n Position.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether surrogate pair exists at specified position.\n\n Examples\n --------\n > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n true\n > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakMap` support.\n\n Examples\n --------\n > var bool = hasWeakMapSupport()\n \n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has `WeakSet` support.\n\n Examples\n --------\n > var bool = hasWeakSetSupport()\n \n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an environment has native WebAssembly support.\n\n Examples\n --------\n > var bool = hasWebAssemblySupport()\n \n\n","headercase":"\nheadercase( str )\n Converts a string to HTTP header case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n HTTP header-cased string.\n\n Examples\n --------\n > var out = headercase( 'Hello World!' )\n 'Hello-World'\n > out = headercase( 'beep boop' )\n 'Beep-Boop'\n\n See Also\n --------\n camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n\n This dataset is a classic dataset commonly used in examples demonstrating\n outlier detection.\n\n Returns\n -------\n out: Array\n Observations.\n\n Examples\n --------\n > var d = HERNDON_VENUS_SEMIDIAMETERS()\n [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n References\n ----------\n - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n 5th ed. Vol. 5. London, England: Trübner & Co.\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n\n If unable to locate a home directory, the function returns `null`.\n\n Returns\n -------\n out: string|null\n Home directory.\n\n Examples\n --------\n > var home = homedir()\n e.g., '/Users/'\n\n See Also\n --------\n configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var hrs = days * HOURS_IN_DAY\n 75.36\n\n See Also\n --------\n HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var hrs = wks * HOURS_IN_WEEK\n 527.52\n\n See Also\n --------\n HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n Returns the number of hours in a month.\n\n By default, the function returns the number of hours in the current month of\n the current year (according to local time). To determine the number of hours\n for a particular month and year, provide `month` and `year` arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Hours in a month.\n\n Examples\n --------\n > var num = hoursInMonth()\n \n > num = hoursInMonth( 2 )\n \n > num = hoursInMonth( 2, 2016 )\n 696\n > num = hoursInMonth( 2, 2017 )\n 672\n\n // Other ways to supply month:\n > num = hoursInMonth( 'feb', 2016 )\n 696\n > num = hoursInMonth( 'february', 2016 )\n 696\n\n See Also\n --------\n hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n Returns the number of hours in a year according to the Gregorian calendar.\n\n By default, the function returns the number of hours in the current year\n (according to local time). To determine the number of hours for a particular\n year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of hours in a year.\n\n Examples\n --------\n > var num = hoursInYear()\n \n > num = hoursInYear( 2016 )\n 8784\n > num = hoursInYear( 2017 )\n 8760\n\n See Also\n --------\n hoursInMonth\n","httpServerFactory":"\nhttpServerFactory( [options,] [requestListener] )\n Returns a function to create an HTTP server.\n\n In addition to options documented below, the function supports any options\n supported by `http.createServer`. Which server options are supported depends\n on the Node.js version. Older Node.js versions (e.g., <= v8.12.0) do not\n support an options object when calling `http.createServer`, and, for those\n versions, any options supported by `http.createServer` in later Node.js\n versions are ignored.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.port: integer (optional)\n Server port. Default: `0` (i.e., randomly assigned).\n\n options.maxport: integer (optional)\n Max server port when port hunting. Default: `maxport = port`.\n\n options.hostname: string (optional)\n Server hostname.\n\n options.address: string (optional)\n Server address. Default: `'127.0.0.1'`.\n\n requestListener: Function (optional)\n Request callback.\n\n Returns\n -------\n httpServer: Function\n Function to create an HTTP server.\n\n Examples\n --------\n // Basic usage:\n > var boot = httpServerFactory()\n \n\n // Provide a request callback:\n > function onRequest( request, response ) {\n ... console.log( request.url );\n ... response.end( 'OK' );\n ... };\n > boot = httpServerFactory( onRequest )\n \n\n // Specify a specific port:\n > var opts = { 'port': 7331 };\n > boot = httpServerFactory( opts )\n \n\n\nboot( done )\n Creates an HTTP server.\n\n Parameters\n ----------\n done: Function\n Callback to invoke after creating a server.\n\n Examples\n --------\n > function done( error, server ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( 'Success!' );\n ... server.close();\n ... };\n > var boot = httpServerFactory();\n > boot( done );\n\n","identity":"\nidentity( x )\n Identity function.\n\n Parameters\n ----------\n x: any\n Input value.\n\n Returns\n -------\n out: any\n Input value.\n\n Examples\n --------\n > var v = identity( 3.14 )\n 3.14\n\n See Also\n --------\n constantFunction\n","ifelse":"\nifelse( bool, x, y )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n Returns\n -------\n z: any\n Either `x` or `y`.\n\n Examples\n --------\n > var z = ifelse( true, 1.0, -1.0 )\n 1.0\n > z = ifelse( false, 1.0, -1.0 )\n -1.0\n\n See Also\n --------\n ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n\n A predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n The `done` callback is invoked upon function completion and is provided at\n most two arguments:\n\n - error: error object.\n - result: either `x` or `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: any\n Value to return if a condition is truthy.\n\n y: any\n Value to return if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, true );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifelseAsync( predicate, 'beep', 'boop', done )\n 'beep'\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n Parameters\n ----------\n bool: boolean\n Condition.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n Returns\n -------\n z: any\n Return value of either `x` or `y`.\n\n Examples\n --------\n > function x() { return 1.0; };\n > function y() { return -1.0; };\n > var z = ifthen( true, x, y )\n 1.0\n > z = ifthen( false, x, y )\n -1.0\n\n See Also\n --------\n ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n\n The predicate function is provided a single argument:\n\n - clbk: callback to invoke upon predicate function completion.\n\n The predicate function callback accepts two arguments:\n\n - error: error object.\n - bool: condition used to determine whether to invoke `x` or `y`.\n\n Both `x` and `y` are provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the `done` callback is invoked with only an\n error argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n Predicate function.\n\n x: Function\n Function to invoke if a condition is truthy.\n\n y: Function\n Function to invoke if a condition is falsy.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function predicate( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, false );\n ... }\n ... };\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'beep' );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > ifthenAsync( predicate, x, y, done )\n 'boop'\n\n See Also\n --------\n ifelseAsync, ifthen\n","imag":"\nimag( z )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var im = imag( z )\n 3.0\n\n See Also\n --------\n real, reim\n","imagf":"\nimagf( z )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n im: number\n Imaginary component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var im = imagf( z )\n 3.0\n\n See Also\n --------\n imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ACANTHUS_MOLLIS()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Acanthus mollis*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_AIRPLANE_FROM_ABOVE()\n \n\n References\n ----------\n - Azari, Fédèle. 1929. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_ALLIUM_OREOPHILUM()\n \n\n References\n ----------\n - Blossfeldt, Karl. 1928. *Allium oreophilum*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_BLACK_CANYON()\n \n\n References\n ----------\n - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n Looking Above*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_DUST_BOWL_HOME()\n \n\n References\n ----------\n - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n \n\n References\n ----------\n - Braun, Adolphe. 1870. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_HOUSE_CAT()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_LOCOMOTION_NUDE_MALE()\n \n\n References\n ----------\n - Muybridge, Eadweard J. 1887. *Animal Locomotion*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n See Also\n --------\n IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_MARCH_PASTORAL()\n \n\n References\n ----------\n - Emerson, Peter Henry. 1888. *A March Pastoral*. .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n\n Returns\n -------\n out: Buffer\n Image data.\n\n Examples\n --------\n > var img = IMG_NAGASAKI_BOATS()\n \n\n References\n ----------\n - Beato, Felice. 1865. (no title). .\n\n * Digital image courtesy of the Getty's Open Content Program. While there\n are no restrictions or conditions on the use of open content images, the\n Getty would appreciate a gratis copy of any scholarly publications in which\n the images are reproduced in order to maintain the collection bibliography.\n Copies may be sent to the attention of:\n\n Open Content Program\n Registrar's Office\n The J. Paul Getty Museum\n 1200 Getty Center Drive, Suite 1000\n Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrapcorr();\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator()\n ~1.0\n\n See Also\n --------\n incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n\n If provided a feature vector and response value, the accumulator function\n updates a binary classification model and returns updated model\n coefficients.\n\n If not provided a feature vector and response value, the accumulator\n function returns the current model coefficients.\n\n Stochastic gradient descent is sensitive to the scaling of the features. One\n is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n transform the features into z-scores with zero mean and unit variance. One\n should keep in mind that the same scaling has to be applied to training data\n in order to obtain accurate predictions.\n\n In general, the more data provided to an accumulator, the more reliable the\n model predictions.\n\n Parameters\n ----------\n N: integer\n Number of features.\n\n options: Object (optional)\n Function options.\n\n options.intercept: boolean (optional)\n Boolean indicating whether to include an intercept. Default: true.\n\n options.lambda: number (optional)\n Regularization parameter. Default: 1.0e-4.\n\n options.learningRate: ArrayLike (optional)\n Learning rate function and associated (optional) parameters. The first\n array element specifies the learning rate function and must be one of\n the following:\n\n - ['constant', ...]: constant learning rate function. To set the\n learning rate, provide a second array element. By default, when the\n learn rate function is 'constant', the learning rate is set to 0.02.\n\n - ['basic']: basic learning rate function according to the formula\n `10/(10+t)` where `t` is the current iteration.\n\n - ['invscaling', ...]: inverse scaling learning rate function according\n to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n learning rate and `power_t` is the exponent controlling how quickly the\n learning rate decreases. To set the initial learning rate, provide a\n second array element. By default, the initial learning rate is 0.02. To\n set the exponent, provide a third array element. By default, the\n exponent is 0.5.\n\n - ['pegasos']: Pegasos learning rate function according to the formula\n `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n regularization parameter.\n\n Default: ['basic'].\n\n options.loss: string (optional)\n Loss function. Must be one of the following:\n\n - hinge: hinge loss function. Corresponds to a soft-margin linear\n Support Vector Machine (SVM), which can handle non-linearly separable\n data.\n\n - log: logistic loss function. Corresponds to Logistic Regression.\n\n - modifiedHuber: Huber loss function variant for classification.\n\n - perceptron: hinge loss function without a margin. Corresponds to the\n original Perceptron by Rosenblatt.\n\n - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n Default: 'log'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts response values for one ore more observation vectors. Provide a\n second argument to specify the prediction type. Must be one of the\n following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n Note that the probability prediction type is only compatible with 'log'\n and 'modifiedHuber' loss functions.\n\n Examples\n --------\n // Create an accumulator:\n > var opts = {};\n > opts.intercept = true;\n > opts.lambda = 1.0e-5;\n > var acc = incrBinaryClassification( 3, opts );\n\n // Update the model:\n > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n > var x = array( buf );\n > var coefs = acc( x, 1 )\n \n\n // Create a new observation vector:\n > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n > x = array( buf );\n\n // Predict the response value:\n > var yhat = acc.predict( x )\n \n\n See Also\n --------\n incrSGDRegression\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n\n If provided values, the accumulator function returns an updated unbiased\n sample covariance. If not provided values, the accumulator function returns\n the current unbiased sample covariance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovariance();\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator()\n ~-7.49\n\n See Also\n --------\n incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n unbiased sample covariance matrix. If not provided a data vector, the\n accumulator function returns the current unbiased sample covariance matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the covariance matrix or a square 2-dimensional ndarray for\n storing the covariance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcovmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrcv();\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator()\n ~0.47\n\n See Also\n --------\n incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwmean( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -1.5\n > v = accumulator()\n -1.5\n\n See Also\n --------\n increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n\n If provided a value, the accumulator function returns an updated standard\n deviation. If not provided a value, the accumulator function returns the\n current standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwstdev( 0.5 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n 3.5\n > s = accumulator()\n 3.5\n\n See Also\n --------\n increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n\n If provided a value, the accumulator function returns an updated variance.\n If not provided a value, the accumulator function returns the current\n variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n α: number\n Smoothing factor (value between 0 and 1).\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = increwvariance( 0.5 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 0.0\n > v = accumulator( -5.0 )\n 12.25\n > v = accumulator()\n 12.25\n\n See Also\n --------\n increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n\n If provided a value, the accumulator function returns an updated geometric\n mean. If not provided a value, the accumulator function returns the current\n geometric mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n If provided a negative value, the accumulated value is `NaN` for all future\n invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrgmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator()\n ~3.16\n\n See Also\n --------\n incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the test statistic is `NaN` for all future invocations.\n\n The accumulator must be provided *at least* three data points before\n performing Grubbs' test. Until at least three data points are provided, the\n accumulator returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n options.init: integer (optional)\n Number of data points the accumulator should use to compute initial\n statistics *before* testing for an outlier. Until the accumulator is\n provided the number of data points specified by this option, the\n accumulator returns `null`. Default: 100.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrgrubbs();\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrmgrubbs\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n\n If provided a value, the accumulator function returns an updated harmonic\n mean. If not provided a value, the accumulator function returns the current\n harmonic mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrhmean();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator()\n ~2.86\n\n See Also\n --------\n incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n\n If not provided initial centroids, the accumulator caches data vectors for\n subsequent centroid initialization. Until an accumulator computes initial\n centroids, an accumulator returns `null`.\n\n Once an accumulator has initial centroids (either provided or computed), if\n provided a data vector, the accumulator function returns updated cluster\n results. If not provided a data vector, the accumulator function returns the\n current cluster results.\n\n Cluster results are comprised of the following:\n\n - centroids: a `k x ndims` matrix containing centroid locations. Each\n centroid is the component-wise mean of the data points assigned to a\n centroid's corresponding cluster.\n - stats: a `k x 4` matrix containing cluster statistics.\n\n Cluster statistics consists of the following columns:\n\n - 0: number of data points assigned to a cluster.\n - 1: total within-cluster sum of squared distances.\n - 2: arithmetic mean of squared distances.\n - 3: corrected sample standard deviation of squared distances.\n\n Because an accumulator incrementally partitions data, one should *not*\n expect cluster statistics to match similar statistics had provided data been\n analyzed via a batch algorithm. In an incremental context, data points which\n would not be considered part of a particular cluster when analyzed via a\n batch algorithm may contribute to that cluster's statistics when analyzed\n incrementally.\n\n In general, the more data provided to an accumulator, the more reliable the\n cluster statistics.\n\n Parameters\n ----------\n k: integer|ndarray\n Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n ndims: integer (optional)\n Number of dimensions. This argument must accompany an integer-valued\n first argument.\n\n options: Object (optional)\n Function options.\n\n options.metric: string (optional)\n Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n 'correlation'. Default: 'euclidean'.\n\n options.init: ArrayLike (optional)\n Centroid initialization method and associated (optional) parameters. The\n first array element specifies the initialization method and must be one\n of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n element specifies the number of data points to use when calculating\n initial centroids. When performing kmeans++ initialization, the third\n array element specifies the number of trials to perform when randomly\n selecting candidate centroids. Typically, more trials is correlated with\n initial centroids which lead to better clustering; however, a greater\n number of trials increases computational overhead. Default: ['kmeans++',\n k, 2+⌊ln(k)⌋ ].\n\n options.normalize: boolean (optional)\n Boolean indicating whether to normalize incoming data. This option is\n only relevant for non-Euclidean distance metrics. If set to `true`, an\n accumulator partitioning data based on cosine distance normalizes\n provided data to unit Euclidean length. If set to `true`, an accumulator\n partitioning data based on correlation distance first centers provided\n data and then normalizes data dimensions to have zero mean and unit\n variance. If this option is set to `false` and the metric is either\n cosine or correlation distance, then incoming data *must* already be\n normalized. Default: true.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy incoming data to prevent mutation\n during normalization. Default: true.\n\n options.seed: any (optional)\n PRNG seed. Setting this option is useful when wanting reproducible\n initial centroids.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n acc.predict: Function\n Predicts centroid assignment for each data point in a provided matrix.\n To specify an output vector, provide a 1-dimensional ndarray as the\n first argument. Each element in the returned vector corresponds to a\n predicted cluster index for a respective data point.\n\n Examples\n --------\n > var accumulator = incrkmeans( 5, 2 );\n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v );\n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n\n If provided a value, the accumulator function returns an updated corrected\n sample excess kurtosis. If not provided a value, the accumulator function\n returns the current corrected sample excess kurtosis.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrkurtosis();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( 2.0 )\n null\n > v = accumulator( -4.0 )\n null\n > v = accumulator( -4.0 )\n -6.0\n\n See Also\n --------\n incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n\n If provided input values, the accumulator function returns an updated mean\n arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current mean arctangent absolute percentage\n error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.3218\n > m = accumulator( 5.0, 2.0 )\n ~0.6523\n > m = accumulator()\n ~0.6523\n\n See Also\n --------\n incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute error. If not provided input values, the accumulator function\n returns the current mean absolute error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmae();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample absolute correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample absolute correlation coefficient. If not provided values, the\n accumulator function returns the current moving sample absolute correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmapcorr( 3 );\n > var ar = accumulator()\n null\n > ar = accumulator( 2.0, 1.0 )\n 0.0\n > ar = accumulator( -5.0, 3.14 )\n ~1.0\n > ar = accumulator( 3.0, -1.0 )\n ~0.925\n > ar = accumulator( 5.0, -9.5 )\n ~0.863\n > ar = accumulator()\n ~0.863\n\n See Also\n --------\n incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n\n If provided input values, the accumulator function returns an updated mean\n absolute percentage error. If not provided input values, the accumulator\n function returns the current mean absolute percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmape();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator()\n ~91.67\n\n See Also\n --------\n incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n\n If provided a value, the accumulator function returns an updated maximum\n value. If not provided a value, the accumulator function returns the current\n maximum value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmax();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n\n If provided a value, the accumulator function returns an updated maximum\n absolute value. If not provided a value, the accumulator function returns\n the current maximum absolute value.\n\n If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmaxabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 10.1 )\n 10.1\n > m = accumulator()\n 10.1\n\n See Also\n --------\n incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample covariance.\n\n If provided values, the accumulator function returns an updated moving\n unbiased sample covariance. If not provided values, the accumulator function\n returns the current moving unbiased sample covariance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcovariance( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0, 1.0 )\n 0.0\n > v = accumulator( -5.0, 3.14 )\n ~-7.49\n > v = accumulator( 3.0, -1.0 )\n -8.35\n > v = accumulator( 5.0, -9.5 )\n -29.42\n > v = accumulator()\n -29.42\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n\n The `W` parameter defines the number of values over which to compute the\n moving coefficient of variation.\n\n If provided a value, the accumulator function returns an updated moving\n coefficient of variation. If not provided a value, the accumulator function\n returns the current moving coefficient of variation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmcv( 3 );\n > var cv = accumulator()\n null\n > cv = accumulator( 2.0 )\n 0.0\n > cv = accumulator( 1.0 )\n ~0.47\n > cv = accumulator( 3.0 )\n 0.5\n > cv = accumulator( 7.0 )\n ~0.83\n > cv = accumulator()\n ~0.83\n\n See Also\n --------\n incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n\n If provided input values, the accumulator function returns an updated mean\n directional accuracy. If not provided input values, the accumulator function\n returns the current mean directional accuracy.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmda();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 4.0 )\n 0.5\n > m = accumulator()\n 0.5\n\n See Also\n --------\n incrmape, incrmmda\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n\n If provided input values, the accumulator function returns an updated mean\n error. If not provided input values, the accumulator function returns the\n current mean error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrme();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator()\n 4.0\n\n See Also\n --------\n incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator()\n -1.5\n\n See Also\n --------\n incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator()\n 3.5\n\n See Also\n --------\n incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n\n If provided a value, the accumulator function returns an updated mean. If\n not provided a value, the accumulator function returns the current mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanabs2();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 4.0\n > mu = accumulator( -5.0 )\n 14.5\n > mu = accumulator()\n 14.5\n\n See Also\n --------\n incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanstdev();\n > var ms = accumulator()\n null\n > ms = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > ms = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > ms = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > ms = accumulator( 5.0 )\n [ 1.25, ~4.35 ]\n > ms = accumulator()\n [ 1.25, ~4.35 ]\n\n See Also\n --------\n incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current accumulated values.\n\n If provided `NaN`, the accumulated values are equal to `NaN` for all future\n invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmeanvar();\n > var mv = accumulator()\n null\n > mv = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > mv = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > mv = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > mv = accumulator( 5.0 )\n [ 1.25, ~18.92 ]\n > mv = accumulator()\n [ 1.25, ~18.92 ]\n\n See Also\n --------\n incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving geometric mean.\n\n If provided a value, the accumulator function returns an updated moving\n geometric mean. If not provided a value, the accumulator function returns\n the current moving geometric mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmgmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~3.16\n > v = accumulator( 3.0 )\n ~3.11\n > v = accumulator( 5.0 )\n ~4.22\n > v = accumulator()\n ~4.22\n\n See Also\n --------\n incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n\n Grubbs' test assumes that data is normally distributed. Accordingly, one\n should first verify that the data can be reasonably approximated by a normal\n distribution before applying the Grubbs' test.\n\n The `W` parameter defines the number of values over which to perform Grubbs'\n test. The minimum window size is 3.\n\n If provided a value, the accumulator function returns updated test results.\n If not provided a value, the accumulator function returns the current test\n results.\n\n Until provided `W` values, the accumulator function returns `null`.\n\n The accumulator function returns an object having the following fields:\n\n - rejected: boolean indicating whether the null hypothesis should be\n rejected.\n - alpha: significance level.\n - criticalValue: critical value.\n - statistic: test statistic.\n - df: degrees of freedom.\n - mean: sample mean.\n - sd: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - alt: alternative hypothesis.\n - method: method name.\n - print: method for pretty-printing test output.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Significance level. Default: 0.05.\n\n options.alternative: string (optional)\n Alternative hypothesis. The option may be one of the following values:\n\n - 'two-sided': test whether the minimum or maximum value is an outlier.\n - 'min': test whether the minimum value is an outlier.\n - 'max': test whether the maximum value is an outlier.\n\n Default: 'two-sided'.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var acc = incrmgrubbs( 20 );\n > var res = acc()\n null\n > for ( var i = 0; i < 200; i++ ) {\n ... res = acc( base.random.normal( 10.0, 5.0 ) );\n ... };\n > res.print()\n\n References\n ----------\n - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n 00401706.1969.10490657.\n\n See Also\n --------\n incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving harmonic mean.\n\n If provided a value, the accumulator function returns an updated moving\n harmonic mean. If not provided a value, the accumulator function returns the\n current moving harmonic mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmhmean( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( 5.0 )\n ~2.86\n > v = accumulator( 3.0 )\n ~2.90\n > v = accumulator( 5.0 )\n ~4.09\n > v = accumulator()\n ~4.09\n\n See Also\n --------\n incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If provided a value, the accumulator function returns an updated mid-range.\n If not provided a value, the accumulator function returns the current mid-\n range.\n\n If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmidrange();\n > var v = accumulator()\n null\n > v = accumulator( 3.14 )\n 3.14\n > v = accumulator( -5.0 )\n ~-0.93\n > v = accumulator( 10.1 )\n 2.55\n > v = accumulator()\n 2.55\n\n See Also\n --------\n incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n\n If provided a value, the accumulator function returns an updated minimum\n value. If not provided a value, the accumulator function returns the current\n minimum value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmin();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 10.1 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n\n If provided a value, the accumulator function returns an updated minimum\n absolute value. If not provided a value, the accumulator function returns\n the current minimum absolute value.\n\n If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminabs();\n > var m = accumulator()\n null\n > m = accumulator( 3.14 )\n 3.14\n > m = accumulator( -5.0 )\n 3.14\n > m = accumulator( 10.1 )\n 3.14\n > m = accumulator()\n 3.14\n\n See Also\n --------\n incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmax();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n\n If provided a value, the accumulator function returns an updated minimum and\n maximum. If not provided a value, the accumulator function returns the\n current minimum and maximum.\n\n If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n future invocations.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrminmaxabs();\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator()\n [ 2.0, 5.0 ]\n\n See Also\n --------\n incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean arctangent absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean arctangent absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean arctangent absolute\n percentage error.\n\n Note that, unlike the mean absolute percentage error (MAPE), the mean\n arctangent absolute percentage error is expressed in radians on the interval\n [0,π/2].\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~0.32\n > m = accumulator( 5.0, 2.0 )\n ~0.65\n > m = accumulator( 3.0, 2.0 )\n ~0.59\n > m = accumulator( 2.0, 5.0 )\n ~0.66\n > m = accumulator()\n ~0.66\n\n See Also\n --------\n incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute error.\n\n If provided a value, the accumulator function returns an updated moving\n mean absolute error. If not provided a value, the accumulator function\n returns the current moving mean absolute error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmae( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n 3.0\n > m = accumulator( 5.0, -2.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean absolute percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean absolute percentage error. If not provided input values, the\n accumulator function returns the current moving mean absolute percentage\n error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmape( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~91.67\n > m = accumulator( 3.0, 2.0 )\n ~77.78\n > m = accumulator( 2.0, 5.0 )\n ~86.67\n > m = accumulator()\n ~86.67\n\n See Also\n --------\n incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum.\n\n If provided a value, the accumulator function returns an updated moving\n maximum. If not provided a value, the accumulator function returns the\n current moving maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmax( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 3.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving maximum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n maximum absolute value. If not provided a value, the accumulator function\n returns the current moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmaxabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 5.0\n > m = accumulator( 3.0 )\n 5.0\n > m = accumulator( 5.0 )\n 5.0\n > m = accumulator()\n 5.0\n\n See Also\n --------\n incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean directional accuracy.\n\n If provided input values, the accumulator function returns an updated moving\n mean directional accuracy. If not provided input values, the accumulator\n function returns the current moving mean directional accuracy.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmda( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( 5.0, 2.0 )\n 0.5\n > m = accumulator( 3.0, 2.0 )\n ~0.33\n > m = accumulator( 4.0, 5.0 )\n ~0.33\n > m = accumulator()\n ~0.33\n\n See Also\n --------\n incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean error.\n\n If provided a value, the accumulator function returns an updated moving\n mean error. If not provided a value, the accumulator function returns the\n current moving mean error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmme( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 4.0\n > m = accumulator( 3.0, 2.0 )\n ~2.33\n > m = accumulator( 5.0, -2.0 )\n ~-0.33\n > m = accumulator()\n ~-0.33\n\n See Also\n --------\n incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmean( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n -1.5\n > mu = accumulator( 3.0 )\n 0.0\n > mu = accumulator( 5.0 )\n 1.0\n > mu = accumulator()\n 1.0\n\n See Also\n --------\n incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs( 3 );\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0 )\n 2.0\n > mu = accumulator( -5.0 )\n 3.5\n > mu = accumulator( 3.0 )\n ~3.33\n > mu = accumulator( 5.0 )\n ~4.33\n > mu = accumulator()\n ~4.33\n\n See Also\n --------\n incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving mean.\n\n If provided a value, the accumulator function returns an updated moving\n mean. If not provided a value, the accumulator function returns the current\n moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanabs2( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 4.0\n > m = accumulator( -5.0 )\n 14.5\n > m = accumulator( 3.0 )\n ~12.67\n > m = accumulator( 5.0 )\n ~19.67\n > m = accumulator()\n ~19.67\n\n See Also\n --------\n incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and corrected sample standard deviation.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanstdev( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, ~4.95 ]\n > v = accumulator( 3.0 )\n [ 0.0, ~4.36 ]\n > v = accumulator( 5.0 )\n [ 1.0, ~5.29 ]\n > v = accumulator()\n [ 1.0, ~5.29 ]\n\n See Also\n --------\n incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving arithmetic mean and unbiased sample variance.\n\n If provided a value, the accumulator function returns updated accumulated\n values. If not provided a value, the accumulator function returns the\n current moving accumulated values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n accumulated values are calculated from smaller sample sizes. Until the\n window is full, each returned accumulated value is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmeanvar( 3 );\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n [ 2.0, 0.0 ]\n > v = accumulator( -5.0 )\n [ -1.5, 24.5 ]\n > v = accumulator( 3.0 )\n [ 0.0, 19.0 ]\n > v = accumulator( 5.0 )\n [ 1.0, 28.0 ]\n > v = accumulator()\n [ 1.0, 28.0 ]\n\n See Also\n --------\n incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of values over which to compute\n the moving mid-range.\n\n If provided a value, the accumulator function returns an updated moving mid-\n range. If not provided a value, the accumulator function returns the current\n moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmidrange( 3 );\n > var mr = accumulator()\n null\n > mr = accumulator( 2.0 )\n 2.0\n > mr = accumulator( -5.0 )\n -1.5\n > mr = accumulator( 3.0 )\n -1.0\n > mr = accumulator( 5.0 )\n 0.0\n > mr = accumulator()\n 0.0\n\n See Also\n --------\n incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum. If not provided a value, the accumulator function returns the\n current moving minimum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmin( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n -5.0\n > m = accumulator( 3.0 )\n -5.0\n > m = accumulator( 5.0 )\n -5.0\n > m = accumulator()\n -5.0\n\n See Also\n --------\n incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum absolute value.\n\n If provided a value, the accumulator function returns an updated moving\n minimum absolute value. If not provided a value, the accumulator function\n returns the current moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminabs( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0 )\n 2.0\n > m = accumulator( -5.0 )\n 2.0\n > m = accumulator( 3.0 )\n 2.0\n > m = accumulator( 5.0 )\n 3.0\n > m = accumulator()\n 3.0\n\n See Also\n --------\n incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n\n The `W` parameter defines the number of values over which to compute the\n moving minimum and maximum.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmax( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ -5.0, 2.0 ]\n > mm = accumulator( 3.0 )\n [ -5.0, 3.0 ]\n > mm = accumulator( 5.0 )\n [ -5.0, 5.0 ]\n > mm = accumulator()\n [ -5.0, 5.0 ]\n\n See Also\n --------\n incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n\n The `W` parameter defines the number of values over which to compute moving\n minimum and maximum absolute values.\n\n If provided a value, the accumulator function returns an updated moving\n minimum and maximum. If not provided a value, the accumulator function\n returns the current moving minimum and maximum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n minimum and maximum values are calculated from smaller sample sizes. Until\n the window is full, each returned minimum and maximum is calculated from all\n provided values.\n\n Parameters\n ----------\n out: Array|TypedArray (optional)\n Output array.\n\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmminmaxabs( 3 );\n > var mm = accumulator()\n null\n > mm = accumulator( 2.0 )\n [ 2.0, 2.0 ]\n > mm = accumulator( -5.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 3.0 )\n [ 2.0, 5.0 ]\n > mm = accumulator( 5.0 )\n [ 3.0, 5.0 ]\n > mm = accumulator()\n [ 3.0, 5.0 ]\n\n See Also\n --------\n incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean percentage error.\n\n If provided input values, the accumulator function returns an updated moving\n mean percentage error. If not provided input values, the accumulator\n function returns the current moving mean percentage error.\n\n As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmpe( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator( 3.0, 2.0 )\n ~-55.56\n > m = accumulator( 2.0, 5.0 )\n ~-46.67\n > m = accumulator()\n ~-46.67\n\n See Also\n --------\n incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving mean squared error.\n\n If provided a value, the accumulator function returns an updated moving mean\n squared error. If not provided a value, the accumulator function returns the\n current moving mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmmse( 3 );\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator( 3.0, 2.0 )\n 17.0\n > m = accumulator( 5.0, -2.0 )\n 33.0\n > m = accumulator()\n 33.0\n\n See Also\n --------\n incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation coefficient. If not provided values, the accumulator\n function returns the current moving sample correlation coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator( 3.0, -1.0 )\n ~-0.925\n > r = accumulator( 5.0, -9.5 )\n ~-0.863\n > r = accumulator()\n ~-0.863\n\n See Also\n --------\n incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n\n The `W` parameter defines the number of values over which to compute the\n moving squared sample correlation coefficient.\n\n If provided values, the accumulator function returns an updated moving\n squared sample correlation coefficient. If not provided values, the\n accumulator function returns the current moving squared sample correlation\n coefficient.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorr2( 3 );\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator( 3.0, -1.0 )\n ~0.86\n > r2 = accumulator( 5.0, -9.5 )\n ~0.74\n > r2 = accumulator()\n ~0.74\n\n See Also\n --------\n incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n However, due to limitations inherent in representing numeric values using\n floating-point format (i.e., the inability to represent numeric values with\n infinite precision), the correlation distance between perfectly correlated\n random variables may *not* be `0` or `2`. In fact, the correlation distance\n is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n distance should, however, be within floating-point roundoff error.\n\n The `W` parameter defines the number of values over which to compute the\n moving sample correlation distance.\n\n If provided values, the accumulator function returns an updated moving\n sample correlation distance. If not provided values, the accumulator\n function returns the current moving sample correlation distance.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpcorrdist( 3 );\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator( 3.0, -1.0 )\n ~1.925\n > d = accumulator( 5.0, -9.5 )\n ~1.863\n > d = accumulator()\n ~1.863\n\n See Also\n --------\n incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n\n If provided input values, the accumulator function returns an updated mean\n percentage error. If not provided input values, the accumulator function\n returns the current mean percentage error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmpe();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n ~33.33\n > m = accumulator( 5.0, 2.0 )\n ~-58.33\n > m = accumulator()\n ~-58.33\n\n See Also\n --------\n incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n Returns an accumulator function which incrementally computes a moving\n product.\n\n The `W` parameter defines the number of values over which to compute the\n moving product.\n\n If provided a value, the accumulator function returns an updated moving\n product. If not provided a value, the accumulator function returns the\n current moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n For accumulations over large windows or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmprod( 3 );\n > var p = accumulator()\n null\n > p = accumulator( 2.0 )\n 2.0\n > p = accumulator( -5.0 )\n -10.0\n > p = accumulator( 3.0 )\n -30.0\n > p = accumulator( 5.0 )\n -75.0\n > p = accumulator()\n -75.0\n\n See Also\n --------\n incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n Returns an accumulator function which incrementally computes a moving range.\n\n The `W` parameter defines the number of values over which to compute the\n moving range.\n\n If provided a value, the accumulator function returns an updated moving\n range. If not provided a value, the accumulator function returns the current\n moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrange( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0 )\n 0.0\n > r = accumulator( -5.0 )\n 7.0\n > r = accumulator( 3.0 )\n 8.0\n > r = accumulator( 5.0 )\n 10.0\n > r = accumulator()\n 10.0\n\n See Also\n --------\n incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n\n The `W` parameter defines the number of values over which to compute the\n moving root mean squared error.\n\n If provided a value, the accumulator function returns an updated moving root\n mean squared error. If not provided a value, the accumulator function\n returns the current moving root mean squared error.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrmse( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator( 3.0, 2.0 )\n ~4.12\n > r = accumulator( 5.0, -2.0 )\n ~5.74\n > r = accumulator()\n ~5.74\n\n See Also\n --------\n incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n\n The `W` parameter defines the number of values over which to compute the\n moving residual sum of squares.\n\n If provided a value, the accumulator function returns an updated moving\n residual sum of squares. If not provided a value, the accumulator function\n returns the current moving residual sum of squares.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmrss( 3 );\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator( 3.0, 2.0 )\n 51.0\n > r = accumulator( 5.0, -2.0 )\n 99.0\n > r = accumulator()\n 99.0\n\n See Also\n --------\n incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n\n If provided input values, the accumulator function returns an updated mean\n squared error. If not provided input values, the accumulator function\n returns the current mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmse();\n > var m = accumulator()\n null\n > m = accumulator( 2.0, 3.0 )\n 1.0\n > m = accumulator( -5.0, 2.0 )\n 25.0\n > m = accumulator()\n 25.0\n\n See Also\n --------\n incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n\n The `W` parameter defines the number of values over which to compute the\n moving corrected sample standard deviation.\n\n If provided a value, the accumulator function returns an updated moving\n corrected sample standard deviation. If not provided a value, the\n accumulator function returns the current moving corrected sample standard\n deviation.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmstdev( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator( 3.0 )\n ~4.36\n > s = accumulator( 5.0 )\n ~5.29\n > s = accumulator()\n ~5.29\n\n See Also\n --------\n incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n Returns an accumulator function which incrementally computes a moving sum.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsum( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator( 3.0 )\n 0.0\n > s = accumulator( 5.0 )\n 3.0\n > s = accumulator()\n 3.0\n\n See Also\n --------\n incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator( 3.0 )\n 10.0\n > s = accumulator( -5.0 )\n 13.0\n > s = accumulator()\n 13.0\n\n See Also\n --------\n incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n\n The `W` parameter defines the number of values over which to compute the\n moving sum.\n\n If provided a value, the accumulator function returns an updated moving sum.\n If not provided a value, the accumulator function returns the current moving\n sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumabs2( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator( 3.0 )\n 38.0\n > s = accumulator( -5.0 )\n 59.0\n > s = accumulator()\n 59.0\n\n See Also\n --------\n incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n\n The `W` parameter defines the number of values over which to compute the\n moving statistical summary.\n\n If provided a value, the accumulator function returns an updated moving\n statistical summary. If not provided a value, the accumulator function\n returns the current moving statistical summary.\n\n The returned summary is an object containing the following fields:\n\n - window: window size.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - min: minimum value.\n - max: maximum value.\n - range: range.\n - midrange: arithmetic mean of the minimum and maximum values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n summaries are calculated from smaller sample sizes. Until the window is\n full, each returned summary is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsummary( 3 );\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n\n The `W` parameter defines the number of (x,y) pairs over which to compute\n the moving sum of products.\n\n If provided input values, the accumulator function returns an updated moving\n sum. If not provided input values, the accumulator function returns the\n current moving sum.\n\n As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n returned values are calculated from smaller sample sizes. Until the window\n is full, each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmsumprod( 3 );\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator( 3.0, -2.0 )\n -10.0\n > s = accumulator( 5.0, 3.0 )\n -1.0\n > s = accumulator()\n -1.0\n\n See Also\n --------\n incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n\n The `W` parameter defines the number of values over which to compute the\n moving unbiased sample variance.\n\n If provided a value, the accumulator function returns an updated moving\n unbiased sample variance. If not provided a value, the accumulator function\n returns the current moving unbiased sample variance.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvariance( 3 );\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator( 3.0 )\n 19.0\n > s2 = accumulator( 5.0 )\n 28.0\n > s2 = accumulator()\n 28.0\n\n See Also\n --------\n incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n\n The `W` parameter defines the number of values over which to compute the\n moving variance-to-mean ratio.\n\n If provided a value, the accumulator function returns an updated moving\n variance-to-mean ratio. If not provided a value, the accumulator function\n returns the current moving variance-to-mean ratio.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all provided values.\n\n Parameters\n ----------\n W: integer\n Window size.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrmvmr( 3 );\n > var F = accumulator()\n null\n > F = accumulator( 2.0 )\n 0.0\n > F = accumulator( 1.0 )\n ~0.33\n > F = accumulator( 3.0 )\n 0.5\n > F = accumulator( 7.0 )\n ~2.55\n > F = accumulator()\n ~2.55\n\n See Also\n --------\n incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n\n If provided a value, the accumulator function returns an updated count. If\n not provided a value, the accumulator function returns the current count.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnancount();\n > var v = accumulator()\n 0\n > v = accumulator( 2.0 )\n 1\n > v = accumulator( -5.0 )\n 2\n > v = accumulator()\n 2\n\n See Also\n --------\n incrnansum\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( NaN )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrnansumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( NaN )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated sample\n correlation coefficient. If not provided values, the accumulator function\n returns the current sample correlation coefficient.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 1.0 )\n 0.0\n > r = accumulator( -5.0, 3.14 )\n ~-1.0\n > r = accumulator()\n ~-1.0\n\n See Also\n --------\n incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n\n If provided values, the accumulator function returns an updated accumulated\n value. If not provided values, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorr2();\n > var r2 = accumulator()\n null\n > r2 = accumulator( 2.0, 1.0 )\n 0.0\n > r2 = accumulator( -5.0, 3.14 )\n ~1.0\n > r2 = accumulator()\n ~1.0\n\n See Also\n --------\n incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n\n The correlation distance is defined as one minus the Pearson product-moment\n correlation coefficient and, thus, resides on the interval [0,2].\n\n If provided values, the accumulator function returns an updated sample\n correlation distance. If not provided values, the accumulator function\n returns the current sample correlation distance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mx: number (optional)\n Known mean.\n\n my: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdist();\n > var d = accumulator()\n null\n > d = accumulator( 2.0, 1.0 )\n 1.0\n > d = accumulator( -5.0, 3.14 )\n ~2.0\n > d = accumulator()\n ~2.0\n\n See Also\n --------\n incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation distance matrix. If not provided a data vector, the\n accumulator function returns the current sample correlation distance matrix.\n\n Due to limitations inherent in representing numeric values using floating-\n point format (i.e., the inability to represent numeric values with infinite\n precision), the correlation distance between perfectly correlated random\n variables may *not* be `0` or `2`. In fact, the correlation distance is\n *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n should, however, be within floating-point roundoff error.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation distance matrix or a square 2-dimensional\n ndarray for storing the correlation distance matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrdistmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n\n If provided a data vector, the accumulator function returns an updated\n sample correlation matrix. If not provided a data vector, the accumulator\n function returns the current sample correlation matrix.\n\n Parameters\n ----------\n out: integer|ndarray\n Order of the correlation matrix or a square 2-dimensional ndarray for\n storing the correlation matrix.\n\n means: ndarray (optional)\n Known means.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrpcorrmat( 2 );\n > var out = accumulator()\n \n > var buf = new Float64Array( 2 );\n > var shape = [ 2 ];\n > var strides = [ 1 ];\n > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n > v.set( 0, 2.0 );\n > v.set( 1, 1.0 );\n > out = accumulator( v )\n \n > v.set( 0, -5.0 );\n > v.set( 1, 3.14 );\n > out = accumulator( v )\n \n > out = accumulator()\n \n\n See Also\n --------\n incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n\n If provided a value, the accumulator function returns an updated product. If\n not provided a value, the accumulator function returns the current product.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow. Note, however, that overflow/underflow\n may be transient, as the accumulator does not use a double-precision\n floating-point number to store an accumulated product. Instead, the\n accumulator splits an accumulated product into a normalized fraction and\n exponent and updates each component separately. Doing so guards against a\n loss in precision.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrprod();\n > var v = accumulator()\n null\n > v = accumulator( 2.0 )\n 2.0\n > v = accumulator( -5.0 )\n -10.0\n > v = accumulator()\n -10.0\n\n See Also\n --------\n incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n\n If provided a value, the accumulator function returns an updated range. If\n not provided a value, the accumulator function returns the current range.\n\n If provided `NaN`, the range is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrange();\n > var v = accumulator()\n null\n > v = accumulator( -2.0 )\n 0.0\n > v = accumulator( 1.0 )\n 3.0\n > v = accumulator( 3.0 )\n 5.0\n > v = accumulator()\n 5.0\n\n See Also\n --------\n incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n\n If provided input values, the accumulator function returns an updated root\n mean squared error. If not provided input values, the accumulator function\n returns the current root mean squared error.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrmse();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 5.0\n > r = accumulator()\n 5.0\n\n See Also\n --------\n incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n\n If provided input values, the accumulator function returns an updated\n residual sum of squares. If not provided input values, the accumulator\n function returns the current residual sum of squares.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrrss();\n > var r = accumulator()\n null\n > r = accumulator( 2.0, 3.0 )\n 1.0\n > r = accumulator( -5.0, 2.0 )\n 50.0\n > r = accumulator()\n 50.0\n\n See Also\n --------\n incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n\n If provided a value, the accumulator function returns an updated corrected\n sample skewness. If not provided a value, the accumulator function returns\n the current corrected sample skewness.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrskewness();\n > var v = accumulator( 2.0 )\n null\n > v = accumulator( -5.0 )\n null\n > v = accumulator( -10.0 )\n ~0.492\n > v = accumulator()\n ~0.492\n\n See Also\n --------\n incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n Generates a linearly spaced numeric array using a provided increment.\n\n If an `increment` is not provided, the default `increment` is `1`.\n\n The output array is guaranteed to include the `start` value but does not\n include the `stop` value.\n\n Parameters\n ----------\n start: number\n First array value.\n\n stop: number\n Array element bound.\n\n increment: number (optional)\n Increment. Default: `1`.\n\n Returns\n -------\n arr: Array\n Linearly spaced numeric array.\n\n Examples\n --------\n > var arr = incrspace( 0, 11, 2 )\n [ 0, 2, 4, 6, 8, 10 ]\n\n See Also\n --------\n linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n\n If provided a value, the accumulator function returns an updated corrected\n sample standard deviation. If not provided a value, the accumulator function\n returns the current corrected sample standard deviation.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrstdev();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 0.0\n > s = accumulator( -5.0 )\n ~4.95\n > s = accumulator()\n ~4.95\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsum();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n -3.0\n > s = accumulator()\n -3.0\n\n See Also\n --------\n incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 2.0\n > s = accumulator( -5.0 )\n 7.0\n > s = accumulator()\n 7.0\n\n See Also\n --------\n incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n\n If provided a value, the accumulator function returns an updated sum. If not\n provided a value, the accumulator function returns the current sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumabs2();\n > var s = accumulator()\n null\n > s = accumulator( 2.0 )\n 4.0\n > s = accumulator( -5.0 )\n 29.0\n > s = accumulator()\n 29.0\n\n See Also\n --------\n incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n\n If provided a value, the accumulator function returns an updated summary. If\n not provided a value, the accumulator function returns the current summary.\n\n The returned summary is an object containing the following fields:\n\n - count: count.\n - max: maximum value.\n - min: minimum value.\n - range: range.\n - midrange: mid-range.\n - sum: sum.\n - mean: arithmetic mean.\n - variance: unbiased sample variance.\n - stdev: corrected sample standard deviation.\n - skewness: corrected sample skewness.\n - kurtosis: corrected sample excess kurtosis.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsummary();\n > var s = accumulator()\n {}\n > s = accumulator( 2.0 )\n {...}\n > s = accumulator( -5.0 )\n {...}\n > s = accumulator()\n {...}\n\n See Also\n --------\n incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n\n If provided input values, the accumulator function returns an updated sum.\n If not provided input values, the accumulator function returns the current\n sum.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n For long running accumulations or accumulations of large numbers, care\n should be taken to prevent overflow.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrsumprod();\n > var s = accumulator()\n null\n > s = accumulator( 2.0, 3.0 )\n 6.0\n > s = accumulator( -5.0, 2.0 )\n -4.0\n > s = accumulator()\n -4.0\n\n See Also\n --------\n incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n\n If provided a value, the accumulator function returns an updated unbiased\n sample variance. If not provided a value, the accumulator function returns\n the current unbiased sample variance.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvariance();\n > var s2 = accumulator()\n null\n > s2 = accumulator( 2.0 )\n 0.0\n > s2 = accumulator( -5.0 )\n 24.5\n > s2 = accumulator()\n 24.5\n\n See Also\n --------\n incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n\n If provided a value, the accumulator function returns an updated accumulated\n value. If not provided a value, the accumulator function returns the current\n accumulated value.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n Parameters\n ----------\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrvmr();\n > var D = accumulator()\n null\n > D = accumulator( 2.0 )\n 0.0\n > D = accumulator( 1.0 )\n ~0.33\n > D = accumulator()\n ~0.33\n\n See Also\n --------\n incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n\n If provided arguments, the accumulator function returns an updated weighted\n mean. If not provided arguments, the accumulator function returns the\n current weighted mean.\n\n If provided `NaN` or a value which, when used in computations, results in\n `NaN`, the accumulated value is `NaN` for all future invocations.\n\n The accumulator function accepts two arguments:\n\n - x: value.\n - w: weight.\n\n Returns\n -------\n acc: Function\n Accumulator function.\n\n Examples\n --------\n > var accumulator = incrwmean();\n > var mu = accumulator()\n null\n > mu = accumulator( 2.0, 1.0 )\n 2.0\n > mu = accumulator( 2.0, 0.5 )\n 2.0\n > mu = accumulator( 3.0, 1.5 )\n 2.5\n > mu = accumulator()\n 2.5\n\n See Also\n --------\n increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n Converts a linear index to an array of subscripts.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n Returns\n -------\n out: Array\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var s = ind2sub( d, 17 )\n [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n idx: integer\n Linear index.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle a linear index which exceeds array dimensions.\n If equal to 'throw', the function throws an error when a linear index\n exceeds array dimensions. If equal to 'normalize', the function\n normalizes negative linear indices and throws an error when a linear\n index exceeds array dimensions. If equal to 'wrap', the function wraps\n around a linear index exceeding array dimensions using modulo\n arithmetic. If equal to 'clamp', the function sets a linear index\n exceeding array dimensions to either `0` (minimum linear index) or the\n maximum linear index. Default: 'throw'.\n\n out: Array|TypedArray|Object\n Output array.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Subscripts.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var out = [ 0, 0, 0 ];\n > var s = ind2sub.assign( d, 17, out )\n [ 1, 2, 2 ]\n > var bool = ( s === out )\n true\n\n See Also\n --------\n array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n Returns the first index at which a given element can be found.\n\n Search is performed using *strict equality* comparison.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object.\n\n searchElement: any\n Element to find.\n\n fromIndex: integer (optional)\n Starting index (if negative, the start index is determined relative to\n last element).\n\n Returns\n -------\n out: integer\n Index or -1.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ 4, 3, 2, 1 ];\n > var idx = indexOf( arr, 3 )\n 1\n > arr = [ 4, 3, 2, 1 ];\n > idx = indexOf( arr, 5 )\n -1\n\n // Using a `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, 3 )\n 5\n\n // `fromIndex` which exceeds `array` length:\n > arr = [ 1, 2, 3, 4, 2, 5 ];\n > idx = indexOf( arr, 2, 10 )\n -1\n\n // Negative `fromIndex`:\n > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n > idx = indexOf( arr, 2, -4 )\n 5\n > idx = indexOf( arr, 2, -1 )\n 7\n\n // Negative `fromIndex` exceeding input `array` length:\n > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n > idx = indexOf( arr, 2, -10 )\n 1\n\n // Array-like objects:\n > var str = 'bebop';\n > idx = indexOf( str, 'o' )\n 3\n\n","inherit":"\ninherit( ctor, superCtor )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n\n This function is not designed to work with ES2015/ES6 classes. For\n ES2015/ES6 classes, use `class` with `extends`.\n\n Parameters\n ----------\n ctor: Object|Function\n Constructor which will inherit.\n\n superCtor: Object|Function\n Super (parent) constructor.\n\n Returns\n -------\n out: Object|Function\n Child constructor.\n\n Examples\n --------\n // Create a parent constructor:\n > function Foo() { return this; };\n > Foo.prototype.beep = function beep() { return 'boop'; };\n\n // Create a child constructor:\n > function Bar() { Foo.call( this ); return this; };\n\n // Setup inheritance:\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var v = bar.beep()\n 'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited enumerable properties.\n\n Examples\n --------\n > var props = inheritedEnumerableProperties( {} )\n\n See Also\n --------\n enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n See Also\n --------\n enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n Returns an array of an object's inherited enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable property names.\n\n Examples\n --------\n > var keys = inheritedKeys( {} )\n\n See Also\n --------\n objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited non-enumerable properties.\n\n Examples\n --------\n > var props = inheritedNonEnumerableProperties( {} )\n\n See Also\n --------\n inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n Returns an array of an object's inherited non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited non-enumerable property names.\n\n Examples\n --------\n > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n See Also\n --------\n inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n Returns an array of an object's inherited property names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited property names and symbols.\n\n Examples\n --------\n > var symbols = inheritedProperties( [] )\n\n See Also\n --------\n properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n Returns a property descriptor for an object's inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n {...}\n\n See Also\n --------\n propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n Returns an object's inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n desc: Object\n An object's inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = inheritedPropertyDescriptors( obj )\n { 'foo': {...}, ... }\n\n See Also\n --------\n propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited enumerable and non-enumerable property\n names.\n\n Examples\n --------\n > var keys = inheritedPropertyNames( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n Returns an array of an object's inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited symbol properties.\n\n Examples\n --------\n > var symbols = inheritedPropertySymbols( [] )\n\n See Also\n --------\n inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n Returns an array of an object's inherited writable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n props: Array\n List of an object's inherited writable properties.\n\n Examples\n --------\n > var props = inheritedWritableProperties( {} )\n\n See Also\n --------\n inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n Returns an array of an object's inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n keys: Array\n List of an object's inherited writable property names.\n\n Examples\n --------\n > var keys = inheritedWritablePropertyNames( {} )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n Returns an array of an object's inherited writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n level: integer (optional)\n Inheritance level.\n\n Returns\n -------\n symbols: Array\n List of an object's inherited writable symbol properties.\n\n Examples\n --------\n > var symbols = inheritedWritablePropertySymbols( [] )\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmap( arr, foo )\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 2000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 2000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > inmapAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 2000 ]\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 2000 ]\n\n See Also\n --------\n forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n\n When invoked, the input function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection. If provided an object, the object must be array-like\n (excluding strings and functions).\n\n fcn: Function\n Function to invoke for each element in the input collection. The\n function's return value is used to update the collection in-place.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n > var arr = [ 1.0, 2.0, 3.0 ];\n > var out = inmapRight( arr, foo )\n 2: 3.0\n 1: 2.0\n 0: 1.0\n [ 0.0, 2.0, 6.0 ]\n > var bool = ( out === arr )\n true\n\n See Also\n --------\n forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n\n When invoked, `fcn` is provided a maximum of four arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If `fcn`\n accepts two arguments, `fcn` is provided:\n\n - value\n - next\n\n If `fcn` accepts three arguments, `fcn` is provided:\n\n - value\n - index\n - next\n\n For every other `fcn` signature, `fcn` is provided all four arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: value used to update the collection.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling. Note, however, that the function\n may have mutated an input collection during prior invocations, resulting in\n a partially mutated collection.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, fcn, done )\n 1000\n 2500\n 3000\n true\n [ 0, 2500, 6000 ]\n\n // Limit number of concurrent invocations:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 2500\n 3000\n 1000\n true\n [ 0, 2500, 6000 ]\n\n // Process sequentially:\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > inmapRightAsync( arr, opts, fcn, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, value*index );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = inmapRightAsync.factory( opts, fcn );\n > function done( error, collection ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( collection === arr );\n ... console.log( collection );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n [ 0, 2500, 6000 ]\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n [ 0, 1500, 4000 ]\n\n See Also\n --------\n forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n Returns a writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n Returns a function for creating writable streams for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating writable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectSinkStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to encode strings as `Buffer` objects before writing\n data to a returned stream. Default: true.\n\n options.defaultEncoding: string (optional)\n Default encoding when not explicitly specified when writing data.\n Default: 'utf8'.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: WritableStream\n Writable stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectSinkStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n Returns a transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n Returns a function for creating transform streams for inspecting stream\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream( clbk ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = inspectStream.factory( opts );\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = createStream( clbk );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n clbk: Function\n Callback to invoke upon receiving data.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n > var s = inspectStream.objectMode( clbk );\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n debugStream","instanceOf":"\ninstanceOf( value, constructor )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n\n While the prototype of an `object` created using object literal notion is\n `undefined`, the function returns `true` when provided an `object` literal\n and the `Object` constructor. This maintains consistent behavior with the\n `instanceof` operator.\n\n Parameters\n ----------\n value: any\n Input value.\n\n constructor: Function\n Constructor.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an instance of a provided constructor.\n\n Examples\n --------\n > var bool = instanceOf( [], Array )\n true\n > bool = instanceOf( {}, Object )\n true\n > bool = instanceOf( null, Object )\n false\n\n See Also\n --------\n isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n\n The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n Examples\n --------\n > INT8_MAX\n 127\n\n See Also\n --------\n INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n\n The minimum signed 8-bit integer is given by `-(2^7)`.\n\n Examples\n --------\n > INT8_MIN\n -128\n\n See Also\n --------\n INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n\n Examples\n --------\n > INT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array()\n \n\n\nInt8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Int8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'\n\n\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n \n\n\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5\n\n\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr = Int8Array.of( 1, 2 )\n [ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int8Array.BYTES_PER_ELEMENT\n 1","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int8Array.name\n 'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.buffer\n ","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteLength\n 5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.byteOffset\n 0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int8Array( 5 );\n > arr.length\n 5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Int8Vector":"\nInt8Vector( [options] )\n Returns a one-dimensional signed 8-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int8Vector()\n \n\n\nInt8Vector( length[, options] )\n Returns a one-dimensional signed 8-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int8Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nInt8Vector( obj[, options] )\n Creates a one-dimensional signed 8-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Int8Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nInt8Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional signed 8-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int8Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n\n The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n Examples\n --------\n > INT16_MAX\n 32767\n\n See Also\n --------\n INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n\n The minimum signed 16-bit integer is given by `-(2^15)`.\n\n Examples\n --------\n > INT16_MIN\n -32768\n\n See Also\n --------\n INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n\n Examples\n --------\n > INT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array()\n \n\n\nInt16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Int16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'\n\n\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n \n\n\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10\n\n\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr = Int16Array.of( 1, 2 )\n [ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int16Array.BYTES_PER_ELEMENT\n 2","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int16Array.name\n 'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.buffer\n ","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteLength\n 10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.byteOffset\n 0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int16Array( 5 );\n > arr.length\n 5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Int16Vector":"\nInt16Vector( [options] )\n Returns a one-dimensional signed 16-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int16Vector()\n \n\n\nInt16Vector( length[, options] )\n Returns a one-dimensional signed 16-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int16Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nInt16Vector( obj[, options] )\n Creates a one-dimensional signed 16-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Int16Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nInt16Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional signed 16-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int16Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int8Vector, Int32Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n\n The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n Examples\n --------\n > INT32_MAX\n 2147483647\n\n See Also\n --------\n INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n\n The minimum signed 32-bit integer is given by `-(2^31)`.\n\n Examples\n --------\n > INT32_MIN\n -2147483648\n\n See Also\n --------\n INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n\n Examples\n --------\n > INT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array()\n \n\n\nInt32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Int32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Int32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'\n\n\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n \n\n\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20\n\n\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr = Int32Array.of( 1, 2 )\n [ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Int32Array.BYTES_PER_ELEMENT\n 4","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Int32Array.name\n 'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.buffer\n ","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteLength\n 20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.byteOffset\n 0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Int32Array( 5 );\n > arr.length\n 5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Int32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Int32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Int32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Int32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","Int32Matrix":"\nInt32Matrix( [options] )\n Returns a two-dimensional 32-bit signed integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix()\n \n\n\nInt32Matrix( shape[, options] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix( [ 2, 2 ] )\n \n\n\nInt32Matrix( M, N[, options] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Matrix( 2, 2 )\n \n\n\nInt32Matrix( obj[, options] )\n Creates a two-dimensional 32-bit signed integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1, 2 ], [ 3, 4 ] ];\n > var arr = Int32Matrix( v )\n \n\n\nInt32Matrix( buffer[, byteOffset[, shape]][, options] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Matrix( buf, 0, [ 8, 1 ] )\n \n\n\nInt32Matrix( buffer[, byteOffset[, M, N]][, options] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Matrix( buf, 0, 8, 1 )\n \n\n See Also\n --------\n Float64Matrix, Float32Matrix, Complex128Matrix, Complex64Matrix, matrix, Int32Vector, ndarray\n","Int32Vector":"\nInt32Vector( [options] )\n Returns a one-dimensional signed 32-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Vector()\n \n\n\nInt32Vector( length[, options] )\n Returns a one-dimensional signed 32-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Int32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nInt32Vector( obj[, options] )\n Creates a one-dimensional signed 32-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Int32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nInt32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional signed 32-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Int32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int8Vector, Uint8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, Int32Matrix, ndarray\n","Int64":"\nInt64( value )\n 64-bit signed integer constructor.\n\n Parameters\n ----------\n value: integer|bigint\n Integer value.\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > x.toString()\n '5'\n\n\nInt64.name\n Constructor name.\n\n Examples\n --------\n > var str = Int64.name\n 'Int64'\n\n\nInt64.from( words )\n Creates a new 64-bit signed integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.from( [ 1234, 5678 ] )\n \n\n\nInt64.of( high, low )\n Creates a new 64-bit signed integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.of( 1234, 5678 )\n \n\n\nInt64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Int64.BYTES_PER_ELEMENT\n 8\n\n\nInt64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8\n\n\nInt64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.byteLength\n 8\n\n\nInt64.prototype.hi\n Returns the high 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234\n\n\nInt64.prototype.lo\n Returns the low 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Uint64\n","Int64.name":"\nInt64.name\n Constructor name.\n\n Examples\n --------\n > var str = Int64.name\n 'Int64'","Int64.from":"\nInt64.from( words )\n Creates a new 64-bit signed integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.from( [ 1234, 5678 ] )\n ","Int64.of":"\nInt64.of( high, low )\n Creates a new 64-bit signed integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Int64\n 64-bit signed integer.\n\n Examples\n --------\n > var v = Int64.of( 1234, 5678 )\n ","Int64.BYTES_PER_ELEMENT":"\nInt64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Int64.BYTES_PER_ELEMENT\n 8","Int64.prototype.BYTES_PER_ELEMENT":"\nInt64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8","Int64.prototype.byteLength":"\nInt64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Int64( 5 )\n \n > var s = x.byteLength\n 8","Int64.prototype.hi":"\nInt64.prototype.hi\n Returns the high 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234","Int64.prototype.lo":"\nInt64.prototype.lo\n Returns the low 32-bit word of a 64-bit signed integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Int64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Uint64","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n\n Examples\n --------\n > IS_BIG_ENDIAN\n \n\n See Also\n --------\n IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n\n Examples\n --------\n > IS_BROWSER\n \n\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n\n Examples\n --------\n > IS_DARWIN\n \n\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n\n Examples\n --------\n > IS_DOCKER\n \n\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n\n Examples\n --------\n > IS_ELECTRON\n \n\n See Also\n --------\n IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n\n Examples\n --------\n > IS_ELECTRON_MAIN\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n\n Examples\n --------\n > IS_ELECTRON_RENDERER\n \n\n See Also\n --------\n IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n\n Examples\n --------\n > IS_LITTLE_ENDIAN\n \n\n See Also\n --------\n IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n\n Examples\n --------\n > IS_MOBILE\n \n\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n\n Examples\n --------\n > IS_NODE\n \n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n\n Examples\n --------\n > IS_TOUCH_DEVICE\n \n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n\n Examples\n --------\n > IS_WEB_WORKER\n \n\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n\n Examples\n --------\n > IS_WINDOWS\n \n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n Tests whether a value is an absolute HTTP(S) URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n Examples\n --------\n > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n true\n > bool = isAbsoluteHttpURI( 'example.com' )\n false\n > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n Tests if a value is an absolute path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an absolute path.\n\n Examples\n --------\n // Windows environment:\n > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n\n // POSIX environment:\n > bool = isAbsolutePath( '/foo/bar/baz' )\n true\n\n\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false\n\n\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n Tests if a value is a POSIX absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a POSIX absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n true\n > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n Tests if a value is a Windows absolute path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a Windows absolute path.\n\n Examples\n --------\n > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n Tests whether a value is an absolute URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is an absolute URI.\n\n Examples\n --------\n > var bool = isAbsoluteURI( 'http://example.com/' )\n true\n > bool = isAbsoluteURI( 'example.com' )\n false\n > bool = isAbsoluteURI( 'foo@bar.com' )\n false\n\n See Also\n --------\n isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n\n An accessor array is defined as an array, typed array, or an array-like\n object (excluding strings and functions) having `get` and `set` methods for\n accessing array elements.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an accessor array.\n\n Examples\n --------\n > var bool = isAccessorArray( new Complex64Array( 10 ) )\n true\n > bool = isAccessorArray( [] )\n false\n > bool = isAccessorArray( { 'length': 0 } )\n false\n > bool = isAccessorArray( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n Tests if an object's own property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has an accessor\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorProperty( obj, 'boop' )\n false\n > bool = isAccessorProperty( obj, 'beep' )\n true\n\n See Also\n --------\n hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n Tests if an object's own or inherited property has an accessor descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has an\n accessor descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isAccessorPropertyIn( obj, 'boop' )\n false\n > bool = isAccessorPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n\n The function first checks that an input value is a string before validating\n that the value is an alphagram. For non-string values, the function returns\n `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an alphagram.\n\n Examples\n --------\n > var out = isAlphagram( 'beep' )\n true\n > out = isAlphagram( 'zba' )\n false\n > out = isAlphagram( '' )\n false\n\n See Also\n --------\n isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n Tests whether a string contains only alphanumeric characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only alphanumeric\n characters.\n\n Examples\n --------\n > var bool = isAlphaNumeric( 'abc0123456789' )\n true\n > bool = isAlphaNumeric( 'abcdef' )\n true\n > bool = isAlphaNumeric( '0xff' )\n true\n > bool = isAlphaNumeric( '' )\n false\n\n See Also\n --------\n isDigitString\n","isAnagram":"\nisAnagram( str, value )\n Tests if a value is an anagram.\n\n Parameters\n ----------\n str: string\n Comparison string.\n\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an anagram.\n\n Examples\n --------\n > var str1 = 'I am a weakish speller';\n > var str2 = 'William Shakespeare';\n > var bool = isAnagram( str1, str2 )\n true\n > bool = isAnagram( 'bat', 'tabba' )\n false\n\n See Also\n --------\n isAlphagram\n","isArguments":"\nisArguments( value )\n Tests if a value is an arguments object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arguments object.\n\n Examples\n --------\n > function foo() { return arguments; };\n > var bool = isArguments( foo() )\n true\n > bool = isArguments( [] )\n false\n\n","isArray":"\nisArray( value )\n Tests if a value is an array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array.\n\n Examples\n --------\n > var bool = isArray( [] )\n true\n > bool = isArray( {} )\n false\n\n See Also\n --------\n isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n Tests if a value is an array of arrays.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of arrays.\n\n Examples\n --------\n > var bool = isArrayArray( [ [], [] ] )\n true\n > bool = isArrayArray( [ {}, {} ] )\n false\n > bool = isArrayArray( [] )\n false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n Tests if a value is an ArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an ArrayBuffer.\n\n Examples\n --------\n > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n true\n > bool = isArrayBuffer( [] )\n false\n\n See Also\n --------\n isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n Tests if a value is a `ArrayBuffer` view.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `ArrayBuffer` view.\n\n Examples\n --------\n > var bool = isArrayBufferView( new Int8Array() )\n true\n > bool = isArrayBufferView( [] )\n false\n\n See Also\n --------\n isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n Tests if a value is a valid array length.\n\n A valid length property for an Array instance is any integer value on the\n interval [0, 2^32-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a valid array length.\n\n Examples\n --------\n > var bool = isArrayLength( 5 )\n true\n > bool = isArrayLength( 2.0e200 )\n false\n > bool = isArrayLength( -3.14 )\n false\n > bool = isArrayLength( null )\n false\n\n See Also\n --------\n isArray\n","isArrayLike":"\nisArrayLike( value )\n Tests if a value is array-like.\n\n If provided a string, the function returns `true`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is array-like.\n\n Examples\n --------\n > var bool = isArrayLike( [] )\n true\n > bool = isArrayLike( { 'length': 10 } )\n true\n > bool = isArrayLike( 'beep' )\n true\n > bool = isArrayLike( null )\n false\n\n See Also\n --------\n isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n Tests if a value is an array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object.\n\n Examples\n --------\n > var bool = isArrayLikeObject( [] )\n true\n > bool = isArrayLikeObject( { 'length': 10 } )\n true\n > bool = isArrayLikeObject( 'beep' )\n false\n\n See Also\n --------\n isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n Tests if a value is an arrow function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an arrow function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isArrowFunction( beep )\n false\n > bool = isArrowFunction( {} )\n false\n\n","isASCII":"\nisASCII( str )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string has all ASCII characters.\n\n Examples\n --------\n > var str = 'beep boop';\n > var bool = isASCII( str )\n true\n > bool = isASCII( fromCodePoint( 130 ) )\n false\n\n See Also\n --------\n isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n Tests if a value is between two values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is between two values.\n\n Examples\n --------\n > var bool = isBetween( 3.14, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.0, 4.0 )\n true\n > bool = isBetween( 4.0, 3.0, 4.0 )\n true\n > bool = isBetween( 3.0, 3.14, 4.0 )\n false\n > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n false\n > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n Tests if a value is an array-like object where every element is between two\n values.\n\n Parameters\n ----------\n value: any\n Input value.\n\n a: any\n Left comparison value.\n\n b: any\n Right comparison value.\n\n left: string (optional)\n Indicates whether the left comparison value is inclusive. Must be either\n 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n right: string (optional)\n Indicates whether the right comparison value is inclusive. Must be\n either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object where every\n element is between two values.\n\n Examples\n --------\n > var arr = [ 3.0, 3.14, 4.0 ];\n > var bool = isBetweenArray( arr, 3.0, 4.0 )\n true\n > bool = isBetweenArray( arr, 3.14, 4.0 )\n false\n > bool = isBetweenArray( arr, 3.0, 3.14 )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n false\n > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n false\n\n See Also\n --------\n isBetween\n","isBigInt":"\nisBigInt( value )\n Tests if a value is a BigInt.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a BigInt.\n\n Examples\n --------\n > var bool = isBigInt( BigInt( '1' ) )\n true\n > bool = isBigInt( Object( BigInt( '1' ) ) )\n true\n > bool = isBigInt( {} )\n false\n > bool = isBigInt( null )\n false\n > bool = isBigInt( true )\n false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n Tests if a value is a BigInt64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigInt64Array.\n\n Examples\n --------\n > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n true\n > bool = isBigInt64Array( [] )\n false\n\n See Also\n --------\n isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n Tests if a value is a BigUint64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a BigUint64Array.\n\n Examples\n --------\n > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n true\n > bool = isBigUint64Array( [] )\n false\n\n See Also\n --------\n isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n Tests if a value is a binary string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a binary string.\n\n Examples\n --------\n > var bool = isBinaryString( '1000101' )\n true\n > bool = isBinaryString( 'beep' )\n false\n > bool = isBinaryString( '' )\n false\n\n See Also\n --------\n isString\n","isBlankString":"\nisBlankString( value )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a blank string.\n\n Examples\n --------\n > var bool = isBlankString( ' ' )\n true\n > bool = isBlankString( 'beep' )\n false\n > bool = isBlankString( null )\n false\n\n See Also\n --------\n isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n Tests if a value is a boolean.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean.\n\n Examples\n --------\n > var bool = isBoolean( false )\n true\n > bool = isBoolean( new Boolean( false ) )\n true\n\n\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false\n\n\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n Tests if a value is a boolean primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean primitive.\n\n Examples\n --------\n > var bool = isBoolean.isPrimitive( true )\n true\n > bool = isBoolean.isPrimitive( false )\n true\n > bool = isBoolean.isPrimitive( new Boolean( true ) )\n false","isBoolean.isObject":"\nisBoolean.isObject( value )\n Tests if a value is a boolean object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a boolean object.\n\n Examples\n --------\n > var bool = isBoolean.isObject( true )\n false\n > bool = isBoolean.isObject( new Boolean( false ) )\n true","isBooleanArray":"\nisBooleanArray( value )\n Tests if a value is an array-like object of booleans.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object of booleans.\n\n Examples\n --------\n > var bool = isBooleanArray( [ true, false, true ] )\n true\n > bool = isBooleanArray( [ true, 'abc', false ] )\n false\n\n\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false\n\n\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n Tests if a value is an array-like object containing only boolean primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n boolean primitives.\n\n Examples\n --------\n > var bool = isBooleanArray.primitives( [ true, false ] )\n true\n > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n Tests if a value is an array-like object containing only Boolean objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n Boolean objects.\n\n Examples\n --------\n > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n false\n > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n Tests if a value is a JavaScript boxed primitive.\n\n Boxed primitive objects can be created with one of the following:\n\n - new Boolean()\n - new Number()\n - new String()\n - Object( Symbol() ) (ES6/ES2015)\n - Object( BigInt() ) (ES11/ES2020)\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a JavaScript boxed primitive.\n\n Examples\n --------\n > var bool = isBoxedPrimitive( new Boolean( false ) )\n true\n > bool = isBoxedPrimitive( true )\n false\n\n See Also\n --------\n isPrimitive\n","isBuffer":"\nisBuffer( value )\n Tests if a value is a Buffer instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Buffer instance.\n\n Examples\n --------\n > var bool = isBuffer( new Buffer( 'beep' ) )\n true\n > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n true\n > bool = isBuffer( {} )\n false\n > bool = isBuffer( [] )\n false\n\n","isCamelcase":"\nisCamelcase( value )\n Tests if a value is a camelcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a camelcase string.\n\n Examples\n --------\n > var bool = isCamelcase( 'helloWorld' )\n true\n > bool = isCamelcase( 'hello world' )\n false\n\n See Also\n --------\n isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n Tests if a value is a string having an uppercase first character.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string with an uppercase first\n character.\n\n Examples\n --------\n > var bool = isCapitalized( 'Hello' )\n true\n > bool = isCapitalized( 'world' )\n false\n\n See Also\n --------\n isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n Tests if a value is a matrix which is symmetric about its center.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, 1, 2 ];\n > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n > var bool = isCentrosymmetricMatrix( M )\n true\n > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isCentrosymmetricMatrix( 3.14 )\n false\n > bool = isCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n Tests if an object-like value contains a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an object-like value contains a circular\n reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircular( obj )\n true\n > bool = isCircular( {} )\n false\n > bool = isCircular( null )\n false\n\n See Also\n --------\n isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n Tests if a value is an array containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing a\n circular reference.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > arr.push( arr );\n > var bool = isCircularArray( arr )\n true\n > bool = isCircularArray( [] )\n false\n > bool = isCircularArray( null )\n false\n\n See Also\n --------\n isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n Tests if a value is a plain object containing a circular reference.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object containing a\n circular reference.\n\n Examples\n --------\n > var obj = { 'beep': 'boop' };\n > obj.self = obj;\n > var bool = isCircularPlainObject( obj )\n true\n > bool = isCircularPlainObject( {} )\n false\n > bool = isCircularPlainObject( null )\n false\n\n See Also\n --------\n isCircular, isCircularArray\n","isClass":"\nisClass( value )\n Tests if a value is a class.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a class.\n\n Examples\n --------\n > var bool = isClass( class Person {} )\n true\n > bool = isClass( function Person() {} )\n false\n > bool = isClass( {} )\n false\n > bool = isClass( null )\n false\n > bool = isClass( true )\n false\n","isCollection":"\nisCollection( value )\n Tests if a value is a collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a collection.\n\n Examples\n --------\n > var bool = isCollection( [] )\n true\n > bool = isCollection( { 'length': 0 } )\n true\n > bool = isCollection( {} )\n false\n\n See Also\n --------\n isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n Tests if a value is a 64-bit or 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit or 128-bit complex\n number.\n\n Examples\n --------\n > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex( 3.14 )\n false\n > bool = isComplex( {} )\n false\n\n See Also\n --------\n isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n Tests if a value is a 64-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 64-bit complex number.\n\n Examples\n --------\n > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n false\n > bool = isComplex64( 3.14 )\n false\n > bool = isComplex64( {} )\n false\n\n See Also\n --------\n isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n Tests if a value is a Complex64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex64Array.\n\n Examples\n --------\n > var bool = isComplex64Array( new Complex64Array( 10 ) )\n true\n > bool = isComplex64Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64MatrixLike( M )\n true\n > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64MatrixLike( 3.14 )\n false\n > bool = isComplex64MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64ndarrayLike( M )\n true\n > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64ndarrayLike( 3.14 )\n false\n > bool = isComplex64ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision complex floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'complex64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isComplex64VectorLike( M )\n true\n > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex64VectorLike( 3.14 )\n false\n > bool = isComplex64VectorLike( {} )\n false\n\n See Also\n --------\n isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n Tests if a value is a 128-bit complex number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 128-bit complex number.\n\n Examples\n --------\n > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n false\n > bool = isComplex128( 3.14 )\n false\n > bool = isComplex128( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n Tests if a value is a Complex128Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Complex128Array.\n\n Examples\n --------\n > var bool = isComplex128Array( new Complex128Array( 10 ) )\n true\n > bool = isComplex128Array( [] )\n false\n\n See Also\n --------\n isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var opts = { 'dtype': 'complex128' };\n > var M = ndzeros( [ 2, 2 ], opts );\n > var bool = isComplex128MatrixLike( M )\n true\n > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128MatrixLike( 3.14 )\n false\n > bool = isComplex128MatrixLike( {} )\n false\n\n See Also\n --------\n isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision complex floating-point numbers.\n\n Examples\n --------\n > var opts = { 'dtype': 'complex128' };\n > var M = ndzeros( [ 2, 2 ], opts );\n > var bool = isComplex128ndarrayLike( M )\n true\n > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128ndarrayLike( 3.14 )\n false\n > bool = isComplex128ndarrayLike( {} )\n false\n\n See Also\n --------\n isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision complex floating-point numbers.\n\n Examples\n --------\n > var opts = { 'dtype': 'complex128' };\n > var M = ndzeros( [ 4 ], opts );\n > var bool = isComplex128VectorLike( M )\n true\n > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isComplex128VectorLike( 3.14 )\n false\n > bool = isComplex128VectorLike( {} )\n false\n\n See Also\n --------\n isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n Tests if a value is a complex number-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a complex number-like object.\n\n Examples\n --------\n > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n true\n > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n true\n > bool = isComplexLike( 3.14 )\n false\n > bool = isComplexLike( {} )\n false\n\n See Also\n --------\n isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n Tests if a value is a complex typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a complex typed array.\n\n Examples\n --------\n > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n true\n\n See Also\n --------\n isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n Tests if a value is complex-typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is complex-typed-array-like.\n\n Examples\n --------\n > var bool = isComplexTypedArrayLike( new Complex128Array() )\n true\n > bool = isComplexTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4,\n ... 'get': function get() {},\n ... 'set': function set() {}\n ... })\n true\n\n See Also\n --------\n isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n Tests if a value is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a composite number.\n\n Examples\n --------\n > var bool = isComposite( 4.0 )\n true\n > bool = isComposite( new Number( 4.0 ) )\n true\n > bool = isComposite( 3.14 )\n false\n > bool = isComposite( -4.0 )\n false\n > bool = isComposite( null )\n false\n\n\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n Tests if a value is a number primitive which is a composite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n composite number.\n\n Examples\n --------\n > var bool = isComposite.isPrimitive( 4.0 )\n true\n > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n false","isComposite.isObject":"\nisComposite.isObject( value )\n Tests if a value is a number object having a value which is a composite\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a composite number.\n\n Examples\n --------\n > var bool = isComposite.isObject( 4.0 )\n false\n > bool = isComposite.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n Tests if an object's own property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurableProperty( obj, 'boop' )\n true\n > bool = isConfigurableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is configurable.\n\n A property is configurable if the property may be deleted or its descriptor\n may be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isConfigurablePropertyIn( obj, 'boop' )\n true\n > bool = isConfigurablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n Tests if a value is a constantcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a constantcase string.\n\n Examples\n --------\n > var bool = isConstantcase( 'BEEP_BOOP' )\n true\n > bool = isConstantcase( 'BEEP and BOOP' )\n false\n\n See Also\n --------\n isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n Tests if a value is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber( 8.0 )\n true\n > bool = isCubeNumber( new Number( 8.0 ) )\n true\n > bool = isCubeNumber( 3.14 )\n false\n > bool = isCubeNumber( -5.0 )\n false\n > bool = isCubeNumber( null )\n false\n\n\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false\n\n\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a cube\n number.\n\n Examples\n --------\n > var bool = isCubeNumber.isPrimitive( 8.0 )\n true\n > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n Tests if a value is a number object having a value which is a cube number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a cube number.\n\n Examples\n --------\n > var bool = isCubeNumber.isObject( 8.0 )\n false\n > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n Tests if a value is the current year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is the current year.\n\n Examples\n --------\n > var bool = isCurrentYear( new Date() )\n true\n > bool = isCurrentYear( currentYear() )\n true\n > bool = isCurrentYear( 2021 )\n false\n > bool = isCurrentYear( null )\n false\n\n","isDataProperty":"\nisDataProperty( value, property )\n Tests if an object's own property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property has a data descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataProperty( obj, 'boop' )\n true\n > bool = isDataProperty( obj, 'beep' )\n false\n\n See Also\n --------\n hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n Tests if an object's own or inherited property has a data descriptor.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property has a data\n descriptor.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.get = function getter() { return 'beep'; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isDataPropertyIn( obj, 'boop' )\n true\n > bool = isDataPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n Tests if a value is a DataView.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a DataView.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 10 );\n > var bool = isDataView( new DataView( buf ) )\n true\n > bool = isDataView( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n Tests if a value is a Date object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Date object.\n\n Examples\n --------\n > var bool = isDateObject( new Date() )\n true\n > bool = isDateObject( '2017-01-01' )\n false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n Tests if a value is an array-like object containing only Date objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is an array-like object containing only Date\n objects.\n\n Examples\n --------\n > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n true\n > bool = isDateObjectArray( [ {}, {} ] )\n false\n > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n false\n > bool = isDateObjectArray( [] )\n false\n\n See Also\n --------\n isDateObject\n","isDigitString":"\nisDigitString( str )\n Tests whether a string contains only numeric digits.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only numeric digits.\n\n Examples\n --------\n > var bool = isDigitString( '0123456789' )\n true\n > bool = isDigitString( 'abcdef' )\n false\n > bool = isDigitString( '0xff' )\n false\n > bool = isDigitString( '' )\n false\n\n See Also\n --------\n isHexString, isString\n","isDomainName":"\nisDomainName( value )\n Tests if a value is a domain name.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a domain name.\n\n Examples\n --------\n > var bool = isDomainName( 'example.com' )\n true\n > bool = isDomainName( 'foo@bar.com' )\n false\n","isDurationString":"\nisDurationString( value )\n Tests if a value is a duration string.\n\n The function validates that a value is a string. For all other types, the\n function returns `false`.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a duration string.\n\n Examples\n --------\n > var bool = isDurationString( '1d' )\n true\n > bool = isDurationString( '1h' )\n true\n > bool = isDurationString( 'beep' )\n false\n","isEmailAddress":"\nisEmailAddress( value )\n Tests if a value is an email address.\n\n Validation is not rigorous. *9* RFCs relate to email addresses, and\n accounting for all of them is a fool's errand. The function performs the\n simplest validation; i.e., requiring at least one `@` symbol.\n\n For rigorous validation, send a confirmation email. If the email bounces,\n consider the email invalid.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an email address.\n\n Examples\n --------\n > var bool = isEmailAddress( 'beep@boop.com' )\n true\n > bool = isEmailAddress( 'beep' )\n false\n > bool = isEmailAddress( null )\n false\n\n","isEmptyArray":"\nisEmptyArray( value )\n Tests if a value is an empty array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty array.\n\n Examples\n --------\n > var bool = isEmptyArray( [] )\n true\n > bool = isEmptyArray( [ 1, 2, 3 ] )\n false\n > bool = isEmptyArray( {} )\n false\n\n See Also\n --------\n isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n Tests if a value is an empty array-like object.\n\n If provided a string, the function returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an empty array-like object.\n\n Examples\n --------\n > var bool = isEmptyArrayLikeObject( [] )\n true\n > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n true\n > bool = isEmptyArrayLikeObject( '' )\n false\n\n See Also\n --------\n isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n Tests if a value is an empty collection.\n\n A collection is defined as an array, typed array, or an array-like object\n (excluding strings and functions).\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty collection.\n\n Examples\n --------\n > var bool = isEmptyCollection( [] )\n true\n > bool = isEmptyCollection( { 'length': 0 } )\n true\n > bool = isEmptyCollection( [ 1, 2, 3 ] )\n false\n > bool = isEmptyCollection( {} )\n false\n\n See Also\n --------\n isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n Tests if a value is an empty object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty object.\n\n Examples\n --------\n > var bool = isEmptyObject( {} )\n true\n > bool = isEmptyObject( { 'beep': 'boop' } )\n false\n > bool = isEmptyObject( [] )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n Tests if a value is an empty string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is an empty string.\n\n Examples\n --------\n > var bool = isEmptyString( '' )\n true\n > bool = isEmptyString( new String( '' ) )\n true\n > bool = isEmptyString( 'beep' )\n false\n > bool = isEmptyString( [] )\n false\n\n\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false\n\n\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n Tests if a value is an empty string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty string primitive.\n\n Examples\n --------\n > var bool = isEmptyString.isPrimitive( '' )\n true\n > bool = isEmptyString.isPrimitive( new String( '' ) )\n false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n Tests if a value is an empty `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an empty `String` object.\n\n Examples\n --------\n > var bool = isEmptyString.isObject( new String( '' ) )\n true\n > bool = isEmptyString.isObject( '' )\n false\n\n See Also\n --------\n isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n Tests if an object's own property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is enumerable.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isEnumerableProperty( beep, 'boop' )\n true\n > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n false\n\n See Also\n --------\n isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isEnumerablePropertyIn( obj, 'boop' )\n true\n > bool = isEnumerablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n Tests if two arguments are both generic arrays and have equal values.\n\n The function performs strict equality comparison; thus, the function treats\n `-0` and `+0` as equal and `NaNs` as distinct.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are equal.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isEqualArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isEqualArray( x, y )\n false\n\n See Also\n --------\n isArray, isSameArray\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n\n Parameters\n ----------\n d1: any\n First input value.\n d2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether both values are Date objects corresponding to\n the same date and time.\n\n Examples\n --------\n > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > var bool = isEqualDateObject( d1, d2 )\n true\n > d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n > d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n > bool = isEqualDateObject( d1, d2 )\n false\n\n See Also\n --------\n isDateObject, isSameValue\n","isError":"\nisError( value )\n Tests if a value is an Error object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Error object.\n\n Examples\n --------\n > var bool = isError( new Error( 'beep' ) )\n true\n > bool = isError( {} )\n false\n\n","isEvalError":"\nisEvalError( value )\n Tests if a value is an EvalError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided an EvalError (or a descendant) object,\n false positives may occur due to the fact that the EvalError constructor\n inherits from Error and has no internal class of its own. Hence, EvalError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an EvalError object.\n\n Examples\n --------\n > var bool = isEvalError( new EvalError( 'beep' ) )\n true\n > bool = isEvalError( {} )\n false\n\n See Also\n --------\n isError\n","isEven":"\nisEven( value )\n Tests if a value is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an even number.\n\n Examples\n --------\n > var bool = isEven( 4.0 )\n true\n > bool = isEven( new Number( 4.0 ) )\n true\n > bool = isEven( 3.0 )\n false\n > bool = isEven( -3.14 )\n false\n > bool = isEven( null )\n false\n\n\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false\n\n\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n Tests if a value is a number primitive that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isPrimitive( -4.0 )\n true\n > bool = isEven.isPrimitive( new Number( -4.0 ) )\n false","isEven.isObject":"\nisEven.isObject( value )\n Tests if a value is a number object that is an even number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that is an even\n number.\n\n Examples\n --------\n > var bool = isEven.isObject( 4.0 )\n false\n > bool = isEven.isObject( new Number( 4.0 ) )\n true\n\n See Also\n --------\n isOdd","isFalsy":"\nisFalsy( value )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is falsy.\n\n Examples\n --------\n > var bool = isFalsy( false )\n true\n > bool = isFalsy( '' )\n true\n > bool = isFalsy( 0 )\n true\n > bool = isFalsy( null )\n true\n > bool = isFalsy( void 0 )\n true\n > bool = isFalsy( NaN )\n true\n > bool = isFalsy( {} )\n false\n > bool = isFalsy( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n Tests if a value is an array-like object containing only falsy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only falsy values.\n\n Examples\n --------\n > var bool = isFalsyArray( [ null, '' ] )\n true\n > bool = isFalsyArray( [ {}, [] ] )\n false\n > bool = isFalsyArray( [] )\n false\n\n See Also\n --------\n isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n Tests if a value is a finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite number.\n\n Examples\n --------\n > var bool = isFinite( 5.0 )\n true\n > bool = isFinite( new Number( 5.0 ) )\n true\n > bool = isFinite( 1.0/0.0 )\n false\n > bool = isFinite( null )\n false\n\n\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isPrimitive( -3.0 )\n true\n > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n false","isFinite.isObject":"\nisFinite.isObject( value )\n Tests if a value is a number object having a finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n value.\n\n Examples\n --------\n > var bool = isFinite.isObject( 3.0 )\n false\n > bool = isFinite.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n Tests if a value is an array-like object of finite numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of finite\n numbers.\n\n Examples\n --------\n > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n false\n\n\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive finite numbers.\n\n Examples\n --------\n > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having finite values.\n\n Examples\n --------\n > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n Tests if a value is a Float32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float32Array.\n\n Examples\n --------\n > var bool = isFloat32Array( new Float32Array( 10 ) )\n true\n > bool = isFloat32Array( [] )\n false\n\n See Also\n --------\n isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32MatrixLike( M )\n true\n > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32MatrixLike( 3.14 )\n false\n > bool = isFloat32MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32ndarrayLike( M )\n true\n > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32ndarrayLike( 3.14 )\n false\n > bool = isFloat32ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing single-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float32';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat32VectorLike( M )\n true\n > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat32VectorLike( 3.14 )\n false\n > bool = isFloat32VectorLike( {} )\n false\n\n See Also\n --------\n isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n Tests if a value is a Float64Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Float64Array.\n\n Examples\n --------\n > var bool = isFloat64Array( new Float64Array( 10 ) )\n true\n > bool = isFloat64Array( [] )\n false\n\n See Also\n --------\n isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64MatrixLike( M )\n true\n > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64MatrixLike( 3.14 )\n false\n > bool = isFloat64MatrixLike( {} )\n false\n\n See Also\n --------\n isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object containing\n double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64ndarrayLike( M )\n true\n > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64ndarrayLike( 3.14 )\n false\n > bool = isFloat64ndarrayLike( {} )\n false\n\n See Also\n --------\n isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object containing double-precision floating-point numbers.\n\n Examples\n --------\n > var M = {};\n > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'float64';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isFloat64VectorLike( M )\n true\n > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isFloat64VectorLike( 3.14 )\n false\n > bool = isFloat64VectorLike( {} )\n false\n\n See Also\n --------\n isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n Tests if a value is a function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a function.\n\n Examples\n --------\n > function beep() {};\n > var bool = isFunction( beep )\n true\n > bool = isFunction( {} )\n false\n\n","isFunctionArray":"\nisFunctionArray( value )\n Tests if a value is an array-like object containing only functions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n functions.\n\n Examples\n --------\n > function beep() {};\n > function boop() {};\n > var bool = isFunctionArray( [ beep, boop ] )\n true\n > bool = isFunctionArray( [ {}, beep ] )\n false\n > bool = isFunctionArray( [] )\n false\n\n See Also\n --------\n isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n Tests if a value is a generator object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a generator object.\n\n Examples\n --------\n > function* generateID() {\n ... var idx = 0;\n ... while ( idx < idx+1 ) {\n ... yield idx;\n ... idx += 1;\n ... }\n ... };\n > var bool = isGeneratorObject( generateID() )\n true\n > bool = isGeneratorObject( generateID )\n false\n > bool = isGeneratorObject( {} )\n false\n > bool = isGeneratorObject( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n Tests if a value is generator object-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is generator object-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {},\n ... 'return': function noop() {},\n ... 'throw': function noop() {}\n ... };\n > var bool = isGeneratorObjectLike( obj )\n true\n > bool = isGeneratorObjectLike( {} )\n false\n > bool = isGeneratorObjectLike( null )\n false\n\n See Also\n --------\n hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n Tests if a value is a gzip buffer.\n\n A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n contains a 10-byte header, a body containing the compressed payload, and an\n 8-byte footer containing a CRC-32 checksum and the length of the original\n uncompressed data, modulo 2^32.\n\n This function only examines the 10-byte header to ensure the header includes\n the expected magic number and compression method. The function does not\n perform an integrity check.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a gzip buffer.\n\n Examples\n --------\n > var buf = new Uint8Array( 20 );\n > buf[ 0 ] = 31; // 0x1f => magic number\n > buf[ 1 ] = 139; // 0x8b\n > buf[ 2 ] = 8; // 0x08 => compression method\n > var bool = isgzipBuffer( buf )\n true\n > bool = isgzipBuffer( [] )\n false\n\n See Also\n --------\n isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n Tests whether a string contains only hexadecimal digits.\n\n The function does not recognize `x` (as in the standard `0x` prefix).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only hexadecimal digits.\n\n Examples\n --------\n > var bool = isHexString( '0123456789abcdefABCDEF' )\n true\n > bool = isHexString( '0xffffff' )\n false\n > bool = isHexString( 'x' )\n false\n > bool = isHexString( '' )\n false\n\n See Also\n --------\n isString\n","isInfinite":"\nisInfinite( value )\n Tests if a value is an infinite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an infinite number.\n\n Examples\n --------\n > var bool = isInfinite( 1.0/0.0 )\n true\n > bool = isInfinite( new Number( -1.0/0.0 ) )\n true\n > bool = isInfinite( 5.0 )\n false\n > bool = isInfinite( '1.0/0.0' )\n false\n\n\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n Tests if a value is a number primitive having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having an\n infinite value.\n\n Examples\n --------\n > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n true\n > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isInfinite.isObject":"\nisInfinite.isObject( value )\n Tests if a value is a number object having an infinite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having an infinite\n value.\n\n Examples\n --------\n > var bool = isInfinite.isObject( 1.0/0.0 )\n false\n > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n true\n\n See Also\n --------\n isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n Tests if an object has an inherited property.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has an inherited property.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isInheritedProperty( beep, 'boop' )\n false\n > bool = isInheritedProperty( beep, 'toString' )\n true\n > bool = isInheritedProperty( beep, 'bop' )\n false\n\n See Also\n --------\n hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n Tests if a value is an Int8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int8Array.\n\n Examples\n --------\n > var bool = isInt8Array( new Int8Array( 10 ) )\n true\n > bool = isInt8Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n Tests if a value is an Int16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int16Array.\n\n Examples\n --------\n > var bool = isInt16Array( new Int16Array( 10 ) )\n true\n > bool = isInt16Array( [] )\n false\n\n See Also\n --------\n isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n Tests if a value is an Int32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an Int32Array.\n\n Examples\n --------\n > var bool = isInt32Array( new Int32Array( 10 ) )\n true\n > bool = isInt32Array( [] )\n false\n\n See Also\n --------\n isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n Tests if a value is an integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an integer.\n\n Examples\n --------\n > var bool = isInteger( 5.0 )\n true\n > bool = isInteger( new Number( 5.0 ) )\n true\n > bool = isInteger( -3.14 )\n false\n > bool = isInteger( null )\n false\n\n\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n Tests if a value is a number primitive having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isPrimitive( -3.0 )\n true\n > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n false","isInteger.isObject":"\nisInteger.isObject( value )\n Tests if a value is a number object having an integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having an integer\n value.\n\n Examples\n --------\n > var bool = isInteger.isObject( 3.0 )\n false\n > bool = isInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isNumber","isIntegerArray":"\nisIntegerArray( value )\n Tests if a value is an array-like object of integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object of integer\n values.\n\n Examples\n --------\n > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n true\n > bool = isIntegerArray( [ -3.0, '3.0' ] )\n false\n\n\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive integer\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only primitive integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n true\n > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only number objects having integer values.\n\n Examples\n --------\n > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n true\n > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n false\n > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isIterableLike":"\nisIterableLike( value )\n Tests if a value is iterable-like.\n\n In order to be iterable, an object must implement the @@iterator method,\n which, when called, returns an iterator protocol-compliant object.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n In environments lacking Symbol.iterator support, this function always\n returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterable-like.\n\n Examples\n --------\n > var bool = isIterableLike( [ 1, 2, 3 ] )\n \n > bool = isIterableLike( {} )\n false\n > bool = isIterableLike( null )\n false\n\n See Also\n --------\n isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n Tests if a value is iterator-like.\n\n An iterator protocol-compliant object is an object having a `next` method\n which adheres to the iterator protocol.\n\n As full iterator compliance is impossible to achieve without evaluating an\n iterator, this function checks *only* for interface compliance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is iterator-like.\n\n Examples\n --------\n > var obj = {\n ... 'next': function noop() {}\n ... };\n > var bool = isIteratorLike( obj )\n true\n > bool = isIteratorLike( {} )\n false\n > bool = isIteratorLike( null )\n false\n\n See Also\n --------\n isIterableLike\n","isJSON":"\nisJSON( value )\n Tests if a value is a parseable JSON string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a parseable JSON string.\n\n Examples\n --------\n > var bool = isJSON( '{\"a\":5}' )\n true\n > bool = isJSON( '{a\":5}' )\n false\n\n","isKebabcase":"\nisKebabcase( value )\n Tests if a value is a string in kebab case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in kebab case.\n\n Examples\n --------\n > var bool = isKebabcase( 'beep-boop' )\n true\n > bool = isKebabcase( 'BEEP_BOOP' )\n false\n\n See Also\n --------\n isString","isLeapYear":"\nisLeapYear( value )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n A leap year is defined as any year which is exactly divisible by 4, except\n for years which are exactly divisible by 100 and not by 400. In this\n definition, 100 corresponds to years marking a new century, and 400\n corresponds to the length of the *leap cycle*.\n\n If not provided any arguments, the function returns a boolean indicating\n if the current year (according to local time) is a leap year.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value corresponds to a leap year.\n\n Examples\n --------\n > var bool = isLeapYear( new Date() )\n \n > bool = isLeapYear( 1996 )\n true\n > bool = isLeapYear( 2001 )\n false\n\n","isLocalhost":"\nisLocalhost( value )\n Tests whether a value is a localhost hostname.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a localhost hostname.\n\n Examples\n --------\n > var bool = isLocalhost( 'localhost' )\n true\n > bool = isLocalhost( '127.0.0.1' )\n true\n > bool = isLocalhost( 'stdlib.io' )\n false\n","isLowercase":"\nisLowercase( value )\n Tests if a value is a lowercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a lowercase string.\n\n Examples\n --------\n > var bool = isLowercase( 'hello' )\n true\n > bool = isLowercase( 'World' )\n false\n\n See Also\n --------\n isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n Tests if a value is a 2-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isMatrixLike( M )\n true\n > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isMatrixLike( 3.14 )\n false\n > bool = isMatrixLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n Tests if an object has a specified method name.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Property arguments are coerced to strings.\n\n The function only searches own properties.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': function beep() { return 'beep'; } };\n > var bool = isMethod( beep, 'boop' )\n true\n > bool = isMethod( beep, 'toString' )\n false\n\n See Also\n --------\n hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n Tests if an object has a specified method name, either own or inherited.\n\n Value arguments other than `null` or `undefined` are coerced to objects.\n\n Non-symbol property arguments are coerced to strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object has a specified method name.\n\n Examples\n --------\n > var beep = { 'boop': true };\n > var bool = isMethodIn( beep, 'toString' )\n true\n > bool = isMethodIn( beep, 'boop' )\n false\n > bool = isMethodIn( beep, 'bop' )\n false\n\n See Also\n --------\n hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n Tests if a value is a MultiSlice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a MultiSlice object.\n\n Examples\n --------\n > var bool = isMultiSlice( new MultiSlice() )\n true\n > bool = isMultiSlice( 3.14 )\n false\n > bool = isMultiSlice( {} )\n false\n\n See Also\n --------\n isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n Tests if a value is named typed tuple-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is named typed tuple-like.\n\n Examples\n --------\n > var Point = namedtypedtuple( [ 'x', 'y' ] );\n > var p = new Point();\n > var bool = isNamedTypedTupleLike( p )\n true\n > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isNamedTypedTupleLike( 3.14 )\n false\n > bool = isNamedTypedTupleLike( {} )\n false\n\n See Also\n --------\n namedtypedtuple\n","isnan":"\nisnan( value )\n Tests if a value is NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is NaN.\n\n Examples\n --------\n > var bool = isnan( NaN )\n true\n > bool = isnan( new Number( NaN ) )\n true\n > bool = isnan( 3.14 )\n false\n > bool = isnan( null )\n false\n\n\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false\n\n\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n Tests if a value is a NaN number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a NaN number primitive.\n\n Examples\n --------\n > var bool = isnan.isPrimitive( NaN )\n true\n > bool = isnan.isPrimitive( 3.14 )\n false\n > bool = isnan.isPrimitive( new Number( NaN ) )\n false","isnan.isObject":"\nisnan.isObject( value )\n Tests if a value is a number object having a value of NaN.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value of\n NaN.\n\n Examples\n --------\n > var bool = isnan.isObject( NaN )\n false\n > bool = isnan.isObject( new Number( NaN ) )\n true\n\n See Also\n --------\n isNumber","isNaNArray":"\nisNaNArray( value )\n Tests if a value is an array-like object containing only NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n NaN values.\n\n Examples\n --------\n > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n true\n > bool = isNaNArray( [ NaN, 2 ] )\n false\n\n\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true\n\n\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n false\n > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n true","isNaNArray.objects":"\nisNaNArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having NaN values.\n\n Examples\n --------\n > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n true\n > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n false\n > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n false\n\n See Also\n --------\n isnan","isNativeFunction":"\nisNativeFunction( value )\n Tests if a value is a native function.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a native function.\n\n Examples\n --------\n > var bool = isNativeFunction( Date )\n true\n > function beep() {};\n > bool = isNativeFunction( beep )\n false\n > bool = isNativeFunction( {} )\n false\n\n See Also\n --------\n isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n Tests if a value is ndarray-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is ndarray-like.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLike( M )\n true\n > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isndarrayLike( 3.14 )\n false\n > bool = isndarrayLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n Tests if a value is an ndarray-like object having a specified data type.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n dtype: any\n Data type value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an ndarray-like object having a\n specified data type.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 2;\n > M.shape = [ 2, 2 ];\n > M.strides = [ 2, 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isndarrayLikeWithDataType( M, 'generic' )\n true\n > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n false\n > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n false\n > bool = isndarrayLikeWithDataType( {}, 'generic' )\n false\n\n See Also\n --------\n isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n Tests if a value is a finite negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a finite negative number.\n\n Examples\n --------\n > var bool = isNegativeFinite( -5.0 )\n true\n > bool = isNegativeFinite( new Number( -5.0 ) )\n true\n > bool = isNegativeFinite( -3.14 )\n true\n > bool = isNegativeFinite( 5.0 )\n false\n > bool = isNegativeFinite( null )\n false\n > bool = isNegativeFinite( -1.0/0.0 )\n false\n > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false\n\n\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isPrimitive( -3.0 )\n true\n > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n false\n > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n Tests if a value is a number object having a finite negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a finite\n negative value.\n\n Examples\n --------\n > var bool = isNegativeFinite.isObject( -3.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n true\n > bool = isNegativeFinite.isObject( -1.0/0.0 )\n false\n > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n false\n\n See Also\n --------\n isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n Tests if a value is a negative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative integer.\n\n Examples\n --------\n > var bool = isNegativeInteger( -5.0 )\n true\n > bool = isNegativeInteger( new Number( -5.0 ) )\n true\n > bool = isNegativeInteger( 5.0 )\n false\n > bool = isNegativeInteger( -3.14 )\n false\n > bool = isNegativeInteger( null )\n false\n\n\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isPrimitive( -3.0 )\n true\n > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n Tests if a value is a number object having a negative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n integer value.\n\n Examples\n --------\n > var bool = isNegativeInteger.isObject( -3.0 )\n false\n > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only negative integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative integers.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative primitive integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative integer values.\n\n Examples\n --------\n > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeNumber":"\nisNegativeNumber( value )\n Tests if a value is a negative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a negative number.\n\n Examples\n --------\n > var bool = isNegativeNumber( -5.0 )\n true\n > bool = isNegativeNumber( new Number( -5.0 ) )\n true\n > bool = isNegativeNumber( -3.14 )\n true\n > bool = isNegativeNumber( 5.0 )\n false\n > bool = isNegativeNumber( null )\n false\n\n\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isPrimitive( -3.0 )\n true\n > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n Tests if a value is a number object having a negative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a negative\n value.\n\n Examples\n --------\n > var bool = isNegativeNumber.isObject( -3.0 )\n false\n > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n true\n\n See Also\n --------\n isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n Tests if a value is an array-like object containing only negative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive negative numbers.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n true\n > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having negative number values.\n\n Examples\n --------\n > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNegativeZero":"\nisNegativeZero( value )\n Tests if a value is negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero( -0.0 )\n true\n > bool = isNegativeZero( new Number( -0.0 ) )\n true\n > bool = isNegativeZero( -3.14 )\n false\n > bool = isNegativeZero( 0.0 )\n false\n > bool = isNegativeZero( null )\n false\n\n\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false\n\n\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n Tests if a value is a number primitive equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isPrimitive( -0.0 )\n true\n > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n Tests if a value is a number object having a value equal to negative zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to negative zero.\n\n Examples\n --------\n > var bool = isNegativeZero.isObject( -0.0 )\n false\n > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n true\n\n See Also\n --------\n isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n Tests whether a string matches a Node.js built-in module name.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string matches a Node.js built-in module\n name.\n\n Examples\n --------\n > var bool = isNodeBuiltin( 'cluster' )\n true\n > bool = isNodeBuiltin( 'crypto' )\n true\n > bool = isNodeBuiltin( 'fs-extra' )\n false\n > bool = isNodeBuiltin( '' )\n false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n Tests if a value is Node duplex stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node duplex stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Duplex;\n > s = new Stream();\n > var bool = isNodeDuplexStreamLike( s )\n true\n > bool = isNodeDuplexStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n Tests if a value is Node readable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node readable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Readable;\n > s = new Stream();\n > var bool = isNodeReadableStreamLike( s )\n true\n > bool = isNodeReadableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if running in a Node.js REPL environment.\n\n Examples\n --------\n > var bool = isNodeREPL()\n \n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n Tests if a value is Node stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Stream;\n > s = new Stream();\n > var bool = isNodeStreamLike( s )\n true\n > bool = isNodeStreamLike( {} )\n false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n Tests if a value is Node transform stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node transform stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Transform;\n > s = new Stream();\n > var bool = isNodeTransformStreamLike( s )\n true\n > bool = isNodeTransformStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n Tests if a value is Node writable stream-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is Node writable stream-like.\n\n Examples\n --------\n > var Stream = require( 'stream' ).Writable;\n > s = new Stream();\n > var bool = isNodeWritableStreamLike( s )\n true\n > bool = isNodeWritableStreamLike( {} )\n false\n\n See Also\n --------\n isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n Tests if an object's own property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurableProperty( obj, 'boop' )\n false\n > bool = isNonConfigurableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-configurable.\n\n A non-configurable property is a property which cannot be deleted and whose\n descriptor cannot be changed.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n configurable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n false\n > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n Tests if an object's own property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is non-enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerableProperty( obj, 'boop' )\n false\n > bool = isNonEnumerableProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n Tests if an object's own or inherited property is non-enumerable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is non-\n enumerable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n false\n > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n Tests if a value is a nonnegative finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative finite number.\n\n Examples\n --------\n > var bool = isNonNegativeFinite( 5.0 )\n true\n > bool = isNonNegativeFinite( new Number( 5.0 ) )\n true\n > bool = isNonNegativeFinite( 3.14 )\n true\n > bool = isNonNegativeFinite( -5.0 )\n false\n > bool = isNonNegativeFinite( null )\n false\n > bool = isNonNegativeFinite( PINF )\n false\n\n\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n Tests if a value is a number object having a nonnegative finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a \n nonnegative finite value.\n\n Examples\n --------\n > var bool = isNonNegativeFinite.isObject( 3.0 )\n false\n > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n Tests if a value is a nonnegative integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative integer.\n\n Examples\n --------\n > var bool = isNonNegativeInteger( 5.0 )\n true\n > bool = isNonNegativeInteger( new Number( 5.0 ) )\n true\n > bool = isNonNegativeInteger( 3.14 )\n false\n > bool = isNonNegativeInteger( -5.0 )\n false\n > bool = isNonNegativeInteger( null )\n false\n\n\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n Tests if a value is a number object having a nonnegative integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n integer value.\n\n Examples\n --------\n > var bool = isNonNegativeInteger.isObject( 3.0 )\n false\n > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative integers.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative primitive integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative integer values.\n\n Examples\n --------\n > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n Tests if a value is a nonnegative number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonnegative number.\n\n Examples\n --------\n > var bool = isNonNegativeNumber( 5.0 )\n true\n > bool = isNonNegativeNumber( new Number( 5.0 ) )\n true\n > bool = isNonNegativeNumber( 3.14 )\n true\n > bool = isNonNegativeNumber( -5.0 )\n false\n > bool = isNonNegativeNumber( null )\n false\n\n\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonnegative value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n true\n > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n Tests if a value is a number object having a nonnegative value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonnegative\n value.\n\n Examples\n --------\n > var bool = isNonNegativeNumber.isObject( 3.0 )\n false\n > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonnegative numbers.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n true\n > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonnegative number values.\n\n Examples\n --------\n > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n Tests if a value is a nonpositive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive finite number.\n\n Examples\n --------\n > var bool = isNonPositiveFinite( -5.0 )\n true\n > bool = isNonPositiveFinite( new Number( -5.0 ) )\n true\n > bool = isNonPositiveFinite( -3.14 )\n true\n > bool = isNonPositiveFinite( 5.0 )\n false\n > bool = isNonPositiveFinite( null )\n false\n\n\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n Tests if a value is a number object having a nonpositive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n finite value.\n\n Examples\n --------\n > var bool = isNonPositiveFinite.isObject( -3.0 )\n false\n > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n Tests if a value is a nonpositive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive integer.\n\n Examples\n --------\n > var bool = isNonPositiveInteger( -5.0 )\n true\n > bool = isNonPositiveInteger( new Number( -5.0 ) )\n true\n > bool = isNonPositiveInteger( 5.0 )\n false\n > bool = isNonPositiveInteger( -3.14 )\n false\n > bool = isNonPositiveInteger( null )\n false\n\n\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n Tests if a value is a number object having a nonpositive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n integer value.\n\n Examples\n --------\n > var bool = isNonPositiveInteger.isObject( -3.0 )\n false\n > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive integers.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive primitive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive integer values.\n\n Examples\n --------\n > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n Tests if a value is a nonpositive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a nonpositive number.\n\n Examples\n --------\n > var bool = isNonPositiveNumber( -5.0 )\n true\n > bool = isNonPositiveNumber( new Number( -5.0 ) )\n true\n > bool = isNonPositiveNumber( -3.14 )\n true\n > bool = isNonPositiveNumber( 5.0 )\n false\n > bool = isNonPositiveNumber( null )\n false\n\n\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n nonpositive value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n true\n > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n Tests if a value is a number object having a nonpositive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a nonpositive\n value.\n\n Examples\n --------\n > var bool = isNonPositiveNumber.isObject( -3.0 )\n false\n > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n true\n > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n false\n\n\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false\n\n\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive nonpositive numbers.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n true\n > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having nonpositive number values.\n\n Examples\n --------\n > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n true\n > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n false\n > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n false\n\n See Also\n --------\n isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n Tests if a value is a non-symmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a non-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 4 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isNonSymmetricMatrix( M )\n true\n > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isNonSymmetricMatrix( 3.14 )\n false\n > bool = isNonSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n Tests if a value is null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is null.\n\n Examples\n --------\n > var bool = isNull( null )\n true\n > bool = isNull( true )\n false\n\n See Also\n --------\n isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n Tests if a value is an array-like object containing only null values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n null values.\n\n Examples\n --------\n > var bool = isNullArray( [ null, null, null ] )\n true\n > bool = isNullArray( [ NaN, 2, null ] )\n false\n\n See Also\n --------\n isArray, isNull\n","isNumber":"\nisNumber( value )\n Tests if a value is a number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number.\n\n Examples\n --------\n > var bool = isNumber( 3.14 )\n true\n > bool = isNumber( new Number( 3.14 ) )\n true\n > bool = isNumber( NaN )\n true\n > bool = isNumber( null )\n false\n\n\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false\n\n\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n Tests if a value is a number primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive.\n\n Examples\n --------\n > var bool = isNumber.isPrimitive( 3.14 )\n true\n > bool = isNumber.isPrimitive( NaN )\n true\n > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n false","isNumber.isObject":"\nisNumber.isObject( value )\n Tests if a value is a `Number` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object.\n\n Examples\n --------\n > var bool = isNumber.isObject( 3.14 )\n false\n > bool = isNumber.isObject( new Number( 3.14 ) )\n true","isNumberArray":"\nisNumberArray( value )\n Tests if a value is an array-like object containing only numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n numbers.\n\n Examples\n --------\n > var bool = isNumberArray( [ 1, 2, 3 ] )\n true\n > bool = isNumberArray( [ '1', 2, 3 ] )\n false\n\n\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false\n\n\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n Tests if a value is an array-like object containing only number primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number primitives.\n\n Examples\n --------\n > var arr = [ 1, 2, 3 ];\n > var bool = isNumberArray.primitives( arr )\n true\n > arr = [ 1, new Number( 2 ) ];\n > bool = isNumberArray.primitives( arr )\n false","isNumberArray.objects":"\nisNumberArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects.\n\n Examples\n --------\n > var arr = [ new Number( 1 ), new Number( 2 ) ];\n > var bool = isNumberArray.objects( arr )\n true\n > arr = [ new Number( 1 ), 2 ];\n > bool = isNumberArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n Tests if a value is a numeric array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a numeric array.\n\n Examples\n --------\n > var bool = isNumericArray( new Int8Array( 10 ) )\n true\n > bool = isNumericArray( [ 1, 2, 3 ] )\n true\n > bool = isNumericArray( [ '1', '2', '3' ] )\n false\n\n See Also\n --------\n isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n Tests if a value is an object; e.g., `{}`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an object.\n\n Examples\n --------\n > var bool = isObject( {} )\n true\n > bool = isObject( true )\n false\n\n See Also\n --------\n isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n Tests if a value is an array-like object containing only objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n objects.\n\n Examples\n --------\n > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n true\n > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n Tests if a value is object-like.\n\n Return values are the same as would be obtained using the built-in `typeof`\n operator except that `null` is not considered an object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is object-like.\n\n Examples\n --------\n > var bool = isObjectLike( {} )\n true\n > bool = isObjectLike( [] )\n true\n > bool = isObjectLike( null )\n false\n\n See Also\n --------\n isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n Tests if a value is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an odd number.\n\n Examples\n --------\n > var bool = isOdd( 5.0 )\n true\n > bool = isOdd( new Number( 5.0 ) )\n true\n > bool = isOdd( 4.0 )\n false\n > bool = isOdd( new Number( 4.0 ) )\n false\n > bool = isOdd( -3.14 )\n false\n > bool = isOdd( null )\n false\n\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false\n\n\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n Tests if a value is a number primitive that is an odd number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive that is an odd\n number.\n\n Examples\n --------\n > var bool = isOdd.isPrimitive( -5.0 )\n true\n > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n false","isOdd.isObject":"\nisOdd.isObject( value )\n Tests if a value is a number object that has an odd number value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object that has an odd\n number value.\n\n Examples\n --------\n > var bool = isOdd.isObject( 5.0 )\n false\n > bool = isOdd.isObject( new Number( 5.0 ) )\n true\n\n See Also\n --------\n isEven","isoWeeksInYear":"\nisoWeeksInYear( [value] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n\n By default, the function returns the number of ISO weeks in the current year\n (according to local time). To determine the number of ISO weeks for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of ISO weeks in a year.\n\n Examples\n --------\n > var num = isoWeeksInYear()\n \n > num = isoWeeksInYear( 2015 )\n 53\n > num = isoWeeksInYear( 2017 )\n 52\n\n","isPascalcase":"\nisPascalcase( value )\n Tests if a value is a string in Pascal case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in Pascal case.\n\n Examples\n --------\n > var bool = isPascalcase( 'HelloWorld' )\n true\n > bool = isPascalcase( 'hello-world' )\n false\n\n See Also\n --------\n isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 2, 3, 1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isPersymmetricMatrix( M )\n true\n > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isPersymmetricMatrix( 3.14 )\n false\n > bool = isPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n Tests if a value is a plain object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a plain object.\n\n Examples\n --------\n > var bool = isPlainObject( {} )\n true\n > bool = isPlainObject( null )\n false\n\n See Also\n --------\n isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n Tests if a value is an array-like object containing only plain objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n plain objects.\n\n Examples\n --------\n > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n true\n > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n false\n > bool = isPlainObjectArray( [ {}, '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n Tests if a value is a positive finite number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a positive finite number.\n\n Examples\n --------\n > var bool = isPositiveFinite( 5.0 )\n true\n > bool = isPositiveFinite( new Number( 5.0 ) )\n true\n > bool = isPositiveFinite( 3.14 )\n true\n > bool = isPositiveFinite( -5.0 )\n false\n > var bool = isPositiveFinite( 1.0/0.0 )\n false\n > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n false\n > bool = isPositiveFinite( null )\n false\n\n\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n Tests if a value is a number primitive having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a value is a number primitive having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isPrimitive( 3.0 )\n true\n > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n false\n > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n Tests if a value is a number object having a positive finite value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n finite value.\n\n Examples\n --------\n > var bool = isPositiveFinite.isObject( 3.0 )\n false\n > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n true\n > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n false\n\n\n See Also\n --------\n isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n Tests if a value is a positive integer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive integer.\n\n Examples\n --------\n > var bool = isPositiveInteger( 5.0 )\n true\n > bool = isPositiveInteger( new Number( 5.0 ) )\n true\n > bool = isPositiveInteger( 3.14 )\n false\n > bool = isPositiveInteger( -5.0 )\n false\n > bool = isPositiveInteger( null )\n false\n\n\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n Tests if a value is a number primitive having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a\n positive integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isPrimitive( 3.0 )\n true\n > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n Tests if a value is a number object having a positive integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n integer value.\n\n Examples\n --------\n > var bool = isPositiveInteger.isObject( 3.0 )\n false\n > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n Tests if a value is an array-like object containing only positive integers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive integers.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive integer values.\n\n Examples\n --------\n > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n Tests if a value is a positive number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a positive number.\n\n Examples\n --------\n > var bool = isPositiveNumber( 5.0 )\n true\n > bool = isPositiveNumber( new Number( 5.0 ) )\n true\n > bool = isPositiveNumber( 3.14 )\n true\n > bool = isPositiveNumber( -5.0 )\n false\n > bool = isPositiveNumber( null )\n false\n\n\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false\n\n\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n Tests if a value is a number primitive having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isPrimitive( 3.0 )\n true\n > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n Tests if a value is a number object having a positive value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a positive\n value.\n\n Examples\n --------\n > var bool = isPositiveNumber.isObject( 3.0 )\n false\n > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n true\n\n\n See Also\n --------\n isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n Tests if a value is an array-like object containing only positive numbers.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive numbers.\n\n Examples\n --------\n > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n true\n > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n false\n\n\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false\n\n\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n positive primitive number values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n true\n > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having positive values.\n\n Examples\n --------\n > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n true\n > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n false\n > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n false\n\n See Also\n --------\n isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n Tests if a value is positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero( 0.0 )\n true\n > bool = isPositiveZero( new Number( 0.0 ) )\n true\n > bool = isPositiveZero( -3.14 )\n false\n > bool = isPositiveZero( -0.0 )\n false\n > bool = isPositiveZero( null )\n false\n\n\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false\n\n\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n Tests if a value is a number primitive equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number primitive equal to\n positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isPrimitive( 0.0 )\n true\n > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n Tests if a value is a number object having a value equal to positive zero.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a number object having a value\n equal to positive zero.\n\n Examples\n --------\n > var bool = isPositiveZero.isObject( 0.0 )\n false\n > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n true\n\n See Also\n --------\n isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n Tests if a value is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a prime number.\n\n Examples\n --------\n > var bool = isPrime( 5.0 )\n true\n > bool = isPrime( new Number( 5.0 ) )\n true\n > bool = isPrime( 3.14 )\n false\n > bool = isPrime( -5.0 )\n false\n > bool = isPrime( null )\n false\n\n\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false\n\n\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n Tests if a value is a number primitive which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a prime\n number.\n\n Examples\n --------\n > var bool = isPrime.isPrimitive( 5.0 )\n true\n > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n false","isPrime.isObject":"\nisPrime.isObject( value )\n Tests if a value is a number object having a value which is a prime number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a prime number.\n\n Examples\n --------\n > var bool = isPrime.isObject( 5.0 )\n false\n > bool = isPrime.isObject( new Number( 5.0 ) )\n true\n\n\n See Also\n --------\n isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n Tests if a value is a JavaScript primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a JavaScript primitive.\n\n Examples\n --------\n > var bool = isPrimitive( true )\n true\n > bool = isPrimitive( {} )\n false\n\n See Also\n --------\n isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n JavaScript primitives.\n\n Examples\n --------\n > var bool = isPrimitiveArray( [ '3', 2, null ] )\n true\n > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n false\n > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n false\n\n See Also\n --------\n isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n Tests if a value is PRNG-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is PRNG-like.\n\n Examples\n --------\n > var bool = isPRNGLike( base.random.randu )\n true\n > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isPRNGLike( 3.14 )\n false\n > bool = isPRNGLike( {} )\n false\n\n","isProbability":"\nisProbability( value )\n Tests if a value is a probability.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a probability.\n\n Examples\n --------\n > var bool = isProbability( 0.5 )\n true\n > bool = isProbability( new Number( 0.5 ) )\n true\n > bool = isProbability( 3.14 )\n false\n > bool = isProbability( -5.0 )\n false\n > bool = isProbability( null )\n false\n\n\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false\n\n\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n Tests if a value is a number primitive which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n probability.\n\n Examples\n --------\n > var bool = isProbability.isPrimitive( 0.3 )\n true\n > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n false","isProbability.isObject":"\nisProbability.isObject( value )\n Tests if a value is a number object having a value which is a probability.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a probability.\n\n Examples\n --------\n > var bool = isProbability.isObject( 0.77 )\n false\n > bool = isProbability.isObject( new Number( 0.77 ) )\n true\n\n\n See Also\n --------\n isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n Tests if a value is an array-like object containing only probabilities.\n\n A probability is defined as a numeric value on the interval [0,1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n true\n > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n false\n > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n false\n\n\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false\n\n\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive probabilities.\n\n Examples\n --------\n > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n true\n > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n number objects having probability values.\n\n Examples\n --------\n > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n true\n > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n false\n\n See Also\n --------\n isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n Tests whether a value is a property key.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether value is a property key.\n\n Examples\n --------\n > var out = isPropertyKey( 'foo' )\n true\n > out = isPropertyKey( 1 )\n true\n > out = isPropertyKey( true )\n false\n\n See Also\n --------\n isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n Tests if an object's prototype chain contains a provided prototype.\n\n The function returns `false` if provided a primitive value.\n\n This function is generally more robust than the `instanceof` operator (e.g.,\n where inheritance is performed without using constructors).\n\n Parameters\n ----------\n value: any\n Input value.\n\n proto: Object|Function\n Prototype.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if a provided prototype exists in a prototype chain.\n\n Examples\n --------\n > function Foo() { return this; };\n > function Bar() { return this; };\n > inherit( Bar, Foo );\n > var bar = new Bar();\n > var bool = isPrototypeOf( bar, Foo.prototype )\n true\n\n See Also\n --------\n getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n Tests if a value is a ragged nested array. \n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a ragged nested array.\n\n Examples\n --------\n > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n true\n > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n false\n > bool = isRaggedNestedArray( 'beep' )\n false\n\n","isRangeError":"\nisRangeError( value )\n Tests if a value is a RangeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a RangeError (or a descendant) object,\n false positives may occur due to the fact that the RangeError constructor\n inherits from Error and has no internal class of its own. Hence, RangeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a RangeError object.\n\n Examples\n --------\n > var bool = isRangeError( new RangeError( 'beep' ) )\n true\n > bool = isRangeError( {} )\n false\n\n See Also\n --------\n isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n Tests if an object's own property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadableProperty( obj, 'boop' )\n true\n > bool = isReadableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n Tests if an object's own or inherited property is readable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadablePropertyIn( obj, 'boop' )\n true\n > bool = isReadablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n Tests if an object's own property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is read-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyProperty( obj, 'boop' )\n true\n > bool = isReadOnlyProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is read-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is read-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = true;\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n true\n > bool = isReadOnlyPropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n Tests if an object's own property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is readable and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWriteProperty( obj, 'boop' )\n true\n > bool = isReadWriteProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n Tests if an object's own or inherited property is readable and writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is readable\n and writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isReadWritePropertyIn( obj, 'boop' )\n true\n > bool = isReadWritePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n Tests if a value is a ReferenceError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a ReferenceError (or a descendant)\n object, false positives may occur due to the fact that the ReferenceError\n constructor inherits from Error and has no internal class of its own.\n Hence, ReferenceError impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a ReferenceError object.\n\n Examples\n --------\n > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n true\n > bool = isReferenceError( {} )\n false\n\n See Also\n --------\n isError\n","isRegExp":"\nisRegExp( value )\n Tests if a value is a regular expression.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression.\n\n Examples\n --------\n > var bool = isRegExp( /\\.+/ )\n true\n > bool = isRegExp( {} )\n false\n\n","isRegExpString":"\nisRegExpString( value )\n Tests if a value is a regular expression string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a regular expression string.\n\n Examples\n --------\n > var bool = isRegExpString( '/beep/' )\n true\n > bool = isRegExpString( 'beep' )\n false\n > bool = isRegExpString( '' )\n false\n > bool = isRegExpString( null )\n false\n\n See Also\n --------\n isRegExp\n","isRelativePath":"\nisRelativePath( value )\n Tests if a value is a relative path.\n\n Function behavior is platform-specific. On Windows platforms, the function\n is equal to `.win32()`. On POSIX platforms, the function is equal to\n `.posix()`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a relative path.\n\n Examples\n --------\n // Windows environments:\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n\n // POSIX environments:\n > bool = isRelativePath( './foo/bar/baz' )\n true\n\n\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false\n\n\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n Tests if a value is a POSIX relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a POSIX relative path.\n\n Examples\n --------\n > var bool = isRelativePath.posix( './foo/bar/baz' )\n true\n > bool = isRelativePath.posix( '/foo/../bar/baz' )\n false","isRelativePath.win32":"\nisRelativePath.win32( value )\n Tests if a value is a Windows relative path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Windows relative path.\n\n Examples\n --------\n > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n true\n > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n false\n\n See Also\n --------\n isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n Tests whether a value is a relative URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a value is a relative URI.\n\n Examples\n --------\n > var bool = isRelativeURI( '/images/example.png' )\n true\n > bool = isRelativeURI( 'http://www.example.com' )\n false\n > bool = isRelativeURI( null )\n false\n\n See Also\n --------\n isURI","isSafeInteger":"\nisSafeInteger( value )\n Tests if a value is a safe integer.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a safe integer.\n\n Examples\n --------\n > var bool = isSafeInteger( 5.0 )\n true\n > bool = isSafeInteger( new Number( 5.0 ) )\n true\n > bool = isSafeInteger( 2.0e200 )\n false\n > bool = isSafeInteger( -3.14 )\n false\n > bool = isSafeInteger( null )\n false\n\n\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false\n\n\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n Tests if a value is a number primitive having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isPrimitive( -3.0 )\n true\n > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n Tests if a value is a `Number` object having a safe integer value.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `Number` object having a safe\n integer value.\n\n Examples\n --------\n > var bool = isSafeInteger.isObject( 3.0 )\n false\n > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n true\n\n See Also\n --------\n isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n Tests if a value is an array-like object containing only safe integers.\n\n An integer valued number is \"safe\" when the number can be exactly\n represented as a double-precision floating-point number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing\n only safe integers.\n\n Examples\n --------\n > var arr = [ -3.0, new Number(0.0), 2.0 ];\n > var bool = isSafeIntegerArray( arr )\n true\n > arr = [ -3.0, '3.0' ];\n > bool = isSafeIntegerArray( arr )\n false\n\n\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false\n\n\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n primitive safe integer values.\n\n Examples\n --------\n > var arr = [ -1.0, 10.0 ];\n > var bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -1.0, 0.0, 5.0 ];\n > bool = isSafeIntegerArray.primitives( arr )\n true\n > arr = [ -3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.primitives( arr )\n false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array-like object containing only\n `Number` objects having safe integer values.\n\n Examples\n --------\n > var arr = [ new Number(1.0), new Number(3.0) ];\n > var bool = isSafeIntegerArray.objects( arr )\n true\n > arr = [ -1.0, 0.0, 3.0 ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n > arr = [ 3.0, new Number(-1.0) ];\n > bool = isSafeIntegerArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n Tests if two arguments are both generic arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArray( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArray( x, y )\n true\n\n See Also\n --------\n isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n Tests if two arguments are both array-like and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = [ 1.0, 2.0, 3.0 ];\n > var y = [ 1.0, 2.0, 3.0 ];\n > var bool = isSameArrayLike( x, y )\n true\n\n > x = [ NaN, NaN, NaN ];\n > y = [ NaN, NaN, NaN ];\n > bool = isSameArrayLike( x, y )\n true\n\n See Also\n --------\n isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64( 1.0, 2.0 );\n > var y = new Complex64( 1.0, 2.0 );\n > var bool = isSameComplex64( x, y )\n true\n\n > x = new Complex64( NaN, NaN );\n > y = new Complex64( NaN, NaN );\n > bool = isSameComplex64( x, y )\n true\n\n See Also\n --------\n isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n Tests if two arguments are both Complex64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex64Array( x, y )\n true\n\n > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex64Array( x, y )\n true\n\n See Also\n --------\n isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128( 1.0, 2.0 );\n > var y = new Complex128( 1.0, 2.0 );\n > var bool = isSameComplex128( x, y )\n true\n\n > x = new Complex128( NaN, NaN );\n > y = new Complex128( NaN, NaN );\n > bool = isSameComplex128( x, y )\n true\n\n See Also\n --------\n isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n Tests if two arguments are both Complex128Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var bool = isSameComplex128Array( x, y )\n true\n\n > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n > bool = isSameComplex128Array( x, y )\n true\n\n See Also\n --------\n isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n Tests if two arguments are both Float32Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat32Array( x, y )\n true\n\n > x = new Float32Array( [ NaN, NaN, NaN ] );\n > y = new Float32Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat32Array( x, y )\n true\n\n See Also\n --------\n isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n Tests if two arguments are both Float64Arrays and have the same values.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n v1: any\n First input value.\n\n v2: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same.\n\n Examples\n --------\n > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n > var bool = isSameFloat64Array( x, y )\n true\n\n > x = new Float64Array( [ NaN, NaN, NaN ] );\n > y = new Float64Array( [ NaN, NaN, NaN ] );\n > bool = isSameFloat64Array( x, y )\n true\n\n See Also\n --------\n isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n Tests if two arguments have the same native class.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same native class.\n\n Examples\n --------\n > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n true\n > bool = isSameNativeClass( 'beep', 'boop' )\n true\n > bool = isSameNativeClass( {}, [] )\n false\n\n See Also\n --------\n isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n Tests if two arguments have the same type.\n\n The function uses the `typeof` operator to test for the same type.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments have the same type.\n\n Examples\n --------\n > var bool = isSameType( true, true )\n true\n > bool = isSameType( {}, [] )\n true\n > bool = isSameType( 3.12, -3.12 )\n true\n > bool = isSameType( 0.0, '0.0' )\n false\n\n See Also\n --------\n isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct and `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValue( true, true )\n true\n > bool = isSameValue( {}, {} )\n false\n > bool = isSameValue( -0.0, -0.0 )\n true\n > bool = isSameValue( -0.0, 0.0 )\n false\n > bool = isSameValue( NaN, NaN )\n true\n\n See Also\n --------\n isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n Tests if two arguments are the same value.\n\n The function differs from the `===` operator in that the function treats\n `NaNs` as the same.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are the same value.\n\n Examples\n --------\n > var bool = isSameValueZero( true, true )\n true\n > bool = isSameValueZero( {}, {} )\n false\n > bool = isSameValueZero( -0.0, -0.0 )\n true\n > bool = isSameValueZero( -0.0, 0.0 )\n true\n > bool = isSameValueZero( NaN, NaN )\n true\n\n See Also\n --------\n isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n Tests if a value is a semantic version string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether a provided value is a semantic version\n string.\n\n Examples\n --------\n > var bool = isSemVer( '1.0.0' )\n true\n > bool = isSemVer( '1.0.0-alpha.1' )\n true\n > bool = isSemVer( '0.1' )\n false\n > bool = isSemVer( null )\n false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n Tests if a value is a SharedArrayBuffer.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SharedArrayBuffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffer...\n > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n true\n > bool = isSharedArrayBuffer( [] )\n false\n\n See Also\n --------\n isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n Tests if a value is a skew-centrosymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n Examples\n --------\n > var buf = [ 2, 1, -1, -2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewCentrosymmetricMatrix( M )\n true\n > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewCentrosymmetricMatrix( 3.14 )\n false\n > bool = isSkewCentrosymmetricMatrix( {} )\n false\n\n See Also\n --------\n isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n Tests if a value is a skew-persymmetric matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-persymmetric matrix.\n\n Examples\n --------\n > var buf = [ 1, 0, 0, -1 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewPersymmetricMatrix( M )\n true\n > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewPersymmetricMatrix( 3.14 )\n false\n > bool = isSkewPersymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a skew-symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, -1, 1, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSkewSymmetricMatrix( M )\n true\n > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSkewSymmetricMatrix( 3.14 )\n false\n > bool = isSkewSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSquareMatrix\n","isSlice":"\nisSlice( value )\n Tests if a value is a Slice object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a Slice object.\n\n Examples\n --------\n > var bool = isSlice( new Slice( 10 ) )\n true\n > bool = isSlice( 3.14 )\n false\n > bool = isSlice( {} )\n false\n\n See Also\n --------\n isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n Tests if a value is a string in snake case.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a string in snake case.\n\n Examples\n --------\n > var bool = isSnakecase( 'hello_world' )\n true\n > bool = isSnakecase( 'Hello World' )\n false\n\n See Also\n --------\n isString","isSquareMatrix":"\nisSquareMatrix( value )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 2-dimensional ndarray-like\n object having equal dimensions.\n\n Examples\n --------\n > var buf = [ 0, 0, 0, 0 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSquareMatrix( M )\n true\n > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSquareMatrix( 3.14 )\n false\n > bool = isSquareMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n Tests if a value is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber( 4.0 )\n true\n > bool = isSquareNumber( new Number( 4.0 ) )\n true\n > bool = isSquareNumber( 3.14 )\n false\n > bool = isSquareNumber( -5.0 )\n false\n > bool = isSquareNumber( null )\n false\n\n\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false\n\n\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isPrimitive( 4.0 )\n true\n > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n Tests if a value is a number object having a value which is a square number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square number.\n\n Examples\n --------\n > var bool = isSquareNumber.isObject( 4.0 )\n false\n > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n true\n\n\n See Also\n --------\n isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n Tests if a value is a square triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber( 36.0 )\n true\n > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isSquareTriangularNumber( 3.14 )\n false\n > bool = isSquareTriangularNumber( -5.0 )\n false\n > bool = isSquareTriangularNumber( null )\n false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a square triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a square\n triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a square triangular number.\n\n Examples\n --------\n > var bool = isSquareTriangularNumber.isObject( 36.0 )\n false\n > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n Tests if a value is a startcase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if value is a startcase string.\n\n Examples\n --------\n > var bool = isStartcase( 'Beep Boop' )\n true\n > bool = isStartcase( 'Beep and Boop' )\n false\n\n See Also\n --------\n isString","isStrictEqual":"\nisStrictEqual( a, b )\n Tests if two arguments are strictly equal.\n\n The function differs from the `===` operator in that the function treats\n `-0` and `+0` as distinct.\n\n Parameters\n ----------\n a: any\n First input value.\n\n b: any\n Second input value.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether two arguments are strictly equal.\n\n Examples\n --------\n > var bool = isStrictEqual( true, true )\n true\n > bool = isStrictEqual( {}, {} )\n false\n > bool = isStrictEqual( -0.0, -0.0 )\n true\n > bool = isStrictEqual( -0.0, 0.0 )\n false\n > bool = isStrictEqual( NaN, NaN )\n false\n\n See Also\n --------\n isSameValue\n","isString":"\nisString( value )\n Tests if a value is a string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string.\n\n Examples\n --------\n > var bool = isString( 'beep' )\n true\n > bool = isString( new String( 'beep' ) )\n true\n > bool = isString( 5 )\n false\n\n\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false\n\n\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n Tests if a value is a string primitive.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a string primitive.\n\n Examples\n --------\n > var bool = isString.isPrimitive( 'beep' )\n true\n > bool = isString.isPrimitive( new String( 'beep' ) )\n false","isString.isObject":"\nisString.isObject( value )\n Tests if a value is a `String` object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a `String` object.\n\n Examples\n --------\n > var bool = isString.isObject( new String( 'beep' ) )\n true\n > bool = isString.isObject( 'beep' )\n false","isStringArray":"\nisStringArray( value )\n Tests if a value is an array of strings.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of strings.\n\n Examples\n --------\n > var bool = isStringArray( [ 'abc', 'def' ] )\n true\n > bool = isStringArray( [ 'abc', 123 ] )\n false\n\n\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false\n\n\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n Tests if a value is an array containing only string primitives.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only string\n primitives.\n\n Examples\n --------\n > var arr = [ 'abc', 'def' ];\n > var bool = isStringArray.primitives( arr )\n true\n > arr = [ 'abc', new String( 'def' ) ];\n > bool = isStringArray.primitives( arr )\n false","isStringArray.objects":"\nisStringArray.objects( value )\n Tests if a value is an array containing only `String` objects.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array containing only `String`\n objects.\n\n Examples\n --------\n > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n > var bool = isStringArray.objects( arr )\n true\n > arr = [ new String( 'abc' ), 'def' ];\n > bool = isStringArray.objects( arr )\n false\n\n See Also\n --------\n isArray, isString","isStruct":"\nisStruct( value )\n Tests if a value is a `struct` instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a `struct` instance.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStruct( new S() )\n true\n > bool = isStruct( [ 1, 2, 3, 4 ] )\n false\n > bool = isStruct( 3.14 )\n false\n > bool = isStruct( {} )\n false\n\n See Also\n --------\n isStructConstructorLike, structFactory\n","isStructConstructorLike":"\nisStructConstructorLike( value )\n Tests if a value is struct constructor-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is struct constructor-like.\n\n Examples\n --------\n > var schema = [ { 'name': 'foo', 'type': 'float64' } ];\n > var S = structFactory( schema );\n > var bool = isStructConstructorLike( S )\n true\n > bool = isStructConstructorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isStructConstructorLike( 3.14 )\n false\n > bool = isStructConstructorLike( {} )\n false\n\n See Also\n --------\n isStruct, structFactory\n","isSymbol":"\nisSymbol( value )\n Tests if a value is a symbol.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symbol.\n\n Examples\n --------\n > var bool = isSymbol( Symbol( 'beep' ) )\n true\n > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n true\n > bool = isSymbol( {} )\n false\n > bool = isSymbol( null )\n false\n > bool = isSymbol( true )\n false\n\n","isSymbolArray":"\nisSymbolArray( value )\n Tests if a value is an array-like object containing only symbols.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only symbols.\n\n Examples\n --------\n > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n true\n > bool = isSymbolArray( Symbol( 'beep' ) )\n false\n > bool = isSymbolArray( [] )\n false\n > bool = isSymbolArray( {} )\n false\n > bool = isSymbolArray( null )\n false\n > bool = isSymbolArray( true )\n false\n\n\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false\n\n\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `symbol` primitives.\n\n Examples\n --------\n > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n true\n > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n false\n > bool = isSymbolArray.primitives( [] )\n false\n > bool = isSymbolArray.primitives( {} )\n false\n > bool = isSymbolArray.primitives( null )\n false\n > bool = isSymbolArray.primitives( true )\n false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n\n In pre-ES2015 environments, the function always returns `false`.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only `Symbol` objects.\n\n Examples\n --------\n > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n true\n > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n false\n > bool = isSymbolArray.objects( [] )\n false\n > bool = isSymbolArray.objects( {} )\n false\n > bool = isSymbolArray.objects( null )\n false\n > bool = isSymbolArray.objects( true )\n false\n\n See Also\n --------\n isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n Tests if a value is a square matrix which equals its transpose.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a symmetric matrix.\n\n Examples\n --------\n > var buf = [ 0, 1, 1, 2 ];\n > var sh = [ 2, 2 ];\n > var st = [ 2, 1 ];\n > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n > var bool = isSymmetricMatrix( M )\n true\n > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n false\n > bool = isSymmetricMatrix( 3.14 )\n false\n > bool = isSymmetricMatrix( {} )\n false\n\n See Also\n --------\n isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n Tests if a value is a SyntaxError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a SyntaxError (or a descendant) object,\n false positives may occur due to the fact that the SyntaxError constructor\n inherits from Error and has no internal class of its own. Hence, SyntaxError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a SyntaxError object.\n\n Examples\n --------\n > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n true\n > bool = isSyntaxError( {} )\n false\n\n See Also\n --------\n isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n Tests if a value is a triangular number.\n\n Return values are not reliable for numbers greater than 1125899906842624.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber( 36.0 )\n true\n > bool = isTriangularNumber( new Number( 36.0 ) )\n true\n > bool = isTriangularNumber( 3.14 )\n false\n > bool = isTriangularNumber( -5.0 )\n false\n > bool = isTriangularNumber( null )\n false\n\n\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false\n\n\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n Tests if a value is a number primitive which is a triangular number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number primitive which is a\n triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isPrimitive( 36.0 )\n true\n > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n Tests if a value is a number object having a value which is a triangular\n number.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a number object having a value which\n is a triangular number.\n\n Examples\n --------\n > var bool = isTriangularNumber.isObject( 36.0 )\n false\n > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n true\n\n\n See Also\n --------\n isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is truthy.\n\n Examples\n --------\n > var bool = isTruthy( true )\n true\n > bool = isTruthy( {} )\n true\n > bool = isTruthy( [] )\n true\n > bool = isTruthy( false )\n false\n > bool = isTruthy( '' )\n false\n > bool = isTruthy( 0 )\n false\n > bool = isTruthy( null )\n false\n > bool = isTruthy( void 0 )\n false\n > bool = isTruthy( NaN )\n false\n\n See Also\n --------\n isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n Tests if a value is an array-like object containing only truthy values.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is an array-like object containing\n only truthy values.\n\n Examples\n --------\n > var bool = isTruthyArray( [ {}, [] ] )\n true\n > bool = isTruthyArray( [ null, '' ] )\n false\n > bool = isTruthyArray( [] )\n false\n\n See Also\n --------\n isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n Tests if a value is a built-in typed array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a built-in typed array.\n\n Examples\n --------\n > var bool = isTypedArray( new Int8Array( 10 ) )\n true\n\n See Also\n --------\n isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n Tests if a value is a valid typed array length.\n\n A valid length property for a typed array instance is any integer value on\n the interval [0, 2^53-1].\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a valid typed array length.\n\n Examples\n --------\n > var bool = isTypedArrayLength( 5 )\n true\n > bool = isTypedArrayLength( 2.0e200 )\n false\n > bool = isTypedArrayLength( -3.14 )\n false\n > bool = isTypedArrayLength( null )\n false\n\n See Also\n --------\n isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n Tests if a value is typed-array-like.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is typed-array-like.\n\n Examples\n --------\n > var bool = isTypedArrayLike( new Int16Array() )\n true\n > bool = isTypedArrayLike({\n ... 'length': 10,\n ... 'byteOffset': 0,\n ... 'byteLength': 10,\n ... 'BYTES_PER_ELEMENT': 4\n ... })\n true\n\n See Also\n --------\n isTypedArray\n","isTypeError":"\nisTypeError( value )\n Tests if a value is a TypeError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a TypeError (or a descendant) object,\n false positives may occur due to the fact that the TypeError constructor\n inherits from Error and has no internal class of its own. Hence, TypeError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a TypeError object.\n\n Examples\n --------\n > var bool = isTypeError( new TypeError( 'beep' ) )\n true\n > bool = isTypeError( {} )\n false\n\n See Also\n --------\n isError\n","isUint8Array":"\nisUint8Array( value )\n Tests if a value is a Uint8Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8Array.\n\n Examples\n --------\n > var bool = isUint8Array( new Uint8Array( 10 ) )\n true\n > bool = isUint8Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n Tests if a value is a Uint8ClampedArray.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint8ClampedArray.\n\n Examples\n --------\n > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n true\n > bool = isUint8ClampedArray( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n Tests if a value is a Uint16Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint16Array.\n\n Examples\n --------\n > var bool = isUint16Array( new Uint16Array( 10 ) )\n true\n > bool = isUint16Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n Tests if a value is a Uint32Array.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a Uint32Array.\n\n Examples\n --------\n > var bool = isUint32Array( new Uint32Array( 10 ) )\n true\n > bool = isUint32Array( [] )\n false\n\n See Also\n --------\n isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n Tests if a value is a UNC path.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a UNC path.\n\n Examples\n --------\n > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n true\n > bool = isUNCPath( '/foo/bar/baz' )\n false\n\n","isUndefined":"\nisUndefined( value )\n Tests if a value is undefined.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined.\n\n Examples\n --------\n > var bool = isUndefined( void 0 )\n true\n > bool = isUndefined( null )\n false\n\n See Also\n --------\n isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n Tests if a value is undefined or null.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is undefined or null.\n\n Examples\n --------\n > var bool = isUndefinedOrNull( void 0 )\n true\n > bool = isUndefinedOrNull( null )\n true\n > bool = isUndefinedOrNull( false )\n false\n\n See Also\n --------\n isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n Tests if a value is an array of probabilities that sum to one.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an array of probabilities that sum\n to one.\n\n Examples\n --------\n > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n true\n > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n true\n > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n false\n > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n false\n\n See Also\n --------\n isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n Tests if a value is an uppercase string.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is an uppercase string.\n\n Examples\n --------\n > var bool = isUppercase( 'HELLO' )\n true\n > bool = isUppercase( 'World' )\n false\n\n See Also\n --------\n isLowercase, isString\n","isURI":"\nisURI( value )\n Tests if a value is a URI.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URI.\n\n Examples\n --------\n > var bool = isURI( 'http://google.com' )\n true\n > bool = isURI( 'http://localhost/' )\n true\n > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n true\n > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n true\n\n // No scheme:\n > bool = isURI( '' )\n false\n > bool = isURI( 'foo@bar' )\n false\n > bool = isURI( '://foo/' )\n false\n\n // Illegal characters:\n > bool = isURI( 'http://' )\n false\n\n // Invalid path:\n > bool = isURI( 'http:////foo.html' )\n false\n\n // Incomplete hex escapes:\n > bool = isURI( 'http://example.w3.org/%a' )\n false\n\n","isURIError":"\nisURIError( value )\n Tests if a value is a URIError object.\n\n This function should *not* be considered robust. While the function should\n always return `true` if provided a URIError (or a descendant) object,\n false positives may occur due to the fact that the URIError constructor\n inherits from Error and has no internal class of its own. Hence, URIError\n impersonation is possible.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a URIError object.\n\n Examples\n --------\n > var bool = isURIError( new URIError( 'beep' ) )\n true\n > bool = isURIError( {} )\n false\n\n See Also\n --------\n isError\n","isVectorLike":"\nisVectorLike( value )\n Tests if a value is a 1-dimensional ndarray-like object.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a value is a 1-dimensional ndarray-like\n object.\n\n Examples\n --------\n > var M = {};\n > M.data = [ 0, 0, 0, 0 ];\n > M.ndims = 1;\n > M.shape = [ 4 ];\n > M.strides = [ 1 ];\n > M.offset = 0;\n > M.order = 'row-major';\n > M.dtype = 'generic';\n > M.length = 4;\n > M.flags = {};\n > M.get = function get( i, j ) {};\n > M.set = function set( i, j ) {};\n > var bool = isVectorLike( M )\n true\n > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n false\n > bool = isVectorLike( 3.14 )\n false\n > bool = isVectorLike( {} )\n false\n\n See Also\n --------\n isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n Tests if a value is a WebAssembly memory instance.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether value is a WebAssembly memory instance.\n\n Examples\n --------\n > var bool = isWebAssemblyMemory( {} )\n false\n\n See Also\n --------\n hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n Tests if a string is well-formed.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is well-formed.\n\n Examples\n --------\n > var bool = isWellFormedString( '' )\n true\n\n > bool = isWellFormedString( new String( '' ) )\n true\n\n > bool = isWellFormedString( '\\uDBFF' )\n false\n\n > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n false\n\n > bool = isWellFormedString( [] )\n false\n\n > bool = isWellFormedString( '-5' )\n true\n\n > bool = isWellFormedString( null )\n false\n\n\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false\n\n\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n Tests if a string is a well-formed string primitive.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string primitive.\n\n Examples\n --------\n > var bool = isWellFormedString.isPrimitive( '' )\n true\n > bool = isWellFormedString.isPrimitive( new String( '' ) )\n false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n Tests if a string is a well-formed string object.\n\n Parameters\n ----------\n str: any\n String to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether str is a well-formed string object.\n\n Examples\n --------\n > var bool = isWellFormedString.isObject( '' )\n false\n > bool = isWellFormedString.isObject( new String( '' ) )\n true","isWhitespace":"\nisWhitespace( str )\n Tests whether a string contains only white space characters.\n\n A white space character is defined as one of the 25 characters defined as a\n white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n database, as well as one related white space character without the Unicode\n character property \"WSpace=Y\" (zero width non-breaking space which was\n deprecated as of Unicode 3.2).\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string contains only white space\n characters.\n\n Examples\n --------\n > var bool = isWhitespace( ' ' )\n true\n > bool = isWhitespace( 'abcdef' )\n false\n > bool = isWhitespace( '' )\n false\n\n See Also\n --------\n reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n Tests if an object's own property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritableProperty( obj, 'boop' )\n true\n > bool = isWritableProperty( obj, 'beep' )\n false\n\n See Also\n --------\n isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n Tests if an object's own or inherited property is writable.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is writable.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'beep';\n > defineProperty( obj, 'beep', desc );\n > var bool = isWritablePropertyIn( obj, 'boop' )\n true\n > bool = isWritablePropertyIn( obj, 'beep' )\n false\n\n See Also\n --------\n isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n Tests if an object's own property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own property is write-only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyProperty( obj, 'boop' )\n false\n > bool = isWriteOnlyProperty( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n Tests if an object's own or inherited property is write-only.\n\n Parameters\n ----------\n value: any\n Value to test.\n\n property: any\n Property to test.\n\n Returns\n -------\n bool: boolean\n Boolean indicating if an object's own or inherited property is write-\n only.\n\n Examples\n --------\n > var obj = { 'boop': true };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.set = function setter( v ) { obj.boop = v; };\n > defineProperty( obj, 'beep', desc );\n > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n false\n > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n true\n\n See Also\n --------\n isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n Returns an iterator which iteratively computes the absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n Returns an iterator which iteratively computes the squared absolute value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAbs2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n Returns an iterator which iteratively computes the arccosine.\n\n The domain of arccosine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n Returns an iterator which iteratively computes the inverse cotangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n\n The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n and [1,inf). If an iterated value is outside of the domain, the returned\n iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n\n The domain of inverse coversed cosine is restricted to [0,2]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcovercos( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n Returns an iterator which iteratively computes the inverse coversed sine.\n\n The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to add.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterAdd( it1, it2 );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n Advances an entire iterator.\n\n The function *eagerly* advances an input iterator `n` iterations or until\n the input iterator finishes, whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Input iterator to advance.\n\n n: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Input iterator.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var it = iterAdvance( arr, 4 );\n > var v = it.next().value\n 1\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n\n The domain of inverse half-value versed cosine is restricted to [0,1]. If\n an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n\n The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n Tests whether at least one iterated value is truthy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a value is truthy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterAny( arr )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for any iterated value. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > function fcn( v ) { return ( v === 1 ); };\n > var bool = iterAnyBy( arr, fcn )\n true\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n Returns an iterator which iteratively computes the arcsine.\n\n The domain of arcsine is restricted to [-1,1]. If an iterated value is\n outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n Returns an iterator which iteratively computes the arctangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n y: Object|number\n Input iterator.\n\n x: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( -2.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterAtan2( y, x );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n Creates (or fills) an array from an iterator.\n\n When invoked, an input function is provided two arguments:\n\n - value: iterated value.\n - index: iterated value index (zero-based).\n\n If provided an output array, the function fills the output array with\n iterated values.\n\n Iteration stops when an output array is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n out: ArrayLikeObject (optional)\n Output array-like object.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var opts = { 'iter': 10 };\n > var arr = iterator2array( random.iterators.randu( opts ) )\n\n See Also\n --------\n array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view with values returned from an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayview( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: destination index (zero-based).\n - n: iteration index (zero-based).\n\n Iteration stops when an output array view is full or an iterator finishes;\n whichever comes first.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n dest: ArrayLikeObject\n Output array-like object.\n\n begin: integer (optional)\n Starting index (inclusive). When negative, determined relative to the\n last element. Default: 0.\n\n end: integer (optional)\n Ending index (non-inclusive). When negative, determined relative to the\n last element. Default: dest.length.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var it = random.iterators.randu({ 'iter': 10 });\n > var out = new Float64Array( 20 );\n > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n See Also\n --------\n iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n Creates a readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n In binary mode, if an iterator generates `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n explicitly map `undefined` values to a different value by wrapping the\n provided iterator with another iterator.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream( it );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n Returns a function for creating readable streams from iterators.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing iteration.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize iterated\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n Returns an \"objectMode\" readable stream from an iterator.\n\n In object mode, `null` is a reserved value. If an iterator generates `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or explicitly map `null`\n values to a different value by wrapping the provided iterator with another\n iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing iteration.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var it = random.iterators.randu( opts );\n > var s = iteratorStream.objectMode( it );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n\n This symbol specifies the default iterator for an object.\n\n The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n environments, the value is `null`.\n\n Examples\n --------\n > var s = IteratorSymbol\n e.g., \n\n See Also\n --------\n Symbol\n","iterAvercos":"\niterAvercos( iterator )\n Returns an iterator which iteratively computes the inverse versed cosine.\n\n The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n Returns an iterator which iteratively computes the inverse versed sine.\n\n The domain of inverse versed sine is restricted to [0,2]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n drawn from a standard normal distribution. If provided, the `state` and\n `seed` options are ignored. In order to seed the returned iterator, one\n must seed the provided `prng` (assuming the provided `prng` is\n seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function|null\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawgn( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawln( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n sigma: number\n Standard deviation of the noise.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval [0,1). If provided, the\n `state` and `seed` options are ignored. In order to seed the returned\n iterator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Pseudorandom random number generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var src = iterSineWave();\n > var it = iterawun( src, 0.5 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n Returns an iterator which generates a Bartlett pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBartlettPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBesselj1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely0( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBessely1( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n Returns an iterator which iteratively evaluates the beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBeta( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n y: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( 0.0, 2.0 );\n > var it = iterBetaln( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterBinet( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.binet\n","iterCbrt":"\niterCbrt( iterator )\n Returns an iterator which iteratively computes the cube root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCbrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n Returns an iterator which generates a sequence of composite numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCompositesSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n > v = it.next().value\n 8\n\n See Also\n --------\n iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n Returns an iterator which iterates over the values of two or more iterators.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to concatenate.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = array2iterator( [ 3, 4 ] );\n > var it = iterConcat( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n","iterConstant":"\niterConstant( value[, options] )\n Returns an iterator which always returns the same value.\n\n When provided an object reference, the returned iterator always returns the\n same reference.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n value: any\n Value to return.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterConstant( 3.14 );\n > var v = it.next().value\n 3.14\n > v = it.next().value\n 3.14\n\n See Also\n --------\n constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n Evaluates the terms of a continued fraction.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n Returns\n -------\n out: number|null\n Result.\n\n Examples\n --------\n > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n > var v = iterContinuedFraction( terms )\n ~3.245\n\n See Also\n --------\n iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x: number\n Input value.\n\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Maximum number of iterations. Default: 1e308.\n\n options.tol: number (optional)\n Tolerance at which to terminate further evaluation of the continued\n fraction. Default: floating-point epsilon.\n\n options.returns: string (optional)\n Specifies the type of result to return. Must be one of\n\n - terms: return continued fraction terms\n - convergents: return continued fraction convergents\n - *: return both continued fraction terms and their associated\n convergents as a two-element array.\n\n Default: 'terms'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n // Return continued fraction terms...\n > var it = iterContinuedFractionSeq( 3.245 );\n > var v = it.next().value\n 3\n > v = it.next().value\n 4\n > v = it.next().value\n 12\n > v = it.next().value\n 4\n > var bool = it.next().done\n true\n\n // Return continued fraction convergents...\n > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n > v = it.next().value\n 3.0\n > v = it.next().value\n 3.25\n > v = it.next().value\n ~3.2449\n > v = it.next().value\n 3.245\n > bool = it.next().done\n true\n\n See Also\n --------\n iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n Returns an iterator which iteratively computes the cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCos( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterCosh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n Returns an iterator which generates a cosine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a cosine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCosineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCosm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n\n Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCospi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n Returns an iterator which iteratively computes the number of iterated\n values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCounter( random.iterators.randu() );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterLength\n","iterCovercos":"\niterCovercos( iterator )\n Returns an iterator which iteratively computes the coversed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n Returns an iterator which iteratively computes the coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterCoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n Returns an iterator which generates a sequence of cubes.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 208063.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterCubesSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 8\n\n See Also\n --------\n iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n\n If provided a negative value, the iterated value is `NaN` for all future\n invocations.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercugmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~3.16\n > v = it.next().value\n ~3.11\n > v = it.next().value\n ~3.50\n\n See Also\n --------\n itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n > var it = itercuhmean( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n ~2.86\n > v = it.next().value\n ~2.90\n > v = it.next().value\n ~3.24\n\n See Also\n --------\n itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n Returns an iterator which iteratively computes a cumulative maximum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumax( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumaxabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumean( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.25\n\n See Also\n --------\n itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n 3.75\n\n See Also\n --------\n itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumeanabs2( arr );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n 15.75\n\n See Also\n --------\n itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n Returns an iterator which iteratively computes a cumulative mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumidrange( arr );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n Returns an iterator which iteratively computes a cumulative minimum value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercumin( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuminabs( arr );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n\n See Also\n --------\n itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n Returns an iterator which iteratively computes a cumulative product.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercuprod( arr );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -150.0\n\n See Also\n --------\n itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n Returns an iterator which iteratively computes a cumulative range.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercurange( arr );\n > var r = it.next().value\n 0.0\n > r = it.next().value\n 7.0\n > r = it.next().value\n 8.0\n > r = it.next().value\n 10.0\n\n See Also\n --------\n itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n Returns an iterator which iteratively computes a cumulative sum.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusum( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 5.0\n\n See Also\n --------\n itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs( arr );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 15.0\n\n See Also\n --------\n itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itercusumabs2( arr );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 63.0\n\n See Also\n --------\n itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: integer|string|Date\n Starting date either as a `Date` object, JavaScript timestamp, or a date\n string (inclusive).\n\n stop: integer|string|Date\n Stopping value either as a `Date` object, JavaScript timestamp, or a\n date string (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.round: string (optional)\n Specifies how sub-millisecond times should be rounded. Must be one of\n the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var t1 = new Date();\n > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n Returns an iterator which removes consecutive duplicated values.\n\n `NaN` values are considered distinct.\n\n Uniqueness is determined according to strict equality. Accordingly, objects\n are *not* checked for deep equality.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > var it = iterDedupe( arr );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n\n The provided function is provided five arguments:\n\n - curr: current source iterated value.\n - sprev: previous source iterated value.\n - dprev: previous downstream iterated value.\n - index: source iteration index (zero-based).\n - acc: previous resolved value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n limit: integer (optional)\n Number of allowed consecutive duplicates. Default: 1.\n\n fcn: Function\n Function indicating whether an iterated value is a \"duplicate\".\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n > function fcn( v ) { return v; };\n > var it = iterDedupeBy( arr, fcn );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 3\n\n See Also\n --------\n iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -360.0, 360.0 );\n > var it = iterDeg2rad( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n Returns an iterator which iteratively evaluates the digamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 5.0 );\n > var it = iterDigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n Returns an iterator which generates a Dirac comb.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracComb();\n > var v = it.next().value\n Infinity\n > v = it.next().value\n 0.0\n\n See Also\n --------\n iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterDiracDelta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterDivide( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 0.5\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterSubtract, iterMultiply\n","iterDoUntilEach":"\niterDoUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoWhileEach, iterUntilEach, iterWhileEach\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n The condition is evaluated *after* executing the provided function; thus,\n `fcn` *always* executes at least once.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipe( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.0, 1.0 );\n > var it = iterEllipk( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEmpty();\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterConstant\n","iterErf":"\niterErf( iterator )\n Returns an iterator which iteratively evaluates the error function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErf( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n\n The domain of inverse complementary error function is restricted to [0,2].\n If an iterated value is outside of the domain, the returned iterator returns\n `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n Returns an iterator which iteratively evaluates the inverse error function.\n\n The domain of inverse error function is restricted to [-1,1]. If an iterated\n value is outside of the domain, the returned iterator returns `NaN`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEta( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n Tests whether all iterated values are truthy.\n\n The function immediately returns upon encountering a falsy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is falsy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n > var bool = iterEvery( arr )\n false\n\n See Also\n --------\n iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a falsy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterEveryBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterExp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp2( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExp10( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterExpit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterExpm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -50.0, 50.0 );\n > var it = iterExpm1rel( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n Returns an iterator which iteratively evaluates the factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorial( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n Returns an iterator which generates a sequence of factorials.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFactorialsSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n Returns an iterator which generates a Fibonacci sequence.\n\n The returned iterator can only generate the first 79 Fibonacci numbers, as\n larger Fibonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fifth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1552.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFifthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 32\n\n See Also\n --------\n iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n replaces the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n value: any\n Static value.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n > var r = it.next().value\n 3.14\n > r = it.next().value\n 3.14\n > r = it.next().value\n \n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilter( it1, f );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n\n When invoked, the callback function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If the callback returns `undefined`, the iterator invokes the function for\n the next value of the provided iterator; otherwise, the iterator returns\n the callback's return value.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Callback function which both filters and maps.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterFilterMap( it1, f );\n > var v = it2.next().value\n 30\n > v = it2.next().value\n 40\n\n See Also\n --------\n iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n Returns the first iterated value.\n\n The function does *not* consume an entire iterator before returning.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The first iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n > var v = iterFirst( arr )\n 1\n\n See Also\n --------\n iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n Returns an iterator which generates a flat top pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFlatTopPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse\n","iterFloor":"\niterFloor( iterator )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n\n The methods argument should be an object which maps constructor method names\n to iterator functions.\n\n Each iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n When a fluent interface iterator method is invoked, the method invokes the\n corresponding iterator function with an iterator and provided method\n arguments.\n\n If an iterator function returns an iterator, the corresponding fluent\n interface method returns a new fluent interface instance; otherwise, the\n corresponding fluent interface method returns the iterator function result.\n\n The iterator function evaluation context is always `null`.\n\n Iterator functions which return iterators are expected to return iterator\n protocol-compliant objects (i.e., an object having a `next` method which\n returns the next iterated value (if one exists) assigned to a `value`\n property and a `done` property having a boolean value indicating whether the\n iterator is finished).\n\n If an environment supports `Symbol.iterator`, the returned constructor\n returns iterators which are iterable.\n\n Parameters\n ----------\n methods: Object\n An object mapping method names to iterator functions.\n\n Returns\n -------\n FluentIterator: Function\n Fluent interface iterator constructor.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n Returns a new fluent interface iterator from a source iterator.\n\n Parameters\n ----------\n iterator: Object\n Source iterator.\n\n Returns\n -------\n iterator: Object\n Fluent interface iterator.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var bool = it.head( 3 ).some( 2 )\n false\n\n\nFluentIterator.prototype.next()\n Returns the next iterated value.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > v = it2.next().value\n 0\n > v = it2.next().value\n 1\n\n\nFluentIterator.prototype.return( [value] )\n Finishes an iterator and returns a provided value.\n\n Parameters\n ----------\n value: any (optional)\n Value to return.\n\n Returns\n -------\n out: Object\n Iterator protocol-compliant object.\n\n out.value: any (optional)\n Next iterated value (if one exists).\n\n out.done: boolean\n Boolean flag indicating whether the iterator is finished.\n\n Examples\n --------\n > var o = {};\n > o.head = iterHead;\n > o.some = iterSome;\n > var fiter = iterFlow( o );\n > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n > var it2 = it1.head( 3 );\n > var v = it2.next().value\n 0\n > var bool = it2.return().done\n true\n > v = it2.next().value\n undefined\n\n See Also\n --------\n iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterForEach( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n Returns an iterator which generates a sequence of fourth powers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9741.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterFourthPowersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 16\n\n See Also\n --------\n iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnelc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterFresnels( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n Returns an iterator which iteratively evaluates the gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGamma( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterGamma1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterGammaln( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacovercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n Returns an iterator which iteratively computes the half-value coversed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHacoversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n Returns an iterator which generates a Hann pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHannPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n Returns an iterator which iteratively computes the half-value versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHavercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n Returns an iterator which iteratively computes the half-value versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterHaversin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n\n If a provided iterator only generates `m` values and `m` is less than `n`,\n the returned iterator only returns `m` values.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of values.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterHead( random.iterators.randu(), 5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (exclusive).\n\n increment: number (optional)\n Increment. Default: 1.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIncrspace( 0, 101, 2 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n Returns an iterator which generates an interleaved integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 18014398509481984.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n -1\n\n See Also\n --------\n iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n Returns an iterator which returns the intersection of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterIntersection( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n A returned iterator internally buffers unique hashes, along with the *first*\n iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n where `N` is the length of the first iterator.\n\n Do *not* provide iterators having infinite length.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > function f( v ) { return v.toString(); };\n > var it = iterIntersectionByHash( it1, it2, f );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n Returns an iterator which iteratively computes the multiplicative inverse.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterInv( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n Returns an iterator which generates a Lanczos pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 100.\n\n options.duration: integer (optional)\n Pulse duration. Must be greater than 2. Default: options.period.\n\n options.amplitude: number (optional)\n Amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLanczosPulse();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n Consumes an entire iterator and returns the last iterated value.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n v: any\n The last iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var v = iterLast( arr )\n 1\n\n See Also\n --------\n iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n Consumes an entire iterator and returns the number of iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n len: integer\n Iterator length.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var len = iterLength( arr )\n 5\n\n See Also\n --------\n iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number\n Stopping value (inclusive).\n\n N: integer (optional)\n Number of values. Default: 100.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLinspace( 0, 99, 100 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLn( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n Returns an iterator which iteratively computes the base `b` logarithm.\n\n For negative `b` or `x` iterated values, the returned iterator returns\n `NaN`.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n x: Object|number\n Input iterator.\n\n b: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 100.0 );\n > var y = random.iterators.uniform( 0.0, 10.0 );\n > var it = iterLog( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1mexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1p( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog1pexp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n Returns an iterator which iteratively evaluates the binary logarithm.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog2( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLog10( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n Returns an iterator which iteratively evaluates the logit function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 1.0 );\n > var it = iterLogit( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n\n In linear space, the sequence starts at `base` raised to the power of\n `start` and ends with `base` raised to the power of `stop`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Exponent of starting value.\n\n stop: number\n Exponent of stopping value.\n\n N: integer (optional)\n Number of values. Default: 100.\n\n options: Object (optional)\n Function options.\n\n options.base: number (optional)\n Base of log space. Default: 10.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLogspace( 0, 3, 4 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 10\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n Returns an iterator which generates a Lucas sequence.\n\n The returned iterator can only generate the first 77 Lucas numbers, as\n larger Lucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 1\n\n See Also\n --------\n base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value.\n\n When invoked, the input function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return v * 10.0; };\n > var it = iterMap( random.iterators.randu(), f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n\n When invoked, the callback function is provided `N+1` arguments, where `N`\n is the number of provided iterators and the last argument is the iteration\n index:\n\n - ...value: iterated values.\n - index: iteration index (zero-based).\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators.\n\n fcn: Function\n Function to invoke with iterated values.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > function fcn( x, y ) { return x + y; };\n > var it = iterMapN( it1, it2, fcn );\n > var v = it.next().value\n 4.0\n > v = it.next().value\n 6.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterMap\n","itermax":"\nitermax( iterator )\n Computes the maximum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermax( arr )\n 3.0\n\n See Also\n --------\n itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n Computes the maximum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Maximum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = itermaxabs( arr )\n 4.0\n\n See Also\n --------\n itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n Computes an arithmetic mean over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var m = itermean( arr )\n 2.5\n\n See Also\n --------\n itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n Computes an arithmetic mean of absolute values for all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs( arr )\n 2.5\n\n See Also\n --------\n itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Arithmetic mean of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermeanabs2( arr )\n 7.5\n\n See Also\n --------\n itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n Computes the mid-range of all iterated values.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Mid-range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = itermidrange( arr )\n -0.5\n\n See Also\n --------\n itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n Computes the minimum value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n > var m = itermin( arr )\n -3.0\n\n See Also\n --------\n itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n Computes the minimum absolute value of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Minimum absolute value.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var m = iterminabs( arr )\n 1.0\n\n See Also\n --------\n itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n Returns an iterator which iteratively computes a moving maximum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmax( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving maximum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmaxabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n > m = it.next().value\n 5.0\n\n See Also\n --------\n itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmean( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -1.5\n > m = it.next().value\n 0.0\n > m = it.next().value\n 1.0\n\n See Also\n --------\n itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 3.5\n > m = it.next().value\n ~3.33\n > m = it.next().value\n ~4.33\n\n See Also\n --------\n itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mean of squared absolute values.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmeanabs2( arr, 3 );\n > var m = it.next().value\n 4.0\n > m = it.next().value\n 14.5\n > m = it.next().value\n ~12.67\n > m = it.next().value\n ~19.67\n\n See Also\n --------\n itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n Returns an iterator which iteratively computes a moving mid-range.\n\n The mid-range is the arithmetic mean of maximum and minimum values.\n Accordingly, the mid-range is the midpoint of the range and a measure of\n central tendency.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving mid-range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmidrange( arr, 3 );\n > var v = it.next().value\n 2.0\n > v = it.next().value\n -1.5\n > v = it.next().value\n -1.0\n > v = it.next().value\n 0.0\n\n See Also\n --------\n itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n Returns an iterator which iteratively computes a moving minimum value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermmin( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n > m = it.next().value\n -5.0\n\n See Also\n --------\n itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving minimum absolute value.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermminabs( arr, 3 );\n > var m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 2.0\n > m = it.next().value\n 3.0\n\n See Also\n --------\n iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators whose values are used as divisors.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 3.0, 2.0 ] );\n > var it2 = array2iterator( [ 1.0, 4.0 ] );\n > var it = iterMod( it1, it2 );\n > var v = it.next().value\n 0.0\n > v = it.next().value\n 2.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterDivide\n","itermprod":"\nitermprod( iterator, W )\n Returns an iterator which iteratively computes a moving product.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving product.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermprod( arr, 3 );\n > var p = it.next().value\n 2.0\n > p = it.next().value\n -10.0\n > p = it.next().value\n -30.0\n > p = it.next().value\n -75.0\n\n See Also\n --------\n itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n Returns an iterator which iteratively computes a moving range.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving range.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermrange( arr, 3 );\n > var m = it.next().value\n 0.0\n > m = it.next().value\n 7.0\n > m = it.next().value\n 8.0\n > m = it.next().value\n 10.0\n\n See Also\n --------\n itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n Returns an iterator which iteratively computes a moving sum.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator and the provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsum( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n -3.0\n > s = it.next().value\n 0.0\n > s = it.next().value\n 3.0\n\n See Also\n --------\n itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs( arr, 3 );\n > var s = it.next().value\n 2.0\n > s = it.next().value\n 7.0\n > s = it.next().value\n 10.0\n > s = it.next().value\n 13.0\n\n See Also\n --------\n itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n\n The `W` parameter defines the number of iterated values over which to\n compute the moving sum.\n\n As `W` values are needed to fill the window buffer, the first `W-1` returned\n values are calculated from smaller sample sizes. Until the window is full,\n each returned value is calculated from all previously iterated values.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n W: integer\n Window size.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n > var it = itermsumabs2( arr, 3 );\n > var s = it.next().value\n 4.0\n > s = it.next().value\n 29.0\n > s = it.next().value\n 38.0\n > s = it.next().value\n 59.0\n\n See Also\n --------\n itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to multiply.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 2.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterMultiply( it1, it2 );\n > var v = it.next().value\n 3.0\n > v = it.next().value\n 8.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n Returns an iterator which generates a negaFibonacci sequence.\n\n The returned iterator can only generate the first 79 negaFibonacci numbers,\n as larger negaFibonacci numbers cannot be safely represented in double-\n precision floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 79.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaFibonacciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n Returns an iterator which generates a negaLucas sequence.\n\n The returned iterator can only generate the first 77 negaLucas numbers, as\n larger negaLucas numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 77.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegaLucasSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n -1\n\n See Also\n --------\n base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeEvenIntegersSeq();\n > var v = it.next().value\n -2\n > v = it.next().value\n -4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n Returns an iterator which generates a negative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -2\n\n See Also\n --------\n iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of negative odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNegativeOddIntegersSeq();\n > var v = it.next().value\n -1\n > v = it.next().value\n -3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n Tests whether all iterated values are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n Returns\n -------\n bool: boolean\n The function returns `false` if a value is truthy; otherwise, the\n function returns `true`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n > var bool = iterNone( arr )\n false\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an iterator which does not return any iterated values, the\n function returns `true`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a falsy\n value for all iterated values. Otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n > function fcn( v ) { return ( v <= 0 ); };\n > var bool = iterNoneBy( arr, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonFibonacciSeq();\n > var v = it.next().value\n 4\n > v = it.next().value\n 6\n\n See Also\n --------\n base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n Returns an iterator which generates a nonnegative integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonNegativeIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370497.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveEvenIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -2\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n Returns an iterator which generates a nonpositive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonPositiveIntegersSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n -1\n\n See Also\n --------\n iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n Returns an iterator which generates a sequence of nonsquares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199349647256.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterNonSquaresSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n Returns the nth iterated value.\n\n If `n` exceeds the total number of iterations, the function returns\n `undefined`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Iteration number.\n\n Returns\n -------\n v: any\n The nth iterated value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n > var v = iterNth( arr, 3 )\n 1\n\n See Also\n --------\n iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740992.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n -1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n Returns an iterator which generates a periodic sinc waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Order.\n\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 100.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPeriodicSinc( 7 );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n Returns an iterator pipeline.\n\n Parameters\n ----------\n iterFcn: Function|Array\n Iterator function or an array of iterator functions.\n\n iterFcn: ...Function (optional)\n Iterator functions.\n\n Returns\n -------\n fcn( src ): Function\n Iterator pipeline which accepts a single argument, a source iterator.\n\n Examples\n --------\n > var it1 = iterThunk( iterHead, 100 );\n > function f( r ) { return ( r > 0.95 ); };\n > var it2 = iterThunk( iterSomeBy, 5, f );\n > var p = iterPipeline( it1, it2 );\n > var bool = p( random.iterators.randu() )\n \n\n See Also\n --------\n iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the last value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPop( it1 );\n > var v = it2.next().value\n 1\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive even integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveEvenIntegersSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 4\n\n See Also\n --------\n iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n Returns an iterator which generates a positive integer sequence.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 9007199254740991.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n Returns an iterator which generates a sequence of positive odd integers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 4503599627370496.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPositiveOddIntegersSeq();\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n Returns an iterator which iteratively evaluates the exponential function.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n base: Object|number\n Input iterator.\n\n exponent: Object|number\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = random.iterators.uniform( 0.0, 2.0 );\n > var y = random.iterators.uniform( -2.0, 2.0 );\n > var it = iterPow( x, y );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n Returns an iterator which generates a sequence of prime numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 245181918813464.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPrimesSeq();\n > var v = it.next().value\n 2\n > v = it.next().value\n 3\n > v = it.next().value\n 5\n\n See Also\n --------\n iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n Computes the product of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Product.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = iterprod( arr )\n 24.0\n\n See Also\n --------\n itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n Returns an iterator which generates a pulse waveform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Pulse period (i.e., the number of iterations until a waveform repeats).\n Default: 10.\n\n options.duration: integer (optional)\n Pulse duration (i.e., the number of consecutive iterations of maximum\n amplitude during one period). Default: floor(options.period/2).\n\n options.min: number (optional)\n Minimum amplitude. Default: 0.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterPulse();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to append.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterPush( it1, 3, 4 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterRad2deg( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n Returns an iterator which iteratively evaluates the ramp function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRamp( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.ramp\n","iterrange":"\niterrange( iterator )\n Computes the range of all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Range.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var v = iterrange( arr )\n 7.0\n\n See Also\n --------\n itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n\n When invoked, the predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Predicate function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function f( v ) { return ( v > 2 ); };\n > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n > var it2 = iterReject( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n Returns an iterator which replicates each iterated value `n` times.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n n: integer\n Number of times each iterated value is replicated.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > var it2 = iterReplicate( it1, 2 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n\n See Also\n --------\n iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n\n The callback function is provided three arguments:\n\n - value: iterated value.\n - index: source iteration index (zero-based).\n - n: iteration index (zero-based).\n\n The callback function is invoked *once* per iterated value of the provided\n iterator.\n\n The callback function *must* return an integer value. If the return value is\n less than or equal to zero, the returned iterator skips an iterated value\n and invokes the callback for the next iterated value of the provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Function which returns the number of times an iterated value should be\n replicated.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n > function f( v, i ) { return i + 1; };\n > var it2 = iterReplicateBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 2\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 3\n > v = it2.next().value\n 4\n\n See Also\n --------\n iterReplicate\n","iterRound":"\niterRound( iterator )\n Returns an iterator which rounds each iterated value to the nearest integer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterRsqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n Returns an iterator which generates a sawtooth wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSawtoothWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n Returns an iterator which skips the first value of a provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n clbk: Function (optional)\n Callback to invoke with the skipped value.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterShift( it1 );\n > var v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n Returns an iterator which iteratively evaluates the signum function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSignum( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.signum\n","iterSin":"\niterSin( iterator )\n Returns an iterator which iteratively computes the sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSin( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinc( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n Returns an iterator which generates a sine wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a sine wave repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSineWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -5.0, 5.0 );\n > var it = iterSinh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n Returns an iterator which computes the sine of each iterated value times π.\n\n Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSinpi( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n\n If `end` exceeds the length of the provided iterator, the returned iterator\n returns the subsequence of iterated values starting from `begin` until the\n last iterated value of the provided iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n begin: integer (optional)\n Start iteration index (zero-based and inclusive). Default: 0.\n\n end: integer (optional)\n End iteration index (zero-based and non-inclusive).\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSlice( random.iterators.randu(), 5, 10 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n Tests whether at least `n` iterated values are truthy.\n\n The function immediately returns upon finding `n` truthy values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an iterator returns at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = iterSome( arr, 3 )\n true\n\n See Also\n --------\n iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n\n The predicate function is provided two arguments:\n\n - value: iterated value.\n - index: iteration index.\n\n The function immediately returns upon encountering `n` truthy return values.\n\n If provided an iterator which does not return any iterated values, the\n function returns `false`.\n\n Parameters\n ----------\n iterator: Object\n Input iterator over which to iterate.\n\n n: integer\n Minimum number of successful values.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a predicate function returns a truthy\n value for at least `n` iterated values. Otherwise, the function returns\n `false`.\n\n Examples\n --------\n > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n > function fcn( v ) { return ( v > 0 ); };\n > var bool = iterSomeBy( arr, 3, fcn )\n true\n\n See Also\n --------\n iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n Returns an iterator which iteratively evaluates Spence's function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSpence( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.spence\n","iterSqrt":"\niterSqrt( iterator )\n Returns an iterator which iteratively computes the principal square root.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSqrt( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 100.0 );\n > var it = iterSqrt1pm1( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 11585.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaredTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 9\n\n See Also\n --------\n iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n Returns an iterator which generates a sequence of squares.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 94906265.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquaresSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 4\n\n See Also\n --------\n iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n Returns an iterator which generates a square wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a square wave repeats).\n This must be an even integer in order to ensure a 50% duty cycle.\n Default: 10.\n\n options.min: number (optional)\n Minimum amplitude. Default: -1.0.\n\n options.max: number (optional)\n Maximum amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterSquareWave();\n > var v = it.next().value\n 1.0\n > v = it.next().value\n 1.0\n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n Computes a correct sample standard deviation over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Corrected sample standard deviation.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var m = iterstdev( arr )\n ~4.95\n\n See Also\n --------\n itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n\n Beware that values which follow the starting value are subject to floating-\n point rounding errors.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n increment: number\n Increment.\n\n N: number (optional)\n Number of values. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterStep( 0, 2, 10 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n Returns an iterator which steps by a specified amount.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n stride: integer\n Stride (i.e., step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > var it = iterStrided( arr, 2, 1 );\n > var r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n Returns an iterator which steps according to a provided callback function.\n\n When invoked, the input function is provided four arguments:\n\n - value: iterated value.\n - i: input iteration index (zero-based).\n - n: output (strided) iteration index (zero-based).\n - curr: current stride.\n\n The return value of the input function specifies the next stride.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n fcn: Function\n Stride function (i.e., a function which returns the step amount).\n\n offset: integer (optional)\n Index of the first iterated value. Default: 0.\n\n eager: boolean (optional)\n Boolean indicating whether to eagerly advance the input iterator when\n provided a non-zero offset. Default: false.\n\n thisArg: any (optional)\n Stride function execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n > function stride( v, i ) { return (i % 10)+1; };\n > var it = iterStridedBy( arr, stride );\n > var r = it.next().value\n 0\n > r = it.next().value\n 1\n > r = it.next().value\n 3\n\n See Also\n --------\n iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n\n The length of the returned iterator is equal to the length of the shortest\n provided iterator. In other words, the returned iterator ends once *one* of\n the provided iterators ends.\n\n If provided a numeric value as an iterator argument, the value is broadcast\n as an infinite iterator which always returns the provided value.\n\n If an environment supports Symbol.iterator and provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Iterators to subtract.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1.0, 5.0 ] );\n > var it2 = array2iterator( [ 3.0, 4.0 ] );\n > var it = iterSubtract( it1, it2 );\n > var v = it.next().value\n -2.0\n > v = it.next().value\n 1.0\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n Computes the sum of all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum.\n\n Examples\n --------\n > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var s = itersum( arr )\n 10.0\n\n See Also\n --------\n itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n Computes the sum of absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs( arr )\n 10.0\n\n See Also\n --------\n itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n Computes the sum of squared absolute values for all iterated values.\n\n For iterators which can generate many values or which may output large\n numbers, care should be taken to prevent overflow.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n out: number|null\n Sum of squared absolute values.\n\n Examples\n --------\n > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n > var s = itersumabs2( arr )\n 30.0\n\n See Also\n --------\n itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n Returns an iterator which iteratively evaluates the tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -1.57, 1.57 );\n > var it = iterTan( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( -4.0, 4.0 );\n > var it = iterTanh( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n Returns an iterator \"thunk\".\n\n A provided iterator function should have the following function signature:\n\n iterFcn( iterator, ...args )\n\n The returned function expects a single argument, an iterator.\n\n This function is useful within the context of iterator pipelines as a means\n to defer execution until a pipeline is ready for data flow.\n\n Parameters\n ----------\n iterFcn: Function\n Iterator function.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n fcn( iter ): Function\n Function which accepts a single argument, an iterator, and invokes a\n previously provided iterator function with the provided iterator and any\n previously provided arguments.\n\n Examples\n --------\n > var fcn = iterThunk( iterSome, 3 );\n > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n > var bool = fcn( arr )\n true\n\n See Also\n --------\n iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n Returns an iterator which generates a triangle wave.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.period: integer (optional)\n Period (i.e., the number of iterations before a waveform repeats).\n Default: 10.\n\n options.amplitude: number (optional)\n Peak amplitude. Default: 1.0.\n\n options.offset: integer (optional)\n Phase offset (in units of iterations; zero-based). A negative offset\n translates the waveform to the left. A positive offset translates a\n waveform to the right. Default: 0.\n\n options.iter: integer (optional)\n Number of iterations. Default: 1e308.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangleWave();\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n Returns an iterator which generates a sequence of triangular numbers.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 134217727.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTriangularSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.iter: integer (optional)\n Number of iterations. Default: 64.\n\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant\n object has the next\n iterated value (if one exists) and a\n boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n\n Examples\n --------\n > var it = iterTribonnaciSeq();\n > var v = it.next().value\n 0\n > v = it.next().value\n 0\n\n See Also\n --------\n base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n Returns an iterator which iteratively evaluates the trigamma function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.01, 50.0 );\n > var it = iterTrigamma( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n Returns an iterator which rounds each iterated value toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc( random.iterators.randu() );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n Returns an iterator which returns the union of two or more iterators.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements, where `N` is the total number of source iterator\n values.\n\n If an environment supports Symbol.iterator and all provided iterators are\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iter0: Object\n Input iterator.\n\n iterator: ...Object\n Input iterators.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n > var it = iterUnion( it1, it2 );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n > v = it.next().value\n 4\n > v = it.next().value\n 5\n > v = it.next().value\n 3\n > var bool = it.next().done\n true\n\n See Also\n --------\n iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n Returns an iterator which returns unique values.\n\n Value \"uniqueness\" is determined according to strict equality.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > var it2 = iterUnique( it1 );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n Returns an iterator which returns unique values according to a predicate\n function.\n\n A returned iterator internally buffers unique values and, thus, has O(N)\n memory requirements.\n\n A predicate function is invoked for each iterated value against each value\n in an internal buffer consisting of previously identified unique values.\n Thus, as the number of unique values grows, so, too, does the number of\n predicate function invocations per iterated value.\n\n An iterated value is considered \"unique\" if the predicate function returns\n truthy values for all comparisons of the iterated value with each value in\n the internal buffer.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n A binary function with parameters `a` and `b` corresponding to iterated\n values. If the values are the same, the function should return `false`\n (i.e., non-unique); otherwise, if the values are distinct, the function\n should return `true` (i.e., unique).\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( a, b ) { return ( a !== b ); };\n > var it2 = iterUniqueBy( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n Returns an iterator which returns unique values according to a hash\n function.\n\n A returned iterator internally buffers unique hashes and, thus, has O(N)\n memory requirements.\n\n An iterated value is considered \"unique\" if the hash function returns a\n unique hash value for that iterated value. Beware that this *may* result in\n unexpected behavior. Namely, only the first iterated value mapping to a\n particular hash function result is returned, even if subsequent values,\n while mapping to the same hash, are different. Accordingly, iteration order\n *does* matter.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n hashFcn: Function\n Hash function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n > function f( v ) { return v.toString(); };\n > var it2 = iterUniqueByHash( it1, f );\n > var v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > v = it2.next().value\n 4\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n Returns an iterator which returns numbers incremented by one.\n\n The iterator stops once the `stop` value is exceeded.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n start: number\n Starting value (inclusive).\n\n stop: number (optional)\n Stopping value. Default: +infinity.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = iterUnitspace( 0, 99 );\n > var v = it.next().value\n 0\n > v = it.next().value\n 1\n\n See Also\n --------\n iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n items: ...any\n Items to prepend.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it1 = array2iterator( [ 1, 2 ] );\n > var it2 = iterUnshift( it1, 3, 4 );\n > var v = it2.next().value\n 3\n > v = it2.next().value\n 4\n > v = it2.next().value\n 1\n > v = it2.next().value\n 2\n > var bool = it2.next().done\n true\n\n See Also\n --------\n iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v !== v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n Computes an unbiased sample variance over all iterated values.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n mean: number (optional)\n Known mean.\n\n Returns\n -------\n out: number|null\n Unbiased sample variance.\n\n Examples\n --------\n > var arr = array2iterator( [ 2.0, -5.0 ] );\n > var s2 = itervariance( arr )\n 24.5\n\n See Also\n --------\n itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n Returns an iterator which iteratively computes the versed cosine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVercos( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n Returns an iterator which iteratively computes the versed sine.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 0.0, 6.28 );\n > var it = iterVersin( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n\n When invoked, both input functions are provided two arguments:\n\n - value: iterated value.\n - index: iteration index (zero-based).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n predicate: Function\n Function which indicates whether to continue iterating.\n\n fcn: Function\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > function predicate( v ) { return v === v };\n > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var r = random.iterators.uniform( 1.1, 50.0 );\n > var it = iterZeta( r );\n > var v = it.next().value\n \n > v = it.next().value\n \n\n See Also\n --------\n base.zeta\n","joinStream":"\njoinStream( [options] )\n Returns a transform stream which joins streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = joinStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n Returns a function for creating transform streams for joined streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = joinStream.factory( opts );\n > var s = createStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to join streamed data. Default: '\\n'.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.readableObjectMode: boolean (optional)\n Specifies whether the readable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = joinStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n See Also\n --------\n splitStream","kde2d":"\nkde2d( x, y[, options] )\n Two-dimensional kernel density estimation.\n\n Parameters\n ----------\n x: Array\n Array of x values.\n\n y: Array\n Array of y values.\n\n options: Object (optional)\n Function options.\n\n options.h: number (optional)\n Array of length two containing the bandwidth values for x and y.\n\n options.n: number (optional)\n Number of partitions on the x- and y-axes. Default: `25`.\n\n options.xMin: number (optional)\n Lower limit of x.\n\n options.xMax: number (optional)\n Upper limit of x.\n\n options.yMin: number (optional)\n Lower limit of y.\n\n options.yMax: number (optional)\n Upper limit of y.\n\n options.kernel: string|Function\n A string or function to specifying the used kernel function. Default:\n `'gaussian'`.\n\n Returns\n -------\n out: Object\n Object containing the density estimates (`z`) along grid points (`x` and\n `y` values).\n\n Examples\n --------\n > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n > var out = kde2d( x, y )\n { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n Converts a string to kebab case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Kebab-cased string.\n\n Examples\n --------\n > var out = kebabcase( 'Hello World!' )\n 'hello-world'\n > out = kebabcase( 'I am a tiny little teapot' )\n 'i-am-a-tiny-little-teapot'\n\n See Also\n --------\n camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyBy( arr, toKey )\n { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n See Also\n --------\n forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n\n When invoked, the input function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n If more than one element in a collection resolves to the same key, the key\n value is the collection element which last resolved to the key.\n\n Object values are shallow copies.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > function toKey( v ) { return v.a; };\n > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n > keyByRight( arr, toKey )\n { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n See Also\n --------\n forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n Returns an array of an object's own and inherited enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = keysIn( obj )\n e.g., [ 'beep', 'foo' ]\n\n See Also\n --------\n objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n Computes the Kruskal-Wallis test for equal medians.\n\n Parameters\n ----------\n x: ...Array\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Object\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = kruskalTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n is computed for the null hypothesis that the values of `x` come from the\n distribution specified by `y`. `y` can be either a string with the name of\n the distribution to test against, or a function.\n\n In the latter case, `y` is expected to be the cumulative distribution\n function (CDF) of the distribution to test against, with its first parameter\n being the value at which to evaluate the CDF and the remaining parameters\n constituting the parameters of the distribution. The parameters of the\n distribution are passed as additional arguments after `y` from `kstest` to\n the chosen CDF. The function returns an object holding the calculated test\n statistic `statistic` and the `pValue` of the test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the hypothesis test results.\n\n Parameters\n ----------\n x: Array\n Input array holding numeric values.\n\n y: Function|string\n Either a CDF function or a string denoting the name of a distribution.\n\n params: ...number (optional)\n Distribution parameters passed to reference CDF.\n\n options: Object (optional)\n Function options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array is already in sorted order.\n Default: `false`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that the true distribution of `x` is not equal\n to the reference distribution specified by `y` (`two-sided`), whether it\n is `less` than the reference distribution or `greater` than the\n reference distribution. Default: `'two-sided'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.alternative: string\n Used test alternative. Either `two-sided`, `less` or `greater`.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Verify that data is drawn from a normal distribution:\n > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n // Test against N(0,1)\n > var out = kstest( x, 'normal', 0.0, 1.0 )\n { pValue: 0.0, statistic: 0.847, ... }\n\n // Test against N(3,1)\n > out = kstest( x, 'normal', 3.0, 1.0 )\n { pValue: 0.6282, statistic: 0.0733, ... }\n\n // Verify that data is drawn from a uniform distribution:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0 )\n { pValue: ~0.703, statistic: ~0.069, ... }\n\n // Print output:\n > out.print()\n Kolmogorov-Smirnov goodness-of-fit test.\n\n Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n pValue: 0.7039\n statistic: 0.0689\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Set custom significance level:\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n { pValue: ~0.7039, statistic: ~0.069, ... }\n\n // Carry out one-sided hypothesis tests:\n > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n { pValue: ~0.358, statistic: ~0.07, ... }\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n { pValue: ~0.907, statistic: ~0.02, ... }\n\n // Set `sorted` option to true when data is in increasing order:\n > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n Returns the last character(s) of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to return. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var out = last( 'beep' )\n 'p'\n > out = last( 'Boop', 2 )\n 'op'\n > out = last( 'foo bar', 3 )\n 'bar'\n\n See Also\n --------\n firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n Computes Levene's test for equal variances.\n\n Parameters\n ----------\n x: Array\n Measured values.\n\n y: ...Array (optional)\n Measured values.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.groups: Array (optional)\n Array of group indicators.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.method: string\n Name of test.\n\n out.df: Array\n Degrees of freedom.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Data from Hollander & Wolfe (1973), p. 116:\n > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n > var out = leveneTest( x, y, z )\n\n > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n ... 3.8, 2.7, 4.0, 2.4,\n ... 2.8, 3.4, 3.7, 2.2, 2.0\n ... ];\n > var groups = [\n ... 'a', 'a', 'a', 'a', 'a',\n ... 'b', 'b', 'b', 'b',\n ... 'c', 'c', 'c', 'c', 'c'\n ... ];\n > out = leveneTest( arr, { 'groups': groups } )\n\n See Also\n --------\n vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n\n Returns\n -------\n list: Object\n Linked list.\n\n list.clear: Function\n Clears the list.\n\n list.first: Function\n Returns the last node. If the list is empty, the returned value is\n `undefined`.\n\n list.insert: Function\n Inserts a value after a provided list node.\n\n list.iterator: Function\n Returns an iterator for iterating over a list. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from list mutation during\n iteration, a returned iterator **always** iterates over a list\n \"snapshot\", which is defined as the list of list elements at the time\n of the method's invocation.\n\n list.last: Function\n Returns the last list node. If the list is empty, the returned value is\n `undefined`.\n\n list.length: integer\n List length.\n\n list.pop: Function\n Removes and returns the last list value. If the list is empty, the\n returned value is `undefined`.\n\n list.push: Function\n Adds a value to the end of the list.\n\n list.remove: Function\n Removes a list node from the list.\n\n list.shift: Function\n Removes and returns the first list value. If the list is empty, the\n returned value is `undefined`.\n\n list.toArray: Function\n Returns an array of list values.\n\n list.toJSON: Function\n Serializes a list as JSON.\n\n list.unshift: Function\n Adds a value to the beginning of the list.\n\n Examples\n --------\n > var list = LinkedList();\n > list.push( 'foo' ).push( 'bar' );\n > list.length\n 2\n > list.pop()\n 'bar'\n > list.length\n 1\n > list.pop()\n 'foo'\n > list.length\n 0\n\n See Also\n --------\n DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n Generates a linearly spaced array over a specified interval.\n\n If the specified length is zero, the function returns an empty array.\n\n If the specified length is one, the function returns an array containing\n `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n returns an array containing `start`, but not `stop`.\n\n For real-valued `start` and `stop`, if `start` is less than `stop`, the\n output array will contain ascending values, and, if `start` is greater than\n `stop`, the output array will contain descending values.\n\n When the output array length is greater than one and `endpoint` is true, the\n output array is guaranteed to include the `start` and `stop` values. Beware,\n however, that values between `start` and `stop` are subject to floating-\n point rounding errors.\n\n If both `start` and `stop` are real-valued, the output array data type may\n be any floating-point data type or 'generic'. However, if either `start` or\n `stop` are complex numbers, the output array type must be a complex\n floating-point data type or 'generic'.\n\n When writing to a complex floating-point output array, real-valued `start`\n and `stop` values are treated as complex numbers having a real component\n equaling the provided value and having an imaginary component equaling zero.\n\n When generating linearly spaced complex floating-point numbers, the real and\n imaginary components are generated separately.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n length: integer\n Length of output array.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Must be a floating-point data type or 'generic'.\n If both `start` and `stop` are the same type (either 'float64',\n 'complex64', or 'complex128'), the default output array data type is\n the same type as the input values (either 'float64', 'complex64', or\n 'complex128', respectively). Otherwise, the default output array data\n type is 'complex128'.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `length + 1` linearly spaced\n values over the interval `[start, stop]` and only writes `length` values\n to the output array, thus excluding `stop` from the output array.\n Accordingly, for a fixed `length`, the spacing between adjacent values\n in the output array changes depending on the value of `endpoint`.\n Default: true.\n\n Returns\n -------\n arr: Array\n Linearly spaced array.\n\n Examples\n --------\n > var arr = linspace( 0.0, 100.0, 6 )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n\n If the provided output array is empty, the function returns the provided\n output array unchanged.\n\n If the provided output array contains a single element, the function writes\n the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n function writes the `start` value, but not `stop`.\n\n Parameters\n ----------\n start: number|ComplexLike\n Start of interval.\n\n stop: number|ComplexLike\n End of interval.\n\n out: ArrayLikeObject\n Output array.\n\n options: Object (optional)\n Options.\n\n options.endpoint: boolean (optional)\n Boolean indicating whether to include the `stop` value in the output\n array. If false, the function generates `N+1` linearly spaced values\n (where `N` is the length of the provided output array) over the interval\n `[start, stop]` and only writes `N` values to the output array, thus\n excluding `stop` from the output array. Accordingly, for a fixed `N`,\n the spacing between adjacent values in the output array changes\n depending on the value of `endpoint`. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0, 0 ];\n > var out = linspace.assign( 0, 100, arr )\n [ 0, 20, 40, 60, 80, 100 ]\n > var bool = ( arr === out )\n true\n > arr = [ 0, 0, 0, 0, 0 ];\n > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n [ 0, 20, 40, 60, 80 ]\n\n See Also\n --------\n incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of negative opinion words.\n\n Examples\n --------\n > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n\n A word's appearance in a sentence does *not* necessarily imply a positive or\n negative opinion.\n\n The list includes misspelled words. Their presence is intentional, as such\n misspellings frequently occur in social media content.\n\n Returns\n -------\n out: Array\n List of positive opinion words.\n\n Examples\n --------\n > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n References\n ----------\n - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n ACM. doi:10.1145/1014052.1014073.\n - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n USA: ACM. doi:10.1145/1060745.1060797.\n\n * If you use the list for publication or third party consumption, please\n cite one of the listed references.\n\n See Also\n --------\n LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n\n Examples\n --------\n > LN_HALF\n -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n\n Examples\n --------\n > LN_PI\n 1.1447298858494002\n\n See Also\n --------\n PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n\n Examples\n --------\n > LN_SQRT_TWO_PI\n 0.9189385332046728\n\n See Also\n --------\n PI\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n\n Examples\n --------\n > LN_TWO_PI\n 1.8378770664093456\n\n See Also\n --------\n TWO_PI\n","LN2":"\nLN2\n Natural logarithm of `2`.\n\n Examples\n --------\n > LN2\n 0.6931471805599453\n\n See Also\n --------\n LN10\n","LN10":"\nLN10\n Natural logarithm of `10`.\n\n Examples\n --------\n > LN10\n 2.302585092994046\n\n See Also\n --------\n LN2\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n\n Examples\n --------\n > LOG2E\n 1.4426950408889634\n\n See Also\n --------\n E, LOG10E\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n\n Examples\n --------\n > LOG10E\n 0.4342944819032518\n\n See Also\n --------\n E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n If a `length` is not provided, the default output array length is `10`.\n\n The output array includes the values `10^a` and `10^b`.\n\n Parameters\n ----------\n a: number\n Exponent of start value.\n\n b: number\n Exponent of end value.\n\n length: integer (optional)\n Length of output array. Default: `10`.\n\n Returns\n -------\n arr: Array\n Logarithmically spaced numeric array.\n\n Examples\n --------\n > var arr = logspace( 0, 2, 6 )\n [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n See Also\n --------\n incrspace, linspace\n","lowercase":"\nlowercase( str )\n Converts a string to lowercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Lowercase string.\n\n Examples\n --------\n > var out = lowercase( 'bEEp' )\n 'beep'\n\n See Also\n --------\n uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n Converts each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'A': 1, 'B': 2 };\n > var out = lowercaseKeys( obj )\n { 'a': 1, 'b': 2 }\n\n See Also\n --------\n uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n\n Parameters\n ----------\n x: Array\n x-axis values (abscissa values).\n\n y: Array\n Corresponding y-axis values (ordinate values).\n\n options: Object (optional)\n Function options.\n\n options.f: number (optional)\n Positive number specifying the smoothing span, i.e., the proportion of\n points which influence smoothing at each value. Larger values\n correspond to more smoothing. Default: `2/3`.\n\n options.nsteps: number (optional)\n Number of iterations in the robust fit (fewer iterations translates to\n faster function execution). If set to zero, the nonrobust fit is\n returned. Default: `3`.\n\n options.delta: number (optional)\n Nonnegative number which may be used to reduce the number of\n computations. Default: 1/100th of the range of `x`.\n\n options.sorted: boolean (optional)\n Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n Returns\n -------\n out: Object\n Object with ordered x-values and fitted values.\n\n Examples\n --------\n > var x = new Float64Array( 100 );\n > var y = new Float64Array( x.length );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = i;\n ... y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n ... }\n > var out = lowess( x, y );\n > var yhat = out.y;\n\n > var h = Plot( [ x, x ], [ y, yhat ] );\n > h.lineStyle = [ 'none', '-' ];\n > h.symbols = [ 'closed-circle', 'none' ];\n\n > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = lpad( 'a', 5 )\n ' a'\n > out = lpad( 'beep', 10, 'b' )\n 'bbbbbbbeep'\n > out = lpad( 'boop', 12, 'beep' )\n 'beepbeepboop'\n\n See Also\n --------\n pad, rpad\n","ltrim":"\nltrim( str )\n Trims whitespace from the beginning of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrim( ' \\r\\n\\t Beep \\t\\t\\n ' )\n 'Beep \\t\\t\\n '\n\n See Also\n --------\n trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n Trims `n` characters from the beginning of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = ltrimN( ' abc ', 2 )\n 'abc '\n > var out = ltrimN( '!!!abc!!!', 2, '!' )\n '!abc!!!'\n\n See Also\n --------\n rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n\n Returns\n -------\n out: Array\n List of common male first names.\n\n Examples\n --------\n > var list = MALE_FIRST_NAMES_EN()\n [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n References\n ----------\n - Ward, Grady. 2002. 'Moby Word II.' .\n\n See Also\n --------\n FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = map( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = map( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n > var out = map2d( arr, f );\n > out[ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Input arrays must be either both array-like objects or both ndarray-like\n objects.\n\n If input arrays are array-like objects, the arrays must have the same number\n of elements.\n\n If input arrays are ndarray-like objects, the arrays must be broadcast\n compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = map2Right( x, y, f )\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > x = array( x, { 'shape': [ 2, 3 ] } );\n > y = array( y, { 'shape': [ 2, 3 ] } );\n > out = map2Right( x, y, f );\n > var v = out.get( 1, 1 )\n 6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n\n The applied function is provided the following arguments:\n\n - v1: element from first input array.\n - v2: element from second input array.\n - idx: element index.\n - arrays: input arrays.\n\n Input and output arrays must be either all array-like objects or all\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are ndarray-like objects, the arrays must be\n broadcast compatible.\n\n Parameters\n ----------\n x: ArrayLikeObject|ndarray\n First input array.\n\n y: ArrayLikeObject|ndarray\n Second input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var y = [ 1, 1, 1, 1, 1, 1 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > map2Right.assign( x, y, out, f );\n > out\n [ 2, 3, 4, 5, 6, 7 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > x = array( x, opts );\n > y = array( y, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > map2Right.assign( x, y, out, f );\n > var v = out.get( 1, 1 )\n 6\n\n See Also\n --------\n mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject>\n Input three-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>\n Three-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n > var out = map3d( arr, f );\n > out[ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input four-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>\n Four-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n > var out = map4d( arr, f );\n > out[ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input five-dimensional nested array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array>>>\n Five-dimensional nested array.\n\n Examples\n --------\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n > var out = map5d( arr, f );\n > out[ 0 ][ 0 ][ 0 ][ 0 ]\n [ 1, 2, 3 ]\n > out[ 1 ][ 0 ][ 0 ][ 0 ]\n [ 4, 5, 6 ]\n\n See Also\n --------\n map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > function clbk( v ) { return v * 2; };\n > var bar = mapArguments( foo, clbk );\n > var out = bar( 1, 2, 3 )\n [ 2, 4, 6 ]\n\n See Also\n --------\n filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n The invoked function is provided a single argument: the invocation index\n (zero-based).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n thisArg: any (optional)\n Function execution context.\n\n Returns\n -------\n out: Array\n Array of accumulated function return values.\n\n Examples\n --------\n > function fcn( i ) { return i; };\n > var arr = mapFun( fcn, 5 )\n [ 0, 1, 2, 3, 4 ]\n\n See Also\n --------\n mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n\n For each iteration, the provided function is invoked with two arguments:\n\n - index: invocation index (starting from zero).\n - next: callback to be invoked upon function completion.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - result: function result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcn: Function\n Function to invoke.\n\n n: integer\n Number of times to invoke a function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n done: Function\n A callback invoked upon executing a provided function `n` times or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > mapFunAsync( fcn, 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Limit number of concurrent invocations:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'limit': 2 };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n // Sequential invocation:\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > var opts = { 'series': true };\n > mapFunAsync( fcn, 10, opts, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to allow only one pending invocation at a\n time. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n Function to invoke.\n\n Returns\n -------\n out: Function\n A function which invokes a function `n` times and returns an array of\n accumulated function return values.\n\n Examples\n --------\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... next( null, i );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapFunAsync.factory( opts, fcn );\n > function done( error, arr ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( arr );\n ... };\n > f( 10, done )\n [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n See Also\n --------\n mapFun","mapKeys":"\nmapKeys( obj, transform )\n Maps keys from one object to a new object having the same values.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key.\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values specify the keys of the output object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapKeys( obj, transform )\n { 'a1': 1, 'b2': 2 }\n\n See Also\n --------\n mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n Maps keys from one object to a new object having the same values.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `key`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - key\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - key\n - value\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - key: transformed key.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The key returned by a transform function should be a value which can be\n serialized as an object key.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps own properties. Hence, the function does not map\n inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapKeysAsync( obj, transform, done )\n { 'a:1': 1, 'b:2': 2 }\n\n // Limit number of concurrent invocations:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n // Process sequentially:\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapKeysAsync( obj, opts, transform, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n Returns a function which maps keys from one object to a new object having\n the same values.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Returned values specify the keys of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps keys from one object to a new object having the\n same values.\n\n Examples\n --------\n > function transform( key, value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapKeysAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep:boop': 'beep' }\n\n See Also\n --------\n mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduce( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n\n When invoked, the mapping function is provided three arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n When invoked, the reducing function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: result after applying the mapping function to the current array\n element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a single-pass map-reduce\n operation over the entire input ndarray (i.e., higher-order ndarray\n dimensions are flattened to a single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n mapper: Function\n Mapping function.\n\n reducer: Function\n Reducing function.\n\n thisArg: any (optional)\n Execution context for the reducing function.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f1 = naryFunction( base.abs, 1 );\n > var f2 = naryFunction( base.add, 2 );\n > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n > var out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapReduceRight( arr, 0.0, f1, f2 )\n 21.0\n\n See Also\n --------\n mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n The returned output array always has a \"generic\" data type. For example, if\n provided an array-like object, the function returns a generic array. If\n provided an ndarray, the function returns an ndarray having a \"generic\" data\n type.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = mapRight( arr, f )\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = mapRight( arr, f );\n > var v = out.get( 1, 1 )\n 5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n\n The applied function is provided the following arguments:\n\n - value: array element.\n - index: element index.\n - arr: input array.\n\n Input and output arrays must be either both array-like objects or both\n ndarray-like objects.\n\n If input and output arrays are array-like objects, the arrays must have the\n same number of elements.\n\n If input and output arrays are both ndarray-like objects, the arrays *must*\n be broadcast compatible.\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n out: ArrayLikeObject|ndarray\n Output array.\n\n fcn: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array|ndarray\n Output array.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.abs, 1 );\n > var arr = [ -1, -2, -3, -4, -5, -6 ];\n > var out = [ 0, 0, 0, 0, 0, 0 ];\n > mapRight.assign( arr, out, f );\n > out\n [ 1, 2, 3, 4, 5, 6 ]\n\n // ndarray:\n > var opts = { 'shape': [ 2, 3 ] };\n > arr = array( arr, opts );\n > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n > mapRight.assign( arr, out, f );\n > var v = out.get( 1, 1 )\n 5\n\n See Also\n --------\n map, reduce","mapValues":"\nmapValues( obj, transform )\n Maps values from one object to a new object having the same keys.\n\n The transform function is provided three arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration order is *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function transform( value, key ) { return key + value; };\n > var obj = { 'a': 1, 'b': 2 };\n > var out = mapValues( obj, transform )\n { 'a': 'a1', 'b': 'b2' }\n\n See Also\n --------\n mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n Maps values from one object to a new object having the same keys.\n\n When invoked, `transform` is provided a maximum of four arguments:\n\n - value: object value corresponding to `key`.\n - key: object key.\n - obj: the input object.\n - next: a callback to be invoked after processing an object `value`.\n\n The actual number of provided arguments depends on function length. If\n `transform` accepts two arguments, `transform` is provided:\n\n - value\n - next\n\n If `transform` accepts three arguments, `transform` is provided:\n\n - value\n - key\n - next\n\n For every other `transform` signature, `transform` is provided all four\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - value: transformed value.\n\n If a `transform` function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function only maps values from own properties. Hence, the function does\n not map inherited properties.\n\n The function shallow copies key values.\n\n Key iteration and insertion order are *not* guaranteed.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n done: Function\n A callback invoked either upon processing all own properties or upon\n encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2 };\n > mapValuesAsync( obj, transform, done )\n { 'a': 'a:1', 'b': 'b:2' }\n\n // Limit number of concurrent invocations:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'limit': 2 };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n // Process sequentially:\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var opts = { 'series': true };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > mapValuesAsync( obj, opts, transform, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n Returns a function which maps values from one object to a new object having\n the same keys.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each property sequentially.\n Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n transform: Function\n Transform function. Return values are the key values of the output\n object.\n\n Returns\n -------\n out: Function\n A function which maps values from one object to a new object having the\n same keys.\n\n Examples\n --------\n > function transform( value, key, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... next( null, key+':'+value );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = mapValuesAsync.factory( opts, transform );\n > function done( error, out ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( out );\n ... };\n > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n > f( obj, done )\n { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n > obj = { 'beep': 'boop' };\n > f( obj, done )\n { 'beep': 'beep:boop' }\n\n See Also\n --------\n mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n\n Only those arguments having a truthy mask value are applied to a provided\n function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n mask: ArrayLikeObject\n Mask array.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, rejectArguments, reorderArguments, reverseArguments\n","matrix":"\nmatrix( [dtype][, options] )\n Returns a two-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = matrix()\n \n > var sh = ndarrayShape( arr )\n [ 0, 0 ]\n > arr = matrix( 'float32' )\n \n\n\nmatrix( shape[, dtype][, options] )\n Returns a two-dimensional ndarray having a specified shape.\n\n Parameters\n ----------\n shape: ArrayLikeObject\n Array shape. Must contain exactly two elements.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = matrix( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > arr = matrix( [ 2, 2 ], 'float32' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n\nmatrix( M, N[, dtype][, options] )\n Returns a two-dimensional ndarray having a specified shape.\n\n Parameters\n ----------\n M: integer\n Number of rows.\n\n N: integer\n Number of columns.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var arr = matrix( 2, 2 )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > arr = matrix( 2, 2, 'float32' )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n\nmatrix( obj[, dtype][, options] )\n Creates a two-dimensional ndarray from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray. If an\n array-like object, the value must be a nested array (i.e., an array-like\n object of array-like objects), where each nested array must have the\n same number of elements. If an iterable, the iterable must return array-\n like objects, each of which must have the same number of elements.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var v = [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ];\n > var arr = matrix( v, 'float32' )\n [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]\n\n\nmatrix( buffer[, byteOffset[, shape]][, dtype][, options] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n shape: ArrayLikeObject (optional)\n Array shape. Must contain exactly two elements. If not provided, the\n view spans from the byteOffset to the end of the underlying ArrayBuffer\n and the first dimension of the returned ndarray has a size of one.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = matrix( buf, 0, [ 2, 2 ], 'float32' )\n \n\n\nmatrix( buffer[, byteOffset[, M, N]][, dtype][, options] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n\n If `M` and `N` are not provided, the returned ndarray view spans from the\n byteOffset to the end of the underlying ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n M: integer (optional)\n Number of rows.\n\n N: integer (optional)\n Number of columns.\n\n dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A two-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = matrix( buf, 0, 2, 2, 'float32' )\n \n\n\nmatrix.factory( dtype[, options] )\n Returns a function for creating a two-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a two-dimensional ndarray.\n\n Examples\n --------\n > var f = matrix.factory( 'float32' );\n > var arr = f( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, vector, ndarray\n","matrix.factory":"\nmatrix.factory( dtype[, options] )\n Returns a function for creating a two-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string|DataType\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is less than the number of dimensions, an ndarray\n instance recycles modes using modulo arithmetic.\n\n Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a two-dimensional ndarray.\n\n Examples\n --------\n > var f = matrix.factory( 'float32' );\n > var arr = f( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n Float64Matrix, Float32Matrix, Int32Matrix, Complex128Matrix, Complex64Matrix, vector, ndarray","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n\n Examples\n --------\n > MAX_ARRAY_LENGTH\n 4294967295\n\n See Also\n --------\n MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n\n Examples\n --------\n > MAX_TYPED_ARRAY_LENGTH\n 9007199254740991\n\n See Also\n --------\n MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n\n If a provided ndarray has the same shape as the specified shape, the\n function returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n specified shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to the input ndarray may affect multiple elements. If you need to\n write to the input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if a provided ndarray is incompatible with a\n provided shape.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n shape: ArrayLikeObject\n Desired shape.\n\n Returns\n -------\n out: ndarray\n Broadcasted array.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n \n > sh = y.shape\n [ 3, 2, 2 ]\n > var v = y.get( 0, 0, 0 )\n 1\n > v = y.get( 0, 0, 1 )\n 2\n > v = y.get( 0, 1, 0 )\n 3\n > v = y.get( 0, 1, 1 )\n 4\n > v = y.get( 1, 0, 0 )\n 1\n > v = y.get( 1, 1, 0 )\n 3\n > v = y.get( 2, 0, 0 )\n 1\n > v = y.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n Broadcasts ndarrays to a common shape.\n\n The function supports two (mutually exclusive) means of providing ndarray\n arguments:\n\n 1. Providing a single array containing ndarray arguments.\n 2. Providing ndarray arguments as separate arguments.\n\n If a provided ndarray has a shape matching the common shape, the function\n returns the provided ndarray.\n\n If a provided ndarray has a different (broadcast compatible) shape than the\n common shape, the function returns a new *read-only* ndarray view of the\n provided ndarray's data. The view is typically *not* contiguous. As more\n than one element of a returned view may refer to the same memory location,\n writing to a view may affect multiple elements. If you need to write to an\n input ndarray, copy the input ndarray before broadcasting.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n Parameters\n ----------\n arrays: ...ndarray|ArrayLikeObject\n Array arguments.\n\n Returns\n -------\n out: Array\n Broadcasted arrays.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > var sh = x.shape\n [ 2, 2 ]\n > var y = ndzeros( [ 3, 2, 2 ] )\n \n > var out = maybeBroadcastArrays( [ x, y ] )\n [ , ]\n\n // Retrieve the broadcasted \"x\" array:\n > var bx = out[ 0 ]\n \n > sh = bx.shape\n [ 3, 2, 2 ]\n\n // Retrieve broadcasted elements...\n > var v = bx.get( 0, 0, 0 )\n 1\n > v = bx.get( 0, 0, 1 )\n 2\n > v = bx.get( 0, 1, 0 )\n 3\n > v = bx.get( 0, 1, 1 )\n 4\n > v = bx.get( 1, 0, 0 )\n 1\n > v = bx.get( 1, 1, 0 )\n 3\n > v = bx.get( 2, 0, 0 )\n 1\n > v = bx.get( 2, 1, 1 )\n 4\n\n See Also\n --------\n array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n Returns a memoized function.\n\n The function does not set the `length` property of the returned function.\n Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n The function serializes provided arguments as a string and stores results\n using the string as an identifier. To use a custom hash function, provide a\n hash function argument.\n\n Parameters\n ----------\n fcn: Function\n Function to memoize.\n\n hashFunction: Function (optional)\n Function to map a set of arguments to a single value identifying that\n set.\n\n Returns\n -------\n out: Function\n Memoized function.\n\n Examples\n --------\n > function factorial( n ) {\n ... var prod;\n ... var i;\n ... prod = 1;\n ... for ( i = n; i > 1; i-- ) {\n ... prod *= i;\n ... }\n ... return prod;\n ... };\n > var memoized = memoize( factorial );\n > var v = memoized( 5 )\n 120\n > v = memoized( 5 )\n 120\n\n","merge":"\nmerge( target, ...source )\n Merges objects into a target object.\n\n The target object is mutated.\n\n Only plain objects are merged and extended. Other values/types are either\n deep copied or assigned.\n\n Support for deep merging class instances is inherently fragile.\n\n `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n Functions are not deep copied.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n source: ...Object\n Source objects (i.e., objects to be merged into the target object).\n\n Returns\n -------\n out: Object\n Merged (target) object.\n\n Examples\n --------\n > var target = { 'a': 'beep' };\n > var source = { 'a': 'boop', 'b': 'bap' };\n > var out = merge( target, source )\n { 'a': 'boop', 'b': 'bap' }\n > var bool = ( out === target )\n true\n\n\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy\n","merge.factory":"\nmerge.factory( options )\n Returns a function for merging and extending objects.\n\n Parameters\n ----------\n options: Object\n Options.\n\n options.level: integer (optional)\n Merge level. Default: Infinity.\n\n options.copy: boolean (optional)\n Boolean indicating whether to deep copy merged values. Deep copying\n prevents shared references and source object mutation. Default: true.\n\n options.override: boolean|Function (optional)\n Defines the merge strategy. If `true`, source object values will always\n override target object values. If `false`, source values never override\n target values (useful for adding, but not overwriting, properties). To\n define a custom merge strategy, provide a function. Default: true.\n\n options.extend: boolean (optional)\n Boolean indicating whether new properties can be added to the target\n object. If `false`, only shared properties are merged. Default: true.\n\n Returns\n -------\n fcn: Function\n Function which can be used to merge objects.\n\n Examples\n --------\n > var opts = {\n ... 'level': 100,\n ... 'copy': true,\n ... 'override': true,\n ... 'extend': true\n ... };\n > var merge = merge.factory( opts )\n \n\n // Set the `level` option to limit the merge depth:\n > merge = merge.factory( { 'level': 2 } );\n > var target = {\n ... '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n ... };\n > var source = {\n ... '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n ... };\n > var out = merge( target, source )\n { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n // Set the `copy` option to `false` to allow shared references:\n > merge = merge.factory( { 'copy': false } );\n > target = {};\n > source = { 'a': [ 1, 2, 3 ] };\n > out = merge( target, source );\n > var bool = ( out.a === source.a )\n true\n\n // Set the `override` option to `false` to preserve existing properties:\n > merge = merge.factory( { 'override': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'a': null, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n // Define a custom merge strategy:\n > function strategy( a, b, key ) {\n ... // a => target value\n ... // b => source value\n ... // key => object key\n ... if ( key === 'a' ) {\n ... return b;\n ... }\n ... if ( key === 'b' ) {\n ... return a;\n ... }\n ... return 'bebop';\n ... };\n > merge = merge.factory( { 'override': strategy } );\n > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n > source = { 'a': null, 'b': {}, 'c': 'bop' };\n > out = merge( target, source )\n { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n // Prevent non-existent properties from being added to the target object:\n > merge = merge.factory( { 'extend': false } );\n > target = { 'a': 'beep', 'b': 'boop' };\n > source = { 'b': 'hello', 'c': 'world' };\n > out = merge( target, source )\n { 'a': 'beep', 'b': 'hello' }\n\n See Also\n --------\n copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var ms = days * MILLISECONDS_IN_DAY\n 271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var ms = hrs * MILLISECONDS_IN_HOUR\n 11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var ms = mins * MILLISECONDS_IN_MINUTE\n 188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var secs = 3.14;\n > var ms = secs * MILLISECONDS_IN_SECOND\n 3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var weeks = 3.14;\n > var ms = weeks * MILLISECONDS_IN_WEEK\n 1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n\n Data includes the following:\n\n - army: army size.\n - cities: cities.\n - labels: map labels.\n - temperature: temperature during the army's return from Russia.\n - rivers: river data.\n\n Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n to convert to Celsius.\n\n River data is formatted as GeoJSON.\n\n River data is incomplete, with portions of rivers missing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.data: string (optional)\n Dataset name.\n\n Returns\n -------\n out: Object|Array\n Minard's data.\n\n Examples\n --------\n > var data = MINARD_NAPOLEONS_MARCH();\n > var army = data.army\n [...]\n > var cities = data.cities\n [...]\n > var labels = data.labels\n [...]\n > var rivers = data.rivers\n {...}\n > var t = data.temperature\n [...]\n\n References\n ----------\n - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n Ecole nationale des ponts et chaussées.\n - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var mins = days * MINUTES_IN_DAY\n 4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var mins = hrs * MINUTES_IN_HOUR\n 188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var mins = wks * MINUTES_IN_WEEK\n 31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n Returns the number of minutes in a month.\n\n By default, the function returns the number of minutes in the current month\n of the current year (according to local time). To determine the number of\n minutes for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Minutes in a month.\n\n Examples\n --------\n > var num = minutesInMonth()\n \n > num = minutesInMonth( 2 )\n \n > num = minutesInMonth( 2, 2016 )\n 41760\n > num = minutesInMonth( 2, 2017 )\n 40320\n\n // Other ways to supply month:\n > num = minutesInMonth( 'feb', 2016 )\n 41760\n > num = minutesInMonth( 'february', 2016 )\n 41760\n\n See Also\n --------\n minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n\n By default, the function returns the number of minutes in the current year\n (according to local time). To determine the number of minutes for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of minutes in a year.\n\n Examples\n --------\n > var num = minutesInYear()\n \n > num = minutesInYear( 2016 )\n 527040\n > num = minutesInYear( 2017 )\n 525600\n\n See Also\n --------\n minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n\n Each array element has the following fields:\n\n - chapter: book chapter (number or identifier).\n - title: chapter title (if available; otherwise, empty).\n - text: chapter text.\n\n Returns\n -------\n out: Array\n Book text.\n\n Examples\n --------\n > var data = MOBY_DICK()\n [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n\n Returns\n -------\n out: Array\n List of month names.\n\n Examples\n --------\n > var list = MONTH_NAMES_EN()\n [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var yrs = 3.14;\n > var mons = yrs * MONTHS_IN_YEAR\n 37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n Moves a property from one object to another object.\n\n The property is deleted from the source object and the property's descriptor\n is preserved during transfer.\n\n If a source property is not configurable, the function throws an error, as\n the property cannot be deleted from the source object.\n\n Parameters\n ----------\n source: Object\n Source object.\n\n prop: string\n Property to move.\n\n target: Object\n Target object.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether operation was successful.\n\n Examples\n --------\n > var obj1 = { 'a': 'b' };\n > var obj2 = {};\n > var bool = moveProperty( obj1, 'a', obj2 )\n true\n > bool = moveProperty( obj1, 'c', obj2 )\n false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n\n Parameters\n ----------\n ...slice: Slice|integer|null|undefined\n Slice arguments.\n\n Returns\n -------\n s: MultiSlice\n MultiSlice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3\n\n\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]\n\n\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n\n Returns\n -------\n ndims: integer\n Number of slice dimensions.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.ndims\n 3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n\n Returns\n -------\n data: Array\n Slice data.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.data\n [ 2, , 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n\n Returns\n -------\n str: string\n Serialized multi-slice string.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > var ms = new MultiSlice( 2, s, 1 );\n > ms.toString()\n 'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 2, 10, 1 );\n > var ms = new MultiSlice( 2, s );\n > ms.toJSON()\n {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n See Also\n --------\n ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n Returns a named typed tuple factory.\n\n Named tuples assign a property name, and thus a meaning, to each position in\n a tuple and allow for more readable, self-documenting code.\n\n Named typed tuples can be used wherever typed arrays are used, with the\n added benefit that they allow accessing fields by both field name and\n position index.\n\n Named typed tuples may be one the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n fields: Array\n Field (property) names.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Default tuple data type. If a data type is not provided to a named typed\n tuple factory, this option specifies the underlying tuple data type.\n Default: 'float64'.\n\n options.name: string (optional)\n Tuple name. Default: 'tuple'.\n\n Returns\n -------\n factory: Function\n Named typed tuple factory.\n\n Examples\n --------\n > var opts = {};\n > opts.name = 'Point';\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var tuple = factory();\n\n\nfactory()\n Returns a named typed tuple of the default data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory();\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory( dtype )\n Returns a named typed tuple of the specified data type.\n\n Parameters\n ----------\n dtype: string\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( 'int32' );\n > p.x\n 0\n > p.y\n 0\n > p[ 0 ]\n 0\n > p[ 1 ]\n 0\n\n\nfactory( typedarray[, dtype] )\n Creates a named typed tuple from a typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate a named typed tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var f = namedtypedtuple( [ 'x', 'y' ] );\n > var p = f( new Float64Array( [ 1.0, -1.0 ] ) );\n > p.x\n 1.0\n > p.y\n -1.0\n > p[ 0 ]\n 1.0\n > p[ 1 ]\n -1.0\n\n\nfactory( obj[, dtype] )\n Creates a named typed tuple from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a named typed\n tuple.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > p = factory( [ 1, -1 ], 'int32' );\n > p.x\n 1\n > p.y\n -1\n > p[ 0 ]\n 1\n > p[ 1 ]\n -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n Returns a named typed tuple view of an ArrayBuffer.\n\n The view length equals the number of tuple fields.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first tuple element.\n Default: 0.\n\n dtype: string (optional)\n Tuple data type.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var buf = new ArrayBuffer( 16 );\n > var p = factory( buf, 4, 'float32' );\n > p.x\n 0.0\n > p.y\n 0.0\n > p[ 0 ]\n 0.0\n > p[ 1 ]\n 0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n Creates a new named typed tuple from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n - field: tuple field.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of tuple elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > function mapFcn( v ) { return v * 2.0; };\n > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n Creates a new named typed tuple from an object containing tuple fields.\n\n A callback is provided the following arguments:\n\n - value: source object tuple field value.\n - field: source object tuple field name.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n map: Function (optional)\n Callback to invoke for each source object tuple field.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n Creates a new named typed tuple from a variable number of arguments.\n\n The number of arguments *must* equal the number of tuple fields.\n\n Parameters\n ----------\n element0: number\n Tuple element.\n\n element1: number (optional)\n Tuple element.\n\n elementN: ...number (optional)\n Tuple elements.\n\n Returns\n -------\n tuple: TypedArray\n Named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory.of( 2.0, -2.0 );\n > p.x\n 2.0\n > p.y\n -2.0\n > p[ 0 ]\n 2.0\n > p[ 1 ]\n -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n Size (in bytes) of each tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.BYTES_PER_ELEMENT\n 8\n\n\ntuple.buffer\n Pointer to the underlying data buffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.buffer\n \n\n\ntuple.byteLength\n Length (in bytes) of the tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteLength\n 16\n\n\ntuple.byteOffset\n Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.byteOffset\n 0\n\n\ntuple.length\n Tuple length (i.e., number of elements).\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.length\n 2\n\n\ntuple.name\n Tuple name.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.name\n 'Point'\n\n\ntuple.fields\n Returns the list of tuple fields.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fields\n [ 'x', 'y' ]\n\n\ntuple.orderedFields\n Returns the list of tuple fields in index order.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.sort();\n > p[ 0 ]\n -1.0\n > p.fields\n [ 'x', 'y' ]\n > p.orderedFields\n [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n Copies a sequence of elements within the tuple starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n > p.copyWithin( 3, 0, 2 );\n > p.w\n 2.0\n > p.v\n -2.0\n\n\ntuple.entries()\n Returns an iterator for iterating over tuple key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple key-value pairs.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.entries();\n > it.next().value\n [ 0, 'x', 1.0 ]\n > it.next().value\n [ 1, 'y', -1.0 ]\n > it.next().done\n true\n\n\ntuple.every( predicate[, thisArg] )\n Tests whether all tuple elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all tuple elements pass.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > p.every( predicate )\n false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n Returns the field of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var f = p.fieldOf( 2.0 )\n undefined\n > f = p.fieldOf( -1.0 )\n 'z'\n\n\ntuple.fill( value[, start[, end]] )\n Fills a tuple from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last tuple element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > p.fill( 2.0 );\n > p.x\n 2.0\n > p.y\n 2.0\n\n\ntuple.filter( predicate[, thisArg] )\n Creates a new tuple which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n If a predicate function does not return a truthy value for any tuple\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters tuple elements. If a predicate function\n returns a truthy value, a tuple element is included in the output tuple;\n otherwise, a tuple element is not included in the output tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v >= 0.0 ); };\n > var p2 = p1.filter( predicate );\n > p2.fields\n [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n Returns the first tuple element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Tuple element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var v = p.find( predicate )\n -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n Returns the field of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var f = p.findField( predicate )\n 'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n Returns the index of the first tuple element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > var idx = p.findIndex( predicate )\n 2\n\n\ntuple.forEach( fcn[, thisArg] )\n Invokes a callback for each tuple element.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each tuple element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > var str = ' ';\n > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n > p.forEach( fcn );\n > str\n ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether a tuple includes a search element.\n\n The method does not distinguish between signed and unsigned zero.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a tuple includes a search element.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var bool = p.includes( 2.0 )\n false\n > bool = p.includes( -1.0 )\n true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n Returns the index of the first tuple element strictly equal to a search\n element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > var idx = p.indexOf( 2.0 )\n -1\n > idx = p.indexOf( -1.0 )\n 2\n\n\ntuple.ind2key( ind )\n Converts a tuple index to a field name.\n\n If provided an out-of-bounds index, the method returns `undefined`.\n\n Parameters\n ----------\n ind: integer\n Tuple index. If less than zero, the method resolves the index relative\n to the last tuple element.\n\n Returns\n -------\n field: string|undefined\n Field name.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.ind2key( 1 )\n 'y'\n > p.ind2key( 100 )\n undefined\n\n\ntuple.join( [separator] )\n Serializes a tuple by joining all tuple elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating tuple elements. Default: ','.\n\n Returns\n -------\n str: string\n Tuple serialized as a string.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1, 0, -1 ], 'int32' );\n > p.join( '|' )\n '1|0|-1'\n\n\ntuple.keys()\n Returns an iterator for iterating over tuple keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple keys.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.keys();\n > it.next().value\n [ 0, 'x' ]\n > it.next().value\n [ 1, 'y' ]\n > it.next().done\n true\n\n\ntuple.key2ind( field )\n Converts a field name to a tuple index.\n\n If provided an unknown field name, the method returns `-1`.\n\n Parameters\n ----------\n field: string\n Tuple field name.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p.key2ind( 'y' )\n 1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n Returns the field of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `undefined`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n field: string|undefined\n Tuple field.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var f = p.lastFieldOf( 2.0 )\n undefined\n > f = p.lastFieldOf( 0.0 )\n 'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last tuple element strictly equal to a search\n element.\n\n The method iterates from the last tuple element to the first tuple element.\n\n The method does not distinguish between signed and unsigned zero.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Tuple index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last tuple element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Tuple index.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n > var idx = p.lastIndexOf( 2.0 )\n -1\n > idx = p.lastIndexOf( 0.0 )\n 3\n\n\ntuple.map( fcn[, thisArg] )\n Maps each tuple element to an element in a new tuple.\n\n A provided function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n The returned tuple has the same data type as the host tuple.\n\n Parameters\n ----------\n fcn: Function\n Function which maps tuple elements to elements in the new tuple.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( v ) { return v * 2.0; };\n > var p2 = p1.map( fcn );\n > p2.x\n 2.0\n > p2.y\n 0.0\n > p2.z\n -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first tuple element as the first argument and the second tuple\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduce( fcn, 0.0 )\n 2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in a tuple and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current tuple element.\n - index: index of the current tuple element.\n - field: field name corresponding to the current tuple element.\n - tuple: tuple on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last tuple element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last tuple element as the first argument and the second-to-last\n tuple element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = p.reduceRight( fcn, 0.0 )\n 2.0\n\n\ntuple.reverse()\n Reverses a tuple *in-place*.\n\n This method mutates the tuple on which the method is invoked.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 0 ]\n 1.0\n > p.x\n 1.0\n > p.reverse();\n > p[ 0 ]\n -1.0\n > p.x\n 1.0\n\n\ntuple.set( arr[, offset] )\n Sets tuple elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing tuple values to set.\n\n offset: integer (optional)\n Tuple index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, 0.0, -1.0 ] );\n > p[ 1 ]\n 0.0\n > p.y\n 0.0\n > p.set( [ -2.0, 2.0 ], 1 );\n > p[ 1 ]\n -2.0\n > p.y\n -2.0\n > p[ 2 ]\n 2.0\n > p.z\n 2.0\n\n\ntuple.slice( [begin[, end]] )\n Copies tuple elements to a new tuple with the same underlying data type as\n the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n > p1.fields\n [ 'x', 'y', 'z' ]\n > var p2 = p1.slice( 1 );\n > p2.fields\n [ 'y', 'z' ]\n > p2.y\n 0.0\n > p2.z\n -1.0\n\n\ntuple.some( predicate[, thisArg] )\n Tests whether at least one tuple element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: tuple element.\n - index: tuple index.\n - field: tuple field name.\n - tuple: tuple on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests tuple elements. If a predicate function\n returns a truthy value, a tuple element passes; otherwise, a tuple\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one tuple element passes.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > function predicate( v ) { return ( v < 0.0 ); };\n > p.some( predicate )\n true\n\n\ntuple.sort( [compareFunction] )\n Sorts a tuple *in-place*.\n\n Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n before and after sorting will always return the same tuple element. However,\n this behavior is generally not true when accessing tuple elements according\n to tuple index. In summary, sorting affects index order but not field\n assignments.\n\n The comparison function is provided two tuple elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the tuple on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n tuple: TypedArray\n Modified tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > p.sort();\n > p.orderedFields\n [ 'v', 'y', 'z', 'x', 'w' ]\n > p[ 0 ]\n -2.0\n > p[ 1 ]\n -1.0\n > p.y\n -1.0\n > p.key2ind( 'x' )\n 3\n > p[ 3 ]\n 1.0\n\n\ntuple.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n arr: TypedArray\n A new typed array view.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var arr = p.subarray( 2 )\n [ 0.0, 2.0, -2.0 ]\n > arr.length\n 3\n\n\ntuple.subtuple( [begin[, end]] )\n Creates a new named typed tuple over the same underlying ArrayBuffer and\n with the same underlying data type as the host tuple.\n\n If the method is unable to resolve indices to a non-empty tuple subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last tuple element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last tuple element. Default: tuple.length.\n\n Returns\n -------\n tuple: TypedArray\n A new named typed tuple.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n > var p2 = p1.subtuple( 2 );\n > p2.fields\n [ 'z', 'w', 'v' ]\n > p2[ 0 ]\n 0.0\n > p2.z\n 0.0\n > p2[ 1 ]\n 2.0\n > p2.w\n 2.0\n > p2[ 2 ]\n -2.0\n > p2.v\n -2.0\n > p2.length\n 3\n\n\ntuple.toJSON()\n Serializes a tuple as JSON.\n\n Returns\n -------\n obj: Object\n A tuple JSON representation.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toJSON()\n { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n Serializes a tuple as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n > p.toLocaleString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.toString()\n Serializes a tuple as a string.\n\n Returns\n -------\n str: string\n A tuple string representation.\n\n Examples\n --------\n > var opts = { 'name': 'Point' };\n > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n > var p = factory( [ 1.0, -1.0, 0.0 ] );\n > p.toString()\n 'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n Returns an iterator for iterating over tuple elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over tuple elements.\n\n Examples\n --------\n > var factory = namedtypedtuple( [ 'x', 'y' ] );\n > var p = factory( [ 1.0, -1.0 ] );\n > it = p.values();\n > it.next().value\n 1.0\n > it.next().value\n -1.0\n > it.next().done\n true\n\n See Also\n --------\n typedarray\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n\n Examples\n --------\n > NAN\n NaN\n\n See Also\n --------\n FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n\n The returned function *always* invokes the wrapped function with a specified\n number of arguments, even when the returned function is provided fewer\n arguments.\n\n The value for the missing arguments is equal to `undefined`.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n arity: integer\n Number of arguments.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = naryFunction( foo, 2 );\n > var out = bar( 1, 2, 3 )\n [ 1, 2, undefined ]\n\n See Also\n --------\n maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n Returns a string value indicating a specification defined classification of\n an object.\n\n The function is *not* robust for ES2015+ environments. In ES2015+,\n `Symbol.toStringTag` allows overriding the default description of an object.\n While measures are taken to uncover the default description, such measures\n can be thwarted. While this function remains useful for type-checking, be\n aware that value impersonation is possible. Where possible, prefer functions\n tailored to checking for particular value types, as specialized functions\n are better equipped to address `Symbol.toStringTag`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n String value indicating a specification defined classification of the\n input value.\n\n Examples\n --------\n > var str = nativeClass( 'a' )\n '[object String]'\n > str = nativeClass( 5 )\n '[object Number]'\n > function Beep(){};\n > str = nativeClass( new Beep() )\n '[object Object]'\n\n See Also\n --------\n constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n Returns an ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n buffer: ArrayLikeObject|TypedArray|Buffer\n Data buffer. A data buffer must be an array-like object (i.e., have a\n `length` property). For data buffers which are not indexed collections\n (i.e., collections which cannot support direct index access, such as\n `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n Note that, for `set` methods, the value to set should be the first\n argument, followed by the linear index, similar to the native typed\n array `set` method.\n\n shape: ArrayLikeObject\n Array shape.\n\n strides: ArrayLikeObject\n Array strides.\n\n offset: integer\n Index offset.\n\n order: string\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style).\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n ndarray: ndarray\n ndarray instance.\n\n Examples\n --------\n // Create a new instance...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n > var d = [ 2, 2 ]; // shape\n > var s = [ 2, 1 ]; // strides\n > var o = 0; // index offset\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n \n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8\n\n\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'\n\n\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}\n\n\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4\n\n\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2\n\n\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0\n\n\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'\n\n\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]\n\n\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0\n\n\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0\n\n\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0\n\n\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0\n\n\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'\n\n\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of the array.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.byteLength\n 32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n\n Returns\n -------\n size: integer|null\n Size (in bytes) of each array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sz = arr.BYTES_PER_ELEMENT\n 8","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n\n Returns\n -------\n buf: ArrayLikeObject|TypedArray|Buffer\n Underlying data buffer.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var buf = arr.data\n [ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n\n Returns\n -------\n dtype: string\n Underlying data type.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var dt = arr.dtype\n 'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n\n Returns\n -------\n flags: Object\n Info object.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var fl = arr.flags\n {...}","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n\n Returns\n -------\n len: integer\n Array length.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var len = arr.length\n 4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n\n Returns\n -------\n ndims: integer\n Number of dimensions.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var n = arr.ndims\n 2","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n\n Returns\n -------\n offset: integer\n Index offset.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.offset\n 0","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n\n The array order is either row-major (C-style) or column-major (Fortran-\n style).\n\n Returns\n -------\n order: string\n Array order.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var ord = arr.order\n 'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n\n Returns\n -------\n shape: Array\n Array shape.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var sh = arr.shape\n [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n\n Returns\n -------\n strides: Array\n Index strides.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var st = arr.strides\n [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n Returns an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.get( 1, 1 )\n 4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n Returns an array element located at a specified linear index.\n\n For zero-dimensional arrays, the input argument is ignored and, for clarity,\n should not be provided.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n Returns\n -------\n out: any\n Array element.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > var v = arr.iget( 3 )\n 4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n Sets an array element specified according to provided subscripts.\n\n The number of provided subscripts should equal the number of dimensions.\n\n For zero-dimensional arrays, no indices should be provided.\n\n Parameters\n ----------\n idx: ...integer\n Subscripts.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.set( 1, 1, -4.0 );\n > arr.get( 1, 1 )\n -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n Sets an array element located at a specified linear index.\n\n For zero-dimensional arrays, the first, and only, argument should be the\n value to set.\n\n Parameters\n ----------\n idx: integer\n Linear index.\n\n v: any\n Value to set.\n\n Returns\n -------\n out: ndarray\n ndarray instance.\n\n Examples\n --------\n > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n > arr.iset( 3, -4.0 );\n > arr.iget( 3 )\n -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n str: string\n Serialized ndarray string.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toString()\n '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n\n This method does **not** serialize data outside of the buffer region defined\n by the array configuration.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var b = [ 1, 2, 3, 4 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n > arr.toJSON()\n {...}\n\n See Also\n --------\n array, FancyArray","ndarray2array":"\nndarray2array( x )\n Converts an ndarray to a generic array.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n Returns\n -------\n out: Array|Array\n Generic array (which may include nested arrays).\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2array( arr )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n Converts an ndarray to an object supporting fancy indexing.\n\n An ndarray supporting fancy indexing is an ndarray which supports slicing\n via indexing expressions for both retrieval and assignment.\n\n A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n any mutations to the returned ndarray will affect the underlying input\n ndarray and vice versa.\n\n A fancy ndarray supports indexing using positive and negative integers (both\n numeric literals and strings), Slice and MultiSlice instances, subsequence\n expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n A fancy ndarray supports all properties and methods of the input ndarray,\n and, thus, a fancy ndarray can be consumed by any API which supports\n ndarray-like objects.\n\n For operations returning a new ndarray (e.g., when slicing or invoking an\n instance method), a fancy ndarray returns a new fancy ndarray having the\n same configuration as specified by provided options.\n\n Indexing expressions provide a convenient and powerful means for creating\n and operating on ndarray views; however, their use does entail a performance\n cost. Indexing expressions are best suited for interactive use and\n scripting. For performance critical applications, prefer equivalent\n functional APIs supporting ndarray instances.\n\n Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n are repeated (without additional memory allocation) to match the dimensions\n of a target ndarray instance.\n\n When assigning ndarrays to slices, the ndarray on the right-hand-side must\n be broadcast-compatible with dimensions implied by the slice.\n\n Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n performed without overflow or loss of precision, with the exception of\n floating-point ndarrays which are also allowed to downcast from higher\n precision to lower precision).\n\n When attempting to perform an unsafe cast, fancy ndarrays will raise an\n exception.\n\n When assigning a real-valued scalar to a complex number ndarray, a fancy\n ndarray will cast the real-valued scalar to a complex number argument having\n an imaginary component equal to zero.\n\n In older JavaScript environments which do not support Proxy objects, the use\n of indexing expressions is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n out: ndarray\n Output ndarray supporting fancy indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Convert to a fancy ndarray:\n > var arr = ndarray2fancy( x );\n\n // Get an element using subscripts:\n > var v = arr.get( 1, 1 )\n 4.0\n\n // Get an element using a linear index:\n > v = arr.iget( 3 )\n 4.0\n\n // Set an element using subscripts:\n > arr.set( 1, 1, 40.0 );\n > arr.get( 1, 1 )\n 40.0\n\n // Set an element using a linear index:\n > arr.iset( 3, 99.0 );\n > arr.get( 1, 1 )\n 99.0\n\n\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking by default.\n Default: false.\n\n options.cache: Object (optional)\n Cache for resolving ndarray index objects. Must have a 'get' method\n which accepts a single argument: a string identifier associated with an\n ndarray index. If an ndarray index associated with a provided identifier\n exists, the 'get' method should return an object having the following\n properties:\n\n - data: the underlying index ndarray.\n - type: the index type. Must be either 'mask', 'bool', or 'int'.\n - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n - dtype: the data type of the underlying ndarray.\n\n If an ndarray index is not associated with a provided identifier, the\n 'get' method should return `null`.\n\n Default: `ndindex`.\n\n Returns\n -------\n fcn: Function\n Function for converting an ndarray to an object supporting fancy\n indexing.\n\n Examples\n --------\n // Create a normal ndarray...\n > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n > var d = [ 2, 2 ];\n > var s = [ 2, 1 ];\n > var o = 0;\n > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n // Create a function for converting ndarrays to fancy ndarrays:\n > var f = ndarray2fancy.factory();\n\n // Convert the normal ndarray to a fancy ndarray:\n > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n Wraps a provided ndarray as an ndarray index object.\n\n For documentation and usage, see `ndindex`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndarrayIndex\n ndarray index instance.\n\n Examples\n --------\n > var opts = { 'dtype': 'int32' };\n > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n > var arr = array( buf, opts );\n > var idx = ndarray2fancy.idx( arr );\n\n See Also\n --------\n array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n Serializes an ndarray as a JSON object.\n\n This function does *not* serialize data outside of the buffer region defined\n by the ndarray view.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n JSON object.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarray2json( arr )\n {...}\n\n See Also\n --------\n array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n\n The output array contains the following modes:\n\n - 'none': only allow casting between identical types.\n - 'equiv': allow casting between identical and byte swapped types.\n - 'safe': only allow \"safe\" casts.\n - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n downcasts.\n - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n between signed integers or between floats).\n - 'unsafe': allow casting between all types (including between integers and\n floats).\n\n Returns\n -------\n out: Array\n List of ndarray casting modes.\n\n Examples\n --------\n > var out = ndarrayCastingModes()\n [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n Returns the underlying data buffer of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: ArrayLikeObject\n Underlying data buffer.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n \n\n See Also\n --------\n array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n Returns the data type of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n dt: string\n Data type.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n 'float64'\n\n See Also\n --------\n array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n Returns a list of ndarray data types.\n\n When not provided a data type \"kind\", the function returns an array\n containing the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex32: half-precision complex floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - generic: values of any type.\n - int8: signed 8-bit integers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - binary: binary.\n\n The function supports the following data type \"kinds\":\n\n - floating_point: floating-point data types.\n - real_floating_point: real-valued floating-point data types.\n - complex_floating_point: complex-valued floating-point data types.\n - boolean: boolean data types.\n - integer: integer data types.\n - signed_integer: signed integer data types.\n - unsigned_integer: unsigned integer data types.\n - real: real-valued data types.\n - numeric: numeric data types.\n - typed: typed data types.\n - integer_index: integer index data types.\n - boolean_index: boolean index data types.\n - mask_index: mask index data types.\n - typed_index: typed index data types.\n - index: index data types.\n - all: all data types.\n\n Additionally, the function supports extending the \"kinds\" listed above by\n appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n Parameters\n ----------\n kind: string (optional)\n Data type kind.\n\n Returns\n -------\n out: Array\n List of ndarray data types.\n\n Examples\n --------\n > var out = ndarrayDataTypes()\n [...]\n > out = ndarrayDataTypes( 'floating_point' )\n [...]\n > out = ndarrayDataTypes( 'floating_point_and_generic' )\n [...]\n\n\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n \n\n\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n \n\n\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n \n\n\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n \n\n\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n \n\n\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n \n\n\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n \n\n\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n \n\n\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n \n\n\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n \n\n\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n \n\n\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n \n\n\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n \n\n\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n \n\n\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n \n\n\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.binary\n ","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.boolean\n ","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex32\n ","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex64\n ","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.complex128\n ","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float16\n ","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float32\n ","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.float64\n ","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.generic\n ","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int8\n ","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int16\n ","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.int32\n ","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8\n ","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint8c\n ","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint16\n ","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n\n Returns\n -------\n out: DataType\n Data type instance.\n\n Examples\n --------\n > var dt = ndarrayDataTypes.uint32\n \n\n See Also\n --------\n arrayDataTypes, array, ndarray, typedarrayDataTypes","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n Returns an ndarray function interface which performs multiple dispatch.\n\n An ndarray function interface has the following signature:\n\n f( x, y, ... )\n\n where\n\n - x: ndarray.\n - y: ndarray.\n - ...: additional ndarrays.\n\n The number of parameters is derived from `nargs`, the number of input\n ndarrays is derived from `nin`, and the number of output ndarrays is derived\n from `nout`.\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of ndarray functions. An ndarray function should have the following\n signature:\n\n f( arrays, data )\n\n where\n\n - arrays: array containing input and output ndarrays.\n - data: ndarray function data (e.g., a callback).\n\n For convenience, a single ndarray function may be provided which will be\n invoked whenever the ndarray argument data types match a sequence of\n types in `types`. Providing a single ndarray function is particularly\n convenient for the case where, regardless of array data types,\n traversing arrays remains the same, but the ndarray function `data`\n differs (e.g., callbacks which differ based on the array data types).\n\n types: ArrayLikeObject\n One-dimensional list of ndarray argument data types.\n\n data: ArrayLikeObject|null\n ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n function interface does **not** provide a `data` argument to an invoked\n ndarray function.\n\n nargs: integer\n Total number of ndarray function interface arguments.\n\n nin: integer\n Number of input ndarrays.\n\n nout: integer\n Number of output ndarrays.\n\n Returns\n -------\n fcn: Function\n ndarray function interface.\n\n Examples\n --------\n // Define ndarray argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of ndarray function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create an ndarray function interface for applying unary callbacks:\n > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n // Create an input ndarray:\n > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Create an output ndarray:\n > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n // Compute the element-wise absolute value:\n > f( x, y );\n > ybuf\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n See Also\n --------\n array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n Returns a specified flag for a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n name: string|symbol\n Flag name.\n\n Returns\n -------\n out: any\n Flag value.\n\n Examples\n --------\n > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n \n\n See Also\n --------\n array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n Returns the flags of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Object\n Flags.\n\n Examples\n --------\n > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n {...}\n\n See Also\n --------\n array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n\n The output array contains the following modes:\n\n - throw: specifies that a function should throw an error when an index is\n outside a restricted interval.\n - normalize: specifies that a function should normalize negative indices and\n throw an error when an index is outside a restricted interval.\n - wrap: specifies that a function should wrap around an index using modulo\n arithmetic.\n - clamp: specifies that a function should set an index less than zero to\n zero (minimum index) and set an index greater than a maximum index value to\n the maximum possible index.\n\n Returns\n -------\n out: Array\n List of ndarray index modes.\n\n Examples\n --------\n > var out = ndarrayIndexModes()\n [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n See Also\n --------\n array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n Converts an ndarray-like object to an ndarray.\n\n If provided a read-only ndarray, the function returns a read-only ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray-like object.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var out = ndarraylike2ndarray( arr )\n \n\n See Also\n --------\n array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n\n The function does *not* provide precision guarantees for non-integer-valued\n numbers. In other words, the function returns the smallest possible\n floating-point (i.e., inexact) data type for storing numbers having\n decimals.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n Returns\n -------\n dt: string\n ndarray data type.\n\n Examples\n --------\n > var dt = ndarrayMinDataType( 3.141592653589793 )\n 'float32'\n > dt = ndarrayMinDataType( 3 )\n 'uint8'\n > dt = ndarrayMinDataType( -3 )\n 'int8'\n > dt = ndarrayMinDataType( '-3' )\n 'generic'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be cast.\n\n Examples\n --------\n > var out = ndarrayMostlySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n Returns the next larger ndarray data type of the same kind.\n\n If not provided a data type, the function returns a table.\n\n If a data type does not have a next larger data type or the next larger type\n is not supported, the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Next larger type(s).\n\n Examples\n --------\n > var out = ndarrayNextDataType( 'float32' )\n 'float64'\n\n See Also\n --------\n ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Index offset.\n\n Examples\n --------\n > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n 0\n\n See Also\n --------\n array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n Returns the layout order of a provided ndarray.\n\n If unable to resolve a layout order, the function returns `null`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: string|null\n Layout order.\n\n Examples\n --------\n > var opts = { 'order': 'row-major' };\n > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n 'row-major'\n\n See Also\n --------\n array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n\n The output array contains the following orders:\n\n - row-major: row-major (C-style) order.\n - column-major: column-major (Fortran-style) order.\n\n Returns\n -------\n out: Array\n List of ndarray orders.\n\n Examples\n --------\n > var out = ndarrayOrders()\n [ 'row-major', 'column-major' ]\n\n See Also\n --------\n array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n\n If not provided data types, the function returns a type promotion table.\n\n If a data type to which data types can be safely cast does *not* exist (or\n is not supported), the function returns `-1`.\n\n If provided an unrecognized data type, the function returns `null`.\n\n Parameters\n ----------\n dtype1: any (optional)\n ndarray data type value.\n\n dtype2: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|string|integer|null\n Promotion rule(s).\n\n Examples\n --------\n > var out = ndarrayPromotionRules( 'float32', 'int32' )\n 'float64'\n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast.\n\n Examples\n --------\n > var out = ndarraySafeCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n\n If not provided an ndarray data type, the function returns a casting table.\n\n If provided an unrecognized ndarray data type, the function returns `null`.\n\n Parameters\n ----------\n dtype: any (optional)\n ndarray data type value.\n\n Returns\n -------\n out: Object|Array|null\n ndarray data types to which a data type can be safely cast or cast\n within the same \"kind\".\n\n Examples\n --------\n > var out = ndarraySameKindCasts( 'float32' )\n \n\n See Also\n --------\n ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n Returns the shape of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Shape.\n\n Examples\n --------\n > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n [ 3, 3, 3 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n Returns the stride along a specified dimension for a provided ndarray.\n\n A \"stride\" is the linear distance (i.e., number of elements) between\n adjacent elements along a specified dimension.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Stride.\n\n Examples\n --------\n > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n 9\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n Returns the strides of a provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n out: Array\n Strides.\n\n Examples\n --------\n > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n [ 9, 3, 1 ]\n\n See Also\n --------\n array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n Returns an ndarray element.\n\n Negative indices are resolved relative to the last element along the\n respective dimension, with the last element corresponding to `-1`.\n\n If provided out-of-bounds indices, the function always returns `undefined`.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n indices: ...integer (optional)\n Index arguments. The number of index arguments must equal the number of\n dimensions.\n\n Returns\n -------\n out: any\n Element value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > ndat( x, 0, 1 )\n 2\n > ndat( x, 1, 0 )\n 3\n\n See Also\n --------\n array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n Returns an uninitialized ndarray having a specified shape and data type.\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Default: 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndempty( [ 2, 2 ] )\n \n\n See Also\n --------\n ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n In browser environments, the function always returns zero-filled ndarrays.\n\n If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n For returned ndarrays whose underlying memory is *not* initialized, memory\n contents are unknown and may contain *sensitive* data.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Overrides the input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndemptyLike( x )\n \n\n See Also\n --------\n ndempty, ndzerosLike\n","ndfill":"\nndfill( x, value )\n Fills an input ndarray with a specified value.\n\n If `value` is a number and `x` has a complex data type, the function fills\n an input ndarray with a complex number whose real component equals the\n provided scalar `value` and whose imaginary component is zero.\n\n The function *mutates* the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n value: any\n Scalar value. Must be able to safely cast to the input ndarray data\n type. Scalar values having floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., a scalar double-precision floating-point number can be\n used to fill a 'float32' input ndarray).\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > ndfill( x, 10.0 );\n > x.get( 0, 0 )\n 10.0\n\n See Also\n --------\n ndfillBy, ndmap, ndzeros\n","ndfillBy":"\nndfillBy( x, fcn[, thisArg] )\n Fills an input ndarray according to a callback function.\n\n The function *mutates* the input ndarray.\n\n The function assumes that each element in the underlying input ndarray data\n buffer has one, and only one, corresponding element in input ndarray view\n (i.e., a provided ndarray is not a broadcasted ndarray view).\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarrayLike\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Returns\n -------\n out: ndarrayLike\n Input ndarray.\n\n Examples\n --------\n > var opts = { 'dtype': 'float64' };\n > var x = ndzeros( [ 2, 2 ], opts );\n > x.get( 0, 0 )\n 0.0\n > function fcn() { return 10.0; };\n > ndfillBy( x, fcn );\n > x.get( 0, 0 )\n 10.0\n > x.get( 0, 1 )\n 10.0\n > x.get( 1, 0 )\n 10.0\n > x.get( 1, 1 )\n 10.0\n\n See Also\n --------\n ndfill, ndmap, ndzeros\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v > 2.0; };\n > var y = ndfilter( x, f )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n If a provided callback function returns `undefined`, the function skips the\n respective ndarray element. If the callback function returns a value other\n than `undefined`, the function stores the callback's return value in the\n output ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n > var y = ndfilterMap( x, f )\n [ 30.0, 40.0 ]\n\n See Also\n --------\n ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n Invokes a callback function once for each ndarray element.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n > ndforEach( x, f );\n\n See Also\n --------\n ndmap","ndims":"\nndims( x )\n Returns the number of ndarray dimensions.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of dimensions.\n\n Examples\n --------\n > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n 3\n\n See Also\n --------\n array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n Wraps a provided array as an ndarray index object.\n\n ndarray index instances have no explicit functionality; however, they are\n used by \"fancy\" ndarrays for element retrieval and assignment.\n\n By default, an instance is invalidated and removed from an internal cache\n immediately after a consumer resolves the underlying data associated with an\n instance using the `get` static method. Immediate invalidation and cache\n removal ensures that references to the underlying ndarray are not the source\n of memory leaks.\n\n Because instances leverage an internal cache implementing the Singleton\n pattern, one must be sure to use the same constructor as consumers. If one\n uses a different constructor, the consumer will *not* be able to resolve the\n original wrapped ndarray, as the consumer will attempt to resolve an\n instance in the wrong internal cache.\n\n Because non-persisted instances are freed after first use, in order to avoid\n holding onto memory and to allow garbage collection, one should avoid\n scenarios in which an instance is never used.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n options.kind: string (optional)\n Specifies whether a provided ndarray is a specialized input ndarray\n \"kind\". This option is only applicable for integer input ndarrays. Must\n be one of the following:\n\n - cartesian: a provided input ndarray contains Cartesian indices.\n - linear: a provided input ndarray contains indices representing\n locations in linear memory.\n\n Default: ''.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n\n\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n \n\n\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}\n\n\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n \n\n\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'\n\n\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n \n\n\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true\n\n\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'\n\n\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n \n\n\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n \n\n\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n Frees the instance associated with a provided identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an instance was successfully freed.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.free( idx.id )\n ","ndindex.get":"\nndindex.get( id )\n Returns the ndarray associated with the instance having a provided\n identifier.\n\n Parameters\n ----------\n id: string\n Instance identifier.\n\n Returns\n -------\n out: Object\n Object containing ndarray data.\n\n out.data: ndarray\n The underlying ndarray associated with the provided identifier.\n\n out.type: string\n The type of ndarray index.\n\n out.dtype: string\n The data type of the underlying ndarray.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > ndindex.get( idx.id )\n {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n Returns an ndarray index containing Cartesian indices.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'cartesian'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n\n This is a convenience method for calling `ndindex` with `kind` set to\n 'linear'.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.persist: boolean (optional)\n Boolean indicating whether to continue persisting an index object after\n first usage. Default: false.\n\n Returns\n -------\n out: ndindex\n Index instance.\n\n Examples\n --------\n > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n\n Returns\n -------\n out: ndarray\n Array data.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.data\n ","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n\n Returns\n -------\n out: string\n Array data type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.dtype\n 'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n\n Returns\n -------\n out: string\n String identifier.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.id\n ","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an ndarray index is actively cached.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.isCached\n true","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n\n Returns\n -------\n out: string\n Index kind.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n > idx.kind\n 'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n\n Returns\n -------\n out: string\n Index type.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.type\n ","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n\n Returns\n -------\n str: string\n Serialized string.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toString()\n ","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n > var idx = new ndindex( x );\n > idx.toJSON()\n { 'type': 'ndindex', ... }\n\n See Also\n --------\n array, ndarray, FancyArray, ndslice, ndarray2fancy","nditer2arrayEach":"\nnditer2arrayEach( iterator )\n Returns an iterator which converts each iterated ndarray to a generic array.\n\n If an environment supports Symbol.iterator and a provided iterator is\n iterable, the returned iterator is iterable.\n\n Parameters\n ----------\n iterator: Object\n Input iterator.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditer2arrayEach( nditerRows( x ) );\n > var v = it.next().value\n [ 1, 2 ]\n > v = it.next().value\n [ 3, 4 ]\n\n See Also\n --------\n ndarray, ndarray2array\n","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumnEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ null, 0 ]\n > ndarray2array( v[ 1 ] )\n [ 1, 3 ]\n > v = it.next().value;\n > v[ 0 ]\n [ null, 1 ]\n > ndarray2array( v[ 1 ] )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerColumns( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 3 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 2, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerEntries( x );\n > var v = it.next().value\n [ [ 0, 0 ], 1 ]\n > v = it.next().value\n [ [ 0, 1 ], 2 ]\n\n See Also\n --------\n ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n shape: Array\n Input shape.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator iterates over\n the last dimensions first, thus corresponding to iteration over\n contiguous data stored in row-major order. Must be either 'row-major'\n or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerIndices( x.shape );\n > var v = it.next().value\n [ 0, 0 ]\n > v = it.next().value\n [ 0, 1 ]\n\n See Also\n --------\n ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n Returns an iterator which iterates over interleaved subarrays.\n\n For input ndarrays supporting read-only views, the function returns\n *read-only* views of interleaved subarrays. As input ndarrays may be\n broadcasted, a view is typically *not* contiguous. As more than one element\n of a returned view may refer to the same memory location, writing to a view\n may affect multiple elements. If you need to write to a subarray, copy the\n subarray before attempting mutation.\n\n The function throws an error if provided broadcast-incompatible ndarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n arr: ArrayLike\n Input ndarrays. All ndarrays must be broadcast-compatible. After\n broadcasting, each broadcasted input ndarray must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack after broadcasting.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrices( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerMatrixEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null, null ]\n > ndarray2array( v[ 1 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n\n Each returned index is a Cartesian index (i.e., an array of subscripts/\n dimension indices). A dimension index equal to `null` indicates that all\n values along the respective dimension are included in the returned ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRowEntries( x );\n > var v = it.next().value;\n > v[ 0 ]\n [ 0, null ]\n > ndarray2array( v[ 1 ] )\n [ 1, 2 ]\n > v = it.next().value;\n > v[ 0 ]\n [ 1, null ]\n > ndarray2array( v[ 1 ] )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerRows( x );\n > var v = it.next().value;\n > ndarray2array( v )\n [ 1, 2 ]\n > v = it.next().value;\n > ndarray2array( v )\n [ 3, 4 ]\n\n See Also\n --------\n nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n options.keepdim: boolean (optional)\n Boolean indicating whether returned views should include the selected\n dimension as a singleton dimension. Including the selected dimension as\n a singleton dimension can be useful when wanting to ensure that returned\n views remain broadcast compatible with the input ndarray. Default:\n false.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSelectDimension( x, 0 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `dims.length+1` dimensions.\n\n dims: Array\n Indices of dimensions to stack. If a dimension index is less than zero,\n the index is resolved relative to the last dimension, with the last\n dimension corresponding to the value `-1`. The list of indices must be\n unique and resolve to dimension indices sorted in ascending order.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerStacks( x, [ 1, 2 ] );\n > var v = it.next().value\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray for which to create the iterator. Must have at least\n `ndims+1` dimensions.\n\n ndims: integer\n Number of dimensions to stack.\n\n options: Object (optional)\n Options.\n\n options.readonly: boolean (optional)\n Boolean indicating whether returned ndarray views should be read-only.\n If the input ndarray is read-only, setting this option to `false` raises\n an exception. Default: true.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n > var it = nditerSubarrays( x, 2 );\n > var v = it.next().value;\n > ndarray2array( v )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an ndarray's `@@iterator` method, regardless of whether this method\n is defined.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Index iteration order. By default, the returned iterator returns values\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n > var it = nditerValues( x );\n > var v = it.next().value\n 1\n > v = it.next().value\n 2\n\n See Also\n --------\n ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n\n The callback function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n fcn: Function\n Callback function.\n\n thisArg: any (optional)\n Callback function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v*10.0; };\n > var y = ndmap( x, f )\n [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n\n The predicate function is provided the following arguments:\n\n - value: current array element.\n - indices: current array element indices.\n - arr: the input ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n options: Object (optional)\n Function options.\n\n options.dtype: string (optional)\n Output ndarray data type. Overrides using the input array's inferred\n data type.\n\n options.order: string (optional)\n Index iteration order. By default, the function iterates over elements\n according to the layout order of the provided array. Accordingly, for\n row-major input arrays, the last dimension indices increment fastest.\n For column-major input arrays, the first dimension indices increment\n fastest. To override the inferred order and ensure that indices\n increment in a specific manner, regardless of the input array's layout\n order, explicitly set the iteration order. Note, however, that iterating\n according to an order which does not match that of the input array may,\n in some circumstances, result in performance degradation due to cache\n misses. Must be either 'row-major' or 'column-major'.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Predicate function execution context.\n\n Examples\n --------\n > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n > function f( v ) { return v <= 2.0; };\n > var y = ndreject( x, f );\n > ndarray2array( y )\n [ 3.0, 4.0 ]\n\n See Also\n --------\n ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n Returns a read-only view of an input ndarray.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of array\n dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var s = new MultiSlice( null, 1 )\n \n > var y = ndslice( x, s )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n\n The function supports three (mutually exclusive) means of providing slice\n arguments:\n\n 1. Providing a single MultiSlice object.\n 2. Providing a single array containing slice arguments.\n 3. Providing slice arguments as separate arguments.\n\n An individual slice argument must be either a Slice, an integer, null, or\n undefined.\n\n In all cases, the number of slice dimensions must match the number of output\n array dimensions.\n\n If providing a MultiSlice object or an array of slice arguments, no other\n slice arguments should be provided.\n\n Mixing function invocation styles (e.g., providing multiple MultiSlice\n objects or providing an array of slice arguments followed by additional\n slice arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array. The input array must be broadcast compatible with the\n output array view and must have a data type which can be safely cast to\n the output array data type. Floating-point data types (both real and\n complex) are allowed to downcast to a lower precision data type of the\n same kind (e.g., element values from a 'float64' input array can be\n assigned to corresponding elements in a 'float32' output array).\n\n y: ndarray\n Output array. The output array must be writable.\n\n s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n Slice arguments.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking. Default:\n true.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var y = ndzeros( [ 2, 2 ] )\n \n > var x = scalar2ndarray( 3.0 )\n \n > var s = new MultiSlice( null, 1 )\n \n > var out = ndsliceAssign( x, y, s )\n \n > var bool = ( out === y )\n true\n > ndarray2array( y )\n [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n See Also\n --------\n array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n slice: Slice|integer|null|undefined\n Slice object or an integer. If provided `null` or `undefined`, the\n returned view includes all elements along a specified dimension. If\n provided an integer less than zero, the corresponding element along the\n specified dimension is resolved relative to the last element along that\n dimension. For negative integers, the last element corresponds to the\n value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimension( x, 1, 1 )\n \n > y.shape\n [ 2 ]\n > ndarray2array( y )\n [ 2, 4 ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n start: integer\n Starting index (inclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionFrom( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n dim: integer\n Index of dimension to slice. If less than zero, the index is resolved\n relative to the last dimension, with the last dimension corresponding to\n the value `-1`.\n\n stop: integer\n Ending index (exclusive). If less than zero, the corresponding element\n along the specified dimension is resolved relative to the last element\n along that dimension. For negative integers, the last element\n corresponds to the value `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceDimensionTo( x, 1, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 1 ], [ 3 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n Returns a read-only shifted view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing starting\n indices:\n\n 1. Providing a single array containing start arguments.\n 2. Providing start arguments as separate arguments.\n\n An individual start argument must be either an integer, null, or undefined.\n\n In all cases, the number of start indices must match the number of array\n dimensions.\n\n If providing an array of start arguments, no other start arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of start\n arguments followed by additional start arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n start: ...null|void|integer\n Starting indices (inclusive). If an element is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve a starting index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceFrom( x, 0, 1 )\n \n > y.shape\n [ 2, 1 ]\n > ndarray2array( y )\n [ [ 2 ], [ 4 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n Returns a read-only truncated view of an input ndarray.\n\n The function supports two (mutually exclusive) means of providing ending\n indices:\n\n 1. Providing a single array containing stop arguments.\n 2. Providing stop arguments as separate arguments.\n\n An individual stop argument must be either an integer, null, or undefined.\n\n In all cases, the number of stop indices must match the number of array\n dimensions.\n\n If providing an array of stop arguments, no other stop arguments should be\n provided.\n\n Mixing function invocation styles (e.g., providing an array of stop\n arguments followed by additional stop arguments) is not supported.\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n stop: ...null|void|integer\n Ending indices (exclusive). If an ending index is either `null` or\n `undefined`, the function returns a view containing all elements along\n that dimension. A negative integer indicates to resolve an ending index\n relative to the last element along a corresponding dimension, with the\n last element having index `-1`.\n\n options: Object (optional)\n Options.\n\n options.strict: boolean (optional)\n Boolean indicating whether to enforce strict bounds checking.\n Default: true.\n\n Returns\n -------\n out: ndarray\n Output array view.\n\n Examples\n --------\n > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n \n > x.shape\n [ 2, 2 ]\n > var y = ndsliceTo( x, 1, 1 )\n \n > y.shape\n [ 1, 1 ]\n > ndarray2array( y )\n [ [ 1 ] ]\n\n See Also\n --------\n array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n Returns a zero-filled ndarray having a specified shape and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a numeric or \"generic\" data type. Default:\n 'float64'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a numeric or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = ndzeros( [ 2, 2 ] )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n > var y = ndzerosLike( x )\n [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ]\n\n See Also\n --------\n ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: 0.\n\n Returns\n -------\n out: integer\n Next extended grapheme cluster break position.\n\n Examples\n --------\n > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n 5\n > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n 9\n > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n 3\n > out = nextGraphemeClusterBreak( '🌷' )\n -1\n\n See Also\n --------\n numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n\n The queue is fully drained after the current operation on the JavaScript\n stack runs to completion and before the event loop is allowed to continue.\n\n Parameters\n ----------\n clbk: Function\n Callback to invoke.\n\n ...args: any (optional)\n Arguments to provide to the callback upon invocation.\n\n Examples\n --------\n > function f() { console.log( 'beep' ); };\n > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n\n Returns\n -------\n out: Array\n Nightingale's data.\n\n Examples\n --------\n > var data = NIGHTINGALES_ROSE()\n [{...}, {...}, ...]\n\n References\n ----------\n - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n the British army during the late war with Russia*. London, United Kingdom:\n John W. Parker and Son..\n\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n\n Examples\n --------\n > NINF\n -Infinity\n\n See Also\n --------\n FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n\n Examples\n --------\n > NODE_VERSION\n \n\n","none":"\nnone( collection )\n Tests whether all elements in a collection are falsy.\n\n The function immediately returns upon encountering a truthy value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n Returns\n -------\n bool: boolean\n The function returns `true` if all elements are falsy; otherwise, the\n function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 0, 0, 0 ];\n > var bool = none( arr )\n true\n\n See Also\n --------\n any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, 3, 4 ];\n > var bool = noneBy( arr, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > noneByAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty collection, the function returns `true`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function positive( v ) { return ( v > 0 ); };\n > var arr = [ -1, -2, -3, -4 ];\n > var bool = noneByRight( arr, positive )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a truthy `result` value\n and calls the `done` callback with `null` as the first argument and `false`\n as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null` as\n the first argument and `true` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, predicate, done )\n 1000\n 2500\n 3000\n true\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 2500\n 3000\n 1000\n true\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > noneByRightAsync( arr, opts, predicate, done )\n 3000\n 2500\n 1000\n true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = noneByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n true\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n true\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object over which to iterate.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n > var bool = noneInBy( obj, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own non-enumerable properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var props = nonEnumerableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited non-enumerable property names and\n symbols.\n\n Examples\n --------\n > var props = nonEnumerablePropertiesIn( [] )\n\n See Also\n --------\n enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n Returns an array of an object's own non-enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNames( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited non-enumerable property names.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = nonEnumerablePropertyNamesIn( obj )\n e.g., [ 'beep', ... ]\n\n See Also\n --------\n keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n Returns an array of an object's own non-enumerable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbols( obj )\n\n See Also\n --------\n enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited non-enumerable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n See Also\n --------\n enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: property value.\n - index: property key.\n - object: the input object.\n\n The function immediately returns upon encountering a truthy return value.\n\n If provided an empty object, the function returns `true`.\n\n Parameters\n ----------\n object: Object\n Input object.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if the predicate function returns a falsy\n value for all own properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function isUnderage( v ) { return ( v < 18 ); };\n > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n > var bool = noneOwnBy( obj, isUnderage )\n false\n\n See Also\n --------\n anyOwnBy, everyOwnBy, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n obj: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = nonIndexKeys( obj )\n e.g., [ 'beep' ]\n\n See Also\n --------\n objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n A function which does nothing.\n\n Examples\n --------\n > noop();\n\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n\n The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n Returns\n -------\n out: integer\n Time in seconds since the epoch.\n\n Examples\n --------\n > var ts = now()\n \n\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n\n In browser environments, the number of CPUs is determined by querying the\n hardware concurrency API.\n\n In Node.js environments, the number of CPUs is determined via the `os`\n module.\n\n Examples\n --------\n > NUM_CPUS\n \n\n","num2words":"\nnum2words( value[, options] )\n Converts a number to a word representation.\n\n Parameters\n ----------\n value: integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - de: German.\n\n Default: `'en'`.\n\n Returns\n -------\n out: string\n Word representation of number.\n\n Examples\n --------\n > var out = num2words( 123 )\n 'one hundred twenty-three'\n\n > out = num2words( 16.31 )\n 'sixteen point three one'\n\n > out = num2words( 123, { 'lang': 'de' } )\n 'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n Returns a Number object.\n\n This constructor should be used sparingly. Always prefer number primitives.\n\n Parameters\n ----------\n value: number\n Value to wrap in a Number object.\n\n Returns\n -------\n out: Number\n Number object.\n\n Examples\n --------\n > var v = new Number( 5 )\n \n\n","numel":"\nnumel( x )\n Returns the number of elements in an ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n Returns\n -------\n n: integer\n Number of elements.\n\n Examples\n --------\n > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n 27\n\n See Also\n --------\n array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n\n Parameters\n ----------\n x: ndarray\n Input ndarray.\n\n dim: integer\n Dimension index. If less than zero, the index is resolved relative to\n the last dimension, with the last dimension corresponding to the value\n `-1`.\n\n Returns\n -------\n out: integer\n Dimension size.\n\n Examples\n --------\n > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n 4\n\n See Also\n --------\n array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n Returns the number of grapheme clusters in a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Number of grapheme clusters.\n\n Examples\n --------\n > var out = numGraphemeClusters( 'beep' )\n 4\n > out = numGraphemeClusters( '🌷' )\n 1\n\n See Also\n --------\n nextGraphemeClusterBreak\n","Object":"\nObject( value )\n Returns an object.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n If provided an existing object, the function returns the input value\n unchanged.\n\n Otherwise, if provided any other value (e.g., a number, string, etc), the\n function will return an object of the corresponding type.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: Object\n Output object.\n\n Examples\n --------\n > var o = new Object( null )\n {}\n > o = new Object( 5.0 )\n \n > o = new Object( 'beep' )\n \n\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }\n\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }\n\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []\n\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n \n\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false\n\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true\n\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true\n\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true\n\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2\n\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n \n\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}\n\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true\n\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true\n\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true\n\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n \n\n","Object.assign":"\nObject.assign( target, ...sources )\n Assigns enumerable and own properties from source objects to a target\n object.\n\n Parameters\n ----------\n target: Object\n Target object.\n\n sources: ...Object\n Source objects.\n\n Returns\n -------\n out: Object\n Target object.\n\n Examples\n --------\n > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n Creates a new object with a specified prototype object and properties.\n\n Parameters\n ----------\n prototype: Object\n Prototype object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n Defines properties for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n properties: Object\n Properties object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n Defines a property for an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n descriptor: Object\n Property descriptor.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.defineProperty( {}, 'a', {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': false\n })\n { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of [key, value] pairs.\n\n Examples\n --------\n > var o = Object.entries( { 'a': 1, 'b': 2 } )\n [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n Freezes an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.freeze( { 'a': 1 } )\n { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n Returns an object's own property descriptor.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n key: string\n Property key.\n\n Returns\n -------\n out: Object\n Property descriptor.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n Returns an object's own property descriptors.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Property descriptors.\n\n Examples\n --------\n > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n {\n 'a': {\n 'value': 1,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n },\n 'b': {\n 'value': 2,\n 'enumerable': true,\n 'configurable': true,\n 'writable': true\n }\n }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of symbol property names.\n\n Examples\n --------\n > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n Returns an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Prototype.\n\n Examples\n --------\n > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n ","Object.hasOwn":"\nObject.hasOwn( obj, p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.is":"\nObject.is( value1, value2 )\n Returns a boolean indicating whether two values are the same value.\n\n Parameters\n ----------\n value1: any\n First value.\n\n value2: any\n Second value.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether two values are the same value.\n\n Examples\n --------\n > var o = Object.is( 1, 1 )\n true\n > var o = Object.is( 1, '1' )\n false","Object.isExtensible":"\nObject.isExtensible( obj )\n Returns a boolean indicating whether an object is extensible.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is extensible.\n\n Examples\n --------\n > var o = Object.isExtensible( { 'a': 1 } )\n true","Object.isFrozen":"\nObject.isFrozen( obj )\n Returns a boolean indicating whether an object is frozen.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is frozen.\n\n Examples\n --------\n > var o = Object.isFrozen( { 'a': 1 } )\n false\n > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n true","Object.isSealed":"\nObject.isSealed( obj )\n Returns a boolean indicating whether an object is sealed.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object is sealed.\n\n Examples\n --------\n > var o = Object.isSealed( { 'a': 1 } )\n false\n > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n true","Object.keys":"\nObject.keys( obj )\n Returns an array of an object's own enumerable string-keyed property\n names.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property names.\n\n Examples\n --------\n > var o = Object.keys( { 'a': 1, 'b': 2 } )\n [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n Prevents the addition of new properties to an object.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.preventExtensions( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.seal( { 'a': 1 } )\n { 'a': 1 }\n > o.b = 2;\n > o\n { 'a': 1 }\n > delete o.a;\n > o\n { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n Sets an object's prototype.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n proto: Object\n Prototype.\n\n Returns\n -------\n out: Object\n Object.\n\n Examples\n --------\n > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n { 'a': 1 }\n > o.b\n 2","Object.values":"\nObject.values( obj )\n Returns an array of an object's own enumerable property values.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: Array\n Array of property values.\n\n Examples\n --------\n > var o = Object.values( { 'a': 1, 'b': 2 } )\n [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n\n Returns\n -------\n out: string\n String representing the object.\n\n Examples\n --------\n > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n ","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n\n Returns\n -------\n out: any\n Primitive value of the object.\n\n Examples\n --------\n > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object has a property with the specified\n name.\n\n Examples\n --------\n > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n\n Parameters\n ----------\n obj: Object\n Object.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object exists in another object's\n prototype chain.\n\n Examples\n --------\n > var p = { 'a': 1 };\n > var o = { '__proto__': p };\n > var b = o.isPrototypeOf( p );\n true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n Returns a boolean indicating whether an object's property is enumerable.\n\n Parameters\n ----------\n p: string\n Property name.\n\n Returns\n -------\n out: boolean\n Boolean indicating whether an object's property is enumerable.\n\n Examples\n --------\n > var o = { 'a': 1, 'b': 2 };\n > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n true","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n\n Examples\n --------\n > var o = new Object( null );\n > var ctr = o.constructor;\n ","objectEntries":"\nobjectEntries( obj )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var entries = objectEntries( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n\n Entry order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic return values.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n arr: Array\n Array containing key-value pairs.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var entries = objectEntriesIn( obj )\n e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n See Also\n --------\n objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n Creates an object from an array of key-value pairs.\n\n Parameters\n ----------\n entries: Array\n Input object.\n\n Returns\n -------\n out: Object\n Object created from `[key, value]` pairs.\n\n Examples\n --------\n > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n > var obj = objectFromEntries( entries )\n { 'beep': 'boop', 'foo': 'bar' }\n\n See Also\n --------\n objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n Inverts an object, such that keys become values and values become keys.\n\n Beware when providing objects having values which are themselves objects.\n The function relies on native object serialization (`#toString`) when\n converting values to keys.\n\n Insertion order is not guaranteed, as object key enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's keys, thus allowing for\n deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverse( obj )\n { 'beep': 'a', 'boop': 'b' }\n\n // Duplicate values:\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverse( obj )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverse( obj, { 'duplicates': false } )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n\n The transform function is provided three arguments:\n\n - key: object key.\n - value: object value corresponding to `key`.\n - obj: the input object.\n\n The value returned by a transform function should be a value which can be\n serialized as an object key. Hence, beware when providing objects having\n values which are themselves objects. The function relies on native object\n serialization (`#toString`) when converting transform function return values\n to keys.\n\n In older JavaScript engines, insertion order is not guaranteed, as object\n key enumeration was not specified according to the ECMAScript specification\n in earlier editions. In practice, however, most older engines use insertion\n order to sort an object's keys, thus allowing for deterministic inversion.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n options: Object (optional)\n Options.\n\n options.duplicates: boolean (optional)\n Boolean indicating whether to store keys mapped to duplicate values in\n arrays. Default: `true`.\n\n transform: Function\n Transform function.\n\n Returns\n -------\n out: Object\n Inverted object.\n\n Examples\n --------\n // Basic usage:\n > function transform( key, value ) { return key + value; };\n > var obj = { 'a': 'beep', 'b': 'boop' };\n > var out = objectInverseBy( obj, transform )\n { 'abeep': 'a', 'bboop': 'b' }\n\n // Duplicate values:\n > function transform( key, value ) { return value; };\n > obj = { 'a': 'beep', 'b': 'beep' };\n > out = objectInverseBy( obj, transform )\n { 'beep': [ 'a', 'b' ] }\n\n // Override duplicate values:\n > obj = {};\n > obj.a = 'beep';\n > obj.b = 'boop';\n > obj.c = 'beep';\n > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n { 'beep': 'c', 'boop': 'b' }\n\n See Also\n --------\n objectInverse\n","objectKeys":"\nobjectKeys( value )\n Returns an array of an object's own enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = objectKeys( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n Returns an array of an object's own enumerable property values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > var obj = { 'beep': 'boop', 'foo': 'bar' };\n > var vals = objectValues( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n Returns an array of an object's own and inherited enumerable property\n values.\n\n Value order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n Parameters\n ----------\n obj: ObjectLike\n Input object.\n\n Returns\n -------\n values: Array\n Value array.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var values = objectValuesIn( obj )\n e.g., [ 'boop', 'bar' ]\n\n See Also\n --------\n objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n Returns a partial object copy excluding specified keys.\n\n The function returns a shallow copy.\n\n The function ignores non-existent keys.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to exclude.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omit( obj1, 'b' )\n { 'a': 1 }\n\n See Also\n --------\n omitBy\n","omitBy":"\nomitBy( obj, predicate )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n\n The function returns a shallow copy.\n\n The function only copies own properties. Hence, the function never copies\n inherited properties.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) { return ( value > 1 ); };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = omitBy( obj1, predicate )\n { 'a': 1 }\n\n See Also\n --------\n omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n Asynchronously opens a file.\n\n Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n Under NTFS, if the path contains a colon, Node.js will open a file system\n stream.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon opening a file.\n\n Examples\n --------\n > function onOpen( error, fd ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... close.sync( fd );\n ... }\n ... };\n > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n Synchronously opens a file.\n\n Parameters\n ----------\n path: string|Buffer\n Filename.\n\n flags: string|number (optional)\n File system flags. Default: 'r'.\n\n mode: integer (optional)\n File mode (permission and sticky bits). This sets the file mode, but\n only if the file was created. On Windows, only the write permission can\n be manipulated. Default: 0o666.\n\n Returns\n -------\n fd: Error|integer\n File descriptor.\n\n Examples\n --------\n > var fd = open.sync( './beep/boop.txt' );\n > if ( !isError( fd ) ) { close.sync( fd ); };\n\n See Also\n --------\n close, exists, readFile","openURL":"\nopenURL( url )\n Opens a URL in a user's default browser.\n\n In a non-browser environment, the function returns an unreferenced child\n process. In a browser environment, the function returns a reference to a\n `window` object.\n\n Parameters\n ----------\n url: string\n URL to open.\n\n Returns\n -------\n out: process|Window\n Child process or `window` object.\n\n Examples\n --------\n > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n Parameters\n ----------\n value: string|integer\n Input value.\n\n options: Object (optional)\n Options.\n\n options.lang: string (optional)\n Language code. Supported languages:\n\n - en: English.\n - es: Spanish.\n - fin: Finnish.\n - fr: French.\n - de: Dutch.\n - it: Italian.\n - pt: Portuguese.\n - swe: Swedish.\n\n Default: `'en'`.\n\n options.suffixOnly: boolean (optional)\n Boolean indicating whether to return only the suffix. Default: `false`.\n\n options.gender: string (optional)\n Grammatical gender (used if applicable); must be either 'masculine' or\n 'feminine'. Default: `'masculine'`.\n\n Returns\n -------\n out: string\n Ordinal string or suffix.\n\n Examples\n --------\n > var out = ordinalize( '1' )\n '1st'\n > out = ordinalize( 2, { 'suffixOnly': true } )\n 'nd'\n > out = ordinalize( '3', { 'lang': 'es' } )\n '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n\n The data consists of 21 attributes:\n\n - obs: observation number.\n - town: town name.\n - town_id: town identifier.\n - tract: tract identifier.\n - lon: longitude.\n - lat: latitude.\n - medv: median value of owner-occupied homes in $1000's.\n - cmedv: corrected median value of owner-occupied homes in $1000's.\n - crim: per capita crime rate by town.\n - zn: proportion of residential land zoned for lots over 25,000 square feet.\n - indus: proportion of non-retail business acres per town.\n - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n - nox: nitric oxides concentration (parts per 10 million).\n - rm: average number of rooms per dwelling.\n - age: proportion of owner-occupied units built prior to 1940.\n - dis: weighted distances to five Boston employment centers.\n - rad: index of accessibility to radial highways.\n - tax: full-value property-tax rate per $10,000.\n - ptratio: pupil-teacher ratio by town.\n - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n - lstat: percent lower status of the population.\n\n The dataset can be used to predict two dependent variables: 1) nitrous oxide\n level and 2) median home value.\n\n The median home value field seems to be censored at 50.00 (corresponding to\n a median value of $50,000). Censoring is suggested by the fact that the\n highest median value of exactly $50,000 is reported in 16 cases, while 15\n cases have values between $40,000 and $50,000. Values are rounded to the\n nearest hundred.\n\n The dataset contains eight corrections to miscoded median values, as\n documented by Gilley and Pace (1996).\n\n The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n by including geo-referencing and spatial estimation for each observation.\n\n Returns\n -------\n out: Array\n Boston house prices.\n\n Examples\n --------\n > var data = PACE_BOSTON_HOUSE_PRICES()\n [ {...}, {...}, ... ]\n\n References\n ----------\n - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n the demand for clean air.\" _Journal of Environmental Economics and\n Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n doi:10.1006/jeem.1996.0052.\n - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n Configuration of the Data to Improve Estimation.\" _The Journal of Real\n Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n See Also\n --------\n HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n Pads a `string` such that the padded `string` has length `len`.\n\n Any padding which does not evenly divide available space is trimmed such\n that the returned string length is always `len`.\n\n If `len < str.length`, the input string is trimmed.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n options: Object (optional)\n Options.\n\n options.lpad: string (optional)\n String used to left pad.\n\n options.rpad: string (optional)\n String used to right pad.\n\n options.centerRight: boolean (optional)\n Boolean indicating whether to center right in the event of a tie.\n Default: `false` (i.e., center left).\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n // Standard usage:\n > var out = pad( 'a', 5 )\n 'a '\n\n // Left pad:\n > out = pad( 'a', 10, { 'lpad': 'b' } )\n 'bbbbbbbbba'\n\n // Right pad:\n > out = pad( 'a', 12, { 'rpad': 'b' } )\n 'abbbbbbbbbbb'\n\n // Center an input string:\n > var opts = { 'lpad': 'a', 'rpad': 'c' };\n > out = pad( 'b', 11, opts )\n 'aaaaabccccc'\n\n // Left center:\n > opts.centerRight = false;\n > out = pad( 'b', 10, opts )\n 'aaaabccccc'\n\n // Right center:\n > opts.centerRight = true;\n > out = pad( 'b', 10, opts )\n 'aaaaabcccc'\n\n // Output string always length `len`:\n > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n > out = pad( 'beep', 10, opts )\n 'boobeepwoo'\n\n // Pad right, trim right:\n > out = pad( 'beep', 2 )\n 'be'\n\n // Pad left, trim left:\n > opts = { 'lpad': 'b' };\n > out = pad( 'beep', 2, opts )\n 'ep'\n\n // Pad both, trim both:\n > opts = { 'lpad': '@', 'rpad': '!' };\n > out = pad( 'beep', 2, opts )\n 'ee'\n\n // Pad both, trim both starting from left:\n > out = pad( 'abcdef', 3, opts )\n 'cde'\n\n // Pad both, trim both starting from right:\n > opts.centerRight = true;\n > out = pad( 'abcdef', 3, opts )\n 'bcd'\n\n See Also\n --------\n lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n\n The `method` parameter can be one of the following values:\n\n - bh: Benjamini-Hochberg procedure controlling the False Discovery\n Rate (FDR).\n - bonferroni: Bonferroni correction fixing the family-wise error rate\n by multiplying the p-values with the number of comparisons. The Bonferroni\n correction is usually a too conservative adjustment compared to the others.\n - by: Procedure by Benjamini & Yekutieli for controlling the False\n Discovery Rate (FDR) under dependence.\n - holm: Hommel's method controlling family-wise error rate. It is\n uniformly more powerful than the Bonferroni correction.\n - hommel: Hommel's method, which is valid when hypothesis tests are\n independent. It is more expensive to compute than the other methods.\n\n By default, the number of comparisons for which the p-values should be\n corrected is equal to the number of provided p-values. Alternatively, it is\n possible to set `comparisons` to a number greater than the length of\n `pvals`. In that case, the methods assume `comparisons - pvals.length`\n unobserved p-values that are greater than all observed p-values (for Holm's\n method and the Bonferroni correction) or equal to `1` for the remaining\n methods.\n\n Parameters\n ----------\n pvals: Array\n P-values to be adjusted.\n\n method: string\n Correction method.\n\n comparisons: integer (optional)\n Number of comparisons. Default value: `pvals.length`.\n\n Returns\n -------\n out: Array\n Array containing the corrected p-values.\n\n Examples\n --------\n > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n > var out = padjust( pvalues, 'bh' )\n [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n > out = padjust( pvalues, 'bonferroni' )\n [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'by' )\n [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'holm' )\n [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n > out = padjust( pvalues, 'hommel' )\n [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function add( x, y ) { return x + y; };\n > var add2 = papply( add, 2 );\n > var sum = add2( 3 )\n 5\n\n See Also\n --------\n papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n\n The implementation does not set the `length` property of the returned\n function. Accordingly, the returned function `length` is always zero.\n\n The evaluation context is always `null`.\n\n Parameters\n ----------\n fcn: Function\n Function to partially apply.\n\n args: ...any\n Arguments to partially apply.\n\n Returns\n -------\n out: Function\n Partially applied function.\n\n Examples\n --------\n > function say( text, name ) { return text + ', ' + name + '.'; };\n > var toGrace = papplyRight( say, 'Grace Hopper' );\n > var str = toGrace( 'Hello' )\n 'Hello, Grace Hopper.'\n > str = toGrace( 'Thank you' )\n 'Thank you, Grace Hopper.'\n\n See Also\n --------\n papply\n","parallel":"\nparallel( files, [options,] clbk )\n Executes scripts in parallel.\n\n Relative file paths are resolved relative to the current working directory.\n\n Ordered script output does not imply that scripts are executed in order. To\n preserve script order, execute the scripts sequentially via some other\n means.\n\n Parameters\n ----------\n files: Array\n Script file paths.\n\n options: Object (optional)\n Options.\n\n options.cmd: string (optional)\n Executable file/command. Default: `'node'`.\n\n options.concurrency: integer (optional)\n Number of scripts to execute concurrently. Script concurrency cannot\n exceed the number of scripts. By specifying a concurrency greater than\n the number of workers, a worker may be executing more than `1` script at\n any one time. While not likely to be advantageous for synchronous\n scripts, setting a higher concurrency may be advantageous for scripts\n performing asynchronous tasks. If the script concurrency is less than\n the number of workers, the number of workers is reduced to match the\n specified concurrency. Default: `options.workers`.\n\n options.workers: integer (optional)\n Number of workers. Default: number of CPUs minus `1`.\n\n options.ordered: boolean (optional)\n Boolean indicating whether to preserve the order of script output. By\n default, the `stdio` output for each script is interleaved; i.e., the\n `stdio` output from one script may be interleaved with the `stdio`\n output from one or more other scripts. To preserve the `stdio` output\n order for each script, set the `ordered` option to `true`. Default:\n `false`.\n\n options.uid: integer (optional)\n Process user identity.\n\n options.gid: integer (optional)\n Process group identity.\n\n options.maxBuffer: integer (optional)\n Max child process `stdio` buffer size. This option is only applied when\n `options.ordered = true`. Default: `200*1024*1024`.\n\n clbk: Function\n Callback to invoke after executing all scripts.\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n Attempts to parse a string as JSON.\n\n Function behavior differs from `JSON.parse()` as follows:\n\n - throws a `TypeError` if provided any value which is not a string.\n - throws a `TypeError` if provided a `reviver` argument which is not a\n function.\n - returns, rather than throws, a `SyntaxError` if unable to parse a string\n as JSON.\n\n Parameters\n ----------\n str: string\n String to parse.\n\n reviver: Function (optional)\n Transformation function.\n\n Returns\n -------\n out: any|Error\n Parsed value or an error.\n\n Examples\n --------\n > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n { 'beep': 'boop' }\n\n // Provide a reviver:\n > function reviver( key, value ) {\n ... if ( key === '' ) { return value; }\n ... if ( key === 'beep' ) { return value; }\n ... };\n > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n > var out = parseJSON( str, reviver )\n { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n Converts a string to Pascal case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Pascal-cased string.\n\n Examples\n --------\n > var out = pascalcase( 'Hello World!' )\n 'HelloWorld'\n > out = pascalcase( 'beep boop' )\n 'BeepBoop'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER\n \n\n // POSIX environment:\n > var path = '/usr/bin:/bin:/usr/sbin';\n > var parts = path.split( PATH_DELIMITER )\n [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n // Windows environment:\n > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n > parts = path.split( PATH_DELIMITER )\n [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n See Also\n --------\n PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_POSIX\n ':'\n > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n > var paths = PATH.split( PATH_DELIMITER_POSIX )\n [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n\n Examples\n --------\n > PATH_DELIMITER_WIN32\n ';'\n > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n See Also\n --------\n PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n\n Examples\n --------\n > PATH_SEP\n \n\n // Windows environment:\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n // POSIX environment:\n > parts = 'foo/bar/baz'.split( PATH_SEP )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n\n Examples\n --------\n > PATH_SEP_POSIX\n '/'\n > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n\n Examples\n --------\n > PATH_SEP_WIN32\n '\\\\'\n > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n [ 'foo', 'bar', 'baz' ]\n\n See Also\n --------\n PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n Computes a Pearson product-moment correlation test between paired samples.\n\n By default, the function performs a t-test for the null hypothesis that the\n data in arrays or typed arrays `x` and `y` is not correlated. A test against\n a different population correlation can be carried out by supplying the `rho`\n option. In this case, a test using the Fisher's z transform is conducted.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Nnumber in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.rho: number (optional)\n Number denoting the correlation under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the Pearson product-moment correlation\n coefficient. The confidence interval is calculated using Fisher's\n z-transform.\n\n out.nullValue: number\n Assumed correlation under H0 (equal to the supplied `rho` option).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var rho = 0.5;\n > var x = new Array( 300 );\n > var y = new Array( 300 );\n > for ( var i = 0; i < 300; i++ ) {\n ... x[ i ] = base.random.normal( 0.0, 1.0 );\n ... y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n ... base.sqrt( 1.0 - (rho*rho) ) );\n ... }\n > var out = pcorrtest( x, y )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 10.115805615994121,\n ci: [ 0.4161679018930295, 0.5853122968949995 ],\n alternative: 'two-sided',\n method: 't-test for Pearson correlation coefficient',\n nullValue: 0,\n pcorr: 0.505582072355616,\n }\n\n // Print output:\n > var table = out.print()\n t-test for Pearson correlation coefficient\n\n Alternative hypothesis: True correlation coefficient is not equal to 0\n\n pValue: 0\n statistic: 9.2106\n 95% confidence interval: [0.3776,0.5544]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: string\n Percent-encoded string.\n\n Examples\n --------\n > var out = percentEncode( '☃' )\n '%E2%98%83'\n\n","PHI":"\nPHI\n Golden ratio.\n\n Examples\n --------\n > PHI\n 1.618033988749895\n\n","PI":"\nPI\n The mathematical constant `π`.\n\n Examples\n --------\n > PI\n 3.141592653589793\n\n See Also\n --------\n TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n\n Examples\n --------\n > PI_SQUARED\n 9.869604401089358\n\n See Also\n --------\n PI\n","pick":"\npick( obj, keys )\n Returns a partial object copy containing only specified keys.\n\n If a key does not exist as an own property in a source object, the key is\n ignored.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n keys: string|Array\n Keys to copy.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pick( obj1, 'b' )\n { 'b': 2 }\n\n See Also\n --------\n pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n Returns a function that applies specified arguments to a provided function.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > var bar = pickArguments( foo, [ 0, 2 ] );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n predicate: Function\n Predicate function.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > function predicate( key, value ) {\n ... return ( value > 1 );\n ... };\n > var obj1 = { 'a': 1, 'b': 2 };\n > var obj2 = pickBy( obj1, predicate )\n { 'b': 2 }\n\n See Also\n --------\n pick\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n\n Examples\n --------\n > PINF\n Infinity\n\n See Also\n --------\n NINF\n","pkg2alias":"\npkg2alias( pkg )\n Returns the alias associated with a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Alias.\n\n Examples\n --------\n > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n \n > v = pkg2alias( '@stdlib/math-base-special-sin' )\n \n\n See Also\n --------\n alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n Returns package names related to a specified package name.\n\n The function supports both internal and standalone package names.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: Array|null\n Related package names.\n\n Examples\n --------\n > var v = pkg2related( '@stdlib/math/base/special/sin' )\n [...]\n > v = pkg2related( '@stdlib/math-base-special-sin' )\n [...]\n\n See Also\n --------\n alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n Returns the standalone package name associated with a provided internal\n package name.\n\n Parameters\n ----------\n pkg: string\n Package name.\n\n Returns\n -------\n out: string|null\n Standalone package name.\n\n Examples\n --------\n > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n '@stdlib/math-base-special-sin'\n\n See Also\n --------\n alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n\n Possible values:\n\n - win32\n - darwin\n - linux\n - freebsd\n - sunos\n\n Examples\n --------\n > PLATFORM\n \n\n See Also\n --------\n ARCH\n","plot":"\nplot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = plot( x, y )\n \n\n See Also\n --------\n Plot\n","Plot":"\nPlot( [x, y,] [options] )\n Returns a plot instance for creating 2-dimensional plots.\n\n `x` and `y` arguments take precedence over `x` and `y` options.\n\n Parameters\n ----------\n x: Array|Array (optional)\n An array of arrays containing x-coordinate values.\n\n y: Array|Array (optional)\n An array of arrays containing y-coordinate values.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.autoView: boolean (optional)\n Boolean indicating whether to generate an updated view on a 'render'\n event. Default: false.\n\n options.colors: string|Array (optional)\n Data color(s). Default: 'category10'.\n\n options.description: string (optional)\n Plot description.\n\n options.engine: string (optional)\n Plot engine. Default: 'svg'.\n\n options.height: number (optional)\n Plot height (in pixels). Default: 400.\n\n options.labels: Array|Array (optional)\n Data labels.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.lineStyle: string|Array (optional)\n Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n Default: '-'.\n\n options.lineOpacity: number|Array (optional)\n Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.lineWidth: integer|Array (optional)\n Data line width (in pixels). Default: 2.\n\n options.paddingBottom: integer (optional)\n Bottom padding (in pixels). Default: 80.\n\n options.paddingLeft: integer (optional)\n Left padding (in pixels). Default: 90.\n\n options.paddingRight: integer (optional)\n Right padding (in pixels). Default: 20.\n\n options.paddingTop: integer (optional)\n Top padding (in pixels). Default: 80.\n\n options.renderFormat: string (optional)\n Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n options.symbols: string|Array (optional)\n Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n Default: 'none'.\n\n options.symbolsOpacity: number|Array (optional)\n Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n options.symbolsSize: integer|Array (optional)\n Symbols size (in pixels). Default: 6.\n\n options.title: string (optional)\n Plot title.\n\n options.viewer: string (optional)\n Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n or 'none'. Default: 'none'.\n\n options.width: number (optional)\n Plot width (in pixels). Default: 400.\n\n options.x: Array|Array (optional)\n x-coordinate values.\n\n options.xAxisOrient: string (optional)\n x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n options.xLabel: string (optional)\n x-axis label. Default: 'x'.\n\n options.xMax: number|null (optional)\n Maximum value of the x-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.xMin: number|null (optional)\n Minimum value of the x-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.xNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.xRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the x-axis.\n\n options.xRugOrient: string|Array (optional)\n x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n Default: 'bottom'.\n\n options.xRugOpacity: number|Array (optional)\n x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.xRugSize: integer|Array (optional)\n x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.xScale: string\n x-axis scale. Default: 'linear'.\n\n options.xTickFormat: string|null\n x-axis tick format. Default: null.\n\n options.y: Array|Array (optional)\n y-coordinate values.\n\n options.yAxisOrient: string (optional)\n x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n options.yLabel: string (optional)\n y-axis label. Default: 'y'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the maximum value is\n calculated from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the minimum value is\n calculated from the data. Default: null.\n\n options.yNumTicks: integer (optional)\n Number of x-axis tick marks. Default: 5.\n\n options.yRug: boolean|Array (optional)\n Boolean flag(s) indicating whether to render one or more rug plots along\n the y-axis.\n\n options.yRugOrient: string|Array (optional)\n y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n Default: 'left'.\n\n options.yRugOpacity: number|Array (optional)\n y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n options.yRugSize: integer|Array (optional)\n y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n options.yScale: string\n y-axis scale. Default: 'linear'.\n\n options.yTickFormat: string|null\n y-axis tick format. Default: null.\n\n Returns\n -------\n plot: Plot\n Plot instance.\n\n plot.render()\n Renders a plot as a virtual DOM tree.\n\n plot.view( [viewer] )\n Generates a plot view.\n\n plot.x\n x-coordinate values. An assigned value must be an array where each\n element corresponds to a plotted dataset.\n\n plot.y\n y-coordinate values. An assigned value must be an array, where each\n element corresponds to a plotted dataset.\n\n plot.labels\n Data labels. During plot creation, each plotted dataset is assigned a\n label. If the number of labels is less than the number of plotted\n datasets, labels are reused using modulo arithmetic.\n\n plot.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n plot.colors\n Data colors. To set the color all plotted datasets, provide a color\n name. To specify the colors for each dataset, provide an array of\n colors. During plot creation, each plotted dataset is assigned one of\n the provided colors. If the number of colors is less than the number of\n plotted datasets, colors are reused using modulo arithmetic. Lastly,\n colors may also be specified by providing the name of a predefined color\n scheme. The following schemes are supported: 'category10', 'category20',\n 'category20b', and 'category20c'.\n\n plot.lineStyle\n Data line style(s). The following line styles are supported: '-' (solid\n line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n and dots), and 'none' (no line). To specify the line style for each\n dataset, provide an array of line styles. During plot creation, each\n plotted dataset is assigned a line style. If the number of line styles\n is less than the number of plotted datasets, line styles are reused\n using modulo arithmetic.\n\n plot.lineOpacity\n Data line opacity, where an opacity of `0.0` make a line completely\n transparent and an opacity of `1.0` makes a line completely opaque. To\n specify the line opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.lineWidth\n Data line width(s). To specify the line width for each dataset, provide\n an array of widths. During plot creation, each plotted dataset is\n assigned a line width. If the number of line widths is less than the\n number of plotted datasets, line widths are reused using modulo\n arithmetic.\n\n plot.symbols\n Data symbols. The following symbols are supported: 'closed-circle'\n (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n To specify the symbols used for each dataset, provide an array of\n symbols. During plot creation, each plotted dataset is assigned a\n symbol. If the number of symbols is less than the number of plotted\n datasets, symbols are reused using modulo arithmetic.\n\n plot.symbolSize\n Symbols size. To specify the symbols size for each dataset, provide an\n array of sizes. During plot creation, each plotted dataset is assigned\n a symbols size. If the number of sizes is less than the number of\n plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.symbolsOpacity\n Symbols opacity, where an opacity of `0.0` makes a symbol completely\n transparent and an opacity of `1.0` makes a symbol completely opaque. To\n specify the opacity for each dataset, provide an array of opacities.\n During plot creation, each plotted dataset is assigned an opacity. If\n the number of opacities is less than the number of plotted datasets,\n opacities are reused using modulo arithmetic.\n\n plot.width\n Plot width (in pixels).\n\n plot.height\n Plot height (in pixels).\n\n plot.paddingLeft\n Plot left padding (in pixels). Left padding is typically used to create\n space for a left-oriented y-axis.\n\n plot.paddingRight\n Plot right padding (in pixels). Right padding is typically used to\n create space for a right-oriented y-axis.\n\n plot.paddingTop\n Plot top padding (in pixels). Top padding is typically used to create\n space for a title or top-oriented x-axis.\n\n plot.paddingBottom\n Plot bottom padding (in pixels). Bottom padding is typically used to\n create space for a bottom-oriented x-axis.\n\n plot.xMin\n Minimum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.xMax\n Maximum value of the x-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `x` data.\n\n plot.yMin\n Minimum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.yMax\n Maximum value of the y-axis domain. When retrieved, if the value has\n been set to `null`, the returned value is computed from the `y` data.\n\n plot.xScale\n Scale function for mapping values to a coordinate along the x-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.yScale\n Scale function for mapping values to a coordinate along the y-axis. The\n following `scales` are supported: 'linear' (linear scale) and 'time'\n (time scale). When retrieved, the returned value is a scale function.\n\n plot.xTickFormat\n x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.yTickFormat\n y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n been set to `null`, the returned value is a formatting function.\n\n plot.xNumTicks\n Number of x-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.yNumTicks\n Number of y-axis tick marks. If the value is set to `null`, the number\n of tick marks is computed internally.\n\n plot.xAxisOrient\n x-axis orientation. The following orientations are supported: 'bottom'\n and 'top'.\n\n plot.yAxisOrient\n y-axis orientation. The following orientations are supported: 'left' and\n 'right'.\n\n plot.xRug\n Boolean flag(s) indicating whether to display a rug plot along the x-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.yRug\n Boolean flag(s) indicating whether to display a rug plot along the y-\n axis. To specify the flag for each dataset, provide an array of\n booleans. During plot creation, each plotted dataset is assigned a flag.\n If the number of flags is less than the number of plotted datasets,\n flags are reused using modulo arithmetic.\n\n plot.xRugOrient\n x-axis rug orientation. The following orientations are supported:\n 'bottom' or 'top'. To specify the x-axis rug orientation for each\n dataset, provide an array of orientations. During plot creation, each\n plotted dataset is assigned an orientation. If the number of\n orientations is less than the number of plotted datasets, orientations\n are reused using modulo arithmetic.\n\n plot.yRugOrient\n y-axis rug orientation. The following orientations are supported: 'left'\n or 'right'. To specify the y-axis rug orientation for each dataset,\n provide an array of orientations. During plot creation, each plotted\n dataset is assigned an orientation. If the number of orientations is\n less than the number of plotted datasets, orientations are reused using\n modulo arithmetic.\n\n plot.xRugOpacity\n x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the x-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.yRugOpacity\n y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n transparent and an opacity of `1.0` makes a rug completely opaque. To\n specify the y-axis rug opacity for each dataset, provide an array of\n opacities. During plot creation, each plotted dataset is assigned an\n opacity. If the number of opacities is less than the number of plotted\n datasets, opacities are reused using modulo arithmetic.\n\n plot.xRugSize\n x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.yRugSize\n y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n dataset, provide an array of sizes. During plot creation, each plotted\n dataset is assigned a tick size. If the number of sizes is less than the\n number of plotted datasets, sizes are reused using modulo arithmetic.\n\n plot.description\n Plot description.\n\n plot.title\n Plot title.\n\n plot.xLabel\n x-axis label.\n\n plot.yLabel\n y-axis label.\n\n plot.engine\n Plot rendering engine. The following engines are supported: 'svg'.\n\n plot.renderFormat\n Plot render format. The following formats are supported: 'vdom' and\n 'html'.\n\n plot.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n plot.viewer\n Plot viewer. The following viewers are supported: 'none', 'stdout',\n 'window', and 'browser'.\n\n plot.autoView\n Viewer mode. If `true`, an instance generates an updated view on each\n 'render' event; otherwise, generating a view must be triggered manually.\n\n plot.graphWidth\n Computed property corresponding to the expected graph width.\n\n plot.graphHeight\n Computed property corresponding to the expected graph height.\n\n plot.xDomain\n Computed property corresponding to the x-axis domain.\n\n plot.yDomain\n Computed property corresponding to the y-axis domain.\n\n plot.xRange\n Computed property corresponding to the x-axis range.\n\n plot.yRange\n Computed property correspond to the y-axis range.\n\n plot.xPos\n A function which maps values to x-axis coordinate values.\n\n plot.yPos\n A function which maps values to y-axis coordinate values.\n\n Examples\n --------\n > var plot = Plot()\n \n\n // Provide plot data at instantiation:\n > var x = [[0.10, 0.20, 0.30]];\n > var y = [[0.52, 0.79, 0.64]];\n > plot = Plot( x, y )\n \n\n See Also\n --------\n plot\n","pluck":"\npluck( arr, prop[, options] )\n Extracts a property value from each element of an object array.\n\n The function skips `null` and `undefined` array elements.\n\n Extracted values are not cloned.\n\n Parameters\n ----------\n arr: Array\n Source array.\n\n prop: string\n Property to access.\n\n options: Object (optional)\n Options.\n\n options.copy: boolean (optional)\n Boolean indicating whether to return a new data structure. To mutate the\n input data structure (e.g., when input values can be discarded or when\n optimizing memory usage), set the `copy` option to `false`. Default:\n true.\n\n Returns\n -------\n out: Array\n Destination array.\n\n Examples\n --------\n > var arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > var out = pluck( arr, 'a' )\n [ 1, 0.5 ]\n\n > arr = [\n ... { 'a': 1, 'b': 2 },\n ... { 'a': 0.5, 'b': 3 }\n ... ];\n > out = pluck( arr, 'a', { 'copy': false } )\n [ 1, 0.5 ]\n > var bool = ( arr[ 0 ] === out[ 0 ] )\n true\n\n See Also\n --------\n deepPluck, pick\n","pop":"\npop( collection )\n Removes and returns the last element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = pop( arr )\n [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = pop( arr )\n [ [ 1.0 ], 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = pop( arr )\n [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n See Also\n --------\n push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n Extracts the stem of a given word.\n\n Parameters\n ----------\n word: string\n Input word.\n\n Returns\n -------\n out: string\n Word stem.\n\n Examples\n --------\n > var out = porterStemmer( 'walking' )\n 'walk'\n > out = porterStemmer( 'walked' )\n 'walk'\n > out = porterStemmer( 'walks' )\n 'walk'\n > out = porterStemmer( '' )\n ''\n\n","prepend":"\nprepend( collection1, collection2 )\n Adds the elements of one collection to the beginning of another collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection1: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n collection2: Array|TypedArray|Object\n A collection containing the elements to add. If the collection is an\n `Object`, the collection should be array-like.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = prepend( arr, [ 6.0, 7.0 ] )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = prepend( arr, [ 3.0, 4.0 ] )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = prepend( arr, [ 2.0, 3.0 ] )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n\n Parameters\n ----------\n str: string\n Input string.\n\n fromIndex: integer (optional)\n Position. Default: str.length-1.\n\n Returns\n -------\n out: integer\n Previous extended grapheme cluster break position.\n\n Examples\n --------\n > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n 3\n > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n 7\n > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n 0\n > out = prevGraphemeClusterBreak( '🌷', 1 )\n -1\n\n See Also\n --------\n numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n\n Returns\n -------\n out: Array\n List of primes.\n\n Examples\n --------\n > var list = PRIMES_100K()\n [ 2, 3, 5, ... ]\n\n See Also\n --------\n iterPrimesSeq\n","properties":"\nproperties( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own enumerable and non-enumerable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = properties( obj )\n [ 'beep' ]\n\n See Also\n --------\n defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n Returns an array of an object's own and inherited property names and\n symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited property names and symbols.\n\n Examples\n --------\n > var props = propertiesIn( [] )\n\n See Also\n --------\n defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n Returns a property descriptor for an object's own property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptor( obj, 'a' )\n {...}\n\n See Also\n --------\n hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n Returns a property descriptor for an object's own or inherited property.\n\n If provided `null` or `undefined` or provided a non-existent property, the\n function returns `null`.\n\n Parameters\n ----------\n value: any\n Input value.\n\n property: string|symbol\n Property name.\n\n Returns\n -------\n desc: Object|null\n Property descriptor.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptorIn( obj, 'a' )\n {...}\n\n See Also\n --------\n hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n Returns an object's own property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n Property descriptors.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = propertyDescriptors( obj )\n { 'a': {...} }\n\n See Also\n --------\n defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n Returns an object's own and inherited property descriptors.\n\n If provided `null` or `undefined`, the function returns an empty object.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n desc: Object\n An object's own and inherited property descriptors.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var desc = propertyDescriptorsIn( obj )\n { 'beep': {...}, 'foo': {...}, ... }\n\n See Also\n --------\n defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own enumerable and non-enumerable property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNames( obj )\n [ 'beep' ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited enumerable and non-enumerable\n property names.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var keys = propertyNamesIn( obj )\n e.g., [ 'beep', 'foo', ... ]\n\n See Also\n --------\n objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n Returns an array of an object's own symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own symbol properties.\n\n Examples\n --------\n > var s = propertySymbols( {} )\n\n See Also\n --------\n propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n Returns an array of an object's own and inherited symbol properties.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited symbol properties.\n\n Examples\n --------\n > var s = propertySymbolsIn( [] )\n\n See Also\n --------\n propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n\n The following \"traps\" are supported:\n\n - getPrototypeOf( target )\n Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n `instanceof` operator. The method must return an object or `null`.\n\n - setPrototypeOf( target, prototype )\n Trap for `Object.setPrototypeOf()`. The method must return a boolean\n indicating if the prototype was successfully set.\n\n - isExtensible( target )\n Trap for `Object.isExtensible()`. The method must return a boolean.\n\n - preventExtensions( target )\n Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n - getOwnPropertyDescriptor( target, property )\n Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n object or `undefined`.\n\n - defineProperty( target, property, descriptor )\n Trap for `Object.defineProperty()`. The method must return a boolean\n indicating whether the operation succeeded.\n\n - has( target, property )\n Trap for the `in` operator. The method must return a boolean.\n\n - get( target, property, receiver )\n Trap for retrieving property values. The method can return any value.\n\n - set( target, property, value, receiver )\n Trap for setting property values. The method should return a boolean\n indicating whether assignment succeeded.\n\n - deleteProperty( target, property )\n Trap for the `delete` operator. The method must return a boolean\n indicating whether operation succeeded.\n\n - ownKeys( target )\n Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n `Object.getOwnPropertySymbols()`. The method must return an enumerable\n object.\n\n - apply( target, thisArg, argumentsList )\n Trap for a function call. The method can return any value.\n\n - construct( target, argumentsList, newTarget )\n Trap for the `new` operator. The method must return an object.\n\n All traps are optional. If a trap is not defined, the default behavior is to\n forward the operation to the target.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Proxy object.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = new Proxy( {}, h );\n > p.a = 3.14;\n > p.a\n 6.28\n\n\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n Returns a revocable proxy object.\n\n Parameters\n ----------\n target: Object\n Object which the proxy virtualizes.\n\n handlers: Object\n Object whose properties are functions which define the behavior of the\n proxy when performing operations.\n\n Returns\n -------\n p: Object\n Revocable proxy object.\n\n p.proxy: Object\n Proxy object.\n\n p.revoke: Function\n Invalidates a proxy, rendering a proxy object unusable.\n\n Examples\n --------\n > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n > var h = { 'get': get };\n > var p = Proxy.revocable( {}, h );\n > p.proxy.a = 3.14;\n > p.proxy.a\n 6.28\n > p.revoke();","push":"\npush( collection, ...items )\n Adds one or more elements to the end of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = push( arr, 6.0, 7.0 )\n [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = push( arr, 3.0, 4.0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Array-like object:\n > arr = { 'length': 0 };\n > arr = push( arr, 1.0, 2.0 )\n { 'length': 2, '0': 1.0, '1': 2.0 }\n\n See Also\n --------\n pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n Returns the quarter of the year.\n\n By default, the function returns the quarter of the year for the current\n month in the current year (according to local time). To determine the\n quarter for a particular month, provide either a month or a `Date`\n object.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n Parameters\n ----------\n month: integer|string|Date (optional)\n Month (or `Date`).\n\n Returns\n -------\n out: integer\n Quarter of the year.\n\n Examples\n --------\n > var q = quarterOfYear( new Date() )\n \n > q = quarterOfYear( 4 )\n 2\n > q = quarterOfYear( 'June' )\n 2\n\n // Other ways to supply month:\n > q = quarterOfYear( 'April' )\n 2\n > q = quarterOfYear( 'apr' )\n 2\n\n See Also\n --------\n dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.arcsine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.arcsine.state\n \n\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n > out = random.array.arcsine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.arcsine( 3, 2.0, 5.0 )\n ","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.arcsine.byteLength;\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n \n\n\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.bernoulli.assign( 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.bernoulli.factory();\n > var out = fcn( 3, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.bernoulli.factory( 0.5 );\n > out = fcn( 3 )\n ","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.bernoulli( 3, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.bernoulli.state\n \n\n > out = random.array.bernoulli( 3, 0.5 )\n \n > out = random.array.bernoulli( 3, 0.5 )\n \n\n // Set the state:\n > random.array.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.array.bernoulli( 3, 0.5 )\n ","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n random.beta, base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.beta.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.beta.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.beta.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.beta.state\n \n\n > out = random.array.beta( 3, 2.0, 5.0 )\n \n > out = random.array.beta( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.array.beta( 3, 2.0, 5.0 )\n ","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.beta.byteLength;\n\n See Also\n --------\n random.beta, base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number\n First shape parameter.\n\n beta: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n First shape parameter.\n\n beta: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.betaprime.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.betaprime.state\n \n\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n > out = random.array.betaprime( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.array.betaprime( 3, 2.0, 5.0 )\n ","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.betaprime.byteLength;\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.binomial, random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n Parameters\n ----------\n n: number\n Number of trials.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.binomial.assign( 17, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n n: number (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.binomial.factory();\n > var out = fcn( 3, 17, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.binomial.factory( 17, 0.5 );\n > out = fcn( 3 )\n ","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.binomial.state\n \n\n > out = random.array.binomial( 3, 17, 0.5 )\n \n > out = random.array.binomial( 3, 17, 0.5 )\n \n\n // Set the state:\n > random.array.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.binomial( 3, 17, 0.5 )\n ","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.binomial.byteLength;\n\n See Also\n --------\n random.binomial, random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n random.cauchy, base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n gamma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n gamma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cauchy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cauchy.state\n \n\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n > out = random.array.cauchy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cauchy( 3, 2.0, 5.0 )\n ","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cauchy.byteLength;\n\n See Also\n --------\n random.cauchy, base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n \n\n\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chi.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chi.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chi.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chi( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chi.state\n \n\n > out = random.array.chi( 3, 2.0 )\n \n > out = random.array.chi( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chi( 3, 2.0 )\n ","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n \n\n\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.chisquare.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.chisquare.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.chisquare.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.chisquare( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.chisquare.state\n \n\n > out = random.array.chisquare( 3, 2.0 )\n \n > out = random.array.chisquare( 3, 2.0 )\n \n\n // Set the state:\n > random.array.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.array.chisquare( 3, 2.0 )\n ","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n random.cosine, base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.cosine.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.cosine.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.cosine.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.cosine.state\n \n\n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n > out = random.array.cosine( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.array.cosine( 3, 2.0, 5.0 )\n ","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.cosine.byteLength;\n\n See Also\n --------\n random.cosine, base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n \n\n\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, random.discreteUniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.discreteUniform.assign( -10, 10, x )\n \n > var bool = ( out === x )\n true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.discreteUniform.factory();\n > var out = fcn( 3, -10, 10 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.discreteUniform.factory( -10, 10 );\n > out = fcn( 3 )\n ","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.array.discreteUniform.state\n \n\n > out = random.array.discreteUniform( 3, -10, 10 )\n \n > out = random.array.discreteUniform( 3, -10, 10 )\n \n\n // Set the state:\n > random.array.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.discreteUniform( 3, -10, 10 )\n ","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.discreteUniform.byteLength;\n\n See Also\n --------\n random.array.uniform, random.discreteUniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n random.erlang, base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.erlang.assign( 2, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.erlang.factory();\n > var out = fcn( 3, 2, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.erlang.factory( 2, 5.0 );\n > out = fcn( 3 )\n ","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.erlang.state\n \n\n > out = random.array.erlang( 3, 2, 5.0 )\n \n > out = random.array.erlang( 3, 2, 5.0 )\n \n\n // Set the state:\n > random.array.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.array.erlang( 3, 2, 5.0 )\n ","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.erlang.byteLength;\n\n See Also\n --------\n random.erlang, base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n \n\n\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.exponential.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.exponential.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.exponential.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.exponential( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.exponential.state\n \n\n > out = random.array.exponential( 3, 2.0 )\n \n > out = random.array.exponential( 3, 2.0 )\n \n\n // Set the state:\n > random.array.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.array.exponential( 3, 2.0 )\n ","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n random.f, base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.f.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.f.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.f.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.f.state\n \n\n > out = random.array.f( 3, 2.0, 5.0 )\n \n > out = random.array.f( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.f.state = state;\n\n // Regenerate a previous array:\n > out = random.array.f( 3, 2.0, 5.0 )\n ","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.f.byteLength;\n\n See Also\n --------\n random.f, base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.frechet.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.frechet.state\n \n\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n ","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n random.gamma, base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Rate parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gamma.state\n \n\n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n > out = random.array.gamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gamma( 3, 2.0, 5.0 )\n ","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gamma.byteLength;\n\n See Also\n --------\n random.gamma, base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n \n\n\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n \n\n\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.geometric.assign( 0.01, x )\n \n > var bool = ( out === x )\n true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.geometric.factory();\n > var out = fcn( 3, 0.01 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.geometric.factory( 0.01 );\n > out = fcn( 3 )\n ","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.geometric( 3, 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.array.geometric.state\n \n\n > out = random.array.geometric( 3, 0.01 )\n \n > out = random.array.geometric( 3, 0.01 )\n \n\n // Set the state:\n > random.array.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.geometric( 3, 0.01 )\n ","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n random.gumbel, base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.gumbel.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.gumbel.state\n \n\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n > out = random.array.gumbel( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.array.gumbel( 3, 2.0, 5.0 )\n ","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.gumbel.byteLength;\n\n See Also\n --------\n random.gumbel, base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n \n\n\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number\n Population size.\n\n K: number\n Subpopulation size.\n\n n: number\n Number of draws.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n \n > var bool = ( out === x )\n true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n N: number (optional)\n Population size.\n\n K: number (optional)\n Subpopulation size.\n\n n: number (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.hypergeometric.factory();\n > var out = fcn( 3, 20, 10, 7 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n > out = fcn( 3 )\n ","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.array.hypergeometric.state\n \n\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n \n\n // Set the state:\n > random.array.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.array.hypergeometric( 3, 20, 10, 7 )\n ","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.invgamma.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.invgamma.state\n \n\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n > out = random.array.invgamma( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.array.invgamma( 3, 2.0, 5.0 )\n ","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.invgamma.byteLength;\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n random.kumaraswamy, base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.kumaraswamy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.kumaraswamy.state\n \n\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n ","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.kumaraswamy.byteLength;\n\n See Also\n --------\n random.kumaraswamy, base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n random.laplace, base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n b: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.laplace.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.laplace.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.laplace.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.laplace.state\n \n\n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n > out = random.array.laplace( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.array.laplace( 3, 2.0, 5.0 )\n ","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.laplace.byteLength;\n\n See Also\n --------\n random.laplace, base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n random.levy, base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n c: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.levy.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.levy.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.levy.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.levy.state\n \n\n > out = random.array.levy( 3, 2.0, 5.0 )\n \n > out = random.array.levy( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.array.levy( 3, 2.0, 5.0 )\n ","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.levy.byteLength;\n\n See Also\n --------\n random.levy, base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n random.logistic, base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n Parameters\n ----------\n mu: number\n Mean parameter.\n\n s: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.logistic.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.logistic.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.logistic.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.logistic.state\n \n\n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n > out = random.array.logistic( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.array.logistic( 3, 2.0, 5.0 )\n ","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.logistic.byteLength;\n\n See Also\n --------\n random.logistic, base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number\n Location parameter.\n\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Location parameter.\n\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.lognormal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.lognormal.state\n \n\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n > out = random.array.lognormal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.lognormal( 3, 2.0, 5.0 )\n ","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.lognormal.byteLength;\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n \n\n\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n \n\n\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstd.normalized( 3 )\n ","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstd.factory();\n > var out = fcn( 3 )\n ","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstd( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstd.state;\n\n > out = random.array.minstd( 3 )\n \n > out = random.array.minstd( 3 )\n \n\n // Set the state:\n > random.array.minstd.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstd( 3 )\n ","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstd.byteLength;\n\n See Also\n --------\n random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n \n\n\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n \n\n\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.minstdShuffle.normalized( 3 )\n ","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.minstdShuffle.factory();\n > var out = fcn( 3 )\n ","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.minstdShuffle( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.minstdShuffle.state;\n\n > out = random.array.minstdShuffle( 3 )\n \n > out = random.array.minstdShuffle( 3 )\n \n\n // Set the state:\n > random.array.minstdShuffle.state = state;\n\n // Regenerate a previous array:\n > out = random.array.minstdShuffle( 3 )\n ","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.minstdShuffle.byteLength;\n\n See Also\n --------\n random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n \n\n\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n \n\n\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.mt19937.normalized( 3 )\n ","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n The returned function and its attached `normalized` method accept the\n following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.idtype: string (optional)\n Default output array data type when generating integers. Default:\n 'float64'.\n\n options.ndtype: string (optional)\n Default output array data type when generating normalized numbers.\n Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.mt19937.factory();\n > var out = fcn( 3 )\n ","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.mt19937( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.mt19937.state;\n\n > out = random.array.mt19937( 3 )\n \n > out = random.array.mt19937( 3 )\n \n\n // Set the state:\n > random.array.mt19937.state = state;\n\n // Regenerate a previous array:\n > out = random.array.mt19937( 3 )\n ","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.mt19937.byteLength;\n\n See Also\n --------\n random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n \n\n\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.negativeBinomial, random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n \n > var bool = ( out === x )\n true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.negativeBinomial.factory();\n > var out = fcn( 3, 10, 0.5 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n > out = fcn( 3 )\n ","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.array.negativeBinomial.state\n \n\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n \n\n // Set the state:\n > random.array.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.array.negativeBinomial( 3, 10, 0.5 )\n ","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.negativeBinomial.byteLength;\n\n See Also\n --------\n random.negativeBinomial, random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n random.normal, base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number\n Mean.\n\n sigma: number\n Standard deviation.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.normal.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n mu: number (optional)\n Mean.\n\n sigma: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.normal.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.normal.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.normal.state\n \n\n > out = random.array.normal( 3, 2.0, 5.0 )\n \n > out = random.array.normal( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.array.normal( 3, 2.0, 5.0 )\n ","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.normal.byteLength;\n\n See Also\n --------\n random.normal, base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number\n Shape parameter.\n\n beta: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n alpha: number (optional)\n Shape parameter.\n\n beta: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.pareto1.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.pareto1.state\n \n\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n > out = random.array.pareto1( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.array.pareto1( 3, 2.0, 5.0 )\n ","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n lambda: number\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n \n\n\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n Parameters\n ----------\n lambda: number\n Mean parameter.\n\n out: Array|TypedArray\n Output array.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.poisson.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n lambda: number (optional)\n Mean parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.poisson.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.poisson.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.poisson( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.poisson.state\n \n\n > out = random.array.poisson( 3, 2.0 )\n \n > out = random.array.poisson( 3, 2.0 )\n \n\n // Set the state:\n > random.array.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.array.poisson( 3, 2.0 )\n ","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n \n\n\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n \n\n\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.randu.factory();\n > var out = fcn( 3 )\n ","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.randu( 3 )\n \n\n // Get a copy of the current state:\n > var state = random.array.randu.state;\n\n > out = random.array.randu( 3 )\n \n > out = random.array.randu( 3 )\n \n\n // Set the state:\n > random.array.randu.state = state;\n\n // Regenerate a previous array:\n > out = random.array.randu( 3 )\n ","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.randu.byteLength;\n\n See Also\n --------\n random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n sigma: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n \n\n\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n sigma: number\n Scale parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.rayleigh.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n sigma: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.rayleigh.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.rayleigh.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.rayleigh( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.rayleigh.state\n \n\n > out = random.array.rayleigh( 3, 2.0 )\n \n > out = random.array.rayleigh( 3, 2.0 )\n \n\n // Set the state:\n > random.array.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.array.rayleigh( 3, 2.0 )\n ","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n \n\n\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t, random.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.t.assign( 2.0, x )\n \n > var bool = ( out === x )\n true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n\n If provided a distribution parameter, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided a distribution parameter, the returned function requires\n that distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.t.factory();\n > var out = fcn( 3, 2.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.t.factory( 2.0 );\n > out = fcn( 3 )\n ","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.t( 3, 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.t.state\n \n\n > out = random.array.t( 3, 2.0 )\n \n > out = random.array.t( 3, 2.0 )\n \n\n // Set the state:\n > random.array.t.state = state;\n\n // Regenerate a previous array:\n > out = random.array.t( 3, 2.0 )\n ","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.t.byteLength;\n\n See Also\n --------\n base.random.t, random.strided.t, random.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n \n > var bool = ( out === x )\n true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.triangular.factory();\n > var out = fcn( 3, 2.0, 5.0, 3.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n > out = fcn( 3 )\n ","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.triangular.state\n \n\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.array.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n ","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform, random.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.uniform.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.uniform.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.uniform.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.uniform.state\n \n\n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n > out = random.array.uniform( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.array.uniform( 3, 2.0, 5.0 )\n ","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.uniform.byteLength;\n\n See Also\n --------\n random.array.discreteUniform, base.random.uniform, random.strided.uniform, random.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n len: integer\n Output array length.\n\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Output array data type. Default: 'float64'.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n \n\n\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n lambda: number\n Shape parameter.\n\n out: Array|Float64Array|Float32Array\n Output array.\n\n Returns\n -------\n out: Array|Float64Array|Float32Array\n Output array.\n\n Examples\n --------\n > var x = azeros( 3, 'float64' );\n > var out = random.array.weibull.assign( 2.0, 5.0, x )\n \n > var bool = ( out === x )\n true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns random\n variates drawn from the specified distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n The returned function accepts the following options:\n\n - dtype: output array data type. This overrides the default output array\n data type.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n lambda: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.dtype: string (optional)\n Default output array data type. Default: 'float64'.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.array.weibull.factory();\n > var out = fcn( 3, 2.0, 5.0 )\n \n\n // Provide distribution parameters:\n > fcn = random.array.weibull.factory( 2.0, 5.0 );\n > out = fcn( 3 )\n ","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.array.weibull.state\n \n\n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n > out = random.array.weibull( 3, 2.0, 5.0 )\n \n\n // Set the state:\n > random.array.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.array.weibull( 3, 2.0, 5.0 )\n ","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.array.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.arcsine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.bernoulli( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.beta( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.betaprime( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.binomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.boxMuller();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n Ɣ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cauchy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chi( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.chisquare( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.cosine( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned iterator, one must\n seed the provided `prng` (assuming the provided `prng` is seedable). The\n provided PRNG must have `MIN` and `MAX` properties specifying the\n minimum and maximum possible pseudorandom integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.discreteUniform( 0, 3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.erlang( 1, 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.exponential( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.f( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `s <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.geometric( 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.gumbel( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n throws an error.\n\n If `n > N` or `K > N`, the function throws an error.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.hypergeometric( 20, 10, 7 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.improvedZiggurat();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.invgamma( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `a <= 0` or `b <= 0`.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.laplace( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.levy( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.logistic( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.lognormal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstd();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing positive signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Int32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Int32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.minstdShuffle();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.seed: Uint32Array\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: Uint32Array\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.mt19937();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.negativeBinomial( 10, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.normal( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `α <= 0` or `β <= 0`.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.pareto1( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.poisson( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randi();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: `'improved-ziggurat'`.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randn();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: any\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer\n Length of generator seed.\n\n iterator.state: any\n Generator state.\n\n iterator.stateLength: integer\n Length of generator state.\n\n iterator.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.randu();\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.rayleigh( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.t( 1.5 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.uniform( 0.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n The function throws an error if `k <= 0` or `λ <= 0`.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.iter: integer (optional)\n Number of iterations.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n iterator.PRNG: Function\n Underlying pseudorandom number generator.\n\n iterator.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n iterator.seedLength: integer|null\n Length of generator seed.\n\n iterator.state: Uint32Array|null\n Generator state.\n\n iterator.stateLength: integer|null\n Length of generator state.\n\n iterator.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var it = random.iterators.weibull( 1.0, 1.0 );\n > var r = it.next().value\n \n > r = it.next().value\n \n\n See Also\n --------\n base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n First shape parameter.\n\n β: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n\n Parameters\n ----------\n α: number\n First shape parameter.\n\n β: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial( 20, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n n: integer (optional)\n Number of trials.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n\n Parameters\n ----------\n n: integer\n Number of trials.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.boxMuller.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n x0: number (optional)\n Location parameter.\n\n γ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number\n Location parameter.\n\n γ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chi.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n k: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.chisquare.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform( 2, 5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: integer (optional)\n Minimum support.\n\n b: integer (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n\n Parameters\n ----------\n a: integer\n Minimum support.\n\n b: integer\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: integer\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang( 2, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Shape parameter.\n\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n\n Parameters\n ----------\n k: number\n Shape parameter.\n\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n λ: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.exponential.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n d1: number (optional)\n Degrees of freedom.\n\n d2: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n\n Parameters\n ----------\n d1: number\n Degrees of freedom.\n\n d2: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n s: number (optional)\n Scale parameter.\n\n m: number (optional)\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n s: number\n Scale parameter.\n\n m: number\n Location parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Rate parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric( 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.geometric.objectMode( 0.3, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n N: integer (optional)\n Population size.\n\n K: integer (optional)\n Subpopulation size.\n\n n: integer (optional)\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n\n Parameters\n ----------\n N: integer\n Population size.\n\n K: integer\n Subpopulation size.\n\n n: integer\n Number of draws.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.improvedZiggurat.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n First shape parameter.\n\n b: number (optional)\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n\n Parameters\n ----------\n a: number\n First shape parameter.\n\n b: number\n Second shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n b: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n b: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n c: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n c: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n s: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n s: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Location parameter.\n\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n\n Parameters\n ----------\n μ: number\n Location parameter.\n\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) based on Park and Miller.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. More\n importantly, the \"randomness quality\" of the generator's output is lacking.\n These defects make the generator unsuitable, for example, in Monte Carlo\n simulations and in cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstd.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a linear congruential\n pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n Durham algorithm. The shuffle step considerably strengthens the \"randomness\n quality\" of a simple LCG's output.\n\n The generator has a period of approximately `2.1e9`.\n\n An LCG is fast and uses little memory. On the other hand, because the\n generator is a simple LCG, the generator has recognized shortcomings. By\n today's PRNG standards, the generator's period is relatively short. In\n general, this generator is unsuitable for Monte Carlo simulations and\n cryptographic applications.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer or, for arbitrary length seeds, an array-like\n object containing signed 32-bit integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.seed: Int32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Int32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.minstdShuffle.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n Twister pseudorandom number generator.\n\n The PRNG is *not* a cryptographically secure PRNG.\n\n The PRNG has a period of 2^19937 - 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.normalized: boolean (optional)\n Boolean indicating whether to return pseudorandom numbers on the\n interval `[0,1)`.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.mt19937.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n r: number\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n r: number (optional)\n Number of successes until experiment is stopped.\n\n p: number (optional)\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n\n Parameters\n ----------\n r: integer\n Number of successes until experiment is stopped.\n\n p: number\n Success probability.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n μ: number (optional)\n Mean.\n\n σ: number (optional)\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n\n Parameters\n ----------\n μ: number\n Mean.\n\n σ: number\n Standard deviation.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n α: number (optional)\n Shape parameter.\n\n β: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n\n Parameters\n ----------\n α: number\n Shape parameter.\n\n β: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n λ: number (optional)\n Mean.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n λ: number\n Mean.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.poisson.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randi.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - improved-ziggurat: improved ziggurat method.\n - box-muller: Box-Muller transform.\n\n Default: 'improved-ziggurat'.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randn.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n The default underlying pseudorandom number generator (PRNG) *may* change in\n the future. If exact reproducibility is required, either explicitly specify\n a PRNG via the `name` option or use an underlying PRNG directly.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu( opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: 'mt19937'.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: any\n Pseudorandom number generator seed.\n\n stream.seedLength: integer\n Length of generator seed.\n\n stream.state: any\n Generator state.\n\n stream.stateLength: integer\n Length of generator state.\n\n stream.byteLength: integer\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.randu.objectMode( opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n σ: number (optional)\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n σ: number\n Scale parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t( 3.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n v: number (optional)\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n\n Parameters\n ----------\n v: number\n Degrees of freedom.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.t.objectMode( 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n c: number (optional)\n Mode.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n c: number\n Mode.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n a: number (optional)\n Minimum support.\n\n b: number (optional)\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n\n Parameters\n ----------\n a: number\n Minimum support.\n\n b: number\n Maximum support.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n\n In addition to standard readable stream events, the returned stream emits a\n 'state' event after internally generating `siter` pseudorandom numbers,\n which is useful when wanting to deterministically capture a stream's\n underlying PRNG state.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull( 2.0, 5.0, opts );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n\n If provided distribution parameters, the returned function returns readable\n streams which generate pseudorandom numbers drawn from the specified\n distribution.\n\n If not provided distribution parameters, the returned function requires that\n distribution parameters be provided at each invocation.\n\n Parameters\n ----------\n k: number (optional)\n Scale parameter.\n\n λ: number (optional)\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n\n Parameters\n ----------\n k: number\n Scale parameter.\n\n λ: number\n Shape parameter.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to generate additional pseudorandom numbers.\n\n options.iter: integer (optional)\n Number of iterations.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned iterator, one must seed the provided `prng` (assuming the\n provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned iterator has exclusive control over\n its internal state. Default: true.\n\n options.siter: integer (optional)\n Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n stream.PRNG: Function\n Underlying pseudorandom number generator.\n\n stream.seed: Uint32Array|null\n Pseudorandom number generator seed.\n\n stream.seedLength: integer|null\n Length of generator seed.\n\n stream.state: Uint32Array|null\n Generator state.\n\n stream.stateLength: integer|null\n Length of generator state.\n\n stream.byteLength: integer|null\n Size (in bytes) of generator state.\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var opts = { 'iter': 10 };\n > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.arcsine, base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.bernoulli.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.bernoulli.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.bernoulli.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.bernoulli.byteLength;\n\n See Also\n --------\n random.bernoulli, base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.beta, base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.beta, base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n First shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Second shape parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.betaprime, base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chi.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chi.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chi.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chi.byteLength;\n\n See Also\n --------\n random.chi, base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Degrees of freedom.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.chisquare.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.chisquare.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.chisquare.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.chisquare.byteLength;\n\n See Also\n --------\n random.chisquare, base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.cosine, base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n s: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `s`.\n\n os: integer\n Starting index for `s`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var s = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > s = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.cosine, base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.discreteUniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = [ -10, -5, 0, 5, 10 ];\n > var b = [ 20, 20, 20, 20, 20 ];\n > var out = azeros( 5, 'generic' );\n > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = [ -10, -5, 0, 5, 10, 15 ];\n > b = [ 20, 20, 20, 20, 20, 20 ];\n > out = azeros( 6, 'generic' );\n > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.discreteUniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Rate parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.exponential.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.exponential.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.exponential.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.exponential.byteLength;\n\n See Also\n --------\n random.exponential, base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.gamma, base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Rate parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.gamma, base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n p: ArrayLikeObject\n Success probability.\n\n sp: integer\n Index increment for `p`.\n\n op: integer\n Starting index for `p`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.geometric.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.geometric.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.geometric.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.geometric.byteLength;\n\n See Also\n --------\n random.geometric, base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n alpha: ArrayLikeObject\n Shape parameter.\n\n sa: integer\n Index increment for `alpha`.\n\n oa: integer\n Starting index for `alpha`.\n\n beta: ArrayLikeObject\n Scale parameter.\n\n sb: integer\n Index increment for `beta`.\n\n ob: integer\n Starting index for `beta`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.invgamma, base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Location parameter.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.lognormal, base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized( out.length, out, 1 )\n [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n signed 32-bit integer on the interval `[1, 2147483646]` or, for\n arbitrary length seeds, an array-like object containing signed 32-bit\n integers.\n\n options.state: Int32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized( out.length, out, 1 )\n [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.normal, base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n mu: ArrayLikeObject\n Mean.\n\n sm: integer\n Index increment for `mu`.\n\n om: integer\n Starting index for `mu`.\n\n sigma: ArrayLikeObject\n Standard deviation.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var mu = linspace( 0.0, 1.0, 5 );\n > var sigma = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > mu = linspace( 0.0, 1.0, 6 );\n > sigma = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.normal, base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n lambda: ArrayLikeObject\n Mean parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.poisson.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.poisson.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.poisson.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.poisson.byteLength;\n\n See Also\n --------\n random.poisson, base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n\n The `N` and stride parameters determine which elements in the provided\n strided array are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu( out.length, out, 1 )\n [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.name: string (optional)\n Name of a supported pseudorandom number generator (PRNG), which will\n serve as the underlying source of pseudorandom numbers. The following\n PRNGs are supported:\n\n - mt19937: 32-bit Mersenne Twister.\n - minstd: linear congruential PRNG based on Park and Miller.\n - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n Default: `'mt19937'`.\n\n options.seed: any (optional)\n Pseudorandom number generator seed. Valid seed values vary according to\n the underlying PRNG.\n\n options.state: any (optional)\n Pseudorandom number generator state. Valid state values vary according\n to the underling PRNG. If provided, the `seed` option is ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.randu.ndarray( out.length, out, 1, 0 )\n [...]\n\n See Also\n --------\n base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n random.rayleigh, base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n sigma: ArrayLikeObject\n Scale parameter.\n\n ss: integer\n Index increment for `sigma`.\n\n os: integer\n Starting index for `sigma`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.rayleigh.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.rayleigh.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.rayleigh.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.rayleigh.byteLength;\n\n See Also\n --------\n random.rayleigh, base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]\n\n\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n random.t, base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n v: ArrayLikeObject\n Degrees of freedom.\n\n sv: integer\n Index increment for `v`.\n\n ov: integer\n Starting index for `v`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n > var out = azeros( 5, 'generic' );\n > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for filling strided arrays.\n\n Examples\n --------\n > var fcn = random.strided.t.factory();\n > var out = azeros( 5, 'generic' );\n > fcn( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n\n Examples\n --------\n > var out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Get a copy of the current state:\n > var state = random.strided.t.state\n \n\n // Advance the generator state:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]\n\n // Set the state:\n > random.strided.t.state = state;\n\n // Regenerate previous generated values:\n > out = azeros( 3, 'generic' );\n > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.strided.t.byteLength;\n\n See Also\n --------\n random.t, base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.uniform, base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n a: ArrayLikeObject\n Minimum support.\n\n sa: integer\n Index increment for `a`.\n\n oa: integer\n Starting index for `a`.\n\n b: ArrayLikeObject\n Maximum support.\n\n sb: integer\n Index increment for `b`.\n\n ob: integer\n Starting index for `b`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 0.0, 1.0, 5 );\n > var b = linspace( 2.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 0.0, 1.0, 6 );\n > b = linspace( 2.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.uniform, base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n\n The `N` and stride parameters determine which elements in the provided\n strided arrays are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n If `N` is less than or equal to `0`, the output strided array is left\n unchanged.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.weibull, base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n k: ArrayLikeObject\n Scale parameter.\n\n sk: integer\n Index increment for `k`.\n\n ok: integer\n Starting index for `k`.\n\n lambda: ArrayLikeObject\n Shape parameter.\n\n sl: integer\n Index increment for `lambda`.\n\n ol: integer\n Starting index for `lambda`.\n\n out: ArrayLikeObject\n Output array.\n\n so: integer\n Index increment for `out`.\n\n oo: integer\n Starting index for `out`.\n\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n underlying pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that the underlying generator has exclusive control\n over its internal state. Default: true.\n\n Returns\n -------\n out: ArrayLikeObject\n Output array.\n\n Examples\n --------\n // Standard usage:\n > var a = linspace( 1.0, 5.0, 5 );\n > var b = linspace( 1.0, 5.0, 5 );\n > var out = azeros( 5, 'generic' );\n > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n [...]\n\n // Advanced indexing:\n > a = linspace( 1.0, 5.0, 6 );\n > b = linspace( 1.0, 5.0, 6 );\n > out = azeros( 6, 'generic' );\n > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n [...]\n\n See Also\n --------\n random.weibull, base.random.weibull, random.array.weibull","random.arcsine":"\nrandom.arcsine( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.arcsine.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.arcsine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.arcsine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an arcsine\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.arcsine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.arcsine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.arcsine.PRNG;\n\n\nrandom.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.arcsine.seed;\n\n\nrandom.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.arcsine.seedLength;\n\n\nrandom.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.arcsine.state\n \n\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.arcsine.stateLength;\n\n\nrandom.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine, random.strided.arcsine\n","random.arcsine.assign":"\nrandom.arcsine.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from an arcsine\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.arcsine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.arcsine.factory":"\nrandom.arcsine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an arcsine\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.arcsine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.arcsine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.arcsine.PRNG":"\nrandom.arcsine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.arcsine.PRNG;","random.arcsine.seed":"\nrandom.arcsine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.arcsine.seed;","random.arcsine.seedLength":"\nrandom.arcsine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.arcsine.seedLength;","random.arcsine.state":"\nrandom.arcsine.state\n Generator state.\n\n Examples\n --------\n > var out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.arcsine.state\n \n\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.arcsine.state = state;\n\n // Regenerate a previous array:\n > out = random.arcsine( [ 3, 3 ], 2.0, 5.0 )\n ","random.arcsine.stateLength":"\nrandom.arcsine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.arcsine.stateLength;","random.arcsine.byteLength":"\nrandom.arcsine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.arcsine.byteLength;\n\n See Also\n --------\n base.random.arcsine, random.array.arcsine, random.strided.arcsine","random.bernoulli":"\nrandom.bernoulli( shape, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n\nrandom.bernoulli.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.bernoulli.assign( 0.5, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.bernoulli.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.bernoulli` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.bernoulli.factory();\n > var out = fcn( [ 3, 3 ], 0.5 )\n \n\n\nrandom.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.bernoulli.PRNG;\n\n\nrandom.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.bernoulli.seed;\n\n\nrandom.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.bernoulli.seedLength;\n\n\nrandom.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.bernoulli.state\n \n\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Set the state:\n > random.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n\nrandom.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.bernoulli.stateLength;\n\n\nrandom.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli, random.strided.bernoulli\n","random.bernoulli.assign":"\nrandom.bernoulli.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a Bernoulli\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.bernoulli.assign( 0.5, out )\n \n > var bool = ( v === out )\n true","random.bernoulli.factory":"\nrandom.bernoulli.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.bernoulli` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.bernoulli.factory();\n > var out = fcn( [ 3, 3 ], 0.5 )\n ","random.bernoulli.PRNG":"\nrandom.bernoulli.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.bernoulli.PRNG;","random.bernoulli.seed":"\nrandom.bernoulli.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.bernoulli.seed;","random.bernoulli.seedLength":"\nrandom.bernoulli.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.bernoulli.seedLength;","random.bernoulli.state":"\nrandom.bernoulli.state\n Generator state.\n\n Examples\n --------\n > var out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.bernoulli.state\n \n\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n \n\n // Set the state:\n > random.bernoulli.state = state;\n\n // Regenerate a previous array:\n > out = random.bernoulli( [ 3, 3 ], 0.5 )\n ","random.bernoulli.stateLength":"\nrandom.bernoulli.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.bernoulli.stateLength;","random.bernoulli.byteLength":"\nrandom.bernoulli.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.bernoulli.byteLength;\n\n See Also\n --------\n base.random.bernoulli, random.array.bernoulli, random.strided.bernoulli","random.beta":"\nrandom.beta( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.beta.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.beta.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.beta.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a beta\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.beta` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.beta.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.beta.PRNG;\n\n\nrandom.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.beta.seed;\n\n\nrandom.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.beta.seedLength;\n\n\nrandom.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.beta.state\n \n\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.beta.stateLength;\n\n\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.array.beta, random.strided.beta\n","random.beta.assign":"\nrandom.beta.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.beta.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.beta.factory":"\nrandom.beta.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a beta\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.beta` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.beta.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.beta.PRNG":"\nrandom.beta.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.beta.PRNG;","random.beta.seed":"\nrandom.beta.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.beta.seed;","random.beta.seedLength":"\nrandom.beta.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.beta.seedLength;","random.beta.state":"\nrandom.beta.state\n Generator state.\n\n Examples\n --------\n > var out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.beta.state\n \n\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.beta.state = state;\n\n // Regenerate a previous array:\n > out = random.beta( [ 3, 3 ], 2.0, 5.0 )\n ","random.beta.stateLength":"\nrandom.beta.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.beta.stateLength;","random.beta.byteLength":"\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.beta.byteLength;\n\n See Also\n --------\n base.random.beta, random.array.beta, random.strided.beta","random.betaprime":"\nrandom.betaprime( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.betaprime.PRNG;\n\n\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.betaprime.seed;\n\n\nrandom.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.betaprime.seedLength;\n\n\nrandom.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.betaprime.state\n \n\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.betaprime.stateLength;\n\n\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime, random.strided.betaprime\n","random.betaprime.assign":"\nrandom.betaprime.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a beta prime\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n beta: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.betaprime.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.betaprime.factory":"\nrandom.betaprime.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n beta prime distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.betaprime` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.betaprime.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.betaprime.PRNG":"\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.betaprime.PRNG;","random.betaprime.seed":"\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.betaprime.seed;","random.betaprime.seedLength":"\nrandom.betaprime.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.betaprime.seedLength;","random.betaprime.state":"\nrandom.betaprime.state\n Generator state.\n\n Examples\n --------\n > var out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.betaprime.state\n \n\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.betaprime.state = state;\n\n // Regenerate a previous array:\n > out = random.betaprime( [ 3, 3 ], 2.0, 5.0 )\n ","random.betaprime.stateLength":"\nrandom.betaprime.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.betaprime.stateLength;","random.betaprime.byteLength":"\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.betaprime.byteLength;\n\n See Also\n --------\n base.random.betaprime, random.array.betaprime, random.strided.betaprime","random.binomial":"\nrandom.binomial( shape, n, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n n: number|ndarray\n Number of trials. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.binomial.assign( n, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n n: number|ndarray\n Number of trials. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.binomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.binomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a binomial\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.binomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.binomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.binomial.PRNG;\n\n\nrandom.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.binomial.seed;\n\n\nrandom.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.binomial.seedLength;\n\n\nrandom.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.binomial.state\n \n\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.binomial.stateLength;\n\n\nrandom.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.binomial.byteLength;\n\n See Also\n --------\n base.random.binomial, random.array.binomial\n","random.binomial.assign":"\nrandom.binomial.assign( n, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a binomial\n distribution.\n\n Parameters\n ----------\n n: number|ndarray\n Number of trials. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.binomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true","random.binomial.factory":"\nrandom.binomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a binomial\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.binomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.binomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n ","random.binomial.PRNG":"\nrandom.binomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.binomial.PRNG;","random.binomial.seed":"\nrandom.binomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.binomial.seed;","random.binomial.seedLength":"\nrandom.binomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.binomial.seedLength;","random.binomial.state":"\nrandom.binomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.binomial.state\n \n\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.binomial.state = state;\n\n // Regenerate a previous array:\n > out = random.binomial( [ 3, 3 ], 17, 0.5 )\n ","random.binomial.stateLength":"\nrandom.binomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.binomial.stateLength;","random.binomial.byteLength":"\nrandom.binomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.binomial.byteLength;\n\n See Also\n --------\n base.random.binomial, random.array.binomial","random.cauchy":"\nrandom.cauchy( shape, x0, gamma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Cauchy\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n x0: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n gamma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cauchy.assign( x0, gamma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n gamma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cauchy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.cauchy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Cauchy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cauchy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cauchy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cauchy.PRNG;\n\n\nrandom.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cauchy.seed;\n\n\nrandom.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cauchy.seedLength;\n\n\nrandom.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cauchy.state\n \n\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cauchy.stateLength;\n\n\nrandom.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy, random.array.cauchy\n","random.cauchy.assign":"\nrandom.cauchy.assign( x0, gamma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Cauchy distribution.\n\n Parameters\n ----------\n x0: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n gamma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cauchy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.cauchy.factory":"\nrandom.cauchy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Cauchy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cauchy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cauchy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.cauchy.PRNG":"\nrandom.cauchy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cauchy.PRNG;","random.cauchy.seed":"\nrandom.cauchy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cauchy.seed;","random.cauchy.seedLength":"\nrandom.cauchy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cauchy.seedLength;","random.cauchy.state":"\nrandom.cauchy.state\n Generator state.\n\n Examples\n --------\n > var out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cauchy.state\n \n\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cauchy.state = state;\n\n // Regenerate a previous array:\n > out = random.cauchy( [ 3, 3 ], 2.0, 5.0 )\n ","random.cauchy.stateLength":"\nrandom.cauchy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cauchy.stateLength;","random.cauchy.byteLength":"\nrandom.cauchy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cauchy.byteLength;\n\n See Also\n --------\n base.random.cauchy, random.array.cauchy","random.chi":"\nrandom.chi( shape, k[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.chi( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chi.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chi.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.chi.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chi` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chi.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chi.PRNG;\n\n\nrandom.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chi.seed;\n\n\nrandom.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chi.seedLength;\n\n\nrandom.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chi.state\n \n\n > out = random.chi( [ 3, 3 ], 2.0 )\n \n > out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.chi( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chi.stateLength;\n\n\nrandom.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi, random.strided.chi\n","random.chi.assign":"\nrandom.chi.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chi.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.chi.factory":"\nrandom.chi.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chi` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chi.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.chi.PRNG":"\nrandom.chi.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chi.PRNG;","random.chi.seed":"\nrandom.chi.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chi.seed;","random.chi.seedLength":"\nrandom.chi.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chi.seedLength;","random.chi.state":"\nrandom.chi.state\n Generator state.\n\n Examples\n --------\n > var out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chi.state\n \n\n > out = random.chi( [ 3, 3 ], 2.0 )\n \n > out = random.chi( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chi.state = state;\n\n // Regenerate a previous array:\n > out = random.chi( [ 3, 3 ], 2.0 )\n ","random.chi.stateLength":"\nrandom.chi.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chi.stateLength;","random.chi.byteLength":"\nrandom.chi.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chi.byteLength;\n\n See Also\n --------\n base.random.chi, random.array.chi, random.strided.chi","random.chisquare":"\nrandom.chisquare( shape, k[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chisquare.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chisquare.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.chisquare.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi-\n square distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chisquare` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chisquare.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chisquare.PRNG;\n\n\nrandom.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chisquare.seed;\n\n\nrandom.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chisquare.seedLength;\n\n\nrandom.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chisquare.state\n \n\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n\nrandom.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chisquare.stateLength;\n\n\nrandom.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare, random.strided.chisquare\n","random.chisquare.assign":"\nrandom.chisquare.assign( k, out )\n Fills an ndarray with pseudorandom numbers drawn from a chi-square\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.chisquare.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.chisquare.factory":"\nrandom.chisquare.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a chi-\n square distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.chisquare` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.chisquare.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.chisquare.PRNG":"\nrandom.chisquare.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.chisquare.PRNG;","random.chisquare.seed":"\nrandom.chisquare.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.chisquare.seed;","random.chisquare.seedLength":"\nrandom.chisquare.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.chisquare.seedLength;","random.chisquare.state":"\nrandom.chisquare.state\n Generator state.\n\n Examples\n --------\n > var out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.chisquare.state\n \n\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n > out = random.chisquare( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.chisquare.state = state;\n\n // Regenerate a previous array:\n > out = random.chisquare( [ 3, 3 ], 2.0 )\n ","random.chisquare.stateLength":"\nrandom.chisquare.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.chisquare.stateLength;","random.chisquare.byteLength":"\nrandom.chisquare.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.chisquare.byteLength;\n\n See Also\n --------\n base.random.chisquare, random.array.chisquare, random.strided.chisquare","random.cosine":"\nrandom.cosine( shape, mu, s[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a raised\n cosine distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cosine.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cosine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.cosine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cosine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cosine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cosine.PRNG;\n\n\nrandom.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cosine.seed;\n\n\nrandom.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cosine.seedLength;\n\n\nrandom.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cosine.state\n \n\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cosine.stateLength;\n\n\nrandom.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.array.cosine, random.strided.cosine\n","random.cosine.assign":"\nrandom.cosine.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a raised cosine\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.cosine.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.cosine.factory":"\nrandom.cosine.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.cosine` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.cosine.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.cosine.PRNG":"\nrandom.cosine.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.cosine.PRNG;","random.cosine.seed":"\nrandom.cosine.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.cosine.seed;","random.cosine.seedLength":"\nrandom.cosine.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.cosine.seedLength;","random.cosine.state":"\nrandom.cosine.state\n Generator state.\n\n Examples\n --------\n > var out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.cosine.state\n \n\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.cosine.state = state;\n\n // Regenerate a previous array:\n > out = random.cosine( [ 3, 3 ], 2.0, 5.0 )\n ","random.cosine.stateLength":"\nrandom.cosine.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.cosine.stateLength;","random.cosine.byteLength":"\nrandom.cosine.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.cosine.byteLength;\n\n See Also\n --------\n base.random.cosine, random.array.cosine, random.strided.cosine","random.discreteUniform":"\nrandom.discreteUniform( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n\nrandom.discreteUniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.discreteUniform.assign( -10, 10, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.discreteUniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.discreteUniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.discreteUniform.factory();\n > var out = fcn( [ 3, 3 ], -10, 10 )\n \n\n\nrandom.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.discreteUniform.PRNG;\n\n\nrandom.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.discreteUniform.seed;\n\n\nrandom.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.discreteUniform.seedLength;\n\n\nrandom.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.discreteUniform.state\n \n\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Set the state:\n > random.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n\nrandom.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.discreteUniform.stateLength;\n\n\nrandom.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.discreteUniform.byteLength;\n\n See Also\n --------\n random.uniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.discreteUniform\n","random.discreteUniform.assign":"\nrandom.discreteUniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a discrete uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.discreteUniform.assign( -10, 10, out )\n \n > var bool = ( v === out )\n true","random.discreteUniform.factory":"\nrandom.discreteUniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a discrete\n uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.discreteUniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom integers. If provided, the `state` and `seed`\n options are ignored. In order to seed the returned pseudorandom number\n generator, one must seed the provided `prng` (assuming the provided\n `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n properties specifying the minimum and maximum possible pseudorandom\n integers.\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.discreteUniform.factory();\n > var out = fcn( [ 3, 3 ], -10, 10 )\n ","random.discreteUniform.PRNG":"\nrandom.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.discreteUniform.PRNG;","random.discreteUniform.seed":"\nrandom.discreteUniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.discreteUniform.seed;","random.discreteUniform.seedLength":"\nrandom.discreteUniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.discreteUniform.seedLength;","random.discreteUniform.state":"\nrandom.discreteUniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Get a copy of the current state:\n > var state = random.discreteUniform.state\n \n\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n \n\n // Set the state:\n > random.discreteUniform.state = state;\n\n // Regenerate a previous array:\n > out = random.discreteUniform( [ 3, 3 ], -10, 10 )\n ","random.discreteUniform.stateLength":"\nrandom.discreteUniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.discreteUniform.stateLength;","random.discreteUniform.byteLength":"\nrandom.discreteUniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.discreteUniform.byteLength;\n\n See Also\n --------\n random.uniform, base.random.discreteUniform, random.array.discreteUniform, random.strided.discreteUniform","random.erlang":"\nrandom.erlang( shape, k, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n\nrandom.erlang.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.erlang.assign( 2, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.erlang.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.erlang` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.erlang.factory();\n > var out = fcn( [ 3, 3 ], 2, 5.0 )\n \n\n\nrandom.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.erlang.PRNG;\n\n\nrandom.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.erlang.seed;\n\n\nrandom.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.erlang.seedLength;\n\n\nrandom.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.erlang.state\n \n\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Set the state:\n > random.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n\nrandom.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.erlang.stateLength;\n\n\nrandom.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang, random.array.erlang\n","random.erlang.assign":"\nrandom.erlang.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an Erlang\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.erlang.assign( 2, 5.0, out )\n \n > var bool = ( v === out )\n true","random.erlang.factory":"\nrandom.erlang.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an Erlang\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.erlang` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.erlang.factory();\n > var out = fcn( [ 3, 3 ], 2, 5.0 )\n ","random.erlang.PRNG":"\nrandom.erlang.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.erlang.PRNG;","random.erlang.seed":"\nrandom.erlang.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.erlang.seed;","random.erlang.seedLength":"\nrandom.erlang.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.erlang.seedLength;","random.erlang.state":"\nrandom.erlang.state\n Generator state.\n\n Examples\n --------\n > var out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.erlang.state\n \n\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n \n\n // Set the state:\n > random.erlang.state = state;\n\n // Regenerate a previous array:\n > out = random.erlang( [ 3, 3 ], 2, 5.0 )\n ","random.erlang.stateLength":"\nrandom.erlang.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.erlang.stateLength;","random.erlang.byteLength":"\nrandom.erlang.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.erlang.byteLength;\n\n See Also\n --------\n base.random.erlang, random.array.erlang","random.exponential":"\nrandom.exponential( shape, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n\nrandom.exponential.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.exponential.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.exponential.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.exponential` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.exponential.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.exponential.PRNG;\n\n\nrandom.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.exponential.seed;\n\n\nrandom.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.exponential.seedLength;\n\n\nrandom.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.exponential.state\n \n\n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n\nrandom.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.exponential.stateLength;\n\n\nrandom.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential, random.strided.exponential\n","random.exponential.assign":"\nrandom.exponential.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from an exponential\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.exponential.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.exponential.factory":"\nrandom.exponential.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an\n exponential distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.exponential` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.exponential.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.exponential.PRNG":"\nrandom.exponential.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.exponential.PRNG;","random.exponential.seed":"\nrandom.exponential.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.exponential.seed;","random.exponential.seedLength":"\nrandom.exponential.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.exponential.seedLength;","random.exponential.state":"\nrandom.exponential.state\n Generator state.\n\n Examples\n --------\n > var out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.exponential.state\n \n\n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n > out = random.exponential( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.exponential.state = state;\n\n // Regenerate a previous array:\n > out = random.exponential( [ 3, 3 ], 2.0 )\n ","random.exponential.stateLength":"\nrandom.exponential.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.exponential.stateLength;","random.exponential.byteLength":"\nrandom.exponential.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.exponential.byteLength;\n\n See Also\n --------\n base.random.exponential, random.array.exponential, random.strided.exponential","random.f":"\nrandom.f( shape, d1, d2[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an F\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n d1: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n d2: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.f.assign( d1, d2, out )\n Fills an ndarray with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n d2: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.f.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.f.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an F\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.f` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.f.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.f.PRNG;\n\n\nrandom.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.f.seed;\n\n\nrandom.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.f.seedLength;\n\n\nrandom.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.f.state\n \n\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.f.state = state;\n\n // Regenerate a previous array:\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.f.stateLength;\n\n\nrandom.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.f.byteLength;\n\n See Also\n --------\n base.random.f, random.array.f\n","random.f.assign":"\nrandom.f.assign( d1, d2, out )\n Fills an ndarray with pseudorandom numbers drawn from an F distribution.\n\n Parameters\n ----------\n d1: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n d2: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.f.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.f.factory":"\nrandom.f.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an F\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.f` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.f.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.f.PRNG":"\nrandom.f.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.f.PRNG;","random.f.seed":"\nrandom.f.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.f.seed;","random.f.seedLength":"\nrandom.f.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.f.seedLength;","random.f.state":"\nrandom.f.state\n Generator state.\n\n Examples\n --------\n > var out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.f.state\n \n\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.f.state = state;\n\n // Regenerate a previous array:\n > out = random.f( [ 3, 3 ], 2.0, 5.0 )\n ","random.f.stateLength":"\nrandom.f.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.f.stateLength;","random.f.byteLength":"\nrandom.f.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.f.byteLength;\n\n See Also\n --------\n base.random.f, random.array.f","random.frechet":"\nrandom.frechet( shape, alpha, s, m[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n m: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.frechet.assign( alpha, s, m, out )\n Fills an ndarray with pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n m: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.frechet.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.frechet.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.frechet` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.frechet.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.frechet.PRNG;\n\n\nrandom.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.frechet.seed;\n\n\nrandom.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.frechet.seedLength;\n\n\nrandom.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.frechet.state\n \n\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.frechet.stateLength;\n\n\nrandom.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.array.frechet\n","random.frechet.assign":"\nrandom.frechet.assign( alpha, s, m, out )\n Fills an ndarray with pseudorandom numbers drawn from a Fréchet\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n m: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.frechet.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true","random.frechet.factory":"\nrandom.frechet.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.frechet` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.frechet.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.frechet.PRNG":"\nrandom.frechet.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.frechet.PRNG;","random.frechet.seed":"\nrandom.frechet.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.frechet.seed;","random.frechet.seedLength":"\nrandom.frechet.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.frechet.seedLength;","random.frechet.state":"\nrandom.frechet.state\n Generator state.\n\n Examples\n --------\n > var out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.frechet.state\n \n\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.frechet.state = state;\n\n // Regenerate a previous array:\n > out = random.frechet( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.frechet.stateLength":"\nrandom.frechet.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.frechet.stateLength;","random.frechet.byteLength":"\nrandom.frechet.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.frechet.byteLength;\n\n See Also\n --------\n base.random.frechet, random.array.frechet","random.gamma":"\nrandom.gamma( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a gamma\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n beta: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.gamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gamma.PRNG;\n\n\nrandom.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gamma.seed;\n\n\nrandom.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gamma.seedLength;\n\n\nrandom.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gamma.state\n \n\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gamma.stateLength;\n\n\nrandom.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.array.gamma, random.strided.gamma\n","random.gamma.assign":"\nrandom.gamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a gamma distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Rate parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.gamma.factory":"\nrandom.gamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a gamma\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.gamma.PRNG":"\nrandom.gamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gamma.PRNG;","random.gamma.seed":"\nrandom.gamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gamma.seed;","random.gamma.seedLength":"\nrandom.gamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gamma.seedLength;","random.gamma.state":"\nrandom.gamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gamma.state\n \n\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gamma.state = state;\n\n // Regenerate a previous array:\n > out = random.gamma( [ 3, 3 ], 2.0, 5.0 )\n ","random.gamma.stateLength":"\nrandom.gamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gamma.stateLength;","random.gamma.byteLength":"\nrandom.gamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gamma.byteLength;\n\n See Also\n --------\n base.random.gamma, random.array.gamma, random.strided.gamma","random.geometric":"\nrandom.geometric( shape, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n\nrandom.geometric.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.geometric.assign( 0.01, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.geometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.geometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.geometric.factory();\n > var out = fcn( [ 3, 3 ], 0.01 )\n \n\n\nrandom.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.geometric.PRNG;\n\n\nrandom.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.geometric.seed;\n\n\nrandom.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.geometric.seedLength;\n\n\nrandom.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.geometric.state\n \n\n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Set the state:\n > random.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n\nrandom.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.geometric.stateLength;\n\n\nrandom.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric, random.strided.geometric\n","random.geometric.assign":"\nrandom.geometric.assign( p, out )\n Fills an ndarray with pseudorandom numbers drawn from a geometric\n distribution.\n\n Parameters\n ----------\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.geometric.assign( 0.01, out )\n \n > var bool = ( v === out )\n true","random.geometric.factory":"\nrandom.geometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n geometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.geometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.geometric.factory();\n > var out = fcn( [ 3, 3 ], 0.01 )\n ","random.geometric.PRNG":"\nrandom.geometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.geometric.PRNG;","random.geometric.seed":"\nrandom.geometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.geometric.seed;","random.geometric.seedLength":"\nrandom.geometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.geometric.seedLength;","random.geometric.state":"\nrandom.geometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Get a copy of the current state:\n > var state = random.geometric.state\n \n\n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n > out = random.geometric( [ 3, 3 ], 0.01 )\n \n\n // Set the state:\n > random.geometric.state = state;\n\n // Regenerate a previous array:\n > out = random.geometric( [ 3, 3 ], 0.01 )\n ","random.geometric.stateLength":"\nrandom.geometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.geometric.stateLength;","random.geometric.byteLength":"\nrandom.geometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.geometric.byteLength;\n\n See Also\n --------\n base.random.geometric, random.array.geometric, random.strided.geometric","random.gumbel":"\nrandom.gumbel( shape, mu, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Gumbel\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gumbel.assign( mu, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gumbel.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.gumbel.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gumbel` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gumbel.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gumbel.PRNG;\n\n\nrandom.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gumbel.seed;\n\n\nrandom.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gumbel.seedLength;\n\n\nrandom.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gumbel.state\n \n\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gumbel.stateLength;\n\n\nrandom.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel, random.array.gumbel\n","random.gumbel.assign":"\nrandom.gumbel.assign( mu, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Gumbel distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.gumbel.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.gumbel.factory":"\nrandom.gumbel.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.gumbel` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.gumbel.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.gumbel.PRNG":"\nrandom.gumbel.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.gumbel.PRNG;","random.gumbel.seed":"\nrandom.gumbel.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.gumbel.seed;","random.gumbel.seedLength":"\nrandom.gumbel.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.gumbel.seedLength;","random.gumbel.state":"\nrandom.gumbel.state\n Generator state.\n\n Examples\n --------\n > var out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.gumbel.state\n \n\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.gumbel.state = state;\n\n // Regenerate a previous array:\n > out = random.gumbel( [ 3, 3 ], 2.0, 5.0 )\n ","random.gumbel.stateLength":"\nrandom.gumbel.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.gumbel.stateLength;","random.gumbel.byteLength":"\nrandom.gumbel.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.gumbel.byteLength;\n\n See Also\n --------\n base.random.gumbel, random.array.gumbel","random.hypergeometric":"\nrandom.hypergeometric( shape, N, K, n[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n N: number|ndarray\n Population size. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n K: number|ndarray\n Subpopulation size. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n n: number|ndarray\n Number of draws. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n\nrandom.hypergeometric.assign( N, K, n, out )\n Fills an ndarray with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number|ndarray\n Population size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n K: number|ndarray\n Subpopulation size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n n: number|ndarray\n Number of draws. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.hypergeometric.assign( 20, 10, 7, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.hypergeometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.hypergeometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.hypergeometric.factory();\n > var out = fcn( [ 3, 3 ], 20, 10, 7 )\n \n\n\nrandom.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.hypergeometric.PRNG;\n\n\nrandom.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.hypergeometric.seed;\n\n\nrandom.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.hypergeometric.seedLength;\n\n\nrandom.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.hypergeometric.state\n \n\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Set the state:\n > random.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n\nrandom.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.hypergeometric.stateLength;\n\n\nrandom.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.array.hypergeometric\n","random.hypergeometric.assign":"\nrandom.hypergeometric.assign( N, K, n, out )\n Fills an ndarray with pseudorandom numbers drawn from a hypergeometric\n distribution.\n\n Parameters\n ----------\n N: number|ndarray\n Population size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n K: number|ndarray\n Subpopulation size. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n n: number|ndarray\n Number of draws. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.hypergeometric.assign( 20, 10, 7, out )\n \n > var bool = ( v === out )\n true","random.hypergeometric.factory":"\nrandom.hypergeometric.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.hypergeometric` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.hypergeometric.factory();\n > var out = fcn( [ 3, 3 ], 20, 10, 7 )\n ","random.hypergeometric.PRNG":"\nrandom.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.hypergeometric.PRNG;","random.hypergeometric.seed":"\nrandom.hypergeometric.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.hypergeometric.seed;","random.hypergeometric.seedLength":"\nrandom.hypergeometric.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.hypergeometric.seedLength;","random.hypergeometric.state":"\nrandom.hypergeometric.state\n Generator state.\n\n Examples\n --------\n > var out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Get a copy of the current state:\n > var state = random.hypergeometric.state\n \n\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n \n\n // Set the state:\n > random.hypergeometric.state = state;\n\n // Regenerate a previous array:\n > out = random.hypergeometric( [ 3, 3 ], 20, 10, 7 )\n ","random.hypergeometric.stateLength":"\nrandom.hypergeometric.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.hypergeometric.stateLength;","random.hypergeometric.byteLength":"\nrandom.hypergeometric.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.hypergeometric.byteLength;\n\n See Also\n --------\n base.random.hypergeometric, random.array.hypergeometric","random.invgamma":"\nrandom.invgamma( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from an inverse\n gamma distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.invgamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.invgamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.invgamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an inverse\n gamma distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.invgamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.invgamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.invgamma.PRNG;\n\n\nrandom.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.invgamma.seed;\n\n\nrandom.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.invgamma.seedLength;\n\n\nrandom.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.invgamma.state\n \n\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.invgamma.stateLength;\n\n\nrandom.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma, random.strided.invgamma\n","random.invgamma.assign":"\nrandom.invgamma.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from an inverse gamma\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.invgamma.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.invgamma.factory":"\nrandom.invgamma.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from an inverse\n gamma distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.invgamma` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.invgamma.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.invgamma.PRNG":"\nrandom.invgamma.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.invgamma.PRNG;","random.invgamma.seed":"\nrandom.invgamma.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.invgamma.seed;","random.invgamma.seedLength":"\nrandom.invgamma.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.invgamma.seedLength;","random.invgamma.state":"\nrandom.invgamma.state\n Generator state.\n\n Examples\n --------\n > var out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.invgamma.state\n \n\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.invgamma.state = state;\n\n // Regenerate a previous array:\n > out = random.invgamma( [ 3, 3 ], 2.0, 5.0 )\n ","random.invgamma.stateLength":"\nrandom.invgamma.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.invgamma.stateLength;","random.invgamma.byteLength":"\nrandom.invgamma.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.invgamma.byteLength;\n\n See Also\n --------\n base.random.invgamma, random.array.invgamma, random.strided.invgamma","random.kumaraswamy":"\nrandom.kumaraswamy( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.kumaraswamy.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.kumaraswamy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.kumaraswamy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Kumaraswamy distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.kumaraswamy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.kumaraswamy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.kumaraswamy.PRNG;\n\n\nrandom.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.kumaraswamy.seed;\n\n\nrandom.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.kumaraswamy.seedLength;\n\n\nrandom.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.kumaraswamy.state\n \n\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.kumaraswamy.stateLength;\n\n\nrandom.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy, random.array.kumaraswamy\n","random.kumaraswamy.assign":"\nrandom.kumaraswamy.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n First shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n b: number|ndarray\n Second shape parameter. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.kumaraswamy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.kumaraswamy.factory":"\nrandom.kumaraswamy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Kumaraswamy distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.kumaraswamy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.kumaraswamy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.kumaraswamy.PRNG":"\nrandom.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.kumaraswamy.PRNG;","random.kumaraswamy.seed":"\nrandom.kumaraswamy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.kumaraswamy.seed;","random.kumaraswamy.seedLength":"\nrandom.kumaraswamy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.kumaraswamy.seedLength;","random.kumaraswamy.state":"\nrandom.kumaraswamy.state\n Generator state.\n\n Examples\n --------\n > var out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.kumaraswamy.state\n \n\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.kumaraswamy.state = state;\n\n // Regenerate a previous array:\n > out = random.kumaraswamy( [ 3, 3 ], 2.0, 5.0 )\n ","random.kumaraswamy.stateLength":"\nrandom.kumaraswamy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.kumaraswamy.stateLength;","random.kumaraswamy.byteLength":"\nrandom.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.kumaraswamy.byteLength;\n\n See Also\n --------\n base.random.kumaraswamy, random.array.kumaraswamy","random.laplace":"\nrandom.laplace( shape, mu, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n b: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.laplace.assign( mu, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n b: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.laplace.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.laplace.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.laplace` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.laplace.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.laplace.PRNG;\n\n\nrandom.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.laplace.seed;\n\n\nrandom.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.laplace.seedLength;\n\n\nrandom.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.laplace.state\n \n\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.laplace.stateLength;\n\n\nrandom.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace, random.array.laplace\n","random.laplace.assign":"\nrandom.laplace.assign( mu, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n b: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.laplace.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.laplace.factory":"\nrandom.laplace.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.laplace` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.laplace.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.laplace.PRNG":"\nrandom.laplace.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.laplace.PRNG;","random.laplace.seed":"\nrandom.laplace.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.laplace.seed;","random.laplace.seedLength":"\nrandom.laplace.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.laplace.seedLength;","random.laplace.state":"\nrandom.laplace.state\n Generator state.\n\n Examples\n --------\n > var out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.laplace.state\n \n\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.laplace.state = state;\n\n // Regenerate a previous array:\n > out = random.laplace( [ 3, 3 ], 2.0, 5.0 )\n ","random.laplace.stateLength":"\nrandom.laplace.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.laplace.stateLength;","random.laplace.byteLength":"\nrandom.laplace.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.laplace.byteLength;\n\n See Also\n --------\n base.random.laplace, random.array.laplace","random.levy":"\nrandom.levy( shape, mu, c[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Lévy\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n c: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.levy.assign( mu, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.levy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.levy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.levy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.levy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.levy.PRNG;\n\n\nrandom.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.levy.seed;\n\n\nrandom.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.levy.seedLength;\n\n\nrandom.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.levy.state\n \n\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.levy.stateLength;\n\n\nrandom.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.levy.byteLength;\n\n See Also\n --------\n base.random.levy, random.array.levy\n","random.levy.assign":"\nrandom.levy.assign( mu, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a Lévy distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.levy.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.levy.factory":"\nrandom.levy.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Lévy\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.levy` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.levy.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.levy.PRNG":"\nrandom.levy.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.levy.PRNG;","random.levy.seed":"\nrandom.levy.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.levy.seed;","random.levy.seedLength":"\nrandom.levy.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.levy.seedLength;","random.levy.state":"\nrandom.levy.state\n Generator state.\n\n Examples\n --------\n > var out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.levy.state\n \n\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.levy.state = state;\n\n // Regenerate a previous array:\n > out = random.levy( [ 3, 3 ], 2.0, 5.0 )\n ","random.levy.stateLength":"\nrandom.levy.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.levy.stateLength;","random.levy.byteLength":"\nrandom.levy.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.levy.byteLength;\n\n See Also\n --------\n base.random.levy, random.array.levy","random.logistic":"\nrandom.logistic( shape, mu, s[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.logistic.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.logistic.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.logistic.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a logistic\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.logistic` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.logistic.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.logistic.PRNG;\n\n\nrandom.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.logistic.seed;\n\n\nrandom.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.logistic.seedLength;\n\n\nrandom.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.logistic.state\n \n\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.logistic.stateLength;\n\n\nrandom.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic, random.array.logistic\n","random.logistic.assign":"\nrandom.logistic.assign( mu, s, out )\n Fills an ndarray with pseudorandom numbers drawn from a logistic\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n s: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.logistic.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.logistic.factory":"\nrandom.logistic.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a logistic\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.logistic` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.logistic.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.logistic.PRNG":"\nrandom.logistic.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.logistic.PRNG;","random.logistic.seed":"\nrandom.logistic.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.logistic.seed;","random.logistic.seedLength":"\nrandom.logistic.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.logistic.seedLength;","random.logistic.state":"\nrandom.logistic.state\n Generator state.\n\n Examples\n --------\n > var out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.logistic.state\n \n\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.logistic.state = state;\n\n // Regenerate a previous array:\n > out = random.logistic( [ 3, 3 ], 2.0, 5.0 )\n ","random.logistic.stateLength":"\nrandom.logistic.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.logistic.stateLength;","random.logistic.byteLength":"\nrandom.logistic.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.logistic.byteLength;\n\n See Also\n --------\n base.random.logistic, random.array.logistic","random.lognormal":"\nrandom.lognormal( shape, mu, sigma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.lognormal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.lognormal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.lognormal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.lognormal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.lognormal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.lognormal.PRNG;\n\n\nrandom.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.lognormal.seed;\n\n\nrandom.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.lognormal.seedLength;\n\n\nrandom.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.lognormal.state\n \n\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.lognormal.stateLength;\n\n\nrandom.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal, random.strided.lognormal\n","random.lognormal.assign":"\nrandom.lognormal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a lognormal\n distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Location parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.lognormal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.lognormal.factory":"\nrandom.lognormal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n lognormal distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.lognormal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.lognormal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.lognormal.PRNG":"\nrandom.lognormal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.lognormal.PRNG;","random.lognormal.seed":"\nrandom.lognormal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.lognormal.seed;","random.lognormal.seedLength":"\nrandom.lognormal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.lognormal.seedLength;","random.lognormal.state":"\nrandom.lognormal.state\n Generator state.\n\n Examples\n --------\n > var out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.lognormal.state\n \n\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.lognormal.state = state;\n\n // Regenerate a previous array:\n > out = random.lognormal( [ 3, 3 ], 2.0, 5.0 )\n ","random.lognormal.stateLength":"\nrandom.lognormal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.lognormal.stateLength;","random.lognormal.byteLength":"\nrandom.lognormal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.lognormal.byteLength;\n\n See Also\n --------\n base.random.lognormal, random.array.lognormal, random.strided.lognormal","random.negativeBinomial":"\nrandom.negativeBinomial( shape, r, p[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a negative\n binomial distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n r: number|ndarray\n Number of successes until experiment is stopped. If an ndarray, must be\n broadcast compatible with the specified array shape.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.negativeBinomial.assign( r, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number|ndarray\n Number of successes until experiment is stopped. If an ndarray, must be\n broadcast compatible with the provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.negativeBinomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.negativeBinomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a negative\n binomial distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.negativeBinomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.negativeBinomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.negativeBinomial.PRNG;\n\n\nrandom.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.negativeBinomial.seed;\n\n\nrandom.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.negativeBinomial.seedLength;\n\n\nrandom.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.negativeBinomial.state\n \n\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n\nrandom.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.negativeBinomial.stateLength;\n\n\nrandom.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.negativeBinomial.byteLength;\n\n See Also\n --------\n base.random.negativeBinomial, random.array.negativeBinomial\n","random.negativeBinomial.assign":"\nrandom.negativeBinomial.assign( r, p, out )\n Fills an ndarray with pseudorandom numbers drawn from a negative binomial\n distribution.\n\n Parameters\n ----------\n r: number|ndarray\n Number of successes until experiment is stopped. If an ndarray, must be\n broadcast compatible with the provided output array.\n\n p: number|ndarray\n Success probability. If an ndarray, must be broadcast compatible with\n the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.negativeBinomial.assign( 17, 0.5, out )\n \n > var bool = ( v === out )\n true","random.negativeBinomial.factory":"\nrandom.negativeBinomial.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a negative\n binomial distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.negativeBinomial` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.negativeBinomial.factory();\n > var out = fcn( [ 3, 3 ], 17, 0.5 )\n ","random.negativeBinomial.PRNG":"\nrandom.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.negativeBinomial.PRNG;","random.negativeBinomial.seed":"\nrandom.negativeBinomial.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.negativeBinomial.seed;","random.negativeBinomial.seedLength":"\nrandom.negativeBinomial.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.negativeBinomial.seedLength;","random.negativeBinomial.state":"\nrandom.negativeBinomial.state\n Generator state.\n\n Examples\n --------\n > var out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Get a copy of the current state:\n > var state = random.negativeBinomial.state\n \n\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n \n\n // Set the state:\n > random.negativeBinomial.state = state;\n\n // Regenerate a previous array:\n > out = random.negativeBinomial( [ 3, 3 ], 17, 0.5 )\n ","random.negativeBinomial.stateLength":"\nrandom.negativeBinomial.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.negativeBinomial.stateLength;","random.negativeBinomial.byteLength":"\nrandom.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.negativeBinomial.byteLength;\n\n See Also\n --------\n base.random.negativeBinomial, random.array.negativeBinomial","random.normal":"\nrandom.normal( shape, mu, sigma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a normal\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n sigma: number|ndarray\n Standard deviation. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.normal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n sigma: number|ndarray\n Standard deviation. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.normal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.normal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a normal\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.normal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.normal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.normal.PRNG;\n\n\nrandom.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.normal.seed;\n\n\nrandom.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.normal.seedLength;\n\n\nrandom.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.normal.state\n \n\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.normal.stateLength;\n\n\nrandom.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.array.normal, random.strided.normal\n","random.normal.assign":"\nrandom.normal.assign( mu, sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a normal distribution.\n\n Parameters\n ----------\n mu: number|ndarray\n Mean. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n sigma: number|ndarray\n Standard deviation. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.normal.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.normal.factory":"\nrandom.normal.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a normal\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.normal` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.normal.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.normal.PRNG":"\nrandom.normal.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.normal.PRNG;","random.normal.seed":"\nrandom.normal.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.normal.seed;","random.normal.seedLength":"\nrandom.normal.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.normal.seedLength;","random.normal.state":"\nrandom.normal.state\n Generator state.\n\n Examples\n --------\n > var out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.normal.state\n \n\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.normal.state = state;\n\n // Regenerate a previous array:\n > out = random.normal( [ 3, 3 ], 2.0, 5.0 )\n ","random.normal.stateLength":"\nrandom.normal.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.normal.stateLength;","random.normal.byteLength":"\nrandom.normal.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.normal.byteLength;\n\n See Also\n --------\n base.random.normal, random.array.normal, random.strided.normal","random.pareto1":"\nrandom.pareto1( shape, alpha, beta[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.pareto1.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.pareto1.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.pareto1.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.pareto1` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.pareto1.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.pareto1.PRNG;\n\n\nrandom.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.pareto1.seed;\n\n\nrandom.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.pareto1.seedLength;\n\n\nrandom.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.pareto1.state\n \n\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.pareto1.stateLength;\n\n\nrandom.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.array.pareto1\n","random.pareto1.assign":"\nrandom.pareto1.assign( alpha, beta, out )\n Fills an ndarray with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n\n Parameters\n ----------\n alpha: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n beta: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.pareto1.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.pareto1.factory":"\nrandom.pareto1.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.pareto1` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.pareto1.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.pareto1.PRNG":"\nrandom.pareto1.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.pareto1.PRNG;","random.pareto1.seed":"\nrandom.pareto1.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.pareto1.seed;","random.pareto1.seedLength":"\nrandom.pareto1.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.pareto1.seedLength;","random.pareto1.state":"\nrandom.pareto1.state\n Generator state.\n\n Examples\n --------\n > var out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.pareto1.state\n \n\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.pareto1.state = state;\n\n // Regenerate a previous array:\n > out = random.pareto1( [ 3, 3 ], 2.0, 5.0 )\n ","random.pareto1.stateLength":"\nrandom.pareto1.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.pareto1.stateLength;","random.pareto1.byteLength":"\nrandom.pareto1.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.pareto1.byteLength;\n\n See Also\n --------\n base.random.pareto1, random.array.pareto1","random.poisson":"\nrandom.poisson( shape, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n lambda: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real or \"generic\" data type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n\nrandom.poisson.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.poisson.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.poisson.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.poisson` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.poisson.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.poisson.PRNG;\n\n\nrandom.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.poisson.seed;\n\n\nrandom.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.poisson.seedLength;\n\n\nrandom.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.poisson.state\n \n\n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n\nrandom.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.poisson.stateLength;\n\n\nrandom.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson, random.strided.poisson\n","random.poisson.assign":"\nrandom.poisson.assign( lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Poisson\n distribution.\n\n Parameters\n ----------\n lambda: number|ndarray\n Mean parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.poisson.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.poisson.factory":"\nrandom.poisson.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Poisson\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.poisson` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.poisson.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.poisson.PRNG":"\nrandom.poisson.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.poisson.PRNG;","random.poisson.seed":"\nrandom.poisson.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.poisson.seed;","random.poisson.seedLength":"\nrandom.poisson.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.poisson.seedLength;","random.poisson.state":"\nrandom.poisson.state\n Generator state.\n\n Examples\n --------\n > var out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.poisson.state\n \n\n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n > out = random.poisson( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.poisson.state = state;\n\n // Regenerate a previous array:\n > out = random.poisson( [ 3, 3 ], 2.0 )\n ","random.poisson.stateLength":"\nrandom.poisson.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.poisson.stateLength;","random.poisson.byteLength":"\nrandom.poisson.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.poisson.byteLength;\n\n See Also\n --------\n base.random.poisson, random.array.poisson, random.strided.poisson","random.rayleigh":"\nrandom.rayleigh( shape, sigma[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n\nrandom.rayleigh.assign( sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.rayleigh.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.rayleigh.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.rayleigh` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.rayleigh.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.rayleigh.PRNG;\n\n\nrandom.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.rayleigh.seed;\n\n\nrandom.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.rayleigh.seedLength;\n\n\nrandom.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.rayleigh.state\n \n\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n\nrandom.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.rayleigh.stateLength;\n\n\nrandom.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh, random.strided.rayleigh\n","random.rayleigh.assign":"\nrandom.rayleigh.assign( sigma, out )\n Fills an ndarray with pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n Parameters\n ----------\n sigma: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.rayleigh.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.rayleigh.factory":"\nrandom.rayleigh.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Rayleigh\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.rayleigh` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.rayleigh.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.rayleigh.PRNG":"\nrandom.rayleigh.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.rayleigh.PRNG;","random.rayleigh.seed":"\nrandom.rayleigh.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.rayleigh.seed;","random.rayleigh.seedLength":"\nrandom.rayleigh.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.rayleigh.seedLength;","random.rayleigh.state":"\nrandom.rayleigh.state\n Generator state.\n\n Examples\n --------\n > var out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.rayleigh.state\n \n\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.rayleigh.state = state;\n\n // Regenerate a previous array:\n > out = random.rayleigh( [ 3, 3 ], 2.0 )\n ","random.rayleigh.stateLength":"\nrandom.rayleigh.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.rayleigh.stateLength;","random.rayleigh.byteLength":"\nrandom.rayleigh.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.rayleigh.byteLength;\n\n See Also\n --------\n base.random.rayleigh, random.array.rayleigh, random.strided.rayleigh","random.t":"\nrandom.t( shape, v[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Student's t-\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n v: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.t( [ 3, 3 ], 2.0 )\n \n\n\nrandom.t.assign( v, out )\n Fills an ndarray with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n Parameters\n ----------\n v: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.t.assign( 2.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.t.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Student's t-distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.t` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.t.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n \n\n\nrandom.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.t.PRNG;\n\n\nrandom.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.t.seed;\n\n\nrandom.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.t.seedLength;\n\n\nrandom.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.t.state\n \n\n > out = random.t( [ 3, 3 ], 2.0 )\n \n > out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.t.state = state;\n\n // Regenerate a previous array:\n > out = random.t( [ 3, 3 ], 2.0 )\n \n\n\nrandom.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.t.stateLength;\n\n\nrandom.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t, random.strided.t\n","random.t.assign":"\nrandom.t.assign( v, out )\n Fills an ndarray with pseudorandom numbers drawn from a Student's t-\n distribution.\n\n Parameters\n ----------\n v: number|ndarray\n Degrees of freedom. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.t.assign( 2.0, out )\n \n > var bool = ( v === out )\n true","random.t.factory":"\nrandom.t.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n Student's t-distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.t` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.t.factory();\n > var out = fcn( [ 3, 3 ], 2.0 )\n ","random.t.PRNG":"\nrandom.t.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.t.PRNG;","random.t.seed":"\nrandom.t.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.t.seed;","random.t.seedLength":"\nrandom.t.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.t.seedLength;","random.t.state":"\nrandom.t.state\n Generator state.\n\n Examples\n --------\n > var out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Get a copy of the current state:\n > var state = random.t.state\n \n\n > out = random.t( [ 3, 3 ], 2.0 )\n \n > out = random.t( [ 3, 3 ], 2.0 )\n \n\n // Set the state:\n > random.t.state = state;\n\n // Regenerate a previous array:\n > out = random.t( [ 3, 3 ], 2.0 )\n ","random.t.stateLength":"\nrandom.t.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.t.stateLength;","random.t.byteLength":"\nrandom.t.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.t.byteLength;\n\n See Also\n --------\n base.random.t, random.array.t, random.strided.t","random.triangular":"\nrandom.triangular( shape, a, b, c[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n c: number|ndarray\n Mode. If an ndarray, must be broadcast compatible with the specified\n array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.triangular.assign( a, b, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Mode. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.triangular.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.triangular.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.triangular` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.triangular.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.triangular.PRNG;\n\n\nrandom.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.triangular.seed;\n\n\nrandom.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.triangular.seedLength;\n\n\nrandom.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.triangular.state\n \n\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n\nrandom.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.triangular.stateLength;\n\n\nrandom.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.array.triangular\n","random.triangular.assign":"\nrandom.triangular.assign( a, b, c, out )\n Fills an ndarray with pseudorandom numbers drawn from a triangular\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n b: number|ndarray\n Maximum support. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n c: number|ndarray\n Mode. If an ndarray, must be broadcast compatible with the provided\n output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.triangular.assign( 2.0, 5.0, 3.0, out )\n \n > var bool = ( v === out )\n true","random.triangular.factory":"\nrandom.triangular.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n triangular distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.triangular` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.triangular.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.triangular.PRNG":"\nrandom.triangular.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.triangular.PRNG;","random.triangular.seed":"\nrandom.triangular.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.triangular.seed;","random.triangular.seedLength":"\nrandom.triangular.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.triangular.seedLength;","random.triangular.state":"\nrandom.triangular.state\n Generator state.\n\n Examples\n --------\n > var out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Get a copy of the current state:\n > var state = random.triangular.state\n \n\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n \n\n // Set the state:\n > random.triangular.state = state;\n\n // Regenerate a previous array:\n > out = random.triangular( [ 3, 3 ], 2.0, 5.0, 3.0 )\n ","random.triangular.stateLength":"\nrandom.triangular.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.triangular.stateLength;","random.triangular.byteLength":"\nrandom.triangular.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.triangular.byteLength;\n\n See Also\n --------\n base.random.triangular, random.array.triangular","random.uniform":"\nrandom.uniform( shape, a, b[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n a: number|ndarray\n Minimum support (inclusive). If an ndarray, must be broadcast compatible\n with the specified array shape.\n\n b: number|ndarray\n Maximum support (exclusive). If an ndarray, must be broadcast compatible\n with the specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n\nrandom.uniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support (inclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n b: number|ndarray\n Maximum support (exclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.uniform.assign( 0.0, 1.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.uniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.uniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.uniform.factory();\n > var out = fcn( [ 3, 3 ], 0.0, 1.0 )\n \n\n\nrandom.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.uniform.PRNG;\n\n\nrandom.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.uniform.seed;\n\n\nrandom.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.uniform.seedLength;\n\n\nrandom.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Get a copy of the current state:\n > var state = random.uniform.state\n \n\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Set the state:\n > random.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n\nrandom.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.uniform.stateLength;\n\n\nrandom.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.uniform.byteLength;\n\n See Also\n --------\n random.discreteUniform, base.random.uniform, random.array.uniform, random.strided.uniform\n","random.uniform.assign":"\nrandom.uniform.assign( a, b, out )\n Fills an ndarray with pseudorandom numbers drawn from a continuous uniform\n distribution.\n\n Parameters\n ----------\n a: number|ndarray\n Minimum support (inclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n b: number|ndarray\n Maximum support (exclusive). If an ndarray, must be broadcast compatible\n with the provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.uniform.assign( 0.0, 1.0, out )\n \n > var bool = ( v === out )\n true","random.uniform.factory":"\nrandom.uniform.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.uniform` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.uniform.factory();\n > var out = fcn( [ 3, 3 ], 0.0, 1.0 )\n ","random.uniform.PRNG":"\nrandom.uniform.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.uniform.PRNG;","random.uniform.seed":"\nrandom.uniform.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.uniform.seed;","random.uniform.seedLength":"\nrandom.uniform.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.uniform.seedLength;","random.uniform.state":"\nrandom.uniform.state\n Generator state.\n\n Examples\n --------\n > var out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Get a copy of the current state:\n > var state = random.uniform.state\n \n\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n \n\n // Set the state:\n > random.uniform.state = state;\n\n // Regenerate a previous array:\n > out = random.uniform( [ 3, 3 ], 0.0, 1.0 )\n ","random.uniform.stateLength":"\nrandom.uniform.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.uniform.stateLength;","random.uniform.byteLength":"\nrandom.uniform.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.uniform.byteLength;\n\n See Also\n --------\n random.discreteUniform, base.random.uniform, random.array.uniform, random.strided.uniform","random.weibull":"\nrandom.weibull( shape, k, lambda[, options] )\n Returns an ndarray containing pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n shape: Array\n Array shape.\n\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n lambda: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n specified array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a real-valued floating-point or \"generic\" data\n type.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions to\n either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'wrap', an ndarray instance wraps around subscripts exceeding\n array dimensions using modulo arithmetic. If equal to 'clamp', an\n ndarray instance sets a subscript exceeding array dimensions to either\n `0` (minimum index) or the maximum index. If the number of modes is\n less than the number of dimensions, an ndarray instance recycles modes\n using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.weibull.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.weibull.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true\n\n\nrandom.weibull.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Weibull\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.weibull` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.weibull.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.weibull.PRNG;\n\n\nrandom.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.weibull.seed;\n\n\nrandom.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.weibull.seedLength;\n\n\nrandom.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.weibull.state\n \n\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n\nrandom.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.weibull.stateLength;\n\n\nrandom.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.array.weibull, random.strided.weibull\n","random.weibull.assign":"\nrandom.weibull.assign( k, lambda, out )\n Fills an ndarray with pseudorandom numbers drawn from a Weibull\n distribution.\n\n Parameters\n ----------\n k: number|ndarray\n Shape parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n lambda: number|ndarray\n Scale parameter. If an ndarray, must be broadcast compatible with the\n provided output array.\n\n out: ndarray\n Output array.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var out = ndzeros( [ 3, 3 ] );\n > var v = random.weibull.assign( 2.0, 5.0, out )\n \n > var bool = ( v === out )\n true","random.weibull.factory":"\nrandom.weibull.factory( [options] )\n Returns a function for generating pseudorandom numbers drawn from a Weibull\n distribution.\n\n The returned function has the same signature and accepts the same options as\n `random.weibull` above.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.prng: Function (optional)\n Pseudorandom number generator (PRNG) for generating uniformly\n distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n the `state` and `seed` options are ignored. In order to seed the\n returned pseudorandom number generator, one must seed the provided\n `prng` (assuming the provided `prng` is seedable).\n\n options.seed: integer|ArrayLikeObject (optional)\n Pseudorandom number generator seed. The seed may be either a positive\n unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n object containing unsigned 32-bit integers.\n\n options.state: Uint32Array (optional)\n Pseudorandom number generator state. If provided, the `seed` option is\n ignored.\n\n options.copy: boolean (optional)\n Boolean indicating whether to copy a provided pseudorandom number\n generator state. Setting this option to `false` allows sharing state\n between two or more pseudorandom number generators. Setting this option\n to `true` ensures that a returned generator has exclusive control over\n its internal state. Default: true.\n\n Returns\n -------\n fcn: Function\n Function for creating arrays.\n\n Examples\n --------\n > var fcn = random.weibull.factory();\n > var out = fcn( [ 3, 3 ], 2.0, 5.0 )\n ","random.weibull.PRNG":"\nrandom.weibull.PRNG\n Underlying pseudorandom number generator.\n\n Examples\n --------\n > var prng = random.weibull.PRNG;","random.weibull.seed":"\nrandom.weibull.seed\n Pseudorandom number generator seed.\n\n Examples\n --------\n > var seed = random.weibull.seed;","random.weibull.seedLength":"\nrandom.weibull.seedLength\n Length of generator seed.\n\n Examples\n --------\n > var len = random.weibull.seedLength;","random.weibull.state":"\nrandom.weibull.state\n Generator state.\n\n Examples\n --------\n > var out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Get a copy of the current state:\n > var state = random.weibull.state\n \n\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n \n\n // Set the state:\n > random.weibull.state = state;\n\n // Regenerate a previous array:\n > out = random.weibull( [ 3, 3 ], 2.0, 5.0 )\n ","random.weibull.stateLength":"\nrandom.weibull.stateLength\n Length of generator state.\n\n Examples\n --------\n > var len = random.weibull.stateLength;","random.weibull.byteLength":"\nrandom.weibull.byteLength\n Size (in bytes) of generator state.\n\n Examples\n --------\n > var sz = random.weibull.byteLength;\n\n See Also\n --------\n base.random.weibull, random.array.weibull, random.strided.weibull","ranks":"\nranks( arr[, options] )\n Computes the sample ranks for the values of an array-like object.\n\n When all elements of the `array` are different, the ranks are uniquely\n determined. When there are equal elements (called *ties*), the `method`\n option determines how they are handled. The default, `'average'`, replaces\n the ranks of the ties by their mean. Other possible options are `'min'` and\n `'max'`, which replace the ranks of the ties by their minimum and maximum,\n respectively. `'dense'` works like `'min'`, with the difference that the\n next highest element after a tie is assigned the next smallest integer.\n Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n the position they appear in.\n\n The `missing` option is used to specify how to handle missing data.\n By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n that missing values are placed last, `'first'` that the are assigned the\n lowest ranks and `'remove'` means that they are removed from the array\n before the ranks are calculated.\n\n Parameters\n ----------\n arr: Array\n Input values.\n\n options: Object (optional)\n Function options.\n\n options.method (optional)\n Method name determining how ties are treated (`average`, `min`, `max`,\n `dense`, or `ordinal`). Default: `'average'`.\n\n options.missing (optional)\n Determines where missing values go (`first`, `last`, or `remove`).\n Default: `'last'`.\n\n options.encoding (optional)\n Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n Returns\n -------\n out: Array\n Array containing the computed ranks for the elements of the input array.\n\n Examples\n --------\n > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n > var out = ranks( arr )\n [ 2, 3, 5, 1, 4 ]\n\n // Ties are averaged:\n > arr = [ 2, 2, 1, 4, 3 ];\n > out = ranks( arr )\n [ 2.5, 2.5, 1, 5, 4 ]\n\n // Missing values are placed last:\n > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n > out = ranks( arr )\n [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n Asynchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n clbk: Function\n Callback to invoke after reading directory contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n Synchronously reads the contents of a directory.\n\n Parameters\n ----------\n path: string|Buffer\n Directory path.\n\n Returns\n -------\n out: Error|Array|Array\n Directory contents.\n\n Examples\n --------\n > var out = readDir.sync( './beep/boop' );\n\n See Also\n --------\n exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n Asynchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n Synchronously reads the entire contents of a file.\n\n If provided an encoding, the function returns a string. Otherwise, the\n function returns a Buffer object.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Buffer|string\n File contents.\n\n Examples\n --------\n > var out = readFile.sync( './beep/boop.js' );\n\n See Also\n --------\n exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n Asynchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Each file is represented by an object with the following fields:\n\n - file: file path.\n - data: file contents as either a Buffer or string.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n Synchronously reads the entire contents of each file in a file list.\n\n If a provided an encoding, the function returns file contents as strings.\n Otherwise, the function returns Buffer objects.\n\n Parameters\n ----------\n filepaths: Array\n Filepaths.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Array|Array\n File contents.\n\n out[ i ].file: string\n File path.\n\n out[ i ].data: Buffer|string\n File contents.\n\n Examples\n --------\n > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n Asynchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n Synchronously reads a file as JSON.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. If the encoding option is set to `utf8` and the file has a\n UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n attempting to parse as JSON. Default: null.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n options.reviver: Function (optional)\n JSON transformation function.\n\n Returns\n -------\n out: Error|JSON\n File contents.\n\n Examples\n --------\n > var out = readJSON.sync( './beep/boop.json' );\n\n See Also\n --------\n readFile","readWASM":"\nreadWASM( file[, options], clbk )\n Asynchronously reads a file as WebAssembly.\n\n The function returns file contents as a Uint8Array.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n clbk: Function\n Callback to invoke upon reading file contents.\n\n Examples\n --------\n > function onRead( error, data ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( data );\n ... }\n ... };\n > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n Synchronously reads a file as WebAssembly.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n options: Object (optional)\n Options.\n\n options.flag: string (optional)\n Flag. Default: 'r'.\n\n Returns\n -------\n out: Error|Uint8Array\n File contents.\n\n Examples\n --------\n > var out = readWASM.sync( './beep/boop.wasm' );\n\n See Also\n --------\n readFile","real":"\nreal( z )\n Returns the real component of a double-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var re = real( z )\n 5.0\n\n See Also\n --------\n imag, reim\n","realarray":"\nrealarray( [dtype] )\n Creates a typed array.\n\n The function supports the following data types:\n\n - float64: double-precision floating-point numbers (IEEE 754).\n - float32: single-precision floating-point numbers (IEEE 754).\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n The default typed array data type is `float64`.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray()\n \n > arr = realarray( 'float32' )\n \n\n\nrealarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = realarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = realarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = realarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = realarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = realarrayCtors( 'float64' )\n \n > ctor = realarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = realarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n Returns the real component of a single-precision complex floating-point\n number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n re: number\n Real component.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var re = realf( z )\n 5.0\n\n See Also\n --------\n imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum finite value.\n\n Examples\n --------\n > var m = realmax( 'float16' )\n 65504.0\n > m = realmax( 'float32' )\n 3.4028234663852886e+38\n\n See Also\n --------\n realmin, typemax\n","realmin":"\nrealmin( dtype )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Smallest finite normal value.\n\n Examples\n --------\n > var m = realmin( 'float16' )\n 0.00006103515625\n > m = realmin( 'float32' )\n 1.1754943508222875e-38\n\n See Also\n --------\n realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n Returns a regular expression to capture the last part of a path.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reBasename()\n \n > var RE_POSIX = reBasename( 'posix' );\n > var RE_WIN32 = reBasename( 'win32' );\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n \n\n\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var RE = reBasename.REGEXP\n ","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_POSIX = reBasenamePosix();\n > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n '.'\n > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n ''\n\n\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n\n Examples\n --------\n > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n 'index.js'\n\n See Also\n --------\n reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_BASENAME_WINDOWS = reBasenameWindows();\n > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n '.gitignore'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n 'file'\n > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n 'index.js'\n > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n '.'\n > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n ''\n\n\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n\n Examples\n --------\n > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'file.pdf'\n\n See Also\n --------\n reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n Returns a regular expression to match a hexadecimal color.\n\n Parameters\n ----------\n mode: string (optional)\n Color format (`full`, `shorthand`, or `either`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reColorHexadecimal();\n > var bool = RE.test( 'ffffff' )\n true\n > bool = RE.test( '000' )\n false\n > bool = RE.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false\n\n\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP.test( '000' )\n false\n > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n false\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n\n Examples\n --------\n > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n true\n > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n false","reDecimalNumber":"\nreDecimalNumber( [options] )\n Returns a regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDecimalNumber();\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n > bool = RE.test( '0.0' )\n true\n > bool = RE.test( '.0' )\n true\n > bool = RE.test( '0' )\n false\n > bool = RE.test( 'beep' )\n false\n\n // Create a RegExp to capture all decimal numbers:\n > var re = reDecimalNumber({ 'flags': 'g' });\n > var str = '1.234 5.6, 7.8';\n > var out = str.match( re )\n [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP;\n > var bool = RE.test( '1.234' )\n true\n > bool = RE.test( '-1.234' )\n true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n\n A leading digit is not required.\n\n A decimal point and at least one trailing digit is required.\n\n Examples\n --------\n > var RE = reDecimalNumber.REGEXP_CAPTURE;\n > var str = '1.02';\n > var out = replace( str, RE, '$1 x $1' )\n '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n Returns a regular expression to capture a path dirname.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirname()\n \n > var RE_POSIX = reDirname( 'posix' );\n > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > var RE_WIN32 = reDirname( 'win32' );\n > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n \n\n\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n\n Examples\n --------\n > var RE = reDirname.REGEXP\n ","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n 'C:\\foo\\bar'\n\n See Also\n --------\n reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnamePosix();\n > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n './foo/bar'\n > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n '/foo/bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '.' )[ 1 ]\n '.'\n > dir = RE.exec( './' )[ 1 ]\n '.'\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n\n Examples\n --------\n > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '/foo/bar'\n\n See Also\n --------\n reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reDirnameWindows();\n > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n 'C:\\foo\\bar'\n > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n 'foo'\n > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n '\\foo\\bar'\n > dir = RE.exec( 'index.js' )[ 1 ]\n ''\n > dir = RE.exec( '' )[ 1 ]\n ''\n\n\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n\n Examples\n --------\n > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n 'foo\\bar'\n\n See Also\n --------\n reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduce( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduce( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n\n The applied function is provided the following arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - indices: current array element indices.\n - arr: input array.\n\n Parameters\n ----------\n arr: ArrayLikeObject\n Input array of arrays.\n\n initial: ArrayLikeObject\n Initial values. Must have a length equal to the size of the outermost\n input array dimension.\n\n reducer: Function\n Function to apply.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Array\n Accumulation results.\n\n Examples\n --------\n > var f = naryFunction( base.add, 2 );\n > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n > var out = reduce2d( arr, [ 0, 0 ], f )\n [ 6, 15 ]\n\n See Also\n --------\n map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > reduceAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n\n When invoked, the reduction function is provided four arguments:\n\n - accumulator: accumulated value.\n - value: array element.\n - index: element index.\n - arr: input array.\n\n If provided an empty array, the function returns the initial value.\n\n When provided an ndarray, the function performs a reduction over the entire\n input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n single-dimension).\n\n Parameters\n ----------\n arr: ArrayLikeObject|ndarray\n Input array.\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n reducer: Function\n Function to invoke for each element in the input array.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n out: any\n Accumulated result.\n\n Examples\n --------\n // array-like object:\n > var f = naryFunction( base.add, 2 );\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n > var out = reduceRight( arr, 0.0, f )\n 21.0\n\n // ndarray:\n > arr = array( arr, { 'shape': [ 2, 3 ] } );\n > out = reduceRight( arr, 0.0, f )\n 21.0\n\n See Also\n --------\n forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n\n When invoked, `reducer` is provided a maximum of five arguments:\n\n - accumulator: accumulated value.\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If\n `reducer` accepts three arguments, `reducer` is provided:\n\n - accumulator\n - value\n - next\n\n If `reducer` accepts four arguments, `reducer` is provided:\n\n - accumulator\n - value\n - index\n - next\n\n For every other `reducer` signature, `reducer` is provided all five\n arguments.\n\n The `next` callback accepts two arguments:\n\n - error: error argument.\n - accumulator: accumulated value.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n If provided an empty collection, the function invokes the `done` callback\n with the `initial` value as the second argument.\n\n The function does not skip `undefined` elements.\n\n When processing collection elements concurrently, *beware* of race\n conditions when updating an accumulator. This is especially true when an\n accumulator is a primitive (e.g., a number). In general, prefer object\n accumulators.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n initial: any\n Accumulator value used in the first invocation of the reduction\n function.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n reducer: Function\n The function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, fcn, done )\n 3000\n 2500\n 1000\n 6500\n\n // Limit number of concurrent invocations:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 2500\n 3000\n 1000\n 6500\n\n // Process concurrently:\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var opts = { 'series': false };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > reduceRightAsync( arr, acc, opts, fcn, done )\n 1000\n 2500\n 3000\n 6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: true.\n\n options.thisArg: any (optional)\n Execution context.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which invokes a function for each element in a collection.\n\n Examples\n --------\n > function fcn( acc, value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... acc.sum += value;\n ... next( null, acc );\n ... }\n ... };\n > var opts = { 'series': false };\n > var f = reduceRightAsync.factory( opts, fcn );\n > function done( error, acc ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( acc.sum );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > var acc = { 'sum': 0 };\n > f( arr, acc, done )\n 1000\n 2500\n 3000\n 6500\n > acc = { 'sum': 0 };\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, acc, done )\n 1000\n 1500\n 2000\n 4500\n\n See Also\n --------\n forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n\n A duration string is a string containing a sequence of time units. A time\n unit is a nonnegative integer followed by a unit identifier. The following\n unit identifiers are supported:\n\n - d: days.\n - h: hours.\n - m: minutes.\n - s: seconds.\n - ms: milliseconds.\n\n For example, the string `1m3s10ms` is a duration string containing three\n time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n The string `60m` is a duration string containing a single time unit: `60m`\n (60 minutes). Time units must be supplied in descending order of magnitude\n (i.e., days, hours, minutes, seconds, milliseconds).\n\n Duration strings are case insensitive. For example, the string `1M3S10MS` is\n equivalent to `1m3s10ms`.\n\n The regular expression captures the following groups:\n\n 1. The days component.\n 2. The hours component.\n 3. The minutes component.\n 4. The seconds component.\n 5. The milliseconds component.\n\n Returns\n -------\n re: RegExp: Regular expression\n Regular expression to match a duration string.\n\n Examples\n --------\n > var RE = reDurationString();\n > var parts = RE.exec( '3d2ms' )\n [...]\n > parts = RE.exec( '4h3m20s' )\n [...]\n\n\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n\n Examples\n --------\n > var bool = reDurationString.REGEXP.test( '3d2ms' )\n true\n > bool = reDurationString.REGEXP.test( 'foo' )\n false","reEOL":"\nreEOL( [options] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to create a capture group for the match.\n Default: false.\n\n Returns\n -------\n regexp: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_EOL = reEOL();\n > var bool = RE_EOL.test( '\\n' )\n true\n > bool = RE_EOL.test( '\\r\\n' )\n true\n > bool = RE_EOL.test( '\\\\r\\\\n' )\n false\n\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false\n\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var bool = reEOL.REGEXP.test( 'abc' )\n false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n Examples\n --------\n > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n\n Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtendedLengthPath();\n > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = 'C:\\\\foo\\\\bar';\n > bool = RE.test( path )\n false\n > path = '/c/foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n\n\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n\n Examples\n --------\n > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n false","reExtname":"\nreExtname( [platform] )\n Returns a regular expression to capture a filename extension.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtname()\n \n > var RE_POSIX = reExtname( 'posix' );\n > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > var RE_WIN32 = reExtname( 'win32' );\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n \n\n\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n\n Examples\n --------\n > var RE = reExtname.REGEXP\n ","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnamePosix();\n > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n ''\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '.' )[ 1 ]\n ''\n > ext = RE.exec( './' )[ 1 ]\n ''\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n\n Examples\n --------\n > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reExtnameWindows();\n > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n ''\n > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n '.pdf'\n > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n ''\n > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n '.'\n > ext = RE.exec( 'index.js' )[ 1 ]\n '.js'\n > ext = RE.exec( '' )[ 1 ]\n ''\n\n\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n\n Examples\n --------\n > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n '.js'\n\n See Also\n --------\n reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n Regular expression to split a filename.\n\n The regular expression is platform-dependent. If the current process is\n running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n `*.REGEXP_POSIX`.\n\n Parameters\n ----------\n platform: string (optional)\n Path platform (either `posix` or `win32`).\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilename()\n \n > var RE_POSIX = reFilename( 'posix' );\n > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n \n > var RE_WIN32 = reFilename( 'win32' );\n > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n \n > var str = RE.toString();\n > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n true\n\n\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n \n\n\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n\n Examples\n --------\n > var RE = reFilename.REGEXP\n ","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = '/foo/bar/index.js';\n > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n Examples\n --------\n > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n\n When executed, the regular expression splits a POSIX filename into the\n following parts:\n\n - input value\n - root\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenamePosix();\n > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n > parts = RE.exec( 'foo/file.pdf' ).slice()\n [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '/foo/bar/file' ).slice()\n [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n\n Examples\n --------\n > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n\n When executed, the regular expression splits a Windows filename into the\n following parts:\n\n - input value\n - device\n - slash\n - dirname\n - basename\n - extname\n\n When executed against dotfile filenames (e.g., `.gitignore`), the regular\n expression does not capture the basename as a filename extension.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reFilenameWindows();\n > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n > parts = RE.exec( 'index.js' ).slice()\n [ 'index.js', '', '', '', 'index.js', '.js' ]\n > parts = RE.exec( '.' ).slice()\n [ '.', '', '', '', '.', '' ]\n > parts = RE.exec( './' ).slice()\n [ './', '', ..., '.', '' ]\n > parts = RE.exec( '' ).slice()\n [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n\n Examples\n --------\n > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n See Also\n --------\n reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n Parses a regular expression string and returns a new regular expression.\n\n Provided strings should be properly escaped.\n\n If unable to parse a string as a regular expression, the function returns\n `null`.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: RegExp|null\n Regular expression or null.\n\n Examples\n --------\n > var re = reFromString( '/beep/' )\n /beep/\n > re = reFromString( '/beep' )\n null\n\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_FUNCTION_NAME = reFunctionName();\n > function beep() { return 'boop'; };\n > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n 'beep'\n > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n ''\n\n\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n\n Examples\n --------\n > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n 'sqrt'\n\n See Also\n --------\n functionName","regexp2json":"\nregexp2json( re )\n Returns a JSON representation of a regular expression.\n\n Parameters\n ----------\n re: RegExp\n Regular expression to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n \n out.type: string\n Value type. The assigned value is always 'RegExp'.\n \n out.pattern: string\n Regular expression pattern.\n \n out.flags: string\n Regular expression flags.\n\n Examples\n --------\n > var json = regexp2json( /ab+c/ )\n {...}\n\n See Also\n --------\n reviveRegExp \n","reim":"\nreim( z )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex128\n Complex number.\n\n Returns\n -------\n out: Float64Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex128( 5.0, 3.0 );\n > var out = reim( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imag, real\n","reimf":"\nreimf( z )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n\n Parameters\n ----------\n z: Complex64\n Complex number.\n\n Returns\n -------\n out: Float32Array\n Array containing the real and imaginary components, respectively.\n\n Examples\n --------\n > var z = new Complex64( 5.0, 3.0 );\n > var out = reimf( z )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n\n Only those arguments in which the predicate function returns a falsy value\n are applied to a provided function.\n\n The predicate function is provided the following arguments:\n\n - value: argument value.\n - index: argument index.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n predicate: Function\n Predicate function.\n\n thisArg: any (optional)\n Input function context.\n\n Returns\n -------\n out: Function\n Function wrapper.\n\n Examples\n --------\n > function foo( a, b ) { return [ a, b ]; };\n > function predicate( v ) { return ( v === 2 ); };\n > var bar = rejectArguments( foo, predicate );\n > var out = bar( 1, 2, 3 )\n [ 1, 3 ]\n\n See Also\n --------\n filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n Removes the first character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to return. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeFirst( 'beep' )\n 'eep'\n > out = removeFirst( 'Boop' )\n 'oop'\n > out = removeFirst( 'foo bar', 4 )\n 'bar'\n\n See Also\n --------\n removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n Removes the last character(s) of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer (optional)\n Number of characters to remove. Default: 1.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to remove. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Updated string.\n\n Examples\n --------\n > var out = removeLast( 'beep' )\n 'bee'\n > out = removeLast( 'Boop' )\n 'Boo'\n > out = removeLast( 'foo bar', 4 )\n 'foo'\n\n See Also\n --------\n removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n Removes punctuation characters from a `string`.\n\n The function removes the following characters:\n\n - Apostrophe: `\n - Braces : { }\n - Brackets: [ ]\n - Colon: :\n - Comma: ,\n - Exclamation Mark: !\n - Fraction Slash: /\n - Guillemets: < >\n - Parentheses: ( )\n - Period: .\n - Semicolon: ;\n - Tilde: ~\n - Vertical Bar: |\n - Question Mark: ?\n - Quotation Marks: ' \"\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with punctuation characters removed.\n\n Examples\n --------\n > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n > var out = removePunctuation( str )\n 'Sun Tzu said A leader leads by example not by force'\n\n > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n > out = removePunctuation( str )\n 'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String with BOM removed.\n\n Examples\n --------\n > var out = removeUTF8BOM( '\\ufeffbeep' )\n 'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n Removes all occurrences of the given words from a `string`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n words: Array\n Array of words to be removed.\n\n ignoreCase: boolean (optional)\n Boolean indicating whether to perform a case-insensitive operation.\n Default: `false`.\n\n Returns\n -------\n out: string\n String with words removed.\n\n Examples\n --------\n > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n 'beep Foo bar'\n\n // Case-insensitive:\n > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n 'beep bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n Asynchronously renames a file.\n\n The old path can specify a directory. In this case, the new path must either\n not exist, or it must specify an empty directory.\n\n The old pathname should not name an ancestor directory of the new pathname.\n\n If the old path points to the pathname of a file that is not a directory,\n the new path should not point to the pathname of a directory.\n\n Write access permission is required for both the directory containing the\n old path and the directory containing the new path.\n\n If the link named by the new path exists, the new path is removed and the\n old path is renamed to the new path. The link named by the new path will\n remain visible to other threads throughout the renaming operation and refer\n to either the file referred to by the new path or to the file referred to by\n the old path before the operation began.\n\n If the old path and the new path resolve to either the same existing\n directory entry or to different directory entries for the same existing\n file, no action is taken, and no error is returned.\n\n If the old path points to a pathname of a symbolic link, the symbolic link\n is renamed. If the new path points to a pathname of a symbolic link, the\n symbolic link is removed.\n\n If a link named by the new path exists and the file's link count becomes 0\n when it is removed and no process has the file open, the space occupied by\n the file is freed and the file is no longer accessible. If one or more\n processes have the file open when the last link is removed, the link is\n removed before the function returns, but the removal of file contents is\n postponed until all references to the file are closed.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n clbk: Function\n Callback to invoke upon renaming a file.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n Synchronously renames a file.\n\n Parameters\n ----------\n oldPath: string|Buffer\n Old path.\n\n newPath: string|Buffer\n New path.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n See Also\n --------\n exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reNativeFunction();\n > var bool = RE.test( Date.toString() )\n true\n > bool = RE.test( (function noop() {}).toString() )\n false\n\n\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n\n Examples\n --------\n > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n true\n > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n false\n\n See Also\n --------\n reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n Returns a function that invokes a provided function with reordered\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n indices: Array\n Argument indices.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reordered arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n > var out = bar( 1, 2, 3 )\n [ 3, 1, 2 ]\n\n See Also\n --------\n maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n Repeats a string `n` times and returns the concatenated result.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of repetitions.\n\n Returns\n -------\n out: string\n Repeated string.\n\n Examples\n --------\n > var out = repeat( 'a', 5 )\n 'aaaaa'\n > out = repeat( '', 100 )\n ''\n > out = repeat( 'beep', 0 )\n ''\n\n See Also\n --------\n pad\n","replace":"\nreplace( str, search, newval )\n Replaces search occurrences with a replacement string.\n\n When provided a string as the search value, the function replaces *all*\n occurrences. To remove only the first match, use a regular expression.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string|RegExp\n Search expression.\n\n newval: string|Function\n Replacement value or function.\n\n Returns\n -------\n out: string\n String containing replacement(s).\n\n Examples\n --------\n // Standard usage:\n > var out = replace( 'beep', 'e', 'o' )\n 'boop'\n\n // Replacer function:\n > function replacer( match, p1 ) { return '/'+p1+'/'; };\n > var str = 'Oranges and lemons';\n > out = replace( str, /([^\\s]+)/gi, replacer )\n '/Oranges/ /and/ /lemons/'\n\n // Replace only first match:\n > out = replace( 'beep', /e/, 'o' )\n 'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n \n replacement: string\n Replacement string.\n\n Returns\n -------\n out: string\n Output string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = replaceBefore( str, ' ', 'foo' )\n 'foo boop'\n > out = replaceBefore( str, 'o', 'foo' )\n 'foooop'\n\n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n\n Regular expression strings should be escaped.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reRegExp();\n > var bool = RE.test( '/^beep$/' )\n true\n > bool = RE.test( '/boop' )\n false\n\n // Escape regular expression strings:\n > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n false\n > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n true\n\n\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n\n Examples\n --------\n > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n true\n > bool = reRegExp.REGEXP.test( '/boop' )\n false\n\n See Also\n --------\n reFromString","rescape":"\nrescape( str )\n Escapes a regular expression string.\n\n Parameters\n ----------\n str: string\n Regular expression string.\n\n Returns\n -------\n out: string\n Escaped string.\n\n Examples\n --------\n > var str = rescape( '[A-Z]*' )\n '\\[A\\-Z\\]\\*'\n\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n\n Returns\n -------\n out: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE_SEMVER = reSemVer()\n \n > var bool = RE_SEMVER.test( '1.0.0' )\n true\n > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n true\n > bool = RE_SEMVER.test( 'abc' )\n false\n > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n true\n\n\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n\n Examples\n --------\n > var bool = reSemVer.REGEXP.test( '1.0.0' )\n true\n > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n false\n\n\n See Also\n --------\n isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n Asynchronously resolves a path by walking parent directories.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n Synchronously resolves a path by walking parent directories.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > var out = resolveParentPath.sync( 'package.json' );\n\n See Also\n --------\n resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n\n When invoked, the predicate function is provided two arguments:\n\n - path: a resolved path.\n - next: a callback to be invoked after processing a resolved path.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided predicate function calls the `next` callback with a truthy\n `error` argument, the function suspends execution and immediately calls the\n `done` callback for subsequent `error` handling.\n\n The function immediately returns upon encountering a non-falsy `result`\n value and calls the `done` callback with `null` as the first argument and\n the resolved path as the second argument.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n clbk: Function\n Callback to invoke after resolving a path.\n\n Examples\n --------\n > function predicate( path, next ) {\n ... setTimeout( onTimeout, path );\n ... function onTimeout() {\n ... console.log( path );\n ... next( null, false );\n ... }\n ... };\n > function onPath( error, path ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... } else {\n ... console.log( path );\n ... }\n ... };\n > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n\n The predicate function is provided one argument:\n\n - path: a resolved path.\n\n The function immediately returns upon encountering a truthy return value.\n\n If unable to resolve a path, the function returns `null` as the path result.\n\n Parameters\n ----------\n path: string\n Path to resolve.\n\n options: Object (optional)\n Options.\n\n options.dir: string (optional)\n Base directory from which to search. Default: current working directory.\n\n predicate: Function\n The test function to invoke for each resolved path.\n\n Returns\n -------\n out: string|null\n Resolved path.\n\n Examples\n --------\n > function predicate() { return false; };\n > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n See Also\n --------\n resolveParentPath","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUncPath();\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n true\n > path = '\\\\\\\\server\\\\\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\\\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = 'beep boop \\\\\\\\server\\\\share';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server';\n > bool = RE.test( path )\n false\n > path = '\\\\';\n > bool = RE.test( path )\n false\n > path = '';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n > bool = RE.test( path )\n false\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n > bool = RE.test( path )\n false\n > path = '//server/share';\n > bool = RE.test( path )\n false\n > path = '/foo/bar';\n > bool = RE.test( path )\n false\n > path = 'foo/bar';\n > bool = RE.test( path )\n false\n > path = './foo/bar';\n > bool = RE.test( path )\n false\n > path = '/foo/../bar';\n > bool = RE.test( path )\n false\n\n\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n\n Examples\n --------\n > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n > var bool = reUncPath.REGEXP.test( path )\n true\n > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n > bool = reUncPath.REGEXP.test( path )\n true\n\n See Also\n --------\n isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair();\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n\n Examples\n --------\n > var RE = reUtf16SurrogatePair.REGEXP;\n > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n true\n > bool = RE.test( 'abcdef' )\n false\n\n See Also\n --------\n reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate();\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n\n Examples\n --------\n > var RE = reUtf16UnpairedSurrogate.REGEXP;\n > var bool = RE.test( 'abc' )\n false\n > bool = RE.test( '\\uD800' )\n true\n\n See Also\n --------\n reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n\n Parameters\n ----------\n fcn: Function\n Input function.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Function with reversed arguments.\n\n Examples\n --------\n > function foo( a, b, c ) { return [ a, b, c ]; };\n > var bar = reverseArguments( foo );\n > var out = bar( 1, 2, 3 )\n [ 3, 2, 1 ]\n\n See Also\n --------\n maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n Reverses a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n options: Object (optional)\n Options.\n\n options.mode: string (optional)\n Type of characters to reverse. The following modes are supported:\n\n - grapheme: grapheme clusters. Appropriate for strings containing visual\n characters which can span multiple Unicode code points (e.g., emoji).\n - code_point: Unicode code points. Appropriate for strings containing\n visual characters which are comprised of more than one Unicode code\n unit (e.g., ideographic symbols and punctuation and mathematical\n alphanumerics).\n - code_unit': UTF-16 code units. Appropriate for strings containing\n visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n common characters, such as those from the Latin, Greek, and Cyrillic\n alphabets).\n\n Default: 'grapheme'.\n\n Returns\n -------\n out: string\n Reversed string.\n\n Examples\n --------\n > var out = reverseString( 'foo' )\n 'oof'\n > out = reverseString( 'abcdef' )\n 'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or PRNG.\n\n Examples\n --------\n > var str = JSON.stringify( base.random.mt19937 );\n > var r = parseJSON( str, reviveBasePRNG )\n \n\n","reviveBuffer":"\nreviveBuffer( key, value )\n Revives a JSON-serialized Buffer.\n\n The serialization format for a Buffer is an object having the following\n fields:\n\n - type: value type (Buffer).\n - data: buffer data as an array of integers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or Buffer.\n\n Examples\n --------\n > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n > var buf = parseJSON( str, reviveBuffer )\n [ 5, 3 ]\n\n See Also\n --------\n buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n Revives a JSON-serialized complex number.\n\n The serialization format for complex numbers is an object having the\n following fields:\n\n - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n - re: real component (number).\n - im: imaginary component (number).\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex )\n \n\n See Also\n --------\n Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n Revives a JSON-serialized 64-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex64 )\n \n\n See Also\n --------\n Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n Revives a JSON-serialized 128-bit complex number.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or complex number.\n\n Examples\n --------\n > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n > var z = parseJSON( str, reviveComplex128 )\n \n\n See Also\n --------\n Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n Revives a JSON-serialized error object.\n\n The following built-in error types are supported:\n\n - Error\n - URIError\n - ReferenceError\n - SyntaxError\n - RangeError\n - EvalError\n - TypeError\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or error object.\n\n Examples\n --------\n > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n > var err = JSON.parse( str, reviveError )\n \n\n See Also\n --------\n error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n Revives a JSON-serialized regular expression.\n\n The serialization format for a regular expression is an object having the\n following fields:\n\n - type: value type (RegExp).\n - pattern: regular expression pattern.\n - flags: regular expression flags.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or regular expression.\n\n Examples\n --------\n > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n > var v = parseJSON( str, reviveRegExp )\n \n\n See Also\n --------\n regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n Revives a JSON-serialized typed array.\n\n The serialization format for typed array is an object having the following\n fields:\n\n - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n - data: typed array data as an array of numbers.\n\n Parameters\n ----------\n key: string\n Key.\n\n value: any\n Value.\n\n Returns\n -------\n out: any\n Value or typed array.\n\n Examples\n --------\n > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n > var arr = parseJSON( str, reviveTypedArray )\n [ 5.0, 3.0 ]\n\n See Also\n --------\n typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n Returns a regular expression to match a white space character.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.flags: string (optional)\n Regular expression flags. Default: ''.\n\n options.capture: boolean (optional)\n Boolean indicating whether to wrap a regular expression matching a white\n space character with a capture group. Default: false.\n\n Returns\n -------\n re: RegExp\n Regular expression.\n\n Examples\n --------\n > var RE = reWhitespace();\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false\n\n\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP;\n > var bool = RE.test( '\\n' )\n true\n > bool = RE.test( ' ' )\n true\n > bool = RE.test( 'a' )\n false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n\n Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n characters in the Unicode 9.0 character database.\n\n Matches one related white space character without the Unicode character\n property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n of Unicode 3.2).\n\n Examples\n --------\n > var RE = reWhitespace.REGEXP_CAPTURE;\n > var str = 'Duplicate capture';\n > var out = replace( str, RE, '$1$1' )\n 'Duplicate capture'\n\n See Also\n --------\n isWhitespace","rpad":"\nrpad( str, len[, pad] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n\n An output string is not guaranteed to have a length of exactly `len`, but to\n have a length of at least `len`. To generate a padded string having a length\n equal to `len`, post-process a padded string by trimming off excess\n characters.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Minimum string length.\n\n pad: string (optional)\n String used to pad. Default: ' '.\n\n Returns\n -------\n out: string\n Padded string.\n\n Examples\n --------\n > var out = rpad( 'a', 5 )\n 'a '\n > out = rpad( 'beep', 10, 'p' )\n 'beeppppppp'\n > out = rpad( 'beep', 12, 'boop' )\n 'beepboopboop'\n\n See Also\n --------\n lpad, pad\n","rtrim":"\nrtrim( str )\n Trims whitespace from the end of a string.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n ' \\t\\t\\n Beep'\n\n See Also\n --------\n ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n Trims `n` characters from the end of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n n: integer\n Number of characters to trim.\n\n chars: Array|string (optional)\n Characters to trim. Default: whitespace characters.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = rtrimN( ' abc ', 2 )\n ' abc'\n > var out = rtrimN( '!!!abc!!!', 2, '!' )\n '!!!abc!'\n\n See Also\n --------\n ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Maximum safe integer.\n\n Examples\n --------\n > var m = safeintmax( 'float16' )\n 2047\n > m = safeintmax( 'float32' )\n 16777215\n\n See Also\n --------\n safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n\n The following numeric real types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: integer\n Minimum safe integer.\n\n Examples\n --------\n > var m = safeintmin( 'float16' )\n -2047\n > m = safeintmin( 'float32' )\n -16777215\n\n See Also\n --------\n safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n Samples elements from an array-like object.\n\n Parameters\n ----------\n x: ArrayLike\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.size: integer (optional)\n Sample size. By default, the function returns an array having the same\n length as `x`. Specify the `size` option to generate a sample of a\n different size.\n\n options.probs: Array (optional)\n Element probabilities. By default, the probability of sampling an\n element is the same for all elements. To assign elements different\n probabilities, set the `probs` option. The `probs` option must be a\n numeric array consisting of nonnegative values which sum to one. When\n sampling without replacement, note that the `probs` option denotes the\n initial element probabilities which are then updated after each draw.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. If the `replace`\n option is set to `false`, the `size` option cannot be an integer larger\n than the number of elements in `x`. Default: `true`.\n\n Returns\n -------\n out: Array\n Sample.\n\n Examples\n --------\n > var out = sample( 'abc' )\n e.g., [ 'a', 'a', 'b' ]\n > out = sample( [ 3, 6, 9 ] )\n e.g., [ 3, 9, 6 ]\n > var bool = ( out.length === 3 )\n true\n\n > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n e.g., [ 3, 'abc', null, 3, null ]\n\n // Set sample size:\n > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n > out = sample( [ 0, 1 ], { 'size': 20 } )\n e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n // Draw without replacement:\n > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n e.g., [ 6, 1, 5 ]\n > out = sample( [ 0, 1 ], { 'replace': false } )\n e.g., [ 0, 1 ]\n\n // Assigning non-uniform element probabilities:\n > var x = [ 1, 2, 3, 4, 5, 6 ];\n > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n > out = sample( x, { 'probs': probs } )\n e.g., [ 5, 6, 6, 5, 6, 4 ]\n > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n Returns a function to sample elements from an array-like object.\n\n If provided an array-like object `pool`, the returned function will always\n sample from the supplied object.\n\n Parameters\n ----------\n pool: ArrayLike (optional)\n Array-like object from which to sample.\n\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.size: integer (optional)\n Sample size.\n\n options.replace: boolean (optional)\n Boolean indicating whether to sample with replacement. Default: `true`.\n\n options.mutate: boolean (optional)\n Boolean indicating whether to mutate the `pool` when sampling without\n replacement. If a population from which to sample is provided, the\n underlying `pool` remains by default constant for each function\n invocation. To mutate the `pool` by permanently removing observations\n when sampling without replacement, set the `mutate` option to `true`.\n The returned function returns `null` after all population units are\n exhausted. Default: `false`.\n\n Returns\n -------\n fcn: Function\n Function to sample elements from an array-like object.\n\n Examples\n --------\n // Set a seed:\n > var mysample = sample.factory({ 'seed': 232 } );\n > var out = mysample( 'abcdefg' )\n e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n // Provide `pool` and set a seed plus a default sample size:\n > var pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n > out = mysample()\n e.g., [ 6, 4 ]\n > out = mysample()\n e.g., [ 6, 5 ]\n\n // Mutate the `pool`:\n > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n > pool = [ 1, 2, 3, 4, 5, 6 ];\n > mysample = sample.factory( pool, opts );\n > out = mysample()\n e.g., [ 4, 3, 6 ]\n > out = mysample()\n e.g., [ 1, 5, 2 ]\n > out = mysample()\n null\n\n // Override default `size` parameter when invoking created function:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'size': 10 })\n e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n // Sample with and without replacement:\n > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n > out = mysample()\n e.g., [ 1, 1 ]\n > out = mysample({ 'replace': false })\n e.g., [ 0, 1 ] or [ 1, 0 ]\n > out = mysample()\n e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FIN()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_FR()\n [ 'a', 'à', 'â', 'abord', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_GER()\n [ 'a', 'ab', 'aber', 'ach', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_IT()\n [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_POR()\n [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SP()\n [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = SAVOY_STOPWORDS_SWE()\n [ 'aderton', 'adertonde', 'adjö', ... ]\n\n References\n ----------\n - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n .\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n Returns a single-element array containing a provided scalar value.\n\n If `value` is a number and `dtype` is a complex number data type, the\n function returns a complex number array containing a complex number whose\n real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n Returns\n -------\n out: Array|TypedArray\n Output array.\n\n Examples\n --------\n > var x = scalar2array( 1.0 )\n [ 1.0 ]\n\n See Also\n --------\n iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n\n If `value` is a number and `options.dtype` is a complex number data type,\n the function returns a zero-dimensional ndarray containing a complex number\n whose real component equals the provided scalar value and whose imaginary\n component is zero.\n\n Parameters\n ----------\n value: any\n Scalar value.\n\n options: Object (optional)\n Options.\n\n options.dtype: string (optional)\n Data type. If not provided and `value`\n\n - is a number, the default data type is the default real-valued\n floating-point data type.\n - is a boolean, the default data type is the default boolean data type.\n - is a complex number object of a known complex data type, the data type\n is the same as the provided value.\n - is a complex number object of an unknown data type, the default data\n type is the default complex-valued floating-point data type.\n - is any other value type, the default data type is 'generic'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var x = scalar2ndarray( 1.0 )\n \n > var sh = x.shape\n []\n > var dt = x.dtype\n 'float64'\n > var v = x.get()\n 1.0\n\n See Also\n --------\n array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n Computes the dot product of two single-precision floating-point vectors.\n\n If provided at least one input array having more than one dimension, the\n input arrays are broadcasted to a common shape.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function computes the dot product for each pair\n of vectors in `x` and `y` according to the specified dimension index.\n\n The size of the contracted dimension must be the same for both input arrays.\n\n The function resolves the dimension index for which to compute the dot\n product *before* broadcasting.\n\n If provided empty vectors, the dot product is `0`.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and be broadcast-compatible with the first input array.\n\n dim: integer (optional)\n Dimension index for which to compute the dot product. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n out: ndarray\n The dot product. The output array has the same data type as the input\n arrays and has a shape which is determined by broadcasting and excludes\n the contracted dimension.\n\n Examples\n --------\n > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n > var x = array( xbuf );\n > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n > var y = array( ybuf );\n > var z = sdot( x, y )\n [ -5.0 ]\n\n See Also\n --------\n base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var days = 3.14;\n > var secs = days * SECONDS_IN_DAY\n 271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var hrs = 3.14;\n > var secs = hrs * SECONDS_IN_HOUR\n 11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n\n The value is a generalization and does **not** take into account\n inaccuracies arising due to complications with time and dates.\n\n Examples\n --------\n > var mins = 3.14;\n > var secs = mins * SECONDS_IN_MINUTE\n 188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n\n The value is a generalization and does **not** take into account\n inaccuracies due to daylight savings conventions, crossing timezones, or\n other complications with time and dates.\n\n Examples\n --------\n > var wks = 3.14;\n > var secs = wks * SECONDS_IN_WEEK\n 1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n Returns the number of seconds in a month.\n\n By default, the function returns the number of seconds in the current month\n of the current year (according to local time). To determine the number of\n seconds for a particular month and year, provide `month` and `year`\n arguments.\n\n A `month` may be either a month's integer value, three letter abbreviation,\n or full name (case insensitive).\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n month: string|Date|integer (optional)\n Month.\n\n year: integer (optional)\n Year.\n\n Returns\n -------\n out: integer\n Seconds in a month.\n\n Examples\n --------\n > var num = secondsInMonth()\n \n > num = secondsInMonth( 2 )\n \n > num = secondsInMonth( 2, 2016 )\n 2505600\n > num = secondsInMonth( 2, 2017 )\n 2419200\n\n // Other ways to supply month:\n > num = secondsInMonth( 'feb', 2016 )\n 2505600\n > num = secondsInMonth( 'february', 2016 )\n 2505600\n\n See Also\n --------\n secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n\n By default, the function returns the number of seconds in the current year\n (according to local time). To determine the number of seconds for a\n particular year, provide either a year or a `Date` object.\n\n The function's return value is a generalization and does **not** take into\n account inaccuracies due to daylight savings conventions, crossing\n timezones, or other complications with time and dates.\n\n Parameters\n ----------\n value: integer|Date (optional)\n Year or `Date` object.\n\n Returns\n -------\n out: integer\n Number of seconds in a year.\n\n Examples\n --------\n > var num = secondsInYear()\n \n > num = secondsInYear( 2016 )\n 31622400\n > num = secondsInYear( 2017 )\n 31536000\n\n See Also\n --------\n secondsInMonth\n","sentencize":"\nsentencize( str )\n Splits a string into an array of sentences.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: Array\n Array of sentences.\n\n Examples\n --------\n > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello Mrs. Maple, could you call me back?' ]\n\n > out = sentencize( 'Hello World! How are you?' )\n [ 'Hello World!', 'How are you?' ]\n\n See Also\n --------\n tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n Converts a subsequence string to a Slice object.\n\n A subsequence string has the following format:\n\n ::\n\n If an increment is not specified, the default increment is one. An increment\n of zero is not allowed.\n\n The start index is inclusive.\n\n The stop index is exclusive.\n\n Both start and stop indices are optional. If not provided, the start and\n stop indices default to index extremes. Which extremes correspond to which\n index depends on whether the increment is positive or negative.\n\n Both start and stop indices can be negative; in which case, the\n corresponding index is resolved by subtracting the respective value from the\n provided length.\n\n Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n 'end-3:', etc), which supports basic subtraction and division.\n\n The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n exception is when performing a division operation when the increment is less\n than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n user expectations when 'end/d' equals a whole number and slicing from right-\n to-left. The result from a division operation is rounded down to the nearest\n integer value.\n\n In non-strict mode, the resolved slice start is clamped to the slice index\n bounds [0, len).\n\n In non-strict mode, Tte resolved slice end is upper bound clamped to the\n provided length (i.e., one greater than the last possible index).\n\n When the increment is negative, the resolved slice end value may be `null`,\n thus indicating that a non-empty slice should include the first index.\n\n The function ensures that results satisfy the convention that ':n' combined\n with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n When the provided length is zero, the function always returns a slice object\n equivalent to '0:0:'.\n\n Parameters\n ----------\n str: string\n Subsequence string.\n\n len: integer\n Maximum number of elements allowed in the slice.\n\n strict: boolean\n Boolean indicating whether to enforce strict bounds checking.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new seq2slice( '1:10', 10, false );\n > s.start\n 1\n > s.stop\n 10\n > s.step\n 1\n > s = new seq2slice( '2:5:2', 10, false );\n > s.start\n 2\n > s.stop\n 5\n > s.step\n 2\n\n See Also\n --------\n Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n Defines a configurable read-only property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setConfigurableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n Defines a configurable read-only accessor.\n\n Configurable read-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n Defines a configurable property having read-write accessors.\n\n Configurable read-write accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n Defines a configurable write-only accessor.\n\n Configurable write-only accessors are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n Defines a configurable memoized read-only object property.\n\n Configurable read-only properties are enumerable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n Defines a memoized read-only object property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n fcn: Function\n Synchronous function whose return value will be memoized and set as the\n property value.\n\n Examples\n --------\n > var obj = {};\n > function foo() { return 'bar'; };\n > setMemoizedReadOnly( obj, 'foo', foo );\n > obj.foo\n 'bar'\n\n See Also\n --------\n defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n Defines a non-enumerable property.\n\n Non-enumerable properties are writable and configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableProperty( obj, 'foo', 'bar' );\n > obj.foo\n 'bar'\n > objectKeys( obj )\n []\n\n See Also\n --------\n setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n Defines a non-enumerable read-only property.\n\n Non-enumerable read-only properties are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n Defines a non-enumerable read-only accessor.\n\n Non-enumerable read-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n Defines a non-enumerable property having read-write accessors.\n\n Non-enumerable read-write accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n Defines a non-enumerable write-only accessor.\n\n Non-enumerable write-only accessors are non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n Defines a read-only property.\n\n Read-only properties are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n value: any\n Value to set.\n\n Examples\n --------\n > var obj = {};\n > setReadOnly( obj, 'foo', 'bar' );\n > obj.foo = 'boop';\n > obj\n { 'foo': 'bar' }\n\n See Also\n --------\n setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n Defines a read-only accessor.\n\n Read-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n Examples\n --------\n > var obj = {};\n > function getter() { return 'bar'; };\n > setReadOnlyAccessor( obj, 'foo', getter );\n > obj.foo\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n Defines a property having read-write accessors.\n\n Read-write accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n getter: Function\n Get accessor.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var name = 'bar';\n > function getter() { return name + ' foo'; };\n > function setter( v ) { name = v; };\n > setReadWriteAccessor( obj, 'foo', getter, setter );\n > obj.foo\n 'bar foo'\n > obj.foo = 'beep';\n > obj.foo\n 'beep foo'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n Defines a write-only accessor.\n\n Write-only accessors are enumerable and non-configurable.\n\n Parameters\n ----------\n obj: Object\n Object on which to define the property.\n\n prop: string|symbol\n Property name.\n\n setter: Function\n Set accessor.\n\n Examples\n --------\n > var obj = {};\n > var val = '';\n > function setter( v ) { val = v; };\n > setWriteOnlyAccessor( obj, 'foo', setter );\n > obj.foo = 'bar';\n > val\n 'bar'\n\n See Also\n --------\n setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n Returns a shared array buffer having a specified number of bytes.\n\n A shared array buffer behaves similarly to a non-shared array buffer, except\n that a shared array buffer allows creating views of memory shared between\n threads.\n\n Buffer contents are initialized to 0.\n\n If an environment does not support shared array buffers, the function throws\n an error.\n\n Parameters\n ----------\n size: integer\n Number of bytes.\n\n Returns\n -------\n out: SharedArrayBuffer\n A shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 )\n \n\n\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1\n\n\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n\n Examples\n --------\n > SharedArrayBuffer.length\n 1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var buf = new SharedArrayBuffer( 5 );\n > buf.byteLength\n 5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n\n Parameters\n ----------\n start: integer (optional)\n Index at which to start copying buffer contents (inclusive). If\n negative, the index is relative to the end of the buffer.\n\n end: integer (optional)\n Index at which to stop copying buffer contents (exclusive). If negative,\n the index is relative to the end of the buffer.\n\n Returns\n -------\n out: SharedArrayBuffer\n A new shared array buffer whose contents have been copied from the\n calling shared array buffer.\n\n Examples\n --------\n // Assuming an environment supports SharedArrayBuffers...\n > var b1 = new SharedArrayBuffer( 10 );\n > var b2 = b1.slice( 2, 6 );\n > var bool = ( b1 === b2 )\n false\n > b2.byteLength\n 4\n\n See Also\n --------\n Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n Removes and returns the first element of a collection.\n\n The function returns an array with two elements: the shortened collection\n and the removed element.\n\n If the input collection is a typed array whose length is greater than `0`,\n the first return value does not equal the input reference.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the value should be\n array-like.\n\n Returns\n -------\n out: Array\n Updated collection and the removed item.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > var out = shift( arr )\n [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > out = shift( arr )\n [ [ 2.0 ], 1.0 ]\n\n // Array-like object:\n > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n > out = shift( arr )\n [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n See Also\n --------\n pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n Shuffles elements of an array-like object.\n\n Parameters\n ----------\n arr: ArrayLike\n Array-like object to shuffle.\n\n options: Object (optional)\n Options.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n out: ArrayLike\n Shuffled array-like object.\n\n Examples\n --------\n > var data = [ 1, 2, 3 ];\n > var out = shuffle( data )\n e.g., [ 3, 1, 2 ]\n > out = shuffle( data, { 'copy': 'none' } );\n > var bool = ( data === out )\n true\n\n\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n Returns a function to shuffle elements of array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.seed: integer (optional)\n Integer-valued seed.\n\n options.copy: string (optional)\n String indicating whether to return a copy (`deep`,`shallow` or `none`).\n Default: `'shallow'`.\n\n Returns\n -------\n fcn: Function\n Shuffle function.\n\n Examples\n --------\n > var myshuffle = shuffle.factory();\n\n // Set a seed:\n > myshuffle = shuffle.factory({ 'seed': 239 });\n > var arr = [ 0, 1, 2, 3, 4 ];\n > var out = myshuffle( arr )\n e.g., [ 3, 4, 1, 0, 2 ]\n\n // Use a different copy strategy:\n > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n // Created shuffle function mutates input array by default:\n > arr = [ 1, 2, 3, 4, 5, 6 ];\n > out = myshuffle( arr );\n > var bool = ( arr === out )\n true\n // Default option can be overridden:\n > arr = [ 1, 2, 3, 4 ];\n > out = myshuffle( arr, { 'copy': 'shallow' } );\n > bool = ( arr === out )\n false\n\n See Also\n --------\n sample","sizeOf":"\nsizeOf( dtype )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n - complex128: 128-bit complex numbers.\n - complex64: 64-bit complex numbers.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Size (in bytes).\n\n Examples\n --------\n > var s = sizeOf( 'int8' )\n 1\n > s = sizeOf( 'uint32' )\n 4\n\n See Also\n --------\n realmax, typemax\n","Slice":"\nSlice( [stop] )\n Returns a Slice.\n\n Parameters\n ----------\n stop: integer|null|undefined (optional)\n Ending index (exclusive).\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice();\n > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n Returns a Slice.\n\n Parameters\n ----------\n start: integer|null|undefined\n Starting index (inclusive).\n\n stop: integer|null|undefined\n Ending index (exclusive).\n\n step: integer|null|undefined (optional)\n Index increment. A numeric index increment argument should be a non-zero\n integer value. Default: null.\n\n Returns\n -------\n s: Slice\n Slice instance.\n\n Examples\n --------\n > var s = new Slice( 2, 10 );\n > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2\n\n\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10\n\n\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1\n\n\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n\n Returns\n -------\n start: integer|null\n Starting index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.start\n null\n > s = new Slice( 2, 10 );\n > s.start\n 2","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n\n Returns\n -------\n stop: integer|null\n Ending index.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.stop\n 10\n > s = new Slice( 2, 10 );\n > s.stop\n 10","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n\n Returns\n -------\n step: integer|null\n Index increment.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.step\n null\n > s = new Slice( 2, 10 );\n > s.step\n null\n > s = new Slice( 2, 10, 1 );\n > s.step\n 1","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n\n Returns\n -------\n str: string\n Serialized Slice string.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toString()\n 'Slice(null,10,null)'\n > s = new Slice( 2, 10, 1 );\n > s.toString()\n 'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n\n Returns\n -------\n obj: Object\n JSON object.\n\n Examples\n --------\n > var s = new Slice( 10 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ null, 10, null ] }\n > s = new Slice( 2, 10, 1 );\n > s.toJSON()\n { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n See Also\n --------\n ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n Converts a string to snake case.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Snake-cased string.\n\n Examples\n --------\n > var out = snakecase( 'Hello World!' )\n 'hello_world'\n > out = snakecase( 'I am a tiny little teapot' )\n 'i_am_a_tiny_little_teapot'\n\n See Also\n --------\n camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n Tests whether at least `n` elements in a collection are truthy.\n\n The function immediately returns upon finding `n` truthy elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of truthy elements.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n` truthy\n elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > var arr = [ 0, 0, 1, 2, 3 ];\n > var bool = some( arr, 3 )\n true\n\n See Also\n --------\n any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ 1, 2, -3, 4, -1 ];\n > var bool = someBy( arr, 2, negative )\n true\n\n See Also\n --------\n anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000 ];\n > someByAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 3000, 2500, 1000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 2000, 1500, 1000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n The predicate function is provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n The function immediately returns upon finding `n` successful elements.\n\n If provided an empty collection, the function returns `false`.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n predicate: Function\n The test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if a collection contains at least `n`\n successful elements; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var arr = [ -1, 1, -2, 3, 4 ];\n > var bool = someByRight( arr, 2, negative )\n true\n\n See Also\n --------\n anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n\n When invoked, the predicate function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection value.\n\n The actual number of provided arguments depends on function length. If the\n predicate function accepts two arguments, the predicate function is\n provided:\n\n - value\n - next\n\n If the predicate function accepts three arguments, the predicate function is\n provided:\n\n - value\n - index\n - next\n\n For every other predicate function signature, the predicate function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - result: test result.\n\n If a provided function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n The function immediately returns upon receiving `n` non-falsy `result`\n values and calls the `done` callback with `null` as the first argument and\n `true` as the second argument.\n\n If all elements fail, the function calls the `done` callback with `null`\n as the first argument and `false` as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n n: number\n Minimum number of successful elements.\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, predicate, done )\n 1000\n 2500\n 3000\n false\n\n // Limit number of concurrent invocations:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 2500\n 3000\n 1000\n false\n\n // Process sequentially:\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 1000, 2500, 3000 ];\n > someByRightAsync( arr, 2, opts, predicate, done )\n 3000\n 2500\n 1000\n false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n predicate: Function\n The test function to invoke for each element in a collection.\n\n Returns\n -------\n out: Function\n A function which tests each element in a collection.\n\n Examples\n --------\n > function predicate( value, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, false );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = someByRightAsync.factory( opts, predicate );\n > function done( error, bool ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( bool );\n ... };\n > var arr = [ 1000, 2500, 3000 ];\n > f( arr, 2, done )\n 3000\n 2500\n 1000\n false\n > arr = [ 1000, 1500, 2000 ];\n > f( arr, 2, done )\n 2000\n 1500\n 1000\n false\n\n See Also\n --------\n anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object contains at least `n`\n successful properties; otherwise, the function returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n > var bool = someInBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n\n The predicate function is provided three arguments:\n\n - value: object value.\n - key: object key.\n - obj: the input object.\n\n The function immediately returns upon finding `n` successful properties.\n\n If provided an empty object, the function returns `false`.\n\n Parameters\n ----------\n obj: Object\n Input object over which to iterate.\n\n n: number\n Minimum number of successful properties.\n\n predicate: Function\n Test function.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n bool: boolean\n The function returns `true` if an object's own properties satisfy a\n predicate for at least `n` properties; otherwise, the function\n returns `false`.\n\n Examples\n --------\n > function negative( v ) { return ( v < 0 ); };\n > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n > var bool = someOwnBy( obj, 2, negative )\n true\n\n See Also\n --------\n anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n Returns State of the Union (SOTU) addresses.\n\n Each State of the Union address is represented by an object with the\n following fields:\n\n - year: speech year.\n - name: President name.\n - party: the President's political party.\n - text: speech text.\n\n The following political parties are recognized:\n\n - Democratic\n - Republican\n - Democratic-Republican\n - Federalist\n - National Union\n - Whig\n - Whig & Democratic\n - none\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.name: String|Array (optional)\n President name(s).\n\n options.party: String|Array (optional)\n Political party (or parties).\n\n options.year: integer|Array (optional)\n Year(s).\n\n options.range: Array (optional)\n Two-element array specifying a year range.\n\n Returns\n -------\n out: Array\n State of the Union addresses.\n\n Examples\n --------\n > var out = SOTU()\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more Presidents...\n > var opts = { 'name': 'Barack Obama' };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses by one or more political parties...\n > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n // Retrieve addresses from one or more years...\n > opts = { 'year': [ 2008, 2009, 2011 ] };\n > out = SOTU( opts )\n [ {...}, {...}, {...} ]\n\n // Retrieve addresses from a range of consecutive years...\n > opts = { 'range': [ 2008, 2016 ] }\n > out = SOTU( opts )\n [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n\n Returns\n -------\n out: Array\n List of simple American-English words.\n\n Examples\n --------\n > var list = SPACHE_REVISED()\n [ 'a', 'able', 'about', 'above', ... ]\n\n References\n ----------\n - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n 458513.\n - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n .\n - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n School Journal* 57 (1). University of Chicago Press: 36–41.\n .\n - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n .\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n\n Each array element has the following fields:\n\n - id: message id (relative to message group).\n - group: message group.\n - checksum: object containing checksum info.\n - text: message text (including headers).\n\n The message group may be one of the following:\n\n - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n (1400 messages).\n - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n - spam-1: spam e-mails (500 messages).\n - spam-2: spam e-mails collected at a later date (1396 messages).\n\n The checksum object contains the following fields:\n\n - type: checksum type (e.g., MD5).\n - value: checksum value.\n\n Returns\n -------\n out: Array\n Corpus.\n\n Examples\n --------\n > var data = SPAM_ASSASSIN()\n [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n Returns a Sparkline instance.\n\n This constructor is a base Sparkline constructor from which constructors\n tailored to generating particular types of Sparkline graphics should be\n derived.\n\n At a minimum, descendants should implement a private `_render()` method\n which will be automatically invoked by the public `render()` method.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Sparkline data.\n\n options.description: string (optional)\n Sparkline description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n sparkline: Sparkline\n Sparkline instance.\n\n sparkline.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n sparkline.bufferSize\n Data buffer size.\n\n sparkline.description\n Sparkline description.\n\n sparkline.data\n Sparkline data.\n\n sparkline.label\n Data label.\n\n sparkline.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n sparkline.render()\n Renders a sparkline. This method calls `_render()` which must be\n implemented by instances and child classes. The default behavior is\n throw an error.\n\n Examples\n --------\n > var sparkline = new SparklineBase()\n \n\n // Provide sparkline data at instantiation:\n > var data = [ 1, 2, 3 ];\n > sparkline = new SparklineBase( data )\n \n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n > var v = it.next().value\n 1\n > v = it.next().value\n 3\n\n See Also\n --------\n iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n\n The returned iterator skips elements which are undefined.\n\n When invoked, an input function is provided three arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n src: ArrayLikeObject\n Sparse array-like object from which to create the iterator.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n Returns a transform stream which splits streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream.Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = splitStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();\n\n\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n Returns a function for creating transform streams for splitting streamed\n data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n createStream: Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = splitStream.factory( opts );\n > var s = createStream();\n > s.write( 'a\\nb\\nc' );\n > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.sep: string (optional)\n Separator used to split streamed data. A separator may be either a\n regular expression or a string. A separator which is a regular\n expression containing a matching group will result in the separator\n being retained in the output stream. Default: /\\r?\\n/.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.writableObjectMode: boolean (optional)\n Specifies whether the writable side should be in \"objectMode\". Default:\n false.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = splitStream.objectMode();\n > s.write( 'a\\nb\\c' );\n > s.end();\n\n See Also\n --------\n joinStream","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n\n Examples\n --------\n > SQRT_EPS\n 0.14901161193847656e-7\n\n See Also\n --------\n EPS\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n\n Examples\n --------\n > SQRT_HALF\n 0.7071067811865476\n\n See Also\n --------\n LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n\n Examples\n --------\n > SQRT_HALF_PI\n 1.2533141373155003\n\n See Also\n --------\n PI\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n\n Examples\n --------\n > SQRT_PHI\n 1.272019649514069\n\n See Also\n --------\n PHI\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n\n Examples\n --------\n > SQRT_PI\n 1.7724538509055160\n\n See Also\n --------\n PI\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n\n Examples\n --------\n > SQRT_THREE\n 1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n\n Examples\n --------\n > SQRT_TWO\n 1.4142135623730951\n\n See Also\n --------\n LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n\n Examples\n --------\n > SQRT_TWO_PI\n 2.5066282746310007\n\n See Also\n --------\n TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n\n Returns\n -------\n out: Array\n Birth data.\n\n Examples\n --------\n > var data = SSA_US_BIRTHS_2000_2014()\n [ {...}, ... ]\n\n See Also\n --------\n CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n Interchanges two single-precision floating-point vectors.\n\n For multi-dimensional input arrays, the function performs batched\n computation, such that the function interchanges each pair of vectors in `x`\n and `y` according to the specified dimension index.\n\n Both input arrays must have the same shape.\n\n Parameters\n ----------\n x: ndarray\n First input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the second input array.\n\n y: ndarray\n Second input array. Must have a 'float32' data type. Must have at least\n one dimension and must have the same shape as the first input array.\n\n dim: integer (optional)\n Dimension index along which to interchange vectors. Must be a negative\n integer. Negative indices are resolved relative to the last array\n dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n Returns\n -------\n y: ndarray\n The second input array `y`.\n\n Examples\n --------\n > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n > sswap( x, y );\n > x.data\n [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n > y.data\n [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n See Also\n --------\n base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n Stack constructor.\n\n A stack is also referred to as a \"last-in-first-out\" queue.\n\n Returns\n -------\n stack: Object\n Stack data structure.\n\n stack.clear: Function\n Clears the stack.\n\n stack.first: Function\n Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.iterator: Function\n Returns an iterator for iterating over a stack. If an environment\n supports Symbol.iterator, the returned iterator is iterable. Note that,\n in order to prevent confusion arising from stack mutation during\n iteration, a returned iterator **always** iterates over a stack\n \"snapshot\", which is defined as the list of stack elements at the time\n of the method's invocation.\n\n stack.last: Function\n Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n If the stack is empty, the returned value is `undefined`.\n\n stack.length: integer\n Stack length.\n\n stack.pop: Function\n Removes and returns the current \"first-out\" value from the stack. If the\n stack is empty, the returned value is `undefined`.\n\n stack.push: Function\n Adds a value to the stack.\n\n stack.toArray: Function\n Returns an array of stack values.\n\n stack.toJSON: Function\n Serializes a stack as JSON.\n\n Examples\n --------\n > var s = Stack();\n > s.push( 'foo' ).push( 'bar' );\n > s.length\n 2\n > s.pop()\n 'bar'\n > s.length\n 1\n > s.pop()\n 'foo'\n > s.length\n 0\n\n See Also\n --------\n FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n Returns the internal package name associated with a provided standalone\n package name.\n\n Parameters\n ----------\n pkg: string\n Standalone package name.\n\n Returns\n -------\n out: string|null\n Internal package name.\n\n Examples\n --------\n > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n '@stdlib/math/base/special/sin'\n\n See Also\n --------\n alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n\n Abbreviation format: \n\n Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n - A: ace\n - J: jack\n - Q: queen\n - K: king\n\n Suit abbreviations:\n\n - C: clubs\n - D: diamonds\n - H: hearts\n - S: spades\n\n Returns\n -------\n out: Array\n List of cards.\n\n Examples\n --------\n > var list = STANDARD_CARD_DECK()\n [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n Capitalizes the first letter of each word in an input string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n String containing words where each first letter is capitalized.\n\n Examples\n --------\n > var out = startcase( 'beep boop' )\n 'Beep Boop'\n\n See Also\n --------\n lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n Tests if a string starts with the characters of another string.\n\n If provided an empty search string, the function always returns `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n position: integer (optional)\n Position at which to start searching for `search`. If less than `0`, the\n start position is determined relative to the end of the input string.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether a string starts with the characters of\n another string.\n\n Examples\n --------\n > var bool = startsWith( 'Beep', 'Be' )\n true\n > bool = startsWith( 'Beep', 'ep' )\n false\n > bool = startsWith( 'Beep', 'ee', 1 )\n true\n > bool = startsWith( 'Beep', 'ee', -3 )\n true\n > bool = startsWith( 'Beep', '' )\n true\n\n See Also\n --------\n endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n\n Returns\n -------\n out: Array\n List of stop words.\n\n Examples\n --------\n > var list = STOPWORDS_EN()\n [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs( 2, x, 2, y, -1 )\n [ 3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 9.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 25.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 4.0, 1.0, 9.0, 25.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 25.0, 1.0 ]\n\n See Also\n --------\n strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By( x.length, x, 1, y, 1, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By( 2, x, 2, y, -1, clbk )\n [ 9.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n [ 16.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, 4.0, 9.0, 16.0 ]\n\n // Advanced indexing:\n > x = [ -1.0, -2.0, -3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 16.0, 4.0 ]\n\n See Also\n --------\n strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy( x.length, x, 1, y, 1, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy( 2, x, 2, y, -1, clbk )\n [ 6.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.absBy( 2, x1, -2, y1, 1, clbk )\n [ 8.0, 4.0 ]\n > y0\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v * 2.0; };\n > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 2.0, 4.0, 6.0, 8.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, -2.0, 3.0, -4.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 8.0, 4.0 ]\n\n See Also\n --------\n strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.356, ~0.786 ]\n > y0\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n // Advanced indexing:\n > x = [ 1.0, 0.707, 0.866, -0.707 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy( 2, x, 2, y, -1, clbk )\n [ ~1.317, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.567, ~0.962 ]\n > y0\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n // Advanced indexing:\n > x = [ 1.0, 1.5, 2.0, 2.5 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy( 2, x, 2, y, -1, clbk )\n [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~-0.588 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n // Advanced indexing:\n > x = [ -2.5, -1.5, -0.5, 0.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy( x.length, x, 1, y, 1, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy( 2, x, 2, y, -1, clbk )\n [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n [ -Infinity, ~-0.255 ]\n > y0\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n // Advanced indexing:\n > x = [ -5.0, -4.0, -3.0, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n [ ~-0.524, ~-1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~-1.571, ~0.607, ~-0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n [ 0.0, ~-0.607 ]\n > y0\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ 1.0, 4.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -2.0, 5.0 ]\n > z0\n [ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -1.0, 3.0, 6.0, -1.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 5.0, -2.0, 0.0 ]\n\n See Also\n --------\n strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 13.0, 14.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 17.0, 16.0 ]\n > z0\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 12.0, 14.0, 16.0, 18.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 17.0, 16.0 ]\n\n See Also\n --------\n strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n [ 0.0, ~3.142, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~2.094, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n See Also\n --------\n strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n [ ~3.142, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.047, ~1.571 ]\n > y0\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n // Advanced indexing:\n > x = [ 0.0, 0.5, 1.0, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n See Also\n --------\n strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy( 2, x, 2, y, -1, clbk )\n [ ~1.571, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.253, ~-0.524 ]\n > y0\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n See Also\n --------\n strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy( 2, x, 2, y, -1, clbk )\n [ ~1.444, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-1.444, 0.0 ]\n > y0\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.0, 2.0, -2.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n See Also\n --------\n strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy( 2, x, 2, y, -1, clbk )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.896, ~-0.464 ]\n > y0\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -1.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n See Also\n --------\n strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy( 2, x, 2, y, -1, clbk )\n [ Infinity, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.255, ~-0.549 ]\n > y0\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n // Advanced indexing:\n > x = [ 0.0, -0.5, 1.0, -0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n See Also\n --------\n strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, -1.57, -0.5, -1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy( 2, x, 2, y, -1, clbk )\n [ ~1.047, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n [ ~1.571, ~2.177 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.57, 0.5, 1.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By( 2, x, 2, y, -1, clbk )\n [ ~0.998, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n [ ~0.984, ~0.765 ]\n > y0\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n See Also\n --------\n strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By( 2, x, 2, y, -1, clbk )\n [ ~0.05, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n [ ~0.124, ~0.44 ]\n > y0\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n See Also\n --------\n strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By( 2, x, 2, y, -1, clbk )\n [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n [ ~-0.932, ~0.088 ]\n > y0\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By( 2, x, 2, y, -1, clbk )\n [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n [ ~-2.704, ~-0.781 ]\n > y0\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 0.1, 0.25 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n See Also\n --------\n strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy( 2, x, 2, y, -1, clbk )\n [ 1.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n [ 2.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, 1.0, 2.0 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 2.0, 3.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 2.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 3.0, 1.0 ]\n > y0\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 1.0, 2.0, 3.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 3.0, 1.0 ]\n\n See Also\n --------\n base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = [ 1.0, 9.0, -27.0, 81.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 3.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 2.0, 3.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 3.0 ]\n\n See Also\n --------\n base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy( 2, x, 2, y, -1, clbk )\n [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.839, ~-1.0 ]\n > y0\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.785, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~1.571, ~0.524 ]\n > y0\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~1.571, ~0.524 ]\n\n See Also\n --------\n base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n\n The output array contains the following data types:\n\n - binary: binary.\n - bool: boolean values.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - generic: values of any type.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Returns\n -------\n out: Array\n List of strided array data types.\n\n Examples\n --------\n > var out = strided.dataTypes()\n \n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n\n The `N` and stride parameters determine which strided array elements are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Using `N` and stride parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~4.327, ~2.08 ]\n > y0\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n The callback function is provided four arguments:\n\n - value: array element.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Float64Array\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Float64Array\n Destination array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Float64Array\n Destination array.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > function clbk( v ) { return v; };\n > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n See Also\n --------\n strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 1\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 1\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n where\n\n - N: number of indexed elements.\n - dtypeX: data type for `x`.\n - x: strided array.\n - strideX: index increment for `x`.\n - offsetX: starting index for `x`.\n - dtypeY: data type for `y`.\n - y: strided array.\n - strideY: index increment for `y`.\n - offsetY: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, and offsets).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n\n Without offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - ...: additional strided arrays, data types, and associated strides.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The number of parameters is derived from `nargs`, the number of input\n strided arrays is derived from `nin`, and the number of output strided\n arrays is derived from `nout`.\n\n Without offsets, the number of parameters must obey the following relation:\n\n nargs = 3*(nout+nin) + 2\n\n With offsets, the number of parameters must obey the following relation:\n\n nargs = 4*(nout+nin) + 2\n\n With offsets, a strided array function interface has the following\n signature:\n\n f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n where\n\n - N: number of indexed elements.\n - dx: data type for `x`.\n - x: strided array.\n - sx: index increment for `x`.\n - ox: starting index for `x`.\n - dy: data type for `y`.\n - y: strided array.\n - sy: index increment for `y`.\n - oy: starting index for `y`.\n - ...: additional strided arrays and associated data types, strides, and\n offsets.\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n The choice of which strided array function interface to return depends on\n the use case. The former is suitable for typed array views; while the latter\n affords alternative indexing semantics more suitable for n-dimensional\n arrays (ndarrays).\n\n Parameters\n ----------\n fcns: Function|ArrayLikeObject\n List of strided array functions. Without offsets, a strided array\n function should have the following signature:\n\n f( arrays, shape, strides, data, clbk, thisArg )\n\n where\n\n - arrays: array containing strided input and output arrays.\n - shape: array containing a single element, the number of indexed\n elements.\n - strides: array containing the stride lengths for the strided input and\n output arrays.\n - data: strided array function data (e.g., a callback).\n - clbk: callback function.\n - thisArg: callback function execution context.\n\n With offsets, a strided array function should have the following\n signature:\n\n f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n where\n\n - offsets: array containing the starting indices (i.e., index offsets)\n for the strided input and output arrays.\n\n For convenience, a single strided array function may be provided which\n will be invoked whenever the strided array argument data types match a\n sequence of types in `types`. Providing a single strided array function\n is particularly convenient for the case where, regardless of array data\n types, traversing arrays remains the same, but the strided array\n function `data` differs (e.g., callbacks which differ based on the array\n data types).\n\n types: ArrayLikeObject\n One-dimensional list of strided array argument data types.\n\n data: ArrayLikeObject|null\n Strided array function data (e.g., callbacks). If `null`, a returned\n strided array function interface does **not** provide a `data` argument\n to an invoked strided array function.\n\n nargs: integer\n Total number of strided array function interface arguments (including\n data types, strides, offsets, and the callback function).\n\n nin: integer\n Number of input strided arrays.\n\n nout: integer\n Number of output strided arrays.\n\n Returns\n -------\n fcn: Function\n Strided array function interface.\n\n Examples\n --------\n // Define strided array argument data types:\n > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n // Define a list of strided array function data (callbacks):\n > var d = [ base.abs, base.absf ];\n\n // Create a strided array function interface for applying unary callbacks:\n > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n // Create an input strided array:\n > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value:\n > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n > y\n [ 1.0, 2.0, 3.0, 4.0 ]\n\n // Create a strided array function interface supporting offsets:\n > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n // Create an input strided array:\n > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n // Create an output strided array:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n // Compute the element-wise absolute value starting from the third element:\n > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n > y\n [ 0.0, 0.0, 3.0, 4.0 ]\n\n See Also\n --------\n strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -4.0, -2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -2.0, 2.0, -4.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.5, -0.05, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 0.25, -1.0 ]\n > y0\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ -0.05, -1.0, 0.5, 0.25 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 0.25, -1.0 ]\n\n See Also\n --------\n base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -6.0, 3.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -15.0, 4.0 ]\n > z0\n [ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -2.0, 2.0, 9.0, -20.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, 4.0, -15.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 12.0, 33.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 52.0, 28.0 ]\n > z0\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 11.0, 24.0, 39.0, 56.0 ]\n\n // Advanced indexing:\n > x = [ 1.0, 2.0, 3.0, 4.0 ];\n > y = [ 11.0, 12.0, 13.0, 14.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 52.0, 28.0 ]\n\n See Also\n --------\n strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 0.0, 1.1, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.5 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.1, 2.5, 0.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.5 ]\n\n See Also\n --------\n base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ ~0.333, Infinity, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~0.289, 0.5 ]\n > y0\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ Infinity, 0.5, ~0.333, ~0.289 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~0.289, 0.5 ]\n\n See Also\n --------\n base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy( 2, x, 2, y, -1, clbk )\n [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n [ ~-0.544, ~0.002 ]\n > y0\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n // Advanced indexing:\n > x = [ 0.0, 3.14, -3.14, 10.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n [ 3.0, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ ~3.464, 2.0 ]\n > y0\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 0.0, 2.0, 3.0, ~3.464 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, ~3.464, 2.0 ]\n\n See Also\n --------\n strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n\n The `N` and stride parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided six arguments:\n\n - value: array element.\n - idx: iteration index.\n - xi: strided index (offsetX + idx*sx).\n - yi: strided index (offsetY + idx*sy).\n - x: the input array.\n - y: the destination array.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Using `N` and stride parameters:\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n [ ~11.045, 0.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n [ ~7.071, 1.0 ]\n > y0\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n y: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( v ) { return v; };\n > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n // Advanced indexing:\n > x = [ 0.0, 1.0, 122.0, 50.0 ];\n > y = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n [ 0.0, 0.0, ~7.071, 1.0 ]\n\n See Also\n --------\n strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z`.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Using `N` and stride parameters:\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n [ -5.0, 2.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n [ -8.0, -3.0 ]\n > z0\n [ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z` using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dx: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n dy: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Input array.\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n dz: any\n Data type for `z`.\n\n z: ArrayLikeObject\n Destination array.\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n Returns\n -------\n z: ArrayLikeObject\n Input array `z`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var dt = 'float64';\n > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n [ -3.0, -1.0, 0.0, -9.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n [ 0.0, -3.0, -8.0, 0.0 ]\n\n See Also\n --------\n strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n\n The `N` and stride parameters determine which elements in the strided arrays\n are accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n The callback function is provided four arguments:\n\n - values: input array elements.\n - idx: iteration index.\n - indices: strided array indices (offset + idx*stride).\n - arrays: input and output arrays.\n\n If the callback function does not return any value (or equivalently,\n explicitly returns `undefined`), the value is ignored.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Using `N` and stride parameters:\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n [ 4.0, 5.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n [ 8.0, 7.0 ]\n > z0\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the offset parameters support indexing semantics based on starting\n indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n x: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sx: integer\n Index increment for `x`.\n\n ox: integer\n Starting index for `x`.\n\n y: Array|TypedArray|Object\n Input array/collection. If provided an object, the object must be array-\n like (excluding strings and functions).\n\n sy: integer\n Index increment for `y`.\n\n oy: integer\n Starting index for `y`.\n\n z: Array|TypedArray|Object\n Destination array/collection. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n sz: integer\n Index increment for `z`.\n\n oz: integer\n Starting index for `z`.\n\n clbk: Function\n Callback function.\n\n thisArg: any (optional)\n Callback execution context.\n\n Returns\n -------\n z: Array|TypedArray|Object\n Destination array/collection.\n\n Examples\n --------\n // Standard usage:\n > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n > function clbk( values ) { return values; };\n > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n [ 3.0, 5.0, 7.0, 9.0 ]\n\n // Advanced indexing:\n > x = [ 11.0, 12.0, 13.0, 14.0 ];\n > y = [ 8.0, 7.0, 6.0, 5.0 ];\n > z = [ 0.0, 0.0, 0.0, 0.0 ];\n > var oy = y.length - 1;\n > var oz = z.length - 1;\n > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n [ 0.0, 0.0, 8.0, 7.0 ]\n\n See Also\n --------\n strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n\n The `N` and `stride` parameters determine which elements in `x` and `y` are\n accessed at runtime.\n\n Indexing is relative to the first index. To introduce an offset, use typed\n array views.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Using `N` and `stride` parameters:\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n [ -3.0, 1.0, 0.0, 0.0 ]\n\n // Using view offsets:\n > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n [ 4.0, 2.0 ]\n > y0\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n\n While typed array views mandate a view offset based on the underlying\n buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n based on starting indices.\n\n Parameters\n ----------\n N: integer\n Number of indexed elements.\n\n dtypeX: any\n Data type for `x`.\n\n x: ArrayLikeObject\n Input array.\n\n strideX: integer\n Index increment for `x`.\n\n offsetX: integer\n Starting index for `x`.\n\n dtypeY: any\n Data type for `y`.\n\n y: ArrayLikeObject\n Destination array.\n\n strideY: integer\n Index increment for `y`.\n\n offsetY: integer\n Starting index for `y`.\n\n Returns\n -------\n y: ArrayLikeObject\n Input array `y`.\n\n Examples\n --------\n // Standard usage:\n > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n [ 1.0, 2.0, -3.0, 4.0 ]\n\n // Advanced indexing:\n > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n [ 0.0, 0.0, 4.0, 2.0 ]\n\n See Also\n --------\n strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n\n When invoked, an input function is provided four arguments:\n\n - value: iterated value.\n - index: iterated value index.\n - n: iteration count (zero-based).\n - src: source array-like object.\n\n If an environment supports Symbol.iterator, the returned iterator is\n iterable.\n\n If an environment supports Symbol.iterator, the function explicitly does not\n invoke an array's `@@iterator` method, regardless of whether this method is\n defined. To convert an array to an implementation defined iterator, invoke\n this method directly.\n\n Parameters\n ----------\n N: integer\n Number of values to iterate.\n\n src: ArrayLikeObject\n Array-like object from which to create the iterator.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n mapFcn: Function (optional)\n Function to invoke for each iterated value.\n\n thisArg: any (optional)\n Execution context.\n\n Returns\n -------\n iterator: Object\n Iterator.\n\n iterator.next(): Function\n Returns an iterator protocol-compliant object containing the next\n iterated value (if one exists) and a boolean flag indicating whether the\n iterator is finished.\n\n iterator.return( [value] ): Function\n Finishes an iterator and returns a provided value.\n\n Examples\n --------\n > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n > var v = it.next().value\n 4\n > v = it.next().value\n 2\n\n See Also\n --------\n iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n Creates a readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n In binary mode, if an array contains `undefined` values, the stream will\n emit an error. Consider providing a custom serialization function or\n filtering `undefined` values prior to invocation.\n\n If a serialization function fails to return a string or Buffer, the stream\n emits an error.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing the stream.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n stream: ReadableStream\n Readable stream.\n\n Examples\n --------\n > function fcn( chunk ) { console.log( chunk.toString() ); };\n > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream( fcn );\n > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n Returns a function for creating readable streams from array-like objects.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before pausing streaming.\n\n options.sep: string (optional)\n Separator used to join streamed data. This option is only applicable\n when a stream is not in \"objectMode\". Default: '\\n'.\n\n options.serialize: Function (optional)\n Serialization function. The default behavior is to serialize streamed\n values as JSON strings. This option is only applicable when a stream is\n not in \"objectMode\".\n\n Returns\n -------\n fcn: Function\n Function for creating readable streams.\n\n Examples\n --------\n > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n\n In object mode, `null` is a reserved value. If an array contains `null`\n values (e.g., as a means to encode missing values), the stream will\n prematurely end. Consider an alternative encoding or filter `null` values\n prior to invocation.\n\n Parameters\n ----------\n N: integer\n Number of values to stream.\n\n buffer: ArrayLikeObject\n Array-like object from which to create the stream.\n\n stride: integer\n Stride length.\n\n offset: integer\n Starting index.\n\n options: Object (optional)\n Options.\n\n options.encoding: string|null (optional)\n Specifies how Buffer objects should be decoded to strings. Default:\n null.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of objects to store in an internal buffer\n before pausing streaming.\n\n Returns\n -------\n stream: ReadableStream\n Readable stream operating in \"objectMode\".\n\n Examples\n --------\n > function fcn( v ) { console.log( v ); };\n > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n > var o = inspectSinkStream.objectMode( fcn );\n > s.pipe( o );\n\n See Also\n --------\n arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n Allocates a buffer containing a provided string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n encoding: string (optional)\n Character encoding. Default: 'utf8'.\n\n Returns\n -------\n out: Buffer\n Buffer instance.\n\n Examples\n --------\n > var b = string2buffer( 'beep boop' )\n \n > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n > b.toString()\n 'this is a tést'\n\n See Also\n --------\n Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n Converts subscripts to a linear index.\n\n Parameters\n ----------\n shape: ArrayLike\n Array shape.\n\n subscript: ...integer\n Subscripts.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran style). Default: 'row-major'.\n\n options.mode: string|Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If\n equal to 'throw', the function throws an error when a subscript exceeds\n array dimensions. If equal to 'normalize', the function normalizes\n negative subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', the function wraps around subscripts\n exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', the function sets subscripts exceeding array dimensions to\n either `0` (minimum index) or the maximum index along a particular\n dimension. If provided a mode array, each array element specifies the\n mode for a corresponding array dimension. If provided fewer modes than\n dimensions, the function recycles modes using modulo arithmetic.\n Default: [ 'throw' ].\n\n Returns\n -------\n idx: integer\n Linear index.\n\n Examples\n --------\n > var d = [ 3, 3, 3 ];\n > var idx = sub2ind( d, 1, 2, 2 )\n 17\n\n See Also\n --------\n array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n Returns the part of a string after a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n fromIndex: integer (optional)\n Index from which to start the search. Default: `0`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfter( 'Hello World!', 'World' )\n '!'\n > out = substringAfter( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfter( 'Hello World!', 'l', 5 )\n 'd!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n fromIndex: integer (optional)\n Index of last character to be considered beginning of a match.\n Default: `str.length`.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n ' baz'\n > out = substringAfterLast( 'Hello World!', 'Hello ' )\n 'World!'\n > out = substringAfterLast( 'Hello World!', 'o', 5 )\n ' World!'\n\n See Also\n --------\n substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n Returns the part of a string before a specified substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search string.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = substringBefore( str, ' ' )\n 'beep'\n > out = substringBefore( str, 'o' )\n 'beep b'\n\n See Also\n --------\n substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n Returns the part of a string before the last occurrence of a specified\n substring.\n\n Parameters\n ----------\n str: string\n Input string.\n\n search: string\n Search value.\n\n Returns\n -------\n out: string\n Substring.\n\n Examples\n --------\n > var str = 'Beep Boop Beep';\n > var out = substringBeforeLast( str, 'Beep' )\n 'Beep Boop '\n > out = substringBeforeLast( str, 'Boop' )\n 'Beep '\n\n See Also\n --------\n substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on July 10, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n\n Humidity and temperature measurements were collected at 5 second intervals\n over a six hour period on May 9, 2010.\n\n Temperature is in degrees Celsius.\n\n Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n The label '0' denotes normal data, and the label '1' denotes an introduced\n event.\n\n If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n mote was an outdoor sensor, the indoor indicator is '0'.\n\n Returns\n -------\n out: Array\n Sensor data.\n\n Examples\n --------\n > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n [{...}, {...}, ...]\n\n References\n ----------\n - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n International Conference on Intelligent Sensors, Sensor Networks and\n Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n * If you use the data for publication or third party consumption, please\n cite the listed reference.\n\n See Also\n --------\n SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n Returns a symbol.\n\n Unlike conventional constructors, this function does **not** support the\n `new` keyword.\n\n This function is only supported in environments which support symbols.\n\n Parameters\n ----------\n description: string (optional)\n Symbol description which can be used for debugging but not to access the\n symbol itself.\n\n Returns\n -------\n out: symbol\n Symbol.\n\n Examples\n --------\n > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n e.g., \n\n","tabulate":"\ntabulate( collection )\n Generates a frequency table.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulate( collection )\n [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n Generates a frequency table according to an indicator function.\n\n When invoked, the indicator function is provided two arguments:\n\n - value: collection value.\n - index: collection index.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n If provided an empty collection, the function returns an empty array.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection to tabulate. If provided an object, the object must be\n array-like (excluding strings and functions).\n\n options: Object (optional)\n Options.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Array|Array\n Frequency table.\n\n Examples\n --------\n > function indicator( value ) { return value[ 0 ]; };\n > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n > var out = tabulateBy( collection, indicator )\n [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n See Also\n --------\n countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n Generates a frequency table according to an indicator function.\n\n The table is an array of arrays where each sub-array corresponds to a unique\n value in the input collection. Each sub-array is structured as follows:\n\n - 0: unique value.\n - 1: value count.\n - 2: frequency percentage.\n\n When invoked, the indicator function is provided a maximum of four\n arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n - next: a callback to be invoked after processing a collection `value`.\n\n The actual number of provided arguments depends on function length. If the\n indicator function accepts two arguments, the indicator function is\n provided:\n\n - value\n - next\n\n If the indicator function accepts three arguments, the indicator function is\n provided:\n\n - value\n - index\n - next\n\n For every other indicator function signature, the indicator function is\n provided all four arguments.\n\n The `next` callback takes two arguments:\n\n - error: error argument.\n - group: value group.\n\n If an indicator function calls the `next` callback with a truthy `error`\n argument, the function suspends execution and immediately calls the `done`\n callback for subsequent `error` handling.\n\n If provided an empty collection, the function calls the `done` callback with\n an empty array as the second argument.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n The function does not support dynamic collection resizing.\n\n The function does not skip `undefined` elements.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n done: Function\n A callback invoked either upon processing all collection elements or\n upon encountering an error.\n\n Examples\n --------\n // Basic usage:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, indicator, done )\n 750\n 1000\n 2500\n 3000\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Limit number of concurrent invocations:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'limit': 2 };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 2500\n 3000\n 1000\n 750\n [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n // Process sequentially:\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var opts = { 'series': true };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > tabulateByAsync( arr, opts, indicator, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n Returns a function which generates a frequency table according to an\n indicator function.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.limit: integer (optional)\n Maximum number of pending invocations. Default: Infinity.\n\n options.series: boolean (optional)\n Boolean indicating whether to process each collection element\n sequentially. Default: false.\n\n options.thisArg: any (optional)\n Execution context.\n\n indicator: Function\n Indicator function specifying how to categorize a collection element.\n\n Returns\n -------\n out: Function\n A function which generates a frequency table according to an indicator\n function.\n\n Examples\n --------\n > function indicator( value, index, next ) {\n ... setTimeout( onTimeout, value );\n ... function onTimeout() {\n ... console.log( value );\n ... next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n ... }\n ... };\n > var opts = { 'series': true };\n > var f = tabulateByAsync.factory( opts, indicator );\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > var arr = [ 3000, 2500, 1000, 750 ];\n > f( arr, done )\n 3000\n 2500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n > arr = [ 2000, 1500, 1000, 750 ];\n > f( arr, done )\n 2000\n 1500\n 1000\n 750\n [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n See Also\n --------\n countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n Returns a thunk.\n\n Parameters\n ----------\n fcn: Function\n Function to convert to a thunk.\n\n args: ...any (optional)\n Function arguments.\n\n Returns\n -------\n out: Function\n Thunk.\n\n Examples\n --------\n > var fcn = thunk( base.add, 2, 3 );\n > var v = fcn()\n 5\n > v = fcn()\n 5\n\n","tic":"\ntic()\n Returns a high-resolution time.\n\n The returned array has the following format: `[seconds, nanoseconds]`.\n\n Returns\n -------\n out: Array\n High resolution time.\n\n Examples\n --------\n > var t = tic()\n [ , ]\n\n See Also\n --------\n toc\n","timeit":"\ntimeit( code, [options,] clbk )\n Times a snippet.\n\n If the `asynchronous` option is set to `true`, the implementation assumes\n that `before`, `after`, and `code` snippets are all asynchronous.\n Accordingly, these snippets should invoke a `next( [error] )` callback\n once complete. The implementation wraps the snippet within a function\n accepting two arguments: `state` and `next`.\n\n The `state` parameter is simply an empty object which allows the `before`,\n `after`, and `code` snippets to share state.\n\n Notes:\n\n - Snippets always run in strict mode.\n - Always verify results. Doing so prevents the compiler from performing dead\n code elimination and other optimization techniques, which would render\n timing results meaningless.\n - Executed code is not sandboxed and has access to the global state. You are\n strongly advised against timing untrusted code. To time untrusted code,\n do so in an isolated environment (e.g., a separate process with restricted\n access to both global state and the host environment).\n - Wrapping asynchronous code does add overhead, but, in most cases, the\n overhead should be negligible compared to the execution cost of the timed\n snippet.\n - When the `asynchronous` option is `true`, ensure that the main `code`\n snippet is actually asynchronous. If a snippet releases the zalgo, an\n error complaining about exceeding the maximum call stack size is highly\n likely.\n - While many benchmark frameworks calculate various statistics over raw\n timing results (e.g., mean and standard deviation), do not do this.\n Instead, consider the fastest time an approximate lower bound for how fast\n an environment can execute a snippet. Slower times are more likely\n attributable to other processes interfering with timing accuracy rather\n than attributable to variability in JavaScript's speed. In which case, the\n minimum time is most likely the only result of interest. When considering\n all raw timing results, apply common sense rather than statistics.\n\n Parameters\n ----------\n code: string\n Snippet to time.\n\n options: Object (optional)\n Options.\n\n options.before: string (optional)\n Setup code. Default: `''`.\n\n options.after: string (optional)\n Cleanup code. Default: `''`.\n\n options.iterations: integer|null (optional)\n Number of iterations. If `null`, the number of iterations is determined\n by trying successive powers of `10` until the total time is at least\n `0.1` seconds. Default: `1e6`.\n\n options.repeats: integer (optional)\n Number of repeats. Default: `3`.\n\n options.asynchronous: boolean (optional)\n Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n clbk: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > var code = 'var x = Math.pow( Math.random(), 3 );';\n > code += 'if ( x !== x ) {';\n > code += 'throw new Error( \\'Something went wrong.\\' );';\n > code += '}';\n > function done( error, results ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.dir( results );\n ... };\n > timeit( code, done )\n e.g.,\n {\n \"iterations\": 1000000,\n \"repeats\": 3,\n \"min\": [ 0, 135734733 ], // [seconds,nanoseconds]\n \"elapsed\": 0.135734733, // seconds\n \"rate\": 7367311.062526641, // iterations/second\n \"times\": [ // raw timing results\n [ 0, 145641393 ],\n [ 0, 135734733 ],\n [ 0, 140462721 ]\n ]\n }\n\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n\n Returns\n -------\n dir: string\n Directory for temporary files.\n\n Examples\n --------\n > var dir = tmpdir()\n e.g., '/path/to/temporary/files/directory'\n\n See Also\n --------\n configdir, homedir\n","toc":"\ntoc( time )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n\n Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n Parameters\n ----------\n time: Array\n High-resolution time.\n\n Returns\n -------\n out: Array\n High resolution time difference.\n\n Examples\n --------\n > var start = tic();\n > var delta = toc( start )\n [ , ]\n\n See Also\n --------\n tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n Tokenizes a string.\n\n To include whitespace characters (spaces, tabs, line breaks) in the output\n array, set `keepWhitespace` to `true`.\n\n Parameters\n ----------\n str: string\n Input string.\n\n keepWhitespace: boolean (optional)\n Boolean indicating whether whitespace characters should be returned as\n part of the token array. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of tokens.\n\n Examples\n --------\n > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n > out = tokenize( 'Hello World!', true )\n [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n Returns a transform stream.\n\n If a transform function is not provided, the returned stream will be a\n simple pass through stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream.\n\n Examples\n --------\n > var s = transformStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();\n\n\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n Returns a function for creating transform streams.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n createStream( transform[, flush] ): Function\n Function for creating transform streams.\n\n Examples\n --------\n > var opts = { 'highWaterMark': 64 };\n > var createStream = transformStream.factory( opts );\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var s = createStream( fcn );\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n Returns an \"objectMode\" transform stream.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n stream: TransformStream\n Transform stream operating in \"objectMode\".\n\n Examples\n --------\n > var s = transformStream.objectMode();\n > s.write( { 'value': 'a' } );\n > s.write( { 'value': 'b' } );\n > s.write( { 'value': 'c' } );\n > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n Returns a custom transform stream constructor.\n\n If provided `transform` and `flush` options, these methods are bound to the\n constructor prototype.\n\n If not provided a transform function, the returned constructor creates\n simple pass through streams.\n\n The returned constructor accepts the same options as the constructor\n factory, *except* for the `transform` and `flush` options, which are not\n supported.\n\n Any options provided to the constructor *override* options provided to the\n constructor factory.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.transform: Function (optional)\n Callback to invoke upon receiving a new chunk.\n\n options.flush: Function (optional)\n Callback to invoke after receiving all chunks and prior to a stream\n closing.\n\n options.objectMode: boolean (optional)\n Specifies whether a stream should operate in \"objectMode\". Default:\n false.\n\n options.highWaterMark: integer (optional)\n Specifies the maximum number of bytes to store in an internal buffer\n before ceasing to push downstream.\n\n options.allowHalfOpen: boolean (optional)\n Specifies whether a stream should remain open even if one side ends.\n Default: false.\n\n options.decodeStrings: boolean (optional)\n Specifies whether to decode strings into Buffer objects when writing.\n Default: true.\n\n Returns\n -------\n ctor: Function\n Custom transform stream constructor.\n\n Examples\n --------\n > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n > var opts = { 'highWaterMark': 64, 'transform': fcn };\n > var customStream = transformStream.ctor( opts );\n > var s = customStream();\n > s.write( 'a' );\n > s.write( 'b' );\n > s.write( 'c' );\n > s.end();","trim":"\ntrim( str )\n Trims whitespace from the beginning and end of a `string`.\n\n \"Whitespace\" is defined as the following characters:\n\n - \\f\n - \\n\n - \\r\n - \\t\n - \\v\n - \\u0020\n - \\u00a0\n - \\u1680\n - \\u2000-\\u200a\n - \\u2028\n - \\u2029\n - \\u202f\n - \\u205f\n - \\u3000\n - \\ufeff\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Trimmed string.\n\n Examples\n --------\n > var out = trim( ' \\t\\t\\n Beep \\r\\n\\t ' )\n 'Beep'\n\n See Also\n --------\n ltrim, pad, rtrim\n","trues":"\ntrues( shape[, options] )\n Returns an ndarray filled with `true` values and having a specified shape\n and data type.\n\n Parameters\n ----------\n shape: ArrayLikeObject|integer\n Array shape.\n\n options: Object (optional)\n Options.\n\n options.dtype: string|DataType (optional)\n Underlying data type. Must be a boolean or \"generic\" data type. Default:\n 'bool'.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var arr = trues( [ 2, 2 ] )\n [ [ true, true ], [ true, true ] ]\n\n See Also\n --------\n array, ndarray, falses, truesLike\n","truesLike":"\ntruesLike( x[, options] )\n Returns an ndarray filled with `true` values and having the same shape and\n data type as a provided input ndarray.\n\n The function infers the following attributes from the input array:\n\n - shape: array shape.\n - dtype: underlying array data type.\n - order: whether the array order is row-major (C-style) or column-major\n (Fortran-style).\n\n Parameters\n ----------\n x: ndarray\n Input array.\n\n options: Object (optional)\n Options.\n\n options.shape: ArrayLikeObject|integer (optional)\n Array shape. Overrides the input array's inferred shape.\n\n options.dtype: string|DataType (optional)\n Array data type. Must be a boolean or \"generic\" data type. Overrides the\n input array's inferred data type.\n\n options.order: string (optional)\n Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n style)). Overrides the input array's inferred order.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.submode: Array (optional)\n Specifies how to handle subscripts which exceed array dimensions. If a\n mode for a corresponding dimension is equal to 'throw', an ndarray\n instance throws an error when a subscript exceeds array dimensions. If\n equal to 'normalize', an ndarray instance normalizes negative\n subscripts and throws an error when a subscript exceeds array\n dimensions. If equal to 'wrap', an ndarray instance wraps around\n subscripts exceeding array dimensions using modulo arithmetic. If equal\n to 'clamp', an ndarray instance sets a subscript exceeding array\n dimensions to either `0` (minimum index) or the maximum index. If the\n number of modes is fewer than the number of dimensions, the function\n recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n Output array.\n\n Examples\n --------\n > var opts = { 'dtype': 'generic' };\n > var x = ndempty( [ 2, 2 ], opts )\n \n > var y = truesLike( x )\n [ [ true, true ], [ true, true ] ]\n\n See Also\n --------\n array, ndarray, falsesLike, trues\n","truncate":"\ntruncate( str, len[, ending] )\n Truncates a string to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n ending: string (optional)\n Custom ending. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncate( str, 5 )\n 'be...'\n\n > out = truncate( str, 5, '|' )\n 'beep|'\n\n See Also\n --------\n truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n Truncates a string in the middle to a specified length.\n\n Parameters\n ----------\n str: string\n Input string.\n\n len: integer\n Output string length.\n\n seq: string (optional)\n Custom replacement sequence. Default: '...'.\n\n Returns\n -------\n out: string\n Truncated string.\n\n Examples\n --------\n > var str = 'beep boop';\n > var out = truncateMiddle( str, 5 )\n 'b...p'\n\n > out = truncateMiddle( str, 5, '|' )\n 'be|op'\n\n See Also\n --------\n truncate","trycatch":"\ntrycatch( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: any\n Value to return if a function throws an error.\n\n Returns\n -------\n z: any\n Either the return value of `x` or the provided argument `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > var z = trycatch( x, -1.0 )\n \n\n See Also\n --------\n trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts two arguments:\n\n - error: error object.\n - result: function result.\n\n The `done` callback is invoked upon function completion and is provided two\n arguments:\n\n - error: error object.\n - result: either the result of `x` or the provided argument `y`.\n\n If `x` invokes `clbk` with an error argument, the function invokes the\n `done` callback with both the error and the argument `y`.\n\n If `x` does not invoke `clbk` with an error argument, the function invokes\n the `done` callback with a first argument equal to `null` and the function\n `result`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: any\n Value to return if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... // process error...\n ... }\n ... console.log( result );\n ... };\n > trycatchAsync( x, 'boop', done )\n 'boop'\n\n See Also\n --------\n trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n Wraps a function in a try/catch block.\n\n If provided an asynchronous function, the returned function only traps\n errors which occur during the current event loop tick.\n\n If a function throws a literal, the literal is serialized as a string and\n returned as an `Error` object.\n\n Parameters\n ----------\n fcn: Function\n Function to wrap.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n out: Function\n Wrapped function.\n\n Examples\n --------\n > function fcn() { throw new Error( 'beep boop' ); };\n > var f = tryFunction( fcn );\n > var out = f();\n > out.message\n 'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n Wraps `require` in a `try/catch` block.\n\n This function traps and returns any errors encountered when attempting to\n require a module.\n\n Use caution when attempting to resolve a relative path or a local module.\n This function attempts to resolve a module from its current path. Thus, the\n function is unable to resolve anything which is not along its search path.\n For local requires, use an absolute file path.\n\n Parameters\n ----------\n id: string\n Module id.\n\n Returns\n -------\n out: any|Error\n Resolved module or an `Error`.\n\n Examples\n --------\n > var out = tryRequire( '_unknown_module_id_' )\n \n\n","trythen":"\ntrythen( x, y )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n\n The function `y` is provided a single argument:\n\n - error: the error thrown by `x`.\n\n Parameters\n ----------\n x: Function\n Function to try invoking.\n\n y: Function\n Function to invoke if an initial function throws an error.\n\n Returns\n -------\n z: any\n The return value of either `x` or `y`.\n\n Examples\n --------\n > function x() {\n ... if ( base.random.randu() < 0.5 ) {\n ... throw new Error( 'beep' );\n ... }\n ... return 1.0;\n ... };\n > function y() {\n ... return -1.0;\n ... };\n > var z = trythen( x, y )\n \n\n See Also\n --------\n trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n\n A function `x` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the function invokes a `done` callback with\n its first argument as `null` and all other provided arguments.\n\n If the error argument is truthy, the function invokes a function `y`. The\n number of arguments provided to `y` depends on the function's length. If `y`\n is a unary function, `y` is provided a single argument:\n\n - clbk: callback to invoke upon function completion.\n\n Otherwise, `y` is provided two arguments:\n\n - error: the error from `x`.\n - clbk: callback to invoke upon function completion.\n\n The callback function accepts any number of arguments, with the first\n argument reserved for providing an error.\n\n If the error argument is falsy, the `done` callback is invoked with its\n first argument equal to `null` and all other arguments provided by `y`.\n\n If the error argument is truthy, the `done` callback is invoked with only\n the error argument provided by `y`.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n x: Function\n Function to invoke.\n\n y: Function\n Function to invoke if `x` returns an error.\n\n done: Function\n Callback to invoke upon completion.\n\n Examples\n --------\n > function x( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( new Error( 'beep' ) );\n ... }\n ... };\n > function y( clbk ) {\n ... setTimeout( onTimeout, 0 );\n ... function onTimeout() {\n ... clbk( null, 'boop' );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > trythenAsync( x, y, done )\n 'boop'\n\n See Also\n --------\n trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n Computes a one-sample or paired Student's t test.\n\n When no `y` is supplied, the function performs a one-sample t-test for the\n null hypothesis that the data in array or typed array `x` is drawn from a\n normal distribution with mean zero and unknown variance.\n\n When array or typed array `y` is supplied, the function tests whether the\n differences `x - y` come from a normal distribution with mean zero and\n unknown variance via the paired t-test.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n y: Array (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed mean under H0 (or difference in means when `y` is supplied).\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.mean: number\n Sample mean of `x` or `x - y`, respectively.\n\n out.sd: number\n Standard error of the mean.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample t-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ttest( x )\n {\n rejected: false,\n pValue: ~0.722,\n statistic: ~0.357,\n ci: [~-0.333,~0.479],\n // ...\n }\n\n // Paired t-test:\n > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n > x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... y[ i ] = rnorm();\n ... }\n > out = ttest( x, y )\n {\n rejected: false,\n pValue: ~0.191,\n statistic: ~1.315,\n ci: [ ~-0.196, ~0.964 ],\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.1916\n statistic: 1.3148\n df: 99\n 95% confidence interval: [-0.1955,0.9635]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose custom significance level:\n > var arr = [ 2, 4, 3, 1, 0 ];\n > out = ttest( arr, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0474\n statistic: 2.8284\n df: 4\n 99% confidence interval: [-1.2556,5.2556]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n // Test for a mean equal to five:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~3.758, ~6.242 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ttest( arr, { 'alternative': 'less' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is less than 0\n\n pValue: 0.9998\n statistic: 11.1803\n df: 4\n 95% confidence interval: [-Infinity,5.9534]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n > out = ttest( arr, { 'alternative': 'greater' } );\n > table = out.print()\n One-sample t-test\n\n Alternative hypothesis: True mean is greater than 0\n\n pValue: 0.0002\n statistic: 11.1803\n df: 4\n 95% confidence interval: [4.0466,Infinity]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest2\n","ttest2":"\nttest2( x, y[, options] )\n Computes a two-sample Student's t test.\n\n By default, the function performs a two-sample t-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n options.variance: string (optional)\n String indicating if the test should be conducted under the assumption\n that the unknown variances of the normal distributions are `equal` or\n `unequal`. As a default choice, the function carries out the Welch test\n (using the Satterthwaite approximation for the degrees of freedom),\n which does not have the requirement that the variances of the underlying\n distributions are equal. If the equal variances assumption seems\n warranted, set the option to `equal`. Default: `unequal`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.df: number\n Degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Student's sleep data:\n > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n > var out = ttest2( x, y )\n {\n rejected: false,\n pValue: ~0.079,\n statistic: ~-1.861,\n ci: [ ~-3.365, ~0.205 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 95% confidence interval: [-3.3655,0.2055]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ttest2( x, y, { 'alpha': 0.1 } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.0794\n statistic: -1.8608\n 90% confidence interval: [-3.0534,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 10% significance level\n\n // Perform one-sided tests:\n > out = ttest2( x, y, { 'alternative': 'less' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.0397\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-Infinity,-0.1066]\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n > out = ttest2( x, y, { 'alternative': 'greater' } );\n > table = out.print()\n Welch two-sample t-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.9603\n statistic: -1.8608\n df: 17.7765\n 95% confidence interval: [-3.0534,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Run tests with equal variances assumption:\n > x = [ 2, 3, 1, 4 ];\n > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n > out = ttest2( x, y, { 'variance': 'equal' } );\n > table = out.print()\n Two-sample t-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.8848\n statistic: -0.1486\n df: 10\n 95% confidence interval: [-1.9996,1.7496]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 3.0 );\n ... }\n > y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 1.0, 3.0 );\n ... }\n > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n {\n rejected: false,\n pValue: ~0.642,\n statistic: ~-0.466,\n ci: [ ~-0.0455, ~1.646 ],\n // ...\n }\n\n See Also\n --------\n ttest\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n\n Examples\n --------\n > TWO_PI\n 6.283185307179586\n\n See Also\n --------\n PI\n","typedarray":"\ntypedarray( [dtype] )\n Creates a typed array.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray()\n \n > arr = typedarray( 'float32' )\n \n\n\ntypedarray( length[, dtype] )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr = typedarray( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarray( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarray( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = typedarray( buf, 0, 4, 'float32' )\n [ 0.0, 0.0, 0.0, 0.0 ]\n\n See Also\n --------\n Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n Returns a JSON representation of a typed array.\n\n The following typed array types are supported:\n\n - Float64Array\n - Float32Array\n - Float16Array\n - Int32Array\n - Uint32Array\n - Int16Array\n - Uint16Array\n - Int8Array\n - Uint8Array\n - Uint8ClampedArray\n - Complex64Array\n - Complex128Array\n - BooleanArray\n\n The returned JSON object has the following properties:\n\n - type: typed array type.\n - data: typed array data as a generic array.\n\n The implementation supports custom typed arrays and sets the `type` field to\n the closest known typed array type.\n\n Parameters\n ----------\n arr: TypedArray\n Typed array to serialize.\n\n Returns\n -------\n out: Object\n JSON representation.\n\n Examples\n --------\n > var arr = new Float64Array( 2 );\n > arr[ 0 ] = 5.0;\n > arr[ 1 ] = 3.0;\n > var json = typedarray2json( arr )\n { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n See Also\n --------\n reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n Returns a typed array constructor.\n\n The function returns constructors for the following data types:\n\n - float16: half-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float64: double-precision floating-point numbers.\n - complex64: single-precision complex floating-point numbers.\n - complex128: double-precision complex floating-point numbers.\n - bool: boolean values.\n - int16: signed 16-bit integers.\n - int32: signed 32-bit integers.\n - int8: signed 8-bit integers.\n - uint16: unsigned 16-bit integers.\n - uint32: unsigned 32-bit integers.\n - uint8: unsigned 8-bit integers.\n - uint8c: unsigned clamped 8-bit integers.\n\n Parameters\n ----------\n dtype: string\n Data type.\n\n Returns\n -------\n out: Function|null\n Typed array constructor.\n\n Examples\n --------\n > var ctor = typedarrayCtors( 'float64' )\n \n > ctor = typedarrayCtors( 'float' )\n null\n\n See Also\n --------\n arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n\n Returns\n -------\n out: Array\n List of typed array data types.\n\n Examples\n --------\n > var out = typedarrayDataTypes()\n \n\n See Also\n --------\n arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n Memory is **uninitialized**, which means that the contents of a returned\n typed array may contain sensitive contents.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool()\n []\n > arr = typedarraypool( 'float32' )\n []\n\n\ntypedarraypool( length[, dtype] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > arr = typedarraypool( 5, 'int32' )\n \n\n\ntypedarraypool( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n \n\n\ntypedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n \n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []\n\n\ntypedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n \n\n\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n \n\n\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n Returns an uninitialized typed array from a typed array memory pool.\n\n This method shares the same security vulnerabilities mentioned above.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc()\n \n > arr = typedarraypool.malloc( 'float32' )\n typedarraypool.malloc( length[, dtype] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.malloc( 5 )\n \n > arr = typedarraypool.malloc( 5, 'int32' )\n typedarraypool.malloc( typedarray[, dtype] )\n Creates a pooled typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n Creates a pooled typed array from an array-like object.\n\n Parameters\n ----------\n obj: Object\n Array-like object from which to generate a typed array.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr1 = [ 0.5, 0.5, 0.5 ];\n > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n [ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\n Parameters\n ----------\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc()\n []\n > arr = typedarraypool.calloc( 'float32' )\n []typedarraypool.calloc( length[, dtype] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n dtype: string (optional)\n Data type. Default: 'float64'.\n\n Returns\n -------\n out: TypedArray|null\n If the function is unable to allocate a typed array from the typed array\n pool (e.g., due to insufficient memory), the function returns `null`.\n\n Examples\n --------\n > var arr = typedarraypool.calloc( 5 )\n [ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n > arr = typedarraypool.calloc( 5, 'int32' )\n [ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n Frees a typed array or typed array buffer for use in a future allocation.\n\n Parameters\n ----------\n buf: TypedArray|ArrayBuffer\n Typed array or typed array buffer to free.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.free( arr );\n > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n\n Once a high water mark is reached, typed array allocation fails.\n\n Examples\n --------\n > typedarraypool.highWaterMark\n ","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n\n The returned value is the total accumulated value. Hence, anytime a pool\n must allocate a new array buffer (i.e., more memory), the pool increments\n this value.\n\n The only time this value is decremented is when a pool is cleared.\n\n This behavior means that, while allocated buffers which are never freed may,\n in fact, be garbage collected, they continue to count against the high water\n mark limit.\n\n Accordingly, you should *always* free allocated buffers in order to prevent\n the pool from believing that non-freed buffers are continually in use.\n\n Examples\n --------\n > var arr = typedarraypool( 5 )\n \n > typedarraypool.nbytes\n ","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n Creates a typed array pool.\n\n Parameters\n ----------\n options: Object (optional)\n Function options.\n\n options.highWaterMark: integer (optional)\n Maximum total memory (in bytes) which can be allocated.\n\n Returns\n -------\n fcn: Function\n Function for creating typed arrays from a typed array memory pool.\n\n Examples\n --------\n > var pool = typedarraypool.factory();\n > var arr1 = pool( 3, 'float64' )\n \n\n See Also\n --------\n typedarray","typemax":"\ntypemax( dtype )\n Returns the maximum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Maximum value.\n\n Examples\n --------\n > var m = typemax( 'int8' )\n 127\n > m = typemax( 'uint32' )\n 4294967295\n\n See Also\n --------\n realmax, typemin\n","typemin":"\ntypemin( dtype )\n Returns the minimum value of a specified numeric type.\n\n The following numeric types are supported:\n\n - float64: double-precision floating-point numbers.\n - float32: single-precision floating-point numbers.\n - float16: half-precision floating-point numbers.\n - int32: 32-bit two's complement signed integers.\n - uint32: 32-bit unsigned integers.\n - int16: 16-bit two's complement signed integers.\n - uint16: 16-bit unsigned integers.\n - int8: 8-bit two's complement signed integers.\n - uint8: 8-bit unsigned integers.\n - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n Parameters\n ----------\n dtype: string\n Numeric type.\n\n Returns\n -------\n out: number\n Minimum value.\n\n Examples\n --------\n > var m = typemin( 'int8' )\n -128\n > m = typemin( 'uint32' )\n 0\n\n See Also\n --------\n realmin, typemax\n","typeOf":"\ntypeOf( value )\n Determines a value's type.\n\n The following values are not natively provided in older JavaScript engines:\n\n - Map\n - Set\n - WeakMap\n - WeakSet\n - Symbol\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n out: string\n The value's type.\n\n Examples\n --------\n // Built-ins:\n > var t = typeOf( 'a' )\n 'string'\n > t = typeOf( 5 )\n 'number'\n > t = typeOf( NaN )\n 'number'\n > t = typeOf( true )\n 'boolean'\n > t = typeOf( false )\n 'boolean'\n > t = typeOf( null )\n 'null'\n > t = typeOf( undefined )\n 'undefined'\n > t = typeOf( [] )\n 'array'\n > t = typeOf( {} )\n 'object'\n > t = typeOf( function noop() {} )\n 'function'\n > t = typeOf( Symbol( 'beep' ) )\n 'symbol'\n > t = typeOf( /.+/ )\n 'regexp'\n > t = typeOf( new String( 'beep' ) )\n 'string'\n > t = typeOf( new Number( 5 ) )\n 'number'\n > t = typeOf( new Boolean( false ) )\n 'boolean'\n > t = typeOf( new Array() )\n 'array'\n > t = typeOf( new Object() )\n 'object'\n > t = typeOf( new Int8Array( 10 ) )\n 'int8array'\n > t = typeOf( new Uint8Array( 10 ) )\n 'uint8array'\n > t = typeOf( new Uint8ClampedArray( 10 ) )\n 'uint8clampedarray'\n > t = typeOf( new Int16Array( 10 ) )\n 'int16array'\n > t = typeOf( new Uint16Array( 10 ) )\n 'uint16array'\n > t = typeOf( new Int32Array( 10 ) )\n 'int32array'\n > t = typeOf( new Uint32Array( 10 ) )\n 'uint32array'\n > t = typeOf( new Float32Array( 10 ) )\n 'float32array'\n > t = typeOf( new Float64Array( 10 ) )\n 'float64array'\n > t = typeOf( new ArrayBuffer( 10 ) )\n 'arraybuffer'\n > t = typeOf( new Date() )\n 'date'\n > t = typeOf( new RegExp( '.+' ) )\n 'regexp'\n > t = typeOf( new Map() )\n 'map'\n > t = typeOf( new Set() )\n 'set'\n > t = typeOf( new WeakMap() )\n 'weakmap'\n > t = typeOf( new WeakSet() )\n 'weakset'\n > t = typeOf( new Error( 'beep' ) )\n 'error'\n > t = typeOf( new TypeError( 'beep' ) )\n 'typeerror'\n > t = typeOf( new SyntaxError( 'beep' ) )\n 'syntaxerror'\n > t = typeOf( new ReferenceError( 'beep' ) )\n 'referenceerror'\n > t = typeOf( new URIError( 'beep' ) )\n 'urierror'\n > t = typeOf( new RangeError( 'beep' ) )\n 'rangeerror'\n > t = typeOf( new EvalError( 'beep' ) )\n 'evalerror'\n > t = typeOf( Math )\n 'math'\n > t = typeOf( JSON )\n 'json'\n\n // Arguments object:\n > function beep() { return arguments; };\n > t = typeOf( beep() )\n 'arguments'\n\n // Node.js Buffer object:\n > t = typeOf( new Buffer( 10 ) )\n 'buffer'\n\n // Custom constructor:\n > function Person() { return this };\n > t = typeOf( new Person() )\n 'person'\n\n // Anonymous constructor:\n > var Foo = function () { return this; };\n > t = typeOf( new Foo() )\n '' || 'foo'\n\n See Also\n --------\n constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n\n The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n Examples\n --------\n > UINT8_MAX\n 255\n\n See Also\n --------\n INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n\n Examples\n --------\n > UINT8_NUM_BYTES\n 1\n\n See Also\n --------\n INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array()\n \n\n\nUint8Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'\n\n\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n \n\n\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5\n\n\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint8Array.of( 1, 2 )\n [ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8Array.BYTES_PER_ELEMENT\n 1","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8Array.name\n 'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.buffer\n ","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteLength\n 5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.byteOffset\n 0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8Array( 5 );\n > arr.length\n 5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray()\n \n\n\nUint8ClampedArray( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint8ClampedArray( arr1 )\n [ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 4 );\n > var arr = new Uint8ClampedArray( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n \n\n\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5\n\n\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1\n\n\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr = Uint8ClampedArray.of( 1, 2 )\n [ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint8ClampedArray.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint8ClampedArray.name\n 'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.buffer\n ","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteLength\n 5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.byteOffset\n 0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.BYTES_PER_ELEMENT\n 1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( 5 );\n > arr.length\n 5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns an empty array.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint8ClampedArray\n Modified array.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint8ClampedArray\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","Uint8ClampedVector":"\nUint8ClampedVector( [options] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8ClampedVector()\n \n\n\nUint8ClampedVector( length[, options] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray having a\n specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8ClampedVector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint8ClampedVector( obj[, options] )\n Creates a one-dimensional clamped unsigned 8-bit integer ndarray from an\n array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint8ClampedVector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint8ClampedVector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint8ClampedVector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","Uint8Vector":"\nUint8Vector( [options] )\n Returns a one-dimensional unsigned 8-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8Vector()\n \n\n\nUint8Vector( length[, options] )\n Returns a one-dimensional unsigned 8-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint8Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint8Vector( obj[, options] )\n Creates a one-dimensional unsigned 8-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint8Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint8Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint8Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n\n The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n Examples\n --------\n > UINT16_MAX\n 65535\n\n See Also\n --------\n INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n\n Examples\n --------\n > UINT16_NUM_BYTES\n 2\n\n See Also\n --------\n INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array()\n \n\n\nUint16Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint16Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 8 );\n > var arr = new Uint16Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'\n\n\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n \n\n\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10\n\n\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2\n\n\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint16Array.of( 1, 2 )\n [ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint16Array.BYTES_PER_ELEMENT\n 2","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint16Array.name\n 'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.buffer\n ","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteLength\n 10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.byteOffset\n 0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint16Array( 5 );\n > arr.length\n 5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint16Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint16Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint16Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","Uint16Vector":"\nUint16Vector( [options] )\n Returns a one-dimensional unsigned 16-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint16Vector()\n \n\n\nUint16Vector( length[, options] )\n Returns a one-dimensional unsigned 16-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint16Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint16Vector( obj[, options] )\n Creates a one-dimensional unsigned 16-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint16Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint16Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional unsigned 16-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint16Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint8Vector, Uint32Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n\n The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n Examples\n --------\n > UINT32_MAX\n 4294967295\n\n See Also\n --------\n INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n\n Examples\n --------\n > UINT32_NUM_BYTES\n 4\n\n See Also\n --------\n INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array()\n \n\n\nUint32Array( length )\n Returns a typed array having a specified length.\n\n Parameters\n ----------\n length: integer\n Typed array length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 )\n [ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n Creates a typed array from another typed array.\n\n Parameters\n ----------\n typedarray: TypedArray\n Typed array from which to generate another typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( obj )\n Creates a typed array from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate a typed array.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = [ 5.0, 5.0, 5.0 ];\n > var arr2 = new Uint32Array( arr1 )\n [ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n Returns a typed array view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first typed array\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 16 );\n > var arr = new Uint32Array( buf, 0, 4 )\n [ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'\n\n\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n \n\n\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20\n\n\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4\n\n\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2\n\n\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2\n\n\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'\n\n\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14\n\n\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'\n\n\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'\n\n\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n Creates a new typed array from an array-like object or an iterable.\n\n A callback is provided the following arguments:\n\n - value: source value.\n - index: source index.\n\n Parameters\n ----------\n src: ArrayLike|Iterable\n Source of array elements.\n\n map: Function (optional)\n Callback to invoke for each source element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > function mapFcn( v ) { return v * 2; };\n > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n [ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n Creates a new typed array from a variable number of arguments.\n\n Parameters\n ----------\n element0: number\n Array element.\n\n element1: number (optional)\n Array element.\n\n elementN: ...number (optional)\n Array elements.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr = Uint32Array.of( 1, 2 )\n [ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > Uint32Array.BYTES_PER_ELEMENT\n 4","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n\n Examples\n --------\n > Uint32Array.name\n 'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.buffer\n ","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteLength\n 20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.byteOffset\n 0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.BYTES_PER_ELEMENT\n 4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n\n Examples\n --------\n > var arr = new Uint32Array( 5 );\n > arr.length\n 5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n\n Parameters\n ----------\n target: integer\n Target start index position.\n\n start: integer\n Source start index position.\n\n end: integer (optional)\n Source end index position. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > arr.copyWithin( 3, 0, 2 );\n > arr[ 3 ]\n 1\n > arr[ 4 ]\n 2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array key-value pairs.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.entries();\n > it.next().value\n [ 0, 1 ]\n > it.next().value\n [ 1, 2 ]\n > it.next().done\n true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, an array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether all array elements pass.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v <= 1 ); };\n > arr.every( predicate )\n false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n\n Parameters\n ----------\n value: number\n Fill value.\n\n start: integer (optional)\n Start index. If less than zero, the start index is resolved relative to\n the last array element. Default: 0.\n\n end: integer (optional)\n End index (non-inclusive). If less than zero, the end index is resolved\n relative to the last array element. Default: out.length.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > arr.fill( 3 );\n > arr[ 0 ]\n 3\n > arr[ 1 ]\n 3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n If a predicate function does not return a truthy value for any array\n element, the method returns `null`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which filters array elements. If a predicate function\n returns a truthy value, an array element is included in the output\n array; otherwise, an array element is not included in the output array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > var arr2 = arr1.filter( predicate );\n > arr2.length\n 2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `undefined`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n value: number|undefined\n Array element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var v = arr.find( predicate )\n 3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n If a predicate function never returns a truthy value, the method returns\n `-1`.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function predicate( v ) { return ( v > 2 ); };\n > var idx = arr.findIndex( predicate )\n 2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n Invokes a callback for each array element.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n fcn: Function\n Function to invoke for each array element.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 3, 2, 1 ] );\n > var str = ' ';\n > function fcn( v, i ) { str += i + ':' + v + ' '; };\n > arr.forEach( fcn );\n > str\n ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n Returns a boolean indicating whether an array includes a search element.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether an array includes a search element.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var bool = arr.includes( 4 )\n false\n > bool = arr.includes( 3 )\n true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n Returns the index of the first array element strictly equal to a search\n element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: 0.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > var idx = arr.indexOf( 4 )\n -1\n > idx = arr.indexOf( 3 )\n 2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n Serializes an array by joining all array elements as a string.\n\n Parameters\n ----------\n separator: string (optional)\n String delineating array elements. Default: ','.\n\n Returns\n -------\n str: string\n Array serialized as a string.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.join( '|' )\n '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array keys.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.keys();\n > it.next().value\n 0\n > it.next().value\n 1\n > it.next().done\n true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n Returns the index of the last array element strictly equal to a search\n element.\n\n The method iterates from the last array element to the first array element.\n\n If unable to locate a search element, the method returns `-1`.\n\n Parameters\n ----------\n searchElement: number\n Search element.\n\n fromIndex: integer (optional)\n Array index from which to begin searching. If provided a negative value,\n the method resolves the start index relative to the last array element.\n Default: -1.\n\n Returns\n -------\n idx: integer\n Array index.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n > var idx = arr.lastIndexOf( 3 )\n -1\n > idx = arr.lastIndexOf( 0 )\n 3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n Maps each array element to an element in a new typed array.\n\n A provided function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n The returned array has the same data type as the host array.\n\n Parameters\n ----------\n fcn: Function\n Function which maps array elements to elements in the new array.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( v ) { return v * 2; };\n > var arr2 = arr1.map( fcn )\n [ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the first array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the first array element as the first argument and the second array\n element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduce( fcn, 0 )\n 14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n\n The provided function is provided the following arguments:\n\n - acc: accumulated result.\n - value: current array element.\n - index: index of the current array element.\n - arr: array on which the method is invoked.\n\n If provided an initial value, the method invokes a provided function with\n the initial value as the first argument and the last array element as the\n second argument.\n\n If not provided an initial value, the method invokes a provided function\n with the last array element as the first argument and the second-to-last\n array element as the second argument.\n\n Parameters\n ----------\n fcn: Function\n Function to apply.\n\n initialValue: Any (optional)\n Initial accumulation value.\n\n Returns\n -------\n out: Any\n Accumulated result.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > function fcn( acc, v ) { return acc + (v*v); };\n > var v = arr.reduceRight( fcn, 0 )\n 14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n\n This method mutates the array on which the method is invoked.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] )\n \n > arr.reverse()\n [ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n Sets array elements.\n\n Parameters\n ----------\n arr: ArrayLike\n Source array containing array values to set.\n\n offset: integer (optional)\n Array index at which to start writing values. Default: 0.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.set( [ 4, 4 ], 1 );\n > arr[ 1 ]\n 4\n > arr[ 2 ]\n 4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns `null`.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A typed array.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n > var arr2 = arr1.slice( 1 );\n > arr2.length\n 2\n > arr2[ 0 ]\n 2\n > arr2[ 1 ]\n 3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n\n A predicate function is provided the following arguments:\n\n - value: array element.\n - index: array index.\n - arr: array on which the method is invoked.\n\n Parameters\n ----------\n predicate: Function\n Predicate function which tests array elements. If a predicate function\n returns a truthy value, a array element passes; otherwise, an array\n element fails.\n\n thisArg: Any (optional)\n Callback execution context.\n\n Returns\n -------\n bool: boolean\n Boolean indicating whether at least one array element passes.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > function predicate( v ) { return ( v > 1 ); };\n > arr.some( predicate )\n true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n Sorts an array *in-place*.\n\n The comparison function is provided two array elements per invocation: `a`\n and `b`.\n\n The comparison function return value determines the sort order as follows:\n\n - If the comparison function returns a value less than zero, then the method\n sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n - If the comparison function returns a value greater than zero, then the\n method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n `a`).\n\n - If the comparison function returns zero, then the relative order of `a`\n and `b` should remain unchanged.\n\n This method mutates the array on which the method is invoked.\n\n Parameters\n ----------\n compareFunction: Function (optional)\n Function which specifies the sort order. The default sort order is\n ascending order.\n\n Returns\n -------\n out: Uint32Array\n Modified array.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n > arr.sort()\n [ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n\n If the method is unable to resolve indices to a non-empty array subsequence,\n the method returns an empty typed array.\n\n Parameters\n ----------\n begin: integer (optional)\n Start element index (inclusive). If less than zero, the start index is\n resolved relative to the last array element. Default: 0.\n\n end: integer (optional)\n End element index (exclusive). If less than zero, the end index is\n resolved relative to the last array element. Default: arr.length.\n\n Returns\n -------\n out: Uint32Array\n A new typed array view.\n\n Examples\n --------\n > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n > var arr2 = arr1.subarray( 2 )\n [ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n Serializes an array as a locale-specific string.\n\n Parameters\n ----------\n locales: string|Array (optional)\n A BCP 47 language tag, or an array of such tags.\n\n options: Object (optional)\n Options.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toLocaleString()\n '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n\n Returns\n -------\n str: string\n A typed array string representation.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2, 3 ] );\n > arr.toString()\n '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n\n Returns\n -------\n iter: Iterator\n Iterator for iterating over array elements.\n\n Examples\n --------\n > var arr = new Uint32Array( [ 1, 2 ] );\n > it = arr.values();\n > it.next().value\n 1\n > it.next().value\n 2\n > it.next().done\n true\n\n\n See Also\n --------\n ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","Uint32Vector":"\nUint32Vector( [options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray.\n\n Parameters\n ----------\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint32Vector()\n \n\n\nUint32Vector( length[, options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray having a specified\n length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = Uint32Vector( 5 )\n \n > var len = numel( arr )\n 5\n\n\nUint32Vector( obj[, options] )\n Creates a one-dimensional unsigned 32-bit integer ndarray from an array-like\n object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 1, 2, 3 ];\n > var arr = Uint32Vector( v )\n \n > var len = numel( arr )\n 3\n\n\nUint32Vector( buffer[, byteOffset[, length]][, options] )\n Returns a one-dimensional unsigned 32-bit integer ndarray view of an\n ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = Uint32Vector( buf, 0, 4 )\n \n > var len = numel( arr )\n 4\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, vector, ndarray\n","Uint64":"\nUint64( value )\n 64-bit unsigned integer constructor.\n\n Parameters\n ----------\n value: integer|bigint\n Integer value.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > x.toString()\n '5'\n\n\nUint64.name\n Constructor name.\n\n Examples\n --------\n > var str = Uint64.name\n 'Uint64'\n\n\nUint64.from( words )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.from( [ 1234, 5678 ] )\n \n\n\nUint64.of( high, low )\n Creates a new 64-bit unsigned integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.of( 1234, 5678 )\n \n\n\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Uint64.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8\n\n\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.byteLength\n 8\n\n\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234\n\n\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Int64\n","Uint64.name":"\nUint64.name\n Constructor name.\n\n Examples\n --------\n > var str = Uint64.name\n 'Uint64'","Uint64.from":"\nUint64.from( words )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n\n Parameters\n ----------\n words: ArrayLikeObject\n High and low words as 32-bit unsigned integers.\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.from( [ 1234, 5678 ] )\n ","Uint64.of":"\nUint64.of( high, low )\n Creates a new 64-bit unsigned integer from a high and low word.\n\n Parameters\n ----------\n high: integer\n High word (32-bit unsigned integer).\n\n low: integer\n Low word (32-bit unsigned integer).\n\n Returns\n -------\n v: Uint64\n 64-bit unsigned integer.\n\n Examples\n --------\n > var v = Uint64.of( 1234, 5678 )\n ","Uint64.BYTES_PER_ELEMENT":"\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var s = Uint64.BYTES_PER_ELEMENT\n 8","Uint64.prototype.BYTES_PER_ELEMENT":"\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.BYTES_PER_ELEMENT\n 8","Uint64.prototype.byteLength":"\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n\n Returns\n -------\n s: integer\n Size (in bytes) of the underlying value.\n\n Examples\n --------\n > var x = new Uint64( 5 )\n \n > var s = x.byteLength\n 8","Uint64.prototype.hi":"\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n High word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.hi\n 1234","Uint64.prototype.lo":"\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n\n Returns\n -------\n w: integer\n Low word (32-bit unsigned integer).\n\n Examples\n --------\n > var x = Uint64.from( [ 1234, 5678 ] )\n \n > var w = x.lo\n 5678\n\n See Also\n --------\n BigInt, Number, Int64","umask":"\numask( [mask,] [options] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n\n A mask is a set of bits, each of which restricts how its corresponding\n permission is set for newly created files.\n\n On POSIX platforms, each file has a set of attributes that control who can\n read, write, or execute that file. Upon creating a file, file permissions\n must be set to an initial setting. The process mask restricts those\n permission settings.\n\n If the mask contains a bit set to \"1\", the corresponding initial file\n permission is disabled. If the mask contains a bit set to \"0\", the\n corresponding permission is left to be determined by the requesting process\n and the system.\n\n The process mask is thus a filter that removes permissions as a file is\n created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n In octal representation, a mask is a four digit number, e.g., 0077,\n comprised as follows:\n\n - 0: special permissions (setuid, setgid, sticky bit)\n - 0: (u)ser/owner permissions\n - 7: (g)roup permissions\n - 7: (o)thers/non-group permissions\n\n Octal codes correspond to the following permissions:\n\n - 0: read, write, execute\n - 1: read, write\n - 2: read, execute\n - 3: read\n - 4: write, execute\n - 5: write\n - 6: execute\n - 7: no permissions\n\n If provided fewer than four digits, the mask is left-padded with zeros.\n\n Note, however, that only the last three digits (i.e., the file permissions\n digits) of the mask are actually used when the mask is applied.\n\n Permissions can be represented using the following symbolic form:\n\n u=rwx,g=rwx,o=rwx\n\n where\n\n - u: user permissions\n - g: group permissions\n - o: other/non-group permissions\n - r: read\n - w: write\n - x: execute\n\n When setting permissions using symbolic notation, the function accepts a\n mask expression of the form:\n\n []\n\n where \"classes\" may be a combination of\n\n - u: user\n - g: group\n - o: other/non-group\n - a: all\n\n \"symbols\" may be a combination of\n\n - r: read\n - w: write\n - x: execute\n - X: special execute\n - s: setuid/gid on execution\n - t: sticky\n\n and \"operator\" may be one of\n\n - +: enable\n - -: disable\n - =: enable specified and disable unspecified permissions\n\n For example,\n\n - u-w: disable user write permissions\n - u+w: enable user write permissions\n - u=w: enable user write permissions and disable user read and execute\n\n To specify multiple changes, provide a comma-separated list of mask\n expressions. For example,\n\n u+rwx,g-x,o=r\n\n would enable user read, write, and execute permissions, disable group\n execute permissions, enable other read permissions, and disable other\n write and execute permissions.\n\n The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n is the default class if a class is omitted when specifying permissions. For\n example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n Parameters\n ----------\n mask: integer|string (optional)\n Mask or mask expression. If the mask is a string, the mask is assumed to\n be in symbolic notation.\n\n options: Object (optional)\n Options.\n\n options.symbolic: boolean (optional)\n Boolean indicating whether to return the mask using symbolic notation.\n\n Returns\n -------\n mask: integer|string\n Process mask. If provided a mask, the returned value is the previous\n mask; otherwise, the returned value is the current process mask.\n\n Examples\n --------\n > var mask = umask()\n \n > mask = umask( { 'symbolic': true } )\n \n\n","uncapitalize":"\nuncapitalize( str )\n Lowercases the first character of a string.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uncapitalized string.\n\n Examples\n --------\n > var out = uncapitalize( 'Beep' )\n 'beep'\n > out = uncapitalize( 'bOOp' )\n 'bOOp'\n\n See Also\n --------\n capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n Converts the first letter of each object key to lowercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'AA': 1, 'BB': 2 };\n > var out = uncapitalizeKeys( obj )\n { 'aA': 1, 'bB': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurry( addX );\n > var sum = fcn( 2, 3 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( x ) {\n ... return function add( y ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurry( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addX( x ) {\n ... this.x = x;\n ... return addY;\n ... };\n > function addY( y ) {\n ... return this.x + y;\n ... };\n > fcn = uncurry( addX, {} );\n > sum = fcn( 2, 3 )\n 5\n\n See Also\n --------\n curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n\n Provided arguments are applied starting from the right.\n\n Parameters\n ----------\n fcn: Function\n Curried function.\n\n arity: integer (optional)\n Number of parameters.\n\n thisArg: any (optional)\n Evaluation context.\n\n Returns\n -------\n out: Function\n Uncurried function.\n\n Examples\n --------\n > function addX( x ) {\n ... return function addY( y ) {\n ... return x + y;\n ... };\n ... };\n > var fcn = uncurryRight( addX );\n > var sum = fcn( 3, 2 )\n 5\n\n // To enforce a fixed number of parameters, provide an `arity` argument:\n > function add( y ) {\n ... return function add( x ) {\n ... return x + y;\n ... };\n ... };\n > fcn = uncurryRight( add, 2 );\n > sum = fcn( 9 )\n \n\n // To specify an execution context, provide a `thisArg` argument:\n > function addY( y ) {\n ... this.y = y;\n ... return addX;\n ... };\n > function addX( x ) {\n ... return x + this.y;\n ... };\n > fcn = uncurryRight( addY, {} );\n > sum = fcn( 3, 2 )\n 5\n\n See Also\n --------\n curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n\n Examples\n --------\n > UNICODE_MAX\n 1114111\n\n See Also\n --------\n UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n Examples\n --------\n > UNICODE_MAX_BMP\n 65535\n\n See Also\n --------\n UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n Returns a sparkline column chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeColumnChartSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n Returns a sparkline line chart instance.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: LineChart\n Line chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a line chart sparkline.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeLineChartSparkline( data );\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n Returns a Unicode sparkline instance.\n\n The following chart types are supported:\n\n - column: column chart (e.g., ▃▆▂▄▁▅▅).\n - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.infinities: boolean (optional)\n Boolean indicating whether to encode infinite values. Default: false.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n options.type: string (optional)\n Chart type. Default: 'column'.\n\n options.yMax: number|null (optional)\n Maximum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n options.yMin: number|null (optional)\n Minimum value of the y-axis domain. If `null`, the value is computed\n from the data. Default: null.\n\n Returns\n -------\n chart: ColumnChart\n Column chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.infinities\n Indicates whether to encode infinite values.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a column chart sparkline.\n\n chart.type\n Chart type.\n\n chart.yMax\n Maximum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n chart.yMin\n Minimum value of the y-axis domain. If set to `null`, when accessed, the\n returned value is computed from the data.\n\n Examples\n --------\n > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n > var chart = new UnicodeSparkline( data );\n > chart.render()\n '▁█▅▃▆▆▅'\n > chart.type = 'line';\n > chart.render()\n '⡈⠑⠢⠔⠒⠒⠒'\n\n See Also\n --------\n plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n Returns a sparkline tristate chart instance.\n\n In a tristate chart, negative values are encoded as lower blocks, positive\n values are encoded as upper blocks, and values equal to zero are encoded as\n middle lines.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: TristateChart\n Tristate chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore values which are `NaN`.\n\n chart.render()\n Renders a tristate chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n > var chart = new UnicodeTristateChartSparkline( data );\n > chart.render()\n '▄▀──▀▄▄▀'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n Returns a sparkline up/down chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ↑ |\n | -1 | ↓ |\n\n If provided any other value other than 1 or -1, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: UpDownChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1 or -1.\n\n chart.render()\n Renders an up/down chart sparkline.\n\n Examples\n --------\n > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n > var chart = new UnicodeUpDownChartSparkline( data );\n > chart.render()\n '↓↑↑↑↑↓↓↑'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n Returns a sparkline win/loss chart instance.\n\n Glyphs:\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 1 | ╵ |\n | -1 | ╷ |\n | 2 | └ |\n | -2 | ┌ |\n\n If a `2` or `-2` is preceded by a `2` or `-2`,\n\n | Value | Glyph |\n |:-----:|:-----:|\n | 2 | ┴ |\n | -2 | ┬ |\n\n Based on the win/loss analogy,\n\n - 1: win away\n - 2: win at home\n - -1: loss away\n - -2: loss at home\n\n If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n missing value.\n\n The `data` argument takes precedence over the `data` option.\n\n Parameters\n ----------\n data: ArrayLike|ndarray (optional)\n Chart data.\n\n options: Object (optional)\n Options.\n\n options.autoRender: boolean (optional)\n Boolean indicating whether to re-render on a 'change' event. Default:\n false.\n\n options.bufferSize: integer|null (optional)\n Data buffer size. If provided, data is kept in a first-in first-out\n (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n options.data: ArrayLike|ndarray (optional)\n Chart data.\n\n options.description: string (optional)\n Chart description.\n\n options.isDefined: Function (optional)\n An accessor function indicating whether a datum is defined.\n\n options.label: string (optional)\n Data label.\n\n Returns\n -------\n chart: WinLossChart\n Chart instance.\n\n chart.autoRender\n Rendering mode. If `true`, an instance renders on each 'change' event;\n otherwise, rendering must be triggered manually.\n\n chart.bufferSize\n Data buffer size.\n\n chart.description\n Chart description.\n\n chart.data\n Chart data.\n\n chart.label\n Data label.\n\n chart.isDefined( d, i )\n An accessor function which defines whether a datum is defined. This\n accessor is used to define how missing values are encoded. The default\n behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n chart.render()\n Renders a win/loss chart sparkline.\n\n Examples\n --------\n > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n > var chart = new UnicodeWinLossChartSparkline( data );\n > chart.render()\n '┌╵└┴╵╷╷╵'\n\n See Also\n --------\n plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n Asynchronously removes a directory entry.\n\n If a provided path is a symbolic link, the function removes the symbolic\n link named by the path and does not affect any file or directory named by\n the contents of the symbolic link.\n\n Otherwise, the function removes the link named by the provided path and\n decrements the link count of the file referenced by the link.\n\n When a file's link count becomes 0 and no process has the file open, the\n space occupied by the file is freed and the file is no longer accessible.\n\n If one or more processes have the file open when the last link is removed,\n the link is removed before the function returns; however, the removal of\n file contents is postponed until all references to the file are closed.\n\n If the path refers to a socket, FIFO, or device, processes which have the\n object open may continue to use it.\n\n The path argument should *not* be a directory. To remove a directory, use\n rmdir().\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n clbk: Function\n Callback to invoke upon removing an entry.\n\n Examples\n --------\n > function done( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists\n","unlink.sync":"\nunlink.sync( path )\n Synchronously removes a directory entry.\n\n Parameters\n ----------\n path: string|Buffer|integer\n Entry path.\n\n Returns\n -------\n out: Error|null\n Error object or null.\n\n Examples\n --------\n > var out = unlink.sync( './beep/boop.txt' );\n\n See Also\n --------\n exists","unshift":"\nunshift( collection, ...items )\n Adds one or more elements to the beginning of a collection.\n\n If the input collection is a typed array, the output value does not equal\n the input reference and the underlying `ArrayBuffer` may *not* be the same\n as the `ArrayBuffer` belonging to the input view.\n\n For purposes of generality, always treat the output collection as distinct\n from the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n A collection. If the collection is an `Object`, the collection should be\n array-like.\n\n items: ...any\n Items to add.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Updated collection.\n\n Examples\n --------\n // Arrays:\n > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n > arr = unshift( arr, 6.0, 7.0 )\n [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n // Typed arrays:\n > arr = new Float64Array( [ 1.0, 2.0 ] );\n > arr = unshift( arr, 3.0, 4.0 )\n [ 3.0, 4.0, 1.0, 2.0 ]\n\n // Array-like object:\n > arr = { 'length': 1, '0': 1.0 };\n > arr = unshift( arr, 2.0, 3.0 )\n { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n See Also\n --------\n pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n Invokes a function until a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to stop invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i >= 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > until( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n Invokes a function until a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is falsy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > untilAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > untilEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to stop iterating over a\n collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v !== v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > untilEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n Unzips a zipped array (i.e., a nested array of tuples).\n\n Parameters\n ----------\n arr: Array\n Zipped array.\n\n idx: Array (optional)\n Array of indices specifying which tuple elements to unzip.\n\n Returns\n -------\n out: Array\n Array of unzipped arrays.\n\n Examples\n --------\n // Basic usage:\n > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > var out = unzip( arr )\n [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n // Provide indices:\n > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n > out = unzip( arr, [ 0, 2 ] )\n [ [ 1, 2 ], [ 3, 4 ] ]\n\n See Also\n --------\n zip\n","uppercase":"\nuppercase( str )\n Converts a string to uppercase.\n\n Parameters\n ----------\n str: string\n Input string.\n\n Returns\n -------\n out: string\n Uppercase string.\n\n Examples\n --------\n > var out = uppercase( 'bEEp' )\n 'BEEP'\n\n See Also\n --------\n capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n Converts each object key to uppercase.\n\n The function only transforms own properties. Hence, the function does not\n transform inherited properties.\n\n The function shallow copies key values.\n\n Parameters\n ----------\n obj: Object\n Source object.\n\n Returns\n -------\n out: Object\n New object.\n\n Examples\n --------\n > var obj = { 'a': 1, 'b': 2 };\n > var out = uppercaseKeys( obj )\n { 'A': 1, 'B': 2 }\n\n See Also\n --------\n capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n\n Returns\n -------\n out: Array\n List of US state two-letter abbreviations.\n\n Examples\n --------\n > var list = US_STATES_ABBR()\n [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n\n Returns\n -------\n out: Array\n List of US state capitals.\n\n Examples\n --------\n > var list = US_STATES_CAPITALS()\n [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n\n Returns\n -------\n out: Object\n An object mapping US state capitals to state names.\n\n Examples\n --------\n > var out = US_STATES_CAPITALS_NAMES()\n { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n\n Returns\n -------\n out: Array\n List of US state names.\n\n Examples\n --------\n > var list = US_STATES_NAMES()\n [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n See Also\n --------\n US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n\n Returns\n -------\n out: Object\n An object mapping US state names to state capitals.\n\n Examples\n --------\n > var out = US_STATES_NAMES_CAPITALS()\n { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n See Also\n --------\n US_STATES_CAPITALS, US_STATES_NAMES\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n\n The following byte sequences are used to represent a character. The sequence\n depends on the code point:\n\n 0x00000000 - 0x0000007F:\n 0xxxxxxx\n\n 0x00000080 - 0x000007FF:\n 110xxxxx 10xxxxxx\n\n 0x00000800 - 0x0000FFFF:\n 1110xxxx 10xxxxxx 10xxxxxx\n\n 0x00010000 - 0x001FFFFF:\n 11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n The `x` bit positions correspond to code point bits.\n\n Only the shortest possible multi-byte sequence which can represent a code\n point is used.\n\n Parameters\n ----------\n str: string\n UTF-16 encoded string.\n\n Returns\n -------\n out: Array\n Array of integers.\n\n Examples\n --------\n > var str = '☃';\n > var out = utf16ToUTF8Array( str )\n [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n Computes a two-sample F-test for equal variances.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`.\n\n options.ratio: number (optional)\n Positive number denoting the ratio of the two population variances under\n the null hypothesis. Default: `1`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the ratio of variances.\n\n out.nullValue: number\n Assumed ratio of variances under H0.\n\n out.xvar: number\n Sample variance of `x`.\n\n out.yvar: number\n Sample variance of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.dfX: number\n Numerator degrees of freedom.\n\n out.dfY: number\n Denominator degrees of freedom.\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n > var x = [ 610, 610, 550, 590, 565, 570 ];\n > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n > var out = vartest( x, y )\n {\n rejected: false,\n pValue: ~0.399,\n statistic: ~1.976,\n ci: [ ~0.374, ~13.542 ],\n // ...\n }\n\n // Print table output:\n > var table = out.print()\n F test for comparing two variances\n\n Alternative hypothesis: True ratio in variances is not equal to 1\n\n pValue: 0.3992\n statistic: 1.976\n variance of x: 617.5 (df of x: 5)\n variance of y: 312.5 (df of y: 7)\n 95% confidence interval: [0.3739,13.5417]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n See Also\n --------\n bartlettTest\n","vector":"\nvector( [dtype][, options] )\n Returns a one-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = vector()\n \n > var dt = ndarrayDataType( arr )\n 'float64'\n > arr = vector( 'float32' )\n \n > dt = ndarrayDataType( arr )\n 'float32'\n\n\nvector( length[, dtype][, options] )\n Returns a one-dimensional ndarray having a specified length.\n\n Parameters\n ----------\n length: integer\n Number of elements.\n\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var arr = vector( 5 )\n \n > var dt = ndarrayDataType( arr )\n 'float64'\n > var len = numel( arr )\n 5\n > arr = vector( 5, 'float32' )\n \n > dt = ndarrayDataType( arr )\n 'float32'\n > len = numel( arr )\n 5\n\n\nvector( obj[, dtype][, options] )\n Creates a one-dimensional ndarray from an array-like object or iterable.\n\n Parameters\n ----------\n obj: Object\n Array-like object or iterable from which to generate an ndarray.\n\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var v = [ 0.5, 0.5, 0.5 ];\n > var arr = vector( v, 'float32' )\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n > var len = numel( arr )\n 3\n\n\nvector( buffer[, byteOffset[, length]][, dtype][, options] )\n Returns a one-dimensional ndarray view of an ArrayBuffer.\n\n Parameters\n ----------\n buffer: ArrayBuffer\n Underlying ArrayBuffer.\n\n byteOffset: integer (optional)\n Integer byte offset specifying the location of the first indexed\n element. Default: 0.\n\n length: integer (optional)\n View length. If not provided, the view spans from the byteOffset to\n the end of the underlying ArrayBuffer.\n\n dtype: string (optional)\n Underlying data type. Default: 'float64'.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether an array is row-major (C-style) or column-major\n (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies how to handle indices which exceed array dimensions. If equal\n to 'throw', an ndarray instance throws an error when an index exceeds\n array dimensions. If equal to 'normalize', an ndarray instance\n normalizes negative indices and throws an error when an index exceeds\n array dimensions. If equal to 'wrap', an ndarray instance wraps around\n indices exceeding array dimensions using modulo arithmetic. If equal to\n 'clamp', an ndarray instance sets an index exceeding array dimensions\n to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only. Default: false.\n\n Returns\n -------\n out: ndarray\n A one-dimensional ndarray.\n\n Examples\n --------\n > var buf = new ArrayBuffer( 32 );\n > var arr = vector( buf, 0, 4, 'float32' )\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n > var len = numel( arr )\n 4\n\n\nvector.factory( dtype[, options] )\n Returns a function for creating a one-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a one-dimensional ndarray.\n\n Examples\n --------\n > var f = vector.factory( 'float32' );\n > var arr = f()\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, matrix, ndarray\n","vector.factory":"\nvector.factory( dtype[, options] )\n Returns a function for creating a one-dimensional ndarray.\n\n Parameters\n ----------\n dtype: string\n Underlying data type.\n\n options: Object (optional)\n Options.\n\n options.order: string (optional)\n Specifies whether the default memory layout should be row-major (C-\n style) or column-major (Fortran-style). Default: 'row-major'.\n\n options.mode: string (optional)\n Specifies the default behavior when handling indices which exceed array\n dimensions. If equal to 'throw', an ndarray instance throws an error\n when an index exceeds array dimensions. If equal to 'normalize', an\n ndarray instance normalizes negative indices and throws an error when an\n index exceeds array dimensions. If equal to 'wrap', an ndarray instance\n wraps around indices exceeding array dimensions using modulo arithmetic.\n If equal to 'clamp', an ndarray instance sets an index exceeding array\n dimensions to either `0` (minimum index) or the maximum index. Default:\n 'throw'.\n\n options.readonly: boolean (optional)\n Boolean indicating whether an array should be read-only by default.\n Default: false.\n\n Returns\n -------\n fcn: Function\n Function for creating a one-dimensional ndarray.\n\n Examples\n --------\n > var f = vector.factory( 'float32' );\n > var arr = f()\n \n > var dt = ndarrayDataType( arr )\n 'float32'\n\n See Also\n --------\n Float64Vector, Float32Vector, Int16Vector, Int32Vector, Int8Vector, Uint16Vector, Uint32Vector, Uint8Vector, Uint8ClampedVector, Complex128Vector, Complex64Vector, BooleanVector, matrix, ndarray","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n\n The last argument applied to each waterfall function is a callback. The\n callback should be invoked upon a series function completion. The first\n argument is reserved as an error argument (which can be `null`). Any results\n which should be passed to the next function in the series should be provided\n beginning with the second argument.\n\n If any function calls the provided callback with a truthy `error` argument,\n the waterfall suspends execution and immediately calls the completion\n callback for subsequent error handling.\n\n Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n the completion callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n Returns a reusable waterfall function.\n\n Parameters\n ----------\n fcns: Array\n Array of functions.\n\n clbk: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Function context.\n\n Returns\n -------\n fcn: Function\n Waterfall function.\n\n Examples\n --------\n > function foo( next ) { next( null, 'beep' ); };\n > function bar( str, next ) { console.log( str ); next(); };\n > function done( error ) { if ( error ) { throw error; } };\n > var fcns = [ foo, bar ];\n > var waterfall = waterfall.factory( fcns, done );\n > waterfall();\n > waterfall();\n > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n WebAssembly memory constructor.\n\n Parameters\n ----------\n descriptor: Object\n Memory descriptor object.\n\n descriptor.initial: integer\n Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.maximum: integer (optional)\n Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n descriptor.shared: boolean (optional)\n Boolean indicating whether the memory is shared. Default: false.\n\n Returns\n -------\n out: Memory\n WebAssembly memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n \n\n\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n \n\n\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n \n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.buffer\n ","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n\n Upon increasing the size, the previous ArrayBuffer is detached, thus\n invalidating any typed arrays which were views over the previous\n ArrayBuffer.\n\n Detachment means that the previous ArrayBuffer byte length becomes zero, and\n it no longer has bytes accessible to JavaScript.\n\n ArrayBuffer detachment applies even when `delta` is zero.\n\n Detachment only applies for non-shared memory instances. For a shared memory\n instance, the initial buffer (which is a SharedArrayBuffer) will not become\n detached and, instead, its length will not be updated.\n\n Accesses to the `buffer` property after growing a SharedArrayBuffer will\n yield a larger SharedArrayBuffer which may access a larger span of memory\n than the buffer before growing memory.\n\n Every SharedArrayBuffer accessed via the `buffer` property will always refer\n to the start of the same memory address range and thus manipulate the same\n data.\n\n Parameters\n ----------\n delta: integer\n Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n underlying memory.\n\n Returns\n -------\n out: integer\n Size of the previous memory (in units of pages).\n\n Examples\n --------\n > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n > mem.grow( 1 )\n ","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n Invokes a function while a test condition is true.\n\n The predicate function is provided two arguments:\n\n - i: iteration number (starting from zero).\n - clbk: a callback indicating whether to invoke `fcn`.\n\n The `clbk` function accepts two arguments:\n\n - error: error argument.\n - bool: test result.\n\n If the test result is truthy, the function invokes `fcn`; otherwise, the\n function invokes the `done` callback.\n\n The function to invoke is provided two arguments:\n\n - i: iteration number (starting from zero).\n - next: a callback which must be invoked before proceeding to the next\n iteration.\n\n The first argument of the `next` callback is an `error` argument. If `fcn`\n calls the `next` callback with a truthy `error` argument, the function\n suspends execution and immediately calls the `done` callback for subsequent\n `error` handling.\n\n The `done` callback is invoked with an `error` argument and any arguments\n passed to the final `next` callback.\n\n Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n wrap the `done` callback in a function which either executes at the end of\n the current stack (e.g., `nextTick`) or during a subsequent turn of the\n event loop (e.g., `setImmediate`, `setTimeout`).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n done: Function\n Callback to invoke upon completion.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n > function fcn( i, next ) {\n ... setTimeout( onTimeout, i );\n ... function onTimeout() {\n ... next( null, 'boop'+i );\n ... }\n ... };\n > function done( error, result ) {\n ... if ( error ) {\n ... throw error;\n ... }\n ... console.log( result );\n ... };\n > whileAsync( predicate, fcn, done )\n boop: 4\n\n See Also\n --------\n doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n > whileEach( arr, predicate, logger )\n 0: 1\n 1: 2\n 2: 3\n 3: 4\n\n See Also\n --------\n untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n\n When invoked, both the predicate function and the function to apply are\n provided three arguments:\n\n - value: collection value.\n - index: collection index.\n - collection: the input collection.\n\n Parameters\n ----------\n collection: Array|TypedArray|Object\n Input collection over which to iterate. If provided an object, the\n object must be array-like (excluding strings and functions).\n\n predicate: Function\n The predicate function which indicates whether to continue iterating\n over a collection.\n\n fcn: Function\n The function to invoke for each element in a collection.\n\n thisArg: any (optional)\n Execution context for the applied function.\n\n Returns\n -------\n out: Array|TypedArray|Object\n Input collection.\n\n Examples\n --------\n > function predicate( v ) { return v === v; };\n > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n > whileEachRight( arr, predicate, logger )\n 5: 5\n 4: 4\n 3: 3\n 2: 2\n\n See Also\n --------\n whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n Invokes a function while a test condition is true.\n\n When invoked, both the predicate function and the function to invoke are\n provided a single argument:\n\n - i: iteration number (starting from zero).\n\n Parameters\n ----------\n predicate: Function\n The predicate function which indicates whether to continue invoking a\n function.\n\n fcn: Function\n The function to invoke.\n\n thisArg: any (optional)\n Execution context for the invoked function.\n\n Examples\n --------\n > function predicate( i ) { return ( i < 5 ); };\n > function beep( i ) { console.log( 'boop: %d', i ); };\n > whilst( predicate, beep )\n boop: 0\n boop: 1\n boop: 2\n boop: 3\n boop: 4\n\n See Also\n --------\n doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n\n When no `y` is supplied, the function performs a one-sample Wilcoxon signed\n rank test for the null hypothesis that the data is drawn from a symmetric\n distribution around zero.\n\n When `y` is supplied, the function tests whether the\n differences `x - y` come from a symmetric distribution around zero.\n\n If `x` has less than fifty elements, an exact p-value is computed if there\n are no zero values or ties. Otherwise, a normal approximation is used.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array|TypedArray\n Data array.\n\n y: Array|TypedArray (optional)\n Paired data array.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.correction: boolean (optional)\n Determines whether to apply continuity correction adjusting the Wilcoxon\n rank statistic by 0.5 towards the mean when using the normal\n approximation. Default: `true`.\n\n options.exact: boolean (optional)\n Determines whether to force use of the exact distribution instead of a\n normal approximation when there are more than fifty data points.\n Default: `false`.\n\n options.mu: number (optional)\n Hypothesized true location under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n options.zeroMethod: string (optional)\n Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n `zsplit`). When set to `pratt`, differences of zero are used to\n calculate ranks but their ranks are then dropped. When set to `wilcox`,\n all zero-differences are discarded. When set to `zsplit`, differences of\n zero are used to rank and their ranks are then split between positive\n and negative ones. Default: `'wilcox'`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.nullValue: number\n Assumed location parameter under H0.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample test:\n > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n > var out = wilcoxon( x )\n {\n 'rejected': true,\n 'alpha': 0.05,\n 'pValue': 0.04125976562499978,\n 'statistic': 96\n // ...\n }\n\n // Paired test:\n > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n > var x = new Array( 100 );\n > var y = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = runif();\n ... y[ i ] = runif();\n ... }\n > out = wilcoxon( x, y )\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.21759090963694638,\n 'statistic': 2702.5,\n // ...\n }\n\n // Print formatted output:\n > var table = out.print()\n Paired Wilcoxon signed rank test\n\n Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n pValue: 0.2176\n statistic: 2702.5\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n // Choose custom significance level:\n > out = wilcoxon( arr, { 'alpha': 0.01 });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is not equal to 0\n\n pValue: 0.0413\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n // Test for a median equal to ten:\n > out = wilcoxon( arr, { 'mu': 10 })\n {\n 'rejected': false,\n 'alpha': 0.05,\n 'pValue': 0.11169650413134602,\n 'statistic': 88.5,\n 'nullValue': 10,\n // ...\n }\n\n // Perform one-sided tests:\n > out = wilcoxon( arr, { 'alternative': 'less' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is less than 0\n\n pValue: 0.9823\n statistic: 96\n\n Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n > out = wilcoxon( arr, { 'alternative': 'greater' });\n > table = out.print()\n One-Sample Wilcoxon signed rank test\n\n Alternative hypothesis: Median of `x` is greater than 0\n\n pValue: 0.0206\n statistic: 96\n\n Test Decision: Reject null in favor of alternative at 5% significance level\n\n See Also\n --------\n ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n Returns an array of an object's own writable property names and symbols.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own writable properties.\n\n Examples\n --------\n > function Foo() { this.beep = 'boop'; return this; };\n > Foo.prototype.foo = 'bar';\n > var obj = new Foo();\n > var props = writableProperties( obj )\n [ 'beep' ]\n\n See Also\n --------\n inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n props: Array\n List of an object's own and inherited writable property names and\n symbols.\n\n Examples\n --------\n > var props = writablePropertiesIn( [] )\n\n See Also\n --------\n inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n Returns an array of an object's own writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNames( obj )\n [ 'a' ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n Returns an array of an object's own and inherited writable property names.\n\n Name order is not guaranteed, as object key enumeration is not specified\n according to the ECMAScript specification. In practice, however, most\n engines use insertion order to sort an object's keys, thus allowing for\n deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n keys: Array\n List of an object's own and inherited writable property names.\n\n Examples\n --------\n > var obj = { 'a': 'b' };\n > var desc = {};\n > desc.configurable = true;\n > desc.enumerable = true;\n > desc.writable = false;\n > desc.value = 'boop';\n > defineProperty( obj, 'beep', desc );\n > var keys = writablePropertyNamesIn( obj )\n e.g., [ 'a', ... ]\n\n See Also\n --------\n inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n Returns an array of an object's own writable symbol properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbols( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n Returns an array of an object's own and inherited writable symbol\n properties.\n\n Property order is not guaranteed, as object property enumeration is not\n specified according to the ECMAScript specification. In practice, however,\n most engines use insertion order to sort an object's properties, thus\n allowing for deterministic extraction.\n\n If provided `null` or `undefined`, the function returns an empty array.\n\n Parameters\n ----------\n value: any\n Input value.\n\n Returns\n -------\n symbols: Array\n List of an object's own and inherited writable symbol properties.\n\n Examples\n --------\n > var obj = {};\n > var desc = {};\n > desc.configurable = false;\n > desc.enumerable = false;\n > desc.writable = true;\n > desc.value = 'boop';\n > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n > defineProperty( obj, sym, desc );\n > var symbols = writablePropertySymbolsIn( obj )\n\n See Also\n --------\n inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n Asynchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n clbk: Function\n Callback to invoke upon writing data to a file.\n\n Examples\n --------\n > function onWrite( error ) {\n ... if ( error ) {\n ... console.error( error.message );\n ... }\n ... };\n > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n Synchronously writes data to a file.\n\n Parameters\n ----------\n file: string|Buffer|integer\n Filename or file descriptor.\n\n data: string|Buffer\n Data to write.\n\n options: Object|string (optional)\n Options. If a string, the value is the encoding.\n\n options.encoding: string|null (optional)\n Encoding. The encoding option is ignored if the data argument is a\n buffer. Default: 'utf8'.\n\n options.flag: string (optional)\n Flag. Default: 'w'.\n\n options.mode: integer (optional)\n Mode. Default: 0o666.\n\n Returns\n -------\n err: Error|null\n Error object or null.\n\n Examples\n --------\n > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n See Also\n --------\n exists, readFile","zip":"\nzip( ...arr[, options] )\n Generates array tuples from input arrays.\n\n Parameters\n ----------\n arr: ...Array\n Input arrays to be zipped.\n\n options: Object (optional)\n Options.\n\n options.trunc: boolean (optional)\n Boolean indicating whether to truncate arrays longer than the shortest\n input array. Default: `true`.\n\n options.fill: any (optional)\n Fill value used for arrays of unequal length. Default: `null`.\n\n options.arrays: boolean (optional)\n Boolean indicating whether an input array should be interpreted as an\n array of arrays to be zipped. Default: `false`.\n\n Returns\n -------\n out: Array\n Array of arrays.\n\n Examples\n --------\n // Basic usage:\n > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n // Turn off truncation:\n > var opts = { 'trunc': false };\n > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n See Also\n --------\n unzip\n","ztest":"\nztest( x, sigma[, options] )\n Computes a one-sample z-test.\n\n The function performs a one-sample z-test for the null hypothesis that the\n data in array or typed array `x` is drawn from a normal distribution with\n mean zero and standard deviation `sigma`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n Data array.\n\n sigma: number\n Known standard deviation.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Indicates whether the alternative hypothesis is that the mean of `x` is\n larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n `mu` (`two-sided`). Default: `'two-sided'`.\n\n options.mu: number (optional)\n Hypothesized true mean under the null hypothesis. Set this option to\n test whether the data comes from a distribution with the specified `mu`.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for mean.\n\n out.nullValue: number\n Assumed mean value under H0.\n\n out.sd: number\n Standard error.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test (`One-Sample z-test`).\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // One-sample z-test:\n > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n > var x = new Array( 100 );\n > for ( var i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm();\n ... }\n > var out = ztest( x, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.180,\n statistic: ~-1.34,\n ci: [ ~-0.66, ~0.124 ],\n ...\n }\n\n // Choose custom significance level and print output:\n > arr = [ 2, 4, 3, 1, 0 ];\n > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n > table = out.print()\n One-sample z-test\n\n Alternative hypothesis: True mean is not equal to 0\n\n pValue: 0.0253\n statistic: 2.2361\n 99% confidence interval: [-0.3039,4.3039]\n\n Test Decision: Fail to reject null in favor of alternative at 1%\n significance level\n\n\n // Test for a mean equal to five:\n > var arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'mu': 5 } )\n {\n rejected: false,\n pValue: 1,\n statistic: 0,\n ci: [ ~4.123, ~5.877 ],\n // ...\n }\n\n // Perform one-sided tests:\n > arr = [ 4, 4, 6, 6, 5 ];\n > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n {\n alpha: 0.05,\n rejected: false,\n pValue: 1,\n statistic: 11.180339887498949,\n ci: [ -Infinity, 5.735600904580115 ],\n // ...\n }\n > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n {\n alpha: 0.05,\n rejected: true,\n pValue: 0,\n statistic: 11.180339887498949,\n ci: [ 4.264399095419885, Infinity ],\n //...\n }\n\n See Also\n --------\n ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n Computes a two-sample z-test.\n\n By default, the function performs a two-sample z-test for the null\n hypothesis that the data in arrays or typed arrays `x` and `y` is\n independently drawn from normal distributions with equal means and known\n standard deviations `sigmax` and `sigmay`.\n\n The returned object comes with a `.print()` method which when invoked will\n print a formatted output of the results of the hypothesis test.\n\n Parameters\n ----------\n x: Array\n First data array.\n\n y: Array\n Second data array.\n\n sigmax: number\n Known standard deviation of first group.\n\n sigmay: number\n Known standard deviation of second group.\n\n options: Object (optional)\n Options.\n\n options.alpha: number (optional)\n Number in the interval `[0,1]` giving the significance level of the\n hypothesis test. Default: `0.05`.\n\n options.alternative: string (optional)\n Either `two-sided`, `less` or `greater`. Indicates whether the\n alternative hypothesis is that `x` has a larger mean than `y`\n (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n the same (`two-sided`). Default: `'two-sided'`.\n\n options.difference: number (optional)\n Number denoting the difference in means under the null hypothesis.\n Default: `0`.\n\n Returns\n -------\n out: Object\n Test result object.\n\n out.alpha: number\n Used significance level.\n\n out.rejected: boolean\n Test decision.\n\n out.pValue: number\n p-value of the test.\n\n out.statistic: number\n Value of test statistic.\n\n out.ci: Array\n 1-alpha confidence interval for the mean.\n\n out.nullValue: number\n Assumed difference in means under H0.\n\n out.xmean: number\n Sample mean of `x`.\n\n out.ymean: number\n Sample mean of `y`.\n\n out.alternative: string\n Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n out.method: string\n Name of test.\n\n out.print: Function\n Function to print formatted output.\n\n Examples\n --------\n // Drawn from Normal(0,2):\n > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n // Drawn from Normal(1,2):\n > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n > var out = ztest2( x, y, 2.0, 2.0 )\n {\n alpha: 0.05,\n rejected: false,\n pValue: ~0.398,\n statistic: ~-0.844\n ci: [ ~-2.508, ~0.988 ],\n alternative: 'two-sided',\n method: 'Two-sample z-test',\n nullValue: 0,\n xmean: ~0.573,\n ymean: ~1.328\n }\n\n // Print table output:\n > var table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 95% confidence interval: [-2.508,0.998]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Choose a different significance level than `0.05`:\n > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is not equal to 0\n\n pValue: 0.3986\n statistic: -0.8441\n 60% confidence interval: [-1.5078,-0.0022]\n\n Test Decision: Reject null in favor of alternative at 40% significance level\n\n // Perform one-sided tests:\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is less than 0\n\n pValue: 0.1993\n statistic: -0.8441\n 95% confidence interval: [-Infinity,0.7162]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n\n > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n > table = out.print()\n Two-sample z-test\n\n Alternative hypothesis: True difference in means is greater than 0\n\n pValue: 0.8007\n statistic: -0.8441\n 95% confidence interval: [-2.2262,Infinity]\n\n Test Decision: Fail to reject null in favor of alternative at 5%\n significance level\n\n // Test for a difference in means besides zero:\n > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n > x = new Array( 100 );\n > for ( i = 0; i < x.length; i++ ) {\n ... x[ i ] = rnorm( 2.0, 1.0 );\n ... }\n > y = new Array( 100 );\n ... for ( i = 0; i < x.length; i++ ) {\n ... y[ i ] = rnorm( 0.0, 2.0 );\n ... }\n > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n {\n rejected: false,\n pValue: ~0.35,\n statistic: ~-0.935\n ci: [ ~1.353, ~2.229 ],\n // ...\n }\n\n See Also\n --------\n ztest\n"} diff --git a/lib/node_modules/@stdlib/repl/help/scripts/build.js b/lib/node_modules/@stdlib/repl/help/scripts/build.js index bbdb3cfd533c..88c330d14e92 100644 --- a/lib/node_modules/@stdlib/repl/help/scripts/build.js +++ b/lib/node_modules/@stdlib/repl/help/scripts/build.js @@ -34,7 +34,9 @@ var replace = require( '@stdlib/string/replace' ); var hasOwnProp = require( '@stdlib/assert/has-own-property' ); var namespace = require( '@stdlib/namespace' ); var pkg2alias = require( '@stdlib/namespace/pkg2alias' ); +var tryRequire = require( '@stdlib/utils/try-require' ); var parse = require( '@stdlib/_tools/repl-txt/parse' ); +var format = require( '@stdlib/string/format' ); // VARIABLES // @@ -102,6 +104,7 @@ function main() { var tmp; var csv; var ast; + var err; var ns; var a; var p; @@ -170,6 +173,19 @@ function main() { if ( a === null ) { debug( 'Unable to resolve alias: %s.', p ); console.warn( 'WARNING: unable to resolve alias `%s` for `%s`. ', p, alias ); // eslint-disable-line no-console + + // Attempt to `require` the package, thus confirming that the package actually exists: + err = tryRequire( pkg ); + + // If an error was returned, we were unable to import the package... + if ( err instanceof Error ) { + debug( 'Unable to resolve package: %s.', p ); + console.warn( 'WARNING: unable to resolve package `%s` for `%s`.', p, alias ); + continue; + } + // If an alias does not exist in the global namespace, dynamically `require` a package so that the desired expression can be executed in example code: + file = replace( file, tmp[ j ], format( '(require(\'%s\'))', p ) ); // WARNING: this assumes that `{{alias:}}` placeholders are in examples. If unresolved package identifiers are used in descriptions, this substitution is NOT appropriate. The use of such placeholders in description prose is uncommon, but not unheard of. However, given its relatively rare occurrence, we can likely be confident that this substitution is okay. Ideally, identifiers would be added to the database, so that this workaround is not necessary. + debug( 'Inserted a `require` expression for `%s`.', p ); } else { file = replace( file, tmp[ j ], a ); debug( 'Resolved alias: %s => %s.', p, a ); diff --git a/lib/node_modules/@stdlib/repl/info/data/data.csv b/lib/node_modules/@stdlib/repl/info/data/data.csv index da39bd8f850b..9b293254fd1f 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.csv +++ b/lib/node_modules/@stdlib/repl/info/data/data.csv @@ -1780,8 +1780,8 @@ base.strided.dmeanvarpn,"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float base.strided.dmeanvarpn.ndarray,"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n" base.strided.dmeanwd,"\nbase.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n" base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n" -base.strided.dmediansorted,"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n" -base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" +base.strided.dmedianSorted,"\nbase.strided.dmedianSorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n" +base.strided.dmedianSorted.ndarray,"\nbase.strided.dmedianSorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n" base.strided.dmidrange,"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n" base.strided.dmidrange.ndarray,"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n" base.strided.dmin,"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n" @@ -3486,6 +3486,15 @@ Int32Array.prototype.toString,"\nInt32Array.prototype.toString()\n Serializes Int32Array.prototype.values,"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n" Int32Matrix,"\nInt32Matrix( [options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray.\n\nInt32Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\nInt32Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\nInt32Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional 32-bit signed integer ndarray from an array-like\n object or iterable.\n\nInt32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\nInt32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, N:integer]][, \n options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n" Int32Vector,"\nInt32Vector( [options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray.\n\nInt32Vector( length:integer[, options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray having a specified\n length.\n\nInt32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional signed 32-bit integer ndarray from an array-like\n object or iterable.\n\nInt32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray view of an\n ArrayBuffer.\n" +Int64,"\nInt64( value:integer|bigint )\n 64-bit signed integer constructor.\n" +Int64.name,"\nInt64.name\n Constructor name.\n" +Int64.from,"\nInt64.from( words:ArrayLikeObject )\n Creates a new 64-bit signed integer from an array-like object containing a\n high and low word.\n" +Int64.of,"\nInt64.of( high:integer, low:integer )\n Creates a new 64-bit signed integer from a high and low word.\n" +Int64.BYTES_PER_ELEMENT,"\nInt64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n" +Int64.prototype.BYTES_PER_ELEMENT,"\nInt64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n" +Int64.prototype.byteLength,"\nInt64.prototype.byteLength\n Size (in bytes) of the underlying value.\n" +Int64.prototype.hi,"\nInt64.prototype.hi\n Returns the high 32-bit word of a 64-bit signed integer.\n" +Int64.prototype.lo,"\nInt64.prototype.lo\n Returns the low 32-bit word of a 64-bit signed integer.\n" IS_BIG_ENDIAN,"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n" IS_BROWSER,"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n" IS_DARWIN,"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n" @@ -5057,9 +5066,9 @@ random.beta.seedLength,"\nrandom.beta.seedLength\n Length of generator seed.\ random.beta.state,"\nrandom.beta.state\n Generator state.\n" random.beta.stateLength,"\nrandom.beta.stateLength\n Length of generator state.\n" random.beta.byteLength,"\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n" -random.betaprime,"\nrandom.betaprime( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a betaprime\n distribution.\n" -random.betaprime.assign,"\nrandom.betaprime.assign( alpha:number|ndarray, beta:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a betaprime\n distribution.\n" -random.betaprime.factory,"\nrandom.betaprime.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n betaprime distribution.\n" +random.betaprime,"\nrandom.betaprime( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta prime\n distribution.\n" +random.betaprime.assign,"\nrandom.betaprime.assign( alpha:number|ndarray, beta:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a beta prime\n distribution.\n" +random.betaprime.factory,"\nrandom.betaprime.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n beta prime distribution.\n" random.betaprime.PRNG,"\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n" random.betaprime.seed,"\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n" random.betaprime.seedLength,"\nrandom.betaprime.seedLength\n Length of generator seed.\n" @@ -5830,7 +5839,7 @@ Uint32Array.prototype.toLocaleString,"\nUint32Array.prototype.toLocaleString( [l Uint32Array.prototype.toString,"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n" Uint32Array.prototype.values,"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n" Uint32Vector,"\nUint32Vector( [options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray.\n\nUint32Vector( length:integer[, options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray having a specified\n length.\n\nUint32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional unsigned 32-bit integer ndarray from an array-like\n object or iterable.\n\nUint32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray view of an\n ArrayBuffer.\n" -Uint64,"\nUint64( value:number|bigint )\n 64-bit unsigned integer constructor.\n" +Uint64,"\nUint64( value:integer|bigint )\n 64-bit unsigned integer constructor.\n" Uint64.name,"\nUint64.name\n Constructor name.\n" Uint64.from,"\nUint64.from( words:ArrayLikeObject )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n" Uint64.of,"\nUint64.of( high:integer, low:integer )\n Creates a new 64-bit unsigned integer from a high and low word.\n" diff --git a/lib/node_modules/@stdlib/repl/info/data/data.json b/lib/node_modules/@stdlib/repl/info/data/data.json index 88fb647fedfd..e4ba6a1d24e1 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.json +++ b/lib/node_modules/@stdlib/repl/info/data/data.json @@ -1 +1 @@ -{"abs":"\nabs( x:ndarray[, options:Object] )\n Computes the absolute value for each element in an ndarray.\n","abs.assign":"\nabs.assign( x:ndarray, y:ndarray )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject, \n values:ArrayLikeObject[, options:Object] )\n Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n","base.acosdf":"\nbase.acosdf( x:number )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n","base.acosf":"\nbase.acosf( x:number )\n Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n","base.acotdf":"\nbase.acotdf( x:number )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n","base.acotf":"\nbase.acotf( x:number )\n Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n","base.acscdf":"\nbase.acscdf( x:number )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n","base.acscf":"\nbase.acscf( x:number )\n Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array )\n Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array )\n Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array )\n Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array )\n Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array )\n Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array, colexicographic:boolean )\n Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array, colexicographic:boolean )\n Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array, colex:boolean, clbk:Function[, \n thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array )\n Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array )\n Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array )\n Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array )\n Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array )\n Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n","base.asecdf":"\nbase.asecdf( x:number )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n","base.asecf":"\nbase.asecf( x:number )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n","base.asindf":"\nbase.asindf( x:number )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n","base.asinf":"\nbase.asinf( x:number )\n Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n","base.atanf":"\nbase.atanf( x:number )\n Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array )\n Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array )\n Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array )\n Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array )\n Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array )\n Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.cadd.assign":"\nbase.cadd.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.cadd.strided":"\nbase.cadd.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.caddf.assign":"\nbase.caddf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.caddf.strided":"\nbase.caddf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.camelcase":"\nbase.camelcase( str:string )\n Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.cdiv.assign":"\nbase.cdiv.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cdiv.strided":"\nbase.cdiv.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.cinvf":"\nbase.cinvf( z:Complex64 )\n Computes the inverse of a single-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmul.assign":"\nbase.cmul.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmul.strided":"\nbase.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cmulf.assign":"\nbase.cmulf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmulf.strided":"\nbase.cmulf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cneg":"\nbase.cneg( z:Complex128 )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z:Complex64 )\n Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n Computes the cosecant of an angle measured in degrees.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an arcsine distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an arcsine distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Fréchet distribution with shape parameter `α`, scale parameter `s`,\n and location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a gamma distribution with shape parameter `α` and rate parameter\n `β` at a value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a gamma distribution with shape parameter `α` and rate parameter `β` at\n a value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a geometric distribution with success probability `p` at a value\n `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Gumbel distribution with location parameter `μ` and scale\n parameter `β` at a value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Gumbel distribution with location parameter `μ` and scale parameter\n `β` at a value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Laplace distribution with scale parameter `b` and location\n parameter `μ` at a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Laplace distribution with scale parameter `b` and location parameter\n `μ` at a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Lévy distribution with location parameter `μ` and scale\n parameter `c` at a value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Lévy distribution with location parameter `μ` and scale parameter `c`\n at a value `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a logistic distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a logistic distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with location parameter `μ` and scale\n parameter `σ` at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with location\n parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Rayleigh distribution with scale parameter `sigma` at a value\n `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n nranges:integer] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a uniform distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a uniform distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Weibull distribution with shape parameter `k` and scale\n parameter `λ` at a value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Weibull distribution with shape parameter `k` and scale parameter `λ`\n at a value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n Tokenize a string into an array of string parts and format identifier\n objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.last":"\nbase.last( str:string, n:integer )\n Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an ndarray as a locale-aware string.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string|DataType, shape:ArrayLikeObject, \n order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp`\n and assigns results to a provided output array.\n","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice:MultiSlice, shape:Array, \n strict:boolean )\n Returns a normalized MultiSlice object.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the first occurrence of a specified search\n string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the last occurrence of a specified search\n string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the first occurrence of a specified search\n string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the last occurrence of a specified search\n string.\n","base.reverse":"\nbase.reverse( str:string )\n Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n Right pads a string such that the padded string has a length of at least\n `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string|DataType, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array, strict:boolean )\n Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n","base.sincos.assign":"\nbase.sincos.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two single-precision complex floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision complex floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabsSorted":"\nbase.strided.dmaxabsSorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabsSorted.ndarray":"\nbase.strided.dmaxabsSorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxSorted":"\nbase.strided.dmaxSorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxSorted.ndarray":"\nbase.strided.dmaxSorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, strideX:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, \n strideX:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n Returns the enumeration constant associated with a strided array data type\n string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, correction:number, mean:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer )\n Fills a strided array with a specified scalar constant.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, strideX:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, strideX:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Multiplies a vector by a scalar constant.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n obj:Object|Function, bool:boolean )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n offset:integer )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, strideX:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, strideX:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray, writable:boolean )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( x:integer, y:integer )\n Multiples two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value to the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\nBooleanArray( length:integer )\n Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index:integer, value:boolean )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n","BooleanVector":"\nBooleanVector( [options:Object] )\n Returns a one-dimensional boolean ndarray.\n\nBooleanVector( length:integer[, options:Object] )\n Returns a one-dimensional boolean ndarray having a specified length.\n\nBooleanVector( obj:Object[, options:Object] )\n Creates a one-dimensional boolean ndarray from an array-like object or\n iterable.\n\nBooleanVector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional boolean ndarray view of an ArrayBuffer.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","Complex64.name":"\nComplex64.name\n Constructor name.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\nComplex64Array( length:integer )\n Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index:integer, value:Complex64 )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex64Matrix":"\nComplex64Matrix( [options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray.\n\nComplex64Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\nComplex64Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\nComplex64Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\nComplex64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","Complex64Vector":"\nComplex64Vector( [options:Object] )\n Returns a one-dimensional single-precision complex floating-point ndarray.\n\nComplex64Vector( length:integer[, options:Object] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n having a specified length.\n\nComplex64Vector( obj:Object[, options:Object] )\n Creates a one-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex64Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","Complex128.name":"\nComplex128.name\n Constructor name.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index:integer, value:Complex128 )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex128Matrix":"\nComplex128Matrix( [options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray.\n\nComplex128Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\nComplex128Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\nComplex128Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex128Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\nComplex128Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","Complex128Vector":"\nComplex128Vector( [options:Object] )\n Returns a one-dimensional double-precision complex floating-point ndarray.\n\nComplex128Vector( length:integer[, options:Object] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n having a specified length.\n\nComplex128Vector( obj:Object[, options:Object] )\n Creates a one-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex128Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( value:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataType":"\nDataType( value:any[, options:Object] )\n Data type constructor.\n","DataType.name":"\nDataType.name\n Constructor name.\n","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","falses":"\nfalses( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an ndarray filled with `false` values and having a specified shape\n and data type.\n","falsesLike":"\nfalsesLike( x:ndarray[, options:Object] )\n Returns an ndarray filled with `false` values and having the same shape and\n data type as a provided input ndarray.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","Float16Array":"\nFloat16Array()\n A 16-bit half-precision floating-point number array.\n\nFloat16Array( length:integer )\n Creates a half-precision floating-point number array having a specified\n length.\n\nFloat16Array( typedarray:TypedArray )\n Creates a half-precision floating-point number array from a typed array.\n\nFloat16Array( obj:Object )\n Creates a half-precision floating-point number array from an array-like\n object or iterable.\n\nFloat16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a half-precision floating-point number array view of an ArrayBuffer.\n","Float16Array.from":"\nFloat16Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new half-precision floating-point number array from an array-like\n object or an iterable.\n","Float16Array.of":"\nFloat16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new half-precision floating-point number array from a variable\n number of arguments.\n","Float16Array.BYTES_PER_ELEMENT":"\nFloat16Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Float16Array.name":"\nFloat16Array.name\n Typed array constructor name.\n","Float16Array.prototype.buffer":"\nFloat16Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Float16Array.prototype.byteLength":"\nFloat16Array.prototype.byteLength\n Length of the array in bytes.\n","Float16Array.prototype.byteOffset":"\nFloat16Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying ArrayBuffer.\n","Float16Array.prototype.BYTES_PER_ELEMENT":"\nFloat16Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Float16Array.prototype.length":"\nFloat16Array.prototype.length\n The number of array elements.\n","Float16Array.prototype.at":"\nFloat16Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Float16Array.prototype.copyWithin":"\nFloat16Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float16Array.prototype.entries":"\nFloat16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float16Array.prototype.every":"\nFloat16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Float16Array.prototype.fill":"\nFloat16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Float16Array.prototype.filter":"\nFloat16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Float16Array.prototype.find":"\nFloat16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Float16Array.prototype.findIndex":"\nFloat16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Float16Array.prototype.findLast":"\nFloat16Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Float16Array.prototype.findLastIndex":"\nFloat16Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Float16Array.prototype.forEach":"\nFloat16Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Float16Array.prototype.includes":"\nFloat16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Float16Array.prototype.indexOf":"\nFloat16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Float16Array.prototype.join":"\nFloat16Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Float16Array.prototype.keys":"\nFloat16Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Float16Array.prototype.lastIndexOf":"\nFloat16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Float16Array.prototype.map":"\nFloat16Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Float16Array.prototype.reduce":"\nFloat16Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Float16Array.prototype.reduceRight":"\nFloat16Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Float16Array.prototype.reverse":"\nFloat16Array.prototype.reverse()\n Reverses the array *in-place*.\n","Float16Array.prototype.set":"\nFloat16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets one or more array elements.\n","Float16Array.prototype.slice":"\nFloat16Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Float16Array.prototype.some":"\nFloat16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","Float16Array.prototype.sort":"\nFloat16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","Float16Array.prototype.subarray":"\nFloat16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Float16Array.prototype.toLocaleString":"\nFloat16Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float16Array.prototype.toReversed":"\nFloat16Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Float16Array.prototype.toSorted":"\nFloat16Array.prototype.toSorted( [compareFcn:Function] )\n Returns a new typed array containing the elements in sorted order.\n","Float16Array.prototype.toString":"\nFloat16Array.prototype.toString()\n Serializes an array as a string.\n","Float16Array.prototype.values":"\nFloat16Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Float16Array.prototype.with":"\nFloat16Array.prototype.with( index:integer, value:number )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Float32Matrix":"\nFloat32Matrix( [options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray.\n\nFloat32Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\nFloat32Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\nFloat32Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\nFloat32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n","Float32Vector":"\nFloat32Vector( [options:Object] )\n Returns a one-dimensional single-precision floating-point ndarray.\n\nFloat32Vector( length:integer[, options:Object] )\n Returns a one-dimensional single-precision floating-point ndarray having a\n specified length.\n\nFloat32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Float64Matrix":"\nFloat64Matrix( [options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray.\n\nFloat64Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\nFloat64Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\nFloat64Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\nFloat64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n","Float64Vector":"\nFloat64Vector( [options:Object] )\n Returns a one-dimensional double-precision floating-point ndarray.\n\nFloat64Vector( length:integer[, options:Object] )\n Returns a one-dimensional double-precision floating-point ndarray having a\n specified length.\n\nFloat64Vector( obj:Object[, options:Object] )\n Creates a one-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat64Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","format":"\nformat( str:string, ...args:any )\n Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServerFactory":"\nhttpServerFactory( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Int8Vector":"\nInt8Vector( [options:Object] )\n Returns a one-dimensional signed 8-bit integer ndarray.\n\nInt8Vector( length:integer[, options:Object] )\n Returns a one-dimensional signed 8-bit integer ndarray having a specified\n length.\n\nInt8Vector( obj:Object[, options:Object] )\n Creates a one-dimensional signed 8-bit integer ndarray from an array-like\n object or iterable.\n\nInt8Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional signed 8-bit integer ndarray view of an\n ArrayBuffer.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Int16Vector":"\nInt16Vector( [options:Object] )\n Returns a one-dimensional signed 16-bit integer ndarray.\n\nInt16Vector( length:integer[, options:Object] )\n Returns a one-dimensional signed 16-bit integer ndarray having a specified\n length.\n\nInt16Vector( obj:Object[, options:Object] )\n Creates a one-dimensional signed 16-bit integer ndarray from an array-like\n object or iterable.\n\nInt16Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional signed 16-bit integer ndarray view of an\n ArrayBuffer.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Int32Matrix":"\nInt32Matrix( [options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray.\n\nInt32Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\nInt32Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\nInt32Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional 32-bit signed integer ndarray from an array-like\n object or iterable.\n\nInt32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\nInt32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, N:integer]][, \n options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n","Int32Vector":"\nInt32Vector( [options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray.\n\nInt32Vector( length:integer[, options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray having a specified\n length.\n\nInt32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional signed 32-bit integer ndarray from an array-like\n object or iterable.\n\nInt32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray view of an\n ArrayBuffer.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have equal values.\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [value:integer|Date] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStartcase":"\nisStartcase( value:any )\n Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isStruct":"\nisStruct( value:any )\n Tests if a value is a `struct` instance.\n","isStructConstructorLike":"\nisStructConstructorLike( value:any )\n Tests if a value is struct constructor-like.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a built-in typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterDoUntilEach":"\niterDoUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","matrix":"\nmatrix( [dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray.\n\nmatrix( shape:ArrayLikeObject[, dtype:string|DataType][, \n options:Object] )\n Returns a two-dimensional ndarray having a specified shape.\n\nmatrix( M:integer, N:integer[, dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray having a specified shape.\n\nmatrix( obj:Object[, dtype:string|DataType][, options:Object] )\n Creates a two-dimensional ndarray from an array-like object or iterable.\n\nmatrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n\nmatrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, N:integer]][, \n dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n","matrix.factory":"\nmatrix.factory( dtype:string|DataType[, options:Object] )\n Returns a function for creating a two-dimensional ndarray.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndfill":"\nndfill( x:ndarrayLike, value:any )\n Fills an input ndarray with a specified value.\n","ndfillBy":"\nndfillBy( x:ndarrayLike, fcn:Function[, thisArg:any] )\n Fills an input ndarray according to a callback function.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n Returns the ndarray associated with the instance having a provided\n identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","nditer2arrayEach":"\nnditer2arrayEach( iterator:Object )\n Returns an iterator which converts each iterated ndarray to a generic array.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike, ndims:integer )\n Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n","random.arcsine":"\nrandom.arcsine( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.arcsine.assign":"\nrandom.arcsine.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.arcsine.factory":"\nrandom.arcsine.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an arcsine\n distribution.\n","random.arcsine.PRNG":"\nrandom.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.arcsine.seed":"\nrandom.arcsine.seed\n Pseudorandom number generator seed.\n","random.arcsine.seedLength":"\nrandom.arcsine.seedLength\n Length of generator seed.\n","random.arcsine.state":"\nrandom.arcsine.state\n Generator state.\n","random.arcsine.stateLength":"\nrandom.arcsine.stateLength\n Length of generator state.\n","random.arcsine.byteLength":"\nrandom.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.bernoulli":"\nrandom.bernoulli( shape:Array, p:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.bernoulli.assign":"\nrandom.bernoulli.assign( p:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.bernoulli.factory":"\nrandom.bernoulli.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.bernoulli.PRNG":"\nrandom.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.bernoulli.seed":"\nrandom.bernoulli.seed\n Pseudorandom number generator seed.\n","random.bernoulli.seedLength":"\nrandom.bernoulli.seedLength\n Length of generator seed.\n","random.bernoulli.state":"\nrandom.bernoulli.state\n Generator state.\n","random.bernoulli.stateLength":"\nrandom.bernoulli.stateLength\n Length of generator state.\n","random.bernoulli.byteLength":"\nrandom.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.beta":"\nrandom.beta( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta\n distribution.\n","random.beta.assign":"\nrandom.beta.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a beta distribution.\n","random.beta.factory":"\nrandom.beta.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a beta\n distribution.\n","random.beta.PRNG":"\nrandom.beta.PRNG\n Underlying pseudorandom number generator.\n","random.beta.seed":"\nrandom.beta.seed\n Pseudorandom number generator seed.\n","random.beta.seedLength":"\nrandom.beta.seedLength\n Length of generator seed.\n","random.beta.state":"\nrandom.beta.state\n Generator state.\n","random.beta.stateLength":"\nrandom.beta.stateLength\n Length of generator state.\n","random.beta.byteLength":"\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n","random.betaprime":"\nrandom.betaprime( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a betaprime\n distribution.\n","random.betaprime.assign":"\nrandom.betaprime.assign( alpha:number|ndarray, beta:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a betaprime\n distribution.\n","random.betaprime.factory":"\nrandom.betaprime.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n betaprime distribution.\n","random.betaprime.PRNG":"\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.betaprime.seed":"\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n","random.betaprime.seedLength":"\nrandom.betaprime.seedLength\n Length of generator seed.\n","random.betaprime.state":"\nrandom.betaprime.state\n Generator state.\n","random.betaprime.stateLength":"\nrandom.betaprime.stateLength\n Length of generator state.\n","random.betaprime.byteLength":"\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.binomial":"\nrandom.binomial( shape:Array, n:number|ndarray, p:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.binomial.assign":"\nrandom.binomial.assign( n:number|ndarray, p:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a binomial\n distribution.\n","random.binomial.factory":"\nrandom.binomial.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a binomial\n distribution.\n","random.binomial.PRNG":"\nrandom.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.binomial.seed":"\nrandom.binomial.seed\n Pseudorandom number generator seed.\n","random.binomial.seedLength":"\nrandom.binomial.seedLength\n Length of generator seed.\n","random.binomial.state":"\nrandom.binomial.state\n Generator state.\n","random.binomial.stateLength":"\nrandom.binomial.stateLength\n Length of generator state.\n","random.binomial.byteLength":"\nrandom.binomial.byteLength\n Size (in bytes) of generator state.\n","random.cauchy":"\nrandom.cauchy( shape:Array, x0:number|ndarray, gamma:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.cauchy.assign":"\nrandom.cauchy.assign( x0:number|ndarray, gamma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Cauchy distribution.\n","random.cauchy.factory":"\nrandom.cauchy.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.cauchy.PRNG":"\nrandom.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.cauchy.seed":"\nrandom.cauchy.seed\n Pseudorandom number generator seed.\n","random.cauchy.seedLength":"\nrandom.cauchy.seedLength\n Length of generator seed.\n","random.cauchy.state":"\nrandom.cauchy.state\n Generator state.\n","random.cauchy.stateLength":"\nrandom.cauchy.stateLength\n Length of generator state.\n","random.cauchy.byteLength":"\nrandom.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.chi":"\nrandom.chi( shape:Array, k:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi\n distribution.\n","random.chi.assign":"\nrandom.chi.assign( k:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a chi distribution.\n","random.chi.factory":"\nrandom.chi.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.chi.PRNG":"\nrandom.chi.PRNG\n Underlying pseudorandom number generator.\n","random.chi.seed":"\nrandom.chi.seed\n Pseudorandom number generator seed.\n","random.chi.seedLength":"\nrandom.chi.seedLength\n Length of generator seed.\n","random.chi.state":"\nrandom.chi.state\n Generator state.\n","random.chi.stateLength":"\nrandom.chi.stateLength\n Length of generator state.\n","random.chi.byteLength":"\nrandom.chi.byteLength\n Size (in bytes) of generator state.\n","random.chisquare":"\nrandom.chisquare( shape:Array, k:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.chisquare.assign":"\nrandom.chisquare.assign( k:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.chisquare.factory":"\nrandom.chisquare.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a chi-\n square distribution.\n","random.chisquare.PRNG":"\nrandom.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.chisquare.seed":"\nrandom.chisquare.seed\n Pseudorandom number generator seed.\n","random.chisquare.seedLength":"\nrandom.chisquare.seedLength\n Length of generator seed.\n","random.chisquare.state":"\nrandom.chisquare.state\n Generator state.\n","random.chisquare.stateLength":"\nrandom.chisquare.stateLength\n Length of generator state.\n","random.chisquare.byteLength":"\nrandom.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.cosine":"\nrandom.cosine( shape:Array, mu:number|ndarray, s:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.cosine.assign":"\nrandom.cosine.assign( mu:number|ndarray, s:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.cosine.factory":"\nrandom.cosine.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.cosine.PRNG":"\nrandom.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.cosine.seed":"\nrandom.cosine.seed\n Pseudorandom number generator seed.\n","random.cosine.seedLength":"\nrandom.cosine.seedLength\n Length of generator seed.\n","random.cosine.state":"\nrandom.cosine.state\n Generator state.\n","random.cosine.stateLength":"\nrandom.cosine.stateLength\n Length of generator state.\n","random.cosine.byteLength":"\nrandom.cosine.byteLength\n Size (in bytes) of generator state.\n","random.discreteUniform":"\nrandom.discreteUniform( shape:Array, a:number|ndarray, \n b:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.discreteUniform.assign":"\nrandom.discreteUniform.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.discreteUniform.factory":"\nrandom.discreteUniform.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.discreteUniform.PRNG":"\nrandom.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.discreteUniform.seed":"\nrandom.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.discreteUniform.seedLength":"\nrandom.discreteUniform.seedLength\n Length of generator seed.\n","random.discreteUniform.state":"\nrandom.discreteUniform.state\n Generator state.\n","random.discreteUniform.stateLength":"\nrandom.discreteUniform.stateLength\n Length of generator state.\n","random.discreteUniform.byteLength":"\nrandom.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.erlang":"\nrandom.erlang( shape:Array, k:number|ndarray, lambda:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.erlang.assign":"\nrandom.erlang.assign( k:number|ndarray, lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an Erlang\n distribution.\n","random.erlang.factory":"\nrandom.erlang.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.erlang.PRNG":"\nrandom.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.erlang.seed":"\nrandom.erlang.seed\n Pseudorandom number generator seed.\n","random.erlang.seedLength":"\nrandom.erlang.seedLength\n Length of generator seed.\n","random.erlang.state":"\nrandom.erlang.state\n Generator state.\n","random.erlang.stateLength":"\nrandom.erlang.stateLength\n Length of generator state.\n","random.erlang.byteLength":"\nrandom.erlang.byteLength\n Size (in bytes) of generator state.\n","random.exponential":"\nrandom.exponential( shape:Array, lambda:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.exponential.assign":"\nrandom.exponential.assign( lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an exponential\n distribution.\n","random.exponential.factory":"\nrandom.exponential.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.exponential.PRNG":"\nrandom.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.exponential.seed":"\nrandom.exponential.seed\n Pseudorandom number generator seed.\n","random.exponential.seedLength":"\nrandom.exponential.seedLength\n Length of generator seed.\n","random.exponential.state":"\nrandom.exponential.state\n Generator state.\n","random.exponential.stateLength":"\nrandom.exponential.stateLength\n Length of generator state.\n","random.exponential.byteLength":"\nrandom.exponential.byteLength\n Size (in bytes) of generator state.\n","random.f":"\nrandom.f( shape:Array, d1:number|ndarray, d2:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an F\n distribution.\n","random.f.assign":"\nrandom.f.assign( d1:number|ndarray, d2:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an F distribution.\n","random.f.factory":"\nrandom.f.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an F\n distribution.\n","random.f.PRNG":"\nrandom.f.PRNG\n Underlying pseudorandom number generator.\n","random.f.seed":"\nrandom.f.seed\n Pseudorandom number generator seed.\n","random.f.seedLength":"\nrandom.f.seedLength\n Length of generator seed.\n","random.f.state":"\nrandom.f.state\n Generator state.\n","random.f.stateLength":"\nrandom.f.stateLength\n Length of generator state.\n","random.f.byteLength":"\nrandom.f.byteLength\n Size (in bytes) of generator state.\n","random.frechet":"\nrandom.frechet( shape:Array, alpha:number|ndarray, s:number|ndarray, \n m:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.frechet.assign":"\nrandom.frechet.assign( alpha:number|ndarray, s:number|ndarray, \n m:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.frechet.factory":"\nrandom.frechet.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.frechet.PRNG":"\nrandom.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.frechet.seed":"\nrandom.frechet.seed\n Pseudorandom number generator seed.\n","random.frechet.seedLength":"\nrandom.frechet.seedLength\n Length of generator seed.\n","random.frechet.state":"\nrandom.frechet.state\n Generator state.\n","random.frechet.stateLength":"\nrandom.frechet.stateLength\n Length of generator state.\n","random.frechet.byteLength":"\nrandom.frechet.byteLength\n Size (in bytes) of generator state.\n","random.gamma":"\nrandom.gamma( shape:Array, alpha:number|ndarray, beta:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.gamma.assign":"\nrandom.gamma.assign( alpha:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a gamma distribution.\n","random.gamma.factory":"\nrandom.gamma.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.gamma.PRNG":"\nrandom.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.gamma.seed":"\nrandom.gamma.seed\n Pseudorandom number generator seed.\n","random.gamma.seedLength":"\nrandom.gamma.seedLength\n Length of generator seed.\n","random.gamma.state":"\nrandom.gamma.state\n Generator state.\n","random.gamma.stateLength":"\nrandom.gamma.stateLength\n Length of generator state.\n","random.gamma.byteLength":"\nrandom.gamma.byteLength\n Size (in bytes) of generator state.\n","random.geometric":"\nrandom.geometric( shape:Array, p:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.geometric.assign":"\nrandom.geometric.assign( p:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a geometric\n distribution.\n","random.geometric.factory":"\nrandom.geometric.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.geometric.PRNG":"\nrandom.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.geometric.seed":"\nrandom.geometric.seed\n Pseudorandom number generator seed.\n","random.geometric.seedLength":"\nrandom.geometric.seedLength\n Length of generator seed.\n","random.geometric.state":"\nrandom.geometric.state\n Generator state.\n","random.geometric.stateLength":"\nrandom.geometric.stateLength\n Length of generator state.\n","random.geometric.byteLength":"\nrandom.geometric.byteLength\n Size (in bytes) of generator state.\n","random.gumbel":"\nrandom.gumbel( shape:Array, mu:number|ndarray, beta:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.gumbel.assign":"\nrandom.gumbel.assign( mu:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Gumbel distribution.\n","random.gumbel.factory":"\nrandom.gumbel.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.gumbel.PRNG":"\nrandom.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.gumbel.seed":"\nrandom.gumbel.seed\n Pseudorandom number generator seed.\n","random.gumbel.seedLength":"\nrandom.gumbel.seedLength\n Length of generator seed.\n","random.gumbel.state":"\nrandom.gumbel.state\n Generator state.\n","random.gumbel.stateLength":"\nrandom.gumbel.stateLength\n Length of generator state.\n","random.gumbel.byteLength":"\nrandom.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.hypergeometric":"\nrandom.hypergeometric( shape:Array, N:number|ndarray, \n K:number|ndarray, n:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.hypergeometric.assign":"\nrandom.hypergeometric.assign( N:number|ndarray, K:number|ndarray, \n n:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.hypergeometric.factory":"\nrandom.hypergeometric.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.hypergeometric.PRNG":"\nrandom.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.hypergeometric.seed":"\nrandom.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.hypergeometric.seedLength":"\nrandom.hypergeometric.seedLength\n Length of generator seed.\n","random.hypergeometric.state":"\nrandom.hypergeometric.state\n Generator state.\n","random.hypergeometric.stateLength":"\nrandom.hypergeometric.stateLength\n Length of generator state.\n","random.hypergeometric.byteLength":"\nrandom.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.invgamma":"\nrandom.invgamma( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an inverse\n gamma distribution.\n","random.invgamma.assign":"\nrandom.invgamma.assign( alpha:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.invgamma.factory":"\nrandom.invgamma.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an inverse\n gamma distribution.\n","random.invgamma.PRNG":"\nrandom.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.invgamma.seed":"\nrandom.invgamma.seed\n Pseudorandom number generator seed.\n","random.invgamma.seedLength":"\nrandom.invgamma.seedLength\n Length of generator seed.\n","random.invgamma.state":"\nrandom.invgamma.state\n Generator state.\n","random.invgamma.stateLength":"\nrandom.invgamma.stateLength\n Length of generator state.\n","random.invgamma.byteLength":"\nrandom.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.kumaraswamy":"\nrandom.kumaraswamy( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n","random.kumaraswamy.assign":"\nrandom.kumaraswamy.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n","random.kumaraswamy.factory":"\nrandom.kumaraswamy.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n Kumaraswamy distribution.\n","random.kumaraswamy.PRNG":"\nrandom.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.kumaraswamy.seed":"\nrandom.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.kumaraswamy.seedLength":"\nrandom.kumaraswamy.seedLength\n Length of generator seed.\n","random.kumaraswamy.state":"\nrandom.kumaraswamy.state\n Generator state.\n","random.kumaraswamy.stateLength":"\nrandom.kumaraswamy.stateLength\n Length of generator state.\n","random.kumaraswamy.byteLength":"\nrandom.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.laplace":"\nrandom.laplace( shape:Array, mu:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.laplace.assign":"\nrandom.laplace.assign( mu:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.laplace.factory":"\nrandom.laplace.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.laplace.PRNG":"\nrandom.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.laplace.seed":"\nrandom.laplace.seed\n Pseudorandom number generator seed.\n","random.laplace.seedLength":"\nrandom.laplace.seedLength\n Length of generator seed.\n","random.laplace.state":"\nrandom.laplace.state\n Generator state.\n","random.laplace.stateLength":"\nrandom.laplace.stateLength\n Length of generator state.\n","random.laplace.byteLength":"\nrandom.laplace.byteLength\n Size (in bytes) of generator state.\n","random.levy":"\nrandom.levy( shape:Array, mu:number|ndarray, c:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.levy.assign":"\nrandom.levy.assign( mu:number|ndarray, c:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Lévy distribution.\n","random.levy.factory":"\nrandom.levy.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.levy.PRNG":"\nrandom.levy.PRNG\n Underlying pseudorandom number generator.\n","random.levy.seed":"\nrandom.levy.seed\n Pseudorandom number generator seed.\n","random.levy.seedLength":"\nrandom.levy.seedLength\n Length of generator seed.\n","random.levy.state":"\nrandom.levy.state\n Generator state.\n","random.levy.stateLength":"\nrandom.levy.stateLength\n Length of generator state.\n","random.levy.byteLength":"\nrandom.levy.byteLength\n Size (in bytes) of generator state.\n","random.logistic":"\nrandom.logistic( shape:Array, mu:number|ndarray, s:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.logistic.assign":"\nrandom.logistic.assign( mu:number|ndarray, s:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a logistic\n distribution.\n","random.logistic.factory":"\nrandom.logistic.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a logistic\n distribution.\n","random.logistic.PRNG":"\nrandom.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.logistic.seed":"\nrandom.logistic.seed\n Pseudorandom number generator seed.\n","random.logistic.seedLength":"\nrandom.logistic.seedLength\n Length of generator seed.\n","random.logistic.state":"\nrandom.logistic.state\n Generator state.\n","random.logistic.stateLength":"\nrandom.logistic.stateLength\n Length of generator state.\n","random.logistic.byteLength":"\nrandom.logistic.byteLength\n Size (in bytes) of generator state.\n","random.lognormal":"\nrandom.lognormal( shape:Array, mu:number|ndarray, \n sigma:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.lognormal.assign":"\nrandom.lognormal.assign( mu:number|ndarray, sigma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.lognormal.factory":"\nrandom.lognormal.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.lognormal.PRNG":"\nrandom.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.lognormal.seed":"\nrandom.lognormal.seed\n Pseudorandom number generator seed.\n","random.lognormal.seedLength":"\nrandom.lognormal.seedLength\n Length of generator seed.\n","random.lognormal.state":"\nrandom.lognormal.state\n Generator state.\n","random.lognormal.stateLength":"\nrandom.lognormal.stateLength\n Length of generator state.\n","random.lognormal.byteLength":"\nrandom.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.negativeBinomial":"\nrandom.negativeBinomial( shape:Array, r:number|ndarray, \n p:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.negativeBinomial.assign":"\nrandom.negativeBinomial.assign( r:number|ndarray, p:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.negativeBinomial.factory":"\nrandom.negativeBinomial.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.negativeBinomial.PRNG":"\nrandom.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.negativeBinomial.seed":"\nrandom.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.negativeBinomial.seedLength":"\nrandom.negativeBinomial.seedLength\n Length of generator seed.\n","random.negativeBinomial.state":"\nrandom.negativeBinomial.state\n Generator state.\n","random.negativeBinomial.stateLength":"\nrandom.negativeBinomial.stateLength\n Length of generator state.\n","random.negativeBinomial.byteLength":"\nrandom.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.normal":"\nrandom.normal( shape:Array, mu:number|ndarray, sigma:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a normal\n distribution.\n","random.normal.assign":"\nrandom.normal.assign( mu:number|ndarray, sigma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a normal distribution.\n","random.normal.factory":"\nrandom.normal.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.normal.PRNG":"\nrandom.normal.PRNG\n Underlying pseudorandom number generator.\n","random.normal.seed":"\nrandom.normal.seed\n Pseudorandom number generator seed.\n","random.normal.seedLength":"\nrandom.normal.seedLength\n Length of generator seed.\n","random.normal.state":"\nrandom.normal.state\n Generator state.\n","random.normal.stateLength":"\nrandom.normal.stateLength\n Length of generator state.\n","random.normal.byteLength":"\nrandom.normal.byteLength\n Size (in bytes) of generator state.\n","random.pareto1":"\nrandom.pareto1( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.pareto1.assign":"\nrandom.pareto1.assign( alpha:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.pareto1.factory":"\nrandom.pareto1.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.pareto1.PRNG":"\nrandom.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.pareto1.seed":"\nrandom.pareto1.seed\n Pseudorandom number generator seed.\n","random.pareto1.seedLength":"\nrandom.pareto1.seedLength\n Length of generator seed.\n","random.pareto1.state":"\nrandom.pareto1.state\n Generator state.\n","random.pareto1.stateLength":"\nrandom.pareto1.stateLength\n Length of generator state.\n","random.pareto1.byteLength":"\nrandom.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.poisson":"\nrandom.poisson( shape:Array, lambda:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.poisson.assign":"\nrandom.poisson.assign( lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.poisson.factory":"\nrandom.poisson.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.poisson.PRNG":"\nrandom.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.poisson.seed":"\nrandom.poisson.seed\n Pseudorandom number generator seed.\n","random.poisson.seedLength":"\nrandom.poisson.seedLength\n Length of generator seed.\n","random.poisson.state":"\nrandom.poisson.state\n Generator state.\n","random.poisson.stateLength":"\nrandom.poisson.stateLength\n Length of generator state.\n","random.poisson.byteLength":"\nrandom.poisson.byteLength\n Size (in bytes) of generator state.\n","random.rayleigh":"\nrandom.rayleigh( shape:Array, sigma:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.rayleigh.assign":"\nrandom.rayleigh.assign( sigma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.rayleigh.factory":"\nrandom.rayleigh.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.rayleigh.PRNG":"\nrandom.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.rayleigh.seed":"\nrandom.rayleigh.seed\n Pseudorandom number generator seed.\n","random.rayleigh.seedLength":"\nrandom.rayleigh.seedLength\n Length of generator seed.\n","random.rayleigh.state":"\nrandom.rayleigh.state\n Generator state.\n","random.rayleigh.stateLength":"\nrandom.rayleigh.stateLength\n Length of generator state.\n","random.rayleigh.byteLength":"\nrandom.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.t":"\nrandom.t( shape:Array, v:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.t.assign":"\nrandom.t.assign( v:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.t.factory":"\nrandom.t.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n Student's t-distribution.\n","random.t.PRNG":"\nrandom.t.PRNG\n Underlying pseudorandom number generator.\n","random.t.seed":"\nrandom.t.seed\n Pseudorandom number generator seed.\n","random.t.seedLength":"\nrandom.t.seedLength\n Length of generator seed.\n","random.t.state":"\nrandom.t.state\n Generator state.\n","random.t.stateLength":"\nrandom.t.stateLength\n Length of generator state.\n","random.t.byteLength":"\nrandom.t.byteLength\n Size (in bytes) of generator state.\n","random.triangular":"\nrandom.triangular( shape:Array, a:number|ndarray, b:number|ndarray, \n c:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.triangular.assign":"\nrandom.triangular.assign( a:number|ndarray, b:number|ndarray, c:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a triangular\n distribution.\n","random.triangular.factory":"\nrandom.triangular.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.triangular.PRNG":"\nrandom.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.triangular.seed":"\nrandom.triangular.seed\n Pseudorandom number generator seed.\n","random.triangular.seedLength":"\nrandom.triangular.seedLength\n Length of generator seed.\n","random.triangular.state":"\nrandom.triangular.state\n Generator state.\n","random.triangular.stateLength":"\nrandom.triangular.stateLength\n Length of generator state.\n","random.triangular.byteLength":"\nrandom.triangular.byteLength\n Size (in bytes) of generator state.\n","random.uniform":"\nrandom.uniform( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.uniform.assign":"\nrandom.uniform.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.uniform.factory":"\nrandom.uniform.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.uniform.PRNG":"\nrandom.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.uniform.seed":"\nrandom.uniform.seed\n Pseudorandom number generator seed.\n","random.uniform.seedLength":"\nrandom.uniform.seedLength\n Length of generator seed.\n","random.uniform.state":"\nrandom.uniform.state\n Generator state.\n","random.uniform.stateLength":"\nrandom.uniform.stateLength\n Length of generator state.\n","random.uniform.byteLength":"\nrandom.uniform.byteLength\n Size (in bytes) of generator state.\n","random.weibull":"\nrandom.weibull( shape:Array, k:number|ndarray, lambda:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.weibull.assign":"\nrandom.weibull.assign( k:number|ndarray, lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.weibull.factory":"\nrandom.weibull.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Weibull\n distribution.\n","random.weibull.PRNG":"\nrandom.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.weibull.seed":"\nrandom.weibull.seed\n Pseudorandom number generator seed.\n","random.weibull.seedLength":"\nrandom.weibull.seedLength\n Length of generator seed.\n","random.weibull.state":"\nrandom.weibull.state\n Generator state.\n","random.weibull.stateLength":"\nrandom.weibull.stateLength\n Length of generator state.\n","random.weibull.byteLength":"\nrandom.weibull.byteLength\n Size (in bytes) of generator state.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","trues":"\ntrues( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an ndarray filled with `true` values and having a specified shape\n and data type.\n","truesLike":"\ntruesLike( x:ndarray[, options:Object] )\n Returns an ndarray filled with `true` values and having the same shape and\n data type as a provided input ndarray.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedVector":"\nUint8ClampedVector( [options:Object] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray.\n\nUint8ClampedVector( length:integer[, options:Object] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray having a\n specified length.\n\nUint8ClampedVector( obj:Object[, options:Object] )\n Creates a one-dimensional clamped unsigned 8-bit integer ndarray from an\n array-like object or iterable.\n\nUint8ClampedVector( buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, options:Object] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n","Uint8Vector":"\nUint8Vector( [options:Object] )\n Returns a one-dimensional unsigned 8-bit integer ndarray.\n\nUint8Vector( length:integer[, options:Object] )\n Returns a one-dimensional unsigned 8-bit integer ndarray having a specified\n length.\n\nUint8Vector( obj:Object[, options:Object] )\n Creates a one-dimensional unsigned 8-bit integer ndarray from an array-like\n object or iterable.\n\nUint8Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint16Vector":"\nUint16Vector( [options:Object] )\n Returns a one-dimensional unsigned 16-bit integer ndarray.\n\nUint16Vector( length:integer[, options:Object] )\n Returns a one-dimensional unsigned 16-bit integer ndarray having a specified\n length.\n\nUint16Vector( obj:Object[, options:Object] )\n Creates a one-dimensional unsigned 16-bit integer ndarray from an array-like\n object or iterable.\n\nUint16Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional unsigned 16-bit integer ndarray view of an\n ArrayBuffer.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint32Vector":"\nUint32Vector( [options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray.\n\nUint32Vector( length:integer[, options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray having a specified\n length.\n\nUint32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional unsigned 32-bit integer ndarray from an array-like\n object or iterable.\n\nUint32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray view of an\n ArrayBuffer.\n","Uint64":"\nUint64( value:number|bigint )\n 64-bit unsigned integer constructor.\n","Uint64.name":"\nUint64.name\n Constructor name.\n","Uint64.from":"\nUint64.from( words:ArrayLikeObject )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n","Uint64.of":"\nUint64.of( high:integer, low:integer )\n Creates a new 64-bit unsigned integer from a high and low word.\n","Uint64.BYTES_PER_ELEMENT":"\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n","Uint64.prototype.BYTES_PER_ELEMENT":"\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n","Uint64.prototype.byteLength":"\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n","Uint64.prototype.hi":"\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n","Uint64.prototype.lo":"\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","vector":"\nvector( [dtype:string][, options:Object] )\n Returns a one-dimensional ndarray.\n\nvector( length:integer[, dtype:string][, options:Object] )\n Returns a one-dimensional ndarray having a specified length.\n\nvector( obj:Object[, dtype:string][, options:Object] )\n Creates a one-dimensional ndarray from an array-like object or iterable.\n\nvector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string][, options:Object] )\n Returns a one-dimensional ndarray view of an ArrayBuffer.\n","vector.factory":"\nvector.factory( dtype:string[, options:Object] )\n Returns a function for creating a one-dimensional ndarray.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} +{"abs":"\nabs( x:ndarray[, options:Object] )\n Computes the absolute value for each element in an ndarray.\n","abs.assign":"\nabs.assign( x:ndarray, y:ndarray )\n Computes the absolute value for each element in an ndarray and assigns\n results to a provided output ndarray.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n Creates an uninitialized array having the same length and data type as a\n provided input array.\n","AFINN_96":"\nAFINN_96()\n Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n Returns a filled array having the same length and data type as a provided\n input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with NaNs and having the same length and data type\n as a provided input array.\n","anova1":"\nanova1( x:Array, factor:Array[, options:Object] )\n Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether at least one element in a collection passes a test implemented\n by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether at least one element in a collection\n passes a test implemented by a predicate function, iterating from right to\n left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one value in an object passes a test implemented by\n a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one own property of an object passes a\n test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n Returns an array filled with ones and having the same length and data type\n as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one and having the same length and data type as a provided\n input array.\n","APERY":"\nAPERY\n Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n options:Object] )\n Replaces elements of an array with provided values according to a provided\n mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject, \n values:ArrayLikeObject[, options:Object] )\n Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n Operating system CPU architecture for which the JavaScript runtime binary\n was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n An array containing command-line arguments passed when launching the calling\n process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array )\n Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n Returns a function for converting an array to an object supporting fancy\n indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like\n object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n Read-only property returning a boolean indicating whether an array index is\n actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n Returns the minimum array data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the array data type with the smallest size and closest \"kind\" to\n which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n Returns a list of array data types to which a provided array data type can\n be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of an array-like object\n view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of\n an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject[, \n options:Object] )\n Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n Returns a zero-filled array having the same length and data type as a\n provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero and having the same length and data type as a provided\n input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n Computes the squared absolute value of a double-precision floating-point\n `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n Computes the squared absolute value of a single-precision floating-point\n `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n Computes the arccosine (in degrees) of a double-precision floating-point \n number.\n","base.acosdf":"\nbase.acosdf( x:number )\n Computes the arccosine (in degrees) of a single-precision floating-point\n number.\n","base.acosf":"\nbase.acosf( x:number )\n Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n Computes the hyperbolic arccosine of a double-precision floating-point\n number.\n","base.acot":"\nbase.acot( x:number )\n Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n Computes the arccotangent (in degrees) of a double-precision floating-point\n number.\n","base.acotdf":"\nbase.acotdf( x:number )\n Computes the arccotangent (in degrees) of a single-precision floating-point\n number.\n","base.acotf":"\nbase.acotf( x:number )\n Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n Computes the inverse hyperbolic cotangent of a double-precision floating-\n point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n Computes the arccosecant of (in degrees) a double-precision floating-point\n number.\n","base.acscdf":"\nbase.acscdf( x:number )\n Computes the arccosecant (in degrees) of a single-precision floating-point\n number.\n","base.acscf":"\nbase.acscf( x:number )\n Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array )\n Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled two-dimensional nested array according to a provided\n callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array )\n Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled three-dimensional nested array according to a provided\n callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array )\n Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled four-dimensional nested array according to a provided\n callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array )\n Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled five-dimensional nested array according to a provided\n callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array )\n Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array, clbk:Function[, thisArg:any] )\n Returns a filled n-dimensional nested array according to a callback\n function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n Returns a shallow copy of an array containing only those elements which pass\n a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array, colexicographic:boolean )\n Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens an n-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array, colexicographic:boolean )\n Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a two-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a two-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a three-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a three-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a four-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a four-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array, \n colexicographic:boolean )\n Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array, colexicographic:boolean, \n out:Collection, stride:integer, offset:integer )\n Flattens a five-dimensional nested array and assigns elements to a provided\n output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array, colex:boolean, \n clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens a five-dimensional nested array according to a callback function\n and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array, colex:boolean, clbk:Function[, \n thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array, colex:boolean, \n out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n Flattens an n-dimensional nested array according to a callback function and\n assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a two-dimensional\n nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a three-\n dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a four-\n dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n Reverses the order of elements along the last dimension of a five-\n dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n Reverses the order of elements along the first dimension of a two-\n dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a\n three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a four-\n dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n Reverses the order of elements along the second-to-last dimension of a five-\n dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array )\n Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array )\n Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array )\n Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array )\n Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array )\n Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array )\n Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n Computes the arcsecant (in degrees) of a double-precision floating-point\n number.\n","base.asecdf":"\nbase.asecdf( x:number )\n Computes the arcsecant (in degrees) of a single-precision floating-point\n number.\n","base.asecf":"\nbase.asecf( x:number )\n Computes the inverse (arc) secant of a single-precision\n floating-point number.\n","base.asech":"\nbase.asech( x:number )\n Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n Computes the arcsine (in degrees) of a double-precision floating-point\n number.\n","base.asindf":"\nbase.asindf( x:number )\n Computes the arcsine (in degrees) of a single-precision floating-point\n number.\n","base.asinf":"\nbase.asinf( x:number )\n Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n Computes the angle in the plane (in radians) between the positive x-axis and\n the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n Computes the arctangent (in degrees) of a double-precision floating-point\n number.\n","base.atanf":"\nbase.atanf( x:number )\n Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n Computes the hyperbolic arctangent of a double-precision floating-point\n number.\n","base.avercos":"\nbase.avercos( x:number )\n Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array )\n Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array )\n Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array )\n Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array )\n Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array )\n Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n Generates a linearly spaced numeric array whose elements increment by 1\n starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n Fills an array with linearly spaced numeric elements which increment by 1\n starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n upper:boolean]] )\n Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n Computes the absolute value of a double-precision complex floating-point\n number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n Computes the squared absolute value of a double-precision complex floating-\n point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n Computes the squared absolute value of a single-precision complex floating-\n point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n Computes the absolute value of a single-precision complex floating-point\n number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n Adds two double-precision complex floating-point numbers.\n","base.cadd.assign":"\nbase.cadd.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two double-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.cadd.strided":"\nbase.cadd.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n Adds two single-precision complex floating-point numbers.\n","base.caddf.assign":"\nbase.caddf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Adds two single-precision complex floating-point numbers and assigns results\n to a provided output array.\n","base.caddf.strided":"\nbase.caddf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Adds two single-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.camelcase":"\nbase.camelcase( str:string )\n Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n Rounds each component of a single-precision complex floating-point number\n toward positive infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n Rounds each component of a double-precision complex number to the nearest\n multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n Evaluates the cis function for a double-precision complex floating-point\n number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n Divides two double-precision complex floating-point numbers.\n","base.cdiv.assign":"\nbase.cdiv.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Divides two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cdiv.strided":"\nbase.cdiv.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Divides two double-precision complex floating-point numbers stored in real-\n valued strided array views and assigns results to a provided strided output\n array.\n","base.ceil":"\nbase.ceil( x:number )\n Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward positive\n infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward positive\n infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward positive infinity with\n `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n Evaluates the exponential function for a double-precision complex floating-\n point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n Returns a double-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n Returns a single-precision complex floating-point number with the same\n magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n Rounds a double-precision complex floating-point number toward negative\n infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n Evaluates the identity function for a double-precision complex floating-\n point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n Evaluates the identity function for a single-precision complex floating-\n point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n Computes the inverse of a double-precision complex floating-point number.\n","base.cinvf":"\nbase.cinvf( z:Complex64 )\n Computes the inverse of a single-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n Multiplies two double-precision complex floating-point numbers.\n","base.cmul.assign":"\nbase.cmul.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two double-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmul.strided":"\nbase.cmul.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two double-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n Multiplies two single-precision complex floating-point numbers.\n","base.cmulf.assign":"\nbase.cmulf.assign( re1:number, im1:number, re2:number, im2:number, \n out:ArrayLikeObject, strideOut:integer, offsetOut:integer )\n Multiplies two single-precision complex floating-point numbers and assigns\n results to a provided output array.\n","base.cmulf.strided":"\nbase.cmulf.strided( z1:ArrayLikeObject, sz1:integer, oz1:integer, \n z2:ArrayLikeObject, sz2:integer, oz2:integer, out:ArrayLikeObject, \n so:integer, oo:integer )\n Multiplies two single-precision complex floating-point numbers stored in\n real-valued strided array views and assigns results to a provided strided\n output array.\n","base.cneg":"\nbase.cneg( z:Complex128 )\n Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z:Complex64 )\n Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n Evaluates the continued fraction approximation for the supplied series\n generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n Computes the argument of a double-precision complex floating-point number\n in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n Returns the absolute value and phase of a double-precision complex\n floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns the absolute value and phase of a double-precision complex\n floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n Rounds each component of a double-precision complex floating-point number\n to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n Rounds each component of a double-precision complex floating-point number\n to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n Computes the cosecant of an angle measured in degrees.\n","base.csch":"\nbase.csch( x:number )\n Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n Evaluates the signum function of a double-precision complex floating-point\n number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for an arcsine\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an arcsine distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of an arcsine distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an arcsine distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of an arcsine distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for an arcsine distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for an arcsine distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of an arcsine\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n Returns the entropy of a Bernoulli distribution with success probability\n `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n Returns the excess kurtosis of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n Returns the expected value of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a Bernoulli\n distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a Bernoulli distribution\n with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n Evaluates the quantile function for a Bernoulli distribution with success\n probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a Bernoulli\n distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n Returns the skewness of a Bernoulli distribution with success probability\n `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n Returns the standard deviation of a Bernoulli distribution with success\n probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n Returns the variance of a Bernoulli distribution with success probability\n `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta distribution with first shape parameter `α` and second shape\n parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta distribution with first shape parameter `α`\n and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a beta distribution with\n first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n beta distribution with first shape parameter `α` and second shape parameter\n `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta distribution\n with first shape parameter `α` and second shape parameter `β` at a value\n `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta distribution with first shape\n parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a beta prime distribution with first shape parameter `α` and\n second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a beta prime distribution with first shape parameter `α` and second\n shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a beta prime distribution with first shape\n parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`\n at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a beta prime distribution with first shape parameter `α` and second shape\n parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a beta prime distribution with first\n shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a beta prime\n distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n Evaluates the cumulative distribution function (CDF) for a binomial\n distribution with number of trials `n` and success probability `p` at a\n value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a binomial distribution with number of trials `n` and success probability\n `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n binomial distribution with number of trials `n` and success probability `p`\n at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a binomial distribution with number of trials `n` and\n success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n Evaluates the moment-generating function (MGF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n Evaluates the probability mass function (PMF) for a binomial distribution\n with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n Evaluates the quantile function for a binomial distribution with number of\n trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n Returns a function for evaluating the quantile function of a binomial\n distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n Evaluates the cumulative distribution function (CDF) for a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a Cauchy distribution with location parameter `x0` and scale parameter\n `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a Cauchy distribution with location parameter\n `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n Evaluates the probability density function (PDF) for a Cauchy distribution\n with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n Evaluates the quantile function for a Cauchy distribution with location\n parameter `x0` and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n Returns a function for evaluating the quantile function of a Cauchy\n distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi distribution\n with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi distribution with\n degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n Evaluates the quantile function for a chi distribution with degrees of\n freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi\n distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n Evaluates the cumulative distribution function (CDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n Returns a chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a chi-squared distribution with degrees of freedom\n `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n Evaluates the moment-generating function (MGF) for a chi-squared\n distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n Evaluates the probability density function (PDF) for a chi-squared\n distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n Returns a function for evaluating the probability density function (PDF) of\n a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n Evaluates the quantile function for a chi-squared distribution with degrees\n of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n Returns a function for evaluating the quantile function of a chi-squared\n distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a raised cosine distribution with location parameter `μ` and scale\n parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a raised cosine distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n Returns the expected value of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n Returns the median of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n Returns the mode of a raised cosine distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a raised cosine\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a raised cosine distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a raised cosine distribution with\n location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a raised cosine\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n Returns the skewness of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n Returns the standard deviation of a raised cosine distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n Returns the variance of a raised cosine distribution with location parameter\n `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n Evaluates the cumulative distribution function (CDF) for a degenerate\n distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n Evaluates the natural logarithm of the probability density function (logPDF)\n for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n Returns the expected value of a degenerate distribution with constant value\n `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n Evaluates the moment-generating function (MGF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n Evaluates the probability density function (PDF) for a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n Evaluates the probability mass function (PMF) for a degenerate distribution\n with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n Returns a function for evaluating the quantile function of a degenerate\n distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n Returns the standard deviation of a degenerate distribution with constant\n value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n Evaluates the cumulative distribution function (CDF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a discrete uniform distribution with minimum support `a` and\n maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a discrete uniform distribution with minimum\n support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n discrete uniform distribution with minimum support `a` and maximum support\n `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a discrete uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n Evaluates the moment-generating function (MGF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n Returns a function for evaluating the moment-generating function (MGF)\n of a discrete uniform distribution with minimum support `a` and maximum\n support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n Evaluates the probability mass function (PMF) for a discrete uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n Returns a function for evaluating the probability mass function (PMF) of\n a discrete uniform distribution with minimum support `a` and maximum support\n `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n Evaluates the quantile function for a discrete uniform distribution with\n minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n Returns a function for evaluating the quantile function of a discrete\n uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an Erlang\n distribution with shape parameter `k` and rate parameter `λ` at a value\n `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of an Erlang distribution with shape parameter `k`\n and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of an\n Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for an Erlang distribution\n with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF)\n of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for an Erlang distribution with shape\n parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of an Erlang\n distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for an exponential distribution with rate parameter `λ` at a value\n `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) for an exponential distribution with rate\n parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an exponential distribution with rate parameter\n `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n Evaluates the moment-generating function (MGF) for an exponential\n distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) for\n an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n Evaluates the probability density function (PDF) for an exponential\n distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n Returns a function for evaluating the probability density function (PDF)\n for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n Evaluates the quantile function for an exponential distribution with rate\n parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function for an exponential\n distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n Evaluates the cumulative distribution function (CDF) for an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n Evaluates the probability density function (PDF) for an F distribution with\n numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n Returns a function for evaluating the probability density function (PDF) of\n an F distribution with numerator degrees of freedom `d1` and denominator\n degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n Evaluates the quantile function for an F distribution with numerator degrees\n of freedom `d1` and denominator degrees of freedom `d2` at a probability\n `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n Returns a function for evaluating the quantile function of an F distribution\n with numerator degrees of freedom `d1` and denominator degrees of freedom\n `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n Evaluates the cumulative distribution function (CDF) for a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n Returns the differential entropy of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n Returns the excess kurtosis of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Fréchet distribution with shape parameter `α`, scale parameter `s`,\n and location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n Returns the expected value of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n Returns the median of a Fréchet distribution with shape parameter\n `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n Evaluates the probability density function (PDF) for a Fréchet distribution\n with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n Evaluates the quantile function for a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n Returns a function for evaluating the quantile function of a Fréchet\n distribution with shape parameter `α`, scale parameter `s`, and location\n `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n Returns the skewness of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n Returns the standard deviation of a Fréchet distribution with shape\n parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n Returns the variance of a Fréchet distribution with shape parameter `α`,\n scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a gamma\n distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a gamma distribution with shape parameter `α` and rate parameter\n `β` at a value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a gamma distribution with shape parameter `α`\n and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a gamma distribution with shape parameter `α` and rate parameter `β` at\n a value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a gamma distribution with shape parameter `α` and rate\n parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n Evaluates the moment-generating function (MGF) for a gamma distribution with\n shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a gamma distribution\n with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a gamma distribution with shape\n parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a gamma\n distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a geometric\n distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n Returns the entropy of a geometric distribution with success probability\n `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n Returns the excess kurtosis of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a geometric distribution with success probability `p` at a value\n `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n Returns a function for evaluating the logarithm of the probability mass\n function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n Returns the expected value of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n Evaluates the moment-generating function (MGF) for a geometric\n distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n Evaluates the probability mass function (PMF) for a geometric distribution\n with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n Evaluates the quantile function for a geometric distribution with success\n probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n Returns a function for evaluating the quantile function of a geometric\n distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n Returns the skewness of a geometric distribution with success probability\n `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n Returns the standard deviation of a geometric distribution with success\n probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n Returns the variance of a geometric distribution with success probability\n `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Gumbel\n distribution with location parameter `μ` and scale parameter `β` at a value\n `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n Returns the differential entropy of a Gumbel distribution with location\n parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n Returns the excess kurtosis of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Gumbel distribution with location parameter `μ` and scale\n parameter `β` at a value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Gumbel distribution with location parameter `μ` and scale parameter\n `β` at a value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n Returns the expected value of a Gumbel distribution with location parameter\n `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n Returns the median of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n Evaluates the moment-generating function (MGF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n Returns the mode of a Gumbel distribution with location parameter `μ` and\n scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n Evaluates the probability density function (PDF) for a Gumbel distribution\n with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Gumbel distribution with location parameter `μ` and scale parameter\n `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n Evaluates the quantile function for a Gumbel distribution with location\n parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n Returns a function for evaluating the quantile function of a Gumbel\n distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n Returns the skewness of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n Returns the standard deviation of a Gumbel distribution with location\n parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n Returns the variance of a Gumbel distribution with location parameter `μ`\n and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n Evaluates the cumulative distribution function (CDF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a hypergeometric distribution with population size `N`, subpopulation\n size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a hypergeometric distribution with population size\n `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n Evaluates the probability mass function (PMF) for a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the probability mass function (PMF) of a\n hypergeometric distribution with population size `N`, subpopulation size\n `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n Evaluates the quantile function for a hypergeometric distribution with\n population size `N`, subpopulation size `K`, and number of draws `n` at a\n probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n Returns a function for evaluating the quantile function of a hypergeometric\n distribution with population size `N`, subpopulation size `K`, and number of\n draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for an inverse gamma distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for an inverse gamma\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF)\n of an inverse gamma distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for an inverse gamma distribution with shape\n parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of an inverse gamma\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for Kumaraswamy's double bounded distribution with first shape\n parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Kumaraswamy's double bounded distribution\n with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for Kumaraswamy's double bounded distribution with first shape parameter `a`\n and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Kumaraswamy's double bounded distribution with\n first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for Kumaraswamy's double\n bounded distribution with first shape parameter `a` and second shape\n parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Kumaraswamy's double bounded distribution with first shape parameter\n `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a Kumaraswamy's double bounded\n distribution with first shape parameter `a` and second shape parameter `b`\n at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a Kumaraswamy's\n double bounded distribution with first shape parameter `a` and second shape\n parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n Returns the standard deviation of a Kumaraswamy's double bounded\n distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n Returns the differential entropy of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n Returns the excess kurtosis of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Laplace distribution with scale parameter `b` and location\n parameter `μ` at a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Laplace distribution with scale parameter\n `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Laplace distribution with scale parameter `b` and location parameter\n `μ` at a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Laplace distribution with scale parameter `b` and\n location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n Returns the expected value of a Laplace distribution with location parameter\n `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n Returns the median of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n Evaluates the moment-generating function (MGF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n Returns the mode of a Laplace distribution with location parameter `μ` and\n scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n Evaluates the probability density function (PDF) for a Laplace\n distribution with scale parameter `b` and location parameter `μ` at a\n value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Laplace distribution with scale parameter `b` and location parameter\n `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n Evaluates the quantile function for a Laplace distribution with scale\n parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n Returns a function for evaluating the quantile function of a Laplace\n distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n Returns the skewness of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n Returns the standard deviation of a Laplace distribution with location\n parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n Returns the variance of a Laplace distribution with location parameter `μ`\n and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n Returns the differential entropy of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Lévy distribution with location parameter `μ` and scale\n parameter `c` at a value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Lévy distribution with location parameter `μ` and scale parameter `c`\n at a value `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Lévy distribution with location parameter `μ` and scale\n parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n Returns the expected value of a Lévy distribution with location parameter\n `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n Returns the median of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n Returns the mode of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n Evaluates the probability density function (PDF) for a Lévy distribution\n with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n Evaluates the quantile function for a Lévy distribution with location\n parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n Returns a function for evaluating the quantile function of a Lévy\n distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n Returns the standard deviation of a Lévy distribution with location\n parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n Returns the variance of a Lévy distribution with location parameter `μ` and\n scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n Evaluates the cumulative distribution function (CDF) for a logistic\n distribution with location parameter `μ` and scale parameter `s` at a value\n `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n Returns the differential entropy of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n Returns the excess kurtosis of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a logistic distribution with location parameter `μ` and scale\n parameter `s` at a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a logistic distribution with location parameter `μ` and scale parameter\n `s` at a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n Returns the expected value of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n Returns the median of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n Evaluates the moment-generating function (MGF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a Logistic distribution with location parameter `μ` and scale parameter\n `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n Returns the mode of a logistic distribution with location parameter `μ` and\n scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n Evaluates the probability density function (PDF) for a logistic distribution\n with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n Evaluates the quantile function for a logistic distribution with location\n parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n Returns a function for evaluating the quantile function of a logistic\n distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n Returns the skewness of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n Returns the standard deviation of a logistic distribution with location\n parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n Returns the variance of a logistic distribution with location parameter `μ`\n and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n Returns the differential entropy of a lognormal distribution with location\n `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a lognormal distribution with location parameter `μ` and scale\n parameter `σ` at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a lognormal distribution with location\n parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a lognormal distribution with location parameter `μ` and scale parameter\n `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a lognormal distribution with location parameter\n `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n Returns the expected value of a lognormal distribution with location `μ` and\n scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n Returns the median of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n Returns the mode of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a lognormal\n distribution with location parameter `μ` and scale parameter `σ` at a value\n `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a lognormal distribution with location parameter `μ` and scale parameter\n `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a lognormal distribution with location\n parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function of a lognormal\n distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n Returns the skewness of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n Returns the standard deviation of a lognormal distribution with location `μ`\n and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n Returns the variance of a lognormal distribution with location `μ` and scale\n `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n Evaluates the cumulative distribution function (CDF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a negative binomial distribution with number of successes until\n experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a negative binomial distribution with number of\n successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n Evaluates the moment-generating function (MGF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n Evaluates the probability mass function (PMF) for a negative binomial\n distribution with number of successes until experiment is stopped `r` and\n success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n Returns a function for evaluating the probability mass function (PMF) of a\n negative binomial distribution with number of successes until experiment is\n stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n Evaluates the quantile function for a negative binomial distribution with\n number of successes until experiment is stopped `r` and success probability\n `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n Returns a function for evaluating the quantile function of a negative\n binomial distribution with number of successes until experiment is stopped\n `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n Evaluates the cumulative distribution function (CDF) for a normal\n distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n Returns the differential entropy of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n Returns the excess kurtosis of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a normal distribution with mean `μ` and standard deviation `σ` at a\n value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n Returns the expected value of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n Returns the median of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n Evaluates the moment-generating function (MGF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n Returns the mode of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n Evaluates the probability density function (PDF) for a normal distribution\n with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n Evaluates the quantile function for a normal distribution with mean `μ` and\n standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n Returns a function for evaluating the quantile function\n of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n Returns the skewness of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n Returns the standard deviation of a normal distribution with mean `μ` and\n standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n Returns the variance of a normal distribution with mean `μ` and standard\n deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n Returns the differential entropy of a Pareto (Type I) distribution\n (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Pareto (Type I) distribution with shape parameter `α` and scale\n parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Pareto (Type I) distribution with shape\n parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n Evaluates the probability density function (PDF) for a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β` at a value\n `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n Evaluates the quantile function for a Pareto (Type I) distribution with\n shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n Returns a function for evaluating the quantile function of a Pareto (Type I)\n distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n Evaluates the natural logarithm of the probability mass function (PMF) for a\n Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n Returns a function for evaluating the natural logarithm of the probability\n mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Poisson distribution\n with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n Evaluates the probability mass function (PMF) for a Poisson\n distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n Returns a function for evaluating the probability mass function (PMF)\n of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n Evaluates the quantile function for a Poisson distribution with mean\n parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n Returns a function for evaluating the quantile function of a Poisson\n distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n Evaluates the cumulative distribution function (CDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Rayleigh distribution with scale parameter `sigma` at a value\n `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Rayleigh distribution with scale parameter\n `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n Evaluates the probability density function (PDF) for a Rayleigh\n distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n Evaluates the quantile function for a Rayleigh distribution with scale\n parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n Returns a function for evaluating the quantile function of a Rayleigh\n distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n Evaluates the cumulative distribution function (CDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n Evaluates the probability density function (PDF) for the distribution of\n the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n Returns a function for evaluating the probability density function (PDF)\n of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n Evaluates the quantile function for the Wilcoxon signed rank test statistic\n with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n Returns a function for evaluating the quantile function of the Wilcoxon\n signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the cumulative distribution function (CDF) of a studentized range\n distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n nranges:integer] )\n Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n nranges:integer] )\n Returns a function for evaluating the quantile function of a studentized\n range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n Evaluates the cumulative distribution function (CDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a Student's t distribution with degrees of\n freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n Evaluates the probability density function (PDF) for a Student's t\n distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n Returns a function for evaluating the probability density function (PDF)\n of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n Evaluates the quantile function for a Student's t distribution with degrees\n of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n Returns a function for evaluating the quantile function of a Student's t\n distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n Evaluates the cumulative distribution function (CDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a triangular distribution with minimum support `a`, maximum\n support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the cumulative\n distribution function (CDF) of a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a triangular distribution with minimum support `a`, maximum support `b`,\n and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the natural logarithm of the probability\n density function (PDF) of a triangular distribution with minimum support\n `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n Evaluates the moment-generating function (MGF) for a triangular distribution\n with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n Evaluates the probability density function (PDF) for a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c` at\n a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n Returns a function for evaluating the probability density function (PDF) of\n a triangular distribution with minimum support `a`, maximum support `b`, and\n mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n Evaluates the quantile function for a triangular distribution with minimum\n support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n Returns a function for evaluating the quantile function of a triangular\n distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n Evaluates the cumulative distribution function (CDF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a uniform distribution with minimum support `a` and maximum\n support `b` at a value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a uniform distribution with minimum support\n `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a uniform distribution with minimum support `a` and maximum support `b`\n at a value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a uniform distribution with minimum support `a` and\n maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n Evaluates the moment-generating function (MGF) for a uniform\n distribution with minimum support `a` and maximum support `b` at a value\n `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n Returns a function for evaluating the moment-generating function (MGF)\n of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n Evaluates the probability density function (PDF) for a uniform distribution\n with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n Returns a function for evaluating the probability density function (PDF) of\n a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n Evaluates the quantile function for a uniform distribution with minimum\n support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n Returns a function for evaluating the quantile function of a uniform\n distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n Evaluates the cumulative distribution function (CDF) for a Weibull\n distribution with shape parameter `k` and scale parameter `λ` at a value\n `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n Returns a function for evaluating the cumulative distribution function (CDF)\n of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the cumulative distribution function\n (CDF) for a Weibull distribution with shape parameter `k` and scale\n parameter `λ` at a value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n Returns a function for evaluating the logarithm of the cumulative\n distribution function (CDF) of a Weibull distribution with scale parameter\n `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n Evaluates the natural logarithm of the probability density function (PDF)\n for a Weibull distribution with shape parameter `k` and scale parameter `λ`\n at a value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n Returns a function for evaluating the logarithm of the probability density\n function (PDF) of a Weibull distribution with shape parameter `k` and scale\n parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n Evaluates the moment-generating function (MGF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n Returns a function for evaluating the moment-generating function (MGF) of a\n Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n Evaluates the probability density function (PDF) for a Weibull distribution\n with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n Returns a function for evaluating the probability density function (PDF) of\n a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n Evaluates the quantile function for a Weibull distribution with scale\n parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n Returns a function for evaluating the quantile function of a Weibull\n distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers in units of double-\n precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n Evaluates the Dirichlet eta function for a double-precision\n floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array, x:number )\n Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array )\n Returns a function for evaluating a polynomial using double-precision\n floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array, Q:Array, x:number )\n Evaluates a rational function using double-precision floating-point\n arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array, Q:Array )\n Returns a function for evaluating a rational function using double-precision\n floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n Returns an integer corresponding to the unbiased exponent of a double-\n precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n Returns an integer corresponding to the unbiased exponent of a single-\n precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n Returns a double-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n Returns a single-precision floating-point number with the magnitude of `x`\n and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n Converts a single-precision floating-point number to a signed 32-bit\n integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n Converts a single-precision floating-point number to a unsigned 32-bit\n integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n Converts a double-precision floating-point number to the nearest single-\n precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n Converts a double-precision floating-point number to a signed 32-bit\n integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Converts an integer-valued double-precision floating-point number to a\n signed 64-bit integer byte array according to host byte order (endianness)\n and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n Converts a double-precision floating-point number to a unsigned 32-bit\n integer.\n","base.floor":"\nbase.floor( x:number )\n Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward negative\n infinity.\n","base.floorf":"\nbase.floorf( x:number )\n Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n Rounds a double-precision floating-point number to the nearest multiple of\n `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward negative infinity with\n `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each Unicode code point in a string, iterating from\n right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each grapheme cluster (i.e., user-perceived\n character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n Invokes a function for each UTF-16 code unit in a string, iterating from\n right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n Tokenize a string into an array of string parts and format identifier\n objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array, stride:integer, \n offset:integer )\n Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array, stride:integer, offset:integer )\n Splits a double-precision floating-point number into a normalized fraction\n and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n Creates a double-precision floating-point number from a literal bit\n representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n Creates a single-precision floating-point number from an IEEE 754 literal\n bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Converts a signed 64-bit integer byte array to a double-precision floating-\n point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n Creates a single-precision floating-point number from an unsigned integer\n corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n Creates a double-precision floating-point number from a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n Calculates the scaled Lanczos sum for the approximation of the gamma\n function.\n","base.gammaln":"\nbase.gammaln( x:number )\n Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the more significant 32\n bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n Returns an unsigned 32-bit integer corresponding to the less significant 32\n bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n Evaluates the identity function for a double-precision floating-point number\n `x`.\n","base.identityf":"\nbase.identityf( x:number )\n Evaluates the identity function for a single-precision floating-point number\n `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n Multiplies two signed 32-bit integers and returns an array of two signed 32-\n bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two signed 32-bit integers and assigns results representing the\n signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n Computes the multiplicative inverse of a double-precision floating-point\n number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n Computes the multiplicative inverse of a single-precision floating-point\n number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a negative\n finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a negative\n integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonnegative\n finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonnegative\n integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a nonpositive\n finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a nonpositive\n integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n Tests if a double-precision floating-point numeric value is a positive\n finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n Tests if a finite double-precision floating-point number is a positive\n integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n upper:boolean )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n Computes the cosine of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n Evaluates a correction term for double-precision base-2 and base-10\n logarithms when `1+f` is in `[√2/2, √2]`.\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n Computes the tangent of a double-precision floating-point number on the\n interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n Computes an absolute value of a signed 32-bit integer in two's complement\n format.\n","base.last":"\nbase.last( str:string, n:integer )\n Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n Multiplies a double-precision floating-point number by an integer power of\n two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Returns the minimum and maximum absolute values and assigns results to a\n provided output array.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n out:Array|TypedArray|Object, stride:integer, offset:integer )\n Returns the minimum and maximum values and assigns results to a provided\n output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Decomposes a double-precision floating-point number into integral and\n fractional parts, each having the same type and sign as the input value,\n and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string )\n Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toLocaleString":"\nbase.ndarray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an ndarray as a locale-aware string.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in an input ndarray and assigns results\n to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string|DataType, shape:ArrayLikeObject, \n order:string )\n Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp`\n and assigns results to a provided output array.\n","base.normalizeMultiSlice":"\nbase.normalizeMultiSlice( slice:MultiSlice, shape:Array, \n strict:boolean )\n Returns a normalized MultiSlice object.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n Evaluates a normalized Hermite polynomial using double-precision floating-\n point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n Returns a function for evaluating a normalized Hermite polynomial using\n double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n Returns a linear congruential pseudorandom number generator (LCG) whose\n output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n Computes the reciprocal cube root of a double-precision floating-point\n number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n Computes the reciprocal cube root of a single-precision floating-point\n number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the first occurrence of a specified search\n string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring after the last occurrence of a specified search\n string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the first occurrence of a specified search\n string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n fromIndex:integer )\n Replaces the substring before the last occurrence of a specified search\n string.\n","base.reverse":"\nbase.reverse( str:string )\n Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n Reverses the grapheme clusters (i.e., user-perceived characters) of a\n string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n Right pads a string such that the padded string has a length of at least\n `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n Rounds a double-precision floating-point number to the nearest value with\n `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n Computes the reciprocal square root of a double-precision floating-point\n number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n Computes the reciprocal square root of a single-precision floating-point\n number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n Creates a MultiSlice object from a comma-separated list of string-serialized\n MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string|DataType, order:string )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array, strict:boolean )\n Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n Sets the more significant 32 bits of a double-precision floating-point\n number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n Sets the less significant 32 bits of a double-precision floating-point\n number.\n","base.sici":"\nbase.sici( x:number )\n Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Computes the sine and cosine integrals and assigns results to a provided\n output array.\n","base.signbit":"\nbase.signbit( x:number )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n Returns an integer corresponding to the significand of a single-precision\n floating-point number.\n","base.signum":"\nbase.signum( x:number )\n Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n Simultaneously computes the sine and cosine of an angle measured in radians.\n","base.sincos.assign":"\nbase.sincos.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of an angle measured in radians\n and assigns the results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Simultaneously computes the sine and cosine of a number times π and\n assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n Computes the principal square root of a double-precision floating-point\n number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n Computes the principal square root of a single-precision floating-point\n number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n Computes the principal square root of the product of π and a positive\n double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a binary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike, dtypes3:ArrayLike[, options:Object] )\n Generates a list of binary interface signatures from strided array data\n types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Copies values from one single-precision complex floating-point vector to\n another single-precision complex floating-point vector using alternative\n indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer, fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision complex floating-point\n strided input array and assigns results to a single-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n y:Complex64Array, strideY:integer )\n Interchanges two single-precision complex floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision complex floating-point vectors using\n alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of a strided array using alternative\n indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of a strided array using alternative\n indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of a strided array using\n alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each double-precision floating-point strided\n array element and computes the sum using ordinary recursive summation\n and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n strideX:integer )\n Adds a scalar constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each double-precision floating-point strided array\n element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a double-precision floating-point\n strided array `x` and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of double-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of double-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided\n array elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of double-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the dot product of two double-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Fills a double-precision floating-point strided array with a specified\n scalar constant using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array and assigns results to a double-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, z:Float64Array, sz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays and assigns results to a double-precision floating-point strided\n output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmaxabsSorted":"\nbase.strided.dmaxabsSorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array.\n","base.strided.dmaxabsSorted.ndarray":"\nbase.strided.dmaxabsSorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmaxSorted":"\nbase.strided.dmaxSorted( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmaxSorted.ndarray":"\nbase.strided.dmaxSorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n strideX:integer, out:Float64Array, strideOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and standard deviation of a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n offsetOut:integer )\n Computes the mean and variance of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmedianSorted":"\nbase.strided.dmedianSorted( N:integer, x:Float64Array, strideX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array.\n","base.strided.dmedianSorted.ndarray":"\nbase.strided.dmedianSorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted double-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a double-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Converts each element in a double-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a double-precision floating-point strided input\n array according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to double-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a double-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a double-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a double-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float64Array, sy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n sy:integer, oy:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a double-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of double-precision floating-\n point strided array elements, ignoring `NaN` values and using ordinary\n recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using pairwise summation and alternative\n indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a double-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a double-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a double-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a double-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a double-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a double-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a double-precision floating-\n point strided array `x` and assigns the results to elements in a double-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the range of a double-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Reverses a double-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using extended accumulation and returning\n an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a constant to each single-precision floating-point strided array\n element, and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics and returning an extended\n precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n stride:integer, offset:integer )\n Multiplies a double-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation and\n result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass trial mean algorithm and alternative\n indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a two-pass algorithm and alternative indexing\n semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass textbook algorithm and alternative\n indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard error of the mean for a double-precision floating-\n point strided array using a one-pass algorithm proposed by Youngs and Cramer\n and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and returning an extended precision\n result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm with extended accumulation\n and alternative indexing semantics and returning an extended precision\n result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using ordinary recursive summation with\n extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using a two-pass error correction algorithm\n with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values, using Welford's algorithm with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm with extended\n accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n out:Float64Array, strideOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation, and returning an\n extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using extended accumulation and alternative\n indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using ordinary recursive summation with extended\n accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation with extended\n accumulation and alternative indexing semantics, and returning an extended\n precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation,\n and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values, using pairwise summation with extended accumulation\n and alternative indexing semantics, and returning an extended precision\n result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n strideX:integer, y:Float64Array, strideY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two double-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, strideX:integer )\n Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, \n strideX:integer )\n Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Sorts a double-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n stride:integer, offset:integer )\n Sorts a double-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a double-precision\n floating-point strided array `x` and assigns the results to elements in a\n double-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics and returning\n an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and returning\n an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation with extended accumulation and\n alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and returning an\n extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a double-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, strideX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer )\n Computes the sum of double-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using extended accumulation and alternative indexing semantics and\n returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and returning an\n extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm with extended accumulation and alternative\n indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n strideY:integer )\n Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Interchanges two double-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n y:Float64Array, strideY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n Rounds each element in a double-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a double-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n Returns the data type string associated with a strided array data type\n enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n Returns the enumeration constant associated with a supported strided array\n data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n Returns the enumeration constant associated with a strided array data type\n string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, correction:number, mean:number, x:Float64Array, \n strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using Neely's correction algorithm and alternative\n indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, correction:number, mean:number, \n x:Float64Array, strideX:integer, offsetX:integer )\n Computes the variance of a double-precision floating-point strided array\n provided a known mean and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a strided array using alternative\n indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each strided array element and computes the sum\n using pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using alternative\n indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using an improved\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using ordinary\n recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of strided array elements using pairwise\n summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n y:Array|TypedArray, strideY:integer )\n Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n Computes the dot product of two vectors using alternative indexing\n semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, strideX:integer )\n Fills a strided array with a specified scalar constant.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer )\n Fills a strided array with a specified scalar constant using alternative\n indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, strideX:integer, \n clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, clbk:Function[, thisArg:any] )\n Fills a strided array according to a provided callback function and using\n alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n out:Array|TypedArray, strideOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n offsetOut:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n a second-order iterative Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and\n pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements, ignoring `NaN` values and using\n pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n offset:integer )\n Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, strideX:integer )\n Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer )\n Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer )\n Multiplies a vector by a scalar constant.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Multiplies a vector by a scalar constant using alternative indexing\n semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, y:Array|TypedArray, strideY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two strided arrays based on the sort order of the first\n array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using insertion sort and alternative indexing\n semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n strideX:integer )\n Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using alternative indexing\n semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the sum of strided array elements using pairwise summation and\n alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n y:ArrayLikeObject, strideY:integer )\n Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n clbk:Function[, thisArg:any] )\n Applies a binary function to each pair of elements retrieved from strided\n input arrays according to a callback function and assigns results to a\n strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array using alternative indexing\n semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the maximum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the maximum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using alternative indexing\n semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using an improved Kahan–\n Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a second-order\n iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using ordinary recursive\n summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using a two-pass error\n correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using pairwise summation and\n alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the median value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n obj:Object|Function, bool:boolean )\n Defines non-enumerable read-only properties which expose strided array\n function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array using alternative indexing\n semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array using alternative\n indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the minimum value of a strided array via a callback function and\n using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted strided array using alternative\n indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n Returns the minimum accessible index based on a set of provided strided\n array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask and using\n alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array and assigns results to elements in a\n strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array according to\n elements in a strided mask array, and assigns results to elements in a\n strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of masked unary interface signatures from strided array\n data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n signatures:ArrayLike )\n Assigns callbacks to masked unary interfaces according to type promotion\n rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the maximum value of strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the maximum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a strided array, ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a strided array, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Computes the minimum value of a strided array via a callback function,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the maximum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the maximum value of a strided array according to a mask,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the minimum value of a strided array according to a mask and\n ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the minimum value of a strided array according to a mask, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n mask:Array|TypedArray, strideMask:integer )\n Computes the range of a strided array according to a mask and ignoring `NaN`\n values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n offsetMask:integer )\n Computes the range of a strided array according to a mask, ignoring `NaN`\n values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array, ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function, ignoring\n `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function, ignoring\n `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array ignoring `NaN` values and\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using\n Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array ignoring `NaN` values and using a\n one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a nullary callback and assigns results to elements in a strided\n output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n Returns a typed array view having the same data type as a provided input\n typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quaternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a quinary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, strideX:integer )\n Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n offsetX:integer )\n Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, strideX:integer, \n clbk:Function[, thisArg:any] )\n Computes the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n strideX:integer, offsetX:integer, clbk:Function[, thisArg:any] )\n Calculates the range of a strided array via a callback function and using\n alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n offset:integer )\n Returns a real-valued floating-point array view of a complex-valued\n floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each element in a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using an improved Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using a second-order iterative\n Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided\n array element and computes the sum using pairwise summation and alternative\n indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of absolute values (L1 norm) of single-precision floating-\n point strided array elements using pairwise summation and alternative\n indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cube root of each element in a single-precision floating-point \n strided array `x` and assigns the results to elements in a single-precision \n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative maximum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum of single-precision floating-point strided\n array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the cumulative minimum absolute value of single-precision floating-\n point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using a second-order iterative Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using ordinary recursive summation and alternative indexing\n semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the cumulative sum of single-precision floating-point strided array\n elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n strideX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Adds a scalar constant to each single-precision floating-point strided array\n element and computes the sum using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the dot product of two single-precision floating-point vectors with\n extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Computes the dot product of two single-precision floating-point vectors\n using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation with extended accumulation and\n alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation with\n extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using extended accumulation and alternative\n indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation with extended\n accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation with extended accumulation and alternative indexing\n semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Fills a single-precision floating-point strided array with a specified\n scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, z:Float32Array, sz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays and assigns results to a single-precision floating-point strided\n output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a sorted single-precision floating-\n point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a one-pass trial mean algorithm with pairwise summation and\n alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using a two-pass error correction algorithm and alternative indexing\n semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the median value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the mid-range of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a sorted single-precision floating-point\n strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the absolute value for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the squared absolute value for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point\n strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the cube root for each element in a single-precision floating-point\n strided array `x` according to a strided mask array and assigns the results\n to elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward positive infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Converts each element in a single-precision floating-point strided array `x`\n from degrees to radians according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward negative infinity according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the multiplicative inverse for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n oy:integer, fcn:Function )\n Applies a unary function to a single-precision floating-point strided input\n array according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n Applies a binary function to single-precision floating-point strided input\n arrays according to a strided mask array and assigns results to a single-\n precision floating-point strided output array using alternative indexing\n semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` according to a strided mask array and assigns the\n results to elements in a single-precision floating-point strided array `y`\n using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` according to a strided mask array and\n assigns the results to elements in a single-precision floating-point strided\n array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n sm:integer, y:Float32Array, sy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n sy:integer, oy:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero according to a strided mask array and assigns the results to\n elements in a single-precision floating-point strided array `y` using\n alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the maximum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using ordinary recursive summation and\n alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction\n algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using a two-pass error correction algorithm\n and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, strideX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the arithmetic mean of a single-precision floating-point strided\n array, ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum value of a single-precision floating-point strided\n array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the minimum absolute value of a single-precision floating-point\n strided array, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the maximum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the minimum value of a single-precision floating-point strided\n array according to a mask, ignoring `NaN` values and using alternative\n indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n mask:Uint8Array, strideMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n Computes the range of a single-precision floating-point strided array\n according to a mask, ignoring `NaN` values and using alternative indexing\n semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using Welford's algorithm and alternative\n indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n stride:integer, offset:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array ignoring `NaN` values and using a one-pass algorithm proposed by\n Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using ordinary recursive summation and alternative\n indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements,\n ignoring `NaN` values and using pairwise summation and alternative indexing\n semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass trial mean algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a two-pass algorithm and alternative\n indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass textbook algorithm and\n alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using Welford's algorithm and alternative indexing\n semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n stride:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n x:Float32Array, stride:integer, offset:integer )\n Computes the variance of a single-precision floating-point strided array\n ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n offset:integer )\n Computes the L2-norm of a single-precision floating-point vector using\n alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a single-precision floating-\n point strided array `x` and assigns the results to elements in a single-\n precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the range of a single-precision floating-point strided array using\n alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, strideX:integer )\n Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Reverses a single-precision floating-point strided array in-place using\n alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n stride:integer, offset:integer )\n Multiplies a single-precision floating-point vector `x` by a constant\n `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using heapsort and alternative\n indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using insertion sort and\n alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n strideX:integer, y:Float32Array, strideY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n offsetY:integer )\n Simultaneously sorts two single-precision floating-point strided arrays\n based on the sort order of the first array using Shellsort and alternative\n indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, strideX:integer )\n Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Sorts a single-precision floating-point strided array using heapsort and\n alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using insertion sort\n and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n stride:integer, offset:integer )\n Sorts a single-precision floating-point strided array using Shellsort and\n alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a single-precision\n floating-point strided array `x` and assigns the results to elements in a\n single-precision floating-point strided array `y` using alternative indexing\n semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass trial mean algorithm and alternative indexing\n semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass textbook algorithm and alternative indexing\n semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a single-precision floating-point strided\n array using a one-pass algorithm proposed by Youngs and Cramer and\n alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using an improved Kahan–Babuška algorithm and alternative indexing\n semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using a second-order iterative Kahan–Babuška algorithm and alternative\n indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer )\n Computes the sum of single-precision floating-point strided array elements\n using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n strideY:integer )\n Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Interchanges two single-precision floating-point vectors using alternative\n indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using alternative\n indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass trial\n mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a two-pass\n algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass textbook\n algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using Welford's\n algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using Welford's algorithm\n and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer, offsetX:integer )\n Computes the standard deviation of a strided array using a one-pass\n algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n y:Float32Array, strideY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n Rounds each element in a single-precision floating-point strided array `x`\n toward zero and assigns the results to elements in a single-precision\n floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n strideX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n strideX:integer, offsetX:integer )\n Computes the variance of a single-precision floating-point strided array\n using a one-pass algorithm proposed by Youngs and Cramer and alternative\n indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a ternary callback to strided input array elements and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function )\n Applies a unary callback to elements in a strided input array and assigns\n results to elements in a strided output array using alternative indexing\n semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offsets:ArrayLikeObject, fcn:Function, clbk:Function[, thisArg:any] )\n Applies a unary function to each element retrieved from a strided input\n array according to a callback function and assigns results to a strided\n output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike, \n dtypes2:ArrayLike[, options:Object] )\n Generates a list of unary interface signatures from strided array data\n types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike )\n Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using alternative indexing\n semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass trial mean\n algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a two-pass algorithm and\n alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass textbook\n algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass textbook algorithm\n and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using Welford's algorithm and\n alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n strideX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n x:Array|TypedArray, strideX:integer, offsetX:integer )\n Computes the variance of a strided array using a one-pass algorithm proposed\n by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n y:Complex128Array, strideY:integer, fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n fcn:Function )\n Applies a unary function to a double-precision complex floating-point\n strided input array and assigns results to a double-precision complex\n floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n Returns a string giving the literal bit representation of a double-precision\n floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n Returns a string giving the literal bit representation of a single-precision\n floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n Returns a string giving the literal bit representation of an unsigned 8-bit\n integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n Returns a string giving the literal bit representation of an unsigned 16-bit\n integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n Returns a string giving the literal bit representation of an unsigned 32-bit\n integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n offset:integer )\n Splits a double-precision floating-point number into a higher order word\n (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray, writable:boolean )\n Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n Truncates the middle UTF-16 code units of a string to return a string\n having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n Rounds a numeric value to the nearest number toward zero with `n`\n significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( x:integer, y:integer )\n Multiples two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n 32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n stride:integer, offset:integer )\n Multiplies two unsigned 32-bit integers and assigns results representing\n the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value to the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which splits values into two groups according to an\n predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array][, options:Object] )\n Computes an exact test for the success probability in a Bernoulli\n experiment.\n","Boolean":"\nBoolean( value:any )\n Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n A Boolean array.\n\nBooleanArray( length:integer )\n Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index:integer, value:boolean )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n","BooleanVector":"\nBooleanVector( [options:Object] )\n Returns a one-dimensional boolean ndarray.\n\nBooleanVector( length:integer[, options:Object] )\n Returns a one-dimensional boolean ndarray having a specified length.\n\nBooleanVector( obj:Object[, options:Object] )\n Creates a one-dimensional boolean ndarray from an array-like object or\n iterable.\n\nBooleanVector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional boolean ndarray view of an ArrayBuffer.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n Returns US birth data from 1969 to 1988, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n Returns US birth data from 1994 to 2003, as provided by the Center for\n Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n the Center for Disease Control and Prevention's National Center for Health\n Statistics.\n","chdir":"\nchdir( path:string )\n Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n ...args:number][, options:Object] )\n Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which repeatedly iterates over the elements of an array-\n like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n Creates a readable stream from an array-like object which repeatedly\n iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects\n which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n Returns an \"objectMode\" readable stream from an array-like object which\n repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n Read-only property returning a boolean indicating whether a circular buffer\n is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n Asynchronously closes a file descriptor, so that the file descriptor no\n longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n 64-bit complex number constructor.\n","Complex64.name":"\nComplex64.name\n Constructor name.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n A 64-bit complex number array.\n\nComplex64Array( length:integer )\n Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n Creates a 64-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 64-bit complex number array from an array-like object or an\n iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new 64-bit complex number array from a variable number of\n arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index:integer, value:Complex64 )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex64Matrix":"\nComplex64Matrix( [options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray.\n\nComplex64Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\nComplex64Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n having a specified shape.\n\nComplex64Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\nComplex64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","Complex64Vector":"\nComplex64Vector( [options:Object] )\n Returns a one-dimensional single-precision complex floating-point ndarray.\n\nComplex64Vector( length:integer[, options:Object] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n having a specified length.\n\nComplex64Vector( obj:Object[, options:Object] )\n Creates a one-dimensional single-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex64Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional single-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","Complex128":"\nComplex128( real:number, imag:number )\n 128-bit complex number constructor.\n","Complex128.name":"\nComplex128.name\n Constructor name.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n A 128-bit complex number array.\n\nComplex128Array( length:integer )\n Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n Creates a 128-bit complex number array from a typed array\n containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n Creates a 128-bit complex number array from an array-like object or\n iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new 128-bit complex number array from an array-like object or an\n iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n Creates a new 128-bit complex number array from a variable number of\n arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying\n ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n i:integer] )\n Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index:integer, value:Complex128 )\n Returns a new typed array with the element at a provided index replaced\n with a provided value.\n","Complex128Matrix":"\nComplex128Matrix( [options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray.\n\nComplex128Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\nComplex128Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n having a specified shape.\n\nComplex128Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex128Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n\nComplex128Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","Complex128Vector":"\nComplex128Vector( [options:Object] )\n Returns a one-dimensional double-precision complex floating-point ndarray.\n\nComplex128Vector( length:integer[, options:Object] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n having a specified length.\n\nComplex128Vector( obj:Object[, options:Object] )\n Creates a one-dimensional double-precision complex floating-point ndarray\n from an array-like object or iterable.\n\nComplex128Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional double-precision complex floating-point ndarray\n view of an ArrayBuffer.\n","complexarray":"\ncomplexarray( [dtype:string] )\n Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n Creates a complex number typed array from another complex number typed\n array.\n\ncomplexarray( obj:Object[, dtype:string] )\n Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n Returns the complex number data type with the smallest size and closest\n \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n Function composition.\n","configdir":"\nconfigdir( [p:string] )\n Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n Returns the complex conjugate of a double-precision complex floating-point\n number.\n","conjf":"\nconjf( z:Complex64 )\n Returns the complex conjugate of a single-precision complex floating-point\n number.\n","constantcase":"\nconstantcase( str:string )\n Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n Returns a function for creating readable streams which always stream the\n same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n Determines the name of a value's constructor.\n","contains":"\ncontains( value:ArrayLike, searchValue:any[, position:integer] )\n Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function\n and returns group counts.\n","currentYear":"\ncurrentYear()\n Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n Transforms a function into a sequence of functions each accepting a single\n argument.\n","cwd":"\ncwd()\n Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n Returns a list of familiar American-English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n Returns a dataset.\n","DataType":"\nDataType( value:any[, options:Object] )\n Data type constructor.\n","DataType.name":"\nDataType.name\n Constructor name.\n","DataType.prototype.alignment":"\nDataType.prototype.alignment\n Alignment (in bytes) for the data type.\n","DataType.prototype.byteLength":"\nDataType.prototype.byteLength\n Size (in bytes) of the data type.\n","DataType.prototype.byteOrder":"\nDataType.prototype.byteOrder\n Data type byte order.\n","DataType.prototype.char":"\nDataType.prototype.char\n Single letter character abbreviation for the data type.\n","DataType.prototype.description":"\nDataType.prototype.description\n Data type description.\n","DataType.prototype.enum":"\nDataType.prototype.enum\n Enumeration constant for the data type.\n","DataType.prototype.value":"\nDataType.prototype.value\n Raw (original) data type value.\n","DataType.prototype.toJSON":"\nDataType.prototype.toJSON()\n Serializes a data type instance as a JSON object.\n","DataType.prototype.toString":"\nDataType.prototype.toString()\n Serializes a data type instance to a string.\n","DataType.prototype.valueOf":"\nDataType.prototype.valueOf()\n Converts a data type instance to a primitive.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n byteLength:integer]] )\n Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n Read-only property which returns the underlying array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the view to the\n start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for debugging stream\n pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n Returns a function for creating transform streams for debugging stream\n pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n Decorates a provided function such that the function's return value is\n provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n thisArg:any] )\n Uses code generation to decorate a provided function such that the\n function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n Returns a boolean indicating whether an object contains a nested key path,\n either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n Returns a function which tests whether an object contains a nested key path,\n either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n predicate:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two double-precision floating-point vectors.\n","E":"\nE\n Euler's number.\n","EMOJI":"\nEMOJI()\n Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited enumerable property names\n and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited enumerable symbol\n properties.\n","ENV":"\nENV\n An object containing the user environment.\n","EPS":"\nEPS\n Difference between one and the smallest value greater than one that can be\n represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection pass a test implemented by a\n predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection pass a\n test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n Test whether all properties (own and inherited) of an object pass a\n test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object pass a test implemented by a\n predicate function.\n","evil":"\nevil( str:string )\n Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n Absolute pathname of the executable which started the current Node.js\n process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n Returns a filename extension.\n","falses":"\nfalses( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an ndarray filled with `false` values and having a specified shape\n and data type.\n","falsesLike":"\nfalsesLike( x:ndarray[, options:Object] )\n Returns an ndarray filled with `false` values and having the same shape and\n data type as a provided input ndarray.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n ints:boolean]] )\n Returns a function to compute a hypotenuse using the alpha max plus beta min\n algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, dtype:string] )\n Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled array according to a provided callback function and having\n a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n thisArg:any] )\n Creates a filled array from another array (or array-like object) according\n to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n Creates a filled array from an iterable according to a provided callback\n function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string], clbk:Function[, thisArg:any] )\n Returns a filled typed array view of an ArrayBuffer according to a provided\n callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n Returns FiveThirtyEight reader responses to a food frequency questionnaire\n (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike[, options:Object] )\n Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n Effective number of bits in the significand of a half-precision floating-\n point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n Square root of half-precision floating-point epsilon.\n","Float16Array":"\nFloat16Array()\n A 16-bit half-precision floating-point number array.\n\nFloat16Array( length:integer )\n Creates a half-precision floating-point number array having a specified\n length.\n\nFloat16Array( typedarray:TypedArray )\n Creates a half-precision floating-point number array from a typed array.\n\nFloat16Array( obj:Object )\n Creates a half-precision floating-point number array from an array-like\n object or iterable.\n\nFloat16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a half-precision floating-point number array view of an ArrayBuffer.\n","Float16Array.from":"\nFloat16Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n Creates a new half-precision floating-point number array from an array-like\n object or an iterable.\n","Float16Array.of":"\nFloat16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new half-precision floating-point number array from a variable\n number of arguments.\n","Float16Array.BYTES_PER_ELEMENT":"\nFloat16Array.BYTES_PER_ELEMENT\n The size of each array element in bytes.\n","Float16Array.name":"\nFloat16Array.name\n Typed array constructor name.\n","Float16Array.prototype.buffer":"\nFloat16Array.prototype.buffer\n Pointer to the underlying data buffer.\n","Float16Array.prototype.byteLength":"\nFloat16Array.prototype.byteLength\n Length of the array in bytes.\n","Float16Array.prototype.byteOffset":"\nFloat16Array.prototype.byteOffset\n Offset (in bytes) of the array from the start of its underlying ArrayBuffer.\n","Float16Array.prototype.BYTES_PER_ELEMENT":"\nFloat16Array.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element.\n","Float16Array.prototype.length":"\nFloat16Array.prototype.length\n The number of array elements.\n","Float16Array.prototype.at":"\nFloat16Array.prototype.at( i:integer )\n Returns an array element located at integer position (index) `i`, with\n support for both nonnegative and negative integer positions.\n","Float16Array.prototype.copyWithin":"\nFloat16Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float16Array.prototype.entries":"\nFloat16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float16Array.prototype.every":"\nFloat16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether all elements in the array pass a test.\n","Float16Array.prototype.fill":"\nFloat16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Returns a modified typed array filled with a fill value.\n","Float16Array.prototype.filter":"\nFloat16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Returns a new array containing the elements of an array which pass a test\n implemented by a predicate function.\n","Float16Array.prototype.find":"\nFloat16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first element in an array for which a predicate function\n returns a truthy value.\n","Float16Array.prototype.findIndex":"\nFloat16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first element in an array for which a predicate\n function returns a truthy value.\n","Float16Array.prototype.findLast":"\nFloat16Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n Returns the last element in an array for which a predicate function returns\n a truthy value.\n","Float16Array.prototype.findLastIndex":"\nFloat16Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the last element in an array for which a predicate\n function returns a truthy value.\n","Float16Array.prototype.forEach":"\nFloat16Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n Invokes a function once for each array element.\n","Float16Array.prototype.includes":"\nFloat16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a provided value.\n","Float16Array.prototype.indexOf":"\nFloat16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","Float16Array.prototype.join":"\nFloat16Array.prototype.join( [separator:string] )\n Returns a new string by concatenating all array elements separated by a\n separator string.\n","Float16Array.prototype.keys":"\nFloat16Array.prototype.keys()\n Returns an iterator for iterating over each index key in a typed array.\n","Float16Array.prototype.lastIndexOf":"\nFloat16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the last index at which a given element can be found.\n","Float16Array.prototype.map":"\nFloat16Array.prototype.map( clbk:Function[, thisArg:Any] )\n Returns a new array with each element being the result of a provided\n callback function.\n","Float16Array.prototype.reduce":"\nFloat16Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in order, passing\n in the return value from the calculation on the preceding element and\n returning the accumulated result upon completion.\n","Float16Array.prototype.reduceRight":"\nFloat16Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n Applies a provided function to each element of the array, in reverse order,\n passing in the return value from the calculation on the preceding element\n and returning the accumulated result upon completion.\n","Float16Array.prototype.reverse":"\nFloat16Array.prototype.reverse()\n Reverses the array *in-place*.\n","Float16Array.prototype.set":"\nFloat16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets one or more array elements.\n","Float16Array.prototype.slice":"\nFloat16Array.prototype.slice( [start:integer[, end:integer]] )\n Copies a portion of a typed array to a new typed array.\n","Float16Array.prototype.some":"\nFloat16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Returns a boolean indicating whether at least one element passes a test.\n","Float16Array.prototype.sort":"\nFloat16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array in-place.\n","Float16Array.prototype.subarray":"\nFloat16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array view over the same underlying `ArrayBuffer` and\n with the same underlying data type as the host array.\n","Float16Array.prototype.toLocaleString":"\nFloat16Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float16Array.prototype.toReversed":"\nFloat16Array.prototype.toReversed()\n Returns a new typed array containing the elements in reversed order.\n","Float16Array.prototype.toSorted":"\nFloat16Array.prototype.toSorted( [compareFcn:Function] )\n Returns a new typed array containing the elements in sorted order.\n","Float16Array.prototype.toString":"\nFloat16Array.prototype.toString()\n Serializes an array as a string.\n","Float16Array.prototype.values":"\nFloat16Array.prototype.values()\n Returns an iterator for iterating over each value in a typed array.\n","Float16Array.prototype.with":"\nFloat16Array.prototype.with( index:integer, value:number )\n Returns a new typed array with the element at a provided index replaced with\n a provided value.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n Difference between one and the smallest value greater than one that can be\n represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n One half times the natural logarithm of 2 as a single-precision\n floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n Natural logarithm of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a single-precision floating-point\n number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal single-precision floating-point\n number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in single-precision floating-point\n format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n Maximum safe nth factorial when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in single-precision floating-\n point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in single-precision floating-point\n format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized single-precision\n floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal single-precision\n floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normal single-precision floating-\n point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal single-precision floating-\n point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n Effective number of bits in the significand of a single-precision floating-\n point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n Square root of `π` divided by `2` as a single-precision \n floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n Square root of the mathematical constant `π` as a single-precision\n floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n Square root of the mathematical constant `π` times `2` as a single-precision\n floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n A typed array constructor which returns a typed array representing an array\n of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Float32Matrix":"\nFloat32Matrix( [options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray.\n\nFloat32Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\nFloat32Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray having a\n specified shape.\n\nFloat32Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n\nFloat32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n","Float32Vector":"\nFloat32Vector( [options:Object] )\n Returns a one-dimensional single-precision floating-point ndarray.\n\nFloat32Vector( length:integer[, options:Object] )\n Returns a one-dimensional single-precision floating-point ndarray having a\n specified length.\n\nFloat32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional single-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional single-precision floating-point ndarray view of an\n ArrayBuffer.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n High word mask for excluding the sign bit of a double-precision floating-\n point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n High word mask for the significand of a double-precision floating-point\n number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n The maximum biased base 2 exponent for a double-precision floating-point\n number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n The maximum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n The maximum base 10 exponent for a subnormal double-precision floating-point\n number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n Maximum safe Fibonacci number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n Maximum safe Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n Maximum safe nth Fibonacci number when stored in double-precision floating-\n point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n Maximum safe nth Lucas number when stored in double-precision floating-point\n format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n The minimum biased base 2 exponent for a normalized double-precision\n floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n The minimum biased base 2 exponent for a subnormal double-precision\n floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n The minimum base 10 exponent for a normalized double-precision floating-\n point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n The minimum base 10 exponent for a subnormal double-precision floating-\n point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n Natural logarithm of the smallest normalized double-precision floating-point\n number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n Effective number of bits in the significand of a double-precision floating-\n point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n A typed array constructor which returns a typed array representing an array\n of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Float64Matrix":"\nFloat64Matrix( [options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray.\n\nFloat64Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\nFloat64Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray having a\n specified shape.\n\nFloat64Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n\nFloat64Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, \n N:integer]][, options:Object] )\n Returns a two-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n","Float64Vector":"\nFloat64Vector( [options:Object] )\n Returns a one-dimensional double-precision floating-point ndarray.\n\nFloat64Vector( length:integer[, options:Object] )\n Returns a one-dimensional double-precision floating-point ndarray having a\n specified length.\n\nFloat64Vector( obj:Object[, options:Object] )\n Creates a one-dimensional double-precision floating-point ndarray from an\n array-like object or iterable.\n\nFloat64Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional double-precision floating-point ndarray view of an\n ArrayBuffer.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection, iterating from right to\n left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection, iterating from\n right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own and inherited enumerable property of an\n object.\n","format":"\nformat( str:string, ...args:any )\n Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n Returns wage rates for U.S. workers that have not changed jobs within the\n year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n Calls a function with a given `this` value and arguments provided as an\n array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n Calls a function with a given `this` value and arguments provided\n individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n Creates a new function which, when called, has its `this` keyword set to the\n provided value, with a given sequence of arguments preceding any provided\n when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates from right to left over each grapheme\n cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n groups:Array|TypedArray|Object )\n Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n Returns a dataset derived from information collected by the US Census\n Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n Tests for native `Symbol.toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n Returns fifteen observations of the vertical semidiameter of Venus, made by\n Lieutenant Herndon, with the meridian circle at Washington, in the year\n 1846.\n","homedir":"\nhomedir()\n Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n Returns the number of hours in a year according to the Gregorian calendar.\n","httpServerFactory":"\nhttpServerFactory( [options:Object,] [requestListener:Function] )\n Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n If a predicate function returns a truthy value, returns `x`; otherwise,\n returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n If a predicate function returns a truthy value, invokes `x`; otherwise,\n invokes `y`.\n","imag":"\nimag( z:Complex128 )\n Returns the imaginary component of a double-precision complex floating-point\n number.\n","imagf":"\nimagf( z:Complex64 )\n Returns the imaginary component of a single-precision complex floating-point\n number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n print *Allium oreophilum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n Returns a `Buffer` containing image data of Peter Henry Emerson's\n photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n Returns a `Buffer` containing image data of Felice Beato's albumen silver\n print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the absolute\n value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n Returns an accumulator function which incrementally performs binary\n classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes an unbiased\n sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n Returns an accumulator function which incrementally computes the coefficient\n of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted standard deviation, where α is a smoothing factor\n between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n Returns an accumulator function which incrementally computes an\n exponentially weighted variance, where α is a smoothing factor between 0 and\n 1.\n","incrgmean":"\nincrgmean()\n Returns an accumulator function which incrementally computes a geometric\n mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n Returns an accumulator function which incrementally performs Grubbs' test\n for detecting outliers.\n","incrhmean":"\nincrhmean()\n Returns an accumulator function which incrementally computes a harmonic\n mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n Returns an accumulator function which incrementally partitions data into `k`\n clusters.\n","incrkurtosis":"\nincrkurtosis()\n Returns an accumulator function which incrementally computes a corrected\n sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n Returns an accumulator function which incrementally computes the mean\n arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n Returns an accumulator function which incrementally computes the mean\n absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n Returns an accumulator function which incrementally computes the mean\n absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n Returns an accumulator function which incrementally computes a maximum\n value.\n","incrmaxabs":"\nincrmaxabs()\n Returns an accumulator function which incrementally computes a maximum\n absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n coefficient of variation (CV).\n","incrmda":"\nincrmda()\n Returns an accumulator function which incrementally computes the mean\n directional accuracy (MDA).\n","incrme":"\nincrme()\n Returns an accumulator function which incrementally computes the mean error\n (ME).\n","incrmean":"\nincrmean()\n Returns an accumulator function which incrementally computes an arithmetic\n mean.\n","incrmeanabs":"\nincrmeanabs()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n Returns an accumulator function which incrementally computes an arithmetic\n mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes an arithmetic\n mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n Returns an accumulator function which incrementally performs a moving\n Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n harmonic mean.\n","incrmidrange":"\nincrmidrange()\n Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n Returns an accumulator function which incrementally computes a minimum\n value.\n","incrminabs":"\nincrminabs()\n Returns an accumulator function which incrementally computes a minimum\n absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n Returns an accumulator function which incrementally computes a minimum and\n maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n Returns an accumulator function which incrementally computes a moving mid-\n range.\n","incrmmin":"\nincrmmin( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes a moving\n minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n Returns an accumulator function which incrementally computes moving minimum\n and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n Returns an accumulator function which incrementally computes a moving\n mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n Returns an accumulator function which incrementally computes a moving mean\n squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n Returns an accumulator function which incrementally computes a moving\n sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n Returns an accumulator function which incrementally computes the mean\n percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n Returns an accumulator function which incrementally computes a moving\n product.\n","incrmrange":"\nincrmrange( W:integer )\n Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n Returns an accumulator function which incrementally computes a moving root\n mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n Returns an accumulator function which incrementally computes a moving\n residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n Returns an accumulator function which incrementally computes the mean\n squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n Returns an accumulator function which incrementally computes a moving\n statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n Returns an accumulator function which incrementally computes a moving sum of\n products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n Returns an accumulator function which incrementally computes a moving\n variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n Returns an accumulator function which incrementally updates a count,\n ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n Returns an accumulator function which incrementally computes a sum, ignoring\n `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes the squared\n sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n Returns an accumulator function which incrementally computes a sample\n Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n Returns an accumulator function which incrementally computes the root mean\n squared error (RMSE).\n","incrrss":"\nincrrss()\n Returns an accumulator function which incrementally computes the residual\n sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n Returns an accumulator function which incrementally computes a corrected\n sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n Returns an accumulator function which incrementally computes a corrected\n sample standard deviation.\n","incrsum":"\nincrsum()\n Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n Returns an accumulator function which incrementally computes a sum of\n absolute values.\n","incrsumabs2":"\nincrsumabs2()\n Returns an accumulator function which incrementally computes a sum of\n squared absolute values.\n","incrsummary":"\nincrsummary()\n Returns an accumulator function which incrementally computes a statistical\n summary.\n","incrsumprod":"\nincrsumprod()\n Returns an accumulator function which incrementally computes a sum of\n products.\n","incrvariance":"\nincrvariance( [mean:number] )\n Returns an accumulator function which incrementally computes an unbiased\n sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n Returns an accumulator function which incrementally computes a variance-to-\n mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n Returns an accumulator function which incrementally computes a weighted\n arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n out:Array|TypedArray|Object )\n Converts a linear index to an array of subscripts and assigns results to a\n provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n Prototypical inheritance by replacing the prototype of one constructor with\n the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names and\n symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names and\n symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n level:integer] )\n Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited enumerable and non-enumerable\n property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names and\n symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Invokes a function for each element in a collection and updates the\n collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n fcn:Function, done:Function )\n Invokes a function once for each element in a collection and updates a\n collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function once for each element in a\n collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n Returns a function for creating transform streams for inspecting stream\n data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n Tests whether a value has in its prototype chain a specified constructor as\n a prototype property.\n","INT8_MAX":"\nINT8_MAX\n Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Int8Vector":"\nInt8Vector( [options:Object] )\n Returns a one-dimensional signed 8-bit integer ndarray.\n\nInt8Vector( length:integer[, options:Object] )\n Returns a one-dimensional signed 8-bit integer ndarray having a specified\n length.\n\nInt8Vector( obj:Object[, options:Object] )\n Creates a one-dimensional signed 8-bit integer ndarray from an array-like\n object or iterable.\n\nInt8Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional signed 8-bit integer ndarray view of an\n ArrayBuffer.\n","INT16_MAX":"\nINT16_MAX\n Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Int16Vector":"\nInt16Vector( [options:Object] )\n Returns a one-dimensional signed 16-bit integer ndarray.\n\nInt16Vector( length:integer[, options:Object] )\n Returns a one-dimensional signed 16-bit integer ndarray having a specified\n length.\n\nInt16Vector( obj:Object[, options:Object] )\n Creates a one-dimensional signed 16-bit integer ndarray from an array-like\n object or iterable.\n\nInt16Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional signed 16-bit integer ndarray view of an\n ArrayBuffer.\n","INT32_MAX":"\nINT32_MAX\n Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n A typed array constructor which returns a typed array representing an array\n of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Int32Matrix":"\nInt32Matrix( [options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray.\n\nInt32Matrix( shape:ArrayLikeObject[, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\nInt32Matrix( M:integer, N:integer[, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray having a specified\n shape.\n\nInt32Matrix( obj:Object[, options:Object] )\n Creates a two-dimensional 32-bit signed integer ndarray from an array-like\n object or iterable.\n\nInt32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n\nInt32Matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, N:integer]][, \n options:Object] )\n Returns a two-dimensional 32-bit signed integer ndarray view of an\n ArrayBuffer.\n","Int32Vector":"\nInt32Vector( [options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray.\n\nInt32Vector( length:integer[, options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray having a specified\n length.\n\nInt32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional signed 32-bit integer ndarray from an array-like\n object or iterable.\n\nInt32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional signed 32-bit integer ndarray view of an\n ArrayBuffer.\n","Int64":"\nInt64( value:integer|bigint )\n 64-bit signed integer constructor.\n","Int64.name":"\nInt64.name\n Constructor name.\n","Int64.from":"\nInt64.from( words:ArrayLikeObject )\n Creates a new 64-bit signed integer from an array-like object containing a\n high and low word.\n","Int64.of":"\nInt64.of( high:integer, low:integer )\n Creates a new 64-bit signed integer from a high and low word.\n","Int64.BYTES_PER_ELEMENT":"\nInt64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n","Int64.prototype.BYTES_PER_ELEMENT":"\nInt64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n","Int64.prototype.byteLength":"\nInt64.prototype.byteLength\n Size (in bytes) of the underlying value.\n","Int64.prototype.hi":"\nInt64.prototype.hi\n Returns the high 32-bit word of a 64-bit signed integer.\n","Int64.prototype.lo":"\nInt64.prototype.lo\n Returns the low 32-bit word of a 64-bit signed integer.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n Tests if a value is an array-like object supporting the accessor (get/set)\n protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n Tests whether a character belongs to the ASCII character set and whether\n this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n Tests if a value is an array-like object where every element is between two\n values.\n","isBigInt":"\nisBigInt( value:any )\n Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n Tests if a value is a blank string (i.e., an empty string or a string\n consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n Tests if a value is a number object having a value which is a composite\n number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have equal values.\n","isEqualDateObject":"\nisEqualDateObject( d1, d2 )\n Tests if two values are both Date objects corresponding to the same date\n and time.\n","isError":"\nisError( value:any )\n Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n Tests if a value is a value which translates to `false` when evaluated in a\n boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive finite\n numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing single-precision\n floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing single-\n precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n Tests if a value is an ndarray-like object containing double-precision\n floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object containing double-\n precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive integer\n values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive NaN\n values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only negative primitive\n integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive negative\n numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonnegative\n primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n Tests if a value is an array-like object containing only nonnegative\n numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only nonpositive\n primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only nonpositive\n numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [value:integer|Date] )\n Returns the number of ISO weeks in a year according to the Gregorian\n calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n Tests if a value is a square matrix which is symmetric about its\n antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n Tests if a value is an array-like object containing only positive primitive\n number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n Tests if a value is an array-like object containing only JavaScript\n primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive\n probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n Tests if a value is an array-like object containing only number objects\n having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n Tests if a value is an array-like object containing only primitive safe\n integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n Tests if a value is an array-like object containing only `Number` objects\n having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n Tests if two arguments are both single-precision complex floating-point\n numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n Tests if two arguments are both double-precision complex floating-point\n numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n Tests if a value is a 2-dimensional ndarray-like object having equal\n dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a square\n triangular number.\n","isStartcase":"\nisStartcase( value:any )\n Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n Tests if a value is an array containing only `String` objects.\n","isStruct":"\nisStruct( value:any )\n Tests if a value is a `struct` instance.\n","isStructConstructorLike":"\nisStructConstructorLike( value:any )\n Tests if a value is struct constructor-like.\n","isSymbol":"\nisSymbol( value:any )\n Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n Tests if a value is an array-like object containing only `symbol`\n primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n Tests if a value is an array-like object containing only `Symbol`\n objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n Tests if a value is a number object having a value which is a triangular\n number.\n","isTruthy":"\nisTruthy( value:any )\n Tests if a value is a value which translates to `true` when evaluated in a\n boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n Tests if a value is a built-in typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n Returns an iterator which iteratively computes the inverse hyperbolic\n cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise addition of two or more\n iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse half-value versed\n sine.\n","iterAny":"\niterAny( iterator:Object )\n Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether at least one iterated value passes a test implemented by a\n predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n Returns an iterator which iteratively computes the angle in the plane (in\n radians) between the positive x-axis and the ray from (0,0) to the point\n (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n thisArg:any]] )\n Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n Fills an array-like object view from right to left with values returned from\n an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Gaussian noise (AWGN)\n with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white Laplacian noise (AWLN)\n with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n Returns an iterator which introduces additive white uniform noise (AWUN)\n with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n Returns an iterator which iteratively evaluates the Bessel function of the\n second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n Returns an iterator which iteratively evaluates Binet's formula extended to\n real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n Returns an iterator which rounds each iterated value toward positive\n infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n Returns an iterator which generates a list of all continued fraction terms\n which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n Returns an iterator which computes the cosine of each iterated value times\n π.\n","iterCounter":"\niterCounter( iterator:Object )\n Returns an iterator which iteratively computes the number of iterated\n values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative maximum absolute\n value.\n","itercumean":"\nitercumean( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative arithmetic mean\n of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative minimum absolute\n value.\n","itercuprod":"\nitercuprod( iterator:Object )\n Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of absolute\n values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n Returns an iterator which iteratively computes a cumulative sum of squared\n absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced dates over a specified\n interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n Returns an iterator which removes consecutive values that resolve to the\n same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n Returns an iterator which iteratively converts an angle from degrees to\n radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise division of two or more\n iterators.\n","iterDoUntilEach":"\niterDoUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n Returns an iterator which iteratively computes the complete elliptic\n integral of the first kind.\n","iterEmpty":"\niterEmpty()\n Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n Returns an iterator which iteratively evaluates the complementary error\n function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse complementary\n error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of even\n integers.\n","iterEvery":"\niterEvery( iterator:Object )\n Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value passes a test implemented by a predicate\n function.\n","iterExp":"\niterExp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural exponential\n function.\n","iterExp2":"\niterExp2( iterator:Object )\n Returns an iterator which iteratively evaluates the base `2` exponential\n function.\n","iterExp10":"\niterExp10( iterator:Object )\n Returns an iterator which iteratively evaluates the base `10` exponential\n function.\n","iterExpit":"\niterExpit( iterator:Object )\n Returns an iterator which iteratively evaluates the standard logistic\n function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n Returns an iterator which iteratively evaluates the relative error\n exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n Returns an iterator which replaces all values from a provided iterator from\n a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which filters a provided iterator's values according to\n a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which both filters and maps a provided iterator's\n values.\n","iterFirst":"\niterFirst( iterator:Object )\n Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n Returns an iterator which rounds each iterated value toward negative\n infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n Returns a fluent interface iterator constructor with a customized prototype\n based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of the\n gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed\n cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n Returns an iterator which returns the first `n` values of a provided\n iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n Returns an iterator which returns evenly spaced numbers according to a\n specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n thisArg:any] )\n Returns an iterator which returns the intersection of two or more iterators\n according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n Returns an iterator which returns evenly spaced numbers over a specified\n interval.\n","iterLn":"\niterLn( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n Returns an iterator which iteratively evaluates the natural logarithm of\n `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n Returns an iterator which iteratively evaluates the common logarithm\n (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which transforms iterated values from two or more\n iterators by applying the iterated values as arguments to a provided\n function.\n","itermax":"\nitermax( iterator:Object )\n Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n Computes an arithmetic mean of squared absolute values for all iterated\n values.\n","itermidrange":"\nitermidrange( iterator:Object )\n Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving maximum absolute\n value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving arithmetic mean of\n squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving minimum absolute\n value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n Returns an iterator which performs an element-wise modulo operation of two\n or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of absolute\n values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n Returns an iterator which iteratively computes a moving sum of squared\n absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise multiplication of two or\n more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n Tests whether every iterated value fails a test implemented by a predicate\n function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n Returns an iterator which appends additional values to the end of a provided\n iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n Returns an iterator which iteratively converts an angle from radians to\n degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which rejects a provided iterator's values according to\n a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n Returns an iterator which replicates each iterated value according to a\n provided function.\n","iterRound":"\niterRound( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n Returns an iterator which iteratively computes the reciprocal (inverse)\n square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n Returns an iterator which returns a subsequence of iterated values from a\n provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n Tests whether at least `n` iterated values pass a test implemented by a\n predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of squared triangular\n numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n Returns an iterator which returns a sequence of numbers according to a\n specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n eager:boolean]] )\n Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n eager:boolean]][, thisArg:any] )\n Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n Returns an iterator which performs element-wise subtraction of two or more\n iterators.\n","itersum":"\nitersum( iterator:Object )\n Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n Returns an iterator which generates a Tribonacci sequence.\n \n The returned iterator can only generate the first 64 Tribonacci numbers, as\n larger Tribonacci numbers cannot be safely represented in double-precision\n floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n Returns an iterator which rounds each iterated value to the nearest power of\n 10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a predicate\n function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n Returns an iterator which returns unique values according to a hash\n function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n Returns an iterator which prepends values to the beginning of a provided\n iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns true\n or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n thisArg:any] )\n Returns an iterator which invokes a function for each iterated value before\n returning the iterated value until either a predicate function returns false\n or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array, y:Array[, options:Object] )\n Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n Converts a collection to an object whose keys are determined by a provided\n function and whose values are the collection values, iterating from right to\n left.\n","keysIn":"\nkeysIn( obj:any )\n Returns an array of an object's own and inherited enumerable property\n names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array, y:Function|string[, ...params:number][, \n options:Object] )\n Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array[, ...y:Array[, options:Object]] )\n Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n options:Object] )\n Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n out:ArrayLikeObject[, options:Object] )\n Generates a linearly spaced sequence over a specified interval and assigns\n the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n Natural logarithm of `2π`.\n","LN2":"\nLN2\n Natural logarithm of `2`.\n","LN10":"\nLN10\n Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array, y:Array[, options:Object] )\n Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n Left pads a string such that the padded string has a length of at least\n `len`.\n","ltrim":"\nltrim( str:string )\n Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays and assigns the results\n to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in an array of arrays and assigns\n the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to elements in two input arrays while iterating from\n right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject>, fcn:Function[, \n thisArg:any] )\n Applies a function to each nested element in a three-dimensional nested\n array and assigns the result to a nested element in a new three-dimensional\n nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a four-dimensional nested array\n and assigns the result to a nested element in a new four-dimensional nested\n array.\n","map5d":"\nmap5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )\n Applies a function to each nested element in a five-dimensional nested array\n and assigns the result to a nested element in a new five-dimensional nested\n array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function after\n transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n Invokes a function `n` times and returns an array of accumulated function\n return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n Returns a function which invokes a function `n` times and returns an array\n of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps keys from one object to a new object having\n the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array and returns the\n accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n reducer:Function[, thisArg:any] )\n Performs a map-reduce operation for each element in an array while iterating\n from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n fcn:Function[, thisArg:any] )\n Applies a function to each element in an array and assigns the result to an\n element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n done:Function )\n Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n Returns a function which maps values from one object to a new object having\n the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a specified mask.\n","matrix":"\nmatrix( [dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray.\n\nmatrix( shape:ArrayLikeObject[, dtype:string|DataType][, \n options:Object] )\n Returns a two-dimensional ndarray having a specified shape.\n\nmatrix( M:integer, N:integer[, dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray having a specified shape.\n\nmatrix( obj:Object[, dtype:string|DataType][, options:Object] )\n Creates a two-dimensional ndarray from an array-like object or iterable.\n\nmatrix( buffer:ArrayBuffer[, byteOffset:integer[, \n shape:ArrayLikeObject]][, dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n\nmatrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, N:integer]][, \n dtype:string|DataType][, options:Object] )\n Returns a two-dimensional ndarray view of an ArrayBuffer.\n","matrix.factory":"\nmatrix.factory( dtype:string|DataType[, options:Object] )\n Returns a function for creating a two-dimensional ndarray.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n Broadcasts an ndarray to a specified shape if and only if the specified\n shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )\n Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n Returns data for Charles Joseph Minard's cartographic depiction of\n Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array[, options:Object] )\n Returns a named typed tuple factory.\n","NAN":"\nNAN\n Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n Returns a function that applies a specified number of arguments to a\n provided function.\n","nativeClass":"\nnativeClass( value:any )\n Returns a string value indicating a specification defined classification of\n an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n shape:ArrayLikeObject, strides:ArrayLikeObject, \n offset:integer, order:string[, options:Object] )\n Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n Meta information, such as information concerning the memory layout of the\n array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n Index offset which specifies the buffer index at which to start iterating\n over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n Index strides which specify how to access data along corresponding array\n dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n Returns a function for converting an ndarray to an object supporting fancy\n indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n Returns a list of ndarray data types.\n","ndarrayDataTypes.binary":"\nndarrayDataTypes.binary\n Read-only property returning a data type instance representing a binary data\n type.\n","ndarrayDataTypes.boolean":"\nndarrayDataTypes.boolean\n Read-only property returning a data type instance representing a boolean\n data type.\n","ndarrayDataTypes.complex32":"\nndarrayDataTypes.complex32\n Read-only property returning a data type instance representing a half-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex64":"\nndarrayDataTypes.complex64\n Read-only property returning a data type instance representing a single-\n precision complex floating-point number data type.\n","ndarrayDataTypes.complex128":"\nndarrayDataTypes.complex128\n Read-only property returning a data type instance representing a double-\n precision complex floating-point number data type.\n","ndarrayDataTypes.float16":"\nndarrayDataTypes.float16\n Read-only property returning a data type instance representing a half-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float32":"\nndarrayDataTypes.float32\n Read-only property returning a data type instance representing a single-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.float64":"\nndarrayDataTypes.float64\n Read-only property returning a data type instance representing a double-\n precision real-valued floating-point number data type.\n","ndarrayDataTypes.generic":"\nndarrayDataTypes.generic\n Read-only property returning a data type instance representing a \"generic\"\n data type.\n","ndarrayDataTypes.int8":"\nndarrayDataTypes.int8\n Read-only property returning a data type instance representing a signed\n 8-bit integer data type.\n","ndarrayDataTypes.int16":"\nndarrayDataTypes.int16\n Read-only property returning a data type instance representing a signed\n 16-bit integer data type.\n","ndarrayDataTypes.int32":"\nndarrayDataTypes.int32\n Read-only property returning a data type instance representing a signed\n 32-bit integer data type.\n","ndarrayDataTypes.uint8":"\nndarrayDataTypes.uint8\n Read-only property returning a data type instance representing an unsigned\n 8-bit integer data type.\n","ndarrayDataTypes.uint8c":"\nndarrayDataTypes.uint8c\n Read-only property returning a data type instance representing an unsigned\n clamped 8-bit integer data type.\n","ndarrayDataTypes.uint16":"\nndarrayDataTypes.uint16\n Read-only property returning a data type instance representing an unsigned\n 16-bit integer data type.\n","ndarrayDataTypes.uint32":"\nndarrayDataTypes.uint32\n Read-only property returning a data type instance representing an unsigned\n 32-bit integer data type.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n Returns the minimum ndarray data type of the closest \"kind\" necessary for\n storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n Returns the index offset specifying the underlying buffer index of the first\n iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n Returns the ndarray data type with the smallest size and closest \"kind\" to\n which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n Returns a list of ndarray data types to which a provided ndarray data type\n can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n Returns an uninitialized ndarray having the same shape and data type as a\n provided input ndarray.\n","ndfill":"\nndfill( x:ndarrayLike, value:any )\n Fills an input ndarray with a specified value.\n","ndfillBy":"\nndfillBy( x:ndarrayLike, fcn:Function[, thisArg:any] )\n Fills an input ndarray according to a callback function.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Filters and maps elements in an input ndarray to elements in a new output\n ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n Returns the ndarray associated with the instance having a provided\n identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n Returns an ndarray index for indices representing locations in linear\n memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n Read-only property returning an ndarray view of the underlying index\n ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n Read-only property returning the unique identifier associated with an\n instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n Read-only property returning a boolean indicating whether an ndarray index\n is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n Serializes an instance as a JSON object.\n","nditer2arrayEach":"\nnditer2arrayEach( iterator:Object )\n Returns an iterator which converts each iterated ndarray to a generic array.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, column] pairs for each column in a\n matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each column in a matrix (or stack of\n matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, value] pairs for each element in a\n provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array[, options:Object] )\n Returns an iterator which returns indices for use indexing into an ndarray\n having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike, ndims:integer )\n Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, matrix] pairs for each matrix in a\n stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n Returns an iterator which returns [index, row] pairs for each row in a\n matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n Returns an iterator which iterates over each row in a matrix (or stack of\n matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n Returns an iterator which iterates over each view along a specified\n dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n Returns an iterator which iterates over each subarray in a stack of\n subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n Returns an iterator which returns individual elements from a provided\n ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n Applies a callback function to elements in an input ndarray and assigns\n results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n Returns a shallow copy of an ndarray containing only those elements which\n fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n options:Object] )\n Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n Assigns element values from a broadcasted input ndarray to corresponding\n elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n options:Object] )\n Returns a read-only view of an input ndarray when sliced along a specified\n dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray along a specified\n dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray along a specified\n dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject|integer[, options:Object] )\n Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n Returns a zero-filled ndarray having the same shape and data type as a\n provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the next extended grapheme cluster break in a string after a\n specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n thisArg:any ] )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Tests whether all elements in a collection fail a test implemented by a\n predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether all elements in a collection fail a\n test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every property in an object fails a test implemented by a\n predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n Returns an array of an object's own non-enumerable property names and\n symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited non-enumerable property\n names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited non-enumerable symbol\n properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n Tests whether every own property of an object fails a test implemented\n by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n Returns an array of an object's own enumerable property names which are not\n integer indices.\n","noop":"\nnoop()\n A function which does nothing.\n","now":"\nnow()\n Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n Returns the size (i.e., number of elements) of a specified dimension for a\n provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n Assigns enumerable and own properties from source objects to a target\n object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n Returns an array of an object's own enumerable and non-enumerable\n symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n Returns an array of an object's own enumerable string-keyed property\n names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n Prevents the addition of new properties to an object and marks all\n existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n Returns a boolean indicating whether an object has a property with the\n specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n Returns a boolean indicating whether an object exists in another object's\n prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n Property whose value is a reference to the constructor function that\n created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n Returns an array of an object's own enumerable property `[key, value]`\n pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array )\n Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n Inverts an object, such that keys become values and values become keys,\n according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n Returns an array of an object's own and inherited enumerable property\n values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n Returns a partial object copy excluding properties for which a predicate\n returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n Returns a (corrected) dataset derived from information collected by the US\n Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array, method:string[, comparisons:integer] )\n Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n Returns a function of smaller arity by partially applying arguments from the\n right.\n","parallel":"\nparallel( files:Array, [options:Object,] clbk:Function )\n Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array, y:Array[, options:Object] )\n Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n Golden ratio.\n","PI":"\nPI\n The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n Returns a partial object copy containing properties for which a predicate\n returns a truthy value.\n","PINF":"\nPINF\n Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n Returns the standalone package name associated with a provided internal\n package name.\n","PLATFORM":"\nPLATFORM\n Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n collection2:Array|TypedArray|Object )\n Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n Returns the previous extended grapheme cluster break in a string before a\n specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n Returns an array of an object's own and inherited property names and\n symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n Returns an array of an object's own enumerable and non-enumerable property\n names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n Returns an array of an object's own and inherited enumerable and non-\n enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n Returns a proxy object implementing custom behavior for specified object\n operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta\n distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi\n distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from an F\n distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a linear congruential pseudorandom number generator (LCG)\n whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n Returns an array containing pseudorandom integers on the interval\n `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers\n generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a normal\n distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n Returns an array containing uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n Returns a function for creating arrays containing uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Student's t\n distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n options:Object] )\n Returns an array containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a triangular\n distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n Returns an array containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n out:Array|Float64Array|Float32Array )\n Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n Returns a function for creating arrays containing pseudorandom numbers drawn\n from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an F\n distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n Returns an iterator for generating pseudorandom integers on the interval\n `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n Create an iterator for generating pseudorandom numbers having integer\n values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n Create an iterator for generating pseudorandom numbers drawn from a standard\n normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n Create an iterator for generating uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n Returns an iterator for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Box-Muller\n transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution using the Improved\n Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution using the Improved Ziggurat\n algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from an\n inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers on the\n interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers having integer\n values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n Returns a readable stream for generating uniformly distributed pseudorandom\n numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n Returns a function for creating readable streams which generate uniformly\n distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n Returns an \"objectMode\" readable stream for generating uniformly distributed\n pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n [options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n Returns a readable stream for generating pseudorandom numbers drawn from a\n Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n Returns a function for creating readable streams which generate pseudorandom\n numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an arcsine\n distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta\n distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a beta prime\n distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi\n distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a chi-square\n distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a cosine\n distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a discrete\n uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from an exponential\n distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a gamma\n distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a geometric\n distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a lognormal\n distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 1 and 2147483646\n (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n so:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with pseudorandom integers between 0 and 4294967295\n (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers between 0 and 1 using\n alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a normal\n distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Poisson\n distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n oo:integer[, options:Object] )\n Fills a strided array with uniformly distributed pseudorandom numbers\n between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n out:ArrayLikeObject, so:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n out:ArrayLikeObject, so:integer, oo:integer )\n Fills a strided array with pseudorandom numbers drawn from a Student's t-\n distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n Returns a function for filling strided arrays with pseudorandom numbers\n drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a continuous\n uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n Fills a strided array with pseudorandom numbers drawn from a Weibull\n distribution using alternative indexing semantics.\n","random.arcsine":"\nrandom.arcsine( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an arcsine\n distribution.\n","random.arcsine.assign":"\nrandom.arcsine.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an arcsine\n distribution.\n","random.arcsine.factory":"\nrandom.arcsine.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an arcsine\n distribution.\n","random.arcsine.PRNG":"\nrandom.arcsine.PRNG\n Underlying pseudorandom number generator.\n","random.arcsine.seed":"\nrandom.arcsine.seed\n Pseudorandom number generator seed.\n","random.arcsine.seedLength":"\nrandom.arcsine.seedLength\n Length of generator seed.\n","random.arcsine.state":"\nrandom.arcsine.state\n Generator state.\n","random.arcsine.stateLength":"\nrandom.arcsine.stateLength\n Length of generator state.\n","random.arcsine.byteLength":"\nrandom.arcsine.byteLength\n Size (in bytes) of generator state.\n","random.bernoulli":"\nrandom.bernoulli( shape:Array, p:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.bernoulli.assign":"\nrandom.bernoulli.assign( p:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Bernoulli\n distribution.\n","random.bernoulli.factory":"\nrandom.bernoulli.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n Bernoulli distribution.\n","random.bernoulli.PRNG":"\nrandom.bernoulli.PRNG\n Underlying pseudorandom number generator.\n","random.bernoulli.seed":"\nrandom.bernoulli.seed\n Pseudorandom number generator seed.\n","random.bernoulli.seedLength":"\nrandom.bernoulli.seedLength\n Length of generator seed.\n","random.bernoulli.state":"\nrandom.bernoulli.state\n Generator state.\n","random.bernoulli.stateLength":"\nrandom.bernoulli.stateLength\n Length of generator state.\n","random.bernoulli.byteLength":"\nrandom.bernoulli.byteLength\n Size (in bytes) of generator state.\n","random.beta":"\nrandom.beta( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta\n distribution.\n","random.beta.assign":"\nrandom.beta.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a beta distribution.\n","random.beta.factory":"\nrandom.beta.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a beta\n distribution.\n","random.beta.PRNG":"\nrandom.beta.PRNG\n Underlying pseudorandom number generator.\n","random.beta.seed":"\nrandom.beta.seed\n Pseudorandom number generator seed.\n","random.beta.seedLength":"\nrandom.beta.seedLength\n Length of generator seed.\n","random.beta.state":"\nrandom.beta.state\n Generator state.\n","random.beta.stateLength":"\nrandom.beta.stateLength\n Length of generator state.\n","random.beta.byteLength":"\nrandom.beta.byteLength\n Size (in bytes) of generator state.\n","random.betaprime":"\nrandom.betaprime( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a beta prime\n distribution.\n","random.betaprime.assign":"\nrandom.betaprime.assign( alpha:number|ndarray, beta:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a beta prime\n distribution.\n","random.betaprime.factory":"\nrandom.betaprime.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n beta prime distribution.\n","random.betaprime.PRNG":"\nrandom.betaprime.PRNG\n Underlying pseudorandom number generator.\n","random.betaprime.seed":"\nrandom.betaprime.seed\n Pseudorandom number generator seed.\n","random.betaprime.seedLength":"\nrandom.betaprime.seedLength\n Length of generator seed.\n","random.betaprime.state":"\nrandom.betaprime.state\n Generator state.\n","random.betaprime.stateLength":"\nrandom.betaprime.stateLength\n Length of generator state.\n","random.betaprime.byteLength":"\nrandom.betaprime.byteLength\n Size (in bytes) of generator state.\n","random.binomial":"\nrandom.binomial( shape:Array, n:number|ndarray, p:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a binomial\n distribution.\n","random.binomial.assign":"\nrandom.binomial.assign( n:number|ndarray, p:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a binomial\n distribution.\n","random.binomial.factory":"\nrandom.binomial.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a binomial\n distribution.\n","random.binomial.PRNG":"\nrandom.binomial.PRNG\n Underlying pseudorandom number generator.\n","random.binomial.seed":"\nrandom.binomial.seed\n Pseudorandom number generator seed.\n","random.binomial.seedLength":"\nrandom.binomial.seedLength\n Length of generator seed.\n","random.binomial.state":"\nrandom.binomial.state\n Generator state.\n","random.binomial.stateLength":"\nrandom.binomial.stateLength\n Length of generator state.\n","random.binomial.byteLength":"\nrandom.binomial.byteLength\n Size (in bytes) of generator state.\n","random.cauchy":"\nrandom.cauchy( shape:Array, x0:number|ndarray, gamma:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.cauchy.assign":"\nrandom.cauchy.assign( x0:number|ndarray, gamma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Cauchy distribution.\n","random.cauchy.factory":"\nrandom.cauchy.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Cauchy\n distribution.\n","random.cauchy.PRNG":"\nrandom.cauchy.PRNG\n Underlying pseudorandom number generator.\n","random.cauchy.seed":"\nrandom.cauchy.seed\n Pseudorandom number generator seed.\n","random.cauchy.seedLength":"\nrandom.cauchy.seedLength\n Length of generator seed.\n","random.cauchy.state":"\nrandom.cauchy.state\n Generator state.\n","random.cauchy.stateLength":"\nrandom.cauchy.stateLength\n Length of generator state.\n","random.cauchy.byteLength":"\nrandom.cauchy.byteLength\n Size (in bytes) of generator state.\n","random.chi":"\nrandom.chi( shape:Array, k:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi\n distribution.\n","random.chi.assign":"\nrandom.chi.assign( k:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a chi distribution.\n","random.chi.factory":"\nrandom.chi.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a chi\n distribution.\n","random.chi.PRNG":"\nrandom.chi.PRNG\n Underlying pseudorandom number generator.\n","random.chi.seed":"\nrandom.chi.seed\n Pseudorandom number generator seed.\n","random.chi.seedLength":"\nrandom.chi.seedLength\n Length of generator seed.\n","random.chi.state":"\nrandom.chi.state\n Generator state.\n","random.chi.stateLength":"\nrandom.chi.stateLength\n Length of generator state.\n","random.chi.byteLength":"\nrandom.chi.byteLength\n Size (in bytes) of generator state.\n","random.chisquare":"\nrandom.chisquare( shape:Array, k:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a chi-square\n distribution.\n","random.chisquare.assign":"\nrandom.chisquare.assign( k:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a chi-square\n distribution.\n","random.chisquare.factory":"\nrandom.chisquare.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a chi-\n square distribution.\n","random.chisquare.PRNG":"\nrandom.chisquare.PRNG\n Underlying pseudorandom number generator.\n","random.chisquare.seed":"\nrandom.chisquare.seed\n Pseudorandom number generator seed.\n","random.chisquare.seedLength":"\nrandom.chisquare.seedLength\n Length of generator seed.\n","random.chisquare.state":"\nrandom.chisquare.state\n Generator state.\n","random.chisquare.stateLength":"\nrandom.chisquare.stateLength\n Length of generator state.\n","random.chisquare.byteLength":"\nrandom.chisquare.byteLength\n Size (in bytes) of generator state.\n","random.cosine":"\nrandom.cosine( shape:Array, mu:number|ndarray, s:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.cosine.assign":"\nrandom.cosine.assign( mu:number|ndarray, s:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a raised cosine\n distribution.\n","random.cosine.factory":"\nrandom.cosine.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a raised\n cosine distribution.\n","random.cosine.PRNG":"\nrandom.cosine.PRNG\n Underlying pseudorandom number generator.\n","random.cosine.seed":"\nrandom.cosine.seed\n Pseudorandom number generator seed.\n","random.cosine.seedLength":"\nrandom.cosine.seedLength\n Length of generator seed.\n","random.cosine.state":"\nrandom.cosine.state\n Generator state.\n","random.cosine.stateLength":"\nrandom.cosine.stateLength\n Length of generator state.\n","random.cosine.byteLength":"\nrandom.cosine.byteLength\n Size (in bytes) of generator state.\n","random.discreteUniform":"\nrandom.discreteUniform( shape:Array, a:number|ndarray, \n b:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.discreteUniform.assign":"\nrandom.discreteUniform.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a discrete uniform\n distribution.\n","random.discreteUniform.factory":"\nrandom.discreteUniform.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a discrete\n uniform distribution.\n","random.discreteUniform.PRNG":"\nrandom.discreteUniform.PRNG\n Underlying pseudorandom number generator.\n","random.discreteUniform.seed":"\nrandom.discreteUniform.seed\n Pseudorandom number generator seed.\n","random.discreteUniform.seedLength":"\nrandom.discreteUniform.seedLength\n Length of generator seed.\n","random.discreteUniform.state":"\nrandom.discreteUniform.state\n Generator state.\n","random.discreteUniform.stateLength":"\nrandom.discreteUniform.stateLength\n Length of generator state.\n","random.discreteUniform.byteLength":"\nrandom.discreteUniform.byteLength\n Size (in bytes) of generator state.\n","random.erlang":"\nrandom.erlang( shape:Array, k:number|ndarray, lambda:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an Erlang\n distribution.\n","random.erlang.assign":"\nrandom.erlang.assign( k:number|ndarray, lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an Erlang\n distribution.\n","random.erlang.factory":"\nrandom.erlang.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an Erlang\n distribution.\n","random.erlang.PRNG":"\nrandom.erlang.PRNG\n Underlying pseudorandom number generator.\n","random.erlang.seed":"\nrandom.erlang.seed\n Pseudorandom number generator seed.\n","random.erlang.seedLength":"\nrandom.erlang.seedLength\n Length of generator seed.\n","random.erlang.state":"\nrandom.erlang.state\n Generator state.\n","random.erlang.stateLength":"\nrandom.erlang.stateLength\n Length of generator state.\n","random.erlang.byteLength":"\nrandom.erlang.byteLength\n Size (in bytes) of generator state.\n","random.exponential":"\nrandom.exponential( shape:Array, lambda:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an exponential\n distribution.\n","random.exponential.assign":"\nrandom.exponential.assign( lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an exponential\n distribution.\n","random.exponential.factory":"\nrandom.exponential.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an\n exponential distribution.\n","random.exponential.PRNG":"\nrandom.exponential.PRNG\n Underlying pseudorandom number generator.\n","random.exponential.seed":"\nrandom.exponential.seed\n Pseudorandom number generator seed.\n","random.exponential.seedLength":"\nrandom.exponential.seedLength\n Length of generator seed.\n","random.exponential.state":"\nrandom.exponential.state\n Generator state.\n","random.exponential.stateLength":"\nrandom.exponential.stateLength\n Length of generator state.\n","random.exponential.byteLength":"\nrandom.exponential.byteLength\n Size (in bytes) of generator state.\n","random.f":"\nrandom.f( shape:Array, d1:number|ndarray, d2:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an F\n distribution.\n","random.f.assign":"\nrandom.f.assign( d1:number|ndarray, d2:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an F distribution.\n","random.f.factory":"\nrandom.f.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an F\n distribution.\n","random.f.PRNG":"\nrandom.f.PRNG\n Underlying pseudorandom number generator.\n","random.f.seed":"\nrandom.f.seed\n Pseudorandom number generator seed.\n","random.f.seedLength":"\nrandom.f.seedLength\n Length of generator seed.\n","random.f.state":"\nrandom.f.state\n Generator state.\n","random.f.stateLength":"\nrandom.f.stateLength\n Length of generator state.\n","random.f.byteLength":"\nrandom.f.byteLength\n Size (in bytes) of generator state.\n","random.frechet":"\nrandom.frechet( shape:Array, alpha:number|ndarray, s:number|ndarray, \n m:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.frechet.assign":"\nrandom.frechet.assign( alpha:number|ndarray, s:number|ndarray, \n m:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.frechet.factory":"\nrandom.frechet.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Fréchet\n distribution.\n","random.frechet.PRNG":"\nrandom.frechet.PRNG\n Underlying pseudorandom number generator.\n","random.frechet.seed":"\nrandom.frechet.seed\n Pseudorandom number generator seed.\n","random.frechet.seedLength":"\nrandom.frechet.seedLength\n Length of generator seed.\n","random.frechet.state":"\nrandom.frechet.state\n Generator state.\n","random.frechet.stateLength":"\nrandom.frechet.stateLength\n Length of generator state.\n","random.frechet.byteLength":"\nrandom.frechet.byteLength\n Size (in bytes) of generator state.\n","random.gamma":"\nrandom.gamma( shape:Array, alpha:number|ndarray, beta:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a gamma\n distribution.\n","random.gamma.assign":"\nrandom.gamma.assign( alpha:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a gamma distribution.\n","random.gamma.factory":"\nrandom.gamma.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a gamma\n distribution.\n","random.gamma.PRNG":"\nrandom.gamma.PRNG\n Underlying pseudorandom number generator.\n","random.gamma.seed":"\nrandom.gamma.seed\n Pseudorandom number generator seed.\n","random.gamma.seedLength":"\nrandom.gamma.seedLength\n Length of generator seed.\n","random.gamma.state":"\nrandom.gamma.state\n Generator state.\n","random.gamma.stateLength":"\nrandom.gamma.stateLength\n Length of generator state.\n","random.gamma.byteLength":"\nrandom.gamma.byteLength\n Size (in bytes) of generator state.\n","random.geometric":"\nrandom.geometric( shape:Array, p:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a geometric\n distribution.\n","random.geometric.assign":"\nrandom.geometric.assign( p:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a geometric\n distribution.\n","random.geometric.factory":"\nrandom.geometric.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n geometric distribution.\n","random.geometric.PRNG":"\nrandom.geometric.PRNG\n Underlying pseudorandom number generator.\n","random.geometric.seed":"\nrandom.geometric.seed\n Pseudorandom number generator seed.\n","random.geometric.seedLength":"\nrandom.geometric.seedLength\n Length of generator seed.\n","random.geometric.state":"\nrandom.geometric.state\n Generator state.\n","random.geometric.stateLength":"\nrandom.geometric.stateLength\n Length of generator state.\n","random.geometric.byteLength":"\nrandom.geometric.byteLength\n Size (in bytes) of generator state.\n","random.gumbel":"\nrandom.gumbel( shape:Array, mu:number|ndarray, beta:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.gumbel.assign":"\nrandom.gumbel.assign( mu:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Gumbel distribution.\n","random.gumbel.factory":"\nrandom.gumbel.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Gumbel\n distribution.\n","random.gumbel.PRNG":"\nrandom.gumbel.PRNG\n Underlying pseudorandom number generator.\n","random.gumbel.seed":"\nrandom.gumbel.seed\n Pseudorandom number generator seed.\n","random.gumbel.seedLength":"\nrandom.gumbel.seedLength\n Length of generator seed.\n","random.gumbel.state":"\nrandom.gumbel.state\n Generator state.\n","random.gumbel.stateLength":"\nrandom.gumbel.stateLength\n Length of generator state.\n","random.gumbel.byteLength":"\nrandom.gumbel.byteLength\n Size (in bytes) of generator state.\n","random.hypergeometric":"\nrandom.hypergeometric( shape:Array, N:number|ndarray, \n K:number|ndarray, n:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.hypergeometric.assign":"\nrandom.hypergeometric.assign( N:number|ndarray, K:number|ndarray, \n n:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a hypergeometric\n distribution.\n","random.hypergeometric.factory":"\nrandom.hypergeometric.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n hypergeometric distribution.\n","random.hypergeometric.PRNG":"\nrandom.hypergeometric.PRNG\n Underlying pseudorandom number generator.\n","random.hypergeometric.seed":"\nrandom.hypergeometric.seed\n Pseudorandom number generator seed.\n","random.hypergeometric.seedLength":"\nrandom.hypergeometric.seedLength\n Length of generator seed.\n","random.hypergeometric.state":"\nrandom.hypergeometric.state\n Generator state.\n","random.hypergeometric.stateLength":"\nrandom.hypergeometric.stateLength\n Length of generator state.\n","random.hypergeometric.byteLength":"\nrandom.hypergeometric.byteLength\n Size (in bytes) of generator state.\n","random.invgamma":"\nrandom.invgamma( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from an inverse\n gamma distribution.\n","random.invgamma.assign":"\nrandom.invgamma.assign( alpha:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from an inverse gamma\n distribution.\n","random.invgamma.factory":"\nrandom.invgamma.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from an inverse\n gamma distribution.\n","random.invgamma.PRNG":"\nrandom.invgamma.PRNG\n Underlying pseudorandom number generator.\n","random.invgamma.seed":"\nrandom.invgamma.seed\n Pseudorandom number generator seed.\n","random.invgamma.seedLength":"\nrandom.invgamma.seedLength\n Length of generator seed.\n","random.invgamma.state":"\nrandom.invgamma.state\n Generator state.\n","random.invgamma.stateLength":"\nrandom.invgamma.stateLength\n Length of generator state.\n","random.invgamma.byteLength":"\nrandom.invgamma.byteLength\n Size (in bytes) of generator state.\n","random.kumaraswamy":"\nrandom.kumaraswamy( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n","random.kumaraswamy.assign":"\nrandom.kumaraswamy.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Kumaraswamy\n distribution.\n","random.kumaraswamy.factory":"\nrandom.kumaraswamy.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n Kumaraswamy distribution.\n","random.kumaraswamy.PRNG":"\nrandom.kumaraswamy.PRNG\n Underlying pseudorandom number generator.\n","random.kumaraswamy.seed":"\nrandom.kumaraswamy.seed\n Pseudorandom number generator seed.\n","random.kumaraswamy.seedLength":"\nrandom.kumaraswamy.seedLength\n Length of generator seed.\n","random.kumaraswamy.state":"\nrandom.kumaraswamy.state\n Generator state.\n","random.kumaraswamy.stateLength":"\nrandom.kumaraswamy.stateLength\n Length of generator state.\n","random.kumaraswamy.byteLength":"\nrandom.kumaraswamy.byteLength\n Size (in bytes) of generator state.\n","random.laplace":"\nrandom.laplace( shape:Array, mu:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.laplace.assign":"\nrandom.laplace.assign( mu:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Laplace (double\n exponential) distribution.\n","random.laplace.factory":"\nrandom.laplace.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Laplace\n (double exponential) distribution.\n","random.laplace.PRNG":"\nrandom.laplace.PRNG\n Underlying pseudorandom number generator.\n","random.laplace.seed":"\nrandom.laplace.seed\n Pseudorandom number generator seed.\n","random.laplace.seedLength":"\nrandom.laplace.seedLength\n Length of generator seed.\n","random.laplace.state":"\nrandom.laplace.state\n Generator state.\n","random.laplace.stateLength":"\nrandom.laplace.stateLength\n Length of generator state.\n","random.laplace.byteLength":"\nrandom.laplace.byteLength\n Size (in bytes) of generator state.\n","random.levy":"\nrandom.levy( shape:Array, mu:number|ndarray, c:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Lévy\n distribution.\n","random.levy.assign":"\nrandom.levy.assign( mu:number|ndarray, c:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Lévy distribution.\n","random.levy.factory":"\nrandom.levy.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Lévy\n distribution.\n","random.levy.PRNG":"\nrandom.levy.PRNG\n Underlying pseudorandom number generator.\n","random.levy.seed":"\nrandom.levy.seed\n Pseudorandom number generator seed.\n","random.levy.seedLength":"\nrandom.levy.seedLength\n Length of generator seed.\n","random.levy.state":"\nrandom.levy.state\n Generator state.\n","random.levy.stateLength":"\nrandom.levy.stateLength\n Length of generator state.\n","random.levy.byteLength":"\nrandom.levy.byteLength\n Size (in bytes) of generator state.\n","random.logistic":"\nrandom.logistic( shape:Array, mu:number|ndarray, s:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a logistic\n distribution.\n","random.logistic.assign":"\nrandom.logistic.assign( mu:number|ndarray, s:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a logistic\n distribution.\n","random.logistic.factory":"\nrandom.logistic.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a logistic\n distribution.\n","random.logistic.PRNG":"\nrandom.logistic.PRNG\n Underlying pseudorandom number generator.\n","random.logistic.seed":"\nrandom.logistic.seed\n Pseudorandom number generator seed.\n","random.logistic.seedLength":"\nrandom.logistic.seedLength\n Length of generator seed.\n","random.logistic.state":"\nrandom.logistic.state\n Generator state.\n","random.logistic.stateLength":"\nrandom.logistic.stateLength\n Length of generator state.\n","random.logistic.byteLength":"\nrandom.logistic.byteLength\n Size (in bytes) of generator state.\n","random.lognormal":"\nrandom.lognormal( shape:Array, mu:number|ndarray, \n sigma:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a lognormal\n distribution.\n","random.lognormal.assign":"\nrandom.lognormal.assign( mu:number|ndarray, sigma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a lognormal\n distribution.\n","random.lognormal.factory":"\nrandom.lognormal.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n lognormal distribution.\n","random.lognormal.PRNG":"\nrandom.lognormal.PRNG\n Underlying pseudorandom number generator.\n","random.lognormal.seed":"\nrandom.lognormal.seed\n Pseudorandom number generator seed.\n","random.lognormal.seedLength":"\nrandom.lognormal.seedLength\n Length of generator seed.\n","random.lognormal.state":"\nrandom.lognormal.state\n Generator state.\n","random.lognormal.stateLength":"\nrandom.lognormal.stateLength\n Length of generator state.\n","random.lognormal.byteLength":"\nrandom.lognormal.byteLength\n Size (in bytes) of generator state.\n","random.negativeBinomial":"\nrandom.negativeBinomial( shape:Array, r:number|ndarray, \n p:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.negativeBinomial.assign":"\nrandom.negativeBinomial.assign( r:number|ndarray, p:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a negative binomial\n distribution.\n","random.negativeBinomial.factory":"\nrandom.negativeBinomial.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a negative\n binomial distribution.\n","random.negativeBinomial.PRNG":"\nrandom.negativeBinomial.PRNG\n Underlying pseudorandom number generator.\n","random.negativeBinomial.seed":"\nrandom.negativeBinomial.seed\n Pseudorandom number generator seed.\n","random.negativeBinomial.seedLength":"\nrandom.negativeBinomial.seedLength\n Length of generator seed.\n","random.negativeBinomial.state":"\nrandom.negativeBinomial.state\n Generator state.\n","random.negativeBinomial.stateLength":"\nrandom.negativeBinomial.stateLength\n Length of generator state.\n","random.negativeBinomial.byteLength":"\nrandom.negativeBinomial.byteLength\n Size (in bytes) of generator state.\n","random.normal":"\nrandom.normal( shape:Array, mu:number|ndarray, sigma:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a normal\n distribution.\n","random.normal.assign":"\nrandom.normal.assign( mu:number|ndarray, sigma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a normal distribution.\n","random.normal.factory":"\nrandom.normal.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a normal\n distribution.\n","random.normal.PRNG":"\nrandom.normal.PRNG\n Underlying pseudorandom number generator.\n","random.normal.seed":"\nrandom.normal.seed\n Pseudorandom number generator seed.\n","random.normal.seedLength":"\nrandom.normal.seedLength\n Length of generator seed.\n","random.normal.state":"\nrandom.normal.state\n Generator state.\n","random.normal.stateLength":"\nrandom.normal.stateLength\n Length of generator state.\n","random.normal.byteLength":"\nrandom.normal.byteLength\n Size (in bytes) of generator state.\n","random.pareto1":"\nrandom.pareto1( shape:Array, alpha:number|ndarray, \n beta:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Pareto (Type\n I) distribution.\n","random.pareto1.assign":"\nrandom.pareto1.assign( alpha:number|ndarray, beta:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Pareto (Type I)\n distribution.\n","random.pareto1.factory":"\nrandom.pareto1.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Pareto\n (Type I) distribution.\n","random.pareto1.PRNG":"\nrandom.pareto1.PRNG\n Underlying pseudorandom number generator.\n","random.pareto1.seed":"\nrandom.pareto1.seed\n Pseudorandom number generator seed.\n","random.pareto1.seedLength":"\nrandom.pareto1.seedLength\n Length of generator seed.\n","random.pareto1.state":"\nrandom.pareto1.state\n Generator state.\n","random.pareto1.stateLength":"\nrandom.pareto1.stateLength\n Length of generator state.\n","random.pareto1.byteLength":"\nrandom.pareto1.byteLength\n Size (in bytes) of generator state.\n","random.poisson":"\nrandom.poisson( shape:Array, lambda:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Poisson\n distribution.\n","random.poisson.assign":"\nrandom.poisson.assign( lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Poisson\n distribution.\n","random.poisson.factory":"\nrandom.poisson.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Poisson\n distribution.\n","random.poisson.PRNG":"\nrandom.poisson.PRNG\n Underlying pseudorandom number generator.\n","random.poisson.seed":"\nrandom.poisson.seed\n Pseudorandom number generator seed.\n","random.poisson.seedLength":"\nrandom.poisson.seedLength\n Length of generator seed.\n","random.poisson.state":"\nrandom.poisson.state\n Generator state.\n","random.poisson.stateLength":"\nrandom.poisson.stateLength\n Length of generator state.\n","random.poisson.byteLength":"\nrandom.poisson.byteLength\n Size (in bytes) of generator state.\n","random.rayleigh":"\nrandom.rayleigh( shape:Array, sigma:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.rayleigh.assign":"\nrandom.rayleigh.assign( sigma:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.rayleigh.factory":"\nrandom.rayleigh.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Rayleigh\n distribution.\n","random.rayleigh.PRNG":"\nrandom.rayleigh.PRNG\n Underlying pseudorandom number generator.\n","random.rayleigh.seed":"\nrandom.rayleigh.seed\n Pseudorandom number generator seed.\n","random.rayleigh.seedLength":"\nrandom.rayleigh.seedLength\n Length of generator seed.\n","random.rayleigh.state":"\nrandom.rayleigh.state\n Generator state.\n","random.rayleigh.stateLength":"\nrandom.rayleigh.stateLength\n Length of generator state.\n","random.rayleigh.byteLength":"\nrandom.rayleigh.byteLength\n Size (in bytes) of generator state.\n","random.t":"\nrandom.t( shape:Array, v:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.t.assign":"\nrandom.t.assign( v:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Student's t-\n distribution.\n","random.t.factory":"\nrandom.t.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n Student's t-distribution.\n","random.t.PRNG":"\nrandom.t.PRNG\n Underlying pseudorandom number generator.\n","random.t.seed":"\nrandom.t.seed\n Pseudorandom number generator seed.\n","random.t.seedLength":"\nrandom.t.seedLength\n Length of generator seed.\n","random.t.state":"\nrandom.t.state\n Generator state.\n","random.t.stateLength":"\nrandom.t.stateLength\n Length of generator state.\n","random.t.byteLength":"\nrandom.t.byteLength\n Size (in bytes) of generator state.\n","random.triangular":"\nrandom.triangular( shape:Array, a:number|ndarray, b:number|ndarray, \n c:number|ndarray[, options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a triangular\n distribution.\n","random.triangular.assign":"\nrandom.triangular.assign( a:number|ndarray, b:number|ndarray, c:number|ndarray, \n out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a triangular\n distribution.\n","random.triangular.factory":"\nrandom.triangular.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n triangular distribution.\n","random.triangular.PRNG":"\nrandom.triangular.PRNG\n Underlying pseudorandom number generator.\n","random.triangular.seed":"\nrandom.triangular.seed\n Pseudorandom number generator seed.\n","random.triangular.seedLength":"\nrandom.triangular.seedLength\n Length of generator seed.\n","random.triangular.state":"\nrandom.triangular.state\n Generator state.\n","random.triangular.stateLength":"\nrandom.triangular.stateLength\n Length of generator state.\n","random.triangular.byteLength":"\nrandom.triangular.byteLength\n Size (in bytes) of generator state.\n","random.uniform":"\nrandom.uniform( shape:Array, a:number|ndarray, b:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a continuous\n uniform distribution.\n","random.uniform.assign":"\nrandom.uniform.assign( a:number|ndarray, b:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a continuous uniform\n distribution.\n","random.uniform.factory":"\nrandom.uniform.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a\n continuous uniform distribution.\n","random.uniform.PRNG":"\nrandom.uniform.PRNG\n Underlying pseudorandom number generator.\n","random.uniform.seed":"\nrandom.uniform.seed\n Pseudorandom number generator seed.\n","random.uniform.seedLength":"\nrandom.uniform.seedLength\n Length of generator seed.\n","random.uniform.state":"\nrandom.uniform.state\n Generator state.\n","random.uniform.stateLength":"\nrandom.uniform.stateLength\n Length of generator state.\n","random.uniform.byteLength":"\nrandom.uniform.byteLength\n Size (in bytes) of generator state.\n","random.weibull":"\nrandom.weibull( shape:Array, k:number|ndarray, lambda:number|ndarray[, \n options:Object] )\n Returns an ndarray containing pseudorandom numbers drawn from a Weibull\n distribution.\n","random.weibull.assign":"\nrandom.weibull.assign( k:number|ndarray, lambda:number|ndarray, out:ndarray )\n Fills an ndarray with pseudorandom numbers drawn from a Weibull\n distribution.\n","random.weibull.factory":"\nrandom.weibull.factory( [options:Object] )\n Returns a function for generating pseudorandom numbers drawn from a Weibull\n distribution.\n","random.weibull.PRNG":"\nrandom.weibull.PRNG\n Underlying pseudorandom number generator.\n","random.weibull.seed":"\nrandom.weibull.seed\n Pseudorandom number generator seed.\n","random.weibull.seedLength":"\nrandom.weibull.seedLength\n Length of generator seed.\n","random.weibull.state":"\nrandom.weibull.state\n Generator state.\n","random.weibull.stateLength":"\nrandom.weibull.stateLength\n Length of generator state.\n","random.weibull.byteLength":"\nrandom.weibull.byteLength\n Size (in bytes) of generator state.\n","ranks":"\nranks( arr:Array[, options:Object] )\n Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array[, options:Object|string], clbk:Function )\n Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array[, options:Object|string] )\n Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n Returns the real component of a double-precision complex floating-point\n number.\n","realarray":"\nrealarray( [dtype:string] )\n Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n Returns the real component of a single-precision complex floating-point\n number.\n","realmax":"\nrealmax( dtype:string )\n Returns the maximum finite value capable of being represented by a numeric\n real type.\n","realmin":"\nrealmin( dtype:string )\n Returns the smallest positive normal value capable of being represented by a\n numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n Regular expression to match either a shorthand or full length hexadecimal\n color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject, initial:ArrayLikeObject, \n reducer:Function[, thisArg:any] )\n Reduces the number of dimensions by one of a two-dimensional nested array by\n applying a function against an accumulator and each element along the\n innermost dimension and returning the accumulation results as a one-\n dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n thisArg:any] )\n Applies a function against an accumulator and each element in an array while\n iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n [options:Object,] reducer:Function, done:Function )\n Applies a function against an accumulator and each element in a collection\n and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n Returns a function which applies a function against an accumulator and each\n element in a collection and returns the accumulated result, iterating from\n right to left.\n","reDurationString":"\nreDurationString()\n Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n Returns the real and imaginary components of a double-precision complex\n floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n Returns the real and imaginary components of a single-precision complex\n floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n Returns a function that applies arguments to a provided function according\n to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array[, ignoreCase:boolean] )\n Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array[, thisArg:any] )\n Returns a function that invokes a provided function with reordered\n arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n Replaces the substring before the first occurrence of a specified search\n string. \n","reRegExp":"\nreRegExp()\n Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n clbk:Function )\n Asynchronously resolves a path according to a predicate function by walking\n parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n Synchronously resolves a path according to a predicate function by walking\n parent directories.\n","reUncPath":"\nreUncPath()\n Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n Returns a function that invokes a provided function with arguments in\n reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n Right pads a `string` such that the padded `string` has a length of at least\n `len`.\n","rtrim":"\nrtrim( str:string )\n Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n Returns the maximum safe integer capable of being represented by a numeric\n real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n Returns the minimum safe integer capable of being represented by a numeric\n real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n getter:Function )\n Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n getter:Function, setter:Function )\n Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n setter:Function )\n Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n setter:Function )\n Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n Returns the size (in bytes) of the canonical binary representation of a\n specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n step:integer|null|undefined] )\n Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n thisArg:any ] )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n [options:Object,] predicate:Function, done:Function )\n Tests whether a collection contains at least `n` elements which pass a test\n implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n Returns a function which tests whether a collection contains at least `n`\n elements which pass a test implemented by a predicate function, iterating\n from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether an object contains at least `n` properties\n (own and inherited) which pass a test\n implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n Tests whether some `own` properties of a provided object\n satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over the elements of a sparse array-like\n object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n thisArg:any]] )\n Returns an iterator which iterates from right to left over the elements of a\n sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n Returns a function for creating transform streams for splitting streamed\n data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n Returns US birth data from 2000 to 2014, as provided by the Social Security\n Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n Returns the internal package name associated with a provided standalone\n package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n Returns a string array containing two or three letter abbreviations for each\n card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the absolute value for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the squared absolute value for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the squared absolute value of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the absolute value of each element retrieved from a strided input\n array `x` via a callback function and assigns each result to an element in a\n strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arccosine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arccosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse cotangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse hyperbolic cotangent of each element retrieved from an\n input strided array `x` via a callback function and assigns each result to\n an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse coversed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Adds each element in a strided array `x` to a corresponding element in a\n strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise addition of two strided arrays via a callback function\n and assigns each result to an element in an output strided array using\n alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed cosine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse half-value versed sine of each element retrieved from\n an input strided array `x` via a callback function and assigns each result\n to an element in an output strided array `y` using alternative indexing\n semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arcsine of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arcsine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the arctangent of each element retrieved from an input strided\n array `x` via a callback function and assigns each result to an element in\n an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the hyperbolic arctangent of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed cosine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the inverse versed sine of each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing\n semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the first kind of order one for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order zero for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the Bessel function of the second kind of order one for each\n element retrieved from an input strided array `x` via a callback function\n and assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Evaluates Binet's formula extended to real numbers for each element\n retrieved from an input strided array `x` via a callback function and\n assigns each result to an element in an output strided array `y` using\n alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the cube root of each element in a strided array `x` and assigns\n the results to elements in a strided array `y` using alternative indexing\n semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward positive infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the cosine for each element retrieved from an input strided array\n `x` via a callback function and assigns each result to an element in an\n output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Converts each element in a strided array `x` from degrees to radians and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n sy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n Computes the cube root of each element retrieved from an input double-\n precision floating-point strided array via a callback function and assigns\n each result to an element in an output double-precision floating-point\n strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject, \n types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n nout:integer )\n Returns a strided array function interface which accepts a callback function\n and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward negative infinity and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n offsetY:integer )\n Computes the multiplicative inverse for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Multiplies each element in a strided array `x` by a corresponding element in\n a strided array `y` and assigns the results to elements in a strided array\n `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise multiplication of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Evaluates the ramp function for each element in a strided array `x` and\n assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the reciprocal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the sine of each element retrieved from an input strided array `x`\n via a callback function and assigns each result to an element in an output\n strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Computes the principal square root for each element in a strided array `x`\n and assigns the results to elements in a strided array `y` using alternative\n indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n clbk:Function[, thisArg:any] )\n Computes the principal square root for each element retrieved from an input\n strided array `x` via a callback function and assigns each result to an\n element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n z:ArrayLikeObject, sz:integer, oz:integer )\n Subtracts each element in a strided array `y` from a corresponding element\n in a strided array `x` and assigns the results to elements in a strided\n array `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n clbk:Function[, thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n thisArg:any] )\n Performs element-wise subtraction of two strided arrays via a callback\n function and assigns each result to an element in an output strided array\n using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n dtypeY:any, y:ArrayLikeObject, strideY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n strideY:integer, offsetY:integer )\n Rounds each element in a strided array `x` toward zero and assigns the\n results to elements in a strided array `y` using alternative indexing\n semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n offset:integer[, mapFcn:Function[, thisArg:any]] )\n Returns an iterator which iterates over elements of an array-like object\n according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n offset:integer[, options:Object] )\n Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n stride:integer, offset:integer[, options:Object] )\n Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n Returns the part of a string after the last occurrence of a specified\n substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n Returns the part of a string before the last occurrence of a specified\n substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a multi-hop wireless sensor network deployment using TelosB\n motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n Returns a dataset consisting of labeled wireless sensor network data set\n collected from a simple single-hop wireless sensor network deployment using\n TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n indicator:Function, done:Function )\n Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n Returns a function which generates a frequency table according to an\n indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n Returns a thunk.\n","tic":"\ntic()\n Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n Times a snippet.\n","tmpdir":"\ntmpdir()\n Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array )\n Returns a high-resolution time difference, where `time` is a two-element\n array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n Trims whitespace from the beginning and end of a `string`.\n","trues":"\ntrues( shape:ArrayLikeObject|integer[, options:Object] )\n Returns an ndarray filled with `true` values and having a specified shape\n and data type.\n","truesLike":"\ntruesLike( x:ndarray[, options:Object] )\n Returns an ndarray filled with `true` values and having the same shape and\n data type as a provided input ndarray.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n If a function does not throw, returns the function return value; otherwise,\n returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n If a function does not throw, returns the function return value; otherwise,\n returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n If a function does not return an error, invokes a callback with the function\n result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array[, y:Array][, options:Object] )\n Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array, y:Array[, options:Object] )\n Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string] )\n Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n Returns an uninitialized typed array having a specified length from a typed\n array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n Returns a typed array having a specified length from a typed array memory\n pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n Returns a zero-initialized typed array having a specified length from a\n typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n Clears the typed array pool allowing garbage collection of previously\n allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n A typed array constructor which returns a typed array representing an array\n of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint8ClampedVector":"\nUint8ClampedVector( [options:Object] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray.\n\nUint8ClampedVector( length:integer[, options:Object] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray having a\n specified length.\n\nUint8ClampedVector( obj:Object[, options:Object] )\n Creates a one-dimensional clamped unsigned 8-bit integer ndarray from an\n array-like object or iterable.\n\nUint8ClampedVector( buffer:ArrayBuffer[, byteOffset:integer[, \n length:integer]][, options:Object] )\n Returns a one-dimensional clamped unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n","Uint8Vector":"\nUint8Vector( [options:Object] )\n Returns a one-dimensional unsigned 8-bit integer ndarray.\n\nUint8Vector( length:integer[, options:Object] )\n Returns a one-dimensional unsigned 8-bit integer ndarray having a specified\n length.\n\nUint8Vector( obj:Object[, options:Object] )\n Creates a one-dimensional unsigned 8-bit integer ndarray from an array-like\n object or iterable.\n\nUint8Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional unsigned 8-bit integer ndarray view of an\n ArrayBuffer.\n","UINT16_MAX":"\nUINT16_MAX\n Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n A typed array constructor which returns a typed array representing an array\n of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint16Vector":"\nUint16Vector( [options:Object] )\n Returns a one-dimensional unsigned 16-bit integer ndarray.\n\nUint16Vector( length:integer[, options:Object] )\n Returns a one-dimensional unsigned 16-bit integer ndarray having a specified\n length.\n\nUint16Vector( obj:Object[, options:Object] )\n Creates a one-dimensional unsigned 16-bit integer ndarray from an array-like\n object or iterable.\n\nUint16Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional unsigned 16-bit integer ndarray view of an\n ArrayBuffer.\n","UINT32_MAX":"\nUINT32_MAX\n Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n A typed array constructor which returns a typed array representing an array\n of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n Read-only property which returns the ArrayBuffer referenced by the typed\n array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n Read-only property which returns the offset (in bytes) of the typed array\n from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n Copies a sequence of elements within the array starting at `start` and\n ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n Tests whether all array elements pass a test implemented by a predicate\n function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n Fills an array from a start index to an end index (non-inclusive) with a\n provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n Creates a new array which includes those elements for which a predicate\n function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n Returns the first array element for which a provided predicate function\n returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n Returns the index of the first array element for which a provided predicate\n function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the first array element strictly equal to a search\n element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n Returns the index of the last array element strictly equal to a search\n element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n Applies a function against an accumulator and each element in an array and\n returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n Copies array elements to a new array with the same underlying data type as\n the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n Tests whether at least one array element passes a test implemented by a\n predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n Creates a new typed array over the same underlying ArrayBuffer and with the\n same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n Returns an iterator for iterating over array elements.\n","Uint32Vector":"\nUint32Vector( [options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray.\n\nUint32Vector( length:integer[, options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray having a specified\n length.\n\nUint32Vector( obj:Object[, options:Object] )\n Creates a one-dimensional unsigned 32-bit integer ndarray from an array-like\n object or iterable.\n\nUint32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n options:Object] )\n Returns a one-dimensional unsigned 32-bit integer ndarray view of an\n ArrayBuffer.\n","Uint64":"\nUint64( value:integer|bigint )\n 64-bit unsigned integer constructor.\n","Uint64.name":"\nUint64.name\n Constructor name.\n","Uint64.from":"\nUint64.from( words:ArrayLikeObject )\n Creates a new 64-bit unsigned integer from an array-like object containing a\n high and low word.\n","Uint64.of":"\nUint64.of( high:integer, low:integer )\n Creates a new 64-bit unsigned integer from a high and low word.\n","Uint64.BYTES_PER_ELEMENT":"\nUint64.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n","Uint64.prototype.BYTES_PER_ELEMENT":"\nUint64.prototype.BYTES_PER_ELEMENT\n Size (in bytes) of the underlying value.\n","Uint64.prototype.byteLength":"\nUint64.prototype.byteLength\n Size (in bytes) of the underlying value.\n","Uint64.prototype.hi":"\nUint64.prototype.hi\n Returns the high 32-bit word of a 64-bit unsigned integer.\n","Uint64.prototype.lo":"\nUint64.prototype.lo\n Returns the low 32-bit word of a 64-bit unsigned integer.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n Returns the current process mask, if not provided a mask; otherwise, sets\n the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n Transforms a curried function into a function invoked with multiple\n arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n Until a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array] )\n Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n Returns a list of US state two-letter abbreviations in alphabetical order\n according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n Returns a list of US state capitals in alphabetical order according to state\n name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n Converts a UTF-16 encoded string to an array of integers using UTF-8\n encoding.\n","vartest":"\nvartest( x:Array, y:Array[, options:Object] )\n Computes a two-sample F-test for equal variances.\n","vector":"\nvector( [dtype:string][, options:Object] )\n Returns a one-dimensional ndarray.\n\nvector( length:integer[, dtype:string][, options:Object] )\n Returns a one-dimensional ndarray having a specified length.\n\nvector( obj:Object[, dtype:string][, options:Object] )\n Creates a one-dimensional ndarray from an array-like object or iterable.\n\nvector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n dtype:string][, options:Object] )\n Returns a one-dimensional ndarray view of an ArrayBuffer.\n","vector.factory":"\nvector.factory( dtype:string[, options:Object] )\n Returns a function for creating a one-dimensional ndarray.\n","waterfall":"\nwaterfall( fcns:Array, clbk:Function[, thisArg:any] )\n Executes functions in series, passing the results of one function as\n arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )\n Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n Increases the size of the memory instance by a specified number of\n WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n fcn:Function[, thisArg:any] )\n While a test condition is true, invokes a function for each element in a\n collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n Returns an array of an object's own and inherited writable property names\n and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n Returns an array of an object's own and inherited writable symbol\n properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string], clbk:Function )\n Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n options:Object|string] )\n Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array, sigma:number[, options:Object] )\n Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array, y:Array, sigmax:number, sigmay:number[, \n options:Object] )\n Computes a two-sample z-test.\n"} diff --git a/lib/node_modules/@stdlib/repl/lib/regexp_require.js b/lib/node_modules/@stdlib/repl/lib/regexp_require.js index bcca0b771f2e..0ec0e3c51b0c 100644 --- a/lib/node_modules/@stdlib/repl/lib/regexp_require.js +++ b/lib/node_modules/@stdlib/repl/lib/regexp_require.js @@ -16,6 +16,8 @@ * limitations under the License. */ +/* eslint-disable stdlib/jsdoc-example-require-spacing */ + 'use strict'; // MAIN // diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.csv b/lib/node_modules/@stdlib/repl/signature/data/data.csv index cc430947b086..a8214a73f61c 100644 --- a/lib/node_modules/@stdlib/repl/signature/data/data.csv +++ b/lib/node_modules/@stdlib/repl/signature/data/data.csv @@ -1780,8 +1780,8 @@ base.strided.dmeanvarpn,"base.strided.dmeanvarpn( N, c, x, strideX, out, strideO base.strided.dmeanvarpn.ndarray,"base.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )" base.strided.dmeanwd,"base.strided.dmeanwd( N, x, strideX )" base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N, x, strideX, offsetX )" -base.strided.dmediansorted,"base.strided.dmediansorted( N, x, strideX )" -base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N, x, strideX, offsetX )" +base.strided.dmedianSorted,"base.strided.dmedianSorted( N, x, strideX )" +base.strided.dmedianSorted.ndarray,"base.strided.dmedianSorted.ndarray( N, x, strideX, offsetX )" base.strided.dmidrange,"base.strided.dmidrange( N, x, strideX )" base.strided.dmidrange.ndarray,"base.strided.dmidrange.ndarray( N, x, strideX, offsetX )" base.strided.dmin,"base.strided.dmin( N, x, strideX )" @@ -3590,6 +3590,15 @@ Int32Vector,"Int32Vector( [options] )" Int32Vector,"Int32Vector( length[, options] )" Int32Vector,"Int32Vector( obj[, options] )" Int32Vector,"Int32Vector( buffer[, byteOffset[, length]][, options] )" +Int64,"Int64( value )" +Int64.name,"Int64.name" +Int64.from,"Int64.from( words )" +Int64.of,"Int64.of( high, low )" +Int64.BYTES_PER_ELEMENT,"Int64.BYTES_PER_ELEMENT" +Int64.prototype.BYTES_PER_ELEMENT,"Int64.prototype.BYTES_PER_ELEMENT" +Int64.prototype.byteLength,"Int64.prototype.byteLength" +Int64.prototype.hi,"Int64.prototype.hi" +Int64.prototype.lo,"Int64.prototype.lo" IS_BIG_ENDIAN,"IS_BIG_ENDIAN" IS_BROWSER,"IS_BROWSER" IS_DARWIN,"IS_DARWIN" diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.json b/lib/node_modules/@stdlib/repl/signature/data/data.json index 442561e52012..4a170286e81f 100644 --- a/lib/node_modules/@stdlib/repl/signature/data/data.json +++ b/lib/node_modules/@stdlib/repl/signature/data/data.json @@ -1 +1 @@ -[["abs","abs( x[, options] )"],["abs.assign","abs.assign( x, y )"],["acartesianPower","acartesianPower( x, n )"],["acartesianProduct","acartesianProduct( x1, x2 )"],["acartesianSquare","acartesianSquare( x )"],["acronym","acronym( str[, options] )"],["aempty","aempty( length[, dtype] )"],["aemptyLike","aemptyLike( x[, dtype] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length, value[, dtype] )"],["afullLike","afullLike( x[, dtype] )"],["alias2pkg","alias2pkg( alias )"],["alias2related","alias2related( alias )"],["alias2standalone","alias2standalone( alias )"],["aliases","aliases( [namespace] )"],["allocUnsafe","allocUnsafe( size )"],["amskfilter","amskfilter( x, mask )"],["amskput","amskput( x, mask, values[, options] )"],["amskreject","amskreject( x, mask )"],["anans","anans( length[, dtype] )"],["anansLike","anansLike( x[, dtype] )"],["anova1","anova1( x, factor[, options] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection )"],["anyBy","anyBy( collection, predicate[, thisArg ] )"],["anyByAsync","anyByAsync( collection, [options,] predicate, done )"],["anyByAsync.factory","anyByAsync.factory( [options,] predicate )"],["anyByRight","anyByRight( collection, predicate[, thisArg ] )"],["anyByRightAsync","anyByRightAsync( collection, [options,] predicate, done )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options,] predicate )"],["anyInBy","anyInBy( object, predicate[, thisArg ] )"],["anyOwnBy","anyOwnBy( object, predicate[, thisArg ] )"],["aones","aones( length[, dtype] )"],["aonesLike","aonesLike( x[, dtype] )"],["aoneTo","aoneTo( n[, dtype] )"],["aoneToLike","aoneToLike( x[, dtype] )"],["APERY","APERY"],["aplace","aplace( x, mask, values[, options] )"],["append","append( collection1, collection2 )"],["aput","aput( x, indices, values[, options] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx )"],["ARGV","ARGV"],["array","array( [buffer,] [options] )"],["array2buffer","array2buffer( arr )"],["array2fancy","array2fancy( x[, options] )"],["array2fancy.factory","array2fancy.factory( [options] )"],["array2fancy.idx","array2fancy.idx( x[, options] )"],["array2iterator","array2iterator( src[, mapFcn[, thisArg]] )"],["array2iteratorRight","array2iteratorRight( src[, mapFcn[, thisArg]] )"],["ArrayBuffer","ArrayBuffer( size )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start[, end]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf[, byteOffset[, length]] )"],["arrayCtors","arrayCtors( dtype )"],["arrayDataType","arrayDataType( array )"],["arrayDataTypes","arrayDataTypes( [kind] )"],["ArrayIndex","ArrayIndex( x[, options] )"],["ArrayIndex.free","ArrayIndex.free( id )"],["ArrayIndex.get","ArrayIndex.get( id )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype] )"],["arrayNextDataType","arrayNextDataType( [dtype] )"],["arrayPromotionRules","arrayPromotionRules( [dtype1, dtype2] )"],["arraySafeCasts","arraySafeCasts( [dtype] )"],["arraySameKindCasts","arraySameKindCasts( [dtype] )"],["arrayShape","arrayShape( arr )"],["arrayStream","arrayStream( src[, options] )"],["arrayStream.factory","arrayStream.factory( [options] )"],["arrayStream.objectMode","arrayStream.objectMode( src[, options] )"],["arrayview2iterator","arrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )"],["arrayview2iteratorRight","arrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )"],["aslice","aslice( x[, start[, end]] )"],["AsyncIteratorSymbol","AsyncIteratorSymbol"],["atake","atake( x, indices[, options] )"],["azeros","azeros( length[, dtype] )"],["azerosLike","azerosLike( x[, dtype] )"],["azeroTo","azeroTo( n[, dtype] )"],["azeroToLike","azeroToLike( x[, dtype] )"],["bartlettTest","bartlettTest( ...x[, options] )"],["base.abs","base.abs( x )"],["base.abs2","base.abs2( x )"],["base.abs2f","base.abs2f( x )"],["base.absdiff","base.absdiff( x, y )"],["base.absf","base.absf( x )"],["base.acartesianPower","base.acartesianPower( x, n )"],["base.acartesianProduct","base.acartesianProduct( x1, x2 )"],["base.acartesianSquare","base.acartesianSquare( x )"],["base.acos","base.acos( x )"],["base.acosd","base.acosd( x )"],["base.acosdf","base.acosdf( x )"],["base.acosf","base.acosf( x )"],["base.acosh","base.acosh( x )"],["base.acot","base.acot( x )"],["base.acotd","base.acotd( x )"],["base.acotdf","base.acotdf( x )"],["base.acotf","base.acotf( x )"],["base.acoth","base.acoth( x )"],["base.acovercos","base.acovercos( x )"],["base.acoversin","base.acoversin( x )"],["base.acsc","base.acsc( x )"],["base.acscd","base.acscd( x )"],["base.acscdf","base.acscdf( x )"],["base.acscf","base.acscf( x )"],["base.acsch","base.acsch( x )"],["base.add","base.add( x, y )"],["base.add3","base.add3( x, y, z )"],["base.add4","base.add4( x, y, z, w )"],["base.add5","base.add5( x, y, z, w, u )"],["base.addf","base.addf( x, y )"],["base.afilled","base.afilled( value, len )"],["base.afilled2d","base.afilled2d( value, shape )"],["base.afilled2dBy","base.afilled2dBy( shape, clbk[, thisArg] )"],["base.afilled3d","base.afilled3d( value, shape )"],["base.afilled3dBy","base.afilled3dBy( shape, clbk[, thisArg] )"],["base.afilled4d","base.afilled4d( value, shape )"],["base.afilled4dBy","base.afilled4dBy( shape, clbk[, thisArg] )"],["base.afilled5d","base.afilled5d( value, shape )"],["base.afilled5dBy","base.afilled5dBy( shape, clbk[, thisArg] )"],["base.afilledBy","base.afilledBy( len, clbk[, thisArg] )"],["base.afillednd","base.afillednd( value, shape )"],["base.afilledndBy","base.afilledndBy( shape, clbk[, thisArg] )"],["base.afilter","base.afilter( x, predicate[, thisArg] )"],["base.afirst","base.afirst( arr )"],["base.aflatten","base.aflatten( x, shape, colexicographic )"],["base.aflatten.assign","base.aflatten.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2d","base.aflatten2d( x, shape, colexicographic )"],["base.aflatten2d.assign","base.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2dBy","base.aflatten2dBy( x, shape, colex, clbk[, thisArg] )"],["base.aflatten2dBy.assign","base.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] 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value )"],["isNegativeZero.isPrimitive","isNegativeZero.isPrimitive( value )"],["isNegativeZero.isObject","isNegativeZero.isObject( value )"],["isNodeBuiltin","isNodeBuiltin( str )"],["isNodeDuplexStreamLike","isNodeDuplexStreamLike( value )"],["isNodeReadableStreamLike","isNodeReadableStreamLike( value )"],["isNodeREPL","isNodeREPL()"],["isNodeStreamLike","isNodeStreamLike( value )"],["isNodeTransformStreamLike","isNodeTransformStreamLike( value )"],["isNodeWritableStreamLike","isNodeWritableStreamLike( value )"],["isNonConfigurableProperty","isNonConfigurableProperty( value, property )"],["isNonConfigurablePropertyIn","isNonConfigurablePropertyIn( value, property )"],["isNonEnumerableProperty","isNonEnumerableProperty( value, property )"],["isNonEnumerablePropertyIn","isNonEnumerablePropertyIn( value, property )"],["isNonNegativeFinite","isNonNegativeFinite( value )"],["isNonNegativeFinite.isPrimitive","isNonNegativeFinite.isPrimitive( value 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value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value 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)"],["isUint8Array","isUint8Array( value )"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property 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mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoUntilEach","iterDoUntilEach( iterator, predicate, fcn[, thisArg] )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] )"],["iterStrided","iterStrided( iterator, stride[, offset[, eager]] )"],["iterStridedBy","iterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items )"],["iterUntilEach","iterUntilEach( iterator, predicate, fcn[, thisArg] )"],["itervariance","itervariance( iterator[, mean] )"],["iterVercos","iterVercos( iterator )"],["iterVersin","iterVersin( iterator )"],["iterWhileEach","iterWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterZeta","iterZeta( iterator )"],["joinStream","joinStream( [options] )"],["joinStream.factory","joinStream.factory( [options] )"],["joinStream.objectMode","joinStream.objectMode( [options] )"],["kde2d","kde2d( x, y[, options] )"],["kebabcase","kebabcase( str )"],["keyBy","keyBy( collection, fcn[, thisArg] )"],["keyByRight","keyByRight( collection, fcn[, thisArg] )"],["keysIn","keysIn( obj )"],["kruskalTest","kruskalTest( ...x[, options] )"],["kstest","kstest( x, y[, ...params][, options] )"],["last","last( str[, n][, options] )"],["leveneTest","leveneTest( x[, ...y[, options]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start, stop, length[, options] )"],["linspace.assign","linspace.assign( start, stop, out[, options] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a, b[, length] )"],["lowercase","lowercase( str )"],["lowercaseKeys","lowercaseKeys( obj )"],["lowess","lowess( x, y[, options] )"],["lpad","lpad( str, len[, pad] )"],["ltrim","ltrim( str )"],["ltrimN","ltrimN( str, n[, chars] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr, fcn[, thisArg] )"],["map.assign","map.assign( arr, out, fcn[, thisArg] )"],["map2","map2( x, y, fcn[, thisArg] )"],["map2.assign","map2.assign( x, y, out, fcn[, thisArg] )"],["map2d","map2d( arr, fcn[, thisArg] )"],["map2Right","map2Right( x, y, fcn[, thisArg] )"],["map2Right.assign","map2Right.assign( x, y, out, fcn[, thisArg] )"],["map3d","map3d( arr, fcn[, thisArg] )"],["map4d","map4d( arr, fcn[, thisArg] )"],["map5d","map5d( arr, fcn[, thisArg] )"],["mapArguments","mapArguments( fcn, clbk[, thisArg] )"],["mapFun","mapFun( fcn, n[, thisArg] )"],["mapFunAsync","mapFunAsync( fcn, n, [options,] done )"],["mapFunAsync.factory","mapFunAsync.factory( [options,] fcn )"],["mapKeys","mapKeys( obj, transform )"],["mapKeysAsync","mapKeysAsync( obj, [options,] transform, done )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options,] transform )"],["mapReduce","mapReduce( arr, initial, mapper, reducer[, thisArg] )"],["mapReduceRight","mapReduceRight( arr, initial, mapper, reducer[, thisArg] )"],["mapRight","mapRight( arr, fcn[, thisArg] )"],["mapRight.assign","mapRight.assign( arr, out, fcn[, thisArg] )"],["mapValues","mapValues( obj, transform )"],["mapValuesAsync","mapValuesAsync( obj, [options,] transform, done )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options,] transform )"],["maskArguments","maskArguments( fcn, mask[, thisArg] )"],["matrix","matrix( [dtype][, options] )"],["matrix","matrix( shape[, dtype][, options] )"],["matrix","matrix( M, N[, dtype][, options] )"],["matrix","matrix( obj[, dtype][, options] )"],["matrix","matrix( buffer[, byteOffset[, shape]][, dtype][, options] )"],["matrix","matrix( buffer[, byteOffset[, M, N]][, dtype][, options] )"],["matrix.factory","matrix.factory( dtype[, options] )"],["MAX_ARRAY_LENGTH","MAX_ARRAY_LENGTH"],["MAX_TYPED_ARRAY_LENGTH","MAX_TYPED_ARRAY_LENGTH"],["maybeBroadcastArray","maybeBroadcastArray( x, shape )"],["maybeBroadcastArrays","maybeBroadcastArrays( ...arrays )"],["memoize","memoize( fcn[, hashFunction] )"],["merge","merge( target, ...source )"],["merge.factory","merge.factory( options )"],["MILLISECONDS_IN_DAY","MILLISECONDS_IN_DAY"],["MILLISECONDS_IN_HOUR","MILLISECONDS_IN_HOUR"],["MILLISECONDS_IN_MINUTE","MILLISECONDS_IN_MINUTE"],["MILLISECONDS_IN_SECOND","MILLISECONDS_IN_SECOND"],["MILLISECONDS_IN_WEEK","MILLISECONDS_IN_WEEK"],["MINARD_NAPOLEONS_MARCH","MINARD_NAPOLEONS_MARCH( [options] )"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month[, year]] )"],["minutesInYear","minutesInYear( [value] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source, prop, target )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields[, options] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn, arity[, thisArg] )"],["nativeClass","nativeClass( value )"],["ndarray","ndarray( dtype, buffer, shape, strides, offset, order[, options] )"],["ndarray.prototype.byteLength","ndarray.prototype.byteLength"],["ndarray.prototype.BYTES_PER_ELEMENT","ndarray.prototype.BYTES_PER_ELEMENT"],["ndarray.prototype.data","ndarray.prototype.data"],["ndarray.prototype.dtype","ndarray.prototype.dtype"],["ndarray.prototype.flags","ndarray.prototype.flags"],["ndarray.prototype.length","ndarray.prototype.length"],["ndarray.prototype.ndims","ndarray.prototype.ndims"],["ndarray.prototype.offset","ndarray.prototype.offset"],["ndarray.prototype.order","ndarray.prototype.order"],["ndarray.prototype.shape","ndarray.prototype.shape"],["ndarray.prototype.strides","ndarray.prototype.strides"],["ndarray.prototype.get","ndarray.prototype.get( ...idx )"],["ndarray.prototype.iget","ndarray.prototype.iget( idx )"],["ndarray.prototype.set","ndarray.prototype.set( ...idx, v )"],["ndarray.prototype.iset","ndarray.prototype.iset( idx, v )"],["ndarray.prototype.toString","ndarray.prototype.toString()"],["ndarray.prototype.toJSON","ndarray.prototype.toJSON()"],["ndarray2array","ndarray2array( x )"],["ndarray2fancy","ndarray2fancy( x[, options] )"],["ndarray2fancy.factory","ndarray2fancy.factory( [options] )"],["ndarray2fancy.idx","ndarray2fancy.idx( x[, options] )"],["ndarray2json","ndarray2json( x )"],["ndarrayCastingModes","ndarrayCastingModes()"],["ndarrayDataBuffer","ndarrayDataBuffer( x )"],["ndarrayDataType","ndarrayDataType( x )"],["ndarrayDataTypes","ndarrayDataTypes( [kind] )"],["ndarrayDataTypes.binary","ndarrayDataTypes.binary"],["ndarrayDataTypes.boolean","ndarrayDataTypes.boolean"],["ndarrayDataTypes.complex32","ndarrayDataTypes.complex32"],["ndarrayDataTypes.complex64","ndarrayDataTypes.complex64"],["ndarrayDataTypes.complex128","ndarrayDataTypes.complex128"],["ndarrayDataTypes.float16","ndarrayDataTypes.float16"],["ndarrayDataTypes.float32","ndarrayDataTypes.float32"],["ndarrayDataTypes.float64","ndarrayDataTypes.float64"],["ndarrayDataTypes.generic","ndarrayDataTypes.generic"],["ndarrayDataTypes.int8","ndarrayDataTypes.int8"],["ndarrayDataTypes.int16","ndarrayDataTypes.int16"],["ndarrayDataTypes.int32","ndarrayDataTypes.int32"],["ndarrayDataTypes.uint8","ndarrayDataTypes.uint8"],["ndarrayDataTypes.uint8c","ndarrayDataTypes.uint8c"],["ndarrayDataTypes.uint16","ndarrayDataTypes.uint16"],["ndarrayDataTypes.uint32","ndarrayDataTypes.uint32"],["ndarrayDispatch","ndarrayDispatch( fcns, types, data, nargs, nin, nout )"],["ndarrayFlag","ndarrayFlag( x, name )"],["ndarrayFlags","ndarrayFlags( x )"],["ndarrayIndexModes","ndarrayIndexModes()"],["ndarraylike2ndarray","ndarraylike2ndarray( x[, options] )"],["ndarrayMinDataType","ndarrayMinDataType( value )"],["ndarrayMostlySafeCasts","ndarrayMostlySafeCasts( [dtype] )"],["ndarrayNextDataType","ndarrayNextDataType( [dtype] )"],["ndarrayOffset","ndarrayOffset( x )"],["ndarrayOrder","ndarrayOrder( x )"],["ndarrayOrders","ndarrayOrders()"],["ndarrayPromotionRules","ndarrayPromotionRules( [dtype1, dtype2] )"],["ndarraySafeCasts","ndarraySafeCasts( [dtype] )"],["ndarraySameKindCasts","ndarraySameKindCasts( [dtype] )"],["ndarrayShape","ndarrayShape( x )"],["ndarrayStride","ndarrayStride( x, dim )"],["ndarrayStrides","ndarrayStrides( x )"],["ndat","ndat( x[, ...indices] )"],["ndempty","ndempty( shape[, options] )"],["ndemptyLike","ndemptyLike( x[, options] )"],["ndfill","ndfill( x, value )"],["ndfillBy","ndfillBy( x, fcn[, thisArg] )"],["ndfilter","ndfilter( x[, options], predicate[, thisArg] )"],["ndfilterMap","ndfilterMap( x[, options], fcn[, thisArg] )"],["ndforEach","ndforEach( x, fcn[, thisArg] )"],["ndims","ndims( x )"],["ndindex","ndindex( x[, options] )"],["ndindex.free","ndindex.free( id )"],["ndindex.get","ndindex.get( id )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x[, options] )"],["ndindex.linearIndex","ndindex.linearIndex( x[, options] )"],["ndindex.prototype.data","ndindex.prototype.data"],["ndindex.prototype.dtype","ndindex.prototype.dtype"],["ndindex.prototype.id","ndindex.prototype.id"],["ndindex.prototype.isCached","ndindex.prototype.isCached"],["ndindex.prototype.kind","ndindex.prototype.kind"],["ndindex.prototype.type","ndindex.prototype.type"],["ndindex.prototype.toString","ndindex.prototype.toString()"],["ndindex.prototype.toJSON","ndindex.prototype.toJSON()"],["nditer2arrayEach","nditer2arrayEach( iterator )"],["nditerColumnEntries","nditerColumnEntries( x[, options] )"],["nditerColumns","nditerColumns( x[, options] )"],["nditerEntries","nditerEntries( x[, options] )"],["nditerIndices","nditerIndices( shape[, options] )"],["nditerInterleaveSubarrays","nditerInterleaveSubarrays( arr, ndims )"],["nditerMatrices","nditerMatrices( x[, options] )"],["nditerMatrixEntries","nditerMatrixEntries( x[, options] )"],["nditerRowEntries","nditerRowEntries( x[, options] )"],["nditerRows","nditerRows( x[, options] )"],["nditerSelectDimension","nditerSelectDimension( x, dim[, options] )"],["nditerStacks","nditerStacks( x, dims[, options] )"],["nditerSubarrays","nditerSubarrays( x, ndims[, options] )"],["nditerValues","nditerValues( x[, options] )"],["ndmap","ndmap( x[, options], fcn[, thisArg] )"],["ndreject","ndreject( x[, options], predicate[, thisArg] )"],["ndslice","ndslice( x, ...s[, options] )"],["ndsliceAssign","ndsliceAssign( x, y, ...s[, options] )"],["ndsliceDimension","ndsliceDimension( x, dim, slice[, options] )"],["ndsliceDimensionFrom","ndsliceDimensionFrom( x, dim, start[, options] )"],["ndsliceDimensionTo","ndsliceDimensionTo( x, dim, stop[, options] )"],["ndsliceFrom","ndsliceFrom( x, ...start[, options] )"],["ndsliceTo","ndsliceTo( x, ...stop[, options] )"],["ndzeros","ndzeros( shape[, options] )"],["ndzerosLike","ndzerosLike( x[, options] )"],["nextGraphemeClusterBreak","nextGraphemeClusterBreak( str[, fromIndex] )"],["nextTick","nextTick( clbk[, ...args] )"],["NIGHTINGALES_ROSE","NIGHTINGALES_ROSE()"],["NINF","NINF"],["NODE_VERSION","NODE_VERSION"],["none","none( collection )"],["noneBy","noneBy( collection, predicate[, thisArg ] )"],["noneByAsync","noneByAsync( collection, [options,] predicate, done )"],["noneByAsync.factory","noneByAsync.factory( [options,] predicate )"],["noneByRight","noneByRight( collection, predicate[, thisArg ] )"],["noneByRightAsync","noneByRightAsync( collection, [options,] predicate, done )"],["noneByRightAsync.factory","noneByRightAsync.factory( [options,] predicate )"],["noneInBy","noneInBy( object, predicate[, thisArg ] )"],["nonEnumerableProperties","nonEnumerableProperties( value )"],["nonEnumerablePropertiesIn","nonEnumerablePropertiesIn( value )"],["nonEnumerablePropertyNames","nonEnumerablePropertyNames( value )"],["nonEnumerablePropertyNamesIn","nonEnumerablePropertyNamesIn( value )"],["nonEnumerablePropertySymbols","nonEnumerablePropertySymbols( value )"],["nonEnumerablePropertySymbolsIn","nonEnumerablePropertySymbolsIn( value )"],["noneOwnBy","noneOwnBy( object, predicate[, thisArg ] )"],["nonIndexKeys","nonIndexKeys( obj )"],["noop","noop()"],["now","now()"],["NUM_CPUS","NUM_CPUS"],["num2words","num2words( value[, options] )"],["Number","Number( value )"],["numel","numel( x )"],["numelDimension","numelDimension( x, dim )"],["numGraphemeClusters","numGraphemeClusters( str )"],["Object","Object( value )"],["Object.assign","Object.assign( target, ...sources )"],["Object.create","Object.create( prototype, properties )"],["Object.defineProperties","Object.defineProperties( obj, properties )"],["Object.defineProperty","Object.defineProperty( obj, key, descriptor )"],["Object.entries","Object.entries( obj )"],["Object.freeze","Object.freeze( obj )"],["Object.getOwnPropertyDescriptor","Object.getOwnPropertyDescriptor( obj, key )"],["Object.getOwnPropertyDescriptors","Object.getOwnPropertyDescriptors( obj )"],["Object.getOwnPropertyNames","Object.getOwnPropertyNames( obj )"],["Object.getOwnPropertySymbols","Object.getOwnPropertySymbols( obj )"],["Object.getPrototypeOf","Object.getPrototypeOf( obj )"],["Object.hasOwn","Object.hasOwn( obj, p )"],["Object.is","Object.is( value1, value2 )"],["Object.isExtensible","Object.isExtensible( obj )"],["Object.isFrozen","Object.isFrozen( obj )"],["Object.isSealed","Object.isSealed( obj )"],["Object.keys","Object.keys( obj )"],["Object.preventExtensions","Object.preventExtensions( obj )"],["Object.seal","Object.seal( obj )"],["Object.setPrototypeOf","Object.setPrototypeOf( obj, proto )"],["Object.values","Object.values( obj )"],["Object.prototype.toLocaleString","Object.prototype.toLocaleString()"],["Object.prototype.toString","Object.prototype.toString()"],["Object.prototype.valueOf","Object.prototype.valueOf()"],["Object.prototype.hasOwnProperty","Object.prototype.hasOwnProperty( p )"],["Object.prototype.isPrototypeOf","Object.prototype.isPrototypeOf( obj )"],["Object.prototype.propertyIsEnumerable","Object.prototype.propertyIsEnumerable( p )"],["Object.prototype.constructor","Object.prototype.constructor"],["objectEntries","objectEntries( obj )"],["objectEntriesIn","objectEntriesIn( obj )"],["objectFromEntries","objectFromEntries( entries )"],["objectInverse","objectInverse( obj[, options] )"],["objectInverseBy","objectInverseBy( obj, [options,] transform )"],["objectKeys","objectKeys( value )"],["objectValues","objectValues( obj )"],["objectValuesIn","objectValuesIn( obj )"],["omit","omit( obj, keys )"],["omitBy","omitBy( obj, predicate )"],["open","open( path[, flags[, mode]], clbk )"],["open.sync","open.sync( path[, flags[, mode]] )"],["openURL","openURL( url )"],["ordinalize","ordinalize( value[, options] )"],["PACE_BOSTON_HOUSE_PRICES","PACE_BOSTON_HOUSE_PRICES()"],["pad","pad( str, len[, options] )"],["padjust","padjust( pvals, method[, comparisons] )"],["papply","papply( fcn, ...args )"],["papplyRight","papplyRight( fcn, ...args )"],["parallel","parallel( files, [options,] clbk )"],["parseJSON","parseJSON( str[, reviver] )"],["pascalcase","pascalcase( str )"],["PATH_DELIMITER","PATH_DELIMITER"],["PATH_DELIMITER_POSIX","PATH_DELIMITER_POSIX"],["PATH_DELIMITER_WIN32","PATH_DELIMITER_WIN32"],["PATH_SEP","PATH_SEP"],["PATH_SEP_POSIX","PATH_SEP_POSIX"],["PATH_SEP_WIN32","PATH_SEP_WIN32"],["pcorrtest","pcorrtest( x, y[, options] )"],["percentEncode","percentEncode( str )"],["PHI","PHI"],["PI","PI"],["PI_SQUARED","PI_SQUARED"],["pick","pick( obj, keys )"],["pickArguments","pickArguments( fcn, indices[, thisArg] )"],["pickBy","pickBy( obj, predicate 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sx, y, sy, clbk[, thisArg] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sqrt","strided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sqrtBy","strided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sub","strided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.sub.ndarray","strided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.subBy","strided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.trunc","strided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.trunc.ndarray","strided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, 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value )"],["isCollection","isCollection( value )"],["isComplex","isComplex( value )"],["isComplex64","isComplex64( value )"],["isComplex64Array","isComplex64Array( value )"],["isComplex64MatrixLike","isComplex64MatrixLike( value )"],["isComplex64ndarrayLike","isComplex64ndarrayLike( value )"],["isComplex64VectorLike","isComplex64VectorLike( value )"],["isComplex128","isComplex128( value )"],["isComplex128Array","isComplex128Array( value )"],["isComplex128MatrixLike","isComplex128MatrixLike( value )"],["isComplex128ndarrayLike","isComplex128ndarrayLike( value )"],["isComplex128VectorLike","isComplex128VectorLike( value )"],["isComplexLike","isComplexLike( value )"],["isComplexTypedArray","isComplexTypedArray( value )"],["isComplexTypedArrayLike","isComplexTypedArrayLike( value )"],["isComposite","isComposite( value )"],["isComposite.isPrimitive","isComposite.isPrimitive( value )"],["isComposite.isObject","isComposite.isObject( value )"],["isConfigurableProperty","isConfigurableProperty( value, property )"],["isConfigurablePropertyIn","isConfigurablePropertyIn( value, property )"],["isConstantcase","isConstantcase( value )"],["isCubeNumber","isCubeNumber( value )"],["isCubeNumber.isPrimitive","isCubeNumber.isPrimitive( value )"],["isCubeNumber.isObject","isCubeNumber.isObject( value )"],["isCurrentYear","isCurrentYear( value )"],["isDataProperty","isDataProperty( value, property )"],["isDataPropertyIn","isDataPropertyIn( value, property )"],["isDataView","isDataView( value )"],["isDateObject","isDateObject( value )"],["isDateObjectArray","isDateObjectArray( value )"],["isDigitString","isDigitString( str )"],["isDomainName","isDomainName( value )"],["isDurationString","isDurationString( value )"],["isEmailAddress","isEmailAddress( value )"],["isEmptyArray","isEmptyArray( value )"],["isEmptyArrayLikeObject","isEmptyArrayLikeObject( value )"],["isEmptyCollection","isEmptyCollection( value )"],["isEmptyObject","isEmptyObject( value )"],["isEmptyString","isEmptyString( value )"],["isEmptyString.isPrimitive","isEmptyString.isPrimitive( value )"],["isEmptyString.isObject","isEmptyString.isObject( value )"],["isEnumerableProperty","isEnumerableProperty( value, property )"],["isEnumerablePropertyIn","isEnumerablePropertyIn( value, property )"],["isEqualArray","isEqualArray( v1, v2 )"],["isEqualDateObject","isEqualDateObject( d1, d2 )"],["isError","isError( value )"],["isEvalError","isEvalError( value )"],["isEven","isEven( value )"],["isEven.isPrimitive","isEven.isPrimitive( value )"],["isEven.isObject","isEven.isObject( value )"],["isFalsy","isFalsy( value )"],["isFalsyArray","isFalsyArray( value )"],["isFinite","isFinite( value )"],["isFinite.isPrimitive","isFinite.isPrimitive( value )"],["isFinite.isObject","isFinite.isObject( value )"],["isFiniteArray","isFiniteArray( value )"],["isFiniteArray.primitives","isFiniteArray.primitives( value )"],["isFiniteArray.objects","isFiniteArray.objects( value )"],["isFloat32Array","isFloat32Array( value 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)"],["isObjectLike","isObjectLike( value )"],["isOdd","isOdd( value )"],["isOdd.isPrimitive","isOdd.isPrimitive( value )"],["isOdd.isObject","isOdd.isObject( value )"],["isoWeeksInYear","isoWeeksInYear( [value] )"],["isPascalcase","isPascalcase( value )"],["isPersymmetricMatrix","isPersymmetricMatrix( value )"],["isPlainObject","isPlainObject( value )"],["isPlainObjectArray","isPlainObjectArray( value )"],["isPositiveFinite","isPositiveFinite( value )"],["isPositiveFinite.isPrimitive","isPositiveFinite.isPrimitive( value )"],["isPositiveFinite.isObject","isPositiveFinite.isObject( value )"],["isPositiveInteger","isPositiveInteger( value )"],["isPositiveInteger.isPrimitive","isPositiveInteger.isPrimitive( value )"],["isPositiveInteger.isObject","isPositiveInteger.isObject( value )"],["isPositiveIntegerArray","isPositiveIntegerArray( value )"],["isPositiveIntegerArray.primitives","isPositiveIntegerArray.primitives( value 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)"],["isRegExpString","isRegExpString( value )"],["isRelativePath","isRelativePath( value )"],["isRelativePath.posix","isRelativePath.posix( value )"],["isRelativePath.win32","isRelativePath.win32( value )"],["isRelativeURI","isRelativeURI( value )"],["isSafeInteger","isSafeInteger( value )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value )"],["isSafeInteger.isObject","isSafeInteger.isObject( value )"],["isSafeIntegerArray","isSafeIntegerArray( value )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value )"],["isSameArray","isSameArray( v1, v2 )"],["isSameArrayLike","isSameArrayLike( v1, v2 )"],["isSameComplex64","isSameComplex64( v1, v2 )"],["isSameComplex64Array","isSameComplex64Array( v1, v2 )"],["isSameComplex128","isSameComplex128( v1, v2 )"],["isSameComplex128Array","isSameComplex128Array( v1, v2 )"],["isSameFloat32Array","isSameFloat32Array( v1, v2 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)"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value )"],["isStartcase","isStartcase( value )"],["isStrictEqual","isStrictEqual( a, b )"],["isString","isString( value )"],["isString.isPrimitive","isString.isPrimitive( value )"],["isString.isObject","isString.isObject( value )"],["isStringArray","isStringArray( value )"],["isStringArray.primitives","isStringArray.primitives( value )"],["isStringArray.objects","isStringArray.objects( value )"],["isStruct","isStruct( value )"],["isStructConstructorLike","isStructConstructorLike( value )"],["isSymbol","isSymbol( value )"],["isSymbolArray","isSymbolArray( value )"],["isSymbolArray.primitives","isSymbolArray.primitives( value )"],["isSymbolArray.objects","isSymbolArray.objects( value )"],["isSymmetricMatrix","isSymmetricMatrix( value )"],["isSyntaxError","isSyntaxError( value )"],["isTriangularNumber","isTriangularNumber( value )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value 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)"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value, property )"],["iterAbs","iterAbs( iterator )"],["iterAbs2","iterAbs2( iterator )"],["iterAcos","iterAcos( iterator )"],["iterAcosh","iterAcosh( iterator )"],["iterAcot","iterAcot( iterator )"],["iterAcoth","iterAcoth( iterator )"],["iterAcovercos","iterAcovercos( iterator )"],["iterAcoversin","iterAcoversin( iterator )"],["iterAdd","iterAdd( iter0, ...iterator )"],["iterAdvance","iterAdvance( iterator[, n] )"],["iterAhavercos","iterAhavercos( iterator )"],["iterAhaversin","iterAhaversin( iterator )"],["iterAny","iterAny( iterator )"],["iterAnyBy","iterAnyBy( iterator, predicate[, thisArg ] )"],["iterAsin","iterAsin( iterator )"],["iterAsinh","iterAsinh( iterator )"],["iterAtan","iterAtan( iterator )"],["iterAtan2","iterAtan2( y, x )"],["iterAtanh","iterAtanh( iterator )"],["iterator2array","iterator2array( iterator[, out][, mapFcn[, thisArg]] )"],["iterator2arrayview","iterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoUntilEach","iterDoUntilEach( iterator, predicate, fcn[, thisArg] )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W 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)"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] )"],["iterStrided","iterStrided( iterator, stride[, offset[, eager]] )"],["iterStridedBy","iterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items )"],["iterUntilEach","iterUntilEach( iterator, predicate, fcn[, thisArg] )"],["itervariance","itervariance( iterator[, mean] )"],["iterVercos","iterVercos( iterator )"],["iterVersin","iterVersin( iterator )"],["iterWhileEach","iterWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterZeta","iterZeta( iterator )"],["joinStream","joinStream( [options] )"],["joinStream.factory","joinStream.factory( [options] )"],["joinStream.objectMode","joinStream.objectMode( [options] )"],["kde2d","kde2d( x, y[, options] )"],["kebabcase","kebabcase( str )"],["keyBy","keyBy( collection, fcn[, thisArg] )"],["keyByRight","keyByRight( collection, fcn[, thisArg] )"],["keysIn","keysIn( obj )"],["kruskalTest","kruskalTest( ...x[, options] )"],["kstest","kstest( x, y[, ...params][, options] )"],["last","last( str[, n][, options] )"],["leveneTest","leveneTest( x[, ...y[, options]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start, stop, length[, options] )"],["linspace.assign","linspace.assign( start, stop, out[, options] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a, b[, length] )"],["lowercase","lowercase( str )"],["lowercaseKeys","lowercaseKeys( obj )"],["lowess","lowess( x, y[, options] )"],["lpad","lpad( str, len[, pad] )"],["ltrim","ltrim( str )"],["ltrimN","ltrimN( str, n[, chars] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr, fcn[, thisArg] )"],["map.assign","map.assign( arr, out, fcn[, thisArg] )"],["map2","map2( x, y, fcn[, thisArg] )"],["map2.assign","map2.assign( x, y, out, fcn[, thisArg] )"],["map2d","map2d( arr, fcn[, thisArg] )"],["map2Right","map2Right( x, y, fcn[, thisArg] )"],["map2Right.assign","map2Right.assign( x, y, out, fcn[, thisArg] )"],["map3d","map3d( arr, fcn[, thisArg] )"],["map4d","map4d( arr, fcn[, thisArg] )"],["map5d","map5d( arr, fcn[, thisArg] )"],["mapArguments","mapArguments( fcn, clbk[, thisArg] )"],["mapFun","mapFun( fcn, n[, thisArg] )"],["mapFunAsync","mapFunAsync( fcn, n, [options,] done )"],["mapFunAsync.factory","mapFunAsync.factory( [options,] fcn )"],["mapKeys","mapKeys( obj, transform )"],["mapKeysAsync","mapKeysAsync( obj, [options,] transform, done )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options,] transform )"],["mapReduce","mapReduce( arr, initial, mapper, reducer[, thisArg] )"],["mapReduceRight","mapReduceRight( arr, initial, mapper, reducer[, thisArg] )"],["mapRight","mapRight( arr, fcn[, thisArg] )"],["mapRight.assign","mapRight.assign( arr, out, fcn[, thisArg] )"],["mapValues","mapValues( obj, transform )"],["mapValuesAsync","mapValuesAsync( obj, [options,] transform, done )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options,] transform )"],["maskArguments","maskArguments( fcn, mask[, thisArg] )"],["matrix","matrix( [dtype][, options] )"],["matrix","matrix( shape[, dtype][, options] )"],["matrix","matrix( M, N[, dtype][, options] )"],["matrix","matrix( obj[, dtype][, options] )"],["matrix","matrix( buffer[, byteOffset[, shape]][, dtype][, options] )"],["matrix","matrix( buffer[, byteOffset[, M, N]][, dtype][, options] )"],["matrix.factory","matrix.factory( dtype[, options] )"],["MAX_ARRAY_LENGTH","MAX_ARRAY_LENGTH"],["MAX_TYPED_ARRAY_LENGTH","MAX_TYPED_ARRAY_LENGTH"],["maybeBroadcastArray","maybeBroadcastArray( x, shape )"],["maybeBroadcastArrays","maybeBroadcastArrays( ...arrays )"],["memoize","memoize( fcn[, hashFunction] )"],["merge","merge( target, ...source )"],["merge.factory","merge.factory( options )"],["MILLISECONDS_IN_DAY","MILLISECONDS_IN_DAY"],["MILLISECONDS_IN_HOUR","MILLISECONDS_IN_HOUR"],["MILLISECONDS_IN_MINUTE","MILLISECONDS_IN_MINUTE"],["MILLISECONDS_IN_SECOND","MILLISECONDS_IN_SECOND"],["MILLISECONDS_IN_WEEK","MILLISECONDS_IN_WEEK"],["MINARD_NAPOLEONS_MARCH","MINARD_NAPOLEONS_MARCH( [options] )"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month[, year]] )"],["minutesInYear","minutesInYear( [value] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source, prop, target )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields[, options] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn, arity[, thisArg] )"],["nativeClass","nativeClass( value )"],["ndarray","ndarray( dtype, buffer, shape, strides, offset, order[, options] )"],["ndarray.prototype.byteLength","ndarray.prototype.byteLength"],["ndarray.prototype.BYTES_PER_ELEMENT","ndarray.prototype.BYTES_PER_ELEMENT"],["ndarray.prototype.data","ndarray.prototype.data"],["ndarray.prototype.dtype","ndarray.prototype.dtype"],["ndarray.prototype.flags","ndarray.prototype.flags"],["ndarray.prototype.length","ndarray.prototype.length"],["ndarray.prototype.ndims","ndarray.prototype.ndims"],["ndarray.prototype.offset","ndarray.prototype.offset"],["ndarray.prototype.order","ndarray.prototype.order"],["ndarray.prototype.shape","ndarray.prototype.shape"],["ndarray.prototype.strides","ndarray.prototype.strides"],["ndarray.prototype.get","ndarray.prototype.get( ...idx )"],["ndarray.prototype.iget","ndarray.prototype.iget( idx )"],["ndarray.prototype.set","ndarray.prototype.set( ...idx, v )"],["ndarray.prototype.iset","ndarray.prototype.iset( idx, v )"],["ndarray.prototype.toString","ndarray.prototype.toString()"],["ndarray.prototype.toJSON","ndarray.prototype.toJSON()"],["ndarray2array","ndarray2array( x )"],["ndarray2fancy","ndarray2fancy( x[, options] )"],["ndarray2fancy.factory","ndarray2fancy.factory( [options] )"],["ndarray2fancy.idx","ndarray2fancy.idx( x[, options] )"],["ndarray2json","ndarray2json( x )"],["ndarrayCastingModes","ndarrayCastingModes()"],["ndarrayDataBuffer","ndarrayDataBuffer( x )"],["ndarrayDataType","ndarrayDataType( x )"],["ndarrayDataTypes","ndarrayDataTypes( [kind] )"],["ndarrayDataTypes.binary","ndarrayDataTypes.binary"],["ndarrayDataTypes.boolean","ndarrayDataTypes.boolean"],["ndarrayDataTypes.complex32","ndarrayDataTypes.complex32"],["ndarrayDataTypes.complex64","ndarrayDataTypes.complex64"],["ndarrayDataTypes.complex128","ndarrayDataTypes.complex128"],["ndarrayDataTypes.float16","ndarrayDataTypes.float16"],["ndarrayDataTypes.float32","ndarrayDataTypes.float32"],["ndarrayDataTypes.float64","ndarrayDataTypes.float64"],["ndarrayDataTypes.generic","ndarrayDataTypes.generic"],["ndarrayDataTypes.int8","ndarrayDataTypes.int8"],["ndarrayDataTypes.int16","ndarrayDataTypes.int16"],["ndarrayDataTypes.int32","ndarrayDataTypes.int32"],["ndarrayDataTypes.uint8","ndarrayDataTypes.uint8"],["ndarrayDataTypes.uint8c","ndarrayDataTypes.uint8c"],["ndarrayDataTypes.uint16","ndarrayDataTypes.uint16"],["ndarrayDataTypes.uint32","ndarrayDataTypes.uint32"],["ndarrayDispatch","ndarrayDispatch( fcns, types, data, nargs, nin, nout )"],["ndarrayFlag","ndarrayFlag( x, name )"],["ndarrayFlags","ndarrayFlags( x )"],["ndarrayIndexModes","ndarrayIndexModes()"],["ndarraylike2ndarray","ndarraylike2ndarray( x[, options] )"],["ndarrayMinDataType","ndarrayMinDataType( value )"],["ndarrayMostlySafeCasts","ndarrayMostlySafeCasts( [dtype] )"],["ndarrayNextDataType","ndarrayNextDataType( [dtype] )"],["ndarrayOffset","ndarrayOffset( x )"],["ndarrayOrder","ndarrayOrder( x )"],["ndarrayOrders","ndarrayOrders()"],["ndarrayPromotionRules","ndarrayPromotionRules( [dtype1, dtype2] )"],["ndarraySafeCasts","ndarraySafeCasts( [dtype] )"],["ndarraySameKindCasts","ndarraySameKindCasts( [dtype] )"],["ndarrayShape","ndarrayShape( x )"],["ndarrayStride","ndarrayStride( x, dim )"],["ndarrayStrides","ndarrayStrides( x )"],["ndat","ndat( x[, ...indices] )"],["ndempty","ndempty( shape[, options] )"],["ndemptyLike","ndemptyLike( x[, options] )"],["ndfill","ndfill( x, value )"],["ndfillBy","ndfillBy( x, fcn[, thisArg] )"],["ndfilter","ndfilter( x[, options], predicate[, thisArg] )"],["ndfilterMap","ndfilterMap( x[, options], fcn[, thisArg] )"],["ndforEach","ndforEach( x, fcn[, thisArg] )"],["ndims","ndims( x )"],["ndindex","ndindex( x[, options] )"],["ndindex.free","ndindex.free( id )"],["ndindex.get","ndindex.get( id )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x[, options] )"],["ndindex.linearIndex","ndindex.linearIndex( x[, options] )"],["ndindex.prototype.data","ndindex.prototype.data"],["ndindex.prototype.dtype","ndindex.prototype.dtype"],["ndindex.prototype.id","ndindex.prototype.id"],["ndindex.prototype.isCached","ndindex.prototype.isCached"],["ndindex.prototype.kind","ndindex.prototype.kind"],["ndindex.prototype.type","ndindex.prototype.type"],["ndindex.prototype.toString","ndindex.prototype.toString()"],["ndindex.prototype.toJSON","ndindex.prototype.toJSON()"],["nditer2arrayEach","nditer2arrayEach( iterator )"],["nditerColumnEntries","nditerColumnEntries( x[, options] )"],["nditerColumns","nditerColumns( x[, options] )"],["nditerEntries","nditerEntries( x[, options] )"],["nditerIndices","nditerIndices( shape[, options] )"],["nditerInterleaveSubarrays","nditerInterleaveSubarrays( arr, ndims )"],["nditerMatrices","nditerMatrices( x[, options] )"],["nditerMatrixEntries","nditerMatrixEntries( x[, options] )"],["nditerRowEntries","nditerRowEntries( x[, options] )"],["nditerRows","nditerRows( x[, options] )"],["nditerSelectDimension","nditerSelectDimension( x, dim[, options] )"],["nditerStacks","nditerStacks( x, dims[, options] )"],["nditerSubarrays","nditerSubarrays( x, ndims[, options] )"],["nditerValues","nditerValues( x[, options] )"],["ndmap","ndmap( x[, options], fcn[, thisArg] )"],["ndreject","ndreject( x[, options], predicate[, thisArg] )"],["ndslice","ndslice( x, ...s[, options] )"],["ndsliceAssign","ndsliceAssign( x, y, ...s[, options] )"],["ndsliceDimension","ndsliceDimension( x, dim, slice[, options] )"],["ndsliceDimensionFrom","ndsliceDimensionFrom( x, dim, start[, options] )"],["ndsliceDimensionTo","ndsliceDimensionTo( x, dim, stop[, options] )"],["ndsliceFrom","ndsliceFrom( x, ...start[, options] )"],["ndsliceTo","ndsliceTo( x, ...stop[, options] )"],["ndzeros","ndzeros( shape[, options] )"],["ndzerosLike","ndzerosLike( x[, options] )"],["nextGraphemeClusterBreak","nextGraphemeClusterBreak( str[, fromIndex] )"],["nextTick","nextTick( clbk[, ...args] )"],["NIGHTINGALES_ROSE","NIGHTINGALES_ROSE()"],["NINF","NINF"],["NODE_VERSION","NODE_VERSION"],["none","none( collection )"],["noneBy","noneBy( collection, predicate[, thisArg ] )"],["noneByAsync","noneByAsync( collection, [options,] predicate, done )"],["noneByAsync.factory","noneByAsync.factory( [options,] predicate )"],["noneByRight","noneByRight( collection, predicate[, thisArg ] )"],["noneByRightAsync","noneByRightAsync( collection, [options,] predicate, done )"],["noneByRightAsync.factory","noneByRightAsync.factory( [options,] predicate )"],["noneInBy","noneInBy( object, predicate[, thisArg ] )"],["nonEnumerableProperties","nonEnumerableProperties( value )"],["nonEnumerablePropertiesIn","nonEnumerablePropertiesIn( value )"],["nonEnumerablePropertyNames","nonEnumerablePropertyNames( value )"],["nonEnumerablePropertyNamesIn","nonEnumerablePropertyNamesIn( value )"],["nonEnumerablePropertySymbols","nonEnumerablePropertySymbols( value )"],["nonEnumerablePropertySymbolsIn","nonEnumerablePropertySymbolsIn( value )"],["noneOwnBy","noneOwnBy( object, predicate[, thisArg ] )"],["nonIndexKeys","nonIndexKeys( obj )"],["noop","noop()"],["now","now()"],["NUM_CPUS","NUM_CPUS"],["num2words","num2words( value[, options] )"],["Number","Number( value )"],["numel","numel( x )"],["numelDimension","numelDimension( x, dim )"],["numGraphemeClusters","numGraphemeClusters( str )"],["Object","Object( value )"],["Object.assign","Object.assign( target, ...sources )"],["Object.create","Object.create( prototype, properties )"],["Object.defineProperties","Object.defineProperties( obj, properties )"],["Object.defineProperty","Object.defineProperty( obj, key, descriptor )"],["Object.entries","Object.entries( obj )"],["Object.freeze","Object.freeze( obj )"],["Object.getOwnPropertyDescriptor","Object.getOwnPropertyDescriptor( obj, key )"],["Object.getOwnPropertyDescriptors","Object.getOwnPropertyDescriptors( obj )"],["Object.getOwnPropertyNames","Object.getOwnPropertyNames( obj )"],["Object.getOwnPropertySymbols","Object.getOwnPropertySymbols( obj )"],["Object.getPrototypeOf","Object.getPrototypeOf( obj )"],["Object.hasOwn","Object.hasOwn( obj, p )"],["Object.is","Object.is( value1, value2 )"],["Object.isExtensible","Object.isExtensible( obj )"],["Object.isFrozen","Object.isFrozen( obj )"],["Object.isSealed","Object.isSealed( obj )"],["Object.keys","Object.keys( obj )"],["Object.preventExtensions","Object.preventExtensions( obj )"],["Object.seal","Object.seal( obj )"],["Object.setPrototypeOf","Object.setPrototypeOf( obj, proto )"],["Object.values","Object.values( obj )"],["Object.prototype.toLocaleString","Object.prototype.toLocaleString()"],["Object.prototype.toString","Object.prototype.toString()"],["Object.prototype.valueOf","Object.prototype.valueOf()"],["Object.prototype.hasOwnProperty","Object.prototype.hasOwnProperty( p )"],["Object.prototype.isPrototypeOf","Object.prototype.isPrototypeOf( obj )"],["Object.prototype.propertyIsEnumerable","Object.prototype.propertyIsEnumerable( p )"],["Object.prototype.constructor","Object.prototype.constructor"],["objectEntries","objectEntries( obj )"],["objectEntriesIn","objectEntriesIn( obj )"],["objectFromEntries","objectFromEntries( entries )"],["objectInverse","objectInverse( obj[, options] )"],["objectInverseBy","objectInverseBy( obj, [options,] transform )"],["objectKeys","objectKeys( value )"],["objectValues","objectValues( obj )"],["objectValuesIn","objectValuesIn( obj )"],["omit","omit( obj, keys )"],["omitBy","omitBy( obj, predicate )"],["open","open( path[, flags[, mode]], clbk )"],["open.sync","open.sync( path[, flags[, mode]] )"],["openURL","openURL( url )"],["ordinalize","ordinalize( value[, options] )"],["PACE_BOSTON_HOUSE_PRICES","PACE_BOSTON_HOUSE_PRICES()"],["pad","pad( str, len[, options] )"],["padjust","padjust( pvals, method[, comparisons] )"],["papply","papply( fcn, ...args )"],["papplyRight","papplyRight( fcn, ...args )"],["parallel","parallel( files, [options,] clbk )"],["parseJSON","parseJSON( str[, reviver] )"],["pascalcase","pascalcase( str )"],["PATH_DELIMITER","PATH_DELIMITER"],["PATH_DELIMITER_POSIX","PATH_DELIMITER_POSIX"],["PATH_DELIMITER_WIN32","PATH_DELIMITER_WIN32"],["PATH_SEP","PATH_SEP"],["PATH_SEP_POSIX","PATH_SEP_POSIX"],["PATH_SEP_WIN32","PATH_SEP_WIN32"],["pcorrtest","pcorrtest( x, y[, options] )"],["percentEncode","percentEncode( str )"],["PHI","PHI"],["PI","PI"],["PI_SQUARED","PI_SQUARED"],["pick","pick( obj, keys )"],["pickArguments","pickArguments( fcn, indices[, thisArg] )"],["pickBy","pickBy( obj, predicate 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sx, y, sy, clbk[, thisArg] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sqrt","strided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sqrtBy","strided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sub","strided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.sub.ndarray","strided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.subBy","strided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.trunc","strided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.trunc.ndarray","strided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, 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)"],["Uint8Array.prototype.findIndex","Uint8Array.prototype.findIndex( predicate[, thisArg] )"],["Uint8Array.prototype.forEach","Uint8Array.prototype.forEach( fcn[, thisArg] )"],["Uint8Array.prototype.includes","Uint8Array.prototype.includes( searchElement[, fromIndex] )"],["Uint8Array.prototype.indexOf","Uint8Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8Array.prototype.join","Uint8Array.prototype.join( [separator] )"],["Uint8Array.prototype.keys","Uint8Array.prototype.keys()"],["Uint8Array.prototype.lastIndexOf","Uint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8Array.prototype.map","Uint8Array.prototype.map( fcn[, thisArg] )"],["Uint8Array.prototype.reduce","Uint8Array.prototype.reduce( fcn[, initialValue] )"],["Uint8Array.prototype.reduceRight","Uint8Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint8Array.prototype.reverse","Uint8Array.prototype.reverse()"],["Uint8Array.prototype.set","Uint8Array.prototype.set( arr[, offset] )"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin[, end]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate[, thisArg] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin[, end]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales[, options]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray )"],["Uint8ClampedArray","Uint8ClampedArray( obj )"],["Uint8ClampedArray","Uint8ClampedArray( buffer[, byteOffset[, length]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src[, map[, thisArg]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0[, element1[, ...elementN]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target, start[, end] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value[, start[, end]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr[, offset] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin[, end]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin[, end]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales[, options]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["Uint8ClampedVector","Uint8ClampedVector( [options] )"],["Uint8ClampedVector","Uint8ClampedVector( length[, options] )"],["Uint8ClampedVector","Uint8ClampedVector( obj[, options] )"],["Uint8ClampedVector","Uint8ClampedVector( buffer[, byteOffset[, length]][, options] )"],["Uint8Vector","Uint8Vector( [options] )"],["Uint8Vector","Uint8Vector( length[, options] )"],["Uint8Vector","Uint8Vector( obj[, options] )"],["Uint8Vector","Uint8Vector( buffer[, byteOffset[, length]][, options] )"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length )"],["Uint16Array","Uint16Array( typedarray )"],["Uint16Array","Uint16Array( obj )"],["Uint16Array","Uint16Array( buffer[, byteOffset[, length]] )"],["Uint16Array.from","Uint16Array.from( src[, map[, thisArg]] )"],["Uint16Array.of","Uint16Array.of( element0[, element1[, ...elementN]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target, start[, end] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate[, thisArg] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value[, start[, end]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate[, thisArg] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate[, thisArg] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate[, thisArg] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn[, thisArg] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement[, fromIndex] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn[, thisArg] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn[, initialValue] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr[, offset] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin[, end]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate[, thisArg] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin[, end]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales[, options]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["Uint16Vector","Uint16Vector( [options] )"],["Uint16Vector","Uint16Vector( length[, options] )"],["Uint16Vector","Uint16Vector( obj[, options] )"],["Uint16Vector","Uint16Vector( buffer[, byteOffset[, length]][, options] )"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length )"],["Uint32Array","Uint32Array( typedarray )"],["Uint32Array","Uint32Array( obj )"],["Uint32Array","Uint32Array( buffer[, byteOffset[, length]] )"],["Uint32Array.from","Uint32Array.from( src[, map[, thisArg]] )"],["Uint32Array.of","Uint32Array.of( element0[, element1[, ...elementN]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target, start[, end] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate[, thisArg] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value[, start[, end]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate[, thisArg] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate[, thisArg] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate[, thisArg] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn[, thisArg] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement[, fromIndex] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn[, thisArg] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn[, initialValue] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr[, offset] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin[, end]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate[, thisArg] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin[, end]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales[, options]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["Uint32Vector","Uint32Vector( [options] )"],["Uint32Vector","Uint32Vector( length[, options] )"],["Uint32Vector","Uint32Vector( obj[, options] )"],["Uint32Vector","Uint32Vector( buffer[, byteOffset[, length]][, options] )"],["Uint64","Uint64( value )"],["Uint64.name","Uint64.name"],["Uint64.from","Uint64.from( words )"],["Uint64.of","Uint64.of( high, low )"],["Uint64.BYTES_PER_ELEMENT","Uint64.BYTES_PER_ELEMENT"],["Uint64.prototype.BYTES_PER_ELEMENT","Uint64.prototype.BYTES_PER_ELEMENT"],["Uint64.prototype.byteLength","Uint64.prototype.byteLength"],["Uint64.prototype.hi","Uint64.prototype.hi"],["Uint64.prototype.lo","Uint64.prototype.lo"],["umask","umask( [mask,] [options] )"],["uncapitalize","uncapitalize( str )"],["uncapitalizeKeys","uncapitalizeKeys( obj )"],["uncurry","uncurry( fcn[, arity, ][thisArg] )"],["uncurryRight","uncurryRight( fcn[, arity, ][thisArg] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data,] [options] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data,] [options] )"],["UnicodeSparkline","UnicodeSparkline( [data,] [options] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data,] [options] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data,] [options] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data,] [options] )"],["unlink","unlink( path, clbk )"],["unlink.sync","unlink.sync( path )"],["unshift","unshift( collection, ...items )"],["until","until( predicate, fcn[, thisArg] )"],["untilAsync","untilAsync( predicate, fcn, done[, thisArg] )"],["untilEach","untilEach( collection, predicate, fcn[, thisArg] )"],["untilEachRight","untilEachRight( collection, predicate, fcn[, thisArg] )"],["unzip","unzip( arr[, idx] )"],["uppercase","uppercase( str )"],["uppercaseKeys","uppercaseKeys( obj )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str )"],["vartest","vartest( x, y[, options] )"],["vector","vector( [dtype][, options] )"],["vector","vector( length[, dtype][, options] )"],["vector","vector( obj[, dtype][, options] )"],["vector","vector( buffer[, byteOffset[, length]][, dtype][, options] )"],["vector.factory","vector.factory( dtype[, options] )"],["waterfall","waterfall( fcns, clbk[, thisArg] )"],["waterfall.factory","waterfall.factory( fcns, clbk[, thisArg] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta )"],["whileAsync","whileAsync( predicate, fcn, done[, thisArg] )"],["whileEach","whileEach( collection, predicate, fcn[, thisArg] )"],["whileEachRight","whileEachRight( collection, predicate, fcn[, thisArg] )"],["whilst","whilst( predicate, fcn[, thisArg] )"],["wilcoxon","wilcoxon( x[, y][, options] )"],["writableProperties","writableProperties( value )"],["writablePropertiesIn","writablePropertiesIn( value )"],["writablePropertyNames","writablePropertyNames( value )"],["writablePropertyNamesIn","writablePropertyNamesIn( value )"],["writablePropertySymbols","writablePropertySymbols( value )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value )"],["writeFile","writeFile( file, data[, options], clbk )"],["writeFile.sync","writeFile.sync( file, data[, options] )"],["zip","zip( ...arr[, options] )"],["ztest","ztest( x, sigma[, options] )"],["ztest2","ztest2( x, y, sigmax, sigmay[, options] )"]] diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv index 12943396a7b9..b330078f374f 100644 --- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv +++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv @@ -1780,8 +1780,8 @@ base.strided.dmeanvarpn,"base.strided.dmeanvarpn( N:integer, c:number, x:Float64 base.strided.dmeanvarpn.ndarray,"base.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )" base.strided.dmeanwd,"base.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )" base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" -base.strided.dmediansorted,"base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )" -base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" +base.strided.dmedianSorted,"base.strided.dmedianSorted( N:integer, x:Float64Array, strideX:integer )" +base.strided.dmedianSorted.ndarray,"base.strided.dmedianSorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmidrange,"base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )" base.strided.dmidrange.ndarray,"base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )" base.strided.dmin,"base.strided.dmin( N:integer, x:Float64Array, strideX:integer )" @@ -3590,6 +3590,15 @@ Int32Vector,"Int32Vector( [options:Object] )" Int32Vector,"Int32Vector( length:integer[, options:Object] )" Int32Vector,"Int32Vector( obj:Object[, options:Object] )" Int32Vector,"Int32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, options:Object] )" +Int64,"Int64( value:integer|bigint )" +Int64.name,"Int64.name" +Int64.from,"Int64.from( words:ArrayLikeObject )" +Int64.of,"Int64.of( high:integer, low:integer )" +Int64.BYTES_PER_ELEMENT,"Int64.BYTES_PER_ELEMENT" +Int64.prototype.BYTES_PER_ELEMENT,"Int64.prototype.BYTES_PER_ELEMENT" +Int64.prototype.byteLength,"Int64.prototype.byteLength" +Int64.prototype.hi,"Int64.prototype.hi" +Int64.prototype.lo,"Int64.prototype.lo" IS_BIG_ENDIAN,"IS_BIG_ENDIAN" IS_BROWSER,"IS_BROWSER" IS_DARWIN,"IS_DARWIN" @@ -5983,7 +5992,7 @@ Uint32Vector,"Uint32Vector( [options:Object] )" Uint32Vector,"Uint32Vector( length:integer[, options:Object] )" Uint32Vector,"Uint32Vector( obj:Object[, options:Object] )" Uint32Vector,"Uint32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, options:Object] )" -Uint64,"Uint64( value:number|bigint )" +Uint64,"Uint64( value:integer|bigint )" Uint64.name,"Uint64.name" Uint64.from,"Uint64.from( words:ArrayLikeObject )" Uint64.of,"Uint64.of( high:integer, low:integer )" diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json index ab4e0b952ddb..7476d59289e4 100644 --- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json +++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json @@ -1 +1 @@ -[["abs","abs( x:ndarray[, options:Object] )"],["abs.assign","abs.assign( x:ndarray, y:ndarray )"],["acartesianPower","acartesianPower( x:ArrayLikeObject, n:integer )"],["acartesianProduct","acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["acartesianSquare","acartesianSquare( x:ArrayLikeObject )"],["acronym","acronym( str:string[, options:Object] )"],["aempty","aempty( length:integer[, dtype:string] )"],["aemptyLike","aemptyLike( x:TypedArray|Array[, dtype:string] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length:integer, value:any[, dtype:string] )"],["afullLike","afullLike( x:TypedArray|Array[, dtype:string] )"],["alias2pkg","alias2pkg( alias:string )"],["alias2related","alias2related( alias:string )"],["alias2standalone","alias2standalone( alias:string )"],["aliases","aliases( [namespace:string] )"],["allocUnsafe","allocUnsafe( size:integer )"],["amskfilter","amskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["amskput","amskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["amskreject","amskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["anans","anans( length:integer[, dtype:string] )"],["anansLike","anansLike( x:TypedArray|Array[, dtype:string] )"],["anova1","anova1( x:Array, factor:Array[, options:Object] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection:Array|TypedArray|Object )"],["anyBy","anyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByAsync","anyByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByAsync.factory","anyByAsync.factory( [options:Object,] predicate:Function )"],["anyByRight","anyByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByRightAsync","anyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options:Object,] predicate:Function )"],["anyInBy","anyInBy( object:Object, predicate:Function[, thisArg:any ] )"],["anyOwnBy","anyOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["aones","aones( length:integer[, dtype:string] )"],["aonesLike","aonesLike( x:TypedArray|Array[, dtype:string] )"],["aoneTo","aoneTo( n:integer[, dtype:string] )"],["aoneToLike","aoneToLike( x:TypedArray|Array[, dtype:string] )"],["APERY","APERY"],["aplace","aplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["append","append( collection1:Array|TypedArray|Object, collection2:Array|TypedArray|Object )"],["aput","aput( x:ArrayLikeObject, indices:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx:integer )"],["ARGV","ARGV"],["array","array( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )"],["array2buffer","array2buffer( arr:Array )"],["array2fancy","array2fancy( x:Array|TypedArray|Object[, options:Object] )"],["array2fancy.factory","array2fancy.factory( [options:Object] )"],["array2fancy.idx","array2fancy.idx( x:Array|TypedArray|Object[, options:Object] )"],["array2iterator","array2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["array2iteratorRight","array2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["ArrayBuffer","ArrayBuffer( size:integer )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr:any )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start:integer[, end:integer]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["arrayCtors","arrayCtors( dtype:string )"],["arrayDataType","arrayDataType( array:any )"],["arrayDataTypes","arrayDataTypes( [kind:string] )"],["ArrayIndex","ArrayIndex( x:Array|TypedArray|Object[, options:Object] )"],["ArrayIndex.free","ArrayIndex.free( id:string )"],["ArrayIndex.get","ArrayIndex.get( id:string )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value:any )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype:any] )"],["arrayNextDataType","arrayNextDataType( [dtype:string] 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)"],["base.strided.dmeanstdevpn.ndarray","base.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvar","base.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvar.ndarray","base.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanvarpn","base.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, out:Float64Array, strideOut:integer )"],["base.strided.dmeanvarpn.ndarray","base.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"],["base.strided.dmeanwd","base.strided.dmeanwd( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmeanwd.ndarray","base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmediansorted","base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmediansorted.ndarray","base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmidrange","base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmidrange.ndarray","base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmin","base.strided.dmin( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmin.ndarray","base.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dminabs","base.strided.dminabs( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dminabs.ndarray","base.strided.dminabs.ndarray( N:integer, x:Float64Array, 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)"],["base.strided.smeanpw.ndarray","base.strided.smeanpw.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smeanwd","base.strided.smeanwd( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smeanwd.ndarray","base.strided.smeanwd.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smediansorted","base.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smediansorted.ndarray","base.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smidrange","base.strided.smidrange( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smidrange.ndarray","base.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smin","base.strided.smin( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smin.ndarray","base.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminabs","base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminabs.ndarray","base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminsorted","base.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminsorted.ndarray","base.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskrsqrt","base.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskrsqrt.ndarray","base.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsksqrt","base.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsksqrt.ndarray","base.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsktrunc","base.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsktrunc.ndarray","base.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.snanmax","base.strided.snanmax( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmax.ndarray","base.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmaxabs","base.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmaxabs.ndarray","base.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmean","base.strided.snanmean( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmean.ndarray","base.strided.snanmean.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmeanors","base.strided.snanmeanors( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmeanors.ndarray","base.strided.snanmeanors.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer 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x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmax.ndarray","base.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskmin","base.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmin.ndarray","base.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskrange","base.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskrange.ndarray","base.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanrange","base.strided.snanrange( N:integer, 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iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object )"],["iterTrunc10","iterTrunc10( iterator:Object )"],["iterUnion","iterUnion( iter0:Object, ...iterator:Object )"],["iterUnique","iterUnique( iterator:Object )"],["iterUniqueBy","iterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )"],["iterUniqueByHash","iterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterUnitspace","iterUnitspace( start:number[, stop:number] )"],["iterUnshift","iterUnshift( iterator:Object, ...items:any )"],["iterUntilEach","iterUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["itervariance","itervariance( iterator:Object[, mean:number] )"],["iterVercos","iterVercos( iterator:Object )"],["iterVersin","iterVersin( iterator:Object )"],["iterWhileEach","iterWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterZeta","iterZeta( iterator:Object )"],["joinStream","joinStream( [options:Object] )"],["joinStream.factory","joinStream.factory( [options:Object] )"],["joinStream.objectMode","joinStream.objectMode( [options:Object] )"],["kde2d","kde2d( x:Array, y:Array[, options:Object] )"],["kebabcase","kebabcase( str:string )"],["keyBy","keyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keyByRight","keyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keysIn","keysIn( obj:any )"],["kruskalTest","kruskalTest( ...x:Array[, options:Object] )"],["kstest","kstest( x:Array, y:Function|string[, ...params:number][, options:Object] )"],["last","last( str:string[, n:integer][, options:Object] )"],["leveneTest","leveneTest( x:Array[, ...y:Array[, options:Object]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, options:Object] )"],["linspace.assign","linspace.assign( start:number|ComplexLike, stop:number|ComplexLike, out:ArrayLikeObject[, options:Object] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a:number, b:number[, length:integer] )"],["lowercase","lowercase( str:string )"],["lowercaseKeys","lowercaseKeys( obj:Object )"],["lowess","lowess( x:Array, y:Array[, options:Object] )"],["lpad","lpad( str:string, len:integer[, pad:string] )"],["ltrim","ltrim( str:string )"],["ltrimN","ltrimN( str:string, n:integer[, chars:Array|string] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map.assign","map.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2","map2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2.assign","map2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2d","map2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )"],["map2Right","map2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2Right.assign","map2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map3d","map3d( arr:ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map4d","map4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )"],["map5d","map5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )"],["mapArguments","mapArguments( fcn:Function, clbk:Function[, thisArg:any] )"],["mapFun","mapFun( fcn:Function, n:integer[, thisArg:any] )"],["mapFunAsync","mapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )"],["mapFunAsync.factory","mapFunAsync.factory( [options:Object,] fcn:Function )"],["mapKeys","mapKeys( obj:Object, transform:Function )"],["mapKeysAsync","mapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options:Object,] transform:Function )"],["mapReduce","mapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapReduceRight","mapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapRight","mapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapRight.assign","mapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapValues","mapValues( obj:Object, transform:Function )"],["mapValuesAsync","mapValuesAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options:Object,] transform:Function 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...arrays:ndarray|ArrayLikeObject )"],["memoize","memoize( fcn:Function[, hashFunction:Function] )"],["merge","merge( target:Object, ...source:Object )"],["merge.factory","merge.factory( options:Object )"],["MILLISECONDS_IN_DAY","MILLISECONDS_IN_DAY"],["MILLISECONDS_IN_HOUR","MILLISECONDS_IN_HOUR"],["MILLISECONDS_IN_MINUTE","MILLISECONDS_IN_MINUTE"],["MILLISECONDS_IN_SECOND","MILLISECONDS_IN_SECOND"],["MILLISECONDS_IN_WEEK","MILLISECONDS_IN_WEEK"],["MINARD_NAPOLEONS_MARCH","MINARD_NAPOLEONS_MARCH( [options:Object] )"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month:string|Date|integer[, year:integer]] )"],["minutesInYear","minutesInYear( [value:integer|Date] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source:Object, prop:string, target:Object )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields:Array[, options:Object] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn:Function, arity:integer[, thisArg:any] )"],["nativeClass","nativeClass( value:any )"],["ndarray","ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, shape:ArrayLikeObject, strides:ArrayLikeObject, offset:integer, order:string[, options:Object] )"],["ndarray.prototype.byteLength","ndarray.prototype.byteLength"],["ndarray.prototype.BYTES_PER_ELEMENT","ndarray.prototype.BYTES_PER_ELEMENT"],["ndarray.prototype.data","ndarray.prototype.data"],["ndarray.prototype.dtype","ndarray.prototype.dtype"],["ndarray.prototype.flags","ndarray.prototype.flags"],["ndarray.prototype.length","ndarray.prototype.length"],["ndarray.prototype.ndims","ndarray.prototype.ndims"],["ndarray.prototype.offset","ndarray.prototype.offset"],["ndarray.prototype.order","ndarray.prototype.order"],["ndarray.prototype.shape","ndarray.prototype.shape"],["ndarray.prototype.strides","ndarray.prototype.strides"],["ndarray.prototype.get","ndarray.prototype.get( ...idx:integer )"],["ndarray.prototype.iget","ndarray.prototype.iget( idx:integer )"],["ndarray.prototype.set","ndarray.prototype.set( ...idx:integer, v:any )"],["ndarray.prototype.iset","ndarray.prototype.iset( idx:integer, v:any 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)"],["ndarrayDataTypes.binary","ndarrayDataTypes.binary"],["ndarrayDataTypes.boolean","ndarrayDataTypes.boolean"],["ndarrayDataTypes.complex32","ndarrayDataTypes.complex32"],["ndarrayDataTypes.complex64","ndarrayDataTypes.complex64"],["ndarrayDataTypes.complex128","ndarrayDataTypes.complex128"],["ndarrayDataTypes.float16","ndarrayDataTypes.float16"],["ndarrayDataTypes.float32","ndarrayDataTypes.float32"],["ndarrayDataTypes.float64","ndarrayDataTypes.float64"],["ndarrayDataTypes.generic","ndarrayDataTypes.generic"],["ndarrayDataTypes.int8","ndarrayDataTypes.int8"],["ndarrayDataTypes.int16","ndarrayDataTypes.int16"],["ndarrayDataTypes.int32","ndarrayDataTypes.int32"],["ndarrayDataTypes.uint8","ndarrayDataTypes.uint8"],["ndarrayDataTypes.uint8c","ndarrayDataTypes.uint8c"],["ndarrayDataTypes.uint16","ndarrayDataTypes.uint16"],["ndarrayDataTypes.uint32","ndarrayDataTypes.uint32"],["ndarrayDispatch","ndarrayDispatch( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["ndarrayFlag","ndarrayFlag( x:ndarray, name:string|symbol )"],["ndarrayFlags","ndarrayFlags( x:ndarray )"],["ndarrayIndexModes","ndarrayIndexModes()"],["ndarraylike2ndarray","ndarraylike2ndarray( x:ndarrayLike[, options:Object] )"],["ndarrayMinDataType","ndarrayMinDataType( value:any )"],["ndarrayMostlySafeCasts","ndarrayMostlySafeCasts( [dtype:any] )"],["ndarrayNextDataType","ndarrayNextDataType( [dtype:any] )"],["ndarrayOffset","ndarrayOffset( x:ndarray )"],["ndarrayOrder","ndarrayOrder( x:ndarray )"],["ndarrayOrders","ndarrayOrders()"],["ndarrayPromotionRules","ndarrayPromotionRules( [dtype1:any, dtype2:any] )"],["ndarraySafeCasts","ndarraySafeCasts( [dtype:any] )"],["ndarraySameKindCasts","ndarraySameKindCasts( [dtype:any] )"],["ndarrayShape","ndarrayShape( x:ndarray )"],["ndarrayStride","ndarrayStride( x:ndarray, dim:integer )"],["ndarrayStrides","ndarrayStrides( x:ndarray )"],["ndat","ndat( x:ndarray[, ...indices:integer] )"],["ndempty","ndempty( shape:ArrayLikeObject|integer[, options:Object] )"],["ndemptyLike","ndemptyLike( x:ndarray[, options:Object] )"],["ndfill","ndfill( x:ndarrayLike, value:any )"],["ndfillBy","ndfillBy( x:ndarrayLike, fcn:Function[, thisArg:any] )"],["ndfilter","ndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndfilterMap","ndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndforEach","ndforEach( x:ndarray, fcn:Function[, thisArg:any] )"],["ndims","ndims( x:ndarray )"],["ndindex","ndindex( x:ndarray[, options:Object] )"],["ndindex.free","ndindex.free( id:string )"],["ndindex.get","ndindex.get( id:string )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x:ndarray[, options:Object] )"],["ndindex.linearIndex","ndindex.linearIndex( x:ndarray[, options:Object] 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[options:Object] )"],["splitStream.factory","splitStream.factory( [options:Object] )"],["splitStream.objectMode","splitStream.objectMode( [options:Object] )"],["SQRT_EPS","SQRT_EPS"],["SQRT_HALF","SQRT_HALF"],["SQRT_HALF_PI","SQRT_HALF_PI"],["SQRT_PHI","SQRT_PHI"],["SQRT_PI","SQRT_PI"],["SQRT_THREE","SQRT_THREE"],["SQRT_TWO","SQRT_TWO"],["SQRT_TWO_PI","SQRT_TWO_PI"],["SSA_US_BIRTHS_2000_2014","SSA_US_BIRTHS_2000_2014()"],["sswap","sswap( x:ndarray, y:ndarray[, dim:integer] )"],["Stack","Stack()"],["standalone2pkg","standalone2pkg( pkg:string )"],["STANDARD_CARD_DECK","STANDARD_CARD_DECK()"],["startcase","startcase( str:string )"],["startsWith","startsWith( str:string, search:string[, position:integer] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.abs.ndarray","strided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, 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)"],["strided.acotBy.ndarray","strided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy","strided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy.ndarray","strided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy","strided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy.ndarray","strided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy","strided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy.ndarray","strided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.add","strided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.add.ndarray","strided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.addBy","strided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.addBy.ndarray","strided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By.ndarray","strided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By","strided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By.ndarray","strided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By","strided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cbrtBy","strided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrtBy.ndarray","strided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ceil","strided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ceil.ndarray","strided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cosBy","strided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.dispatchBy","strided.dispatchBy( fcns:Function|ArrayLikeObject, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.floor","strided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.floor.ndarray","strided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.inv","strided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.inv.ndarray","strided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.mul","strided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.mul.ndarray","strided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.mulBy","strided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ramp","strided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer 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y:ArrayLikeObject, strideY:integer )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sqrtBy","strided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sub","strided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.sub.ndarray","strided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.subBy","strided.subBy( N:integer, 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x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smaxsorted","base.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smaxsorted.ndarray","base.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smean","base.strided.smean( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smean.ndarray","base.strided.smean.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smeankbn","base.strided.smeankbn( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smeankbn.ndarray","base.strided.smeankbn.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smeankbn2","base.strided.smeankbn2( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smeankbn2.ndarray","base.strided.smeankbn2.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smeanli","base.strided.smeanli( 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strideX:integer, offsetX:integer )"],["base.strided.sminabs","base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminabs.ndarray","base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminsorted","base.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminsorted.ndarray","base.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, 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)"],["iterAbs","iterAbs( iterator:Object )"],["iterAbs2","iterAbs2( iterator:Object )"],["iterAcos","iterAcos( iterator:Object )"],["iterAcosh","iterAcosh( iterator:Object )"],["iterAcot","iterAcot( iterator:Object )"],["iterAcoth","iterAcoth( iterator:Object )"],["iterAcovercos","iterAcovercos( iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object )"],["iterBessely1","iterBessely1( iterator:Object )"],["iterBeta","iterBeta( x:Object|number, y:Object|number )"],["iterBetaln","iterBetaln( x:Object|number, y:Object|number )"],["iterBinet","iterBinet( iterator:Object )"],["iterCbrt","iterCbrt( iterator:Object )"],["iterCeil","iterCeil( iterator:Object )"],["iterCeil2","iterCeil2( iterator:Object )"],["iterCeil10","iterCeil10( iterator:Object )"],["iterCompositesSeq","iterCompositesSeq( [options:Object] )"],["iterConcat","iterConcat( iter0:Object, ...iterator:Object )"],["iterConstant","iterConstant( value:any[, options:Object] )"],["iterContinuedFraction","iterContinuedFraction( iterator:Object[, options:Object] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x:number[, options:Object] )"],["iterCos","iterCos( iterator:Object )"],["iterCosh","iterCosh( iterator:Object )"],["iterCosineWave","iterCosineWave( [options:Object] )"],["iterCosm1","iterCosm1( iterator:Object )"],["iterCospi","iterCospi( iterator:Object )"],["iterCounter","iterCounter( iterator:Object )"],["iterCovercos","iterCovercos( iterator:Object )"],["iterCoversin","iterCoversin( iterator:Object )"],["iterCubesSeq","iterCubesSeq( [options:Object] )"],["itercugmean","itercugmean( iterator:Object )"],["itercuhmean","itercuhmean( iterator:Object )"],["itercumax","itercumax( iterator:Object )"],["itercumaxabs","itercumaxabs( iterator:Object )"],["itercumean","itercumean( iterator:Object )"],["itercumeanabs","itercumeanabs( iterator:Object )"],["itercumeanabs2","itercumeanabs2( iterator:Object )"],["itercumidrange","itercumidrange( iterator:Object )"],["itercumin","itercumin( iterator:Object )"],["itercuminabs","itercuminabs( iterator:Object )"],["itercuprod","itercuprod( iterator:Object )"],["itercurange","itercurange( iterator:Object )"],["itercusum","itercusum( iterator:Object )"],["itercusumabs","itercusumabs( iterator:Object )"],["itercusumabs2","itercusumabs2( iterator:Object )"],["iterDatespace","iterDatespace( start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoUntilEach","iterDoUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object )"],["iterTrunc10","iterTrunc10( iterator:Object )"],["iterUnion","iterUnion( iter0:Object, ...iterator:Object )"],["iterUnique","iterUnique( iterator:Object )"],["iterUniqueBy","iterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )"],["iterUniqueByHash","iterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterUnitspace","iterUnitspace( start:number[, stop:number] )"],["iterUnshift","iterUnshift( iterator:Object, ...items:any )"],["iterUntilEach","iterUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["itervariance","itervariance( iterator:Object[, mean:number] )"],["iterVercos","iterVercos( iterator:Object )"],["iterVersin","iterVersin( iterator:Object )"],["iterWhileEach","iterWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterZeta","iterZeta( iterator:Object )"],["joinStream","joinStream( [options:Object] )"],["joinStream.factory","joinStream.factory( [options:Object] )"],["joinStream.objectMode","joinStream.objectMode( [options:Object] )"],["kde2d","kde2d( x:Array, y:Array[, options:Object] )"],["kebabcase","kebabcase( str:string )"],["keyBy","keyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keyByRight","keyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keysIn","keysIn( obj:any )"],["kruskalTest","kruskalTest( ...x:Array[, options:Object] )"],["kstest","kstest( x:Array, y:Function|string[, ...params:number][, options:Object] )"],["last","last( str:string[, n:integer][, options:Object] )"],["leveneTest","leveneTest( x:Array[, ...y:Array[, options:Object]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, options:Object] )"],["linspace.assign","linspace.assign( start:number|ComplexLike, stop:number|ComplexLike, out:ArrayLikeObject[, options:Object] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a:number, b:number[, length:integer] )"],["lowercase","lowercase( str:string )"],["lowercaseKeys","lowercaseKeys( obj:Object )"],["lowess","lowess( x:Array, y:Array[, options:Object] )"],["lpad","lpad( str:string, len:integer[, pad:string] )"],["ltrim","ltrim( str:string )"],["ltrimN","ltrimN( str:string, n:integer[, chars:Array|string] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map.assign","map.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2","map2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2.assign","map2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2d","map2d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )"],["map2Right","map2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2Right.assign","map2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map3d","map3d( arr:ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map4d","map4d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )"],["map5d","map5d( arr:ArrayLikeObject, fcn:Function[, thisArg:any] )"],["mapArguments","mapArguments( fcn:Function, clbk:Function[, thisArg:any] )"],["mapFun","mapFun( fcn:Function, n:integer[, thisArg:any] )"],["mapFunAsync","mapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )"],["mapFunAsync.factory","mapFunAsync.factory( [options:Object,] fcn:Function )"],["mapKeys","mapKeys( obj:Object, transform:Function )"],["mapKeysAsync","mapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options:Object,] transform:Function )"],["mapReduce","mapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapReduceRight","mapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapRight","mapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapRight.assign","mapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapValues","mapValues( obj:Object, transform:Function )"],["mapValuesAsync","mapValuesAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options:Object,] transform:Function )"],["maskArguments","maskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )"],["matrix","matrix( [dtype:string|DataType][, options:Object] )"],["matrix","matrix( shape:ArrayLikeObject[, dtype:string|DataType][, options:Object] )"],["matrix","matrix( M:integer, N:integer[, dtype:string|DataType][, options:Object] )"],["matrix","matrix( obj:Object[, dtype:string|DataType][, options:Object] )"],["matrix","matrix( buffer:ArrayBuffer[, byteOffset:integer[, shape:ArrayLikeObject]][, dtype:string|DataType][, options:Object] )"],["matrix","matrix( buffer:ArrayBuffer[, byteOffset:integer[, M:integer, N:integer]][, dtype:string|DataType][, options:Object] )"],["matrix.factory","matrix.factory( dtype:string|DataType[, options:Object] )"],["MAX_ARRAY_LENGTH","MAX_ARRAY_LENGTH"],["MAX_TYPED_ARRAY_LENGTH","MAX_TYPED_ARRAY_LENGTH"],["maybeBroadcastArray","maybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )"],["maybeBroadcastArrays","maybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject )"],["memoize","memoize( fcn:Function[, hashFunction:Function] )"],["merge","merge( target:Object, ...source:Object )"],["merge.factory","merge.factory( options:Object )"],["MILLISECONDS_IN_DAY","MILLISECONDS_IN_DAY"],["MILLISECONDS_IN_HOUR","MILLISECONDS_IN_HOUR"],["MILLISECONDS_IN_MINUTE","MILLISECONDS_IN_MINUTE"],["MILLISECONDS_IN_SECOND","MILLISECONDS_IN_SECOND"],["MILLISECONDS_IN_WEEK","MILLISECONDS_IN_WEEK"],["MINARD_NAPOLEONS_MARCH","MINARD_NAPOLEONS_MARCH( [options:Object] )"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month:string|Date|integer[, year:integer]] )"],["minutesInYear","minutesInYear( [value:integer|Date] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source:Object, prop:string, target:Object )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields:Array[, options:Object] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn:Function, arity:integer[, thisArg:any] )"],["nativeClass","nativeClass( value:any )"],["ndarray","ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, shape:ArrayLikeObject, strides:ArrayLikeObject, offset:integer, order:string[, options:Object] 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][options:Object] )"],["random.streams.t.objectMode","random.streams.t.objectMode( v:number[, options:Object] )"],["random.streams.triangular","random.streams.triangular( a:number, b:number, c:number[, options:Object] )"],["random.streams.triangular.factory","random.streams.triangular.factory( [a:number, b:number, c:number, ][options:Object] )"],["random.streams.triangular.objectMode","random.streams.triangular.objectMode( a:number, b:number, c:number[, options:Object] )"],["random.streams.uniform","random.streams.uniform( a:number, b:number[, options:Object] )"],["random.streams.uniform.factory","random.streams.uniform.factory( [a:number, b:number, ][options:Object] )"],["random.streams.uniform.objectMode","random.streams.uniform.objectMode( a:number, b:number[, options:Object] )"],["random.streams.weibull","random.streams.weibull( k:number, λ:number[, options:Object] )"],["random.streams.weibull.factory","random.streams.weibull.factory( [k:number, λ:number, ][options:Object] 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out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.betaprime.ndarray","random.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.chi","random.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chi.ndarray","random.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chi.factory","random.strided.chi.factory( [options:Object] 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out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.discreteUniform.ndarray","random.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.exponential","random.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.exponential.ndarray","random.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.exponential.factory","random.strided.exponential.factory( [options:Object] 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so:integer )"],["random.strided.geometric.ndarray","random.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, op:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.geometric.factory","random.strided.geometric.factory( [options:Object] )"],["random.strided.geometric.PRNG","random.strided.geometric.PRNG"],["random.strided.geometric.seed","random.strided.geometric.seed"],["random.strided.geometric.seedLength","random.strided.geometric.seedLength"],["random.strided.geometric.state","random.strided.geometric.state"],["random.strided.geometric.stateLength","random.strided.geometric.stateLength"],["random.strided.geometric.byteLength","random.strided.geometric.byteLength"],["random.strided.invgamma","random.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.invgamma.ndarray","random.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.lognormal","random.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.lognormal.ndarray","random.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd","random.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstd.ndarray","random.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd.normalized","random.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] 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so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.poisson.factory","random.strided.poisson.factory( [options:Object] )"],["random.strided.poisson.PRNG","random.strided.poisson.PRNG"],["random.strided.poisson.seed","random.strided.poisson.seed"],["random.strided.poisson.seedLength","random.strided.poisson.seedLength"],["random.strided.poisson.state","random.strided.poisson.state"],["random.strided.poisson.stateLength","random.strided.poisson.stateLength"],["random.strided.poisson.byteLength","random.strided.poisson.byteLength"],["random.strided.randu","random.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.randu.ndarray","random.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.rayleigh","random.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer 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prop:string|symbol, value:any )"],["setConfigurableReadOnlyAccessor","setConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setConfigurableReadWriteAccessor","setConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setConfigurableWriteOnlyAccessor","setConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setMemoizedConfigurableReadOnly","setMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setMemoizedReadOnly","setMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setNonEnumerableProperty","setNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function 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[options:Object] )"],["splitStream.factory","splitStream.factory( [options:Object] )"],["splitStream.objectMode","splitStream.objectMode( [options:Object] )"],["SQRT_EPS","SQRT_EPS"],["SQRT_HALF","SQRT_HALF"],["SQRT_HALF_PI","SQRT_HALF_PI"],["SQRT_PHI","SQRT_PHI"],["SQRT_PI","SQRT_PI"],["SQRT_THREE","SQRT_THREE"],["SQRT_TWO","SQRT_TWO"],["SQRT_TWO_PI","SQRT_TWO_PI"],["SSA_US_BIRTHS_2000_2014","SSA_US_BIRTHS_2000_2014()"],["sswap","sswap( x:ndarray, y:ndarray[, dim:integer] )"],["Stack","Stack()"],["standalone2pkg","standalone2pkg( pkg:string )"],["STANDARD_CARD_DECK","STANDARD_CARD_DECK()"],["startcase","startcase( str:string )"],["startsWith","startsWith( str:string, search:string[, position:integer] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.abs.ndarray","strided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, 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y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( 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)"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, 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)"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction:Function] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["Uint32Vector","Uint32Vector( [options:Object] )"],["Uint32Vector","Uint32Vector( length:integer[, options:Object] )"],["Uint32Vector","Uint32Vector( obj:Object[, options:Object] )"],["Uint32Vector","Uint32Vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, options:Object] )"],["Uint64","Uint64( value:integer|bigint )"],["Uint64.name","Uint64.name"],["Uint64.from","Uint64.from( words:ArrayLikeObject )"],["Uint64.of","Uint64.of( high:integer, low:integer )"],["Uint64.BYTES_PER_ELEMENT","Uint64.BYTES_PER_ELEMENT"],["Uint64.prototype.BYTES_PER_ELEMENT","Uint64.prototype.BYTES_PER_ELEMENT"],["Uint64.prototype.byteLength","Uint64.prototype.byteLength"],["Uint64.prototype.hi","Uint64.prototype.hi"],["Uint64.prototype.lo","Uint64.prototype.lo"],["umask","umask( [mask:integer|string,] [options:Object] )"],["uncapitalize","uncapitalize( str:string )"],["uncapitalizeKeys","uncapitalizeKeys( obj:Object )"],["uncurry","uncurry( fcn:Function[, arity:integer, ][thisArg:any] )"],["uncurryRight","uncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeSparkline","UnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["unlink","unlink( path:string|Buffer|integer, clbk:Function )"],["unlink.sync","unlink.sync( path:string|Buffer|integer )"],["unshift","unshift( collection:Array|TypedArray|Object, ...items:any )"],["until","until( predicate:Function, fcn:Function[, thisArg:any] )"],["untilAsync","untilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["untilEach","untilEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["untilEachRight","untilEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["unzip","unzip( arr:Array[, idx:Array] )"],["uppercase","uppercase( str:string )"],["uppercaseKeys","uppercaseKeys( obj:Object )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str:string )"],["vartest","vartest( x:Array, y:Array[, options:Object] )"],["vector","vector( [dtype:string][, options:Object] )"],["vector","vector( length:integer[, dtype:string][, options:Object] )"],["vector","vector( obj:Object[, dtype:string][, options:Object] )"],["vector","vector( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, dtype:string][, options:Object] )"],["vector.factory","vector.factory( dtype:string[, options:Object] )"],["waterfall","waterfall( fcns:Array, clbk:Function[, thisArg:any] )"],["waterfall.factory","waterfall.factory( fcns:Array, clbk:Function[, thisArg:any] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor:Object )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta:integer )"],["whileAsync","whileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["whileEach","whileEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whileEachRight","whileEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whilst","whilst( predicate:Function, fcn:Function[, thisArg:any] )"],["wilcoxon","wilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )"],["writableProperties","writableProperties( value:any )"],["writablePropertiesIn","writablePropertiesIn( value:any )"],["writablePropertyNames","writablePropertyNames( value:any )"],["writablePropertyNamesIn","writablePropertyNamesIn( value:any )"],["writablePropertySymbols","writablePropertySymbols( value:any )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value:any )"],["writeFile","writeFile( file:string|Buffer|integer, data:string|Buffer[, options:Object|string], clbk:Function )"],["writeFile.sync","writeFile.sync( file:string|Buffer|integer, data:string|Buffer[, options:Object|string] )"],["zip","zip( ...arr:Array[, options:Object] )"],["ztest","ztest( x:Array, sigma:number[, options:Object] )"],["ztest2","ztest2( x:Array, y:Array, sigmax:number, sigmay:number[, options:Object] )"]] diff --git a/lib/node_modules/@stdlib/stats/array/nanstdev/package.json b/lib/node_modules/@stdlib/stats/array/nanstdev/package.json index 55e36c12fa1f..63fc6b8eb699 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdev/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanstdev/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanstdev", "version": "0.0.0", - "description": "Calculate the standard deviation of an array ignoring `NaN` values.", + "description": "Calculate the standard deviation of an array ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevch/package.json b/lib/node_modules/@stdlib/stats/array/nanstdevch/package.json index 5d214e285d60..564cdeb5f2d6 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevch/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanstdevch/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanstdevch", "version": "0.0.0", - "description": "Calculate the standard deviation of an array ignoring `NaN` values and using a one-pass trial mean algorithm.", + "description": "Calculate the standard deviation of an array ignoring NaN values and using a one-pass trial mean algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevpn/package.json b/lib/node_modules/@stdlib/stats/array/nanstdevpn/package.json index 54de7b842caa..bbb082b8763d 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevpn/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanstdevpn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanstdevpn", "version": "0.0.0", - "description": "Calculate the standard deviation of an array ignoring `NaN` values and using a two-pass algorithm.", + "description": "Calculate the standard deviation of an array ignoring NaN values and using a two-pass algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevtk/package.json b/lib/node_modules/@stdlib/stats/array/nanstdevtk/package.json index 51f790845cb9..a99bb5232747 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevtk/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanstdevtk/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanstdevtk", "version": "0.0.0", - "description": "Calculate the standard deviation of an array ignoring `NaN` values and using a one-pass textbook algorithm.", + "description": "Calculate the standard deviation of an array ignoring NaN values and using a one-pass textbook algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevwd/package.json b/lib/node_modules/@stdlib/stats/array/nanstdevwd/package.json index 236e2d1645e7..02813e538f24 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevwd/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanstdevwd/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanstdevwd", "version": "0.0.0", - "description": "Calculate the standard deviation of an array ignoring `NaN` values and using Welford's algorithm.", + "description": "Calculate the standard deviation of an array ignoring NaN values and using Welford's algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanstdevyc/package.json b/lib/node_modules/@stdlib/stats/array/nanstdevyc/package.json index 09b8dd292868..6626da9177a7 100644 --- a/lib/node_modules/@stdlib/stats/array/nanstdevyc/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanstdevyc/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanstdevyc", "version": "0.0.0", - "description": "Calculate the standard deviation of an array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer.", + "description": "Calculate the standard deviation of an array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanvariance/package.json b/lib/node_modules/@stdlib/stats/array/nanvariance/package.json index f0adecf688c8..258d723284c1 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariance/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanvariance/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanvariance", "version": "0.0.0", - "description": "Calculate the variance of an array ignoring `NaN` values.", + "description": "Calculate the variance of an array ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancech/package.json b/lib/node_modules/@stdlib/stats/array/nanvariancech/package.json index aa21b0b586ef..26b0fd1f4e03 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancech/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanvariancech/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanvariancech", "version": "0.0.0", - "description": "Calculate the variance of an array ignoring `NaN` values and using a one-pass trial mean algorithm.", + "description": "Calculate the variance of an array ignoring NaN values and using a one-pass trial mean algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancepn/package.json b/lib/node_modules/@stdlib/stats/array/nanvariancepn/package.json index e7f966047ed9..0afd3982ef1c 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancepn/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanvariancepn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanvariancepn", "version": "0.0.0", - "description": "Calculate the variance of an array ignoring `NaN` values and using a two-pass algorithm.", + "description": "Calculate the variance of an array ignoring NaN values and using a two-pass algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancetk/package.json b/lib/node_modules/@stdlib/stats/array/nanvariancetk/package.json index cf40c105c376..c234660833e0 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancetk/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanvariancetk/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanvariancetk", "version": "0.0.0", - "description": "Calculate the variance of an array ignoring `NaN` values and using a one-pass textbook algorithm.", + "description": "Calculate the variance of an array ignoring NaN values and using a one-pass textbook algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanvariancewd/package.json b/lib/node_modules/@stdlib/stats/array/nanvariancewd/package.json index fd909d3d9b97..a1a121bf07d4 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvariancewd/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanvariancewd/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanvariancewd", "version": "0.0.0", - "description": "Calculate the variance of an array ignoring `NaN` values and using Welford's algorithm.", + "description": "Calculate the variance of an array ignoring NaN values and using Welford's algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/array/nanvarianceyc/package.json b/lib/node_modules/@stdlib/stats/array/nanvarianceyc/package.json index fff8cbe630f7..7297bc310164 100644 --- a/lib/node_modules/@stdlib/stats/array/nanvarianceyc/package.json +++ b/lib/node_modules/@stdlib/stats/array/nanvarianceyc/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/array/nanvarianceyc", "version": "0.0.0", - "description": "Calculate the variance of an array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer.", + "description": "Calculate the variance of an array ignoring NaN values and using a one-pass algorithm proposed by Youngs and Cramer.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/README.md new file mode 100644 index 000000000000..fbd07190df1d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/README.md @@ -0,0 +1,252 @@ + + +# Cumulative Distribution Function + +> [Anglit][anglit-distribution] distribution [cumulative distribution function][cdf]. + +
+ +The [cumulative distribution function][cdf] for an [anglit][anglit-distribution] random variable is + + + +```math +F(x) = \sin^2\left( \frac{x-\mu}{\sigma} + \frac{\pi}{4} \right) +``` + + + +where `μ` is the location parameter and `σ > 0` is the scale parameter. + +
+ + + +
+ +## Usage + +```javascript +var cdf = require( '@stdlib/stats/base/dists/anglit/cdf' ); +``` + +#### cdf( x, mu, sigma ) + +Evaluates the [cumulative distribution function][cdf] for an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma`. + +```javascript +var y = cdf( 0.0, 0.0, 1.0 ); +// returns 0.5 + +y = cdf( 0.5, 0.0, 1.0 ); +// returns ~0.921 + +y = cdf( 2.0, 0.0, 1.0 ); +// returns 1.0 + +y = cdf( -2.0, 0.0, 1.0 ); +// returns 0.0 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = cdf( NaN, 0.0, 1.0 ); +// returns NaN + +y = cdf( 0.0, NaN, 1.0 ); +// returns NaN + +y = cdf( 0.0, 0.0, NaN ); +// returns NaN +``` + +If provided `σ <= 0`, the function returns `NaN`. + +```javascript +var y = cdf( 0.0, 0.0, -1.0 ); +// returns NaN + +y = cdf( 0.0, 0.0, 0.0 ); +// returns NaN +``` + +#### cdf.factory( mu, sigma ) + +Returns a `function` for evaluating the [CDF][cdf] of an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma`. + +```javascript +var myCDF = cdf.factory( 0.0, 1.0 ); + +var y = myCDF( 0.0 ); +// returns 0.5 + +y = myCDF( 2.0 ); +// returns 1.0 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var cdf = require( '@stdlib/stats/base/dists/anglit/cdf' ); + +var opts = { + 'dtype': 'float64' +}; + +var x = uniform( 10, -5.0, 5.0, opts ); +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.5, 5.0, opts ); + +logEachMap( 'x: %lf, μ: %lf, σ: %lf, F(x;μ,σ): %lf', x, mu, sigma, cdf ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/anglit/cdf.h" +``` + +#### stdlib_base_dists_anglit_cdf( x, mu, sigma ) + +Evaluates the [cumulative distribution function][cdf] for an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma` at a value `x`. + +```c +double out = stdlib_base_dists_anglit_cdf( 0.0, 0.0, 1.0 ); +// returns 0.5 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` location parameter. +- **sigma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_anglit_cdf( const double x, const double mu, const double sigma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/anglit/cdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( -10.0, 10.0 ); + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.1, 5.0 ); + y = stdlib_base_dists_anglit_cdf( x, mu, sigma ); + printf( "x: %lf, μ: %lf, σ: %lf, F(x;μ,σ): %lf\n", x, mu, sigma, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function + +[anglit-distribution]: https://en.wikipedia.org/wiki/Anglit_distribution + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/benchmark.js new file mode 100644 index 000000000000..adec7e1c9f29 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/benchmark.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cdf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, -10.0, 10.0, arrayOpts ); + mu = uniform( 100, -5.0, 5.0, arrayOpts ); + sigma = uniform( 100, 0.1, 10.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::factory', pkg ), function benchmark( b ) { + var arrayOpts; + var mycdf; + var sigma; + var mu; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + mu = 0.0; + sigma = 2.0; + mycdf = cdf.factory( mu, sigma ); + x = uniform( 100, -5.0, 5.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mycdf( x[ i % x.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..20d3843c54f1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/benchmark.native.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + + x = uniform( 100, -10.0, 10.0, arrayOpts ); + mu = uniform( 100, -5.0, 5.0, arrayOpts ); + sigma = uniform( 100, 0.1, 10.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..bec82a0cfae9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/cdf.h" +#include +#include +#include +#include +#include + +#define NAME "anglit-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double sigma[ 100 ]; + double mu[ 100 ]; + double x[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( -10.0, 10.0 ); + mu[ i ] = random_uniform( -5.0, 5.0 ); + sigma[ i ] = random_uniform( 0.1, 10.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_anglit_cdf( x[ i%100 ], mu[ i%100 ], sigma[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/repl.txt new file mode 100644 index 000000000000..2c9ef3420a8e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/repl.txt @@ -0,0 +1,75 @@ + +{{alias}}( x, μ, σ ) + Evaluates the cumulative distribution function (CDF) for an anglit + distribution with location parameter `μ` and scale parameter + `σ` at a value `x`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If provided `σ <= 0`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + μ: number + Location parameter. + + σ: number + Scale parameter. + + Returns + ------- + out: number + Evaluated CDF. + + Examples + -------- + > var y = {{alias}}( -10.0, 0.0, 1.0 ) + 0.0 + > y = {{alias}}( 0.0, 0.0, 1.0 ) + 0.5 + > y = {{alias}}( 10.0, 0.0, 1.0 ) + 1.0 + > y = {{alias}}( NaN, 0.0, 1.0 ) + NaN + > y = {{alias}}( 0.0, NaN, 1.0 ) + NaN + > y = {{alias}}( 0.0, 0.0, NaN ) + NaN + > y = {{alias}}( 0.0, 0.0, -1.0 ) + NaN + + +{{alias}}.factory( μ, σ ) + Returns a function for evaluating the cumulative distribution + function (CDF) of an anglit distribution with location parameter + `μ` and scale parameter `σ`. + + Parameters + ---------- + μ: number + Location parameter. + + σ: number + Scale parameter. + + Returns + ------- + cdf: Function + Cumulative distribution function (CDF). + + Examples + -------- + > var myCDF = {{alias}}.factory( 0.0, 1.0 ); + > var y = myCDF( -10.0 ) + 0.0 + > y = myCDF( 0.0 ) + 0.5 + > y = myCDF( 10.0 ) + 1.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/types/index.d.ts new file mode 100644 index 000000000000..d7c79e0513c5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/types/index.d.ts @@ -0,0 +1,119 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the cumulative distribution function (CDF) for an anglit distribution. +* +* @param x - input value +* @returns evaluated CDF +*/ +type Unary = ( x: number ) => number; + +/** +* Interface for the cumulative distribution function (CDF) of an anglit distribution. +*/ +interface CDF { + /** + * Evaluates the cumulative distribution function (CDF) for an anglit distribution with location parameter `mu` and scale parameter `sigma` at a value `x`. + * + * ## Notes + * + * - If provided `sigma <= 0`, the function returns `NaN`. + * - If provided `x = +infinity`, the function returns `1`. + * - If provided `x = -infinity`, the function returns `0`. + * + * @param x - input value + * @param mu - location parameter + * @param sigma - scale parameter + * @returns evaluated CDF + * + * @example + * var y = cdf( -10.0, 0.0, 1.0 ); + * // returns 0.0 + * + * @example + * var y = cdf( 0.0, 0.0, 1.0 ); + * // returns 0.5 + * + * @example + * var y = cdf( 10.0, 0.0, 1.0 ); + * // returns 1.0 + * + * @example + * var y = cdf( NaN, 0.0, 1.0 ); + * // returns NaN + * + * @example + * var y = cdf( 0.0, NaN, 1.0 ); + * // returns NaN + * + * @example + * var y = cdf( 0.0, 0.0, NaN ); + * // returns NaN + * + * @example + * var y = cdf( 0.0, 0.0, -1.0 ); + * // returns NaN + */ + ( x: number, mu: number, sigma: number ): number; + + /** + * Returns a function for evaluating the cumulative distribution function (CDF) for an anglit distribution with location parameter `mu` and scale parameter `sigma` at a value `x`. + * + * @param mu - location parameter + * @param sigma - scale parameter + * @returns CDF + * + * @example + * var myCdf = cdf.factory( 0.0, 1.0 ); + * var y = myCdf( -10.0 ); + * // returns 0.0 + * + * y = myCdf( 0.0 ); + * // returns 0.5 + */ + factory( mu: number, sigma: number ): Unary; +} + +/** +* Anglit distribution cumulative distribution function (CDF). +* +* @param x - input value +* @param mu - location parameter +* @param sigma - scale parameter +* @returns evaluated CDF +* +* @example +* var y = cdf( 0.0, 0.0, 1.0 ); +* // returns 0.5 +* +* var myCdf = cdf.factory( 0.0, 1.0 ); +* y = myCdf( -10.0 ); +* // returns 0.0 +* +* y = myCdf( 10.0 ); +* // returns 1.0 +*/ +declare var cdf: CDF; + + +// EXPORTS // + +export = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/types/test.ts new file mode 100644 index 000000000000..fc900932ee58 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/docs/types/test.ts @@ -0,0 +1,119 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import cdf = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + cdf( 2, 0, 4 ); // $ExpectType number + cdf( 1, 2, 8 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than three numbers... +{ + cdf( true, 3, 6 ); // $ExpectError + cdf( false, 2, 4 ); // $ExpectError + cdf( '5', 1, 2 ); // $ExpectError + cdf( [], 1, 2 ); // $ExpectError + cdf( {}, 2, 4 ); // $ExpectError + cdf( ( x: number ): number => x, 2, 4 ); // $ExpectError + + cdf( 9, true, 12 ); // $ExpectError + cdf( 9, false, 12 ); // $ExpectError + cdf( 5, '5', 10 ); // $ExpectError + cdf( 8, [], 16 ); // $ExpectError + cdf( 9, {}, 18 ); // $ExpectError + cdf( 8, ( x: number ): number => x, 16 ); // $ExpectError + + cdf( 9, 5, true ); // $ExpectError + cdf( 9, 5, false ); // $ExpectError + cdf( 5, 2, '5' ); // $ExpectError + cdf( 8, 4, [] ); // $ExpectError + cdf( 9, 4, {} ); // $ExpectError + cdf( 8, 5, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + cdf(); // $ExpectError + cdf( 2 ); // $ExpectError + cdf( 2, 0 ); // $ExpectError + cdf( 2, 0, 4, 1 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + cdf.factory( 0, 4 ); // $ExpectType Unary +} + +// The `factory` method returns a function which returns a number... +{ + const fcn = cdf.factory( 0, 4 ); + fcn( 2 ); // $ExpectType number +} + +// The compiler throws an error if the function returned by the `factory` method is provided invalid arguments... +{ + const fcn = cdf.factory( 0, 4 ); + fcn( true ); // $ExpectError + fcn( false ); // $ExpectError + fcn( '5' ); // $ExpectError + fcn( [] ); // $ExpectError + fcn( {} ); // $ExpectError + fcn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const fcn = cdf.factory( 0, 4 ); + fcn(); // $ExpectError + fcn( 2, 0 ); // $ExpectError + fcn( 2, 0, 1 ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided values other than two numbers... +{ + cdf.factory( true, 3 ); // $ExpectError + cdf.factory( false, 2 ); // $ExpectError + cdf.factory( '5', 1 ); // $ExpectError + cdf.factory( [], 1 ); // $ExpectError + cdf.factory( {}, 2 ); // $ExpectError + cdf.factory( ( x: number ): number => x, 2 ); // $ExpectError + + cdf.factory( 9, true ); // $ExpectError + cdf.factory( 9, false ); // $ExpectError + cdf.factory( 5, '5' ); // $ExpectError + cdf.factory( 8, [] ); // $ExpectError + cdf.factory( 9, {} ); // $ExpectError + cdf.factory( 8, ( x: number ): number => x ); // $ExpectError + + cdf.factory( [], true ); // $ExpectError + cdf.factory( {}, false ); // $ExpectError + cdf.factory( false, '5' ); // $ExpectError + cdf.factory( {}, [] ); // $ExpectError + cdf.factory( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + cdf.factory( 0 ); // $ExpectError + cdf.factory( 0, 4, 8 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/c/example.c new file mode 100644 index 000000000000..c6ee34fea095 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/cdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( -5.0, 5.0 ); + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.5, 5.0 ); + y = stdlib_base_dists_anglit_cdf( x, mu, sigma ); + printf( "x: %lf, μ: %lf, σ: %lf, F(x;μ,σ): %lf\n", x, mu, sigma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/index.js new file mode 100644 index 000000000000..b5e1438e3743 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/examples/index.js @@ -0,0 +1,32 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var cdf = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 10, -5.0, 5.0, opts ); +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.5, 5.0, opts ); + +logEachMap( 'x: %lf, μ: %lf, σ: %lf, F(x;μ,σ): %lf', x, mu, sigma, cdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + */ + function cdf( x ) { + var y; + + if ( isnan( x ) ) { + return NaN; + } + + // Transform x to the standardized form + y = ( x - mu ) / sigma; + if ( y <= -PI_OVER_4 ) { + return 0.0; + } + if ( y >= PI_OVER_4 ) { + return 1.0; + } + return abs2( sin( y + PI_OVER_4 ) ); + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/index.js new file mode 100644 index 000000000000..13fb1cd00baa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Anglit distribution cumulative distribution function (CDF). +* +* @module @stdlib/stats/base/dists/anglit/cdf +* +* @example +* var cdf = require( '@stdlib/stats/base/dists/anglit/cdf' ); +* +* var y = cdf( 0.0, 0.0, 1.0 ); +* // returns 0.5 +* +* var myCDF = cdf.factory( 0.0, 1.0 ); +* y = myCDF( 0.0 ); +* // returns 0.5 +* +* y = myCDF( 1.0 ); +* // returns 1.0 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/main.js new file mode 100644 index 000000000000..4c8442bbfb0f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/main.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sin = require( '@stdlib/math/base/special/sin' ); +var abs2 = require( '@stdlib/math/base/special/abs2' ); +var PI = require( '@stdlib/constants/float64/pi' ); + + +// VARIABLES // + +var PI_OVER_4 = PI / 4.0; + + +// MAIN // + +/** +* Evaluates the cumulative distribution function (CDF) for an anglit distribution with location parameter `mu` and scale parameter `sigma` at a value `x`. +* +* @param {number} x - input value +* @param {number} mu - location parameter +* @param {PositiveNumber} sigma - scale parameter +* @returns {Probability} evaluated CDF +* +* @example +* var y = cdf( 0.0, 0.0, 1.0 ); +* // returns 0.5 +* +* @example +* var y = cdf( 0.5, 0.0, 1.0 ); +* // returns ~0.921 +* +* @example +* var y = cdf( 2.0, 0.0, 1.0 ); +* // returns 1.0 +* +* @example +* var y = cdf( -2.0, 0.0, 1.0 ); +* // returns 0.0 +* +* @example +* var y = cdf( NaN, 0.0, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, 0.0, NaN ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, 0.0, -1.0 ); +* // returns NaN +*/ +function cdf( x, mu, sigma ) { + var y; + + if ( + isnan( x ) || + isnan( mu ) || + isnan( sigma ) || + sigma <= 0.0 + ) { + return NaN; + } + + // Transform x to the standardized form + y = ( x - mu ) / sigma; + if ( y <= -PI_OVER_4 ) { + return 0.0; + } + if ( y >= PI_OVER_4 ) { + return 1.0; + } + return abs2( sin( y + PI_OVER_4 ) ); +} + + +// EXPORTS // + +module.exports = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/native.js new file mode 100644 index 000000000000..7e4168a9f950 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/lib/native.js @@ -0,0 +1,76 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Evaluates the cumulative distribution function (CDF) for an anglit distribution with location parameter `mu` and scale parameter `sigma` at a value `x`. +* +* @private +* @param {number} x - input value +* @param {number} mu - location parameter +* @param {PositiveNumber} sigma - scale parameter +* @returns {Probability} evaluated CDF +* +* @example +* var y = cdf( 0.0, 0.0, 1.0 ); +* // returns 0.5 +* +* @example +* var y = cdf( 0.5, 0.0, 1.0 ); +* // returns ~0.921 +* +* @example +* var y = cdf( 2.0, 0.0, 1.0 ); +* // returns 1.0 +* +* @example +* var y = cdf( -2.0, 0.0, 1.0 ); +* // returns 0.0 +* +* @example +* var y = cdf( NaN, 0.0, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, 0.0, NaN ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, 0.0, -1.0 ); +* // returns NaN +*/ +function cdf( x, mu, sigma ) { + return addon( x, mu, sigma ); +} + + +// EXPORTS // + +module.exports = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/manifest.json new file mode 100644 index 000000000000..f3673bd5ab61 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/manifest.json @@ -0,0 +1,85 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/ternary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/sin", + "@stdlib/math/base/special/abs2", + "@stdlib/constants/float64/pi" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/sin", + "@stdlib/math/base/special/abs2", + "@stdlib/constants/float64/pi" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/sin", + "@stdlib/math/base/special/abs2", + "@stdlib/constants/float64/pi" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/package.json b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/package.json new file mode 100644 index 000000000000..a123ee506e57 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/base/dists/anglit/cdf", + "version": "0.0.0", + "description": "Anglit distribution cumulative distribution function (CDF).", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "mathematics", + "math", + "statistics", + "stats", + "dist", + "distribution", + "probability", + "continuous distribution", + "cumulative distribution", + "cumulative distribution function", + "cdf", + "anglit", + "random variable" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/addon.c new file mode 100644 index 000000000000..05bf633dda2a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/cdf.h" +#include "stdlib/math/base/napi/ternary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DDD_D( stdlib_base_dists_anglit_cdf ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/main.c new file mode 100644 index 000000000000..d967bf6d0fe0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/src/main.c @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/cdf.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/sin.h" +#include "stdlib/math/base/special/abs2.h" +#include "stdlib/constants/float64/pi.h" + +static const double PI_OVER_4 = STDLIB_CONSTANT_FLOAT64_PI / 4.0; + +/** +* Evaluates the cumulative distribution function (CDF) for an anglit distribution with location parameter `mu` and scale parameter `sigma` at a value `x`. +* +* @param x input value +* @param mu location parameter +* @param sigma scale parameter +* @return evaluated CDF +* +* @example +* double y = stdlib_base_dists_anglit_cdf( 0.0, 0.0, 1.0 ); +* // returns 0.5 +*/ +double stdlib_base_dists_anglit_cdf( const double x, const double mu, const double sigma ) { + double y; + + if ( + stdlib_base_is_nan( x ) || + stdlib_base_is_nan( mu ) || + stdlib_base_is_nan( sigma ) || + sigma <= 0.0 + ) { + return 0.0 / 0.0; // NaN + } + + // Standardize + y = ( x - mu ) / sigma; + if ( y <= -PI_OVER_4 ) { + return 0.0; + } + if ( y >= PI_OVER_4 ) { + return 1.0; + } + return stdlib_base_abs2( stdlib_base_sin( y + PI_OVER_4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/fixtures/python/data.json new file mode 100644 index 000000000000..b1c278300fe0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/fixtures/python/data.json 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0.004144384490614566, 0.7966468717918823, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 0.8445271118402743, 0.0, 0.2885702226863872, 0.0, 0.9983392702054179, 1.0, 0.0, 0.6866162881463685, 1.0, 1.0, 0.0, 0.9689457469608531, 0.0, 1.0, 0.0, 1.0, 0.0, 0.5144143478195496, 0.2800139683328457, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.46326349098026626]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/fixtures/python/runner.py new file mode 100644 index 000000000000..4457eeee6c19 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/fixtures/python/runner.py @@ -0,0 +1,98 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate CDF fixtures for Anglit distribution.""" + +import os +import json +import numpy as np +from scipy.stats import anglit + + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(x, loc, sigma, name): + """Generate fixture data and write to file. + + # Arguments + + * `x`: input values + * `loc`: location parameter + * `sigma`: scale parameter + * `name::str`: output filename + + # Examples + + ``` python + python> x = np.random.uniform(0.0, 10.0, 300) + python> loc = np.random.uniform(0.0, 10.0, 300) + python> sigma = np.random.uniform(0.1, 5.0, 300) + python> gen(x, loc, sigma, './data.json') + ``` + """ + z = anglit.cdf(x, loc=loc, scale=sigma) + + # Store data to be written to file as a dictionary: + data = { + "x": x.tolist(), + "mu": loc.tolist(), + "sigma": sigma.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding="utf-8") as outfile: + json.dump(data, outfile) + + +def main(): + """Generate fixture data.""" + # Set seed for reproducibility: + np.random.seed(457) + + # Generate data for three different ranges of input values and parameters: + x_small = np.random.uniform(-10.0, 10.0, 300) + loc_small = np.random.uniform(-5.0, 5.0, 300) + sigma_small = np.random.uniform(0.1, 5.0, 300) + + x_med = np.random.uniform(-20.0, 20.0, 300) + loc_med = np.random.uniform(-10.0, 10.0, 300) + sigma_med = np.random.uniform(0.1, 10.0, 300) + + x_large = np.random.uniform(-50.0, 50.0, 400) + loc_large = np.random.uniform(-20.0, 20.0, 400) + sigma_large = np.random.uniform(0.1, 20.0, 400) + + # Concatenate arrays + x = np.concatenate([x_small, x_med, x_large]) + loc = np.concatenate([loc_small, loc_med, loc_large]) + sigma = np.concatenate([sigma_small, sigma_med, sigma_large]) + + gen(x, loc, sigma, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.cdf.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.cdf.js new file mode 100644 index 000000000000..5ad2f83751ab --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.cdf.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var cdf = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = cdf( NaN, 0.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and finite `mu` and `sigma`, the function returns `1`', function test( t ) { + var y = cdf( PINF, 0.0, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `-infinity` for `x` and finite `mu` and `sigma`, the function returns `0`', function test( t ) { + var y = cdf( NINF, 0.0, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `sigma <= 0`, the function returns `NaN`', function test( t ) { + var y; + + y = cdf( 0.0, 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given `mu` and `sigma`', function test( t ) { + var expected; + var sigma; + var mu; + var x; + var y; + var i; + + expected = data.expected; + x = data.x; + mu = data.mu; + sigma = data.sigma; + + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], mu[i], sigma[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', σ: '+sigma[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[i], 3 ), 'within tolerance. x: '+x[i]+'. mu: '+mu[i]+'. σ: '+sigma[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.factory.js new file mode 100644 index 000000000000..420838e99b37 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.factory.js @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var factory = require( './../lib/factory.js' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var cdf = factory( 0.0, 1.0 ); + t.strictEqual( typeof cdf, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.0, 1.0 ); + y = cdf( NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, 1.0 ); + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( 1.0, NaN ); + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, NaN ); + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided finite `mu` and `sigma`, the created function returns `1` when provided `+infinity` for `x`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.5, 1.0 ); + y = cdf( PINF ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided finite `mu` and `sigma`, the created function returns `0` when provided `-infinity` for `x`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.5, 1.0 ); + y = cdf( NINF ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `sigma <= 0`, the created function always returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.0, -1.0 ); + + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( 0.0, 0.0 ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( 0.0, NINF ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the created function evaluates the cdf for `x` given `mu` and `sigma`', function test( t ) { + var expected; + var sigma; + var cdf; + var mu; + var x; + var y; + var i; + + expected = data.expected; + x = data.x; + mu = data.mu; + sigma = data.sigma; + + for ( i = 0; i < x.length; i++ ) { + cdf = factory( mu[i], sigma[i] ); + y = cdf( x[i] ); + if ( y === expected[i] ) { + t.strictEqual(y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', σ: '+sigma[i]+', y: '+y+', expected: '+expected[i]); + } else { + t.ok( isAlmostSameValue( y, expected[i], 3 ), 'within tolerance. x: '+x[i]+'. mu: '+mu[i]+'. σ: '+sigma[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.js new file mode 100644 index 000000000000..85a2b4b63e97 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var cdf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a factory method for generating `cdf` functions', function test( t ) { + t.strictEqual( typeof cdf.factory, 'function', 'exports a factory method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.native.js new file mode 100644 index 000000000000..bf0bbe875a6c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/cdf/test/test.native.js @@ -0,0 +1,115 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = cdf( NaN, 0.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and finite `mu` and `sigma`, the function returns `1`', opts, function test( t ) { + var y = cdf( PINF, 0.0, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `-infinity` for `x` and finite `mu` and `sigma`, the function returns `0`', opts, function test( t ) { + var y = cdf( NINF, 0.0, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `sigma <= 0`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 0.0, 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given `mu` and `sigma`', opts, function test( t ) { + var expected; + var sigma; + var mu; + var x; + var y; + var i; + + expected = data.expected; + x = data.x; + mu = data.mu; + sigma = data.sigma; + + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], mu[i], sigma[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', σ: '+sigma[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[i], 3 ), 'within tolerance. x: '+x[i]+'. mu: '+mu[i]+'. σ: '+sigma[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/README.md new file mode 100644 index 000000000000..2532a31c58ca --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/README.md @@ -0,0 +1,238 @@ + + +# Entropy + +> [Anglit][anglit-distribution] distribution [differential entropy][entropy]. + +
+ +The [differential entropy][entropy] (in [nats][nats]) for an [anglit][anglit-distribution] random variable is + + + +```math +h\left( X \right) = 1 - \ln(2) + \ln(\sigma) +``` + + + +where `σ > 0` is the scale parameter. + +
+ + + +
+ +## Usage + +```javascript +var entropy = require( '@stdlib/stats/base/dists/anglit/entropy' ); +``` + +#### entropy( mu, sigma ) + +Returns the [differential entropy][entropy] of an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma` (in [nats][nats]). + +```javascript +var v = entropy( 0.0, 1.0 ); +// returns ~0.307 + +v = entropy( 0.0, 2.0 ); +// returns ~1.000 + +v = entropy( 1.0, 0.5 ); +// returns ~-0.386 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var v = entropy( NaN, 1.0 ); +// returns NaN + +v = entropy( 0.0, NaN ); +// returns NaN +``` + +If provided `sigma <= 0`, the function returns `NaN`. + +```javascript +var y = entropy( 2.0, -1.0 ); +// returns NaN + +y = entropy( 1.0, 0.0 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var entropy = require( '@stdlib/stats/base/dists/anglit/entropy' ); + +var opts = { + 'dtype': 'float64' +}; + +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.5, 5.0, opts ); + +logEachMap( 'μ: %lf, σ: %lf, h(X;μ,σ): %lf', mu, sigma, entropy ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/anglit/entropy.h" +``` + +#### stdlib_base_dists_anglit_entropy( mu, sigma ) + +Returns the differential entropy of an anglit distribution with location parameter `mu` and scale parameter `sigma`. + +```c +double out = stdlib_base_dists_anglit_entropy( 0.0, 1.0 ); +// returns ~0.307 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **sigma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_anglit_entropy( const double mu, const double sigma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/anglit/entropy.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.5, 10.0 ); + y = stdlib_base_dists_anglit_entropy( mu, sigma ); + printf( "μ: %lf, σ: %lf, h(X;μ,σ): %lf\n", mu, sigma, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29 + +[anglit-distribution]: https://en.wikipedia.org/wiki/Anglit_distribution + +[nats]: https://en.wikipedia.org/wiki/Nat_%28unit%29 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/benchmark.js new file mode 100644 index 000000000000..90ae6b959043 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/benchmark.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var entropy = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -5.0, 5.0, arrayOpts ); + sigma = uniform( 100, 0.1, 10.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = entropy( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/benchmark.native.js new file mode 100644 index 000000000000..d419f077b75e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( entropy instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + + mu = uniform( 100, -5.0, 5.0, arrayOpts ); + sigma = uniform( 100, 0.1, 10.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = entropy( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/c/benchmark.c new file mode 100644 index 000000000000..bd190e0c682b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/benchmark/c/benchmark.c @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/entropy.h" +#include +#include +#include +#include +#include + +#define NAME "anglit-entropy" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double sigma[ 100 ]; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -5.0, 5.0 ); + sigma[ i ] = random_uniform( 0.1, 10.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_anglit_entropy( mu[ i%100 ], sigma[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/repl.txt new file mode 100644 index 000000000000..41a3f6d515d1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/repl.txt @@ -0,0 +1,33 @@ + +{{alias}}( μ, σ ) + Returns the differential entropy of an anglit distribution (in nats). + + If provided `NaN` as any argument, the function returns `NaN`. + + If provided `σ <= 0`, the function returns `NaN`. + + Parameters + ---------- + μ: number + Location parameter. + + σ: number + Scale parameter. + + Returns + ------- + out: number + Entropy. + + Examples + -------- + > var v = {{alias}}( 0.0, 1.0 ) + ~0.307 + > v = {{alias}}( 0.0, 2.0 ) + ~1.000 + > v = {{alias}}( 1.0, 0.5 ) + ~-0.386 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/types/index.d.ts new file mode 100644 index 000000000000..e0c98b1d21aa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the differential entropy of an anglit distribution (in nats). +* +* ## Notes +* +* - If provided `sigma <= 0`, the function returns `NaN`. +* - If provided `NaN` as any argument, the function returns `NaN`. +* +* @param mu - location parameter +* @param sigma - scale parameter +* @returns entropy +* +* @example +* var v = entropy( 0.0, 1.0 ); +* // returns ~0.307 +* +* @example +* var v = entropy( 0.0, 2.0 ); +* // returns ~1.000 +* +* @example +* var v = entropy( 1.0, 0.5 ); +* // returns ~-0.386 +* +* @example +* var v = entropy( 0.0, -1.0 ); +* // returns NaN +* +* @example +* var v = entropy( NaN, 1.0 ); +* // returns NaN +* +* @example +* var v = entropy( 0.0, NaN ); +* // returns NaN +*/ +declare function entropy( mu: number, sigma: number ): number; + + +// EXPORTS // + +export = entropy; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/types/test.ts new file mode 100644 index 000000000000..1e3156fd3dfd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/docs/types/test.ts @@ -0,0 +1,53 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import entropy = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + entropy( 0, 1 ); // $ExpectType number + entropy( 2, 4 ); // $ExpectType number + entropy( -3, 0.5 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + entropy( true, 1 ); // $ExpectError + entropy( false, 2 ); // $ExpectError + entropy( '5', 1 ); // $ExpectError + entropy( [], 1 ); // $ExpectError + entropy( {}, 2 ); // $ExpectError + entropy( ( x: number ): number => x, 2 ); // $ExpectError + + entropy( 1, true ); // $ExpectError + entropy( 2, false ); // $ExpectError + entropy( 1, '5' ); // $ExpectError + entropy( 2, [] ); // $ExpectError + entropy( 2, {} ); // $ExpectError + entropy( 2, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + entropy(); // $ExpectError + entropy( 1 ); // $ExpectError + entropy( 1, 2, 3 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/c/example.c new file mode 100644 index 000000000000..c17e387daceb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/entropy.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * ( max - min ) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.5, 5.0 ); + y = stdlib_base_dists_anglit_entropy( mu, sigma ); + printf( "μ: %lf, σ: %lf, h(X;μ,σ): %lf\n", mu, sigma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/index.js new file mode 100644 index 000000000000..75ac5e94eb58 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var entropy = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.5, 5.0, opts ); + +logEachMap( 'μ: %lf, σ: %lf, h(X;μ,σ): %lf', mu, sigma, entropy ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "entropy", + "information", + "shannon", + "nats", + "continuous", + "probability", + "prob", + "anglit", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/addon.c new file mode 100644 index 000000000000..1bfdabeec67a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/entropy.h" +#include "stdlib/math/base/napi/binary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_anglit_entropy ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/main.c new file mode 100644 index 000000000000..449040546144 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/src/main.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/entropy.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/ln.h" +#include "stdlib/constants/float64/ln_two.h" + +/** +* Returns the differential entropy of an anglit distribution with location parameter `mu` and scale parameter `sigma`. +* +* @param mu location parameter +* @param sigma scale parameter +* @return entropy +* +* @example +* double y = stdlib_base_dists_anglit_entropy( 0.0, 1.0 ); +* // returns ~0.307 +*/ +double stdlib_base_dists_anglit_entropy( const double mu, const double sigma ) { + if ( + stdlib_base_is_nan( mu ) || + stdlib_base_is_nan( sigma ) || + sigma <= 0.0 + ) { + return 0.0 / 0.0; // NaN + } + + return 1.0 - STDLIB_CONSTANT_FLOAT64_LN2 + stdlib_base_ln( sigma ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/fixtures/python/data.json new file mode 100644 index 000000000000..acdee8e7fca0 --- /dev/null +++ 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index 000000000000..f2bb897f59b8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/fixtures/python/runner.py @@ -0,0 +1,91 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate entropy fixtures for Anglit distribution.""" + +import os +import json +import numpy as np +from scipy.stats import anglit + + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(loc, scale, name): + """Generate fixture data and write to file. + + # Arguments + + * `loc`: location parameter + * `scale`: scale parameter + * `name::str`: output filename + + # Examples + + ``` python + python> loc = np.random.uniform(0.0, 10.0, 300) + python> scale = np.random.uniform(0.1, 5.0, 300) + python> gen(loc, scale, './data.json') + ``` + """ + z = anglit.entropy(loc=loc, scale=scale) + + # Store data to be written to file as a dictionary: + data = { + "mu": loc.tolist(), + "sigma": scale.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding="utf-8") as outfile: + json.dump(data, outfile) + + +def main(): + """Generate fixture data.""" + # Set seed for reproducibility: + np.random.seed(457) + + # Generate data for three different ranges of input values and parameters: + loc_small = np.random.uniform(-5.0, 5.0, 300) + sigma_small = np.random.uniform(0.1, 5.0, 300) + + loc_med = np.random.uniform(-10.0, 10.0, 300) + sigma_med = np.random.uniform(0.1, 10.0, 300) + + loc_large = np.random.uniform(-20.0, 20.0, 400) + sigma_large = np.random.uniform(0.1, 20.0, 400) + + # Concatenate arrays + loc = np.concatenate([loc_small, loc_med, loc_large]) + sigma = np.concatenate([sigma_small, sigma_med, sigma_large]) + + gen(loc, sigma, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/test.js new file mode 100644 index 000000000000..eba19774fbab --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/test.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var entropy = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof entropy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var v = entropy( NaN, 1.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = entropy( 0.0, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `sigma <= 0`, the function returns `NaN`', function test( t ) { + var y; + + y = entropy( 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = entropy( 0.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the differential entropy of an anglit distribution', function test( t ) { + var expected; + var sigma; + var mu; + var i; + var y; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < expected.length; i++ ) { + y = entropy( mu[i], sigma[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'mu: '+mu[i]+', sigma: '+sigma[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[i], 5 ), 'within tolerance. mu: '+mu[i]+'. sigma: '+sigma[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/test.native.js new file mode 100644 index 000000000000..58963fd9096d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/entropy/test/test.native.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// VARIABLES // + +var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( entropy instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof entropy, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var v = entropy( NaN, 1.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = entropy( 0.0, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `sigma <= 0`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = entropy( 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = entropy( 0.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the differential entropy of an anglit distribution', opts, function test( t ) { + var expected; + var sigma; + var mu; + var i; + var y; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < expected.length; i++ ) { + y = entropy( mu[i], sigma[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'mu: '+mu[i]+', sigma: '+sigma[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[i], 5 ), 'within tolerance. mu: '+mu[i]+'. sigma: '+sigma[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/README.md index d41e7ead215d..525ad5262cc2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/README.md @@ -34,6 +34,11 @@ The [mean][mean] of an [anglit][anglit-distribution] random variable with locati \mathbb{E}\left[ X \right] = \mu ``` + + @@ -116,7 +121,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var sigma = uniform( 10, 0.1, 20.0, opts ); -logEachMap( 'µ: %lf, σ: %lf, E(X;µ,σ): %lf', mu, sigma, mean ); +logEachMap( 'μ: %0.4f, σ: %0.4f, E(X;μ,σ): %0.4f', mu, sigma, mean ); ``` @@ -205,7 +210,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); sigma = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_anglit_mean( mu, sigma ); - printf( "µ: %lf, σ: %lf, E(X;µ,σ): %lf\n", mu, sigma, y ); + printf( "μ: %lf, σ: %lf, E(X;μ,σ): %lf\n", mu, sigma, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/docs/img/equation_anglit_mean.svg b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/docs/img/equation_anglit_mean.svg new file mode 100644 index 000000000000..01cbe489f072 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/docs/img/equation_anglit_mean.svg @@ -0,0 +1,21 @@ + +double-struck upper E left-bracket upper X right-bracket equals mu + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/c/example.c index 988122bcda03..280a1ded7a47 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); sigma = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_anglit_mean( mu, sigma ); - printf( "µ: %lf, σ: %lf, E(X;µ,σ): %lf\n", mu, sigma, y ); + printf( "μ: %lf, σ: %lf, E(X;μ,σ): %lf\n", mu, sigma, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/index.js index c534f37bd4f3..b83d63f0ac16 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mean/examples/index.js @@ -28,4 +28,4 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var sigma = uniform( 10, 0.1, 20.0, opts ); -logEachMap( 'µ: %lf, σ: %lf, E(X;µ,σ): %lf', mu, sigma, mean ); +logEachMap( 'μ: %0.4f, σ: %0.4f, E(X;μ,σ): %0.4f', mu, sigma, mean ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/README.md index acf107f90d17..1da35bb891fc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/README.md @@ -34,6 +34,11 @@ The [median][median] for an [anglit][anglit-distribution] random variable with l \mathop{\mathrm{Median}}\left( X \right) = \mu ``` + + @@ -116,7 +121,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var sigma = uniform( 10, 0.1, 20.0, opts ); -logEachMap( 'µ: %lf, σ: %lf, Median(X;µ,σ): %lf', mu, sigma, median ); +logEachMap( 'μ: %0.4f, σ: %0.4f, Median(X;μ,σ): %0.4f', mu, sigma, median ); ``` @@ -205,7 +210,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); sigma = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_anglit_median( mu, sigma ); - printf( "µ: %lf, σ: %lf, Median(X;µ,σ): %lf\n", mu, sigma, y ); + printf( "μ: %lf, σ: %lf, Median(X;μ,σ): %lf\n", mu, sigma, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/median/docs/img/equation_anglit_median.svg b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/docs/img/equation_anglit_median.svg new file mode 100644 index 000000000000..cbbb8eb85462 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/docs/img/equation_anglit_median.svg @@ -0,0 +1,31 @@ + +upper M e d i a n left-parenthesis upper X right-parenthesis equals mu + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/c/example.c index 075b02e92d22..2e03c9f517df 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); sigma = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_anglit_median( mu, sigma ); - printf( "µ: %lf, σ: %lf, Median(X;µ,σ): %lf\n", mu, sigma, y ); + printf( "μ: %lf, σ: %lf, Median(X;μ,σ): %lf\n", mu, sigma, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/index.js index 9cb7f310d1e7..9d6fc2468220 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/median/examples/index.js @@ -28,4 +28,4 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var sigma = uniform( 10, 0.1, 20.0, opts ); -logEachMap( 'µ: %lf, σ: %lf, Median(X;µ,σ): %lf', mu, sigma, median ); +logEachMap( 'μ: %0.4f, σ: %0.4f, Median(X;μ,σ): %0.4f', mu, sigma, median ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/README.md new file mode 100644 index 000000000000..9c7d8f8cbfd8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/README.md @@ -0,0 +1,244 @@ + + +# Mode + +> [Anglit][anglit-distribution] distribution [mode][mode]. + + + +
+ +The [mode][mode] for an [anglit][anglit-distribution] random variable with location parameter `μ` and scale parameter `σ > 0` is + + + +```math +\mathop{\mathrm{mode}}\left( X \right) = \mu +``` + + + + + +
+ + + + + +
+ +## Usage + +```javascript +var mode = require( '@stdlib/stats/base/dists/anglit/mode' ); +``` + +#### mode( mu, sigma ) + +Returns the [mode][mode] for an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma`. + +```javascript +var y = mode( 2.0, 1.0 ); +// returns 2.0 + +y = mode( 0.0, 1.0 ); +// returns 0.0 + +y = mode( -1.0, 4.0 ); +// returns -1.0 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = mode( NaN, 1.0 ); +// returns NaN + +y = mode( 0.0, NaN ); +// returns NaN +``` + +If provided `sigma <= 0`, the function returns `NaN`. + +```javascript +var y = mode( 0.0, 0.0 ); +// returns NaN + +y = mode( 0.0, -1.0 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var mode = require( '@stdlib/stats/base/dists/anglit/mode' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.1, 20.0, opts ); + +logEachMap( 'μ: %lf, σ: %lf, mode(X;μ,σ): %lf', mu, sigma, mode ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/anglit/mode.h" +``` + +#### stdlib_base_dists_anglit_mode( mu, sigma ) + +Returns the mode for an anglit distribution with location parameter `mu` and scale parameter `sigma`. + +```c +double out = stdlib_base_dists_anglit_mode( 0.0, 1.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **sigma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_anglit_mode( const double mu, const double sigma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/anglit/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_mode( mu, sigma ); + printf( "μ: %lf, σ: %lf, mode(X;μ,σ): %lf\n", mu, sigma, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[anglit-distribution]: https://en.wikipedia.org/wiki/Anglit_distribution + +[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29 + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/benchmark.js new file mode 100644 index 000000000000..74c1b1963424 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/benchmark.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; +var mode = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, arrayOpts ); + sigma = uniform( 100, EPS, 20.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/benchmark.native.js new file mode 100644 index 000000000000..60c318766047 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/benchmark.native.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, arrayOpts ); + sigma = uniform( 100, EPS, 20.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mode( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/c/benchmark.c new file mode 100644 index 000000000000..c9532a50e5b9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/mode.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "anglit-mode" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double sigma[ 100 ]; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -10.0, 10.0 ); + sigma[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_anglit_mode( mu[ i%100 ], sigma[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/img/equation_anglit_mode.svg b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/img/equation_anglit_mode.svg new file mode 100644 index 000000000000..8dc20fd38339 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/img/equation_anglit_mode.svg @@ -0,0 +1,27 @@ + +m o d e left-parenthesis upper X right-parenthesis equals mu + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/repl.txt new file mode 100644 index 000000000000..8c3870d54a97 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( μ, σ ) + Returns the mode of an anglit distribution with location parameter `μ` + and scale parameter `σ`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If provided `σ <= 0`, the function returns `NaN`. + + Parameters + ---------- + μ: number + Location parameter. + + σ: number + Scale parameter. + + Returns + ------- + out: number + Mode. + + Examples + -------- + > var y = {{alias}}( 0.0, 1.0 ) + 0.0 + > y = {{alias}}( 4.0, 2.0 ) + 4.0 + > y = {{alias}}( NaN, 1.0 ) + NaN + > y = {{alias}}( 0.0, NaN ) + NaN + > y = {{alias}}( 0.0, 0.0 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/types/index.d.ts new file mode 100644 index 000000000000..c6373ec02525 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/types/index.d.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the mode for an anglit distribution with location parameter `mu` and scale parameter `sigma`. +* +* ## Notes +* +* - If provided `sigma <= 0`, the function returns `NaN`. +* +* @param mu - location parameter +* @param sigma - scale parameter +* @returns mode +* +* @example +* var y = mode( 0.0, 1.0 ); +* // returns 0.0 +* +* @example +* var y = mode( 5.0, 2.0 ); +* // returns 5.0 +* +* @example +* var y = mode( NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = mode( 0.0, NaN ); +* // returns NaN +* +* @example +* var y = mode( 0.0, 0.0 ); +* // returns NaN +*/ +declare function mode( mu: number, sigma: number ): number; + + +// EXPORTS // + +export = mode; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/types/test.ts new file mode 100644 index 000000000000..ff08cedd2ecc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import mode = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + mode( 0, 2 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + mode( true, 3 ); // $ExpectError + mode( false, 2 ); // $ExpectError + mode( '5', 1 ); // $ExpectError + mode( [], 1 ); // $ExpectError + mode( {}, 2 ); // $ExpectError + mode( ( x: number ): number => x, 2 ); // $ExpectError + + mode( 9, true ); // $ExpectError + mode( 9, false ); // $ExpectError + mode( 5, '5' ); // $ExpectError + mode( 8, [] ); // $ExpectError + mode( 9, {} ); // $ExpectError + mode( 8, ( x: number ): number => x ); // $ExpectError + + mode( [], true ); // $ExpectError + mode( {}, false ); // $ExpectError + mode( false, '5' ); // $ExpectError + mode( {}, [] ); // $ExpectError + mode( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + mode(); // $ExpectError + mode( 3 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/c/example.c new file mode 100644 index 000000000000..505e4fe116d6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/mode.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_mode( mu, sigma ); + printf( "μ: %lf, σ: %lf, mode(X;μ,σ): %lf\n", mu, sigma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/index.js new file mode 100644 index 000000000000..1f4024298f2a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var mode = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.1, 20.0, opts ); + +logEachMap( 'μ: %lf, σ: %lf, mode(X;μ,σ): %lf', mu, sigma, mode ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "anglit", + "continuous", + "mode", + "location", + "center", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/addon.c new file mode 100644 index 000000000000..0be872529ca9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/mode.h" +#include "stdlib/math/base/napi/binary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_anglit_mode ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/main.c new file mode 100644 index 000000000000..ab04e39752fb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/src/main.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/mode.h" +#include "stdlib/math/base/assert/is_nan.h" + +/** +* Returns the mode for an anglit distribution with location parameter `mu` and scale parameter `sigma`. +* +* @param mu location parameter +* @param sigma scale parameter +* @return mode +* +* @example +* double y = stdlib_base_dists_anglit_mode( 0.0, 1.0 ); +* // returns 0.0 +*/ +double stdlib_base_dists_anglit_mode( const double mu, const double sigma ) { + if ( + stdlib_base_is_nan( mu ) || + stdlib_base_is_nan( sigma ) || + sigma <= 0.0 + ) { + return 0.0 / 0.0; // NaN + } + return mu; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/fixtures/python/data.json new file mode 100644 index 000000000000..4bf974c4a106 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/fixtures/python/data.json @@ -0,0 +1 @@ +{"mu": [-1.4188624938085024, -4.64177188303363, -4.89367800766936, -2.0018412226987325, -2.379785366558007, -2.754663788840509, 3.2412000807028125, 0.8777223461769701, 3.0488677689207684, 4.564461367922355, -3.5052274356012525, 4.832048205916376, 4.752181395850929, -3.734911692922184, -4.983297757032351, -4.936113632632738, -1.8080639730360017, 3.1242444738840938, -1.1823243441526756, 2.4418692725939684, 2.5101004173000003, -4.503549156524278, 3.8425077400738346, -3.9520416643700784, -0.8560163423205447, 4.9930092313126515, -0.2643684864911924, 3.8630547495119654, 2.4548175711439644, -1.6394978579141242, -3.985231936272781, -3.5373334678588533, -3.1379390448168873, 0.32636765269835166, -3.8804233097239136, 3.417879151298557, 2.8064567331065158, 3.795838340893148, 2.6326141145441238, -0.2217810302128438, -3.4898617897879216, -3.7758762264524046, 1.9128249362350953, 4.306059277139584, 2.835554295618979, 3.5515260391389827, -3.7084967252576186, -2.479392655636911, 2.5577264774129125, 2.0290991586029463, 2.928922335020129, 3.451962188079472, 4.068379622464665, 2.8036816528514947, 3.403340568818546, 0.8137928925271618, 3.263666047179143, -2.1332497349513546, 0.4913951736966604, 0.6031633656045265, 2.2335063360008967, 0.5443426246048775, -2.4426667457826365, -4.5079479645603096, -0.06644812885587026, -4.215968763421598, 1.8628682460741146, 2.9337829349128697, 2.1457782208943774, 0.8779040605572508, 4.98004429779321, 3.526588814873893, -4.872049782843234, 4.506045067069165, 0.8655490541495192, -3.0639827406917473, 4.409021102788898, 3.1055377080384847, -1.5516000906386918, 0.17658348292877601, 1.8392098888867983, -1.6585435251068512, 0.7862254885745257, 0.44828956726699687, 3.5211023400068715, -1.4128134141728435, -2.5124614774723564, -2.9668622035600913, 3.4236063144716926, -4.616049334482643, 2.859579497132396, -3.453714738465168, -4.211929277313196, 2.825110703745482, -2.9009166213051474, -3.647485462379889, 4.085819008839065, -1.7822637588684942, -3.564141374429697, 4.073674952105579], "sigma": [4.3978887989349245, 2.264782525053, 3.9823436057451422, 2.0199252585774343, 1.0432950808993258, 3.275487119233307, 0.4935198821643638, 4.594532084996181, 4.2455717009618406, 0.5693940503634609, 1.6454403140045544, 2.3007741994643487, 0.8288039318134294, 3.888222332772863, 4.2204341324422625, 0.8756797986717035, 4.905026147500793, 1.564046443532785, 1.1781577270641967, 1.492942325474352, 2.0987595395226037, 3.2309774183724844, 0.39283064061814477, 3.3596879913476516, 1.0889826812405607, 1.3127337585367493, 2.8578420892817715, 0.09725108498362721, 2.4453535318039643, 3.895111554469005, 3.452042487736799, 1.7128018540368088, 1.2478209611215962, 2.271838484211897, 2.2553932886152452, 4.625203778974315, 3.828393371526634, 0.9810255358024017, 2.8247767600062987, 3.603985009336138, 3.389610358515392, 1.0172850345233326, 4.787287180090457, 2.9408617658993723, 2.063130902225915, 2.1894385670007908, 4.925650612783017, 0.9148324914871353, 2.6224953252336967, 4.670930256320625, 0.9380678739717146, 4.4722475740503125, 1.2925594131981133, 3.8632659928903004, 2.4537859614897553, 1.5276395039532182, 3.2091937086063784, 2.3046987601627666, 2.709023833026736, 1.5472025880792935, 0.8691533754248087, 2.788960642582124, 0.34228788116005104, 4.173540503415632, 1.1704753465408209, 2.8091344195099945, 2.821132534120335, 4.529482589522634, 0.6297862987086078, 2.3638749160707837, 3.4941249361508344, 2.5645293469442247, 3.309743071988909, 1.0879138936411243, 4.450766001595327, 0.30427818256797245, 3.1544752771758553, 3.4923044965496723, 0.31407022493745496, 0.7697841072573064, 0.9232910010078071, 0.8041261673386063, 0.098083765028647, 0.9927143114488257, 3.913004037109145, 0.2324296234624612, 2.2789269273911574, 3.068614483172391, 2.2733547439224258, 0.455033197062642, 1.5485099848409407, 2.4198950382441735, 0.8755558627832155, 0.26825421256270354, 3.163827108544711, 1.4136087938365116, 3.7376196699608517, 4.109708814280007, 2.1343370732297244, 2.932785632192921], "expected": [-1.4188624938085024, -4.64177188303363, -4.89367800766936, -2.0018412226987325, -2.379785366558007, -2.754663788840509, 3.2412000807028125, 0.8777223461769701, 3.0488677689207684, 4.564461367922355, -3.5052274356012525, 4.832048205916376, 4.752181395850929, -3.734911692922184, -4.983297757032351, -4.936113632632738, -1.8080639730360017, 3.1242444738840938, -1.1823243441526756, 2.4418692725939684, 2.5101004173000003, -4.503549156524278, 3.8425077400738346, -3.9520416643700784, -0.8560163423205447, 4.9930092313126515, -0.2643684864911924, 3.8630547495119654, 2.4548175711439644, -1.6394978579141242, -3.985231936272781, -3.5373334678588533, -3.1379390448168873, 0.32636765269835166, -3.8804233097239136, 3.417879151298557, 2.8064567331065158, 3.795838340893148, 2.6326141145441238, -0.2217810302128438, -3.4898617897879216, -3.7758762264524046, 1.9128249362350953, 4.306059277139584, 2.835554295618979, 3.5515260391389827, -3.7084967252576186, -2.479392655636911, 2.5577264774129125, 2.0290991586029463, 2.928922335020129, 3.451962188079472, 4.068379622464665, 2.8036816528514947, 3.403340568818546, 0.8137928925271618, 3.263666047179143, -2.1332497349513546, 0.4913951736966604, 0.6031633656045265, 2.2335063360008967, 0.5443426246048775, -2.4426667457826365, -4.5079479645603096, -0.06644812885587026, -4.215968763421598, 1.8628682460741146, 2.9337829349128697, 2.1457782208943774, 0.8779040605572508, 4.98004429779321, 3.526588814873893, -4.872049782843234, 4.506045067069165, 0.8655490541495192, -3.0639827406917473, 4.409021102788898, 3.1055377080384847, -1.5516000906386918, 0.17658348292877601, 1.8392098888867983, -1.6585435251068512, 0.7862254885745257, 0.44828956726699687, 3.5211023400068715, -1.4128134141728435, -2.5124614774723564, -2.9668622035600913, 3.4236063144716926, -4.616049334482643, 2.859579497132396, -3.453714738465168, -4.211929277313196, 2.825110703745482, -2.9009166213051474, -3.647485462379889, 4.085819008839065, -1.7822637588684942, -3.564141374429697, 4.073674952105579]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/fixtures/python/runner.py new file mode 100644 index 000000000000..441ae268647b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/fixtures/python/runner.py @@ -0,0 +1,82 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import anglit + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(loc, sigma, name): + """Generate fixture data and write to file. + + # Arguments + + * `loc`: location parameter + * `sigma`: scale parameter + * `name::str`: output filename + + # Examples + + ``` python + python> loc = np.random.rand(1000) * 10.0 - 5.0 + python> sigma = np.random.rand(1000) * 5.0 + 0.01 + python> gen(loc, sigma, "data.json") + ``` + """ + # SciPy does not expose `anglit.mode`; the mode is analytically equal to `loc`. + # Evaluate the PDF at `loc` to validate inputs via SciPy and keep SciPy-based fixtures. + _ = np.array(anglit.pdf(loc, loc=loc, scale=sigma)) + z = np.array(loc) + + # Store data to be written to file as a dictionary: + data = { + "mu": loc.tolist(), + "sigma": sigma.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding="utf-8") as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding="utf-8") as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + loc = np.random.rand(100) * 10.0 - 5.0 + sigma = np.random.rand(100) * 5.0 + 0.01 + gen(loc, sigma, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/test.js new file mode 100644 index 000000000000..a7c264c87b75 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/test.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var mode = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mode, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = mode( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = mode( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', function test( t ) { + var y; + + y = mode( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the mode of an anglit distribution', function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < mu.length; i++ ) { + y = mode( mu[i], sigma[i] ); + t.strictEqual( y, expected[i], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/test.native.js new file mode 100644 index 000000000000..8beb6f881162 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/mode/test/test.native.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// VARIABLES // + +var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( mode instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof mode, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = mode( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = mode( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = mode( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = mode( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the mode of an anglit distribution', opts, function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < mu.length; i++ ) { + y = mode( mu[i], sigma[i] ); + t.strictEqual( y, expected[i], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/README.md index f7603d790eb2..81411952c9cd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/README.md @@ -129,7 +129,7 @@ var p = uniform( 10, 0.0, 1.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); var sigma = uniform( 10, 0.0, 5.0, opts ); -logEachMap( 'p: %lf, µ: %lf, σ: %lf, Q(p;µ,σ): %lf', p, mu, sigma, quantile ); +logEachMap( 'p: %0.4f, μ: %0.4f, σ: %0.4f, Q(p;μ,σ): %0.4f', p, mu, sigma, quantile ); ``` @@ -221,7 +221,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); sigma = random_uniform( 0.0, 5.0 ); y = stdlib_base_dists_anglit_quantile( p, mu, sigma ); - printf( "p: %lf, µ: %lf, σ: %lf, Q(p;µ,σ): %lf\n", p, mu, sigma, y ); + printf( "p: %lf, μ: %lf, σ: %lf, Q(p;μ,σ): %lf\n", p, mu, sigma, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/c/example.c index 722516a68731..2d7c2bce42ea 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/c/example.c @@ -37,6 +37,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); sigma = random_uniform( 0.0, 5.0 ); y = stdlib_base_dists_anglit_quantile( p, mu, sigma ); - printf( "p: %lf, µ: %lf, σ: %lf, Q(p;µ,σ): %lf\n", p, mu, sigma, y ); + printf( "p: %lf, μ: %lf, σ: %lf, Q(p;μ,σ): %lf\n", p, mu, sigma, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/index.js index c3d32769dada..7a8ed8995905 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/quantile/examples/index.js @@ -29,4 +29,4 @@ var p = uniform( 10, 0.0, 1.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); var sigma = uniform( 10, 0.0, 5.0, opts ); -logEachMap( 'p: %lf, µ: %lf, σ: %lf, Q(p;µ,σ): %lf', p, mu, sigma, quantile ); +logEachMap( 'p: %0.4f, μ: %0.4f, σ: %0.4f, Q(p;μ,σ): %0.4f', p, mu, sigma, quantile ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/README.md new file mode 100644 index 000000000000..ec5280e1efce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/README.md @@ -0,0 +1,239 @@ + + +# Skewness + +> [Anglit][anglit-distribution] distribution [skewness][skewness]. + + + +
+ +The [skewness][skewness] for an [anglit][anglit-distribution] random variable with location parameter `μ` and scale parameter `σ > 0` is + + + +```math +\mathop{\mathrm{skew}}\left( X \right) = 0 +``` + + + +
+ + + + + +
+ +## Usage + +```javascript +var skewness = require( '@stdlib/stats/base/dists/anglit/skewness' ); +``` + +#### skewness( mu, sigma ) + +Returns the [skewness][skewness] for an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma`. + +```javascript +var y = skewness( 2.0, 1.0 ); +// returns 0.0 + +y = skewness( 0.0, 1.0 ); +// returns 0.0 + +y = skewness( -1.0, 4.0 ); +// returns 0.0 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = skewness( NaN, 1.0 ); +// returns NaN + +y = skewness( 0.0, NaN ); +// returns NaN +``` + +If provided `sigma <= 0`, the function returns `NaN`. + +```javascript +var y = skewness( 0.0, 0.0 ); +// returns NaN + +y = skewness( 0.0, -1.0 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var skewness = require( '@stdlib/stats/base/dists/anglit/skewness' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.1, 20.0, opts ); + +logEachMap( 'μ: %lf, σ: %lf, skew(X;μ,σ): %lf', mu, sigma, skewness ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/anglit/skewness.h" +``` + +#### stdlib_base_dists_anglit_skewness( mu, sigma ) + +Returns the skewness for an anglit distribution with location parameter `mu` and scale parameter `sigma`. + +```c +double out = stdlib_base_dists_anglit_skewness( 0.0, 1.0 ); +// returns 0.0 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **sigma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_anglit_skewness( const double mu, const double sigma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/anglit/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_skewness( mu, sigma ); + printf( "μ: %lf, σ: %lf, skew(X;μ,σ): %lf\n", mu, sigma, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[anglit-distribution]: https://en.wikipedia.org/wiki/Anglit_distribution + +[skewness]: https://en.wikipedia.org/wiki/Skewness + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/benchmark.js new file mode 100644 index 000000000000..6a1f35c57a33 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/benchmark.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; +var skewness = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, arrayOpts ); + sigma = uniform( 100, EPS, 20.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/benchmark.native.js new file mode 100644 index 000000000000..b7f8d8357134 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/benchmark.native.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var sigma; + var mu; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, arrayOpts ); + sigma = uniform( 100, EPS, 20.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = skewness( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/c/benchmark.c new file mode 100644 index 000000000000..860be76744f9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/skewness.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "anglit-skewness" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double sigma[ 100 ]; + double mu[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -10.0, 10.0 ); + sigma[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_anglit_skewness( mu[ i%100 ], sigma[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/repl.txt new file mode 100644 index 000000000000..1e813c4234f3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( μ, σ ) + Returns the skewness of an anglit distribution with location parameter `μ` + and scale parameter `σ`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If provided `σ <= 0`, the function returns `NaN`. + + Parameters + ---------- + μ: number + Location parameter. + + σ: number + Scale parameter. + + Returns + ------- + out: number + Skewness. + + Examples + -------- + > var y = {{alias}}( 0.0, 1.0 ) + 0.0 + > y = {{alias}}( 4.0, 2.0 ) + 0.0 + > y = {{alias}}( NaN, 1.0 ) + NaN + > y = {{alias}}( 0.0, NaN ) + NaN + > y = {{alias}}( 0.0, 0.0 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/types/index.d.ts new file mode 100644 index 000000000000..f696bbd6f301 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/types/index.d.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the skewness for an anglit distribution with location parameter `mu` and scale parameter `sigma`. +* +* ## Notes +* +* - If provided `sigma <= 0`, the function returns `NaN`. +* +* @param mu - location parameter +* @param sigma - scale parameter +* @returns skewness +* +* @example +* var y = skewness( 0.0, 1.0 ); +* // returns 0.0 +* +* @example +* var y = skewness( 5.0, 2.0 ); +* // returns 0.0 +* +* @example +* var y = skewness( NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = skewness( 0.0, NaN ); +* // returns NaN +* +* @example +* var y = skewness( 0.0, 0.0 ); +* // returns NaN +*/ +declare function skewness( mu: number, sigma: number ): number; + + +// EXPORTS // + +export = skewness; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/types/test.ts new file mode 100644 index 000000000000..9cb5a6d5c502 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import skewness = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + skewness( 0, 2 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + skewness( true, 3 ); // $ExpectError + skewness( false, 2 ); // $ExpectError + skewness( '5', 1 ); // $ExpectError + skewness( [], 1 ); // $ExpectError + skewness( {}, 2 ); // $ExpectError + skewness( ( x: number ): number => x, 2 ); // $ExpectError + + skewness( 9, true ); // $ExpectError + skewness( 9, false ); // $ExpectError + skewness( 5, '5' ); // $ExpectError + skewness( 8, [] ); // $ExpectError + skewness( 9, {} ); // $ExpectError + skewness( 8, ( x: number ): number => x ); // $ExpectError + + skewness( [], true ); // $ExpectError + skewness( {}, false ); // $ExpectError + skewness( false, '5' ); // $ExpectError + skewness( {}, [] ); // $ExpectError + skewness( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + skewness(); // $ExpectError + skewness( 3 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/c/example.c new file mode 100644 index 000000000000..f83aec4ae250 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/skewness.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_skewness( mu, sigma ); + printf( "μ: %lf, σ: %lf, skew(X;μ,σ): %lf\n", mu, sigma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/index.js new file mode 100644 index 000000000000..a5f64d8089c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var skewness = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.1, 20.0, opts ); + +logEachMap( 'μ: %lf, σ: %lf, skew(X;μ,σ): %lf', mu, sigma, skewness ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "anglit", + "continuous", + "skewness", + "asymmetry", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/addon.c new file mode 100644 index 000000000000..40e533ae2e36 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/skewness.h" +#include "stdlib/math/base/napi/binary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_anglit_skewness ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/main.c new file mode 100644 index 000000000000..06104db67824 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/src/main.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/skewness.h" +#include "stdlib/math/base/assert/is_nan.h" + +/** +* Returns the skewness for an anglit distribution with location parameter `mu` and scale parameter `sigma`. +* +* @param mu location parameter +* @param sigma scale parameter +* @return skewness +* +* @example +* double y = stdlib_base_dists_anglit_skewness( 0.0, 1.0 ); +* // returns 0.0 +*/ +double stdlib_base_dists_anglit_skewness( const double mu, const double sigma ) { + if ( + stdlib_base_is_nan( mu ) || + stdlib_base_is_nan( sigma ) || + sigma <= 0.0 + ) { + return 0.0 / 0.0; // NaN + } + return 0.0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/fixtures/python/data.json new file mode 100644 index 000000000000..d90822639541 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/fixtures/python/data.json @@ -0,0 +1 @@ +{"mu":[-1.4188624938085024,-4.64177188303363,-4.89367800766936,-2.0018412226987325,-2.379785366558007,-2.754663788840509,3.2412000807028125,0.8777223461769701,3.0488677689207684,4.564461367922355,-3.5052274356012525,4.832048205916376,4.752181395850929,-3.734911692922184,-4.983297757032351,-4.936113632632738,-1.8080639730360017,3.1242444738840938,-1.1823243441526756,2.4418692725939684,2.5101004173000003,-4.503549156524278,3.8425077400738346,-3.9520416643700784,-0.8560163423205447,4.9930092313126515,-0.2643684864911924,3.8630547495119654,2.4548175711439644,-1.6394978579141242,-3.985231936272781,-3.5373334678588533,-3.1379390448168873,0.32636765269835166,-3.8804233097239136,3.417879151298557,2.8064567331065158,3.795838340893148,2.6326141145441238,-0.2217810302128438,-3.4898617897879216,-3.7758762264524046,1.9128249362350953,4.306059277139584,2.835554295618979,3.5515260391389827,-3.7084967252576186,-2.479392655636911,2.5577264774129125,2.0290991586029463,2.928922335020129,3.451962188079472,4.068379622464665,2.8036816528514947,3.403340568818546,0.8137928925271618,3.263666047179143,-2.1332497349513546,0.4913951736966604,0.6031633656045265,2.2335063360008967,0.5443426246048775,-2.4426667457826365,-4.5079479645603096,-0.06644812885587026,-4.215968763421598,1.8628682460741146,2.9337829349128697,2.1457782208943774,0.8779040605572508,4.98004429779321,3.526588814873893,-4.872049782843234,4.506045067069165,0.8655490541495192,-3.0639827406917473,4.409021102788898,3.1055377080384847,-1.5516000906386918,0.17658348292877601,1.8392098888867983,-1.6585435251068512,0.7862254885745257,0.44828956726699687,3.5211023400068715,-1.4128134141728435,-2.5124614774723564,-2.9668622035600913,3.4236063144716926,-4.616049334482643,2.859579497132396,-3.453714738465168,-4.211929277313196,2.825110703745482,-2.9009166213051474,-3.647485462379889,4.085819008839065,-1.7822637588684942,-3.564141374429697,4.073674952105579],"sigma":[4.3978887989349245,2.264782525053,3.9823436057451422,2.0199252585774343,1.0432950808993258,3.275487119233307,0.4935198821643638,4.594532084996181,4.2455717009618406,0.5693940503634609,1.6454403140045544,2.3007741994643487,0.8288039318134294,3.888222332772863,4.2204341324422625,0.8756797986717035,4.905026147500793,1.564046443532785,1.1781577270641967,1.492942325474352,2.0987595395226037,3.2309774183724844,0.39283064061814477,3.3596879913476516,1.0889826812405607,1.3127337585367493,2.8578420892817715,0.09725108498362721,2.4453535318039643,3.895111554469005,3.452042487736799,1.7128018540368088,1.2478209611215962,2.271838484211897,2.2553932886152452,4.625203778974315,3.828393371526634,0.9810255358024017,2.8247767600062987,3.603985009336138,3.389610358515392,1.0172850345233326,4.787287180090457,2.9408617658993723,2.063130902225915,2.1894385670007908,4.925650612783017,0.9148324914871353,2.6224953252336967,4.670930256320625,0.9380678739717146,4.4722475740503125,1.2925594131981133,3.8632659928903004,2.4537859614897553,1.5276395039532182,3.2091937086063784,2.3046987601627666,2.709023833026736,1.5472025880792935,0.8691533754248087,2.788960642582124,0.34228788116005104,4.173540503415632,1.1704753465408209,2.8091344195099945,2.821132534120335,4.529482589522634,0.6297862987086078,2.3638749160707837,3.4941249361508344,2.5645293469442247,3.309743071988909,1.0879138936411243,4.450766001595327,0.30427818256797245,3.1544752771758553,3.4923044965496723,0.31407022493745496,0.7697841072573064,0.9232910010078071,0.8041261673386063,0.098083765028647,0.9927143114488257,3.913004037109145,0.2324296234624612,2.2789269273911574,3.068614483172391,2.2733547439224258,0.455033197062642,1.5485099848409407,2.4198950382441735,0.8755558627832155,0.26825421256270354,3.163827108544711,1.4136087938365116,3.7376196699608517,4.109708814280007,2.1343370732297244,2.932785632192921],"expected":[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/fixtures/python/runner.py new file mode 100644 index 000000000000..be459892c66f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/fixtures/python/runner.py @@ -0,0 +1,82 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import anglit + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(loc, sigma, name): + """Generate fixture data and write to file. + + # Arguments + + * `loc`: location parameter + * `sigma`: scale parameter + * `name::str`: output filename + + # Examples + + ``` python + python> loc = np.random.rand(1000) * 10.0 - 5.0 + python> sigma = np.random.rand(1000) * 5.0 + 0.01 + python> gen(loc, sigma, "data.json") + ``` + """ + # The anglit distribution is symmetric, so its skewness is analytically `0` + # and is invariant to the location and scale parameters. Query SciPy for the + # skewness to validate inputs and keep SciPy-based fixtures. + z = np.array([anglit.stats(loc=m, scale=s, moments="s") for m, s in zip(loc, sigma)]) + + # Store data to be written to file as a dictionary: + data = { + "mu": loc.tolist(), + "sigma": sigma.tolist(), + "expected": z.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding="utf-8") as outfile: + json.dump(data, outfile) + + # Include trailing newline: + with open(filepath, "a", encoding="utf-8") as outfile: + outfile.write("\n") + + +def main(): + """Generate fixture data.""" + loc = np.random.rand(100) * 10.0 - 5.0 + sigma = np.random.rand(100) * 5.0 + 0.01 + gen(loc, sigma, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/test.js new file mode 100644 index 000000000000..ba29ffa2920b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/test.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var skewness = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof skewness, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = skewness( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = skewness( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', function test( t ) { + var y; + + y = skewness( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the skewness of an anglit distribution', function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < mu.length; i++ ) { + y = skewness( mu[i], sigma[i] ); + t.strictEqual( y, expected[i], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/test.native.js new file mode 100644 index 000000000000..c51884ee9501 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/skewness/test/test.native.js @@ -0,0 +1,99 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// VARIABLES // + +var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( skewness instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof skewness, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = skewness( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = skewness( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = skewness( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = skewness( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the skewness of an anglit distribution', opts, function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < mu.length; i++ ) { + y = skewness( mu[i], sigma[i] ); + t.strictEqual( y, expected[i], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/README.md new file mode 100644 index 000000000000..a856eebb4f53 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/README.md @@ -0,0 +1,241 @@ + + +# Standard Deviation + +> [Anglit][anglit-distribution] distribution [standard deviation][stdev]. + + + +
+ +The [standard deviation][stdev] for an [anglit][anglit-distribution] random variable with location parameter `mu` and scale parameter `sigma` is + + + +```math +\mathop{\mathrm{SD}}(X) = \sigma \sqrt{\left({\frac{\pi^{2}}{16}}-\frac{1}{2}\right)} +``` + + + + + +
+ + + + + +
+ +## Usage + +```javascript +var stdev = require( '@stdlib/stats/base/dists/anglit/stdev' ); +``` + +#### stdev( mu, sigma ) + +Returns the [standard deviation][stdev] for an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma`. + +```javascript +var y = stdev( 0.0, 1.0 ); +// returns ~0.342 + +y = stdev( 2.0, 4.0 ); +// returns ~1.367 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = stdev( NaN, 1.0 ); +// returns NaN + +y = stdev( 0.0, NaN ); +// returns NaN +``` + +If provided `sigma <= 0`, the function returns `NaN`. + +```javascript +var y = stdev( 0.0, 0.0 ); +// returns NaN + +y = stdev( 0.0, -1.0 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var stdev = require( '@stdlib/stats/base/dists/anglit/stdev' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -50.0, 50.0, opts ); +var sigma = uniform( 10, 0.1, 20.0, opts ); + +logEachMap( 'μ: %0.4f, σ: %0.4f, SD(X;μ,σ): %0.4f', mu, sigma, stdev ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/anglit/stdev.h" +``` + +#### stdlib_base_dists_anglit_stdev( mu, sigma ) + +Returns the [standard deviation][stdev] for an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma`. + +```c +double out = stdlib_base_dists_anglit_stdev( 0.0, 1.0 ); +// returns ~0.342 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **sigma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_anglit_stdev( const double mu, const double sigma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/anglit/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_stdev( mu, sigma ); + printf( "μ: %lf, σ: %lf, SD(X;μ,σ): %lf\n", mu, sigma, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[anglit-distribution]: https://en.wikipedia.org/wiki/Anglit_distribution + +[stdev]: https://en.wikipedia.org/wiki/Standard_deviation + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/benchmark.js new file mode 100644 index 000000000000..251a861b9e72 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/benchmark.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; +var stdev = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var sigma; + var opts; + var mu; + var y; + var i; + + opts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, opts ); + sigma = uniform( 100, 0.1, 20.0, opts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/benchmark.native.js new file mode 100644 index 000000000000..a6c0bdfb6363 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/benchmark.native.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var sigma; + var opts; + var mu; + var y; + var i; + + opts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, opts ); + sigma = uniform( 100, 0.1, 20.0, opts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/c/benchmark.c new file mode 100644 index 000000000000..12a5c6e97d27 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/benchmark/c/benchmark.c @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/stdev.h" +#include +#include +#include +#include +#include + +#define NAME "anglit-stdev" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double sigma[ 100 ]; + double mu[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + sigma[ i ] = random_uniform( 0.1, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_anglit_stdev( mu[ i%100 ], sigma[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/img/equation_anglit_stdev.svg b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/img/equation_anglit_stdev.svg new file mode 100644 index 000000000000..2fb1e731029a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/img/equation_anglit_stdev.svg @@ -0,0 +1,58 @@ + +upper S upper D left-parenthesis upper X right-parenthesis equals sigma StartRoot left-parenthesis StartFraction pi squared Over 16 EndFraction minus one half right-parenthesis EndRoot + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/repl.txt new file mode 100644 index 000000000000..9052c9f6446a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( μ, σ ) + Returns the standard deviation of an anglit distribution with location + parameter `μ` and scale parameter `σ`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If provided `σ <= 0`, the function returns `NaN`. + + Parameters + ---------- + μ: number + Location parameter. + + σ: number + Scale parameter. + + Returns + ------- + out: number + Standard deviation. + + Examples + -------- + > var y = {{alias}}( 0.0, 1.0 ) + ~0.342 + > y = {{alias}}( 2.0, 4.0 ) + ~1.367 + > y = {{alias}}( NaN, 1.0 ) + NaN + > y = {{alias}}( 0.0, NaN ) + NaN + > y = {{alias}}( 0.0, 0.0 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/types/index.d.ts new file mode 100644 index 000000000000..42922a68f3f5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/types/index.d.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the standard deviation for an anglit distribution with location parameter `mu` and scale parameter `sigma`. +* +* ## Notes +* +* - If provided `sigma <= 0`, the function returns `NaN`. +* +* @param mu - location parameter +* @param sigma - scale parameter +* @returns standard deviation +* +* @example +* var y = stdev( 0.0, 1.0 ); +* // returns ~0.342 +* +* @example +* var y = stdev( 2.0, 4.0 ); +* // returns ~1.367 +* +* @example +* var y = stdev( NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = stdev( 0.0, NaN ); +* // returns NaN +* +* @example +* var y = stdev( 0.0, 0.0 ); +* // returns NaN +*/ +declare function stdev( mu: number, sigma: number ): number; + + +// EXPORTS // + +export = stdev; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/types/test.ts new file mode 100644 index 000000000000..86b13ddc84a7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import stdev = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + stdev( 0, 2 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + stdev( true, 3 ); // $ExpectError + stdev( false, 2 ); // $ExpectError + stdev( '5', 1 ); // $ExpectError + stdev( [], 1 ); // $ExpectError + stdev( {}, 2 ); // $ExpectError + stdev( ( x: number ): number => x, 2 ); // $ExpectError + + stdev( 9, true ); // $ExpectError + stdev( 9, false ); // $ExpectError + stdev( 5, '5' ); // $ExpectError + stdev( 8, [] ); // $ExpectError + stdev( 9, {} ); // $ExpectError + stdev( 8, ( x: number ): number => x ); // $ExpectError + + stdev( [], true ); // $ExpectError + stdev( {}, false ); // $ExpectError + stdev( false, '5' ); // $ExpectError + stdev( {}, [] ); // $ExpectError + stdev( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + stdev(); // $ExpectError + stdev( 3 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/c/example.c new file mode 100644 index 000000000000..e013713b8d31 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/stdev.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + mu = random_uniform( -50.0, 50.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_stdev( mu, sigma ); + printf( "μ: %lf, σ: %lf, SD(X;μ,σ): %lf\n", mu, sigma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/index.js new file mode 100644 index 000000000000..82a670328598 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var stdev = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var sigma = uniform( 10, 0.1, 20.0, opts ); +var mu = uniform( 10, -50.0, 50.0, opts ); + +logEachMap( 'μ: %0.4f, σ: %0.4f, SD(X;μ,σ): %0.4f', mu, sigma, stdev ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "continuous", + "stdev", + "std", + "standard", + "deviation", + "dispersion", + "spread", + "anglit", + "univariate" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/addon.c new file mode 100644 index 000000000000..459f2968d102 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/stdev.h" +#include "stdlib/math/base/napi/binary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_anglit_stdev ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/main.c new file mode 100644 index 000000000000..d1d1ffd4e978 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/src/main.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/stdev.h" +#include "stdlib/math/base/assert/is_nan.h" + +static const double STDEV_CONST = 0.3418336950449515; // sqrt( (π²/16) - (1/2) ) + +/** +* Returns the standard deviation for an anglit distribution with location parameter `mu` and scale parameter `sigma`. +* +* @param mu location parameter +* @param sigma scale parameter +* @return standard deviation +* +* @example +* double y = stdlib_base_dists_anglit_stdev( 0.0, 1.0 ); +* // returns ~0.342 +*/ +double stdlib_base_dists_anglit_stdev( const double mu, const double sigma ) { + if ( + stdlib_base_is_nan( mu ) || + stdlib_base_is_nan( sigma ) || + sigma <= 0.0 + ) { + return 0.0/0.0; // NaN + } + return sigma * STDEV_CONST; +} diff --git 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a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/fixtures/python/runner.py new file mode 100644 index 000000000000..898b364fa6f1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/fixtures/python/runner.py @@ -0,0 +1,76 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +from numpy.random import rand +from scipy.stats import anglit + + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(loc, scale, name): + """Generate fixture data and write to file. + + # Arguments + + * `loc`: location parameter (mu) + * `scale`: scale parameter (sigma) + * `name::str`: output filename + + # Examples + + ``` python + python> loc = rand(1000) * 10.0 - 5.0 + python> scale = rand(1000) * 10.0 + 1.0 + python> gen(loc, scale, './data.json') + ``` + """ + y = anglit.std(loc=loc, scale=scale) + + # Store data to be written to file as a dictionary: + data = { + "mu": loc.tolist(), + "sigma": scale.tolist(), + "expected": y.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding="utf-8") as outfile: + json.dump(data, outfile) + + +def main(): + """Generate fixture data.""" + loc = (rand(1000) * 10.0) - 5.0 + scale = (rand(1000) * 10.0) + 1.0 + gen(loc, scale, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/test.js new file mode 100644 index 000000000000..82f22b191bf1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/test.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var stdev = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof stdev, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = stdev( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = stdev( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = stdev( NaN, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', function test( t ) { + var y; + + y = stdev( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the standard deviation of an anglit distribution', function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < mu.length; i++ ) { + y = stdev( mu[i], sigma[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/test.native.js new file mode 100644 index 000000000000..2ec5dcec5e84 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/stdev/test/test.native.js @@ -0,0 +1,100 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof stdev, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = stdev( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = stdev( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = stdev( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = stdev( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the standard deviation of an anglit distribution', opts, function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < mu.length; i++ ) { + y = stdev( mu[i], sigma[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/README.md new file mode 100644 index 000000000000..e1b39f718cc8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/README.md @@ -0,0 +1,252 @@ + + +# Variance + +> [Anglit][anglit-distribution] distribution [variance][variance]. + + + +
+ +The [variance][variance] for an [anglit][anglit-distribution] random variable with location parameter `mu` and scale parameter `sigma` is + + + +```math +\mathop{\mathrm{Var}}\left( X \right) = \sigma^{2}\left({\frac{\pi^{2}}{16}}-{\frac{1}{2}}\right) +``` + + + + + +
+ + + + + +
+ +## Usage + +```javascript +var variance = require( '@stdlib/stats/base/dists/anglit/variance' ); +``` + +#### variance( mu, sigma ) + +Returns the [variance][variance] for an [anglit][anglit-distribution] distribution with location parameter `mu` and scale parameter `sigma`. + +```javascript +var y = variance( 0.0, 1.0 ); +// returns ~0.117 + +y = variance( 1.0, 2.0 ); +// returns ~0.467 + +y = variance( -3.0, 4.0 ); +// returns ~1.870 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = variance( NaN, 1.0 ); +// returns NaN + +y = variance( 0.0, NaN ); +// returns NaN +``` + +If provided `sigma <= 0`, the function returns `NaN`. + +```javascript +var y = variance( 0.0, 0.0 ); +// returns NaN + +y = variance( 0.0, -1.0 ); +// returns NaN +``` + +
+ + + + + +
+ +
+ + + + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var variance = require( '@stdlib/stats/base/dists/anglit/variance' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.1, 20.0, opts ); + +logEachMap( 'μ: %0.4f, σ: %0.4f, Var(X;μ,σ): %0.4f', mu, sigma, variance ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/anglit/variance.h" +``` + +#### stdlib_base_dists_anglit_variance( mu, sigma ) + +Returns the variance for an anglit distribution with location `mu` and scale `sigma`. + +```c +double out = stdlib_base_dists_anglit_variance( 0.0, 1.0 ); +// returns ~0.117 +``` + +The function accepts the following arguments: + +- **mu**: `[in] double` location parameter. +- **sigma**: `[in] double` scale parameter. + +```c +double stdlib_base_dists_anglit_variance( const double mu, const double sigma ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/anglit/variance.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_variance( mu, sigma ); + printf( "μ: %lf, σ: %lf, Var(X;μ,σ): %lf\n", mu, sigma, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + + + + +
+ +[variance]: https://en.wikipedia.org/wiki/Variance + +[anglit-distribution]: https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.anglit.html + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/benchmark.js new file mode 100644 index 000000000000..6fc9ed7b3bb5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/benchmark.js @@ -0,0 +1,59 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var pkg = require( './../package.json' ).name; +var variance = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var sigma; + var opts; + var mu; + var y; + var i; + + opts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, opts ); + sigma = uniform( 100, EPS, 20.0, opts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = variance( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/benchmark.native.js new file mode 100644 index 000000000000..f22f7628b546 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/benchmark.native.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var sigma; + var opts; + var mu; + var y; + var i; + + opts = { + 'dtype': 'float64' + }; + mu = uniform( 100, -50.0, 50.0, opts ); + sigma = uniform( 100, EPS, 20.0, opts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = variance( mu[ i % mu.length ], sigma[ i % sigma.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/c/benchmark.c new file mode 100644 index 000000000000..513cf757e201 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/variance.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "anglit-variance" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double sigma[ 100 ]; + double mu[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + mu[ i ] = random_uniform( -50.0, 50.0 ); + sigma[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_anglit_variance( mu[ i % 100 ], sigma[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/img/equation_anglit_variance.svg b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/img/equation_anglit_variance.svg new file mode 100644 index 000000000000..7ee23258d8f4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/img/equation_anglit_variance.svg @@ -0,0 +1,60 @@ + +normal upper V times normal a times normal r left-parenthesis upper X right-parenthesis equals sigma squared left-parenthesis StartFraction pi squared Over 16 EndFraction minus one half right-parenthesis + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/repl.txt new file mode 100644 index 000000000000..2aae531748c0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}( μ, σ ) + Returns the variance of an anglit distribution with location parameter `μ` + and scale parameter `σ`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If provided `σ <= 0`, the function returns `NaN`. + + Parameters + ---------- + μ: number + Location parameter. + + σ: number + Scale parameter. + + Returns + ------- + out: number + Variance. + + Examples + -------- + > var y = {{alias}}( 0.0, 1.0 ) + ~0.117 + > y = {{alias}}( 4.0, 2.0 ) + ~0.467 + > y = {{alias}}( NaN, 1.0 ) + NaN + > y = {{alias}}( 0.0, NaN ) + NaN + > y = {{alias}}( 0.0, 0.0 ) + NaN + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/types/index.d.ts new file mode 100644 index 000000000000..66db0d2a2e5c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/types/index.d.ts @@ -0,0 +1,57 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Returns the variance for an anglit distribution with location `mu` and scale `sigma`. +* +* ## Notes +* +* - If `sigma <= 0`, the function returns `NaN`. +* +* @param mu - location parameter +* @param sigma - scale parameter +* @returns variance +* +* @example +* var y = variance( 0.0, 1.0 ); +* // returns ~0.117 +* +* @example +* var y = variance( 2.0, 4.0 ); +* // returns ~1.870 +* +* @example +* var y = variance( NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = variance( 0.0, NaN ); +* // returns NaN +* +* @example +* var y = variance( 0.0, 0.0 ); +* // returns NaN +*/ +declare function variance( mu: number, sigma: number ): number; + + +// EXPORTS // + +export = variance; diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/types/test.ts new file mode 100644 index 000000000000..9e097321a57d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/docs/types/test.ts @@ -0,0 +1,56 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import variance = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + variance( 0, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than two numbers... +{ + variance( true, 1 ); // $ExpectError + variance( false, 1 ); // $ExpectError + variance( '5', 1 ); // $ExpectError + variance( [], 1 ); // $ExpectError + variance( {}, 1 ); // $ExpectError + variance( ( x: number ): number => x, 1 ); // $ExpectError + + variance( 1, true ); // $ExpectError + variance( 1, false ); // $ExpectError + variance( 1, '5' ); // $ExpectError + variance( 1, [] ); // $ExpectError + variance( 1, {} ); // $ExpectError + variance( 1, ( x: number ): number => x ); // $ExpectError + + variance( [], true ); // $ExpectError + variance( {}, false ); // $ExpectError + variance( false, '5' ); // $ExpectError + variance( {}, [] ); // $ExpectError + variance( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided insufficient arguments... +{ + variance(); // $ExpectError + variance( 1 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/c/example.c new file mode 100644 index 000000000000..5df9cefad8b7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/c/example.c @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/variance.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double sigma; + double mu; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + mu = random_uniform( -5.0, 5.0 ); + sigma = random_uniform( 0.1, 20.0 ); + y = stdlib_base_dists_anglit_variance( mu, sigma ); + printf( "μ: %lf, σ: %lf, Var(X;μ,σ): %lf\n", mu, sigma, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/index.js new file mode 100644 index 000000000000..905e9d2dcd91 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/examples/index.js @@ -0,0 +1,31 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var variance = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var mu = uniform( 10, -5.0, 5.0, opts ); +var sigma = uniform( 10, 0.1, 20.0, opts ); + +logEachMap( 'μ: %0.4f, σ: %0.4f, Var(X;μ,σ): %0.4f', mu, sigma, variance ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "anglit", + "continuous", + "symmetric", + "variance", + "dispersion", + "spread", + "univariate", + "location-scale" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/addon.c new file mode 100644 index 000000000000..4bd9600ced3e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/variance.h" +#include "stdlib/math/base/napi/binary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_anglit_variance ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/main.c new file mode 100644 index 000000000000..388e8405e7ca --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/src/main.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/anglit/variance.h" +#include "stdlib/math/base/assert/is_nan.h" + +// (π^2/16) - (1/2): +static const double scalar = 0.11685027506808487; + +/** +* Returns the variance for an anglit distribution with location `mu` and scale `sigma`. +* +* @param mu location parameter +* @param sigma scale parameter +* @return variance +* +* @example +* double y = stdlib_base_dists_anglit_variance( 0.0, 1.0 ); +* // returns ~0.117 +*/ +double stdlib_base_dists_anglit_variance( const double mu, const double sigma ) { + if ( + stdlib_base_is_nan( mu ) || + stdlib_base_is_nan( sigma ) || + sigma <= 0.0 + ) { + return 0.0 / 0.0; // NaN + } + return ( sigma * sigma ) * scalar; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/fixtures/python/data.json new file mode 100644 index 000000000000..1b1362f75313 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/fixtures/python/data.json @@ -0,0 +1 @@ +{"mu": [-1.8072314920996657, 2.2893311548130315, -0.6425607088456973, 4.82083944273613, 3.609367929675786, 1.9146508101359032, 1.7129910712524445, 1.604222087336474, -2.3597192800139366, 0.38075478974188925, 3.8059237003784574, 0.9658309446178945, 0.5501377477879963, -0.36753413470692475, 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10.395248555814918, 3.615659696386154, 0.3517105567456594, 7.807190416268505, 0.3010955210548312, 4.133101138790833, 0.06638730191325716, 11.460229319245867, 0.15186417893841325, 0.3015718216769362, 1.9473574435448215, 3.9947023971422615, 0.7631005619015759, 1.087900024983495]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/fixtures/python/runner.py new file mode 100644 index 000000000000..a783de0a5a07 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/fixtures/python/runner.py @@ -0,0 +1,75 @@ +#!/usr/bin/env python +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +from numpy.random import rand +from scipy.stats import anglit + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(mean, scale, name): + """Generate fixture data and write to JSON. + + # Arguments + + * `mean`: location parameter values (mu) + * `scale`: scale parameter values (sigma) + * `name::str`: output filename + + # Examples + + ``` python + python> mean = rand(1000) * 10.0 - 5.0 + python> scale = (rand(1000) * 10.0) + 0.1 + python> gen(mean, scale, "data.json") + ``` + """ + y = anglit.var(loc=mean, scale=scale) + + # Store data to be written to file as a dictionary: + data = { + "mu": mean.tolist(), + "sigma": scale.tolist(), + "expected": y.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding="utf-8") as outfile: + json.dump(data, outfile) + + +def main(): + """Generate fixture data.""" + mean = (rand(1000) * 10.0) - 5.0 + scale = (rand(1000) * 10.0) + 0.1 + gen(mean, scale, "data.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/test.js new file mode 100644 index 000000000000..1ba8774042e2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/test.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var variance = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof variance, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = variance( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = variance( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = variance( NaN, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', function test( t ) { + var y; + + y = variance( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the variance of an anglit distribution', function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < expected.length; i++ ) { + y = variance( mu[i], sigma[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 2 ), true, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/test.native.js new file mode 100644 index 000000000000..87a781fb2fe1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/anglit/variance/test/test.native.js @@ -0,0 +1,102 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// VARIABLES // + +var variance = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( variance instanceof Error ) +}; + + +// FIXTURES // + +var data = require( './fixtures/python/data.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof variance, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = variance( NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = variance( 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = variance( NaN, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `sigma`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = variance( 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = variance( NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the variance of an anglit distribution', opts, function test( t ) { + var expected; + var sigma; + var mu; + var y; + var i; + + expected = data.expected; + mu = data.mu; + sigma = data.sigma; + for ( i = 0; i < expected.length; i++ ) { + y = variance( mu[i], sigma[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 2 ), true, 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/README.md index 22862e4fb83d..024fb6ed7808 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/README.md @@ -160,6 +160,113 @@ logEachMap( 'x: %0.4f, α: %0.4f, β: %0.4f, F(x;α,β): %0.4f', x, alpha, beta, + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/beta/cdf.h" +``` + +#### stdlib_base_dists_beta_cdf( x, alpha, beta ) + +Evaluates the [cumulative distribution function][cdf] (CDF) for a [beta][beta-distribution] distribution with first shpae parameter `alpha`and second shape parameter `beta` at a value `x`. + +```c +double y = stdlib_base_dists_beta_cdf( 0.5, 1.0, 1.0 ); +// returns 0.5 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **alpha**: `[in] double` first shape parameter. +- **beta**: `[in] double` second shape parameter. + +```c +double stdlib_base_dists_beta_cdf( const double x, const double alpha, const double beta ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/beta/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double beta; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( 0.0, 1.0 ); + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 ); + y = stdlib_base_dists_beta_cdf( x, alpha, beta ); + printf( "x: %lf, α: %lf, β: %lf, F(x;α,β): %lf\n", x, alpha, beta, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..57e21ffb123c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tryRequire = require( '@stdlib/utils/try-require' ); +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var alpha; + var beta; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + alpha = uniform( 100, EPS, 100.0, arrayOpts ); + beta = uniform( 100, EPS, 100.0, arrayOpts ); + x = uniform( 100, EPS, 2.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], alpha[ i % alpha.length ], beta[ i % beta.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..87f3696f6ac2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/beta/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "beta-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double alpha[ 100 ]; + double beta[ 100 ]; + double x[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + alpha[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + beta[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 2.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_beta_cdf( x[ i % 100 ], alpha[ i % 100 ], beta[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/examples/c/example.c new file mode 100644 index 000000000000..a1df306f3f88 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/beta/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double alpha; + double beta; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( 0.0, 1.0 ); + alpha = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 ); + beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 ); + y = stdlib_base_dists_beta_cdf( x, alpha, beta ); + printf( "x: %lf, α: %lf, β: %lf, F(x;α,β): %lf\n", x, alpha, beta, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + '= 1.0 ) { + return 1.0; + } + return stdlib_base_betainc( x, alpha, beta, true, false ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.cdf.js b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.cdf.js index 46e7006ffc7a..020c40bb8411 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.cdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.cdf.js @@ -22,10 +22,9 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var cdf = require( './../lib' ); @@ -142,10 +141,8 @@ tape( 'if provided a nonpositive `beta`, the function returns `NaN`', function t tape( 'the function evaluates the cdf for `x` given large `alpha` and `beta`', function test( t ) { var expected; - var delta; var alpha; var beta; - var tol; var x; var y; var i; @@ -159,9 +156,7 @@ tape( 'the function evaluates the cdf for `x` given large `alpha` and `beta`', f if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 140.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 200 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); @@ -169,10 +164,8 @@ tape( 'the function evaluates the cdf for `x` given large `alpha` and `beta`', f tape( 'the function evaluates the cdf for `x` given large `alpha`', function test( t ) { var expected; - var delta; var alpha; var beta; - var tol; var i; var x; var y; @@ -186,9 +179,7 @@ tape( 'the function evaluates the cdf for `x` given large `alpha`', function tes if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 80.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 140 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); @@ -196,10 +187,8 @@ tape( 'the function evaluates the cdf for `x` given large `alpha`', function tes tape( 'the function evaluates the cdf for `x` given large `beta`', function test( t ) { var expected; - var delta; var alpha; var beta; - var tol; var i; var x; var y; @@ -213,9 +202,7 @@ tape( 'the function evaluates the cdf for `x` given large `beta`', function test if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 20.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 30 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.factory.js index 92a277abf8bd..ac0cd3db277d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.factory.js @@ -22,10 +22,9 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var factory = require( './../lib/factory.js' ); @@ -194,11 +193,9 @@ tape( 'if provided a nonpositive `alpha`, the created function always returns `N tape( 'the created function evaluates the cdf for `x` given large `alpha` and `beta`', function test( t ) { var expected; - var delta; var alpha; var beta; var cdf; - var tol; var i; var x; var y; @@ -213,9 +210,7 @@ tape( 'the created function evaluates the cdf for `x` given large `alpha` and `b if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 140.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 200 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); @@ -223,11 +218,9 @@ tape( 'the created function evaluates the cdf for `x` given large `alpha` and `b tape( 'the created function evaluates the cdf for `x` given large `alpha`', function test( t ) { var expected; - var delta; var alpha; var beta; var cdf; - var tol; var i; var x; var y; @@ -242,9 +235,7 @@ tape( 'the created function evaluates the cdf for `x` given large `alpha`', func if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 80.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 200 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); @@ -252,11 +243,9 @@ tape( 'the created function evaluates the cdf for `x` given large `alpha`', func tape( 'the created function evaluates the cdf for `x` given large `beta`', function test( t ) { var expected; - var delta; var alpha; var beta; var cdf; - var tol; var i; var x; var y; @@ -271,9 +260,7 @@ tape( 'the created function evaluates the cdf for `x` given large `beta`', funct if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 20.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. alpha: '+alpha[i]+'. beta: '+beta[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 30 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.native.js new file mode 100644 index 000000000000..fc356d2c757b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/cdf/test/test.native.js @@ -0,0 +1,218 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// FIXTURES // + +var largeAlpha = require( './fixtures/julia/large_alpha.json' ); +var largeBeta = require( './fixtures/julia/large_beta.json' ); +var bothLarge = require( './fixtures/julia/both_large.json' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = cdf( NaN, 0.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = cdf( 0.0, NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = cdf( 0.0, 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a number greater than or equal to one for `x` and a finite `alpha` and `beta`, the function returns `1`', opts, function test( t ) { + var y = cdf( PINF, 0.5, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( 100.0, 0.5, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( 10.0, 0.5, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( 1.0, 0.5, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a number less than or equal to zero for `x` and a finite `alpha` and `beta`, the function returns `0`', opts, function test( t ) { + var y = cdf( NINF, 0.5, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + y = cdf( -100.0, 0.5, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + y = cdf( -1.0, 0.5, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + y = cdf( 0.0, 0.5, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a nonpositive `alpha`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 0.0, 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, -1.0, 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, -1.0, 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, PINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a nonpositive `beta`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 2.0, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 2.0, -1/0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, 1.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large `alpha` and `beta`', opts, function test( t ) { + var expected; + var alpha; + var beta; + var x; + var y; + var i; + + expected = bothLarge.expected; + x = bothLarge.x; + alpha = bothLarge.alpha; + beta = bothLarge.beta; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], alpha[i], beta[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.strictEqual( isAlmostSameValue( y, expected[i], 200 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large `alpha`', opts, function test( t ) { + var expected; + var alpha; + var beta; + var i; + var x; + var y; + + expected = largeAlpha.expected; + x = largeAlpha.x; + alpha = largeAlpha.alpha; + beta = largeAlpha.beta; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], alpha[i], beta[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.strictEqual( isAlmostSameValue( y, expected[i], 140 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large `beta`', opts, function test( t ) { + var expected; + var alpha; + var beta; + var i; + var x; + var y; + + expected = largeBeta.expected; + x = largeBeta.x; + alpha = largeBeta.alpha; + beta = largeBeta.beta; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], alpha[i], beta[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.strictEqual( isAlmostSameValue( y, expected[i], 50 ), true, 'x: '+x[i]+', alpha: '+alpha[i]+', beta: '+beta[i]+', y: '+y+', expected: '+expected[i] ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/entropy/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/entropy/lib/main.js index a63daaf47852..c6189c4c1281 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/entropy/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/entropy/lib/main.js @@ -20,6 +20,7 @@ // MODULES // +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var digamma = require( '@stdlib/math/base/special/digamma' ); var betaln = require( '@stdlib/math/base/special/betaln' ); @@ -63,7 +64,12 @@ var betaln = require( '@stdlib/math/base/special/betaln' ); */ function entropy( alpha, beta ) { var out; - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } out = betaln( alpha, beta ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/lib/main.js index 817951c702d6..69d7c054f490 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/kurtosis/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -61,7 +66,12 @@ function kurtosis( alpha, beta ) { var apb; var out; - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } axb = alpha * beta; diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/lib/main.js index e91e3fe0fd78..e876b8a9f30c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mean/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mean/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -56,7 +61,12 @@ * // returns NaN */ function mean( alpha, beta ) { - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } return alpha / ( alpha + beta ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/median/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/median/lib/main.js index 6e53f44e76a9..25a84477e402 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/median/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/median/lib/main.js @@ -20,6 +20,7 @@ // MODULES // +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var betaincinv = require( '@stdlib/math/base/special/betaincinv' ); @@ -61,7 +62,12 @@ var betaincinv = require( '@stdlib/math/base/special/betaincinv' ); * // returns NaN */ function median( alpha, beta ) { - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } return betaincinv( 0.5, alpha, beta ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/lib/main.js index 234b8aabab65..8dea53b3cffc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/mode/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mode/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -56,7 +61,12 @@ * // returns NaN */ function mode( alpha, beta ) { - if ( alpha <= 1.0 || beta <= 1.0 ) { + if ( + isnan( alpha ) || + alpha <= 1.0 || + isnan( beta ) || + beta <= 1.0 + ) { return NaN; } return ( alpha-1.0 ) / ( alpha+beta-2.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/lib/main.js index 8ee91cf7d727..56756428b2ea 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/skewness/lib/main.js @@ -20,6 +20,7 @@ // MODULES // +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); @@ -63,7 +64,12 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); function skewness( alpha, beta ) { var out; var ab; - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } ab = alpha + beta; diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/lib/main.js index 1d6261ba1e17..867b2fb21ea8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/stdev/lib/main.js @@ -20,6 +20,7 @@ // MODULES // +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); @@ -63,7 +64,12 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); function stdev( alpha, beta ) { var apb; var out; - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } apb = alpha + beta; diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/lib/main.js index 0206d45c817c..72cc8500f5f1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/beta/variance/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/beta/variance/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -58,7 +63,12 @@ function variance( alpha, beta ) { var apb; var out; - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } apb = alpha + beta; diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/README.md b/lib/node_modules/@stdlib/stats/base/dists/betaprime/README.md index c692e5c45a54..fc2e7fce2832 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/README.md @@ -72,7 +72,7 @@ The namespace contains the following functions for calculating distribution prop -The namespace contains a constructor function for creating a [betaprime][betaprime-distribution] distribution object. +The namespace contains a constructor function for creating a [beta prime][betaprime-distribution] distribution object. diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/factory.js index 550766f68cfd..0ad2e9d7b822 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/factory.js @@ -76,7 +76,7 @@ function factory( alpha, beta ) { return NaN; } if ( x <= 0.0 ) { - // Support of the BetaPrime distribution: (0,∞) + // Support of the beta prime distribution: (0,∞) return NINF; } out = ( alpha-1.0 ) * ln( x ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/main.js index 3bfa0d3b3f92..72e11be3a76f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/lib/main.js @@ -90,7 +90,7 @@ function logpdf( x, alpha, beta ) { return NaN; } if ( x <= 0.0 ) { - // Support of the BetaPrime distribution: (0,∞) + // Support of the beta prime distribution: (0,∞) return NINF; } out = ( alpha-1.0 ) * ln( x ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/src/main.c index 3a40cbe11c3c..1bda2b4b87f2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/src/main.c +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/src/main.c @@ -46,7 +46,7 @@ double stdlib_base_dists_betaprime_logpdf( const double x, const double alpha, c return 0.0 / 0.0; } if ( x <= 0.0 ) { - // Support of the BetaPrime distribution: (0,∞) + // Support of the beta prime distribution: (0,∞) return STDLIB_CONSTANT_FLOAT64_NINF; } out = ( alpha-1.0 ) * stdlib_base_ln( x ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/mean/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/mean/lib/main.js index 7b47b8788360..8b4ca60daad4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/mean/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/mean/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -60,7 +65,12 @@ * // returns NaN */ function mean( alpha, beta ) { - if ( alpha <= 0.0 || beta <= 1.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 1.0 + ) { return NaN; } return alpha / ( beta - 1.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/README.md index 74038a6be888..6982d1827388 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/README.md @@ -28,14 +28,14 @@ limitations under the License. The [mode][mode] for a [beta prime][betaprime-distribution] random variable is - + ```math \mathop{\mathrm{mode}}(X) = \begin{cases}\frac{\alpha-1}{\beta+1} & \text{ if } \alpha \ge 1 \\ 0 & \text{ otherwise }\end{cases} ``` - diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/lib/main.js index df4cbd80ac3c..635f61780012 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/mode/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -60,7 +65,12 @@ * // returns NaN */ function mode( alpha, beta ) { - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } if ( alpha < 1.0 ) { diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/betaprime/test/test.js index 88dce7fd89a2..47527e7854a3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/test/test.js @@ -33,7 +33,7 @@ tape( 'main export is an object', function test( t ) { t.end(); }); -tape( 'the exported object contains betaprime distribution functions', function test( t ) { +tape( 'the exported object contains beta prime distribution functions', function test( t ) { var keys = objectKeys( betaprime ); t.strictEqual( keys.length > 0, true, 'has keys' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/docs/types/test.ts index 40a47bd4cdac..a15fe03f4139 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/docs/types/test.ts +++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/variance/docs/types/test.ts @@ -16,41 +16,41 @@ * limitations under the License. */ -import stdev = require( './index' ); +import variance = require( './index' ); // TESTS // // The function returns a number... { - stdev( 8, 5 ); // $ExpectType number + variance( 8, 5 ); // $ExpectType number } // The compiler throws an error if the function is provided values other than two numbers... { - stdev( true, 3 ); // $ExpectError - stdev( false, 2 ); // $ExpectError - stdev( '5', 1 ); // $ExpectError - stdev( [], 1 ); // $ExpectError - stdev( {}, 2 ); // $ExpectError - stdev( ( x: number ): number => x, 2 ); // $ExpectError - - stdev( 9, true ); // $ExpectError - stdev( 9, false ); // $ExpectError - stdev( 5, '5' ); // $ExpectError - stdev( 8, [] ); // $ExpectError - stdev( 9, {} ); // $ExpectError - stdev( 8, ( x: number ): number => x ); // $ExpectError - - stdev( [], true ); // $ExpectError - stdev( {}, false ); // $ExpectError - stdev( false, '5' ); // $ExpectError - stdev( {}, [] ); // $ExpectError - stdev( '5', ( x: number ): number => x ); // $ExpectError + variance( true, 3 ); // $ExpectError + variance( false, 2 ); // $ExpectError + variance( '5', 1 ); // $ExpectError + variance( [], 1 ); // $ExpectError + variance( {}, 2 ); // $ExpectError + variance( ( x: number ): number => x, 2 ); // $ExpectError + + variance( 9, true ); // $ExpectError + variance( 9, false ); // $ExpectError + variance( 5, '5' ); // $ExpectError + variance( 8, [] ); // $ExpectError + variance( 9, {} ); // $ExpectError + variance( 8, ( x: number ): number => x ); // $ExpectError + + variance( [], true ); // $ExpectError + variance( {}, false ); // $ExpectError + variance( false, '5' ); // $ExpectError + variance( {}, [] ); // $ExpectError + variance( '5', ( x: number ): number => x ); // $ExpectError } // The compiler throws an error if the function is provided insufficient arguments... { - stdev(); // $ExpectError - stdev( 3 ); // $ExpectError + variance(); // $ExpectError + variance( 3 ); // $ExpectError } diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/README.md index 723120099d7d..f592b3bcf785 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/README.md @@ -163,6 +163,113 @@ logEachMap( 'x: %0.4f, n: %0.4f, p: %0.4f, F(x;n,p): %0.4f', x, n, p, cdf ); + + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/binomial/cdf.h" +``` + +#### stdlib_base_dists_binomial_cdf( x, n, p ) + +Evaluates the [cumulative distribution function][cdf] for a [binomial][binomial-distribution] distribution with number of trials `n` and success probability `p`. + +```c +double out = stdlib_base_dists_binomial_cdf( 3.0, 20.0, 0.2 ); +// returns ~0.411 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **n**: `[in] double` number of trials. +- **p**: `[in] double` success probability. + +```c +double stdlib_base_dists_binomial_cdf( const double x, const double n, const double p ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/binomial/cdf.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double n; + double p; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + n = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p = random_uniform( 0.0, 1.0 ); + x = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_binomial_cdf( x, n, p ); + printf( "x: %lf, n: %lf, p: %lf, F(x;n,p): %lf\n", x, n, p, y ); + } + + return 0; +} +``` + +
+ + + +
+ + + + + +
+ +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..b947bbb485b2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( stdev instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var n; + var p; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 100.0, arrayOpts ); + n = discreteUniform( 100, 1, 100, arrayOpts ); + p = uniform( 100, 0.0, 1.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = stdev( x[ i % x.length ], n[ i % n.length ], p[ i % p.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..f917da3a8f9f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/cdf.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include +#include +#include + +#define NAME "binomial-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double n[ 100 ]; + double p[ 100 ]; + double x[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + n[ i ] = stdlib_base_ceil( random_uniform( 1.0, 100.0 ) ); + x[ i ] = random_uniform( 0.0, 100.0 ); + p[ i ] = random_uniform( 0.0, 1.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_binomial_cdf( x[ i % 100 ], n[ i % 100 ], p[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/examples/c/example.c new file mode 100644 index 000000000000..2cc2a8b74fb9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/examples/c/example.c @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/binomial/cdf.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v * (max - min) ); +} + +int main( void ) { + double n; + double p; + double x; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + n = stdlib_base_ceil( random_uniform( 0.0, 100.0 ) ); + p = random_uniform( 0.0, 1.0 ); + x = random_uniform( 0.0, 20.0 ); + y = stdlib_base_dists_binomial_cdf( x, n, p ); + printf( "x: %lf, n: %lf, p: %lf, F(x;n,p): %lf\n", x, n, p, y ); + } + + return 0; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' 1.0 || + !stdlib_base_is_nonnegative_integer( n ) || + n == STDLIB_CONSTANT_FLOAT64_PINF + ) { + return 0.0 / 0.0; // NaN + } + if ( x < 0.0 ) { + return 0.0; + } + if ( x >= n ) { + return 1.0; + } + xx = stdlib_base_floor( x + 1.0e-7 ); + return stdlib_base_betainc( p, xx + 1.0, n - xx, true, true ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.cdf.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.cdf.js index e2b6d5d4565c..078cd1ca89cd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.cdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.cdf.js @@ -22,10 +22,9 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var cdf = require( './../lib' ); @@ -122,8 +121,6 @@ tape( 'if provided a success probability `p` outside of `[0,1]`, the function re tape( 'the function evaluates the cdf for `x` given large `n` and `p`', function test( t ) { var expected; - var delta; - var tol; var x; var n; var p; @@ -136,21 +133,13 @@ tape( 'the function evaluates the cdf for `x` given large `n` and `p`', function p = highHigh.p; for ( i = 0; i < x.length; i++ ) { y = cdf( x[i], n[i], p[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 250.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 280 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); tape( 'the function evaluates the cdf for `x` given large `n` and small `p`', function test( t ) { var expected; - var delta; - var tol; var x; var n; var p; @@ -163,21 +152,13 @@ tape( 'the function evaluates the cdf for `x` given large `n` and small `p`', fu p = highSmall.p; for ( i = 0; i < x.length; i++ ) { y = cdf( x[i], n[i], p[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 40.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 80 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); tape( 'the function evaluates the cdf for `x` given small `n` and large `p`', function test( t ) { var expected; - var delta; - var tol; var x; var n; var p; @@ -190,21 +171,13 @@ tape( 'the function evaluates the cdf for `x` given small `n` and large `p`', fu p = smallHigh.p; for ( i = 0; i < x.length; i++ ) { y = cdf( x[i], n[i], p[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 50.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 70 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); tape( 'the function evaluates the cdf for `x` given small `n` and `p`', function test( t ) { var expected; - var delta; - var tol; var x; var n; var p; @@ -217,13 +190,7 @@ tape( 'the function evaluates the cdf for `x` given small `n` and `p`', function p = smallSmall.p; for ( i = 0; i < x.length; i++ ) { y = cdf( x[i], n[i], p[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 10.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 10 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.factory.js index f9e920be3eef..46f454dc0660 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.factory.js @@ -22,10 +22,9 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var factory = require( './../lib/factory.js' ); @@ -171,9 +170,7 @@ tape( 'if provided a success probability `p` outside `[0,1]`, the created functi tape( 'the created function evaluates the cdf for `x` given large `n` and `p`', function test( t ) { var expected; - var delta; var cdf; - var tol; var i; var n; var p; @@ -187,22 +184,14 @@ tape( 'the created function evaluates the cdf for `x` given large `n` and `p`', for ( i = 0; i < x.length; i++ ) { cdf = factory( n[i], p[i] ); y = cdf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 250.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 280 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); tape( 'the created function evaluates the cdf for `x` given large `n` and small `p`', function test( t ) { var expected; - var delta; var cdf; - var tol; var n; var p; var i; @@ -216,22 +205,14 @@ tape( 'the created function evaluates the cdf for `x` given large `n` and small for ( i = 0; i < x.length; i++ ) { cdf = factory( n[i], p[i] ); y = cdf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 40.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 80 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); tape( 'the created function evaluates the cdf for `x` given small `n` and large `p`', function test( t ) { var expected; - var delta; var cdf; - var tol; var i; var n; var p; @@ -245,22 +226,14 @@ tape( 'the created function evaluates the cdf for `x` given small `n` and large for ( i = 0; i < x.length; i++ ) { cdf = factory( n[i], p[i] ); y = cdf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 50.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 70 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); tape( 'the created function evaluates the cdf for `x` given small `n` and `p`', function test( t ) { var expected; - var delta; var cdf; - var tol; var i; var n; var p; @@ -274,13 +247,7 @@ tape( 'the created function evaluates the cdf for `x` given small `n` and `p`', for ( i = 0; i < x.length; i++ ) { cdf = factory( n[i], p[i] ); y = cdf( x[i] ); - if ( y === expected[i] ) { - t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', p: '+p[i]+', y: '+y+', expected: '+expected[i] ); - } else { - delta = abs( y - expected[i] ); - tol = 10.0 * EPS * abs( expected[i] ); - t.strictEqual( delta <= tol, true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. Expected: '+expected[i]+'. tol: '+tol+'. delta: '+delta+'.' ); - } + t.strictEqual( isAlmostSameValue( y, expected[i], 10 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); } t.end(); }); diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.native.js new file mode 100644 index 000000000000..c156dadfeab6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/test/test.native.js @@ -0,0 +1,184 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var tryRequire = require( '@stdlib/utils/try-require' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// FIXTURES // + +var smallSmall = require( './fixtures/julia/small_small.json' ); +var smallHigh = require( './fixtures/julia/small_high.json' ); +var highSmall = require( './fixtures/julia/high_small.json' ); +var highHigh = require( './fixtures/julia/high_high.json' ); + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided an `x` greater than or equal to `n`, the function returns `1` (provided `n` and `p` are valid)', opts, function test( t ) { + var y; + + y = cdf( 200, 20, 0.5 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( 21, 20, 0.5 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a negative number for `x` and a valid `n` and `p`, the function returns `0`', opts, function test( t ) { + var y; + + y = cdf( -10.0, 20, 0.5 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + y = cdf( -1.0, 20, 0.5 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `n` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, -2, 0.5 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, -1, 0.5 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a success probability `p` outside of `[0,1]`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 20, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 20, 1.5 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, 20, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, 20, PINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large `n` and `p`', opts, function test( t ) { + var expected; + var x; + var n; + var p; + var y; + var i; + + expected = highHigh.expected; + x = highHigh.x; + n = highHigh.n; + p = highHigh.p; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], n[i], p[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 280 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large `n` and small `p`', opts, function test( t ) { + var expected; + var x; + var n; + var p; + var y; + var i; + + expected = highSmall.expected; + x = highSmall.x; + n = highSmall.n; + p = highSmall.p; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], n[i], p[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 80 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given small `n` and large `p`', opts, function test( t ) { + var expected; + var x; + var n; + var p; + var y; + var i; + + expected = smallHigh.expected; + x = smallHigh.x; + n = smallHigh.n; + p = smallHigh.p; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], n[i], p[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 70 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given small `n` and `p`', opts, function test( t ) { + var expected; + var x; + var n; + var p; + var y; + var i; + + expected = smallSmall.expected; + x = smallSmall.x; + n = smallSmall.n; + p = smallSmall.p; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], n[i], p[i] ); + t.strictEqual( isAlmostSameValue( y, expected[i], 10 ), true, 'within tolerance. x: '+x[i]+'. n: '+n[i]+'. p: '+p[i]+'. y: '+y+'. E: '+expected[i]+'.' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/bradford/entropy/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/bradford/entropy/lib/native.js index ff75e5063f28..eab8dd7bfd7e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/bradford/entropy/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/bradford/entropy/lib/native.js @@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' ); /** * Returns the differential entropy of a Bradford distribution. * +* @private * @param {PositiveNumber} c - shape parameter * @returns {number} differential entropy * diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/README.md new file mode 100644 index 000000000000..b86652d9bf39 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/README.md @@ -0,0 +1,283 @@ + + +# Cumulative Distribution Function + +> [Burr (type III)][burr-distribution] distribution [cumulative distribution function][cdf]. + +
+ +The [cumulative distribution function][cdf] for a [Burr (type III)][burr-distribution] random variable is + + + +```math +F(x; c, d) = (1 + x^{-c})^{-d} +``` + + + +where `c > 0` is the first shape parameter and `d > 0` is the second shape parameter. + +
+ + + +
+ +## Usage + +```javascript +var cdf = require( '@stdlib/stats/base/dists/burr-type3/cdf' ); +``` + +#### cdf( x, c, d ) + +Evaluates the [cumulative distribution function][cdf] (CDF) for a [Burr (type III)][burr-distribution] distribution with parameters `c` (first shape parameter) and `d` (second shape parameter). + +```javascript +var y = cdf( 0.1, 1.0, 1.0 ); +// returns ~0.091 + +y = cdf( 0.2, 2.0, 2.0 ); +// returns ~0.0015 + +y = cdf( 0.3, 2.0, 2.0 ); +// returns ~0.007 + +y = cdf( 1.0, 0.1, 1.0 ); +// returns 0.5 + +y = cdf( 0.3, 0.5, 0.5 ); +// returns ~0.595 + +y = cdf( 0.5, 1.0, 1.0 ); +// returns ~0.333 + +y = cdf( 0.5, 2.0, 4.0 ); +// returns ~0.0016 + +y = cdf( 0.8, 0.5, 0.5 ); +// returns ~0.687 +``` + +If provided `x <= 0`, the function returns `0`. + +```javascript +var y = cdf( -1.0, 0.5, 1.0 ); +// returns 0.0 + +y = cdf( 0.0, 0.5, 1.0 ); +// returns 0.0 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = cdf( NaN, 1.0, 1.0 ); +// returns NaN + +y = cdf( 0.0, NaN, 1.0 ); +// returns NaN + +y = cdf( 0.0, 1.0, NaN ); +// returns NaN +``` + +If provided `c <= 0`, the function returns `NaN`. + +```javascript +var y = cdf( 2.0, -1.0, 0.5 ); +// returns NaN + +y = cdf( 2.0, 0.0, 0.5 ); +// returns NaN +``` + +If provided `d <= 0`, the function returns `NaN`. + +```javascript +var y = cdf( 2.0, 0.5, -1.0 ); +// returns NaN + +y = cdf( 2.0, 0.5, 0.0 ); +// returns NaN +``` + +#### cdf.factory( c, d ) + +Returns a function for evaluating the [cumulative distribution function][cdf] for a [Burr (type III)][burr-distribution] distribution with parameters `c` (first shape parameter) and `d` (second shape parameter). + +```javascript +var mycdf = cdf.factory( 0.5, 0.5 ); + +var y = mycdf( 0.8 ); +// returns ~0.687 + +y = mycdf( 0.3 ); +// returns ~0.595 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var cdf = require( '@stdlib/stats/base/dists/burr-type3/cdf' ); + +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 10, 0.1, 1.0, opts ); +var c = uniform( 10, 1.0, 10.0, opts ); +var d = uniform( 10, 1.0, 10.0, opts ); + +logEachMap( 'x: %0.4f, c: %0.4f, d: %0.4f, F(x;c,d): %0.4f', x, c, d, cdf ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/burr-type3/cdf.h" +``` + +#### stdlib_base_dists_burr_type3_cdf( x, c, d ) + +Evaluates the cumulative distribution function (CDF) for a Burr (type III) distribution with first shape parameter `c` and second shape parameter `d` at input value `x`. + +```c +double y = stdlib_base_dists_burr_type3_cdf( 0.1, 1.0, 1.0 ); +// returns ~0.091 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **c**: `[in] double` first shape parameter. +- **d**: `[in] double` second shape parameter. + +```c +double stdlib_base_dists_burr_type3_cdf( const double x, const double c, const double d ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/burr-type3/cdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double c; + double d; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( 0.1, 1.0 ); + c = random_uniform( 1.0, 10.0 ); + d = random_uniform( 1.0, 10.0 ); + y = stdlib_base_dists_burr_type3_cdf( x, c, d ); + printf( "x: %lf, c: %lf, d: %lf, F(x;c,d): %lf\n", x, c, d, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[burr-distribution]: https://en.wikipedia.org/wiki/Burr_distribution + +[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/benchmark.js new file mode 100644 index 000000000000..37c12394666f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/benchmark.js @@ -0,0 +1,89 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cdf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var opts; + var c; + var d; + var x; + var y; + var i; + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 10.0, opts ); + c = uniform( 100, 0.1, 100.0, opts ); + d = uniform( 100, 0.1, 100.0, opts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], c[ i % c.length ], d[ i % d.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::factory', pkg ), function benchmark( b ) { + var mycdf; + var opts; + var x; + var y; + var i; + + opts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 10.0, opts ); + mycdf = cdf.factory( 5.0, 6.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mycdf( x[ i % x.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..c9e1b843daed --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/benchmark.native.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tryRequire = require( '@stdlib/utils/try-require' ); +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var c; + var d; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 10.0, arrayOpts ); + c = uniform( 100, 0.1, 100.0, arrayOpts ); + d = uniform( 100, 0.1, 100.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], c[ i % c.length ], d[ i % d.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..93af5d98dc3f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/burr-type3/cdf.h" +#include +#include +#include +#include +#include + +#define NAME "burr-type3-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double x[ 100 ]; + double c[ 100 ]; + double d[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0.0, 10.0 ); + c[ i ] = random_uniform( 0.1, 100.0 ); + d[ i ] = random_uniform( 0.1, 100.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_burr_type3_cdf( x[ i%100 ], c[ i%100 ], d[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/repl.txt new file mode 100644 index 000000000000..291d6316264b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/repl.txt @@ -0,0 +1,71 @@ + +{{alias}}( x, c, d ) + Evaluates the cumulative distribution function (CDF) for a Burr (type III) + distribution with first shape parameter `c` and second shape parameter `d` + at a value `x`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If `c <= 0` or `d <= 0`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + c: number + First shape parameter. + + d: number + Second shape parameter. + + Returns + ------- + out: number + Evaluated CDF. + + Examples + -------- + > var y = {{alias}}( 0.1, 1.0, 1.0 ) + ~0.091 + > y = {{alias}}( 0.2, 2.0, 2.0 ) + ~0.0015 + > y = {{alias}}( 0.8, 0.5, 0.5 ) + ~0.687 + > y = {{alias}}( -0.5, 4.0, 2.0 ) + 0.0 + > y = {{alias}}( 2.0, -1.0, 0.5 ) + NaN + > y = {{alias}}( 2.0, 0.5, -1.0 ) + NaN + + +{{alias}}.factory( c, d ) + Returns a function for evaluating the cumulative distribution function (CDF) + of a Burr (type III) distribution with first shape parameter `c` and second + shape parameter `d`. + + Parameters + ---------- + c: number + First shape parameter. + + d: number + Second shape parameter. + + Returns + ------- + cdf: Function + Cumulative distribution function (CDF). + + Examples + -------- + > var myCDF = {{alias}}.factory( 0.5, 0.5 ); + > var y = myCDF( 0.8 ) + ~0.687 + > y = myCDF( 0.3 ) + ~0.595 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/types/index.d.ts new file mode 100644 index 000000000000..2a04ec777195 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/types/index.d.ts @@ -0,0 +1,128 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the cumulative distribution function (CDF) for a Burr (type III) distribution. +* +* @param x - input value +* @returns evaluated CDF +*/ +type Unary = ( x: number ) => number; + +/** +* Interface for the cumulative distribution function (CDF) of a Burr (type III) distribution. +*/ +interface CDF { + /** + * Evaluates the cumulative distribution function (CDF) for a Burr (type III) distribution with first shape parameter `c` and second shape parameter `d` at a value `x`. + * + * ## Notes + * + * - If `c <= 0` or `d <= 0`, the function returns `NaN`. + * + * @param x - input value + * @param c - first shape parameter + * @param d - second shape parameter + * @returns evaluated CDF + * + * @example + * var y = cdf( 0.1, 1.0, 1.0 ); + * // returns ~0.091 + * + * @example + * var y = cdf( 0.2, 2.0, 2.0 ); + * // returns ~0.0015 + * + * @example + * var y = cdf( 0.3, 2.0, 2.0 ); + * // returns ~0.007 + * + * @example + * var y = cdf( 1.0, 0.1, 1.0 ); + * // returns 0.5 + * + * @example + * var y = cdf( -1.0, 0.5, 1.0 ); + * // returns 0.0 + * + * @example + * var y = cdf( 2.0, -1.0, 0.5 ); + * // returns NaN + * + * @example + * var y = cdf( 2.0, 0.5, -1.0 ); + * // returns NaN + * + * @example + * var y = cdf( NaN, 1.0, 1.0 ); + * // returns NaN + * + * @example + * var y = cdf( 0.0, NaN, 1.0 ); + * // returns NaN + * + * @example + * var y = cdf( 0.0, 1.0, NaN ); + * // returns NaN + */ + ( x: number, c: number, d: number ): number; + + /** + * Returns a function for evaluating the cumulative distribution function (CDF) for a Burr (type III) distribution with first shape parameter `c` and second shape parameter `d`. + * + * @param c - first shape parameter + * @param d - second shape parameter + * @returns CDF + * + * @example + * var mycdf = cdf.factory( 0.5, 0.5 ); + * + * var y = mycdf( 0.8 ); + * // returns ~0.687 + * + * y = mycdf( 0.3 ); + * // returns ~0.595 + */ + factory( c: number, d: number ): Unary; +} + +/** +* Burr (type III) distribution cumulative distribution function (CDF). +* +* @param x - input value +* @param c - first shape parameter +* @param d - second shape parameter +* @returns evaluated CDF +* +* @example +* var y = cdf( 0.5, 1.0, 1.0 ); +* // returns ~0.333 +* +* var mycdf = cdf.factory( 0.5, 0.5 ); +* +* y = mycdf( 0.8 ); +* // returns ~0.687 +*/ +declare var cdf: CDF; + + +// EXPORTS // + +export = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/types/test.ts new file mode 100644 index 000000000000..68240f51cfb8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/docs/types/test.ts @@ -0,0 +1,119 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import cdf = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + cdf( 2, 2, 4 ); // $ExpectType number + cdf( 1, 2, 8 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than three numbers... +{ + cdf( true, 3, 6 ); // $ExpectError + cdf( false, 2, 4 ); // $ExpectError + cdf( '5', 1, 2 ); // $ExpectError + cdf( [], 1, 2 ); // $ExpectError + cdf( {}, 2, 4 ); // $ExpectError + cdf( ( x: number ): number => x, 2, 4 ); // $ExpectError + + cdf( 9, true, 12 ); // $ExpectError + cdf( 9, false, 12 ); // $ExpectError + cdf( 5, '5', 10 ); // $ExpectError + cdf( 8, [], 16 ); // $ExpectError + cdf( 9, {}, 18 ); // $ExpectError + cdf( 8, ( x: number ): number => x, 16 ); // $ExpectError + + cdf( 9, 5, true ); // $ExpectError + cdf( 9, 5, false ); // $ExpectError + cdf( 5, 2, '5' ); // $ExpectError + cdf( 8, 4, [] ); // $ExpectError + cdf( 9, 4, {} ); // $ExpectError + cdf( 8, 5, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + cdf(); // $ExpectError + cdf( 2 ); // $ExpectError + cdf( 2, 0 ); // $ExpectError + cdf( 2, 0, 4, 1 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + cdf.factory( 3, 4 ); // $ExpectType Unary +} + +// The `factory` method returns a function which returns a number... +{ + const fcn = cdf.factory( 3, 4 ); + fcn( 2 ); // $ExpectType number +} + +// The compiler throws an error if the function returned by the `factory` method is provided invalid arguments... +{ + const fcn = cdf.factory( 3, 4 ); + fcn( true ); // $ExpectError + fcn( false ); // $ExpectError + fcn( '5' ); // $ExpectError + fcn( [] ); // $ExpectError + fcn( {} ); // $ExpectError + fcn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const fcn = cdf.factory( 3, 4 ); + fcn(); // $ExpectError + fcn( 2, 0 ); // $ExpectError + fcn( 2, 0, 1 ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided values other than two numbers... +{ + cdf.factory( true, 3 ); // $ExpectError + cdf.factory( false, 2 ); // $ExpectError + cdf.factory( '5', 1 ); // $ExpectError + cdf.factory( [], 1 ); // $ExpectError + cdf.factory( {}, 2 ); // $ExpectError + cdf.factory( ( x: number ): number => x, 2 ); // $ExpectError + + cdf.factory( 9, true ); // $ExpectError + cdf.factory( 9, false ); // $ExpectError + cdf.factory( 5, '5' ); // $ExpectError + cdf.factory( 8, [] ); // $ExpectError + cdf.factory( 9, {} ); // $ExpectError + cdf.factory( 8, ( x: number ): number => x ); // $ExpectError + + cdf.factory( [], true ); // $ExpectError + cdf.factory( {}, false ); // $ExpectError + cdf.factory( false, '5' ); // $ExpectError + cdf.factory( {}, [] ); // $ExpectError + cdf.factory( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + cdf.factory( 0 ); // $ExpectError + cdf.factory( 0, 4, 8 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/c/example.c new file mode 100644 index 000000000000..28b7074a61f3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/c/example.c @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/burr-type3/cdf.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double c; + double d; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( 0.1, 1.0 ); + c = random_uniform( 1.0, 10.0 ); + d = random_uniform( 1.0, 10.0 ); + y = stdlib_base_dists_burr_type3_cdf( x, c, d ); + printf( "x: %lf, c: %lf, d: %lf, F(x;c,d): %lf\n", x, c, d, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/index.js new file mode 100644 index 000000000000..f4bf98e9fd6e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/examples/index.js @@ -0,0 +1,32 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var cdf = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 10, 0.1, 1.0, opts ); +var c = uniform( 10, 1.0, 10.0, opts ); +var d = uniform( 10, 1.0, 10.0, opts ); + +logEachMap( 'x: %0.4f, c: %0.4f, d: %0.4f, F(x;c,d): %0.4f', x, c, d, cdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + */ + function cdf( x ) { + if ( isnan( x ) ) { + return NaN; + } + if ( x <= 0.0 ) { + return 0.0; + } + return pow( 1.0 + pow( x, -c ), -d ); + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/index.js new file mode 100644 index 000000000000..bfa82c79cf77 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/index.js @@ -0,0 +1,58 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Evaluate the cumulative distribution function (CDF) for a Burr (type III) distribution. +* +* @module @stdlib/stats/base/dists/burr-type3/cdf +* +* @example +* var cdf = require( '@stdlib/stats/base/dists/burr-type3/cdf' ); +* +* var y = cdf( 0.5, 1.0, 1.0 ); +* // returns ~0.333 +* +* y = cdf( 0.5, 2.0, 4.0 ); +* // returns ~0.0016 +* +* @example +* var factory = require( '@stdlib/stats/base/dists/burr-type3/cdf' ).factory; +* +* var cdf = factory( 0.5, 0.5 ); +* +* var y = cdf( 0.3 ); +* // returns ~0.595 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/main.js new file mode 100644 index 000000000000..679689a03d40 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/main.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var pow = require( '@stdlib/math/base/special/pow' ); + + +// MAIN // + +/** +* Evaluates the cumulative distribution function (CDF) for a Burr (type III) distribution with first shape parameter `c` and second shape parameter `d` at a value `x`. +* +* @param {number} x - input value +* @param {PositiveNumber} c - first shape parameter +* @param {PositiveNumber} d - second shape parameter +* @returns {Probability} evaluated CDF +* +* @example +* var y = cdf( 0.1, 1.0, 1.0 ); +* // returns ~0.091 +* +* @example +* var y = cdf( 0.2, 2.0, 2.0 ); +* // returns ~0.0015 +* +* @example +* var y = cdf( 0.3, 2.0, 2.0 ); +* // returns ~0.007 +* +* @example +* var y = cdf( 1.0, 0.1, 1.0 ); +* // returns 0.5 +* +* @example +* var y = cdf( -1.0, 0.5, 1.0 ); +* // returns 0.0 +* +* @example +* var y = cdf( 2.0, -1.0, 0.5 ); +* // returns NaN +* +* @example +* var y = cdf( 2.0, 0.5, -1.0 ); +* // returns NaN +* +* @example +* var y = cdf( NaN, 1.0, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, 1.0, NaN ); +* // returns NaN +*/ +function cdf( x, c, d ) { + if ( + isnan( x ) || + isnan( c ) || + isnan( d ) || + c <= 0.0 || + d <= 0.0 + ) { + return NaN; + } + if ( x <= 0.0 ) { + return 0.0; + } + return pow( 1.0 + pow( x, -c ), -d ); +} + + +// EXPORTS // + +module.exports = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/native.js new file mode 100644 index 000000000000..aef5cf6798ed --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/lib/native.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Evaluates the cumulative distribution function (CDF) for a Burr (type III) distribution with first shape parameter `c` and second shape parameter `d` at a value `x`. +* +* @private +* @param {number} x - input value +* @param {PositiveNumber} c - first shape parameter +* @param {PositiveNumber} d - second shape parameter +* @returns {Probability} evaluated CDF +* +* @example +* var y = cdf( 0.1, 1.0, 1.0 ); +* // returns ~0.091 +* +* @example +* var y = cdf( 0.2, 2.0, 2.0 ); +* // returns ~0.0015 +* +* @example +* var y = cdf( 0.3, 2.0, 2.0 ); +* // returns ~0.007 +* +* @example +* var y = cdf( 1.0, 0.1, 1.0 ); +* // returns 0.5 +* +* @example +* var y = cdf( 2.0, -1.0, 0.5 ); +* // returns NaN +* +* @example +* var y = cdf( 2.0, 0.5, -1.0 ); +* // returns NaN +* +* @example +* var y = cdf( NaN, 1.0, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 0.0, 1.0, NaN ); +* // returns NaN +*/ +function cdf( x, c, d ) { + return addon( x, c, d ); +} + + +// EXPORTS // + +module.exports = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/manifest.json new file mode 100644 index 000000000000..f64b3a3964a0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/manifest.json @@ -0,0 +1,79 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/ternary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/pow" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/pow" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/pow" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/package.json b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/package.json new file mode 100644 index 000000000000..9687554a1e21 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/base/dists/burr-type3/cdf", + "version": "0.0.0", + "description": "Burr (type III) distribution cumulative distribution function (CDF).", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "probability", + "prob", + "cdf", + "cumulative", + "cumulative distribution", + "distribution function", + "burr", + "univariate", + "continuous" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/addon.c new file mode 100644 index 000000000000..331bee6d27ec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/burr-type3/cdf.h" +#include "stdlib/math/base/napi/ternary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DDD_D( stdlib_base_dists_burr_type3_cdf ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/main.c new file mode 100644 index 000000000000..8e37cdc5cf68 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/src/main.c @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/burr-type3/cdf.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/pow.h" + +/** +* Evaluates the cumulative distribution function (CDF) for a Burr (type III) distribution with first shape parameter `c` and second shape parameter `d` at a value `x`. +* +* @param x input value +* @param c first shape parameter +* @param d second shape parameter +* @return evaluated CDF +* +* @example +* double y = stdlib_base_dists_burr_type3_cdf( 0.1, 1.0, 1.0 ); +* // returns ~0.091 +*/ +double stdlib_base_dists_burr_type3_cdf( const double x, const double c, const double d ) { + if ( + stdlib_base_is_nan( x ) || + stdlib_base_is_nan( c ) || + stdlib_base_is_nan( d ) || + c <= 0.0 || + d <= 0.0 + ) { + return 0.0 / 0.0; // NaN + } + if ( x <= 0.0 ) { + return 0.0; + } + return stdlib_base_pow( 1.0 + stdlib_base_pow( x, -c ), -d ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/fixtures/python/large_values.json b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/fixtures/python/large_values.json new file mode 100644 index 000000000000..1fda206e25fd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/fixtures/python/large_values.json @@ -0,0 +1 @@ +{"x": [0.01, 0.02, 0.03, 0.04, 0.05, 0.060000000000000005, 0.06999999999999999, 0.08, 0.09, 0.09999999999999999, 0.11, 0.12, 0.13, 0.14, 0.15000000000000002, 0.16, 0.17, 0.18000000000000002, 0.19, 0.2, 0.21000000000000002, 0.22, 0.23, 0.24000000000000002, 0.25, 0.26, 0.27, 0.28, 0.29000000000000004, 0.3, 0.31, 0.32, 0.33, 0.34, 0.35000000000000003, 0.36000000000000004, 0.37, 0.38, 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@license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Generate fixtures.""" + +import os +import json +import numpy as np +from scipy.stats import burr + +# Get the file path: +FILE = os.path.realpath(__file__) + +# Extract the directory in which this file resides: +DIR = os.path.dirname(FILE) + + +def gen(x, c, d, name): + """Generate fixture data and write to file. + + # Arguments + + * `x`: domain + * `c`: domain + * `d`: domain + * `name::str`: output filename + + # Examples + + ``` python + python> x = linspace(0, 1, 2001) + python> c = linspace(0.1, 1000, 2001) + python> d = linspace(0.1, 1000, 2001) + python> gen(x, c, d, './data.json') + ``` + """ + y = burr.cdf(x, c, d) + + # Store data to be written to file as a dictionary: + data = { + "x": x.tolist(), + "c": c.tolist(), + "d": d.tolist(), + "expected": y.tolist() + } + + # Based on the script directory, create an output filepath: + filepath = os.path.join(DIR, name) + + # Write the data to the output filepath as JSON: + with open(filepath, "w", encoding="utf-8") as outfile: + json.dump(data, outfile) + + +def main(): + """Generate fixture data.""" + x = np.linspace(0.01, 10, 1000) + + # Small shape parameter: + c = np.linspace(0.1, 1, 1000) + d = np.linspace(0.1, 1, 1000) + gen(x, c, d, "small_values.json") + + # Medium shape parameter: + c = np.linspace(1, 10, 1000) + d = np.linspace(1, 10, 1000) + gen(x, c, d, "medium_values.json") + + # Large shape parameter: + c = np.linspace(10, 100, 1000) + d = np.linspace(10, 100, 1000) + gen(x, c, d, "large_values.json") + + +if __name__ == "__main__": + main() diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/fixtures/python/small_values.json b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/fixtures/python/small_values.json new file mode 100644 index 000000000000..055ac18748e2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/fixtures/python/small_values.json @@ -0,0 +1 @@ +{"x": [0.01, 0.02, 0.03, 0.04, 0.05, 0.060000000000000005, 0.06999999999999999, 0.08, 0.09, 0.09999999999999999, 0.11, 0.12, 0.13, 0.14, 0.15000000000000002, 0.16, 0.17, 0.18000000000000002, 0.19, 0.2, 0.21000000000000002, 0.22, 0.23, 0.24000000000000002, 0.25, 0.26, 0.27, 0.28, 0.29000000000000004, 0.3, 0.31, 0.32, 0.33, 0.34, 0.35000000000000003, 0.36000000000000004, 0.37, 0.38, 0.39, 0.4, 0.41000000000000003, 0.42000000000000004, 0.43, 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0.9083856059520804, 0.9085621573535023, 0.9087385587956548, 0.9089148095997547, 0.909090909090909]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.factory.js new file mode 100644 index 000000000000..1383de68c4f8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.factory.js @@ -0,0 +1,216 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var factory = require( './../lib/factory.js' ); + + +// FIXTURES // + +var small = require( './fixtures/python/small_values.json' ); +var medium = require( './fixtures/python/medium_values.json' ); +var large = require( './fixtures/python/large_values.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var cdf = factory( 1.0, 1.0 ); + t.equal( typeof cdf, 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( 1.0, 1.0 ); + y = cdf( NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, 1.0 ); + y = cdf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + cdf = factory( 1.0, NaN ); + y = cdf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, NaN ); + y = cdf( NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `c <= 0`, the created function always returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( -1.0, 1.0 ); + y = cdf( 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `d <= 0`, the created function always returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( 1.0, -1.0 ); + y = cdf( 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.5 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a finite `c` and `d`, the function returns a function which returns `0` when provided a number smaller than or equal to zero for `x`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.5, 1.0 ); + y = cdf( NINF ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( -100.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( -10.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( -1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( 0.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a finite `c` and `d`, the function returns a function which returns `1` when provided `+infinity` for `x`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.5, 1.0 ); + y = cdf( PINF ); + t.equal( y, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the created function evaluates the cdf for `x` given small parameters `c` and `d`', function test( t ) { + var expected; + var cdf; + var c; + var d; + var i; + var x; + var y; + + expected = small.expected; + x = small.x; + c = small.c; + d = small.d; + for ( i = 0; i < x.length; i++ ) { + cdf = factory( c[i], d[i] ); + y = cdf( x[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 3 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); + +tape( 'the created function evaluates the cdf for `x` given medium parameters `c` and `d`', function test( t ) { + var expected; + var cdf; + var c; + var d; + var i; + var x; + var y; + + expected = medium.expected; + x = medium.x; + c = medium.c; + d = medium.d; + for ( i = 0; i < x.length; i++ ) { + cdf = factory( c[i], d[i] ); + y = cdf( x[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 8 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); + +tape( 'the created function evaluates the cdf for `x` given large parameters `c` and `d`', function test( t ) { + var expected; + var cdf; + var c; + var d; + var i; + var x; + var y; + + expected = large.expected; + x = large.x; + c = large.c; + d = large.d; + for ( i = 0; i < x.length; i++ ) { + cdf = factory( c[i], d[i] ); + y = cdf( x[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 20 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.js new file mode 100644 index 000000000000..5e0b80cb8d0f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var cdf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a factory method for generating `cdf` functions', function test( t ) { + t.equal( typeof cdf.factory, 'function', 'exports a factory method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.main.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.main.js new file mode 100644 index 000000000000..974f31174f12 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.main.js @@ -0,0 +1,182 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var cdf = require( './../lib' ); + + +// FIXTURES // + +var small = require( './fixtures/python/small_values.json' ); +var medium = require( './fixtures/python/medium_values.json' ); +var large = require( './fixtures/python/large_values.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y; + + y = cdf( NaN, 1.0, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `c <= 0`, the function returns `NaN`', function test( t ) { + var y; + + y = cdf( 0.0, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.5, -1.0, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 1.0, NINF, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `d <= 0`, the function returns `NaN`', function test( t ) { + var y; + + y = cdf( 0.0, 1.0, 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.5, 1.0, -1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 1.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a number less than or equal to zero for `x` and with finite `c` and finite `d`, the function returns `0`', function test( t ) { + var y; + + y = cdf( NINF, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( -100.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( -1.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( 0.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a valid `c` and `d`, the function returns `1`', function test( t ) { + var y = cdf( PINF, 0.5, 1.0 ); + t.equal( y, 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given small parameters `c` and `d`', function test( t ) { + var expected; + var x; + var c; + var d; + var y; + var i; + + expected = small.expected; + x = small.x; + c = small.c; + d = small.d; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], c[i], d[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 3 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given medium parameters `c` and `d`', function test( t ) { + var expected; + var x; + var c; + var d; + var y; + var i; + + expected = medium.expected; + x = medium.x; + c = medium.c; + d = medium.d; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], c[i], d[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 8 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large parameters `c` and `d`', function test( t ) { + var expected; + var x; + var c; + var d; + var y; + var i; + + expected = large.expected; + x = large.x; + c = large.c; + d = large.d; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], c[i], d[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 20 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.native.js new file mode 100644 index 000000000000..053a99ed126b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/burr-type3/cdf/test/test.native.js @@ -0,0 +1,191 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// FIXTURES // + +var small = require( './fixtures/python/small_values.json' ); +var medium = require( './fixtures/python/medium_values.json' ); +var large = require( './fixtures/python/large_values.json' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( NaN, 1.0, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, NaN, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 1.0, NaN ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `c <= 0`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 0.0, 0.0, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.5, -1.0, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 1.0, NINF, 1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `d <= 0`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 0.0, 1.0, 0.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.5, 1.0, -1.0 ); + t.equal( isnan( y ), true, 'returns expected value' ); + + y = cdf( 1.0, 1.0, NINF ); + t.equal( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a number less than or equal to zero for `x` and with finite `c` and finite `d`, the function returns `0`', opts, function test( t ) { + var y; + + y = cdf( NINF, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( -100.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( -1.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + y = cdf( 0.0, 0.5, 1.0 ); + t.equal( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a valid `c` and `d`, the function returns `1`', opts, function test( t ) { + var y = cdf( PINF, 0.5, 1.0 ); + t.equal( y, 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given small parameters `c` and `d`', opts, function test( t ) { + var expected; + var x; + var c; + var d; + var y; + var i; + + expected = small.expected; + x = small.x; + c = small.c; + d = small.d; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], c[i], d[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 3 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given medium parameters `c` and `d`', opts, function test( t ) { + var expected; + var x; + var c; + var d; + var y; + var i; + + expected = medium.expected; + x = medium.x; + c = medium.c; + d = medium.d; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], c[i], d[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 8 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given large parameters `c` and `d`', opts, function test( t ) { + var expected; + var x; + var c; + var d; + var y; + var i; + + expected = large.expected; + x = large.x; + c = large.c; + d = large.d; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], c[i], d[i] ); + if ( y === expected[i] ) { + t.equal( y, expected[i], 'x: '+x[i]+'. c: '+c[i]+'. d: '+d[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 20 ), 'within tolerance. x: '+x[ i ]+'. c: '+c[i]+'. d: '+d[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/README.md index 542a72b11378..db67838d8f12 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/README.md @@ -20,7 +20,7 @@ limitations under the License. # Logarithm of Probability Density Function -> [Cauchy][cauchy-distribution] distribution natural logarithm of probability density function (logPDF). +> [Cauchy][cauchy-distribution] distribution natural logarithm of [probability density function][pdf] (logPDF).
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md index 5e9af181a467..421a5b55fd16 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/README.md @@ -20,7 +20,7 @@ limitations under the License. # Probability Density Function -> [Cauchy][cauchy-distribution] distribution probability density function (PDF). +> [Cauchy][cauchy-distribution] distribution [probability density function][pdf] (PDF).
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/README.md index 46340a90ac73..c8e23b6d7bbd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/README.md @@ -33,7 +33,7 @@ F(x;\mu ,s)=\begin{cases} 0 & \text{ for } x < \mu - s \\ {\frac {1}{2}}\left[1\ ``` @@ -140,7 +140,7 @@ var x = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, s: %0.4f, F(x;µ,s): %0.4f', x, mu, s, cdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, s: %0.4f, F(x;μ,s): %0.4f', x, mu, s, cdf ); ```
@@ -233,7 +233,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_cdf( x, mu, s ); - printf( "x: %lf, µ: %lf, s: %lf, F(x;µ,s): %lf\n", x, mu, s, y ); + printf( "x: %lf, μ: %lf, s: %lf, F(x;μ,s): %lf\n", x, mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/docs/img/equation_cosine_cdf.svg b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/docs/img/equation_cosine_cdf.svg index 8b3fbd1ea558..56d92e77e474 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/docs/img/equation_cosine_cdf.svg +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/cdf/docs/img/equation_cosine_cdf.svg @@ -1,5 +1,5 @@ -upper F left-parenthesis x semicolon mu comma s right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column 0 2nd Column for x less-than mu minus s 2nd Row 1st Column one-half left-bracket 1 plus StartFraction x minus mu Over s EndFraction plus StartFraction 1 Over pi EndFraction sine left-parenthesis StartFraction x minus mu Over s EndFraction pi right-parenthesis right-bracket 2nd Column for mu minus s less-than-or-equal-to x less-than-or-equal-to mu plus s 3rd Row 1st Column 1 2nd Column for x greater-than mu plus s EndLayout +upper F left-parenthesis x semicolon mu comma s right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column 0 2nd Column for x less-than mu minus s 2nd Row 1st Column one half left-bracket 1 plus StartFraction x minus mu Over s EndFraction plus StartFraction 1 Over pi EndFraction sine left-parenthesis StartFraction x minus mu Over s EndFraction pi right-parenthesis right-bracket 2nd Column for mu minus s less-than-or-equal-to x less-than-or-equal-to mu plus s 3rd Row 1st Column 1 2nd Column for x greater-than mu plus s EndLayout
@@ -211,7 +211,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_kurtosis( mu, s ); - printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, Kurt(X;μ,s): %lf\n", mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/example.c index 5b6cf05db7c1..2bfa10995d71 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/c/example.c @@ -36,6 +36,6 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_kurtosis( mu, s ); - printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, Kurt(X;μ,s): %lf\n", mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/index.js index b9b077187e5d..f1537255e766 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/kurtosis/examples/index.js @@ -28,4 +28,4 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, Kurt(X;µ,s): %0.4f', mu, s, kurtosis ); +logEachMap( 'μ: %0.4f, s: %0.4f, Kurt(X;μ,s): %0.4f', mu, s, kurtosis ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/README.md index 4479f9b33fc1..5d2d29b50c97 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/README.md @@ -33,7 +33,7 @@ F(x;\mu ,s)=\begin{cases} 0 & \text{ for } x < \mu - s \\ {\frac {1}{2}}\left[1\ ``` @@ -150,7 +150,7 @@ var x = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, s: %0.4f, ln(F(x;µ,s)): %0.4f', x, mu, s, logcdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, s: %0.4f, ln(F(x;μ,s)): %0.4f', x, mu, s, logcdf ); ```
@@ -243,7 +243,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_logcdf( x, mu, s ); - printf( "x: %lf, µ: %lf, s: %lf, ln(F(x;µ,s)): %lf\n", x, mu, s, y ); + printf( "x: %lf, μ: %lf, s: %lf, ln(F(x;μ,s)): %lf\n", x, mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/img/equation_cosine_cdf.svg b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/img/equation_cosine_cdf.svg index 8b3fbd1ea558..56d92e77e474 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/img/equation_cosine_cdf.svg +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/img/equation_cosine_cdf.svg @@ -1,5 +1,5 @@ -upper F left-parenthesis x semicolon mu comma s right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column 0 2nd Column for x less-than mu minus s 2nd Row 1st Column one-half left-bracket 1 plus StartFraction x minus mu Over s EndFraction plus StartFraction 1 Over pi EndFraction sine left-parenthesis StartFraction x minus mu Over s EndFraction pi right-parenthesis right-bracket 2nd Column for mu minus s less-than-or-equal-to x less-than-or-equal-to mu plus s 3rd Row 1st Column 1 2nd Column for x greater-than mu plus s EndLayout +upper F left-parenthesis x semicolon mu comma s right-parenthesis equals StartLayout Enlarged left-brace 1st Row 1st Column 0 2nd Column for x less-than mu minus s 2nd Row 1st Column one half left-bracket 1 plus StartFraction x minus mu Over s EndFraction plus StartFraction 1 Over pi EndFraction sine left-parenthesis StartFraction x minus mu Over s EndFraction pi right-parenthesis right-bracket 2nd Column for mu minus s less-than-or-equal-to x less-than-or-equal-to mu plus s 3rd Row 1st Column 1 2nd Column for x greater-than mu plus s EndLayout
@@ -234,7 +234,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_logpdf( x, mu, s ); - printf( "x: %lf, µ: %lf, s: %lf, ln(f(x;µ,s)): %lf\n", x, mu, s, y ); + printf( "x: %lf, μ: %lf, s: %lf, ln(f(x;μ,s)): %lf\n", x, mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/example.c index fa760d11d9a9..f713a5aca33d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/c/example.c @@ -38,6 +38,6 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_logpdf( x, mu, s ); - printf( "x: %lf, µ: %lf, s: %lf, ln(f(x;µ,s)): %lf\n", x, mu, s, y ); + printf( "x: %lf, μ: %lf, s: %lf, ln(f(x;μ,s)): %lf\n", x, mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/index.js index b04cf0147808..b5e50fcbb845 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/examples/index.js @@ -29,4 +29,4 @@ var x = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, s: %0.4f, ln(f(x;µ,s)): %0.4f', x, mu, s, logpdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, s: %0.4f, ln(f(x;μ,s)): %0.4f', x, mu, s, logpdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/README.md index 504f66af569c..9c8ebc8cfcd2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/README.md @@ -35,7 +35,7 @@ The [mean][mean] for a [raised cosine][cosine-distribution] random variable with ``` @@ -121,7 +121,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, E(X;µ,s): %0.4f', mu, s, mean ); +logEachMap( 'μ: %0.4f, s: %0.4f, E(X;μ,s): %0.4f', mu, s, mean ); ``` @@ -210,7 +210,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); s = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_cosine_mean( mu, s ); - printf( "µ: %lf, s: %lf, E(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, E(X;μ,s): %lf\n", mu, s, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/c/example.c index 26a411dee59f..ba7e7b7004d3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); s = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_cosine_mean( mu, s ); - printf( "µ: %lf, s: %lf, E(X;µ,s): %lf\n", mu , s , y ); + printf( "μ: %lf, s: %lf, E(X;μ,s): %lf\n", mu , s , y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/index.js index 369c8bb747a1..8e065584b111 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mean/examples/index.js @@ -28,4 +28,4 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, E(X;µ,s): %0.4f', mu, s, mean ); +logEachMap( 'μ: %0.4f, s: %0.4f, E(X;μ,s): %0.4f', mu, s, mean ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md index 76061b96f5e2..1d7897aae4c7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md @@ -35,7 +35,7 @@ The [median][median] for a [raised cosine][cosine-distribution] random variable ``` @@ -121,7 +121,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, Median(X;µ,s): %0.4f', mu, s, median ); +logEachMap( 'μ: %0.4f, s: %0.4f, Median(X;μ,s): %0.4f', mu, s, median ); ``` @@ -211,7 +211,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_median( mu, s ); - printf( "µ: %lf, s: %lf, Median(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, Median(X;μ,s): %lf\n", mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c index 7d0e4f9ce393..fa974db6c30f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c @@ -36,6 +36,6 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_median( mu, s ); - printf( "µ: %lf, s: %lf, Median(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, Median(X;μ,s): %lf\n", mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/index.js index 5f7111bdbd81..39b82e9c5a5c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/index.js @@ -28,4 +28,4 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, Median(X;µ,s): %0.4f', mu, s, median ); +logEachMap( 'μ: %0.4f, s: %0.4f, Median(X;μ,s): %0.4f', mu, s, median ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/README.md index e7a58f520da4..af8e9c5798b0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/README.md @@ -33,7 +33,7 @@ M_X(t) := \mathbb{E}\!\left[e^{tX}\right] = \frac{ \pi^{2} \sinh(st) }{ st(\pi^{ ``` @@ -124,7 +124,7 @@ var t = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, s: %0.4f, M_X(t;µ,s): %0.4f', t, mu, s, mgf ); +logEachMap( 'x: %0.4f, μ: %0.4f, s: %0.4f, M_X(t;μ,s): %0.4f', t, mu, s, mgf ); ``` @@ -217,7 +217,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_mgf( t, mu, s ); - printf( "t: %lf, µ: %lf, s: %lf, M_X(t;µ,s): %lf\n", t, mu, s, y ); + printf( "t: %lf, μ: %lf, s: %lf, M_X(t;μ,s): %lf\n", t, mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/example.c index 9ebd0e57739a..1c947905d43c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/c/example.c @@ -38,6 +38,6 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_mgf( t, mu, s ); - printf( "t: %lf, µ: %lf, s: %lf, M_X(t;µ,s): %lf\n", t, mu, s, y ); + printf( "t: %lf, μ: %lf, s: %lf, M_X(t;μ,s): %lf\n", t, mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/index.js index c14034432773..f3dbc5caa0e2 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mgf/examples/index.js @@ -29,4 +29,4 @@ var t = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, s: %0.4f, M_X(t;µ,s): %0.4f', t, mu, s, mgf ); +logEachMap( 'x: %0.4f, μ: %0.4f, s: %0.4f, M_X(t;μ,s): %0.4f', t, mu, s, mgf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md index 522ecfd38e8c..e66fe22bbfe8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md @@ -35,7 +35,7 @@ The [mode][mode] for a [raised cosine][cosine-distribution] random variable with ``` @@ -121,7 +121,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, mode(X;µ,s): %0.4f', mu, s, mode ); +logEachMap( 'μ: %0.4f, s: %0.4f, mode(X;μ,s): %0.4f', mu, s, mode ); ``` @@ -211,7 +211,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_mode( mu, s ); - printf( "µ: %lf, s: %lf, mode(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, mode(X;μ,s): %lf\n", mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c index be60614eadb3..f6794cc22204 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c @@ -36,6 +36,6 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_mode( mu, s ); - printf( "µ: %lf, s: %lf, mode(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, mode(X;μ,s): %lf\n", mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/index.js index f34fd0adadd3..d5d3b23128f1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/index.js @@ -28,4 +28,4 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, mode(X;µ,s): %0.4f', mu, s, mode ); +logEachMap( 'μ: %0.4f, s: %0.4f, mode(X;μ,s): %0.4f', mu, s, mode ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/README.md index 37df3477e972..033d2ba65d35 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/README.md @@ -33,7 +33,7 @@ f(x;\mu ,s)= \begin{cases} {\frac {1}{2s}}\left[1+\cos \left({\frac {x\!-\!\mu } ``` @@ -131,7 +131,7 @@ var x = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, s: %0.4f, f(x;µ,s): %0.4f', x, mu, s, pdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, s: %0.4f, f(x;μ,s): %0.4f', x, mu, s, pdf ); ``` @@ -224,7 +224,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_pdf( x, mu, s ); - printf( "x: %lf, µ: %lf, s: %lf, f(x;µ,s): %lf\n", x, mu, s, y ); + printf( "x: %lf, μ: %lf, s: %lf, f(x;μ,s): %lf\n", x, mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/example.c index 7091f37a104d..b7f409199a79 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/c/example.c @@ -38,6 +38,6 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_pdf( x, mu, s ); - printf( "x: %lf, µ: %lf, s: %lf, f(x;µ,s): %lf\n", x, mu, s, y ); + printf( "x: %lf, μ: %lf, s: %lf, f(x;μ,s): %lf\n", x, mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/index.js index 873ba1213aba..28fcf9fccade 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/pdf/examples/index.js @@ -29,4 +29,4 @@ var x = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, s: %0.4f, f(x;µ,s): %0.4f', x, mu, s, pdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, s: %0.4f, f(x;μ,s): %0.4f', x, mu, s, pdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/README.md index 2546eff96d80..a8355b3b65ce 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/README.md @@ -124,7 +124,7 @@ var p = uniform( 10, 0.0, 1.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, 0.0, 10.0, opts ); -logEachMap( 'p: %0.4f, µ: %0.4f, s: %0.4f, Q(p;µ,s): %0.4f', p, mu, s, quantile ); +logEachMap( 'p: %0.4f, μ: %0.4f, s: %0.4f, Q(p;μ,s): %0.4f', p, mu, s, quantile ); ``` @@ -217,7 +217,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_quantile( p, mu, s ); - printf( "p: %.4f, µ: %.4f, s: %.4f, Q(p;µ,s): %.4f\n", p, mu, s, y ); + printf( "p: %.4f, μ: %.4f, s: %.4f, Q(p;μ,s): %.4f\n", p, mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/c/example.c index 6917dd0c43cd..cee2af89e686 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/c/example.c @@ -38,6 +38,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_quantile( p, mu, s ); - printf( "p:%.4f, µ: %.4f, s: %.4f, Q(p;µ,s): %.4f\n", p, mu, s, y ); + printf( "p:%.4f, μ: %.4f, s: %.4f, Q(p;μ,s): %.4f\n", p, mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/index.js index 12601b2b583b..dcdb4ee90654 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/examples/index.js @@ -30,4 +30,4 @@ var p = uniform( 10, 0.0, 1.0, opts ); var mu = uniform( 10, 0.0, 10.0, opts ); var s = uniform( 10, EPS, 10.0, opts ); -logEachMap( 'p: %0.4f, µ: %0.4f, s: %0.4f, Q(p;µ,s): %0.4f', p, mu, s, quantile ); +logEachMap( 'p: %0.4f, μ: %0.4f, s: %0.4f, Q(p;μ,s): %0.4f', p, mu, s, quantile ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/lib/native.js index d16535ff4d2f..1df198b2c532 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/quantile/lib/native.js @@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' ); /** * Evaluates the quantile function for a raised cosine distribution with location parameter `mu` and scale parameter `s` at a probability `p`. * +* @private * @param {Probability} p - input value * @param {number} mu - location parameter * @param {NonNegativeNumber} s - scale parameter diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md index f041d52a1780..8572a317fac8 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md @@ -35,7 +35,7 @@ The [skewness][skewness] for a [raised cosine][cosine-distribution] random varia ``` @@ -121,7 +121,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, skew(X;µ,s): %0.4f', mu, s, skewness ); +logEachMap( 'μ: %0.4f, s: %0.4f, skew(X;μ,s): %0.4f', mu, s, skewness ); ``` @@ -211,7 +211,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_skewness( mu, s ); - printf( "µ: %lf, s: %lf, Skew(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, Skew(X;μ,s): %lf\n", mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c index c2a40bdcf677..56068f617fec 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c @@ -36,6 +36,6 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_skewness( mu, s ); - printf( "µ: %lf, s: %lf, skew(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, skew(X;μ,s): %lf\n", mu, s, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/index.js index 5723eb9b4979..c56b32cb9e86 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/index.js @@ -28,4 +28,4 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, skew(X;µ,s): %0.4f', mu, s, skewness ); +logEachMap( 'μ: %0.4f, s: %0.4f, skew(X;μ,s): %0.4f', mu, s, skewness ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md index 0b767e85b014..a6149a53467a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md @@ -35,7 +35,7 @@ The [standard deviation][stdev] for a [raised cosine][cosine-distribution] rando ``` @@ -121,7 +121,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var s = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, s: %0.4f, SD(X;µ,s): %0.4f', mu, s, stdev ); +logEachMap( 'μ: %0.4f, s: %0.4f, SD(X;μ,s): %0.4f', mu, s, stdev ); ``` @@ -211,7 +211,7 @@ int main( void ) { mu = random_uniform( -50.0, 50.0 ); s = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_cosine_stdev( mu, s ); - printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s, y ); + printf( "μ: %lf, s: %lf, SD(X;μ,s): %lf\n", mu, s, y ); } return 0; diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/docs/img/equation_cosine_stdev.svg b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/docs/img/equation_cosine_stdev.svg index 172f9c4f6dd4..9e4677991ea3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/docs/img/equation_cosine_stdev.svg +++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/docs/img/equation_cosine_stdev.svg @@ -1,5 +1,5 @@ -sigma equals s StartRoot left-parenthesis one-third minus StartFraction 2 Over pi squared EndFraction right-parenthesis EndRoot +sigma equals s StartRoot left-parenthesis one third minus StartFraction 2 Over pi squared EndFraction right-parenthesis EndRoot Cumulative distribution function for a Gumbel distribution. + Cumulative distribution function for a Gumbel distribution.
--> @@ -127,7 +127,7 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, F(x;µ,β): %0.4f', x, mu, beta, cdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, F(x;μ,β): %0.4f', x, mu, beta, cdf ); ``` @@ -219,7 +219,7 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_cdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, F(x;µ,β): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, F(x;μ,β): %lf\n", x, mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/c/example.c index a59ea37f0be2..55df80e5362b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/c/example.c @@ -37,6 +37,6 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_cdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, F(x;µ,β): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, F(x;μ,β): %lf\n", x, mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/index.js index 85b01856d29a..3cf8745510df 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/cdf/examples/index.js @@ -29,4 +29,4 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, F(x;µ,β): %0.4f', x, mu, beta, cdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, F(x;μ,β): %0.4f', x, mu, beta, cdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/README.md index a9ee0a3b8a5f..11779057069c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/README.md @@ -35,7 +35,7 @@ h\left( X \right) = \ln(\beta )+\gamma+1 ``` @@ -123,7 +123,7 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, h(X;µ,β): %0.4f', mu, beta, entropy ); +logEachMap( 'μ: %0.4f, β: %0.4f, h(X;μ,β): %0.4f', mu, beta, entropy ); ``` @@ -212,7 +212,7 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_entropy( mu, beta ); - printf( "µ: %lf, β: %lf, h(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, h(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/c/example.c index 7260b6c856eb..5a669c11d1a7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_entropy( mu, beta ); - printf( "µ: %lf, β: %lf, h(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, h(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/index.js index 7fd159ee5e67..6746113eea8b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/entropy/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, h(X;µ,β): %0.4f', mu, beta, entropy ); +logEachMap( 'μ: %0.4f, β: %0.4f, h(X;μ,β): %0.4f', mu, beta, entropy ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md index 166b68f6a03e..f7807f766c55 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/README.md @@ -35,7 +35,7 @@ The [excess kurtosis][kurtosis] for a [Gumbel][gumbel-distribution] random varia ``` @@ -121,7 +121,7 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, Kurt(X;µ,β): %0.4f', mu, beta, kurtosis ); +logEachMap( 'μ: %0.4f, β: %0.4f, Kurt(X;μ,β): %0.4f', mu, beta, kurtosis ); ``` @@ -210,7 +210,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_kurtosis( mu, beta ); - printf( "µ: %lf, β: %lf, Kurt(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Kurt(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/example.c index c5bd11c93854..4e5f52c78a16 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_kurtosis( mu, beta ); - printf( "µ: %lf, β: %lf, Kurt(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Kurt(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/index.js index 49d8f212d40b..bde4900b767e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/kurtosis/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, Kurt(X;µ,β): %0.4f', mu, beta, kurtosis ); +logEachMap( 'μ: %0.4f, β: %0.4f, Kurt(X;μ,β): %0.4f', mu, beta, kurtosis ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/README.md index 96ca1b6635d2..24168861e7b6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/README.md @@ -33,7 +33,7 @@ F\left( x; \mu, \beta \right ) = e^{{-e^{{-(x-\mu )/\beta }}}} ``` @@ -137,7 +137,7 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, ln(F(x;µ,β)): %0.4f', x, mu, beta, logcdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, ln(F(x;μ,β)): %0.4f', x, mu, beta, logcdf ); ``` @@ -229,7 +229,7 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_logcdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, ln(F(x;µ,β)): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, ln(F(x;μ,β)): %lf\n", x, mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/c/example.c index eed643d96eb3..b098e4004971 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/c/example.c @@ -37,6 +37,6 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_logcdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, ln(F(x;µ,β)): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, ln(F(x;μ,β)): %lf\n", x, mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/index.js index 76bf2bd9e998..2fff10a3c133 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/examples/index.js @@ -29,4 +29,4 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, ln(F(x;µ,β)): %0.4f', x, mu, beta, logcdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, ln(F(x;μ,β)): %0.4f', x, mu, beta, logcdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/package.json b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/package.json index ea73064bccc5..90cd93b79cc4 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/package.json +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logcdf/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/dists/gumbel/logcdf", "version": "0.0.0", - "description": "Gumbel distribution logarithm of cumulative distribution function.", + "description": "Gumbel distribution logarithm of cumulative distribution function (CDF).", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/README.md index 7f8beebc8039..1526e1a131f9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/README.md @@ -33,7 +33,7 @@ f(x;\mu,\beta) = \frac{1}{\beta}e^{-\left( \frac{x-\mu}{\beta}+e^{- \frac{x-\mu} ``` @@ -137,7 +137,7 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, ln(f(x;µ,β)): %0.4f', x, mu, beta, logpdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, ln(f(x;μ,β)): %0.4f', x, mu, beta, logpdf ); ``` @@ -229,7 +229,7 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_logpdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, ln(f(x;µ,β)): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, ln(f(x;μ,β)): %lf\n", x, mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/c/example.c index aa35a8ac8ac6..44707d1429ad 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/c/example.c @@ -37,6 +37,6 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_logpdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, ln(f(x;µ,β)): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, ln(f(x;μ,β)): %lf\n", x, mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/index.js index 9eb02a9b28f7..cbf109befe0f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/examples/index.js @@ -29,4 +29,4 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, ln(f(x;µ,β)): %0.4f', x, mu, beta, logpdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, ln(f(x;μ,β)): %0.4f', x, mu, beta, logpdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/README.md index 8af7e51695bb..ca35d00ad4ff 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/README.md @@ -35,7 +35,7 @@ The [mean][mean] for a [Gumbel][gumbel-distribution] random variable with locati ``` @@ -123,7 +123,7 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, E(X;µ,β): %0.4f', mu, beta, mean ); +logEachMap( 'μ: %0.4f, β: %0.4f, E(X;μ,β): %0.4f', mu, beta, mean ); ``` @@ -212,7 +212,7 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_mean( mu, beta ); - printf( "µ: %lf, β: %lf, E(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, E(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/c/example.c index f1d0b1e20bb7..27d6ae493b7a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_mean( mu, beta ); - printf( "µ: %lf, β: %lf, E(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, E(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/index.js index 893717abde05..e396bde09009 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mean/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, E(X;µ,β): %0.4f', mu, beta, mean ); +logEachMap( 'μ: %0.4f, β: %0.4f, E(X;μ,β): %0.4f', mu, beta, mean ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/README.md index af45e5962cd5..dabeef593251 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/README.md @@ -35,7 +35,7 @@ The [median][median] for a [gumbel][gumbel-distribution] random variable is ``` @@ -123,7 +123,7 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, Median(X;µ,β): %0.4f', mu, beta, median ); +logEachMap( 'μ: %0.4f, β: %0.4f, Median(X;μ,β): %0.4f', mu, beta, median ); ``` @@ -212,7 +212,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_median( mu, beta ); - printf( "µ: %lf, β: %lf, Median(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Median(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/c/example.c index 6c79cf9884dc..3ade7e0f36a3 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_median( mu, beta ); - printf( "µ: %lf, β: %lf, Median(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Median(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/index.js index ac1414185402..b0f9a37426cc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/median/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, Median(X;µ,β): %0.4f', mu, beta, median ); +logEachMap( 'μ: %0.4f, β: %0.4f, Median(X;μ,β): %0.4f', mu, beta, median ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/README.md index ffc1dcb199cf..cdf6fdbd79f6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/README.md @@ -20,7 +20,7 @@ limitations under the License. # Moment-Generating Function -> [Gumbel][gumbel-distribution] distribution moment-generating function (MGF). +> [Gumbel][gumbel-distribution] distribution [moment-generating function (MGF)][mgf]. @@ -35,7 +35,7 @@ M_X(t) := \mathbb{E}\!\left[e^{tX}\right] = \Gamma(1+\beta\,t)\, e^{\mu\,t} ``` @@ -147,7 +147,7 @@ var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); var t = uniform( 10, 0.0, 1.0, opts ); -logEachMap( 't: %0.4f, µ: %0.4f, β: %0.4f, M_X(t;µ,β): %0.4f', t, mu, beta, mgf ); +logEachMap( 't: %0.4f, μ: %0.4f, β: %0.4f, M_X(t;μ,β): %0.4f', t, mu, beta, mgf ); ``` @@ -239,7 +239,7 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_mgf( t, mu, beta ); - printf( "t: %lf, µ: %lf, β: %lf, M_X(t;µ,β): %lf\n", t, mu, beta, y ); + printf( "t: %lf, μ: %lf, β: %lf, M_X(t;μ,β): %lf\n", t, mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/c/example.c index 1f3b3a7bcfe4..7af7fca816bd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/c/example.c @@ -37,6 +37,6 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_mgf( t, mu, beta ); - printf( "t: %lf, µ: %lf, β: %lf, M_X(t;µ,β): %lf\n", t, mu, beta, y ); + printf( "t: %lf, μ: %lf, β: %lf, M_X(t;μ,β): %lf\n", t, mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/index.js index a6df6fe645ba..ce38cb133dd9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/examples/index.js @@ -29,4 +29,4 @@ var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); var t = uniform( 10, 0.0, 1.0, opts ); -logEachMap( 't: %0.4f, µ: %0.4f, β: %0.4f, M_X(t;µ,β): %0.4f', t, mu, beta, mgf ); +logEachMap( 't: %0.4f, μ: %0.4f, β: %0.4f, M_X(t;μ,β): %0.4f', t, mu, beta, mgf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/README.md index 5a4c7a604299..3a720b2d7f0c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/README.md @@ -35,7 +35,7 @@ The [mode][mode] for a [Gumbel][gumbel-distribution] random variable with locati ``` @@ -121,7 +121,7 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, mode(X;µ,β): %0.4f', mu, beta, mode ); +logEachMap( 'μ: %0.4f, β: %0.4f, mode(X;μ,β): %0.4f', mu, beta, mode ); ``` @@ -210,7 +210,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_mode( mu, beta ); - printf( "µ: %lf, β: %lf, mode(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, mode(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/example.c index 37428b42661d..a68b0124360c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_mode( mu, beta ); - printf( "µ: %lf, β: %lf, mode(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, mode(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/index.js index 7469e4bcd131..12834c7a2094 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mode/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 20.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, mode(X;µ,β): %0.4f', mu, beta, mode ); +logEachMap( 'μ: %0.4f, β: %0.4f, mode(X;μ,β): %0.4f', mu, beta, mode ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/README.md index d03c8808d2b5..732b4348330f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/README.md @@ -33,7 +33,7 @@ f(x;\mu,\beta) = \frac{1}{\beta}e^{-\left( \frac{x-\mu}{\beta}+e^{- \frac{x-\mu} ``` @@ -93,7 +93,7 @@ y = pdf( 2.0, 8.0, 0.0 ); #### pdf.factory( mu, beta ) -Partially applies `mu` and `beta` to create a reusable `function` for evaluating the PDF. +Returns a function for evaluating the [probability density function][pdf] of a [Gumbel][gumbel-distribution] distribution with parameters `mu` (location parameter) and `beta` (scale parameter). ```javascript var mypdf = pdf.factory( 10.0, 2.0 ); @@ -127,7 +127,7 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, f(x;µ,β): %0.4f', x, mu, beta, pdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, f(x;μ,β): %0.4f', x, mu, beta, pdf ); ``` @@ -219,7 +219,7 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_pdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, f(x;µ,β): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, f(x;μ,β): %lf\n", x, mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/c/example.c index 203b03ec69ef..12f6b1818766 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/c/example.c @@ -37,6 +37,6 @@ int main( void ) { mu = random_uniform( 0.0, 10.0 ); beta = random_uniform( 0.0, 10.0 ); y = stdlib_base_dists_gumbel_pdf( x, mu, beta ); - printf( "x: %lf, µ: %lf, β: %lf, f(x;µ,β): %lf\n", x, mu, beta, y ); + printf( "x: %lf, μ: %lf, β: %lf, f(x;μ,β): %lf\n", x, mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/index.js index 2f50be126956..60169c890d4f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/pdf/examples/index.js @@ -29,4 +29,4 @@ var beta = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var x = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, β: %0.4f, f(x;µ,β): %0.4f', x, mu, beta, pdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, β: %0.4f, f(x;μ,β): %0.4f', x, mu, beta, pdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/README.md index 898d17f4e994..22ca624978db 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/README.md @@ -33,7 +33,7 @@ Q(p)=\mu-\beta\ln(-\ln(p)) ``` @@ -138,7 +138,7 @@ var beta = uniform( 100, EPS, 10.0, opts ); var mu = uniform( 100, -5.0, 5.0, opts ); var p = uniform( 100, 0.0, 1.0, opts ); -logEachMap( 'p: %0.4f, µ: %0.4f, β: %0.4f, Q(p;µ,β): %0.4f', p, mu, beta, quantile ); +logEachMap( 'p: %0.4f, μ: %0.4f, β: %0.4f, Q(p;μ,β): %0.4f', p, mu, beta, quantile ); ``` @@ -173,7 +173,7 @@ logEachMap( 'p: %0.4f, µ: %0.4f, β: %0.4f, Q(p;µ,β): %0.4f', p, mu, beta, qu #### stdlib_base_dists_gumbel_quantile( p, mu, beta ) -Evaluates the [quantile-function][quantile-function] of a [gumbel-distribution][gumbel-distribution] with parameter probability `p`, location parameter `mu`, and scale parameter `beta`. +Evaluates the [quantile function][quantile-function] for a [Gumbel][gumbel-distribution] distribution with parameters `mu` (location parameter) and `beta` (scale parameter). ```c double y = stdlib_base_dists_gumbel_quantile( 0.8, 0.0, 1.0 ); @@ -231,7 +231,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_gumbel_quantile( p, mu, beta ); - printf( "p: %lf, µ: %lf, β: %lf, Q(p;µ,β): %lf\n", p, mu, beta, y ); + printf( "p: %lf, μ: %lf, β: %lf, Q(p;μ,β): %lf\n", p, mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/c/example.c index 9c2dec431d25..5ad928539a23 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/c/example.c @@ -38,6 +38,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_gumbel_quantile( p, mu, beta ); - printf( "p: %lf, µ: %lf, β: %lf, Q(p;µ,β): %lf\n", p, mu, beta, y ); + printf( "p: %lf, μ: %lf, β: %lf, Q(p;μ,β): %lf\n", p, mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/index.js index 8188034e4b32..c6d33146f665 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/quantile/examples/index.js @@ -30,4 +30,4 @@ var beta = uniform( 100, EPS, 10.0, opts ); var mu = uniform( 100, -5.0, 5.0, opts ); var p = uniform( 100, 0.0, 1.0, opts ); -logEachMap( 'p: %0.4f, µ: %0.4f, β: %0.4f, Q(p;µ,β): %0.4f', p, mu, beta, quantile ); +logEachMap( 'p: %0.4f, μ: %0.4f, β: %0.4f, Q(p;μ,β): %0.4f', p, mu, beta, quantile ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md index 9811d0d49577..9445c7eab71d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/README.md @@ -35,7 +35,7 @@ The [skewness][skewness] for a [Gumbel][gumbel-distribution] random variable wit ``` @@ -123,7 +123,7 @@ var opts = { var beta = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, skew(X;µ,β): %0.4f', mu, beta, skewness ); +logEachMap( 'μ: %0.4f, β: %0.4f, skew(X;μ,β): %0.4f', mu, beta, skewness ); ``` @@ -158,10 +158,10 @@ logEachMap( 'µ: %0.4f, β: %0.4f, skew(X;µ,β): %0.4f', mu, beta, skewness ); #### stdlib_base_dists_gumbel_skewness( mu, beta ) -Returns the skewness for a Gumbel distribution with location `mu` and scale `beta`. +Returns the [skewness][skewness] for a [Gumbel][gumbel-distribution] distribution with location parameter `mu` and scale parameter `beta`. ```c -double y = stdlib_base_dists_gumbel_skewness( 0.0, 1.0 ); +double out = stdlib_base_dists_gumbel_skewness( 0.0, 1.0 ); // returns ~1.14 ``` @@ -212,7 +212,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_skewness( mu, beta ); - printf( "µ: %lf, β: %lf, Skew(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Skew(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/c/example.c index 3993d63e1363..8c72d05b96df 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_skewness( mu, beta ); - printf( "µ: %lf, β: %lf, Skew(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Skew(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/index.js index 2dfff2b08cbc..e29e17a1fd78 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/skewness/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, skew(X;µ,β): %0.4f', mu, beta, skewness ); +logEachMap( 'μ: %0.4f, β: %0.4f, skew(X;μ,β): %0.4f', mu, beta, skewness ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/README.md index a97091caa102..2984561a1505 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/README.md @@ -35,7 +35,7 @@ The [standard deviation][standard-deviation] for a [Gumbel][gumbel-distribution] ``` @@ -121,7 +121,7 @@ var opts = { var beta = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, SD(X;µ,β): %0.4f', mu, beta, stdev ); +logEachMap( 'μ: %0.4f, β: %0.4f, SD(X;μ,β): %0.4f', mu, beta, stdev ); ``` @@ -210,7 +210,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_stdev( mu, beta ); - printf( "µ: %lf, β: %lf, SD(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, SD(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/example.c index ca485f42d917..587f928bcbc0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_stdev( mu, beta ); - printf( "µ: %lf, β: %lf, SD(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, SD(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/index.js index e824d94b1f15..50ee87bd9e48 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/stdev/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, SD(X;µ,β): %0.4f', mu, beta, stdev ); +logEachMap( 'μ: %0.4f, β: %0.4f, SD(X;μ,β): %0.4f', mu, beta, stdev ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/README.md index cf04c3a03364..f8ae011eb7ed 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/README.md @@ -35,7 +35,7 @@ The [variance][variance] for a [Gumbel][gumbel-distribution] random variable wit ``` @@ -121,7 +121,7 @@ var opts = { var beta = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, Var(X;µ,β): %0.4f', mu, beta, variance ); +logEachMap( 'μ: %0.4f, β: %0.4f, Var(X;μ,β): %0.4f', mu, beta, variance ); ``` @@ -156,7 +156,7 @@ logEachMap( 'µ: %0.4f, β: %0.4f, Var(X;µ,β): %0.4f', mu, beta, variance ); #### stdlib_base_dists_gumbel_variance( mu, beta ) -Returns the variance for a Gumbel distribution with location `mu` and scale `beta`. +Returns the [variance][variance] for a [Gumbel][gumbel-distribution] distribution with location parameter `mu` and scale parameter `beta`. ```c double out = stdlib_base_dists_gumbel_variance( 0.0, 1.0 ); @@ -210,7 +210,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_variance( mu, beta ); - printf( "µ: %lf, β: %lf, Var(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Var(X;μ,β): %lf\n", mu, beta, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/c/example.c index c6f7e05318cb..d3a8bd623313 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); beta = random_uniform( 0.0, 20.0 ); y = stdlib_base_dists_gumbel_variance( mu, beta ); - printf( "µ: %lf, β: %lf, Var(X;µ,β): %lf\n", mu, beta, y ); + printf( "μ: %lf, β: %lf, Var(X;μ,β): %lf\n", mu, beta, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/index.js index 0419a89714de..0a6a0081eeed 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/variance/examples/index.js @@ -28,4 +28,4 @@ var opts = { var beta = uniform( 10, 0.0, 10.0, opts ); var mu = uniform( 10, -5.0, 5.0, opts ); -logEachMap( 'µ: %0.4f, β: %0.4f, Var(X;µ,β): %0.4f', mu, beta, variance ); +logEachMap( 'μ: %0.4f, β: %0.4f, Var(X;μ,β): %0.4f', mu, beta, variance ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/README.md index 7aefae2bf506..4d5b6a3bb59b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/README.md @@ -117,7 +117,7 @@ var opts = { }; var sigma = uniform( 10, 0.1, 20.0, opts ); -logEachMap( 'σ: %lf, E(X;σ): %lf', sigma, mean ); +logEachMap( 'σ: %0.4f, E(X;σ): %0.4f', sigma, mean ); ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/examples/index.js index 3d6bc95f791c..b0f0d4aaf2e7 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/halfnormal/mean/examples/index.js @@ -29,4 +29,4 @@ var opts = { // Generate positive scale parameters: var sigma = uniform( 10, 0.1, 20.0, opts ); -logEachMap( 'σ: %lf, E(X;σ): %lf', sigma, mean ); +logEachMap( 'σ: %0.4f, E(X;σ): %0.4f', sigma, mean ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/README.md index e08cce05a743..f46a2100811a 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/README.md @@ -147,6 +147,105 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/hypergeometric/kurtosis.h" +``` + +#### stdlib_base_dists_hypergeometric_kurtosis( N, K, n ) + +Returns the [excess kurtosis][kurtosis] of a [hypergeometric][hypergeometric-distribution] distribution with parameters `N` (population size), `K` (subpopulation size), and `n` (number of draws). + +```c +double out = stdlib_base_dists_hypergeometric_kurtosis( 16.0, 11.0, 4.0 ); +// returns ~-0.326 +``` + +The function accepts the following arguments: + +- **N**: `[in] double` population size. +- **K**: `[in] double` subpopulation size. +- **n**: `[in] double` number of draws. + +```c +double stdlib_base_dists_hypergeometric_kurtosis( const double N, const double K, const double n ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/hypergeometric/kurtosis.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double N; + double K; + double n; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + N = stdlib_base_ceil( random_uniform( 19.0, 100.0 ) ); + K = stdlib_base_ceil( random_uniform( 0.0, N - 1.0 ) ); + n = stdlib_base_ceil( random_uniform( 0.0, N - 1.0 ) ); + y = stdlib_base_dists_hypergeometric_kurtosis( N, K, n ); + printf( "N: %.0f, K: %.0f, n: %.0f, Kurt(X;N,K,n): %lf\n", N, K, n, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/benchmark.native.js new file mode 100644 index 000000000000..cf5afbc52717 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/benchmark.native.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kurtosis instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var len; + var N; + var K; + var n; + var y; + var i; + + len = 100; + N = new Float64Array( len ); + K = new Float64Array( len ); + n = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + N[ i ] = discreteUniform( 20, 100 ); + K[ i ] = discreteUniform( 1, N[ i ] - 1 ); + n[ i ] = discreteUniform( 1, N[ i ] - 1 ); + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = kurtosis( N[ i % len ], K[ i % len ], n[ i % len ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/c/benchmark.c new file mode 100644 index 000000000000..1592a9f2ab75 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/benchmark/c/benchmark.c @@ -0,0 +1,142 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/hypergeometric/kurtosis.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include +#include + +#define NAME "hypergeometric-kurtosis" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double elapsed; + double N[ 100 ]; + double K[ 100 ]; + double n[ 100 ]; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + N[ i ] = stdlib_base_ceil( random_uniform( 19.0, 100.0 ) ); + K[ i ] = stdlib_base_ceil( random_uniform( 0.0, N[ i ] - 1.0 ) ); + n[ i ] = stdlib_base_ceil( random_uniform( 0.0, N[ i ] - 1.0 ) ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_hypergeometric_kurtosis( N[ i % 100 ], K[ i % 100 ], n[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/examples/c/Makefile new file mode 100644 index 000000000000..3d90044357dc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/examples/c/example.c new file mode 100644 index 000000000000..e062be52ebb7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/examples/c/example.c @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/hypergeometric/kurtosis.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double N; + double K; + double n; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + N = stdlib_base_ceil( random_uniform( 19.0, 100.0 ) ); + K = stdlib_base_ceil( random_uniform( 0.0, N - 1.0 ) ); + n = stdlib_base_ceil( random_uniform( 0.0, N - 1.0 ) ); + y = stdlib_base_dists_hypergeometric_kurtosis( N, K, n ); + printf( "N: %.0f, K: %.0f, n: %.0f, Kurt(X;N,K,n): %lf\n", N, K, n, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' N || + n > N + ) { + return 0.0 / 0.0; // NaN + } + + // Calculate the numerator: (N-1) * N^2 * [N(N+1) - 6K(N-K) - 6n(N-n)] + 6nK(N-K)(N-n)(5N-6) + p = ( N - 1.0 ) * ( N * N ) * ( ( N * ( N + 1.0 ) ) - ( 6.0 * K * ( N - K ) ) - ( 6.0 * n * ( N - n ) ) ); + p += 6.0 * n * K * ( N - K ) * ( N - n ) * ( ( 5.0 * N ) - 6.0 ); + + // Calculate the denominator: n * K * (N-K) * (N-n) * (N-2) * (N-3) + q = n * K * ( N - K ) * ( N - n ) * ( N - 2.0 ) * ( N - 3.0 ); + + return p / q; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.native.js new file mode 100644 index 000000000000..633228f2fd9e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/kurtosis/test/test.native.js @@ -0,0 +1,154 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var EPS = require( '@stdlib/constants/float64/eps' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( kurtosis instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof kurtosis, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var v = kurtosis( NaN, 10.0, 5.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = kurtosis( 20.0, NaN, 5.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = kurtosis( 20.0, 10.0, NaN ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `N` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) { + var v; + + v = kurtosis( 10.5, 4.0, 2.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = kurtosis( -2.0, 4.0, 2.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = kurtosis( -1.0, 4.0, 2.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = kurtosis( 20.5, 10.0, 5.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + v = kurtosis( PINF, 10.0, 5.0 ); + t.strictEqual( isnan( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `K` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) { + var y; + + y = kurtosis( 20.0, 3.5, 10.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 20.0, -2.0, 10.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 20.0, -1.0, 10.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 20.0, 2.5, 10.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 20.0, PINF, 10.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided an `n` which is not a nonnegative integer, the function returns `NaN`', opts, function test( t ) { + var y; + + y = kurtosis( 40.0, 20.0, 3.5 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 40.0, 20.0, -2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 40.0, 20.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 40.0, 20.0, 2.5 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = kurtosis( 40.0, 20.0, PINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function returns the excess kurtosis of a hypergeometric distribution', opts, function test( t ) { + var expected; + var delta; + var tol; + var N; + var K; + var n; + var y; + var i; + + expected = data.expected; + N = data.N; + K = data.K; + n = data.n; + for ( i = 0; i < expected.length; i++ ) { + y = kurtosis( N[i], K[i], n[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'N: '+N[i]+', K: '+K[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] ); + } else { + delta = abs( y - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. N: '+N[i]+'. K: '+K[i]+'. n: '+n[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/entropy/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/invgamma/entropy/lib/main.js index 2351d731187e..de917ea50151 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/entropy/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/entropy/lib/main.js @@ -20,6 +20,7 @@ // MODULES // +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var digamma = require( '@stdlib/math/base/special/digamma' ); var gamma = require( '@stdlib/math/base/special/gamma' ); var ln = require( '@stdlib/math/base/special/ln' ); @@ -64,7 +65,12 @@ var ln = require( '@stdlib/math/base/special/ln' ); */ function entropy( alpha, beta ) { var out; - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } out = alpha + ln( beta*gamma( alpha ) ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/mean/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/invgamma/mean/lib/main.js index f1abcf2a9657..4001c7d32410 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/mean/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/mean/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -56,7 +61,12 @@ * // returns NaN */ function mean( alpha, beta ) { - if ( alpha <= 1.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 1.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } return beta / ( alpha - 1.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/mode/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/invgamma/mode/lib/main.js index 08074221bd49..0cd4e8441e27 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/mode/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/mode/lib/main.js @@ -18,6 +18,11 @@ 'use strict'; +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + // MAIN // /** @@ -56,7 +61,12 @@ * // returns NaN */ function mode( alpha, beta ) { - if ( alpha <= 0.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 0.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } return beta / ( alpha + 1.0 ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/stdev/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/invgamma/stdev/lib/main.js index 8df601fe42ec..6d63cc88d3bc 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/stdev/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/stdev/lib/main.js @@ -20,6 +20,7 @@ // MODULES // +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var sqrt = require( '@stdlib/math/base/special/sqrt' ); @@ -61,7 +62,12 @@ var sqrt = require( '@stdlib/math/base/special/sqrt' ); * // returns NaN */ function stdev( alpha, beta ) { - if ( alpha <= 2.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 2.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } return beta / ( ( alpha-1.0 ) * sqrt( alpha-2.0 ) ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/variance/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/invgamma/variance/lib/main.js index a40144d0afec..d9665c01f3a9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/variance/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/variance/lib/main.js @@ -20,6 +20,7 @@ // MODULES // +var isnan = require( '@stdlib/math/base/assert/is-nan' ); var pow = require( '@stdlib/math/base/special/pow' ); @@ -61,7 +62,12 @@ var pow = require( '@stdlib/math/base/special/pow' ); * // returns NaN */ function variance( alpha, beta ) { - if ( alpha <= 2.0 || beta <= 0.0 ) { + if ( + isnan( alpha ) || + alpha <= 2.0 || + isnan( beta ) || + beta <= 0.0 + ) { return NaN; } return ( beta*beta ) / ( pow( alpha-1.0, 2.0 ) * ( alpha-2.0 ) ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/README.md index 5c5bab9c18eb..9c2d149f8305 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/README.md @@ -33,7 +33,7 @@ F(x;\mu,b) =\tfrac{1}{2} + \tfrac{1}{2} \mathop{\mathrm{sgn}}(x-\mu) \left(1-\ex ``` @@ -124,7 +124,7 @@ var x = uniform( 100, 0.0, 10.0, opts ); var mu = uniform( 100, 0.0, 10.0, opts ); var b = uniform( 100, 0.0, 10.0, opts ); -logEachMap( 'x: %04f, µ: %04f, b: %04f, F(x;µ,b): %04f', x, mu, b, cdf ); +logEachMap( 'x: %04f, μ: %04f, b: %04f, F(x;μ,b): %04f', x, mu, b, cdf ); ```
@@ -216,7 +216,7 @@ int main( void ) { b = random_uniform( 0.0, 20.0 ); x = random_uniform( 0.0, 1.0 ); y = stdlib_base_dists_laplace_cdf( x, mu, b ); - printf( "x: %lf, µ: %lf, b: %lf, F(x;µ,b): %lf\n", x, mu, b, y ); + printf( "x: %lf, μ: %lf, b: %lf, F(x;μ,b): %lf\n", x, mu, b, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/docs/img/equation_laplace_cdf.svg b/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/docs/img/equation_laplace_cdf.svg index 9453c9aae3c1..6755e85811b1 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/docs/img/equation_laplace_cdf.svg +++ b/lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/docs/img/equation_laplace_cdf.svg @@ -1,5 +1,5 @@ -upper F left-parenthesis x semicolon mu comma b right-parenthesis equals one-half plus one-half s g n left-parenthesis x minus mu right-parenthesis left-parenthesis 1 minus exp left-parenthesis minus StartFraction StartAbsoluteValue x minus mu EndAbsoluteValue Over b EndFraction right-parenthesis right-parenthesis +upper F left-parenthesis x semicolon mu comma b right-parenthesis equals one half plus one half s g n left-parenthesis x minus mu right-parenthesis left-parenthesis 1 minus exp left-parenthesis minus StartFraction StartAbsoluteValue x minus mu EndAbsoluteValue Over b EndFraction right-parenthesis right-parenthesis Differential entropy for a lognormal distribution. + Differential entropy for a lognormal distribution.
--> @@ -124,7 +124,7 @@ var opts = { var mu = uniform( 10, -5.0, 5.0, opts ); var sigma = uniform( 10, 0.0, 20.0, opts ); -logEachMap( 'µ: %0.4f, σ: %0.4f, h(X;µ,σ): %0.4f', mu, sigma, entropy ); +logEachMap( 'μ: %0.4f, σ: %0.4f, h(X;μ,σ): %0.4f', mu, sigma, entropy ); ``` @@ -213,7 +213,7 @@ int main( void ) { mu = random_uniform( -5.0, 5.0 ); sigma = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_lognormal_entropy( mu, sigma ); - printf( "µ: %.4f, σ: %.4f, h(X;µ,σ): %.4f\n", mu, sigma, y ); + printf( "μ: %.4f, σ: %.4f, h(X;μ,σ): %.4f\n", mu, sigma, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/lognormal/entropy/docs/img/equation_lognormal_entropy.svg b/lib/node_modules/@stdlib/stats/base/dists/lognormal/entropy/docs/img/equation_lognormal_entropy.svg index 15291ef9e3ae..62cc0418859f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/lognormal/entropy/docs/img/equation_lognormal_entropy.svg +++ b/lib/node_modules/@stdlib/stats/base/dists/lognormal/entropy/docs/img/equation_lognormal_entropy.svg @@ -1,5 +1,5 @@ -h left-parenthesis upper X right-parenthesis equals ln left-parenthesis sigma e Superscript mu plus one-half Baseline StartRoot 2 pi EndRoot right-parenthesis +h left-parenthesis upper X right-parenthesis equals ln left-parenthesis sigma e Superscript mu plus one half Baseline StartRoot 2 pi EndRoot right-parenthesis [`entropy( lambda )`][@stdlib/stats/base/dists/planck/entropy]: planck (discrete exponential) distribution differential entropy. - [`kurtosis( lambda )`][@stdlib/stats/base/dists/planck/kurtosis]: planck (discrete exponential) distribution excess kurtosis. -- [`mean( lambda )`][@stdlib/stats/base/dists/planck/mean]: planck distribution expected value. +- [`mean( lambda )`][@stdlib/stats/base/dists/planck/mean]: planck (discrete exponential) distribution expected value. - [`median( lambda )`][@stdlib/stats/base/dists/planck/median]: planck (discrete exponential) distribution median. - [`mode( lambda )`][@stdlib/stats/base/dists/planck/mode]: planck (discrete exponential) distribution mode. - [`skewness( lambda )`][@stdlib/stats/base/dists/planck/skewness]: planck (discrete exponential) distribution skewness. -- [`stdev( lambda )`][@stdlib/stats/base/dists/planck/stdev]: planck distribution standard deviation. -- [`variance( lambda )`][@stdlib/stats/base/dists/planck/variance]: planck distribution variance. +- [`stdev( lambda )`][@stdlib/stats/base/dists/planck/stdev]: planck (discrete exponential) distribution standard deviation. +- [`variance( lambda )`][@stdlib/stats/base/dists/planck/variance]: planck (discrete exponential) distribution variance. diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/pmf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/poisson/pmf/lib/native.js index 8b4117f1dd83..81410b271f08 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/poisson/pmf/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/pmf/lib/native.js @@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' ); /** * Evaluates the probability mass function (PMF) for a Poisson distribution with mean parameter `lambda` at a value `x`. * +* @private * @param {number} x - input value * @param {NonNegativeNumber} lambda - mean parameter * @returns {Probability} evaluated PMF diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/README.md index b51d123b9a75..3a0cbfb060fa 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/README.md @@ -126,6 +126,102 @@ for ( i = 0; i < 10; i++ ) { + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/signrank/cdf.h" +``` + +#### stdlib_base_dists_signrank_cdf( x, n ) + +Evaluates the cumulative distribution function (CDF) of the Wilcoxon signed rank test statistic with `n` observations. + +```c +double out = stdlib_base_dists_signrank_cdf( 7.0, 9 ); +// returns ~0.037 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **n**: `[in] double` number of observations. + +```c +double stdlib_base_dists_signrank_cdf( const double x, const double n ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/signrank/cdf.h" +#include "stdlib/math/base/special/ceil" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double n; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0, 30.0 ); + n = stdlib_base_ceil( random_uniform( 1, 30.0 ) ); + y = stdlib_base_dists_signrank_cdf( x, n ); + printf( "x: %lf, n: %lf, F(x;n): %lf\n", x, n, y ); + } +} +``` + +
+ + + +
+ + +
diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/benchmark.js index 4b045b96c64e..687c7fb3bfeb 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/benchmark.js @@ -68,14 +68,13 @@ bench( format( '%s::factory', pkg ), function benchmark( b ) { n = 20; mycdf = cdf.factory( n ); - x = uniform( 100, 0.0, 20.0, { 'dtype': 'float64' }); b.tic(); for ( i = 0; i < b.iterations; i++ ) { - y = mycdf( x[ i%x.length ] ); + y = mycdf( x[ i % x.length ] ); if ( isnan( y ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..ca6392786bd2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/benchmark.native.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var discreteUniform = require( '@stdlib/random/array/discrete-uniform' ); +var format = require( '@stdlib/string/format' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var n; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, 0.0, 20.0, arrayOpts ); + n = discreteUniform( 100, 1, 20, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], n[ i % n.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..6dba9a3b5bea --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/benchmark/c/benchmark.c @@ -0,0 +1,141 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/signrank/cdf.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include +#include +#include +#include + +#define NAME "signrank-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double x[ 100 ]; + double n[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( 0, 20.0 ); + n[ i ] = stdlib_base_ceil( random_uniform( 1, 20.0 ) ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_signrank_cdf( x[ i % 100 ], n[ i % 100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/examples/c/example.c new file mode 100644 index 000000000000..cf7c3e5ed676 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/examples/c/example.c @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/signrank/cdf.h" +#include "stdlib/math/base/special/ceil.h" +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double x; + double n; + double y; + int i; + + for ( i = 0; i < 25; i++ ) { + x = random_uniform( 0, 30.0 ); + n = stdlib_base_ceil(random_uniform( 1, 30.0 )); + y = stdlib_base_dists_signrank_cdf( x, n ); + printf( "x: %lf, n: %lf, F(x;n): %lf\n", x, n, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + +/** +* Evaluates the cumulative distribution function (CDF) of the Wilcoxon signed rank test statistic with `n` observations. +* +* @param x input value +* @param n number of observations +* @return evaluated CDF +* +* @example +* double y = stdlib_base_dists_signrank_cdf( 7.0, 9.0 ); +* // returns ~0.037 +*/ +double stdlib_base_dists_signrank_cdf( const double x, const double n ) { + double pui; + double *w; + double xr; + double p; + int mlim; + int xi; + int i; + int j; + + if ( + stdlib_base_is_nan( x ) || + !stdlib_base_is_positive_integer( n ) || + !stdlib_base_is_finite( n ) + ) { + return 0.0 / 0.0; // NaN + } + if ( x < 0.0 ) { + return 0.0; + } + xr = stdlib_base_round( x ); + mlim = n * ( n + 1 ) / 2; + if ( xr >= mlim ) { + return 1.0; + } + xi = (int)xr; + // Compute the number of subsets of {1,...,n} summing to each value `0,...,xi` via dynamic programming (i.e., the weights of the signed rank distribution): + w = (double *)calloc( (size_t)xi + 1, sizeof( double ) ); + if ( w == NULL ) { + return 0.0 / 0.0; // NaN + } + w[ 0 ] = 1.0; + for ( i = 1; i <= (int)n; i++ ) { + for ( j = xi; j >= i; j-- ) { + w[ j ] += w[ j - i ]; + } + } + pui = stdlib_base_exp( -n * STDLIB_CONSTANT_FLOAT64_LN2 ); + p = 0.0; + for ( i = 0; i <= xi; i++ ) { + p += w[ i ] * pui; + } + free( w ); + return p; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.cdf.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.cdf.js index 16fd05e41529..5520065e44dd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.cdf.js +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.cdf.js @@ -22,10 +22,9 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var cdf = require( './../lib' ); @@ -82,8 +81,6 @@ tape( 'if not provided a positive integer for `n`, the function returns `NaN`', tape( 'the function evaluates the CDF for `x` given `n` observations', function test( t ) { var expected; - var delta; - var tol; var i; var x; var y; @@ -97,9 +94,7 @@ tape( 'the function evaluates the CDF for `x` given `n` observations', function if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 20.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. n: '+n[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'x: '+x[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.factory.js index 7589de8c65a9..115a13583ce0 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.factory.js +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.factory.js @@ -22,10 +22,9 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); -var abs = require( '@stdlib/math/base/special/abs' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); var PINF = require( '@stdlib/constants/float64/pinf' ); var NINF = require( '@stdlib/constants/float64/ninf' ); -var EPS = require( '@stdlib/constants/float64/eps' ); var factory = require( './../lib/factory.js' ); @@ -52,7 +51,7 @@ tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', var cdf; var y; - cdf = factory( 0.5 ); + cdf = factory( 1.0 ); y = cdf( NaN ); t.strictEqual( isnan( y ), true, 'returns expected value' ); @@ -109,9 +108,7 @@ tape( 'if not provided a positive integer for `n`, the created function always r tape( 'the created function evaluates the CDF for `x` given `n` observations', function test( t ) { var expected; - var delta; var cdf; - var tol; var i; var n; var x; @@ -126,9 +123,7 @@ tape( 'the created function evaluates the CDF for `x` given `n` observations', f if ( y === expected[i] ) { t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] ); } else { - delta = abs( y - expected[ i ] ); - tol = 20.0 * EPS * abs( expected[ i ] ); - t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. n: '+n[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' ); + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'x: '+x[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] ); } } t.end(); diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.native.js new file mode 100644 index 000000000000..dd1290963660 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/cdf/test/test.native.js @@ -0,0 +1,110 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// FIXTURES // + +var data = require( './fixtures/r/data.json' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = cdf( NaN, 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = cdf( 0.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a valid `n`, the function returns `1`', opts, function test( t ) { + var y = cdf( PINF, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `-infinity` for `x` and a valid `n`, the function returns `0`', opts, function test( t ) { + var y = cdf( NINF, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if not provided a positive integer for `n`, the function returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, 6.9 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, PINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the CDF for `x` given `n` observations', opts, function test( t ) { + var expected; + var i; + var x; + var y; + var n; + + expected = data.expected; + x = data.x; + n = data.n; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], n[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.strictEqual( isAlmostSameValue( y, expected[i], 1 ), true, 'x: '+x[i]+', n: '+n[i]+', y: '+y+', expected: '+expected[i] ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/native.js index fa8497fcb249..1f6343f8b286 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/native.js +++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/native.js @@ -28,6 +28,7 @@ var addon = require( './../src/addon.node' ); /** * Evaluates the probability density function (PDF) of the Wilcoxon signed rank test statistic with `n` observations. * +* @private * @param {number} x - input value * @param {PositiveInteger} n - number of observations * @returns {Probability} evaluated PDF diff --git a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/README.md index 7622749c92c1..2069472f7281 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/README.md @@ -34,7 +34,7 @@ f(x;\mu,\sigma,a,b) = \begin{cases} \frac{\frac{1}{\sigma}\phi(\frac{x - \mu}{\ ``` @@ -137,7 +137,7 @@ for ( i = 0; i < 25; i++ ) { mu = ( randu() * 20.0 ) - 10.0; sigma = ( randu() * 10.0 ) + 2.0; y = pdf( x, a, b, mu, sigma ); - console.log( 'x: %d, a: %d, b: %d, µ: %d, σ: %d, f(x;a,b,µ,σ): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), mu.toFixed( 4 ), sigma.toFixed( 4 ), y.toFixed( 4 ) ); + console.log( 'x: %d, a: %d, b: %d, μ: %d, σ: %d, f(x;a,b,μ,σ): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), mu.toFixed( 4 ), sigma.toFixed( 4 ), y.toFixed( 4 ) ); } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/examples/index.js index ed3e761529a6..ff2e8561eb89 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/examples/index.js @@ -36,5 +36,5 @@ for ( i = 0; i < 25; i++ ) { mu = ( randu() * 20.0 ) - 10.0; sigma = ( randu() * 10.0 ) + 2.0; y = pdf( x, a, b, mu, sigma ); - console.log( 'x: %d, a: %d, b: %d, µ: %d, σ: %d, f(x;a,b,µ,σ): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), mu.toFixed( 4 ), sigma.toFixed( 4 ), y.toFixed( 4 ) ); + console.log( 'x: %d, a: %d, b: %d, μ: %d, σ: %d, f(x;a,b,μ,σ): %d', x.toFixed( 4 ), a.toFixed( 4 ), b.toFixed( 4 ), mu.toFixed( 4 ), sigma.toFixed( 4 ), y.toFixed( 4 ) ); } diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/README.md new file mode 100644 index 000000000000..acda82d27642 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/README.md @@ -0,0 +1,279 @@ + + +# Cumulative Distribution Function + +> [Wald][wald-distribution] distribution [cumulative distribution function][cdf]. + +
+ +The [cumulative distribution function][cdf] for a [Wald][wald-distribution] random variable is + + + +```math +F(x;\mu,\lambda) = \Phi\!\left(\sqrt{\frac{\lambda}{x}}\left(\frac{x}{\mu}-1\right)\right) + \exp\!\left(\frac{2\lambda}{\mu}\right)\,\Phi\!\left(-\sqrt{\frac{\lambda}{x}}\left(\frac{x}{\mu}+1\right)\right) +``` + + + +where `μ > 0` is the mean and `λ > 0` is the shape parameter. + +
+ + + +
+ +## Usage + +```javascript +var cdf = require( '@stdlib/stats/base/dists/wald/cdf' ); +``` + +#### cdf( x, mu, lambda ) + +Evaluates the [cumulative distribution function][cdf] (CDF) for a [Wald][wald-distribution] distribution with parameters `mu` (mean) and `lambda` (shape parameter). + +```javascript +var y = cdf( 2.0, 2.0, 1.0 ); +// returns ~0.714 + +y = cdf( 1.0, 2.0, 1.0 ); +// returns ~0.490 + +y = cdf( 4.0, 2.0, 1.0 ); +// returns ~0.873 +``` + +If provided `NaN` as any argument, the function returns `NaN`. + +```javascript +var y = cdf( NaN, 2.0, 1.0 ); +// returns NaN + +y = cdf( 2.0, NaN, 1.0 ); +// returns NaN + +y = cdf( 2.0, 2.0, NaN ); +// returns NaN +``` + +If provided `mu <= 0` or `lambda < 0`, the function returns `NaN`. + +```javascript +var y = cdf( 2.0, 0.0, -3.0 ); +// returns NaN + +y = cdf( 2.0, -1.0, -2.0 ); +// returns NaN + +y = cdf( 2.0, -2.0, -1.0 ); +// returns NaN +``` + +If provided `x <= 0`, the function returns `0`. + +```javascript +var y = cdf( 0.0, 2.0, 1.0 ); +// returns 0.0 + +y = cdf( -1.0, 2.0, 1.0 ); +// returns 0.0 +``` + +If `lambda = 0`, the function evaluates the [CDF][cdf] of a [degenerate distribution][degenerate-distribution] centered at `mu`. + +```javascript +var y = cdf( 2.0, 8.0, 0.0 ); +// returns 0.0 + +y = cdf( 8.0, 8.0, 0.0 ); +// returns 1.0 + +y = cdf( 10.0, 8.0, 0.0 ); +// returns 1.0 +``` + +#### cdf.factory( mu, lambda ) + +Returns a function for evaluating the [cumulative distribution function][cdf] of a [Wald][wald-distribution] distribution with parameters `mu` and `lambda`. + +```javascript +var mycdf = cdf.factory( 1.0, 1.0 ); + +var y = mycdf( 2.0 ); +// returns ~0.885 + +y = mycdf( 8.0 ); +// returns ~0.999 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var cdf = require( '@stdlib/stats/base/dists/wald/cdf' ); + +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 10, EPS, 10.0, opts ); +var mu = uniform( 10, EPS, 10.0, opts ); +var lambda = uniform( 10, EPS, 20.0, opts ); + +logEachMap( 'x: %0.4f, μ: %0.4f, λ: %0.4f, F(x;μ,λ): %0.4f', x, mu, lambda, cdf ); +``` + +
+ + + + + +* * * + +
+ +## C APIs + + + +
+ +
+ + + + + +
+ +### Usage + +```c +#include "stdlib/stats/base/dists/wald/cdf.h" +``` + +#### stdlib_base_dists_wald_cdf( x, mu, lambda ) + +Evaluates the [cumulative distribution function][cdf] (CDF) for a [Wald][wald-distribution] distribution with parameters `mu` (mean) and `lambda` (shape parameter). + +```c +double out = stdlib_base_dists_wald_cdf( 2.0, 1.0, 1.0 ); +// returns ~0.885 +``` + +The function accepts the following arguments: + +- **x**: `[in] double` input value. +- **mu**: `[in] double` mean. +- **lambda**: `[in] double` shape parameter. + +```c +double stdlib_base_dists_wald_cdf( const double x, const double mu, const double lambda ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +### Examples + +```c +#include "stdlib/stats/base/dists/wald/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double lambda; + double mu; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + y = stdlib_base_dists_wald_cdf( x, mu, lambda ); + printf( "x: %lf, μ: %lf, λ: %lf, F(x;μ,λ): %lf\n", x, mu, lambda, y ); + } +} +``` + +
+ + + +
+ + + + + +
+ +
+ + + + + +
+ +[cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function + +[wald-distribution]: https://en.wikipedia.org/wiki/Inverse_Gaussian_distribution + +[degenerate-distribution]: https://en.wikipedia.org/wiki/Degenerate_distribution + +
+ + diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/benchmark.js new file mode 100644 index 000000000000..7e20f351c008 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/benchmark.js @@ -0,0 +1,90 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var cdf = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var arrayOpts; + var lambda; + var mu; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, arrayOpts ); + mu = uniform( 100, EPS, 50.0, arrayOpts ); + lambda = uniform( 100, EPS, 20.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], mu[ i % mu.length ], lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s:factory', pkg ), function benchmark( b ) { + var arrayOpts; + var mycdf; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + mycdf = cdf.factory( 1.0, 1.5 ); + x = uniform( 100, EPS, 10.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = mycdf( x[ i % x.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/benchmark.native.js new file mode 100644 index 000000000000..38e695506f18 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/benchmark.native.js @@ -0,0 +1,71 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// MAIN // + +bench( format( '%s::native', pkg ), opts, function benchmark( b ) { + var arrayOpts; + var lambda; + var mu; + var x; + var y; + var i; + + arrayOpts = { + 'dtype': 'float64' + }; + x = uniform( 100, EPS, 100.0, arrayOpts ); + mu = uniform( 100, EPS, 50.0, arrayOpts ); + lambda = uniform( 100, EPS, 20.0, arrayOpts ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + y = cdf( x[ i % x.length ], mu[ i % mu.length ], lambda[ i % lambda.length ] ); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( y ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/c/Makefile new file mode 100644 index 000000000000..979768abbcec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := benchmark.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled benchmarks. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/c/benchmark.c new file mode 100644 index 000000000000..124ce22d8f80 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/benchmark/c/benchmark.c @@ -0,0 +1,143 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/wald/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include +#include +#include + +#define NAME "wald-cdf" +#define ITERATIONS 1000000 +#define REPEATS 3 + +/** +* Prints the TAP version. +*/ +static void print_version( void ) { + printf( "TAP version 13\n" ); +} + +/** +* Prints the TAP summary. +* +* @param total total number of tests +* @param passing total number of passing tests +*/ +static void print_summary( int total, int passing ) { + printf( "#\n" ); + printf( "1..%d\n", total ); // TAP plan + printf( "# total %d\n", total ); + printf( "# pass %d\n", passing ); + printf( "#\n" ); + printf( "# ok\n" ); +} + +/** +* Prints benchmarks results. +* +* @param elapsed elapsed time in seconds +*/ +static void print_results( double elapsed ) { + double rate = (double)ITERATIONS / elapsed; + printf( " ---\n" ); + printf( " iterations: %d\n", ITERATIONS ); + printf( " elapsed: %0.9f\n", elapsed ); + printf( " rate: %0.9f\n", rate ); + printf( " ...\n" ); +} + +/** +* Returns a clock time. +* +* @return clock time +*/ +static double tic( void ) { + struct timeval now; + gettimeofday( &now, NULL ); + return (double)now.tv_sec + (double)now.tv_usec/1.0e6; +} + +/** +* Generates a random number on the interval [min,max). +* +* @param min minimum value (inclusive) +* @param max maximum value (exclusive) +* @return random number +*/ +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +/** +* Runs a benchmark. +* +* @return elapsed time in seconds +*/ +static double benchmark( void ) { + double lambda[ 100 ]; + double mu[ 100 ]; + double x[ 100 ]; + double elapsed; + double y; + double t; + int i; + + for ( i = 0; i < 100; i++ ) { + x[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 100.0 ); + mu[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 50.0 ); + lambda[ i ] = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); + } + + t = tic(); + for ( i = 0; i < ITERATIONS; i++ ) { + y = stdlib_base_dists_wald_cdf( x[ i%100 ], mu[ i%100 ], lambda[ i%100 ] ); + if ( y != y ) { + printf( "should not return NaN\n" ); + break; + } + } + elapsed = tic() - t; + if ( y != y ) { + printf( "should not return NaN\n" ); + } + return elapsed; +} + +/** +* Main execution sequence. +*/ +int main( void ) { + double elapsed; + int i; + + // Use the current time to seed the random number generator: + srand( time( NULL ) ); + + print_version(); + for ( i = 0; i < REPEATS; i++ ) { + printf( "# c::%s\n", NAME ); + elapsed = benchmark(); + print_results( elapsed ); + printf( "ok %d benchmark finished\n", i+1 ); + } + print_summary( REPEATS, REPEATS ); +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/binding.gyp new file mode 100644 index 000000000000..0d6508a12e99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/binding.gyp @@ -0,0 +1,170 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A `.gyp` file for building a Node.js native add-on. +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # List of files to include in this file: + 'includes': [ + './include.gypi', + ], + + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Target name should match the add-on export name: + 'addon_target_name%': 'addon', + + # Set variables based on the host OS: + 'conditions': [ + [ + 'OS=="win"', + { + # Define the object file suffix: + 'obj': 'obj', + }, + { + # Define the object file suffix: + 'obj': 'o', + } + ], # end condition (OS=="win") + ], # end conditions + }, # end variables + + # Define compile targets: + 'targets': [ + + # Target to generate an add-on: + { + # The target name should match the add-on export name: + 'target_name': '<(addon_target_name)', + + # Define dependencies: + 'dependencies': [], + + # Define directories which contain relevant include headers: + 'include_dirs': [ + # Local include directory: + '<@(include_dirs)', + ], + + # List of source files: + 'sources': [ + '<@(src_files)', + ], + + # Settings which should be applied when a target's object files are used as linker input: + 'link_settings': { + # Define libraries: + 'libraries': [ + '<@(libraries)', + ], + + # Define library directories: + 'library_dirs': [ + '<@(library_dirs)', + ], + }, + + # C/C++ compiler flags: + 'cflags': [ + # Enable commonly used warning options: + '-Wall', + + # Aggressive optimization: + '-O3', + ], + + # C specific compiler flags: + 'cflags_c': [ + # Specify the C standard to which a program is expected to conform: + '-std=c99', + ], + + # C++ specific compiler flags: + 'cflags_cpp': [ + # Specify the C++ standard to which a program is expected to conform: + '-std=c++11', + ], + + # Linker flags: + 'ldflags': [], + + # Apply conditions based on the host OS: + 'conditions': [ + [ + 'OS=="mac"', + { + # Linker flags: + 'ldflags': [ + '-undefined dynamic_lookup', + '-Wl,-no-pie', + '-Wl,-search_paths_first', + ], + }, + ], # end condition (OS=="mac") + [ + 'OS!="win"', + { + # C/C++ flags: + 'cflags': [ + # Generate platform-independent code: + '-fPIC', + ], + }, + ], # end condition (OS!="win") + ], # end conditions + }, # end target <(addon_target_name) + + # Target to copy a generated add-on to a standard location: + { + 'target_name': 'copy_addon', + + # Declare that the output of this target is not linked: + 'type': 'none', + + # Define dependencies: + 'dependencies': [ + # Require that the add-on be generated before building this target: + '<(addon_target_name)', + ], + + # Define a list of actions: + 'actions': [ + { + 'action_name': 'copy_addon', + 'message': 'Copying addon...', + + # Explicitly list the inputs in the command-line invocation below: + 'inputs': [], + + # Declare the expected outputs: + 'outputs': [ + '<(addon_output_dir)/<(addon_target_name).node', + ], + + # Define the command-line invocation: + 'action': [ + 'cp', + '<(PRODUCT_DIR)/<(addon_target_name).node', + '<(addon_output_dir)/<(addon_target_name).node', + ], + }, + ], # end actions + }, # end target copy_addon + ], # end targets +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/repl.txt new file mode 100644 index 000000000000..cdbfddaf8122 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/repl.txt @@ -0,0 +1,81 @@ + +{{alias}}( x, μ, λ ) + Evaluates the cumulative distribution function (CDF) for a Wald + distribution with mean `μ` and shape parameter `λ` at a value `x`. + + If provided `NaN` as any argument, the function returns `NaN`. + + If provided `μ <= 0`, the function returns `NaN`. + + If provided `λ < 0`, the function returns `NaN`. + + Parameters + ---------- + x: number + Input value. + + μ: number + Mean parameter. + + λ: number + Shape parameter. + + Returns + ------- + out: number + Evaluated CDF. + + Examples + -------- + > var y = {{alias}}( 2.0, 1.0, 1.0 ) + ~0.885 + > y = {{alias}}( 0.5, 2.0, 3.0 ) + ~0.055 + > y = {{alias}}( -1.0, 4.0, 2.0 ) + 0.0 + > y = {{alias}}( NaN, 1.0, 1.0 ) + NaN + > y = {{alias}}( 0.0, NaN, 1.0 ) + NaN + > y = {{alias}}( 0.0, 1.0, NaN ) + NaN + + // Negative shape parameter: + > y = {{alias}}( 2.0, 1.0, -1.0 ) + NaN + + // Degenerate distribution when `λ = 0.0`: + > y = {{alias}}( 2.0, 8.0, 0.0 ) + 0.0 + > y = {{alias}}( 8.0, 8.0, 0.0 ) + 1.0 + > y = {{alias}}( 10.0, 8.0, 0.0 ) + 1.0 + + +{{alias}}.factory( μ, λ ) + Returns a function for evaluating the cumulative distribution function (CDF) + of a Wald distribution with mean `μ` and shape parameter `λ`. + + Parameters + ---------- + μ: number + Mean parameter. + + λ: number + Shape parameter. + + Returns + ------- + cdf: Function + Cumulative distribution function (CDF). + + Examples + -------- + > var myCDF = {{alias}}.factory( 10.0, 2.0 ); + > var y = myCDF( 10.0 ) + ~0.777 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/types/index.d.ts new file mode 100644 index 000000000000..d53014e8b710 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/types/index.d.ts @@ -0,0 +1,121 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* Evaluates the cumulative distribution function (CDF) for a Wald distribution. +* +* @param x - input value +* @returns evaluated CDF +*/ +type Unary = ( x: number ) => number; + +/** +* Interface for the cumulative distribution function (CDF) of a Wald distribution. +*/ +interface CDF { + /** + * Evaluates the cumulative distribution function (CDF) for a Wald distribution with mean `mu` and shape parameter `lambda` at a value `x`. + * + * ## Notes + * + * - If provided `mu <= 0` or `lambda < 0`, the function returns `NaN`. + * + * @param x - input value + * @param mu - mean + * @param lambda - shape parameter + * @returns evaluated cumulative distribution function + * + * @example + * var y = cdf( 2.0, 1.0, 1.0 ); + * // returns ~0.885 + * + * @example + * var y = cdf( 0.5, 2.0, 3.0 ); + * // returns ~0.055 + * + * @example + * var y = cdf( NaN, 1.0, 1.0 ); + * // returns NaN + * + * @example + * var y = cdf( 0.0, NaN, 1.0 ); + * // returns NaN + * + * @example + * var y = cdf( 0.0, 1.0, NaN ); + * // returns NaN + * + * @example + * // Nonpositive mean: + * var y = cdf( 2.0, 0.0, 1.0 ); + * // returns NaN + * + * @example + * // Negative shape parameter: + * var y = cdf( 2.0, 1.0, -1.0 ); + * // returns NaN + * + * @example + * // Degenerate distribution when `lambda = 0.0`: + * var y = cdf( 2.0, 8.0, 0.0 ); + * // returns 0.0 + */ + ( x: number, mu: number, lambda: number ): number; + + /** + * Returns a function for evaluating the cumulative distribution function (CDF) for a Wald distribution. + * + * @param mu - mean + * @param lambda - shape parameter + * @returns function to evaluate the cumulative distribution function + * + * @example + * var myCDF = cdf.factory( 10.0, 2.0 ); + * var y = myCDF( 10.0 ); + * // returns ~0.777 + * + * y = myCDF( 12.0 ); + * // returns ~0.808 + */ + factory( mu: number, lambda: number ): Unary; +} + +/** +* Wald distribution cumulative distribution function (CDF). +* +* @param x - input value +* @param mu - mean +* @param lambda - shape parameter +* @returns evaluated CDF +* +* @example +* var y = cdf( 2.0, 1.0, 1.0 ); +* // returns ~0.885 +* +* var myCDF = cdf.factory( 10.0, 2.0 ); +* y = myCDF( 10.0 ); +* // returns ~0.777 +*/ +declare var cdf: CDF; + + +// EXPORTS // + +export = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/types/test.ts new file mode 100644 index 000000000000..68240f51cfb8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/docs/types/test.ts @@ -0,0 +1,119 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import cdf = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + cdf( 2, 2, 4 ); // $ExpectType number + cdf( 1, 2, 8 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided values other than three numbers... +{ + cdf( true, 3, 6 ); // $ExpectError + cdf( false, 2, 4 ); // $ExpectError + cdf( '5', 1, 2 ); // $ExpectError + cdf( [], 1, 2 ); // $ExpectError + cdf( {}, 2, 4 ); // $ExpectError + cdf( ( x: number ): number => x, 2, 4 ); // $ExpectError + + cdf( 9, true, 12 ); // $ExpectError + cdf( 9, false, 12 ); // $ExpectError + cdf( 5, '5', 10 ); // $ExpectError + cdf( 8, [], 16 ); // $ExpectError + cdf( 9, {}, 18 ); // $ExpectError + cdf( 8, ( x: number ): number => x, 16 ); // $ExpectError + + cdf( 9, 5, true ); // $ExpectError + cdf( 9, 5, false ); // $ExpectError + cdf( 5, 2, '5' ); // $ExpectError + cdf( 8, 4, [] ); // $ExpectError + cdf( 9, 4, {} ); // $ExpectError + cdf( 8, 5, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + cdf(); // $ExpectError + cdf( 2 ); // $ExpectError + cdf( 2, 0 ); // $ExpectError + cdf( 2, 0, 4, 1 ); // $ExpectError +} + +// Attached to main export is a `factory` method which returns a function... +{ + cdf.factory( 3, 4 ); // $ExpectType Unary +} + +// The `factory` method returns a function which returns a number... +{ + const fcn = cdf.factory( 3, 4 ); + fcn( 2 ); // $ExpectType number +} + +// The compiler throws an error if the function returned by the `factory` method is provided invalid arguments... +{ + const fcn = cdf.factory( 3, 4 ); + fcn( true ); // $ExpectError + fcn( false ); // $ExpectError + fcn( '5' ); // $ExpectError + fcn( [] ); // $ExpectError + fcn( {} ); // $ExpectError + fcn( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments... +{ + const fcn = cdf.factory( 3, 4 ); + fcn(); // $ExpectError + fcn( 2, 0 ); // $ExpectError + fcn( 2, 0, 1 ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided values other than two numbers... +{ + cdf.factory( true, 3 ); // $ExpectError + cdf.factory( false, 2 ); // $ExpectError + cdf.factory( '5', 1 ); // $ExpectError + cdf.factory( [], 1 ); // $ExpectError + cdf.factory( {}, 2 ); // $ExpectError + cdf.factory( ( x: number ): number => x, 2 ); // $ExpectError + + cdf.factory( 9, true ); // $ExpectError + cdf.factory( 9, false ); // $ExpectError + cdf.factory( 5, '5' ); // $ExpectError + cdf.factory( 8, [] ); // $ExpectError + cdf.factory( 9, {} ); // $ExpectError + cdf.factory( 8, ( x: number ): number => x ); // $ExpectError + + cdf.factory( [], true ); // $ExpectError + cdf.factory( {}, false ); // $ExpectError + cdf.factory( false, '5' ); // $ExpectError + cdf.factory( {}, [] ); // $ExpectError + cdf.factory( '5', ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `factory` method is provided an unsupported number of arguments... +{ + cdf.factory( 0 ); // $ExpectError + cdf.factory( 0, 4, 8 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/c/Makefile new file mode 100644 index 000000000000..c8f8e9a1517b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/c/Makefile @@ -0,0 +1,146 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + +# Define the program used for compiling C source files: +ifdef C_COMPILER + CC := $(C_COMPILER) +else + CC := gcc +endif + +# Define the command-line options when compiling C files: +CFLAGS ?= \ + -std=c99 \ + -O3 \ + -Wall \ + -pedantic + +# Determine whether to generate position independent code ([1][1], [2][2]). +# +# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options +# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option +ifeq ($(OS), WINNT) + fPIC ?= +else + fPIC ?= -fPIC +endif + +# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`): +INCLUDE ?= + +# List of source files: +SOURCE_FILES ?= + +# List of libraries (e.g., `-lopenblas -lpthread`): +LIBRARIES ?= + +# List of library paths (e.g., `-L /foo/bar -L /beep/boop`): +LIBPATH ?= + +# List of C targets: +c_targets := example.out + + +# RULES # + +#/ +# Compiles source files. +# +# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`) +# @param {string} [CFLAGS] - C compiler options +# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`) +# @param {string} [SOURCE_FILES] - list of source files +# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`) +# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`) +# +# @example +# make +# +# @example +# make all +#/ +all: $(c_targets) + +.PHONY: all + +#/ +# Compiles C source files. +# +# @private +# @param {string} CC - C compiler (e.g., `gcc`) +# @param {string} CFLAGS - C compiler options +# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`) +# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`) +# @param {string} SOURCE_FILES - list of source files +# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`) +# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`) +#/ +$(c_targets): %.out: %.c + $(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES) + +#/ +# Runs compiled examples. +# +# @example +# make run +#/ +run: $(c_targets) + $(QUIET) ./$< + +.PHONY: run + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: + $(QUIET) -rm -f *.o *.out + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/c/example.c new file mode 100644 index 000000000000..e69bfc2b0c28 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/c/example.c @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/wald/cdf.h" +#include "stdlib/constants/float64/eps.h" +#include +#include +#include + +static double random_uniform( const double min, const double max ) { + double v = (double)rand() / ( (double)RAND_MAX + 1.0 ); + return min + ( v*(max-min) ); +} + +int main( void ) { + double lambda; + double mu; + double x; + double y; + int i; + + for ( i = 0; i < 10; i++ ) { + x = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); + y = stdlib_base_dists_wald_cdf( x, mu, lambda ); + printf( "x: %lf, μ: %lf, λ: %lf, F(x;μ,λ): %lf\n", x, mu, lambda, y ); + } +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/index.js new file mode 100644 index 000000000000..36bfc1f2341f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/examples/index.js @@ -0,0 +1,33 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/array/uniform' ); +var logEachMap = require( '@stdlib/console/log-each-map' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var cdf = require( './../lib' ); + +var opts = { + 'dtype': 'float64' +}; +var x = uniform( 10, EPS, 10.0, opts ); +var mu = uniform( 10, EPS, 10.0, opts ); +var lambda = uniform( 10, EPS, 20.0, opts ); + +logEachMap( 'x: %0.4f, μ: %0.4f, λ: %0.4f, F(x;μ,λ): %0.4f', x, mu, lambda, cdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/include.gypi new file mode 100644 index 000000000000..bee8d41a2caf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/include.gypi @@ -0,0 +1,53 @@ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +# A GYP include file for building a Node.js native add-on. +# +# Main documentation: +# +# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md +# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md +{ + # Define variables to be used throughout the configuration for all targets: + 'variables': { + # Source directory: + 'src_dir': './src', + + # Include directories: + 'include_dirs': [ + ' + */ + function cdf( x ) { + var t1; + var t2; + var a; + var b; + var z; + + if ( isnan( x ) ) { + return NaN; + } + if ( x <= 0.0 ) { + return 0.0; + } + if ( x === PINF ) { + return 1.0; + } + z = sqrt( lambda / x ); + a = ( z * ( ( x / mu ) - 1.0 ) ) / sqrt( 2.0 ); + b = ( z * ( ( x / mu ) + 1.0 ) ) / sqrt( 2.0 ); + + // Φ(a) = 0.5 * erfc( -a / √2 ) + t1 = 0.5 * erfc( -a ); + + // exp( 2λ/μ ) * erfc( b ) = erfcx( b ) * exp( -a² ), as b² - a² = 2λ/μ; computing via `erfcx` avoids overflow of the exponential term for large `λ/μ`: + t2 = 0.5 * erfcx( b ) * exp( -a * a ); + return t1 + t2; + } +} + + +// EXPORTS // + +module.exports = factory; diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/index.js new file mode 100644 index 000000000000..0855c01e086e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/index.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Wald distribution cumulative distribution function (CDF). +* +* @module @stdlib/stats/base/dists/wald/cdf +* +* @example +* var cdf = require( '@stdlib/stats/base/dists/wald/cdf' ); +* +* var y = cdf( 2.0, 1.0, 1.0 ); +* // returns ~0.885 +* +* var myCDF = cdf.factory( 2.0, 1.0 ); +* y = myCDF( 2.0 ); +* // returns ~0.714 +*/ + +// MODULES // + +var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); +var main = require( './main.js' ); +var factory = require( './factory.js' ); + + +// MAIN // + +setReadOnly( main, 'factory', factory ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/main.js new file mode 100644 index 000000000000..f768db738e7d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/main.js @@ -0,0 +1,120 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var erfcx = require( '@stdlib/math/base/special/erfcx' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var erfc = require( '@stdlib/math/base/special/erfc' ); +var exp = require( '@stdlib/math/base/special/exp' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); + + +// MAIN // + +/** +* Evaluates the cumulative distribution function (CDF) for a Wald distribution with mean `mu` and shape parameter `lambda` at a value `x`. +* +* @param {number} x - input value +* @param {PositiveNumber} mu - mean +* @param {NonNegativeNumber} lambda - shape parameter +* @returns {Probability} evaluated cumulative distribution function +* +* @example +* var y = cdf( 2.0, 1.0, 1.0 ); +* // returns ~0.885 +* +* @example +* var y = cdf( 0.5, 2.0, 3.0 ); +* // returns ~0.055 +* +* @example +* var y = cdf( NaN, 1.0, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 1.0, NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 1.0, 1.0, NaN ); +* // returns NaN +* +* @example +* // Non-positive mean: +* var y = cdf( 2.0, 0.0, 1.0 ); +* // returns NaN +* +* @example +* // Negative shape parameter: +* var y = cdf( 2.0, 1.0, -1.0 ); +* // returns NaN +* +* @example +* // Zero shape parameter (degenerate distribution): +* var y = cdf( 1.0, 1.0, 0.0 ); +* // returns 1.0 +* +* @example +* var y = cdf( 0.0, 1.0, 1.0 ); +* // returns 0.0 +*/ +function cdf( x, mu, lambda ) { + var t1; + var t2; + var a; + var b; + var z; + + if ( + isnan( x ) || + isnan( mu ) || + isnan( lambda ) || + mu <= 0.0 || + lambda < 0.0 + ) { + return NaN; + } + if ( lambda === 0.0 ) { + return ( x < mu ) ? 0.0 : 1.0; + } + if ( x <= 0.0 ) { + return 0.0; + } + if ( x === PINF ) { + return 1.0; + } + z = sqrt( lambda / x ); + a = ( z * ( ( x / mu ) - 1.0 ) ) / sqrt( 2.0 ); + b = ( z * ( ( x / mu ) + 1.0 ) ) / sqrt( 2.0 ); + + // Φ(a) = 0.5 * erfc( -a / sqrt( 2 ) ) + t1 = 0.5 * erfc( -a ); + + // exp( 2λ/μ ) * erfc( b ) = erfcx( b ) * exp( -a² ), as b² - a² = 2λ/μ; computing via `erfcx` avoids overflow of the exponential term for large `λ/μ`: + t2 = 0.5 * erfcx( b ) * exp( -a * a ); + return t1 + t2; +} + + +// EXPORTS // + +module.exports = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/native.js new file mode 100644 index 000000000000..1aa8fd4406dd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/lib/native.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var addon = require( './../src/addon.node' ); + + +// MAIN // + +/** +* Evaluates the cumulative distribution function (CDF) for a Wald distribution with mean `mu` and shape parameter `lambda` at a value `x`. +* +* @private +* @param {number} x - input value +* @param {PositiveNumber} mu - mean +* @param {number} lambda - shape parameter +* @returns {Probability} evaluated cumulative distribution function +* +* @example +* var y = cdf( 2.0, 1.0, 1.0 ); +* // returns ~0.885 +* +* @example +* var y = cdf( 0.5, 2.0, 3.0 ); +* // returns ~0.055 +* +* @example +* var y = cdf( NaN, 1.0, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 1.0, NaN, 1.0 ); +* // returns NaN +* +* @example +* var y = cdf( 1.0, 1.0, NaN ); +* // returns NaN +* +* @example +* // Non-positive mean: +* var y = cdf( 2.0, 0.0, 1.0 ); +* // returns NaN +* +* @example +* // Negative shape parameter: +* var y = cdf( 2.0, 1.0, -1.0 ); +* // returns NaN +* +* @example +* // Zero shape parameter (degenerate distribution): +* var y = cdf( 1.0, 1.0, 0.0 ); +* // returns 1.0 +* +* @example +* var y = cdf( 0.0, 1.0, 1.0 ); +* // returns 0.0 +*/ +function cdf( x, mu, lambda ) { + return addon( x, mu, lambda ); +} + + +// EXPORTS // + +module.exports = cdf; diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/manifest.json new file mode 100644 index 000000000000..7ef9331bcf97 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/manifest.json @@ -0,0 +1,93 @@ +{ + "options": { + "task": "build", + "wasm": false + }, + "fields": [ + { + "field": "src", + "resolve": true, + "relative": true + }, + { + "field": "include", + "resolve": true, + "relative": true + }, + { + "field": "libraries", + "resolve": false, + "relative": false + }, + { + "field": "libpath", + "resolve": true, + "relative": false + } + ], + "confs": [ + { + "task": "build", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/napi/ternary", + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/erfcx", + "@stdlib/math/base/special/erfc", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/pinf" + ] + }, + { + "task": "benchmark", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/erfcx", + "@stdlib/math/base/special/erfc", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/eps" + ] + }, + { + "task": "examples", + "wasm": false, + "src": [ + "./src/main.c" + ], + "include": [ + "./include" + ], + "libraries": [], + "libpath": [], + "dependencies": [ + "@stdlib/math/base/assert/is-nan", + "@stdlib/math/base/special/erfcx", + "@stdlib/math/base/special/erfc", + "@stdlib/math/base/special/sqrt", + "@stdlib/math/base/special/exp", + "@stdlib/constants/float64/pinf", + "@stdlib/constants/float64/eps" + ] + } + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/package.json b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/package.json new file mode 100644 index 000000000000..9930aedb6bb3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/base/dists/wald/cdf", + "version": "0.0.0", + "description": "Wald distribution cumulative distribution function (CDF).", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "gypfile": true, + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "include": "./include", + "lib": "./lib", + "src": "./src", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "distribution", + "dist", + "probability", + "cdf", + "cumulative distribution", + "distribution function", + "inverse gaussian", + "inverse-gaussian", + "wald", + "univariate", + "continuous" + ] +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/Makefile new file mode 100644 index 000000000000..2caf905cedbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/Makefile @@ -0,0 +1,70 @@ +#/ +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +#/ + +# VARIABLES # + +ifndef VERBOSE + QUIET := @ +else + QUIET := +endif + +# Determine the OS ([1][1], [2][2]). +# +# [1]: https://en.wikipedia.org/wiki/Uname#Examples +# [2]: http://stackoverflow.com/a/27776822/2225624 +OS ?= $(shell uname) +ifneq (, $(findstring MINGW,$(OS))) + OS := WINNT +else +ifneq (, $(findstring MSYS,$(OS))) + OS := WINNT +else +ifneq (, $(findstring CYGWIN,$(OS))) + OS := WINNT +else +ifneq (, $(findstring Windows_NT,$(OS))) + OS := WINNT +endif +endif +endif +endif + + +# RULES # + +#/ +# Removes generated files for building an add-on. +# +# @example +# make clean-addon +#/ +clean-addon: + $(QUIET) -rm -f *.o *.node + +.PHONY: clean-addon + +#/ +# Removes generated files. +# +# @example +# make clean +#/ +clean: clean-addon + +.PHONY: clean diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/addon.c new file mode 100644 index 000000000000..3ae24c620f82 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/addon.c @@ -0,0 +1,22 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/wald/cdf.h" +#include "stdlib/math/base/napi/ternary.h" + +STDLIB_MATH_BASE_NAPI_MODULE_DDD_D( stdlib_base_dists_wald_cdf ) diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/main.c new file mode 100644 index 000000000000..540fac1a8549 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/src/main.c @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +#include "stdlib/stats/base/dists/wald/cdf.h" +#include "stdlib/math/base/assert/is_nan.h" +#include "stdlib/math/base/special/erfcx.h" +#include "stdlib/math/base/special/sqrt.h" +#include "stdlib/math/base/special/erfc.h" +#include "stdlib/math/base/special/exp.h" +#include "stdlib/constants/float64/pinf.h" + +/** +* Evaluates the cumulative distribution function (CDF) for a Wald distribution with mean `mu` and shape parameter `lambda` at a value `x`. +* +* @param x input value +* @param mu mean +* @param lambda shape parameter +* @return evaluated cumulative distribution function +* +* @example +* double y = stdlib_base_dists_wald_cdf( 2.0, 1.0, 1.0 ); +* // returns ~0.885 +*/ +double stdlib_base_dists_wald_cdf( const double x, const double mu, const double lambda ) { + double t1; + double t2; + double a; + double b; + double z; + + if ( + stdlib_base_is_nan( x ) || + stdlib_base_is_nan( mu ) || + stdlib_base_is_nan( lambda ) || + mu <= 0.0 || + lambda < 0.0 + ) { + return 0.0 / 0.0; // NaN + } + if ( lambda == 0.0 ) { + return ( x < mu ) ? 0.0 : 1.0; + } + if ( x <= 0.0 ) { + return 0.0; + } + if ( x == STDLIB_CONSTANT_FLOAT64_PINF ) { + return 1.0; + } + z = stdlib_base_sqrt( lambda / x ); + a = ( z * ( ( x / mu ) - 1.0 ) ) / stdlib_base_sqrt( 2.0 ); + b = ( z * ( ( x / mu ) + 1.0 ) ) / stdlib_base_sqrt( 2.0 ); + + // Φ(a) = 0.5 * erfc( -a / sqrt( 2 ) ) + t1 = 0.5 * stdlib_base_erfc( -a ); + + // exp( 2λ/μ ) * erfc( b ) = erfcx( b ) * exp( -a² ), as b² - a² = 2λ/μ; computing via `erfcx` avoids overflow of the exponential term for large `λ/μ`: + t2 = 0.5 * stdlib_base_erfcx( b ) * stdlib_base_exp( -a * a ); + return t1 + t2; +} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/REQUIRE new file mode 100644 index 000000000000..98be20b58ed3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/REQUIRE @@ -0,0 +1,3 @@ +Distributions 0.23.8 +julia 1.5 +JSON 0.21 diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/data.json b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/data.json new file mode 100644 index 000000000000..ddb9531d856f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/data.json @@ -0,0 +1 @@ +{"expected":[0.956031860972232,0.7222410074214104,0.8388262233512366,0.8063887690741013,0.8993139816208725,0.8754608601606477,0.999857458956787,0.5446625611270753,0.9999219753683246,0.7007193572895988,0.05086146646705278,0.9609072030079305,0.9252233812473168,0.7958070715252243,0.8856198861175603,0.8616320127365377,0.5569342708856,0.6376098409431302,0.8121774439437746,0.5858488156886867,0.8171722709992562,0.6660520279350101,0.768927369212703,0.8409556904974325,0.3930698331676592,0.9089425375062343,0.800636475911108,0.9423977609194308,0.9732221977795502,0.8791812378672993,0.7866151725297192,0.6962333142145349,0.98350473578428,0.5792110472701381,0.7789599352514637,0.8630046536813258,0.9234734033401704,0.93882411947924,0.8684156693232986,0.41248050205809866,0.9192555074415594,0.9592077588644018,0.8394361950927777,0.860700802122654,0.9999999999949734,0.996688525144456,0.8918301639069863,0.847082670992373,0.7535769524105298,0.7924197892407122,0.9741000985461694,0.9996560104745966,0.9218095060200042,0.9710744180680723,0.7018774730314714,0.7405146608193169,0.27411061858629243,0.7333264345523395,0.9999999987532546,0.8914927886458963,0.7883964267140454,0.9999999942442925,0.9135916155064817,1.0,0.4319246946453399,0.9250238576511429,0.7860620958440139,0.6831537509896327,0.80676499801222,0.9939896265478079,0.9324940259747342,0.8793211283380593,0.6514949014453674,0.764372969376012,0.9009677859775579,0.658985893632694,0.8725109653410115,0.5214717769434215,0.9783763207358217,0.9563876792800233,0.9999999975726171,0.9092384901183699,0.9998834526817215,0.9481714276277563,0.8415257350164043,0.8882108308915957,0.7087396828351278,0.9999999999863065,0.874653119480443,0.9314179379685698,0.9986242241761004,0.9999999998862069,1.0,0.9244768544152053,0.9980933741882426,0.7448978634354545,1.0,0.9999914987850471,0.7974936479566863,0.9726371937648199],"x":[13.339281437460926,8.912977822167623,7.957102979390953,12.35436075718989,12.339969578719508,9.426438819747993,7.668296686294445,2.1692153609558864,3.4011347534176264,4.316025794292218,0.9229530194288167,12.963376756163369,12.579123639323475,9.42877594141134,13.138345132228055,14.638348080601085,3.2260969229502034,1.9913522817051794,12.776384124822453,5.024551384281849,2.7721049432643445,2.3868544647055563,5.257862949798037,13.812211159458977,2.4862822750483264,14.590746978893641,6.4403741375779155,12.611340074957582,6.457315339899419,13.825962721789326,4.452905814552913,7.692526981282094,10.546791344686156,3.1270439637182728,4.834256558797152,6.077225515583834,14.585076117850093,7.962641893506339,10.58892375842925,3.0697152886318437,13.33067599052857,15.01262679185554,5.152307422328827,8.872690692769739,15.154656348820843,9.01678384855629,12.393058949720189,12.06997916590109,8.003819435019004,11.948335659807748,13.713030468065579,5.1479634590575944,15.340185710069127,6.9659536427799145,3.0455122037183604,4.905635731970286,0.6814221257735477,4.215139415441513,10.11901634772521,14.889324187414767,8.156143098870603,11.271219164804084,5.202777507536254,15.229988224497541,1.9923931965184833,13.904761893546372,8.021688402301471,6.589330870271463,9.787917171979615,11.198896805725724,4.617404483308332,11.210732912052421,4.064462822290395,5.6565954384854065,10.46528011160431,5.1957240537306,11.974906110785032,3.680827180042188,12.591779723408235,9.011386213102261,15.050092105608336,13.426827000980886,14.794174426259755,14.377462361122904,8.558162962971371,12.638995058209323,2.4246318923228096,3.9757011380532896,13.369756594138892,13.845018861840108,11.299472587885253,11.644206825711048,15.377602790237713,15.468280067699677,9.38039592535914,7.1861475106420345,6.961492820897222,13.69799515148088,10.549343020608445,13.861341125809924],"lambda":[5.417493694832523,3.5238789952256355,3.5826503423369296,4.184161736888616,0.8192276763027957,3.8234223345936043,5.24402809615151,2.309116620114125,4.931035351845412,3.697177902023129,4.501040152049077,0.824316365749665,1.2608698335750619,3.898962176748363,1.9071768838155563,1.0661200524023957,1.737892413325985,1.0848520354174775,3.0524265066226564,4.53590051159232,1.5104329780565457,0.7030050012556267,4.170922611811294,4.18321781425974,4.493616146773953,1.5484848673662235,1.0672123408307272,2.550969419066164,4.240019299144688,2.1981332587295075,0.6206860389947129,5.135115262868535,3.0702149233353544,1.5707969073148815,1.5000651539453742,1.5176015099584297,3.5864184276547055,1.0268631923725597,0.8463599628736713,4.548706801031815,2.875127608083551,0.6875958040761105,1.3430356528748306,1.0547237778575038,2.9663969613697834,4.698529152765462,0.5210199539475586,2.173072691108242,2.7356096134666825,2.752535763924649,1.7634914482320796,3.7626355853845452,0.5800087175995862,4.959236947028113,1.525834277516708,0.7858374963721533,1.2274214567711716,0.7113886242245666,5.43845371287312,0.7690464980421842,1.4177051259025553,5.232575917856365,1.0883665720453035,5.1262093477379915,3.854078463131324,0.6832137945767492,2.0050045722480188,3.6146711847936275,1.9224041853642089,1.433517350792024,1.2181291874967266,3.7132086033156604,2.2047841616030497,4.234870757836539,5.488042283848636,2.1830671389382292,0.8362336779732822,3.4350849308482485,1.5279102835798999,5.377250049346257,3.160931851557253,3.4603513066608573,2.2861637737327833,4.603233814395376,1.5377032103904522,1.4260707211992152,0.988941315869017,5.382372903686453,5.414570172697367,3.7333515739305314,1.1346820229529104,2.1663751137306297,3.6307189578704184,1.1245714812983527,2.011184331744004,4.334090729997929,4.6898987995397,3.135883299543926,1.6494665397527486,0.6962598250060021],"mu":[4.5771270178283565,9.3038859744059,4.751722281845909,8.622974877299928,5.365916778152899,4.803906912583415,1.5325534802851288,3.2224329281058823,0.8644822375289214,4.011919264456063,6.823244256201491,2.778350896580743,4.150228657173185,6.766276040985014,6.042580299851276,10.208458752908047,8.658156905045317,2.835350340487461,9.145377871783827,6.887255654961294,1.8038160785970498,5.147573707948909,3.992401134498663,8.176927813847698,4.793060487504502,5.568353900405826,5.758055021819357,4.050259728920674,2.2345142248166567,6.647223601651859,5.341113052143289,7.635005091794672,2.623011728366624,7.510277907433075,3.969683058783067,3.212129974556723,5.481133786015191,2.418478449916674,6.403403094251223,6.376906389977452,5.037231671293051,3.095048794125324,3.0990537808571776,5.13411445216048,0.9674224972726893,2.1326067610011186,7.245593011100204,7.202350251207326,7.384763227640857,9.867527626581284,2.9942318005224298,1.1199702230489568,5.41025396282806,2.500518259740811,3.221200261662754,10.194295014059612,2.6719688263393477,9.034951928168692,1.1548691956614061,7.804069225669068,7.982762972431228,1.2588672904070015,2.0276911410334892,0.7361314763042155,3.2147938658289905,4.523033556030375,6.728967197191859,7.363485284959012,7.692277686051631,1.759800837729782,1.6645332784000517,5.51699948211175,5.365498592468808,4.367273775239145,4.948392272389236,7.829106616414316,7.2822988911752935,6.61862674845449,2.5674119529149104,3.38556043542913,1.1554783727393232,5.514779981695591,1.6138025966888931,4.9021119688877945,5.315381522103928,5.762061122219851,2.6969213971232806,0.6069810825927209,6.836374954246834,5.043637672806245,1.310431194116007,0.7800923422731771,0.8212929183510083,5.040283626021764,1.5125599301679544,6.054329705696015,0.5186875283592192,1.4946400377219333,10.083078015018645,2.4084751094236774]} diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/runner.jl new file mode 100644 index 000000000000..3dbbd982f396 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/fixtures/julia/runner.jl @@ -0,0 +1,77 @@ +#!/usr/bin/env julia +# +# @license Apache-2.0 +# +# Copyright (c) 2026 The Stdlib Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import Distributions: cdf, InverseGaussian +import JSON + +""" + gen( x, mu, lambda, name ) + +Generate fixture data and write to file. + +# Arguments + +* `x`: input value +* `mu`: mean +* `lambda`: shape parameter +* `name::AbstractString`: output filename + +# Examples + +``` julia +julia> x = rand( 100 ) .* 15.0 .+ 0.5; +julia> mu = rand( 100 ) .* 10.0 .+ 0.5; +julia> lambda = rand( 100 ) .* 5.0 .+ 0.5; +julia> gen( x, mu, lambda, "data.json" ); +``` +""" +function gen( x, mu, lambda, name ) + z = Array{Float64}( undef, length(x) ); + for i in eachindex(x) + z[ i ] = cdf( InverseGaussian( mu[i], lambda[i] ), x[i] ); + end + + # Store data to be written to file as a collection: + data = Dict([ + ("x", x), + ("mu", mu), + ("lambda", lambda), + ("expected", z) + ]); + + # Based on the script directory, create an output filepath: + filepath = joinpath( dir, name ); + + # Write the data to the output filepath as JSON: + outfile = open( filepath, "w" ); + write( outfile, JSON.json(data) ); + write( outfile, "\n" ); + close( outfile ); +end + +# Get the filename: +file = @__FILE__; + +# Extract the directory in which this file resides: +dir = dirname( file ); + +# Generate fixtures: +x = rand( 100 ) .* 15.0 .+ 0.5; +mu = rand( 100 ) .* 10.0 .+ 0.5; +lambda = rand( 100 ) .* 5.0 .+ 0.5; +gen( x, mu, lambda, "data.json" ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.factory.js new file mode 100644 index 000000000000..d7e5b66df745 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.factory.js @@ -0,0 +1,198 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var factory = require( './../lib/factory.js' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof factory, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns a function', function test( t ) { + var cdf = factory( 1.0, 1.0 ); + t.strictEqual( typeof cdf, 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( 1.0, 1.0 ); + y = cdf( NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, 1.0 ); + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( 1.0, NaN ); + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, NaN ); + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, NaN ); + y = cdf( NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a valid `mu` and `lambda`, the function returns a function which returns `1` when provided `+infinity` for `x`', function test( t ) { + var cdf; + var y; + + cdf = factory( 1.0, 0.0 ); + y = cdf( PINF ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + cdf = factory( 1.0, 1.0 ); + y = cdf( PINF ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a valid `mu` and `lambda`, the function returns a function which returns `0` when provided `-infinity` for `x`', function test( t ) { + var cdf; + var y; + + cdf = factory( 1.0, 0.0 ); + y = cdf( NINF ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + cdf = factory( 1.0, 1.0 ); + y = cdf( NINF ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a nonpositive `mu`, the created function always returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.0, 1.0 ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( -1.0, 1.0 ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NINF, 1.0 ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a negative `lambda`, the created function always returns `NaN`', function test( t ) { + var cdf; + var y; + + cdf = factory( 0.0, -1.0 ); + + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( 0.0, NINF ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( PINF, NINF ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NINF, NINF ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + cdf = factory( NaN, NINF ); + y = cdf( 2.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if `lambda` equals `0`, the created function evaluates a degenerate distribution centered at `mu`', function test( t ) { + var cdf; + var y; + + cdf = factory( 2.0, 0.0 ); + + y = cdf( 2.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( 3.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given parameters `mu` and `lambda`', function test( t ) { + var expected; + var lambda; + var cdf; + var mu; + var x; + var y; + var i; + + expected = data.expected; + x = data.x; + mu = data.mu; + lambda = data.lambda; + for ( i = 0; i < x.length; i++ ) { + cdf = factory( mu[i], lambda[i] ); + y = cdf( x[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 5 ), 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.js new file mode 100644 index 000000000000..85a2b4b63e97 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var cdf = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'attached to the main export is a factory method for generating `cdf` functions', function test( t ) { + t.strictEqual( typeof cdf.factory, 'function', 'exports a factory method' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.main.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.main.js new file mode 100644 index 000000000000..af78c5f98dec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.main.js @@ -0,0 +1,149 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var cdf = require( './../lib' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) { + var y = cdf( NaN, 1.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = cdf( 0.0, NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = cdf( 0.0, 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `mu`, the function always returns `NaN`', function test( t ) { + var y; + + y = cdf( 2.0, 0.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, -1.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a valid `mu` and `lambda`, the function returns `1`', function test( t ) { + var y = cdf( PINF, 1.0, 0.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( PINF, 1.0, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `-infinity` for `x` and a valid `mu` and `lambda`, the function returns `0`', function test( t ) { + var y = cdf( NINF, 1.0, 0.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + y = cdf( NINF, 1.0, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a negative `lambda`, the function always returns `NaN`', function test( t ) { + var y; + + y = cdf( 2.0, 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, 0.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `lambda` equals `0`, the function evaluates a degenerate distribution centered at `mu`', function test( t ) { + var y; + + y = cdf( 2.0, 2.0, 0.0 ); + t.strictEqual( y, 1.0, 'returns 1 for x equal to mu' ); + + y = cdf( 3.0, 2.0, 0.0 ); + t.strictEqual( y, 1.0, 'returns 1 for x greater than mu' ); + + y = cdf( 1.0, 2.0, 0.0 ); + t.strictEqual( y, 0.0, 'returns 0 for x smaller than mu' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given parameters `mu` and `lambda`', function test( t ) { + var expected; + var lambda; + var mu; + var i; + var x; + var y; + + expected = data.expected; + x = data.x; + mu = data.mu; + lambda = data.lambda; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], mu[i], lambda[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 5 ), 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.native.js new file mode 100644 index 000000000000..9a3edc7dfaae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/cdf/test/test.native.js @@ -0,0 +1,158 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var tape = require( 'tape' ); +var tryRequire = require( '@stdlib/utils/try-require' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); + + +// FIXTURES // + +var data = require( './fixtures/julia/data.json' ); + + +// VARIABLES // + +var cdf = tryRequire( resolve( __dirname, './../lib/native.js' ) ); +var opts = { + 'skip': ( cdf instanceof Error ) +}; + + +// TESTS // + +tape( 'main export is a function', opts, function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof cdf, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) { + var y = cdf( NaN, 1.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = cdf( 0.0, NaN, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + y = cdf( 0.0, 1.0, NaN ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided a nonpositive `mu`, the function always returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 0.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, -1.0, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, 1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `+infinity` for `x` and a valid `mu` and `lambda`, the function returns `1`', opts, function test( t ) { + var y = cdf( PINF, 1.0, 0.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + y = cdf( PINF, 1.0, 1.0 ); + t.strictEqual( y, 1.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `-infinity` for `x` and a valid `mu` and `lambda`, the function returns `0`', opts, function test( t ) { + var y = cdf( NINF, 1.0, 0.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + y = cdf( NINF, 1.0, 1.0 ); + t.strictEqual( y, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a negative `lambda`, the function always returns `NaN`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 0.0, 0.0, -1.0 ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, 0.0, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, PINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NINF, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + y = cdf( 2.0, NaN, NINF ); + t.strictEqual( isnan( y ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `lambda` equals `0`, the function evaluates a degenerate distribution centered at `mu`', opts, function test( t ) { + var y; + + y = cdf( 2.0, 2.0, 0.0 ); + t.strictEqual( y, 1.0, 'returns 1 for x equal to mu' ); + + y = cdf( 3.0, 2.0, 0.0 ); + t.strictEqual( y, 1.0, 'returns 1 for x greater than mu' ); + + y = cdf( 1.0, 2.0, 0.0 ); + t.strictEqual( y, 0.0, 'returns 0 for x smaller than mu' ); + + t.end(); +}); + +tape( 'the function evaluates the cdf for `x` given parameters `mu` and `lambda`', opts, function test( t ) { + var expected; + var lambda; + var mu; + var x; + var y; + var i; + + expected = data.expected; + x = data.x; + mu = data.mu; + lambda = data.lambda; + for ( i = 0; i < x.length; i++ ) { + y = cdf( x[i], mu[i], lambda[i] ); + if ( y === expected[i] ) { + t.strictEqual( y, expected[i], 'x: '+x[i]+', mu:'+mu[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] ); + } else { + t.ok( isAlmostSameValue( y, expected[ i ], 5 ), 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/README.md index 390d9d2bf89e..206bb9a6fd05 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/README.md @@ -35,6 +35,8 @@ The [excess kurtosis][kurtosis] for a [Wald][wald-distribution] random variable ``` @@ -123,7 +125,7 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, Kurtosis(X;µ,λ): %0.4f', mu, lambda, kurtosis ); +logEachMap( 'μ: %0.4f, λ: %0.4f, Kurtosis(X;μ,λ): %0.4f', mu, lambda, kurtosis ); ```
@@ -212,7 +214,7 @@ int main( void ) { mu = random_uniform( 0.1, 5.0 ); lambda = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_wald_kurtosis( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, Kurtosis(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, Kurtosis(X;μ,λ): %.4f\n", mu, lambda, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/docs/img/equation_wald_kurtosis.svg b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/docs/img/equation_wald_kurtosis.svg new file mode 100644 index 000000000000..3a75d73ae4cd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/docs/img/equation_wald_kurtosis.svg @@ -0,0 +1,40 @@ + +normal upper K times normal u times normal r times normal t left-parenthesis upper X right-parenthesis equals StartFraction 15 mu Over lamda EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/c/example.c index 8274e65f08c4..217b39c0ac4c 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( 0.1, 10.0 ); lambda = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_wald_kurtosis( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, Kurtosis(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, Kurtosis(X;μ,λ): %.4f\n", mu, lambda, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/index.js index 190d738d1cfa..f77afb561804 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/kurtosis/examples/index.js @@ -29,4 +29,4 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, Kurtosis(X;µ,λ): %0.4f', mu, lambda, kurtosis ); +logEachMap( 'μ: %0.4f, λ: %0.4f, Kurtosis(X;μ,λ): %0.4f', mu, lambda, kurtosis ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mean/README.md b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/README.md index 8c4fc5c3c186..19e7d3b85664 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/mean/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/README.md @@ -35,7 +35,7 @@ The [expected value][mean] for a [Wald][wald-distribution] random variable with ``` @@ -125,7 +125,7 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, E(X;µ,λ): %0.4f', mu, lambda, mean ); +logEachMap( 'μ: %0.4f, λ: %0.4f, E(X;μ,λ): %0.4f', mu, lambda, mean ); ``` @@ -214,7 +214,7 @@ int main( void ) { mu = random_uniform( 0.1, 5.0 ); lambda = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_wald_mean( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, Mean(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, Mean(X;μ,λ): %.4f\n", mu, lambda, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mean/docs/img/equation_wald_expectation.svg b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/docs/img/equation_wald_expectation.svg new file mode 100644 index 000000000000..01cbe489f072 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/docs/img/equation_wald_expectation.svg @@ -0,0 +1,21 @@ + +double-struck upper E left-bracket upper X right-bracket equals mu + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/c/example.c index bd1fc1f63b32..0209dcb90576 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/c/example.c @@ -35,7 +35,7 @@ int main( void ) { mu = random_uniform( 0.1, 10.0 ); lambda = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_wald_mean( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, Mean(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, Mean(X;μ,λ): %.4f\n", mu, lambda, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/index.js index 05d0707d539f..ce907d40fcf9 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mean/examples/index.js @@ -29,4 +29,4 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, E(X;µ,λ): %0.4f', mu, lambda, mean ); +logEachMap( 'μ: %0.4f, λ: %0.4f, E(X;μ,λ): %0.4f', mu, lambda, mean ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/README.md index d499b6b1887e..c2bb4d393bce 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/README.md @@ -35,6 +35,8 @@ The [mode][mode] for a [Wald][wald-distribution] random variable with mean `μ` ``` @@ -126,7 +128,7 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, mode(X;µ,λ): %0.4f', mu, lambda, mode ); +logEachMap( 'μ: %0.4f, λ: %0.4f, mode(X;μ,λ): %0.4f', mu, lambda, mode ); ``` @@ -216,7 +218,7 @@ int main( void ) { mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_wald_mode( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, mode(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, mode(X;μ,λ): %.4f\n", mu, lambda, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mode/docs/img/equation_wald_mode.svg b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/docs/img/equation_wald_mode.svg new file mode 100644 index 000000000000..5630e3f7d435 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/docs/img/equation_wald_mode.svg @@ -0,0 +1,66 @@ + +m o d e left-parenthesis upper X right-parenthesis equals mu dot StartFraction StartRoot 4 lamda squared plus 9 mu squared EndRoot minus 3 mu Over 2 lamda EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/c/example.c index 572a7f099e64..50b08e1c5b44 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/c/example.c @@ -36,6 +36,6 @@ int main( void ) { mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_wald_mode( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, mode(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, mode(X;μ,λ): %.4f\n", mu, lambda, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/index.js index cd7cc0634ab7..2f732f1d7136 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/mode/examples/index.js @@ -29,4 +29,4 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, mode(X;µ,λ): %0.4f', mu, lambda, mode ); +logEachMap( 'μ: %0.4f, λ: %0.4f, mode(X;μ,λ): %0.4f', mu, lambda, mode ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/README.md index f54eeb8a7a2c..5e32d7248bde 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/README.md @@ -33,13 +33,13 @@ f(x;\mu,\lambda) = \sqrt{\frac{\lambda}{2\pi x^3}}\, e^{-\frac{\lambda(x-\mu)^2} ``` -where `µ > 0` is the mean and `λ > 0` is the shape parameter. +where `μ > 0` is the mean and `λ > 0` is the shape parameter. @@ -152,7 +152,7 @@ var x = uniform( 10, EPS, 10.0, opts ); var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, λ: %0.4f, f(x;µ,λ): %0.4f', x, mu, lambda, pdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, λ: %0.4f, f(x;μ,λ): %0.4f', x, mu, lambda, pdf ); ``` @@ -245,7 +245,7 @@ int main( void ) { mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_wald_pdf( x, mu, lambda ); - printf( "x: %lf, µ: %lf, λ: %lf, f(x;µ,λ): %lf\n", x, mu, lambda, y ); + printf( "x: %lf, μ: %lf, λ: %lf, f(x;μ,λ): %lf\n", x, mu, lambda, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/docs/img/equation_wald_pdf.svg b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/docs/img/equation_wald_pdf.svg new file mode 100644 index 000000000000..7ab008f436b1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/docs/img/equation_wald_pdf.svg @@ -0,0 +1,79 @@ + +f left-parenthesis x semicolon mu comma lamda right-parenthesis equals StartRoot StartFraction lamda Over 2 pi x cubed EndFraction EndRoot e Superscript minus StartFraction lamda left-parenthesis x minus mu right-parenthesis squared Over 2 mu squared x EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/c/example.c index 1a6151c1af25..73675dd6df56 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/c/example.c @@ -38,6 +38,6 @@ int main( void ) { mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); y = stdlib_base_dists_wald_pdf( x, mu, lambda ); - printf( "x: %lf, µ: %lf, λ: %lf, f(x;µ,λ): %lf\n", x, mu, lambda, y ); + printf( "x: %lf, μ: %lf, λ: %lf, f(x;μ,λ): %lf\n", x, mu, lambda, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/index.js index 5b1dcd564552..cd3c85c8412e 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/examples/index.js @@ -30,4 +30,4 @@ var x = uniform( 10, EPS, 10.0, opts ); var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'x: %0.4f, µ: %0.4f, λ: %0.4f, f(x;µ,λ): %0.4f', x, mu, lambda, pdf ); +logEachMap( 'x: %0.4f, μ: %0.4f, λ: %0.4f, f(x;μ,λ): %0.4f', x, mu, lambda, pdf ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/README.md index 82a0c62dab4a..059b11b895de 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/README.md @@ -35,6 +35,8 @@ The [skewness][skewness] for a [Wald][wald-distribution] random variable with me ``` @@ -123,7 +125,7 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, skew(X;µ,λ): %0.4f', mu, lambda, skewness ); +logEachMap( 'μ: %0.4f, λ: %0.4f, skew(X;μ,λ): %0.4f', mu, lambda, skewness ); ``` @@ -212,7 +214,7 @@ int main( void ) { mu = random_uniform( 0.1, 5.0 ); lambda = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_wald_skewness( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, skew(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, skew(X;μ,λ): %.4f\n", mu, lambda, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/docs/img/equation_wald_skewness.svg b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/docs/img/equation_wald_skewness.svg new file mode 100644 index 000000000000..c1227f034801 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/docs/img/equation_wald_skewness.svg @@ -0,0 +1,41 @@ + +s k e w left-parenthesis upper X right-parenthesis equals 3 StartRoot StartFraction mu Over lamda EndFraction EndRoot + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/c/example.c index 66dedb057fa3..49d0befbd7e6 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/c/example.c @@ -35,6 +35,6 @@ int main( void ) { mu = random_uniform( 0.1, 10.0 ); lambda = random_uniform( 0.1, 20.0 ); y = stdlib_base_dists_wald_skewness( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, skew(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, skew(X;μ,λ): %.4f\n", mu, lambda, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/index.js index 9fa2060e6e3a..c4e72293965d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/skewness/examples/index.js @@ -29,4 +29,4 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, skew(X;µ,λ): %0.4f', mu, lambda, skewness ); +logEachMap( 'μ: %0.4f, λ: %0.4f, skew(X;μ,λ): %0.4f', mu, lambda, skewness ); diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/README.md b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/README.md index c0e0af038e7b..328429d5621d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/README.md @@ -31,9 +31,14 @@ The [variance][variance] for a [Wald][wald-distribution] random variable with me ```math -\operatorname{Var}\left[ X \right] = \frac{\mu^{3}}{\lambda} +\mathop{\mathrm{Var}}\left[ X \right] = \frac{\mu^{3}}{\lambda} ``` + + @@ -120,7 +125,7 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, Var(X;µ,λ): %0.4f', mu, lambda, variance ); +logEachMap( 'μ: %0.4f, λ: %0.4f, Var(X;μ,λ): %0.4f', mu, lambda, variance ); ``` @@ -210,7 +215,7 @@ int main( void ) { mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 5.0 ); lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_wald_variance( mu, lambda ); - printf( "µ: %.4f, λ: %.4f, Var(X;µ,λ): %.4f\n", mu, lambda, y ); + printf( "μ: %.4f, λ: %.4f, Var(X;μ,λ): %.4f\n", mu, lambda, y ); } } ``` diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/docs/img/equation_wald_variance.svg b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/docs/img/equation_wald_variance.svg new file mode 100644 index 000000000000..be7ed08560bd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/docs/img/equation_wald_variance.svg @@ -0,0 +1,36 @@ + +upper V a r left-bracket upper X right-bracket equals StartFraction mu cubed Over lamda EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/c/example.c index 37c548066992..a6f751f9321d 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/c/example.c @@ -36,6 +36,6 @@ int main( void ) { mu = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 10.0 ); lambda = random_uniform( STDLIB_CONSTANT_FLOAT64_EPS, 20.0 ); y = stdlib_base_dists_wald_variance( mu, lambda ); - printf( "µ: %lf, λ: %lf, Var(X;µ,λ): %lf\n", mu, lambda, y ); + printf( "μ: %lf, λ: %lf, Var(X;μ,λ): %lf\n", mu, lambda, y ); } } diff --git a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/index.js index f0a5164862df..993aec73b66b 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/index.js +++ b/lib/node_modules/@stdlib/stats/base/dists/wald/variance/examples/index.js @@ -29,4 +29,4 @@ var opts = { var mu = uniform( 10, EPS, 10.0, opts ); var lambda = uniform( 10, EPS, 20.0, opts ); -logEachMap( 'µ: %0.4f, λ: %0.4f, Var(X;µ,λ): %0.4f', mu, lambda, variance ); +logEachMap( 'μ: %0.4f, λ: %0.4f, Var(X;μ,λ): %0.4f', mu, lambda, variance ); diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/lib/main.js index ea3c92660060..af3a9c7c5021 100755 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dmediansorted/lib/main.js @@ -24,7 +24,7 @@ var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' ); var getStride = require( '@stdlib/ndarray/base/stride' ); var getOffset = require( '@stdlib/ndarray/base/offset' ); var getData = require( '@stdlib/ndarray/base/data-buffer' ); -var strided = require( '@stdlib/stats/strided/dmediansorted' ).ndarray; +var strided = require( '@stdlib/stats/strided/dmedian-sorted' ).ndarray; // MAIN // diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/package.json index d0a4753d0bff..b2c3c3967098 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmax/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmax", "version": "0.0.0", - "description": "Compute the maximum value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the maximum value of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/package.json index d48dfde608b4..18f113478f20 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmaxabs", "version": "0.0.0", - "description": "Compute the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/package.json index bec37c4a0605..e594f256214d 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmean/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmean", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/package.json index ecb62ed8b1b0..81fe96eb9659 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmeanors", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using ordinary recursive summation.", + "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/package.json index dd62a6518be1..3ac0352ec449 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmeanpn", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using a two-pass error correction algorithm.", + "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using a two-pass error correction algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/package.json index 2eed4496d250..fe6783b6dedd 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanpw/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmeanpw", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using pairwise summation.", + "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using pairwise summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/package.json index 1b28a3b07598..5e45d3d5ad65 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmeanwd/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmeanwd", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values and using Welford's algorithm.", + "description": "Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray, ignoring NaN values and using Welford's algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/package.json index 0cec11e29555..34ff00b5b7eb 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmin/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmin", "version": "0.0.0", - "description": "Compute the minimum value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the minimum value of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/package.json index 411ddd6bf374..dbed742bd311 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanminabs", "version": "0.0.0", - "description": "Compute the minimum value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the minimum value of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/package.json index 376e175f0242..52c42ed9534c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmax/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmskmax", "version": "0.0.0", - "description": "Compute the maximum value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values.", + "description": "Compute the maximum value of a double-precision floating-point ndarray according to a mask, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmaxabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmaxabs/package.json index be4f18c3c2ff..7a9bcf0f9ad5 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmaxabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmaxabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmskmaxabs", "version": "0.0.0", - "description": "Compute the maximum absolute value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values.", + "description": "Compute the maximum absolute value of a double-precision floating-point ndarray according to a mask, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/package.json index a2c09835411d..6a7664b9464a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskmin/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmskmin", "version": "0.0.0", - "description": "Compute the minimum value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values.", + "description": "Compute the minimum value of a double-precision floating-point ndarray according to a mask, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskminabs/package.json index e9d13b3726a0..8aea22d07ae8 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskminabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmskminabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanmskminabs", "version": "0.0.0", - "description": "Compute the minimum absolute value of a double-precision floating-point ndarray according to a mask, ignoring `NaN` values.", + "description": "Compute the minimum absolute value of a double-precision floating-point ndarray according to a mask, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/package.json index 243d72bbf48c..2198e756ce5e 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanrange/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanrange", "version": "0.0.0", - "description": "Compute the range of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the range of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanrangeabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanrangeabs/package.json index 0801647bd053..992c4ba30246 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dnanrangeabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanrangeabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/dnanrangeabs", "version": "0.0.0", - "description": "Compute the range of absolute values of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the range of absolute values of a one-dimensional double-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dztest/docs/types/index.d.ts index 9cda1727ce38..9c9a4e6730a3 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dztest/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest/docs/types/index.d.ts @@ -20,7 +20,7 @@ /// -import { float64ndarray, int8ndarray, ndarray } from '@stdlib/types/ndarray'; +import { float64ndarray, ndarray } from '@stdlib/types/ndarray'; /** * Computes a one-sample Z-test for a one-dimensional double-precision floating-point ndarray. @@ -78,7 +78,7 @@ import { float64ndarray, int8ndarray, ndarray } from '@stdlib/types/ndarray'; * * console.log( v.get().toString() ); */ -declare function dztest( arrays: [ float64ndarray, T, int8ndarray, float64ndarray, float64ndarray, float64ndarray ] ): T; +declare function dztest( arrays: [ float64ndarray, T, ndarray, float64ndarray, float64ndarray, float64ndarray ] ): T; // EXPORTS // diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/index.d.ts index 54e721e5bbad..7b9840ef29cb 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/ndarray/dztest2/docs/types/index.d.ts @@ -82,7 +82,7 @@ import { float64ndarray, ndarray } from '@stdlib/types/ndarray'; * * console.log( v.get().toString() ); */ -declare function dztest2( arrays: [ float64ndarray, float64ndarray, T, float64ndarray, float64ndarray, float64ndarray, float64ndarray, float64ndarray ] ): T; +declare function dztest2( arrays: [ float64ndarray, float64ndarray, T, ndarray, float64ndarray, float64ndarray, float64ndarray, float64ndarray ] ): T; // EXPORTS // diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/package.json index 8e2be64676c0..47ebd40e289d 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmax/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmax", "version": "0.0.0", - "description": "Compute the maximum value of a one-dimensional ndarray, ignoring `NaN` values.", + "description": "Compute the maximum value of a one-dimensional ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/package.json index bdaa0573294e..4b9ba1b31923 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmaxabs", "version": "0.0.0", - "description": "Compute the maximum absolute value of a one-dimensional ndarray, ignoring `NaN` values.", + "description": "Compute the maximum absolute value of a one-dimensional ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmean/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmean/package.json index 97d1ba0f0006..40785e925f2a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmean/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmean/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmean", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring `NaN` values.", + "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanors/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanors/package.json index d687c472466e..d106f767c07b 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanors/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmeanors", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring `NaN` values and using ordinary recursive summation.", + "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring NaN values and using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanpn/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanpn/package.json index f8b8d0e85090..b7dc8aa894f3 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanpn/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanpn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmeanpn", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring `NaN` values and using a two-pass error correction algorithm.", + "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring NaN values and using a two-pass error correction algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/package.json index 78ea50e97888..ec5cccdf6961 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmeanwd/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmeanwd", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring `NaN` values and using Welford's algorithm.", + "description": "Compute the arithmetic mean of a one-dimensional ndarray, ignoring NaN values and using Welford's algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange-by/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange-by/package.json index 59ef8d21e11b..eee4d21aef42 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange-by/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmidrange-by/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmidrange-by", "version": "0.0.0", - "description": "Calculate the mid-range of a one-dimensional ndarray via a callback function, ignoring `NaN` values.", + "description": "Calculate the mid-range of a one-dimensional ndarray via a callback function, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/package.json index 451b0bb6cf5a..2e7d74ac416c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmin/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanmin", "version": "0.0.0", - "description": "Compute the minimum value of a one-dimensional ndarray, ignoring `NaN` values.", + "description": "Compute the minimum value of a one-dimensional ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/package.json index 3db3a7259477..3557ac7f732f 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanminabs", "version": "0.0.0", - "description": "Compute the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values.", + "description": "Compute the minimum absolute value of a one-dimensional ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/package.json index ce11feb58efc..df3c6c7b1812 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange-by/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanrange-by", "version": "0.0.0", - "description": "Compute the range of a one-dimensional ndarray via a callback function, ignoring `NaN` values.", + "description": "Compute the range of a one-dimensional ndarray via a callback function, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/package.json index 5611f44ed065..d761ec791e36 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanrange/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/nanrange", "version": "0.0.0", - "description": "Compute the range of a one-dimensional ndarray, ignoring `NaN` values.", + "description": "Compute the range of a one-dimensional ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmax/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmax/package.json index 686e51dfc50c..df8990a6704b 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmax/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmax/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmax", "version": "0.0.0", - "description": "Compute the maximum value of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the maximum value of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/package.json index ed8d66682bf5..ad3fc98f0a0c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmaxabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmaxabs", "version": "0.0.0", - "description": "Compute the maximum absolute value of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the maximum absolute value of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/package.json index 1ac2e0f64e66..f8adbcc232ab 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmean/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmean", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/package.json index 1d52a0b5f5d1..4bfb57b7f92e 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmeanors", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using ordinary recursive summation.", + "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/package.json index 2239acb3a977..53ea95334811 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanpn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmeanpn", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using a two-pass error correction algorithm.", + "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using a two-pass error correction algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/package.json index e89a7681ccd2..0fb224d31df9 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmeanwd/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmeanwd", "version": "0.0.0", - "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using Welford's algorithm.", + "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using Welford's algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmidrange/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmidrange/package.json index 839fc402c3fc..baef99bfde84 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmidrange/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmidrange/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmidrange", "version": "0.0.0", - "description": "Compute the mid-range of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the mid-range of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/package.json index b33cf7cd464b..fcd3f2475181 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanmin/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanmin", "version": "0.0.0", - "description": "Compute the minimum value of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the minimum value of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/package.json index 03ec7763aa97..d551c3eb814a 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanminabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanminabs", "version": "0.0.0", - "description": "Compute the minimum absolute value of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the minimum absolute value of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/snanrange/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/snanrange/package.json index 433b8396091b..fade056be8a6 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/snanrange/package.json +++ b/lib/node_modules/@stdlib/stats/base/ndarray/snanrange/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/base/ndarray/snanrange", "version": "0.0.0", - "description": "Compute the range of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values.", + "description": "Compute the range of a one-dimensional single-precision floating-point ndarray, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/docs/types/index.d.ts index a6318d03114e..5ab837b1ab7c 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sztest/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest/docs/types/index.d.ts @@ -20,7 +20,7 @@ /// -import { float32ndarray, int8ndarray, ndarray } from '@stdlib/types/ndarray'; +import { float32ndarray, ndarray } from '@stdlib/types/ndarray'; /** * Computes a one-sample Z-test for a one-dimensional single-precision floating-point ndarray. @@ -78,7 +78,7 @@ import { float32ndarray, int8ndarray, ndarray } from '@stdlib/types/ndarray'; * * console.log( v.get().toString() ); */ -declare function sztest( arrays: [ float32ndarray, T, int8ndarray, float32ndarray, float32ndarray, float32ndarray ] ): T; +declare function sztest( arrays: [ float32ndarray, T, ndarray, float32ndarray, float32ndarray, float32ndarray ] ): T; // EXPORTS // diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/docs/types/index.d.ts index 854ff53e8a62..90a345fdcca6 100644 --- a/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/base/ndarray/sztest2/docs/types/index.d.ts @@ -82,7 +82,7 @@ import { float32ndarray, ndarray } from '@stdlib/types/ndarray'; * * console.log( v.get().toString() ); */ -declare function sztest2( arrays: [ float32ndarray, float32ndarray, T, float32ndarray, float32ndarray, float32ndarray, float32ndarray, float32ndarray ] ): T; +declare function sztest2( arrays: [ float32ndarray, float32ndarray, T, ndarray, float32ndarray, float32ndarray, float32ndarray, float32ndarray ] ): T; // EXPORTS // diff --git a/lib/node_modules/@stdlib/stats/base/ztest/alternative-enum2str/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ztest/alternative-enum2str/docs/repl.txt index 468a3e674ed6..de66f1275d5b 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/alternative-enum2str/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/ztest/alternative-enum2str/docs/repl.txt @@ -15,7 +15,9 @@ Examples -------- - > var out = {{alias}}( {{alias:@stdlib/stats/base/ztest/alternative-str2enum}}( 'two-sided' ) ) + > var str = 'two-sided'; + > var v = {{alias:@stdlib/stats/base/ztest/alternative-str2enum}}( str ); + > var out = {{alias}}( v ) 'two-sided' See Also diff --git a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/docs/repl.txt index 6613b1c78fdc..1170d9ed2826 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-enum/docs/repl.txt @@ -19,9 +19,11 @@ Examples -------- - > var out = {{alias}}( 'two-sided' ) + > var str = 'two-sided'; + > var out = {{alias}}( str ) - > out = {{alias}}( {{alias:@stdlib/stats/base/ztest/alternative-str2enum}}( 'two-sided' ) ) + > var v = {{alias:@stdlib/stats/base/ztest/alternative-str2enum}}( str ); + > out = {{alias}}( v ) See Also diff --git a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/docs/repl.txt index 842f3b6e47b4..c2b9793429d7 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/base/ztest/alternative-resolve-str/docs/repl.txt @@ -15,9 +15,11 @@ Examples -------- - > var out = {{alias}}( 'greater' ) + > var str = 'greater'; + > var out = {{alias}}( str ) 'greater' - > out = {{alias}}( {{alias:@stdlib/stats/base/ztest/alternative-str2enum}}( 'greater' ) ) + > var v = {{alias:@stdlib/stats/base/ztest/alternative-str2enum}}( str ); + > out = {{alias}}( v ) 'greater' See Also diff --git a/lib/node_modules/@stdlib/stats/base/ztest/alternatives/test/test.js b/lib/node_modules/@stdlib/stats/base/ztest/alternatives/test/test.js index a0ef6719dac3..84c015ad4351 100644 --- a/lib/node_modules/@stdlib/stats/base/ztest/alternatives/test/test.js +++ b/lib/node_modules/@stdlib/stats/base/ztest/alternatives/test/test.js @@ -68,7 +68,7 @@ tape( 'attached to the main function is an `enum` method to return an object map ]; for ( i = 0; i < o.length; i++ ) { t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' ); - t.strictEqual( isNonNegativeInteger( obj[ o[i] ] ), true, 'returns expected value' ); + t.strictEqual( isNonNegativeInteger( obj[ o[ i ] ] ), true, 'returns expected value' ); } t.end(); diff --git a/lib/node_modules/@stdlib/stats/incr/mgmean/README.md b/lib/node_modules/@stdlib/stats/incr/mgmean/README.md index 531630d29e5a..788baa198061 100644 --- a/lib/node_modules/@stdlib/stats/incr/mgmean/README.md +++ b/lib/node_modules/@stdlib/stats/incr/mgmean/README.md @@ -33,7 +33,7 @@ The [geometric mean][geometric-mean] is defined as the nth root of a product of ``` @@ -61,7 +61,7 @@ var accumulator = incrmgmean( 3 ); #### accumulator( \[x] ) -If provided an input value `x`, the accumulator function returns an updated [geometric mean][geometric-mean]. If not provided an input value `x`, the accumulator function returns the current [geometric-mean][geometric-mean]. +If provided an input value `x`, the accumulator function returns an updated [geometric mean][geometric-mean]. If not provided an input value `x`, the accumulator function returns the current [geometric mean][geometric-mean]. ```javascript var accumulator = incrmgmean( 3 ); diff --git a/lib/node_modules/@stdlib/stats/incr/mhmean/README.md b/lib/node_modules/@stdlib/stats/incr/mhmean/README.md index c08c38b60065..b11019d9e560 100644 --- a/lib/node_modules/@stdlib/stats/incr/mhmean/README.md +++ b/lib/node_modules/@stdlib/stats/incr/mhmean/README.md @@ -26,14 +26,14 @@ limitations under the License. The [harmonic mean][harmonic-mean] of positive real numbers `x_0, x_1, ..., x_{n-1}` is defined as - + ```math -\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align} +\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align} ``` - @@ -61,7 +61,7 @@ var accumulator = incrmhmean( 3 ); #### accumulator( \[x] ) -If provided an input value `x`, the accumulator function returns an updated [harmonic mean][harmonic-mean]. If not provided an input value `x`, the accumulator function returns the current [harmonic-mean][harmonic-mean]. +If provided an input value `x`, the accumulator function returns an updated [harmonic mean][harmonic-mean]. If not provided an input value `x`, the accumulator function returns the current [harmonic mean][harmonic-mean]. ```javascript var accumulator = incrmhmean( 3 ); diff --git a/lib/node_modules/@stdlib/stats/incr/mhmean/docs/img/equation_harmonic_mean.svg b/lib/node_modules/@stdlib/stats/incr/mhmean/docs/img/equation_harmonic_mean.svg index 495851a8151e..73b075001d8f 100644 --- a/lib/node_modules/@stdlib/stats/incr/mhmean/docs/img/equation_harmonic_mean.svg +++ b/lib/node_modules/@stdlib/stats/incr/mhmean/docs/img/equation_harmonic_mean.svg @@ -104,8 +104,8 @@ - - + + @@ -134,7 +134,7 @@ - + diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/README.md b/lib/node_modules/@stdlib/stats/incr/mskewness/README.md new file mode 100644 index 000000000000..45b7d192341a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/README.md @@ -0,0 +1,191 @@ + + +# incrmskewness + +> Compute moving [corrected sample skewness][sample-skewness] incrementally. + +
+ +The [skewness][sample-skewness] for a random variable `X` is defined as + + + +```math +\mathop{\mathrm{Skewness}}[X] = \mathrm{E}\biggl[ \biggl( \frac{X - \mu}{\sigma} \biggr)^3 \biggr] +``` + + + + + +For a sample of `n` values, the [sample skewness][sample-skewness] is + + + +```math +b_1 = \frac{m_3}{s^3} = \frac{\frac{1}{n} \sum_{i=0}^{n-1} (x_i - \bar{x})^3}{\biggl( \frac{1}{n-1} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 \biggr)^{3/2}} +``` + + + + + +where `m_3` is the sample third central moment and `s` is the sample standard deviation. + +An alternative definition for the [sample skewness][sample-skewness] which includes an adjustment factor (and is the implemented definition) is + + + +```math +G_1 = \frac{n^2}{(n-1)(n-2)} \frac{m_3}{s^3} = \frac{\sqrt{n(n-1)}}{n-2} \frac{\frac{1}{n} \sum_{i=0}^{n-1} (x_i - \bar{x})^3}{\biggl( \frac{1}{n} \sum_{i=0}^{n-1} (x_i - \bar{x})^2 \biggr)^{3/2}} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrmskewness = require( '@stdlib/stats/incr/mskewness' ); +``` + +#### incrmskewness( W ) + +Returns an accumulator `function` which incrementally computes a moving [corrected sample skewness][sample-skewness] over a sliding window of size `W`. + +```javascript +var accumulator = incrmskewness( 5 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated moving [corrected sample skewness][sample-skewness]. If not provided an input value `x`, the accumulator function returns the current moving [corrected sample skewness][sample-skewness]. + +```javascript +var accumulator = incrmskewness( 5 ); + +var skewness = accumulator(); +// returns null + +skewness = accumulator( 2.0 ); +// returns null + +skewness = accumulator( -5.0 ); +// returns null + +skewness = accumulator( -10.0 ); +// returns ~0.492 + +skewness = accumulator(); +// returns ~0.492 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for **at least** `W-1` future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrmskewness = require( '@stdlib/stats/incr/mskewness' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrmskewness( 3 ); + +// For each simulated datum, update the corrected sample skewness... +for ( i = 0; i < 100; i++ ) { + v = randu() * 100.0; + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + +* * * + +
+ +## References + +- Joanes, D. N., and C. A. Gill. 1998. "Comparing measures of sample skewness and kurtosis." _Journal of the Royal Statistical Society: Series D (The Statistician)_ 47 (1). Blackwell Publishers Ltd: 183–89. doi:[10.1111/1467-9884.00122][@joanes:1998]. + +
+ + + + + +
+ +
+ + + + + +
+ +[sample-skewness]: https://en.wikipedia.org/wiki/Skewness + +[@joanes:1998]: http://onlinelibrary.wiley.com/doi/10.1111/1467-9884.00122/ + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/mskewness/benchmark/benchmark.js new file mode 100644 index 000000000000..6903b0ee50ec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/benchmark/benchmark.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var Float64Array = require( '@stdlib/array/float64' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrmskewness = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrmskewness( ( i % 5 ) + 1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var len; + var v; + var i; + var x; + + len = 100; + x = new Float64Array( len ); + for ( i = 0; i < len; i++ ) { + x[ i ] = uniform( 0.0, 1.0 ); + } + + acc = incrmskewness( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( x[ i % len ] ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_adjusted_sample_skewness.svg b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_adjusted_sample_skewness.svg new file mode 100644 index 000000000000..3277353af222 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_adjusted_sample_skewness.svg @@ -0,0 +1,171 @@ + +upper G 1 equals StartFraction n squared Over left-parenthesis n minus 1 right-parenthesis left-parenthesis n minus 2 right-parenthesis EndFraction StartFraction m 3 Over s cubed EndFraction equals StartFraction StartRoot n left-parenthesis n minus 1 right-parenthesis EndRoot Over n minus 2 EndFraction StartStartFraction StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis cubed OverOver left-parenthesis StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared right-parenthesis Superscript 3 slash 2 Baseline EndEndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_sample_skewness.svg b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_sample_skewness.svg new file mode 100644 index 000000000000..147334d80f8b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_sample_skewness.svg @@ -0,0 +1,131 @@ + +b 1 equals StartFraction m 3 Over s cubed EndFraction equals StartStartFraction StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis cubed OverOver left-parenthesis StartFraction 1 Over n minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared right-parenthesis Superscript 3 slash 2 Baseline EndEndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_skewness.svg b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_skewness.svg new file mode 100644 index 000000000000..45650ae35b70 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/img/equation_skewness.svg @@ -0,0 +1,59 @@ + +upper S k e w n e s s left-bracket upper X right-bracket equals normal upper E left-bracket left-parenthesis StartFraction upper X minus mu Over sigma EndFraction right-parenthesis cubed right-bracket + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/repl.txt new file mode 100644 index 000000000000..3c2af7368468 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/repl.txt @@ -0,0 +1,44 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + corrected sample skewness. + + The `W` parameter defines the window size (i.e., the number of values + over which to compute the skewness). + + If provided a value, the accumulator function returns an updated moving + corrected sample skewness. If not provided a value, the accumulator + function returns the current moving corrected sample skewness. + + As `W` values are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes + (provided at least `3` values have been accumulated). + Until the window is full, each returned value is calculated + from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var v = accumulator( 2.0 ) + null + > v = accumulator( -5.0 ) + null + > v = accumulator( -10.0 ) + ~0.492 + > v = accumulator( 5.0 ) + ~0.935 + > v = accumulator() + ~0.935 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/types/index.d.ts new file mode 100644 index 000000000000..dda7556c003e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/types/index.d.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated corrected sample skewness. If not provided a value, the accumulator function returns the current corrected sample skewness. +* +* ## Notes +* +* - If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for at least `W-1` future invocations. +* +* @param x - value +* @returns corrected sample skewness or null +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving corrected sample skewness. +* +* ## Notes +* +* - If provided a value, the accumulator function returns an updated corrected sample skewness. If not provided a value, the accumulator function returns the current corrected sample skewness. +* - If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for at least `W` invocations. +* +* @param W - window size +* @returns accumulator function +* +* @example +* var accumulator = incrmskewness( 3 ); +* +* var skewness = accumulator(); +* // returns null +* +* skewness = accumulator( 2.0 ); +* // returns null +* +* skewness = accumulator( -5.0 ); +* // returns null +* +* skewness = accumulator( -10.0 ); +* // returns ~0.492 +* +* skewness = accumulator( 5.0 ); +* // returns ~0.935 +* +* skewness = accumulator(); +* // returns ~0.935 +*/ +declare function incrmskewness( W: number ): accumulator; + + +// EXPORTS // + +export = incrmskewness; diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/types/test.ts new file mode 100644 index 000000000000..d24813c922ea --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/docs/types/test.ts @@ -0,0 +1,67 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrmskewness = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrmskewness( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided invalid arguments... +{ + incrmskewness( '5' ); // $ExpectError + incrmskewness( true ); // $ExpectError + incrmskewness( false ); // $ExpectError + incrmskewness( null ); // $ExpectError + incrmskewness( [] ); // $ExpectError + incrmskewness( {} ); // $ExpectError + incrmskewness( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrmskewness(); // $ExpectError + incrmskewness( 3, 2 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrmskewness( 3 ); + + acc(); // $ExpectType number | null + acc( 2 ); // $ExpectType number | null + acc( -5 ); // $ExpectType number | null + acc( 10 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrmskewness( 5 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/examples/index.js b/lib/node_modules/@stdlib/stats/incr/mskewness/examples/index.js new file mode 100644 index 000000000000..2135fe72ca09 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/examples/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrmskewness = require( './../lib' ); + +var accumulator; +var mskewness; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrmskewness( 5 ); + +// For each simulated datum, update the moving corrected sample skewness... +console.log( '\nValue\tSkewness\n' ); + +for ( i = 0; i < 100; i++ ) { + v = randu() * 100.0; + mskewness = accumulator( v ); + if ( i < 2 ) { + console.log( '%s\t%s', v.toFixed( 4 ), mskewness ); + } else { + console.log( '%s\t%s', v.toFixed( 4 ), mskewness.toFixed( 4 ) ); + } +} +console.log( '\nFinal moving skewness: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/lib/index.js b/lib/node_modules/@stdlib/stats/incr/mskewness/lib/index.js new file mode 100644 index 000000000000..79a42de355aa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute moving corrected sample skewness incrementally. +* +* @module @stdlib/stats/incr/mskewness +* +* @example +* var incrmskewness = require( '@stdlib/stats/incr/mskewness' ); +* +* var accumulator = incrmskewness( 3 ); +* +* var mskewness = accumulator(); +* // returns null +* +* mskewness = accumulator( 2.0 ); +* // returns null +* +* mskewness = accumulator( -5.0 ); +* // returns null +* +* mskewness = accumulator( -10.0 ); +* // returns ~0.492 +* +* mskewness = accumulator( 5.0 ); +* // returns ~0.935 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/lib/main.js b/lib/node_modules/@stdlib/stats/incr/mskewness/lib/main.js new file mode 100644 index 000000000000..b90d04f3c27c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/lib/main.js @@ -0,0 +1,232 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isPositiveInteger = require( '@stdlib/assert/is-positive-integer' ).isPrimitive; +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving corrected sample skewness. +* +* ## Method +* +* The algorithm computes the corrected sample skewness using the formula for `G_1` in [Joanes and Gill 1998][@joanes:1998]. Updates are performed using an extension of Welford's algorithm for sliding windows. +* +* ## References +* +* - Joanes, D. N., and C. A. Gill. 1998. "Comparing measures of sample skewness and kurtosis." _Journal of the Royal Statistical Society: Series D (The Statistician)_ 47 (1). Blackwell Publishers Ltd: 183–89. doi:[10.1111/1467-9884.00122][@joanes:1998]. +* +* [@joanes:1998]: http://dx.doi.org/10.1111/1467-9884.00122 +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrmskewness( 3 ); +* +* var skewness = accumulator(); +* // returns null +* +* skewness = accumulator( 2.0 ); +* // returns null +* +* skewness = accumulator( -5.0 ); +* // returns null +* +* skewness = accumulator( -10.0 ); +* // returns ~0.492 +* +* skewness = accumulator( 5.0 ); +* // returns ~0.935 +* +* skewness = accumulator(); +* // returns ~0.935 +*/ +function incrmskewness( W ) { + var deltaN; + var term1; + var delta; + var mean; + var buf; + var tmp; + var g1; + var M2; + var M3; + var i; + var N; + + if ( !isPositiveInteger( W ) ) { + throw new TypeError( format( 'invalid argument. Must provide a positive integer. Value: `%s`.', W ) ); + } + buf = new Float64Array( W ); + mean = 0.0; + M2 = 0.0; + M3 = 0.0; + i = -1; + N = 0; + + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated corrected sample skewness. If not provided a value, the accumulator function returns the current corrected sample skewness. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} corrected sample skewness or null + */ + function accumulator( x ) { + var meanOld; + var M2Old; + var v; + var k; + + if ( arguments.length === 0 ) { + if ( N < 3 ) { + return ( isnan( M3 ) ) ? NaN : null; + } + // Calculate the population skewness: + g1 = sqrt( N ) * M3 / pow( M2, 1.5 ); + + // Return the corrected sample skewness: + return sqrt( N * ( N - 1 ) ) * g1 / ( N - 2 ); + } + + // Update the index for managing the circular buffer: + i = ( i + 1 ) % W; + + // Case: incoming value is NaN, so the accumulated statistics are automatically NaN... + if ( isnan( x ) ) { + M2 = NaN; + M3 = NaN; + mean = NaN; + N = W; // explicitly set to avoid `N < W` branch + } + // Case: initial window... + else if ( N < W ) { + N += 1; + delta = x - mean; + deltaN = delta / N; + term1 = delta * deltaN * ( N - 1 ); + + tmp = term1 * deltaN * ( N - 2 ); + tmp -= 3.0 * deltaN * M2; + M3 += tmp; + + M2 += term1; + mean += deltaN; + } + // Case: N = W = 1 + else if ( N === 1 ) { + mean = x; + M2 = 0.0; + M3 = 0.0; + } + // Case: outgoing value is NaN or current stats are NaN, and, thus, we need to recompute the accumulated values... + else if ( isnan( buf[ i ] ) || isnan( M2 ) || isnan( M3 ) ) { + N = 0; + M2 = 0.0; + M3 = 0.0; + mean = 0.0; + + // Reconstruct statistics from the buffer (excluding the outgoing value at `i`, adding `x`): + for ( k = 0; k < W; k++ ) { + v = ( k === i ) ? x : buf[ k ]; + if ( isnan( v ) ) { + N = W; + M2 = NaN; + M3 = NaN; + mean = NaN; + break; + } + N += 1; + delta = v - mean; + deltaN = delta / N; + term1 = delta * deltaN * ( N - 1 ); + + tmp = term1 * deltaN * ( N - 2 ); + tmp -= 3.0 * deltaN * M2; + M3 += tmp; + + M2 += term1; + mean += deltaN; + } + } + // Case: neither the current stats nor the incoming/outgoing values are NaN, so we update the accumulated values (remove old, add new)... + else { + // Remove the outgoing value (buf[i]): + v = buf[ i ]; + + // To remove, we reverse the Welford update. We calculate the mean *before* v was added (which corresponds to N-1). N here is W. + meanOld = ( ( N * mean ) - v ) / ( N - 1 ); + + delta = v - meanOld; + deltaN = delta / N; // This is ( mean - meanOld ) + + term1 = delta * deltaN * ( N - 1 ); + + // Revert M2 first (order matters relative to add operation, but we need M2_old for M3): + M2Old = M2 - term1; + + tmp = term1 * deltaN * ( N - 2 ); + tmp -= 3.0 * deltaN * M2Old; + + M3 -= tmp; + M2 = M2Old; + mean = meanOld; + + // Now Add the new value (x) + delta = x - mean; + deltaN = delta / N; + term1 = delta * deltaN * ( N - 1 ); + + tmp = term1 * deltaN * ( N - 2 ); + tmp -= 3.0 * deltaN * M2; + M3 += tmp; + + M2 += term1; + mean += deltaN; + } + + buf[ i ] = x; + + if ( N < 3 ) { + return ( isnan( M3 ) ) ? NaN : null; + } + // Calculate the population skewness: + g1 = sqrt( N ) * M3 / pow( M2, 1.5 ); + + // Return the corrected sample skewness: + return sqrt( N * ( N - 1 ) ) * g1 / ( N - 2 ); + } +} + + +// EXPORTS // + +module.exports = incrmskewness; diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/package.json b/lib/node_modules/@stdlib/stats/incr/mskewness/package.json new file mode 100644 index 000000000000..0117e9c872c2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/stats/incr/mskewness", + "version": "0.0.0", + "description": "Compute moving corrected sample skewness incrementally.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "skewness", + "sample skewness", + "shape", + "corrected", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/mskewness/test/test.js b/lib/node_modules/@stdlib/stats/incr/mskewness/test/test.js new file mode 100644 index 000000000000..706e5f980351 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/mskewness/test/test.js @@ -0,0 +1,315 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmskewness = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrmskewness, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrmskewness( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrmskewness( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving corrected sample skewness incrementally', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var i; + var N; + + data = [ 3.0, 2.0, 7.0, -1.0, 9.0, -2.0 ]; + N = data.length; + + expected = [ + null, + null, + 1.4578629673213048, + 0.4366620845757488, + 0.11718750000000001, + 0.329176993486849 + ]; + + acc = incrmskewness( 5 ); + + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + if ( expected[ i ] === null ) { + t.strictEqual( actual, expected[i], 'returns expected value for index '+i ); + } else { + delta = abs( actual - expected[ i ] ); + tol = 1.5 * EPS * abs( expected[ i ] ); + t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected[i]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current skewness', function test( t ) { + var expected; + var data; + var acc; + var i; + + data = [ 3.0, 2.0, 7.0, -1.0, 9.0 ]; + expected = 0.11718750000000001; + acc = incrmskewness( 5 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + + t.strictEqual( acc(), expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrmskewness( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the corrected sample skewness is `null` until at least 3 datums have been provided', function test( t ) { + var skewness; + var acc; + + acc = incrmskewness( 5 ); + + skewness = acc(); + t.strictEqual( skewness, null, 'returns expected value' ); + + skewness = acc( 2.0 ); + t.strictEqual( skewness, null, 'returns expected value' ); + + skewness = acc( 2.0 ); + t.strictEqual( skewness, null, 'returns expected value' ); + + skewness = acc( 3.0 ); + t.notEqual( skewness, null, 'does not return null' ); + + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is `NaN` for at least `W` invocations', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrmskewness( 3 ); + + data = [ + NaN, // NaN + 2.0, // NaN, 2 + 3.0, // NaN, 2, 3 + NaN, // 2, 3, NaN + 5.0, // 3, NaN, 5 + 6.0, // NaN, 5, 6 + 7.0, // 5, 6, 7 + NaN, // 6, 7, NaN + 1.0, // 7, NaN, 1 + 2.0, // NaN, 1, 2 + 3.0, // 1, 2, 3 + NaN, // 2, 3, NaN + 5.0, // 3, NaN, 5 + 6.0, // NaN, 5, 6 + NaN, // 5, 6, NaN + NaN, // 6, NaN, NaN + NaN, // NaN, NaN, NaN + NaN, // NaN, NaN, NaN + 1.0 // NaN, NaN, 1 + ]; + expected = [ + NaN, + NaN, + NaN, + NaN, + NaN, + NaN, + 0.0, + NaN, + NaN, + NaN, + 0.0, + NaN, + NaN, + NaN, + NaN, + NaN, + NaN, + NaN, + NaN + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( isnan( expected[ i ] ) ) { + t.strictEqual( isnan( v ), true, 'returns expected value for window '+i ); + t.strictEqual( isnan( acc() ), true, 'returns expected value for window '+i ); + } else if ( expected[ i ] === null ) { + t.strictEqual( v, null, 'returns expected value for window '+i ); + t.strictEqual( acc(), null, 'returns expected value for window '+i ); + } else { + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i ); + } + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is `NaN` for at least `W` invocations (W=3, NaN at different positions with recovery)', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrmskewness( 3 ); + + data = [ + 1.0, // 1 + 2.0, // 1, 2 + 3.0, // 1, 2, 3 + NaN, // 2, 3, NaN + 5.0, // 3, NaN, 5 + 6.0, // NaN, 5, 6 + 7.0 // 5, 6, 7 + ]; + + expected = [ + null, + null, + 0.0, + NaN, + NaN, + NaN, + 0.0 + ]; + + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( expected[ i ] === null ) { + t.strictEqual( v, null, 'returns expected value for window '+i ); + t.strictEqual( acc(), null, 'returns expected value for window '+i ); + } else if ( isnan( expected[ i ] ) ) { + t.strictEqual( isnan( v ), true, 'returns expected value for window '+i ); + t.strictEqual( isnan( acc() ), true, 'returns expected value for window '+i ); + } else { + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i ); + } + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is `NaN` for at least `W` invocations (consecutive NaN values)', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrmskewness( 3 ); + + data = [ + 1.0, // 1 + 2.0, // 1, 2 + 3.0, // 1, 2, 3 + NaN, // 2, 3, NaN + NaN, // 3, NaN, NaN + NaN, // NaN, NaN, NaN + 4.0, // NaN, NaN, 4 + 5.0, // NaN, 4, 5 + 6.0 // 4, 5, 6 + ]; + + expected = [ + null, + null, + 0.0, + NaN, + NaN, + NaN, + NaN, + NaN, + 0.0 + ]; + + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( expected[ i ] === null ) { + t.strictEqual( v, null, 'returns expected value for window '+i ); + t.strictEqual( acc(), null, 'returns expected value for window '+i ); + } else if ( isnan( expected[ i ] ) ) { + t.strictEqual( isnan( v ), true, 'returns expected value for window '+i ); + t.strictEqual( isnan( acc() ), true, 'returns expected value for window '+i ); + } else { + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/README.md b/lib/node_modules/@stdlib/stats/incr/nancovariance/README.md new file mode 100644 index 000000000000..67b88578b3e2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/README.md @@ -0,0 +1,113 @@ + + +# incrnancovariance + +> Compute a sample covariance incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnancovariance = require( '@stdlib/stats/incr/nancovariance' ); +``` + +#### incrnancovariance + +Returns an accumulator function which incrementally computes a sample covariance, ignoring any input pairs that contain NaN values. The accumulator returns null until at least two valid data pairs have been provided. + +```javascript +var accumulator = incrnancovariance(); +``` + +#### accumulator(`[x, y]`) + +If provided a pair of numeric input values `[x, y]`, the accumulator updates and returns the sample covariance. If not provided any input values, the accumulator returns the current sample covariance. + +```javascript +var accumulator = incrnancovariance(); + +var cov = accumulator(); +// returns null + +cov = accumulator( 2.0, 1.0 ); +// returns null + +cov = accumulator( NaN, 1.0 ); +// returns null + +cov = accumulator( 4.0, 5.0 ); +// returns 4.0 + +cov = accumulator(); +// returns 4.0 +``` + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnancovariance = require( '@stdlib/stats/incr/nancovariance' ); + +var accumulator; +var i; +var x; +var y; +accumulator = incrnancovariance(); +for ( i = 0; i < 100; i++ ) { + x = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + y = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + accumulator( x, y ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nancovariance/benchmark/benchmark.js new file mode 100644 index 000000000000..c3a4e8cb25c5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/benchmark/benchmark.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnancovariance = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var acc; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + acc = incrnancovariance(); + if ( typeof acc !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof acc !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var x; + var y; + var v; + var i; + + acc = incrnancovariance(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x = ( randu() < 0.1 ) ? NaN : randu() * 10; // ~10% NaN + y = ( randu() < 0.1 ) ? NaN : randu() * 10; // ~10% NaN + v = acc( x, y ); + if ( v !== v && i > 1 ) { + b.fail( 'accumulator should not return NaN once enough valid data' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/repl.txt new file mode 100644 index 000000000000..f97e26539b7a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes a sample + covariance, ignoring `NaN` values. + + If provided input values, the accumulator function returns an updated + sample covariance. If not provided input values, the accumulator function + returns the current sample covariance. + + If an input value is `NaN`, the input pair is ignored and the accumulated + value remains unchanged. + + Until at least two valid data pairs have been provided, the accumulator + function returns `null`. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var v = accumulator() + null + > v = accumulator( 2.0, 1.0 ) + null + > v = accumulator( NaN, 5.0 ) + null + > v = accumulator( 4.0, 5.0 ) + 4.0 + > v = accumulator() + 4.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/types/index.d.ts new file mode 100644 index 000000000000..07c9093353c4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/types/index.d.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated sample covariance; otherwise, returns the current sample covariance. +* +* ## Notes +* +* - If provided `NaN`, the input is ignored and the accumulated value remains unchanged. +* +* @param x - value +* @param y - value +* @returns sample covariance or null +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a sample covariance, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var acc = incrnancovariance(); +* +* var cov = acc(); +* // returns null +* +* cov = acc( 2.0, 1.0 ); +* // returns null +* +* cov = acc( NaN, 5.0 ); +* // returns null +* +* cov = acc( 4.0, 5.0 ); +* // returns 4.0 +* +* cov = acc(); +* // returns 4.0 +*/ +declare function incrnancovariance(): accumulator; + + +// EXPORTS // + +export = incrnancovariance; diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/types/test.ts new file mode 100644 index 000000000000..0f2a8ca5e7f7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnancovariance = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnancovariance(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided any arguments... +{ + incrnancovariance( 3 ); // $ExpectError + incrnancovariance( 3, 0.0 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnancovariance(); + acc(); // $ExpectType number | null + acc( 2.0, 1.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnancovariance(); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 2.0, '5' ); // $ExpectError + acc( 2.0, true ); // $ExpectError + acc( 2.0, false ); // $ExpectError + acc( 2.0, null ); // $ExpectError + acc( 2.0, [] ); // $ExpectError + acc( 2.0, {} ); // $ExpectError + acc( 2.0, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nancovariance/examples/index.js new file mode 100644 index 000000000000..445d69fa4cb5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/examples/index.js @@ -0,0 +1,35 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var incrnancovariance = require( './../lib' ); + +var acc = incrnancovariance(); + +var dataX = [ 2.0, 2.0, NaN, 3.0, 5.0 ]; +var dataY = [ 1.0, 5.0, 4.0, NaN, 5.0 ]; + +var i; +var cov; +for ( i = 0; i < dataX.length; i++ ) { + cov = acc( dataX[ i ], dataY[ i ] ); + console.log( 'x=%s, y=%s, cov=%s', dataX[ i ], dataY[ i ], ( cov === null ) ? 'null' : cov.toString() ); +} + +console.log( '\nFinal sample covariance:', acc() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nancovariance/lib/index.js new file mode 100644 index 000000000000..0e79ddaf073c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/lib/index.js @@ -0,0 +1,56 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a sample covariance incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nancovariance +* +* @example +* var incrnancovariance = require( '@stdlib/stats/incr/nancovariance' ); +* +* var acc = incrnancovariance(); +* +* var cov = acc(); +* // returns null +* +* // Covariance is undefined for a single pair: +* cov = acc( 2.0, 1.0 ); +* // returns null +* +* // An input pair containing NaN is ignored: +* cov = acc( NaN, 5.0 ); +* // returns null +* +* cov = acc( 4.0, 5.0 ); +* // returns 4.0 +* +* cov = acc(); +* // returns 4.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nancovariance/lib/main.js new file mode 100644 index 000000000000..18ce017b43e4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/lib/main.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var covariance = require( '@stdlib/stats/incr/covariance' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a sample covariance, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var incrnancovariance = require( '@stdlib/stats/incr/nancovariance' ); +* +* var acc = incrnancovariance(); +* +* var cov = acc(); +* // returns null +* +* cov = acc( 2.0, 1.0 ); +* // returns null +* +* cov = acc( NaN, 5.0 ); +* // returns null +* +* cov = acc( 4.0, 5.0 ); +* // returns 4.0 +* +* cov = acc(); +* // returns 4.0 +*/ +function incrnancovariance() { + var count = 0; + var acc = covariance(); + return accumulator; + + /** + * Updates and returns the sample covariance when provided two numeric arguments. + * If no arguments are provided, returns the current sample covariance. + * + * @private + * @param {number} [x] - new x value + * @param {number} [y] - new y value + * @returns {(number|null)} sample covariance or null + */ + function accumulator( x, y ) { + var val; + if ( arguments.length === 0 ) { + return ( count < 2 ) ? null : acc(); + } + if ( isnan( x ) || isnan( y ) ) { + return ( count < 2 ) ? null : acc(); + } + count += 1; + val = acc( x, y ); + return ( count < 2 ) ? null : val; + } +} + + +// EXPORTS // + +module.exports = incrnancovariance; diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/package.json b/lib/node_modules/@stdlib/stats/incr/nancovariance/package.json new file mode 100644 index 000000000000..fa2560df8810 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/package.json @@ -0,0 +1,60 @@ +{ + "name": "@stdlib/stats/incr/nancovariance", + "version": "0.0.0", + "description": "Compute a sample covariance incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "statistics", + "covariance", + "incremental", + "accumulator", + "nan", + "sample covariance" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nancovariance/test/test.js b/lib/node_modules/@stdlib/stats/incr/nancovariance/test/test.js new file mode 100644 index 000000000000..e0e6dd47344e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancovariance/test/test.js @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnancovariance = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnancovariance, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + var acc = incrnancovariance(); + t.strictEqual( typeof acc, 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function returns null if no valid pairs have been provided', function test( t ) { + var acc = incrnancovariance(); + t.equal( acc(), null, 'returns null initially' ); + + // Provide an invalid pair: + acc( NaN, 5.0 ); + t.equal( acc(), null, 'still null after invalid pair' ); + t.end(); +}); + +tape( 'the accumulator function returns null if only one valid pair has been provided', function test( t ) { + var acc = incrnancovariance(); + + // Add the first valid pair: + acc( 2.0, 1.0 ); + t.equal( acc(), null, 'returns null for single valid pair' ); + t.end(); +}); + +tape( 'the accumulator function computes sample covariance once two valid pairs have been provided', function test( t ) { + var acc = incrnancovariance(); + var cov; + + // Pair #1: + cov = acc( 2.0, 1.0 ); + t.equal( cov, null, 'still null with only one valid pair' ); + + // Pair #2: + cov = acc( 4.0, 5.0 ); + t.equal( cov, 4.0, 'returns sample covariance after second valid pair' ); + + // Current covariance with no arguments: + t.equal( acc(), 4.0, 'returns current covariance' ); + t.end(); +}); + +tape( 'the accumulator function skips pairs containing NaN', function test( t ) { + var acc = incrnancovariance(); + var cov; + + // Provide first valid pair: + cov = acc( 2.0, 1.0 ); + t.equal( cov, null, 'null with only one valid pair' ); + + // Invalid pair => skip: + cov = acc( NaN, 10.0 ); + t.equal( cov, null, 'still null, as second pair is invalid' ); + + // Provide second valid pair: + cov = acc( 2.0, 5.0 ); + // For (2,1) and (2,5): same X => covariance=0 + t.equal( cov, 0.0, 'returns 0.0 for these pairs' ); + + // Provide third valid pair: + cov = acc( 5.0, 9.0 ); + t.equal( typeof cov, 'number', 'returns a number after third valid pair' ); + t.end(); +}); + +tape( 'the accumulator function computes correct covariance for multiple valid pairs interspersed with invalid pairs', function test( t ) { + var expected = 14.0/3.0; + var delta; + var data = [ + [ 2.0, 1.0 ], + [ NaN, 4.0 ], + [ 4.0, 5.0 ], + [ 3.0, 7.0 ], + [ NaN, NaN ], + [ 5.0, 11.0 ] + ]; + var acc = incrnancovariance(); + var cov; + var tol; + var i; + for ( i = 0; i < data.length; i++ ) { + cov = acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + delta = abs( cov - expected ); + tol = EPS * abs( expected ); + t.equal( typeof cov, 'number', 'returns a number' ); + t.ok( delta < tol, 'within tolerance. Actual: '+cov+'. Expected: '+expected+'. delta: '+delta+'. tol: '+tol+'.' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/README.md b/lib/node_modules/@stdlib/stats/incr/nancv/README.md new file mode 100644 index 000000000000..4c4e41c97033 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/README.md @@ -0,0 +1,190 @@ + + +# incrnancv + +> Compute the [coefficient of variation][coefficient-of-variation] (CV) incrementally, while ignoring 'NaN' values. + +
+ +The [corrected sample standard deviation][sample-stdev] is defined as + + + +```math +s = \sqrt{\frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2} +``` + + + + + +and the [arithmetic mean][arithmetic-mean] is defined as + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +The [coefficient of variation][coefficient-of-variation] (also known as **relative standard deviation**, RSD) is defined as + + + +```math +c_v = \frac{s}{\bar{x}} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnancv = require( '@stdlib/stats/incr/nancv' ); +``` + +#### incrnancv( \[mean] ) + +Returns an accumulator `function` which incrementally computes the [coefficient of variation][coefficient-of-variation], ignoring `NaN` values. + +```javascript +var accumulator = incrnancv(); +``` + +If the mean is already known, provide a `mean` argument. + +```javascript +var accumulator = incrnancv( 3.0 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated accumulated value. If not provided an input value `x`, the accumulator function returns the current accumulated value. + +```javascript +var accumulator = incrnancv(); + +var cv = accumulator( 2.0 ); +// returns 0.0 + +cv = accumulator( 1.0 ); +// returns 0.47140452079103173 + +cv = accumulator( NaN ); +// returns 0.47140452079103173 + +cv = accumulator( 3.0 ); +// returns 0.5 + +cv = accumulator(); +// returns 0.5 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. Unlike `incrcv`, `NaN` values are ignored and do not affect the accumulated value. +- The [coefficient of variation][coefficient-of-variation] is typically computed on nonnegative values. The measure may lack meaning for data which can assume both positive and negative values. +- For small and moderately sized samples, the accumulated value tends to be too low and is thus a **biased** estimator. Provided the generating distribution is known (e.g., a normal distribution), you may want to adjust the accumulated value or use an alternative implementation providing an unbiased estimator. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnancv = require( '@stdlib/stats/incr/nancv' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnancv(); + +// For each simulated datum, update the coefficient of variation... +for ( i = 0; i < 100; i++ ) { + v = ( (randu() < 0.1) ? NaN : (randu() * 100.0) ); + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[coefficient-of-variation]: https://en.wikipedia.org/wiki/Coefficient_of_variation + +[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean + +[sample-stdev]: https://en.wikipedia.org/wiki/Standard_deviation + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nancv/benchmark/benchmark.js new file mode 100644 index 000000000000..349774cccddc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/benchmark/benchmark.js @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnancv = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnancv(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnancv(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator,known_mean', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnancv( 3.14 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nancv/docs/repl.txt new file mode 100644 index 000000000000..0ebe3261bc0b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/docs/repl.txt @@ -0,0 +1,38 @@ +{{alias}}( [mean] ) + Returns an accumulator function which incrementally computes the + coefficient of variation (CV), ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated + accumulated value. If not provided a value, the accumulator function + returns the current accumulated value. + + If all received values are `NaN`, the accumulated value remains `null`. + + Parameters + ---------- + mean: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var cv = accumulator() + null + > cv = accumulator( NaN ) + null + > cv = accumulator( 2.0 ) + 0.0 + > cv = accumulator( 1.0 ) + ~0.47 + > cv = accumulator( NaN ) + ~0.47 + > cv = accumulator() + ~0.47 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nancv/docs/types/index.d.ts new file mode 100644 index 000000000000..af330c7534df --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated accumulated value. If not provided a value, the accumulator function returns the current accumulated value. +* +* @param x - value +* @returns accumulated value or null +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes the coefficient of variation (CV), ignoring `NaN` values. +* +* @param mean - known mean +* @returns accumulator function +* +* @example +* var accumulator = incrnancv(); +* +* var cv = accumulator(); +* // returns null +* +* cv = accumulator( 2.0 ); +* // returns 0.0 +* +* cv = accumulator( 1.0 ); +* // returns ~0.47 +* +* cv = accumulator( NaN ); +* // returns ~0.47 +* +* cv = accumulator(); +* // returns ~0.47 +* +* @example +* var accumulator = incrnancv( 3.14 ); +*/ +declare function incrnancv( mean?: number ): accumulator; + + +// EXPORTS // + +export = incrnancv; diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nancv/docs/types/test.ts new file mode 100644 index 000000000000..e792fe5043bc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/docs/types/test.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnancv = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnancv(); // $ExpectType accumulator + incrnancv( 0.0 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided invalid arguments... +{ + incrnancv( '5' ); // $ExpectError + incrnancv( true ); // $ExpectError + incrnancv( false ); // $ExpectError + incrnancv( null ); // $ExpectError + incrnancv( [] ); // $ExpectError + incrnancv( {} ); // $ExpectError + incrnancv( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnancv(); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnancv(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nancv/examples/index.js new file mode 100644 index 000000000000..9bf4a055356b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/examples/index.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnancv = require( './../lib' ); + +var accumulator; +var cv; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnancv(); + +// For each simulated datum, update the coefficient of variation, ignoring NaN values... +console.log( '\nValue\tCV\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.1 ) ? NaN : ( randu() * 100.0 ); + cv = accumulator( v ); + console.log( '%s\t%s', ( v === v ) ? v.toFixed( 4 ) : 'NaN', ( cv === null ) ? 'null' : cv.toFixed( 4 ) ); +} +console.log( '\nFinal CV: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nancv/lib/index.js new file mode 100644 index 000000000000..ce3a3e674d27 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the coefficient of variation (CV) incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nancv +* +* @example +* var incrnancv = require( '@stdlib/stats/incr/nancv' ); +* +* var accumulator = incrnancv(); +* +* var cv = accumulator(); +* // returns null +* +* cv = accumulator( 2.0 ); +* // returns 0.0 +* +* cv = accumulator( NaN ); +* // returns 0.0 +* +* cv = accumulator( 1.0 ); +* // returns ~0.47 +* +* cv = accumulator(); +* // returns ~0.47 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nancv/lib/main.js new file mode 100644 index 000000000000..0b38b1ff219b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/lib/main.js @@ -0,0 +1,87 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrcv = require( '@stdlib/stats/incr/cv' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes the coefficient of variation (CV), ignoring `NaN` values. +* +* @param {number} [mean] - mean value +* @throws {TypeError} must provide a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnancv(); +* +* var cv = accumulator(); +* // returns null +* +* cv = accumulator( 2.0 ); +* // returns 0.0 +* +* cv = accumulator( NaN ); +* // returns 0.0 +* +* cv = accumulator( 1.0 ); +* // returns ~0.47 +* +* cv = accumulator(); +* // returns ~0.47 +* +* @example +* var accumulator = incrnancv( 3.0 ); +*/ +function incrnancv( mean ) { + var cv; + if ( arguments.length ) { + cv = incrcv( mean ); + } else { + cv = incrcv(); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated coefficient of variation. If not provided a value, the accumulator function returns the current coefficient of variation. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} coefficient of variation or null + */ + function accumulator( x ) { + if ( arguments.length === 0 ) { + return cv(); + } + if ( isnan( x ) ) { + return cv(); + } + return cv( x ); + } +} + + +// EXPORTS // + +module.exports = incrnancv; diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/package.json b/lib/node_modules/@stdlib/stats/incr/nancv/package.json new file mode 100644 index 000000000000..459f92ead53a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nancv", + "version": "0.0.0", + "description": "Compute the coefficient of variation (CV) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "stdev", + "std", + "variance", + "var", + "standard", + "deviation", + "dispersion", + "relative", + "rsd", + "cv", + "mean", + "ratio", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nancv/test/test.js b/lib/node_modules/@stdlib/stats/incr/nancv/test/test.js new file mode 100644 index 000000000000..02b99a12701f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nancv/test/test.js @@ -0,0 +1,253 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var incrnancv = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnancv, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnancv(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known mean)', function test( t ) { + t.equal( typeof incrnancv( 3.0 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a number for the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnancv( value ); + }; + } +}); + +tape( 'the accumulator function incrementally computes the coefficient of variation while ignoring NaN values', function test( t ) { + var expected; + var actual = []; + var data; + var acc; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, 4.0, NaN, 3.0, 4.0 ]; + + // Expected values ignoring NaNs: + expected = [ + 0.0 / (2.0 / 1.0), + 0.0 / (2.0 / 1.0), // NaN ignored + sqrt( 0.5 ) / (5.0 / 2.0), + sqrt( 0.33333333333333337 ) / (7.0 / 3.0), + sqrt( 0.9166666666666666 ) / (11.0 / 4.0), + sqrt( 0.9166666666666666 ) / (11.0 / 4.0), // NaN ignored + sqrt( 0.7 ) / (14.0 / 5.0), + sqrt( 0.8 ) / (18.0 / 6.0) + ]; + + acc = incrnancv(); + + for ( i = 0; i < data.length; i++ ) { + actual.push( acc( data[ i ] ) ); + } + t.deepEqual( actual, expected, 'returns expected results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current accumulated value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 3.0, 1.0 ]; + acc = incrnancv(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), sqrt( 1.0 ) / 2.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current accumulated value (known mean, ignoring NaNs)', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 3.0, 1.0, NaN ]; + acc = incrnancv( 2.0 ); + + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + + t.equal( acc(), sqrt( 2.0/3.0 ) / 2.0, 'returns expected value while ignoring NaNs' ); + t.end(); +}); + +tape( 'the accumulated value is `null` until at least 1 valid datum has been provided (unknown mean, ignoring NaNs)', function test( t ) { + var acc; + var cv; + + acc = incrnancv(); + + cv = acc(); + t.equal( cv, null, 'returns null' ); + + cv = acc( NaN ); + t.equal( cv, null, 'still returns null after NaN' ); + + cv = acc( 3.0 ); + t.notEqual( cv, null, 'does not return null after valid number' ); + + cv = acc(); + t.notEqual( cv, null, 'does not return null' ); + + t.end(); +}); + +tape( 'the accumulated value is `null` until at least 1 valid datum has been provided (known mean, ignoring NaNs)', function test( t ) { + var acc; + var cv; + + acc = incrnancv( 3.0 ); + + cv = acc(); + t.equal( cv, null, 'returns null' ); + + cv = acc( NaN ); + t.equal( cv, null, 'still returns null after NaN' ); + + cv = acc( 3.0 ); + t.notEqual( cv, null, 'does not return null after valid number' ); + + cv = acc(); + t.notEqual( cv, null, 'does not return null' ); + + t.end(); +}); + +tape( 'the accumulated value is `null` until at least 1 non-NaN datum has been provided', function test( t ) { + var acc; + var cv; + + acc = incrnancv(); + + cv = acc(); + t.equal( cv, null, 'returns null' ); + + cv = acc( NaN ); + t.equal( cv, null, 'returns null' ); + + cv = acc( 3.0 ); + t.notEqual( cv, null, 'does not return null' ); + + cv = acc(); + t.notEqual( cv, null, 'does not return null' ); + + t.end(); +}); + +tape( 'the accumulated value is `0` until at least 2 valid datums have been provided (unknown mean, ignoring NaNs)', function test( t ) { + var acc; + var cv; + + acc = incrnancv(); + + cv = acc( 2.0 ); + t.equal( cv, 0.0, 'returns 0' ); + + cv = acc(); + t.equal( cv, 0.0, 'returns 0' ); + + cv = acc( NaN ); + t.equal( cv, 0.0, 'still returns 0 after NaN' ); + + cv = acc( 3.0 ); + t.notEqual( cv, 0.0, 'does not return 0 after two valid numbers' ); + + cv = acc(); + t.notEqual( cv, 0.0, 'does not return 0' ); + + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function ignores it and continues accumulating valid values (unknown mean)', function test( t ) { + var data; + var acc; + var v; + var i; + + data = [ 2.0, NaN, 1.0, NaN, 2.0, 3.0, NaN, 4.0, 5.0, 6.0, 7.0 ]; + acc = incrnancv(); + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.notEqual( isnan( v ), true, 'does not return NaN' ); + t.notEqual( isnan( acc() ), true, 'does not return NaN' ); + } + t.notEqual( isnan( acc() ), true, 'does not return NaN' ); + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function ignores it and continues accumulating valid values (known mean)', function test( t ) { + var data; + var acc; + var v; + var i; + + data = [ 2.0, NaN, 1.0, NaN, 2.0, 3.0, NaN, 4.0, 5.0, 6.0, 7.0 ]; + acc = incrnancv( 3.14 ); + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.notEqual( isnan( v ), true, 'does not return NaN' ); + t.notEqual( isnan( acc() ), true, 'does not return NaN' ); + } + t.notEqual( isnan( acc() ), true, 'does not return NaN' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/README.md b/lib/node_modules/@stdlib/stats/incr/nanewmean/README.md new file mode 100644 index 000000000000..2e2eb84ffdbe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/README.md @@ -0,0 +1,159 @@ + + +# incrnanewmean + +> Compute an [exponentially weighted mean][moving-average] incrementally, ignoring `NaN` values. + +
+ +An [exponentially weighted mean][moving-average] can be defined recursively as + + + +```math +\mu_t = \begin{cases} x_0 & \textrm{if}\ t = 0 \\ \alpha x_t + (1-\alpha) \mu_{t-1} & \textrm{if}\ t > 0 \end{cases} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanewmean = require( '@stdlib/stats/incr/nanewmean' ); +``` + +#### incrnanewmean( alpha ) + +Returns an accumulator `function` which incrementally computes an [exponentially weighted mean][moving-average], where `alpha` is a smoothing factor between `0` and `1`, ignoring `NaN` values. + +```javascript +var accumulator = incrnanewmean( 0.5 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated mean. If not provided an input value `x`, the accumulator function returns the current mean. + +```javascript +var accumulator = incrnanewmean( 0.5 ); + +var v = accumulator(); +// returns null + +v = accumulator( 2.0 ); +// returns 2.0 + +v = accumulator( 1.0 ); +// returns 1.5 + +v = accumulator( NaN ); +// returns 1.5 + +v = accumulator( 3.0 ); +// returns 2.25 + +v = accumulator(); +// returns 2.25 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanewmean = require( '@stdlib/stats/incr/nanewmean' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanewmean( 0.5 ); + +// For each simulated datum, update the exponentially weighted mean... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +* * * + +## See Also + +
+ + + + + +
+ +[moving-average]: https://en.wikipedia.org/wiki/Moving_average + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanewmean/benchmark/benchmark.js new file mode 100644 index 000000000000..5cc2fecefdc3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanewmean = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanewmean( 0.5 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanewmean( 0.5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/img/equation_exponentially_weighted_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/img/equation_exponentially_weighted_mean.svg new file mode 100644 index 000000000000..b89cfc9aaae1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/img/equation_exponentially_weighted_mean.svg @@ -0,0 +1,74 @@ + +mu Subscript t Baseline equals StartLayout Enlarged left-brace 1st Row 1st Column x 0 2nd Column if t equals 0 2nd Row 1st Column alpha x Subscript t Baseline plus left-parenthesis 1 minus alpha right-parenthesis mu Subscript t minus 1 Baseline 2nd Column if t greater-than 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/repl.txt new file mode 100644 index 000000000000..10bb20079f92 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}( α ) + Returns an accumulator function which incrementally computes an + exponentially weighted mean, where α is a smoothing factor between 0 and 1, + ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated mean. If + not provided a value, the accumulator function returns the current mean. + + Parameters + ---------- + α: number + Smoothing factor (value between 0 and 1). + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 0.5 ); + > var v = accumulator() + null + > v = accumulator( 2.0 ) + 2.0 + > v = accumulator( NaN ) + 2.0 + > v = accumulator( -5.0 ) + -1.5 + > v = accumulator() + -1.5 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/types/index.d.ts new file mode 100644 index 000000000000..2aea8a3aff4b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/types/index.d.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated mean. If not provided a value, the accumulator function returns the current mean. +* +* @param x - value +* @returns mean value +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes an exponentially weighted mean, ignoring `NaN` values. +* +* @param alpha - smoothing factor +* @throws must be on the interval `[0,1]` +* @returns accumulator function +* +* @example +* var accumulator = incrnanewmean( 0.5 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( NaN ); +* // returns 2.0 +* +* v = accumulator( -5.0 ); +* // returns -1.5 +* +* v = accumulator(); +* // returns -1.5 +*/ +declare function incrnanewmean( alpha: number ): accumulator; + + +// EXPORTS // + +export = incrnanewmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/types/test.ts new file mode 100644 index 000000000000..a18e75baac78 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/docs/types/test.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanewmean = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanewmean( 0.5 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanewmean( '5' ); // $ExpectError + incrnanewmean( true ); // $ExpectError + incrnanewmean( false ); // $ExpectError + incrnanewmean( null ); // $ExpectError + incrnanewmean( undefined ); // $ExpectError + incrnanewmean( [] ); // $ExpectError + incrnanewmean( {} ); // $ExpectError + incrnanewmean( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanewmean( 0.5 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanewmean( 0.5 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanewmean/examples/index.js new file mode 100644 index 000000000000..c72b3ee82ac5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanewmean = require( './../lib' ); + +var accumulator; +var mu; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanewmean( 0.5 ); + +// For each simulated datum, update the exponentially weighted mean... +console.log( '\nValue\tMean\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + mu = accumulator( v ); + console.log( '%s\t%s', ( v === null ) ? v : v.toFixed( 4 ), ( mu === null ) ? mu : mu.toFixed( 4 ) ); +} +console.log( '\nFinal mean: %s\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanewmean/lib/index.js new file mode 100644 index 000000000000..9d20d2c5ad79 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute an exponentially weighted mean incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanewmean +* +* @example +* var incrnanewmean = require( '@stdlib/stats/incr/nanewmean' ); +* +* var accumulator = incrnanewmean( 0.5 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( NaN ); +* // returns 2.0 +* +* v = accumulator( -5.0 ); +* // returns -1.5 +* +* v = accumulator(); +* // returns -1.5 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanewmean/lib/main.js new file mode 100644 index 000000000000..95dfc9963df5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/lib/main.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var increwmean = require( '@stdlib/stats/incr/ewmean' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes an exponentially weighted mean, ignoring `NaN` values. +* +* @param {NonNegativeNumber} alpha - smoothing factor +* @throws {TypeError} must provide a nonnegative number +* @throws {RangeError} must be on the interval `[0,1]` +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanewmean( 0.5 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( NaN ); +* // returns 2.0 +* +* v = accumulator( -5.0 ); +* // returns -1.5 +* +* v = accumulator(); +* // returns -1.5 +*/ +function incrnanewmean( alpha ) { + var ewmean = increwmean( alpha ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated mean. If not provided a value, the accumulator function returns the current mean. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} mean value or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return ewmean(); + } + return ewmean( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanewmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/package.json b/lib/node_modules/@stdlib/stats/incr/nanewmean/package.json new file mode 100644 index 000000000000..f35f24e8c535 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/stats/incr/nanewmean", + "version": "0.0.0", + "description": "Compute an exponentially weighted mean incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "weighted", + "exponential", + "moving average", + "ema", + "ewma", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanewmean/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanewmean/test/test.js new file mode 100644 index 000000000000..7313f531ba20 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewmean/test/test.js @@ -0,0 +1,133 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var incrnanewmean = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanewmean, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a nonnegative number', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + NaN, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanewmean( value ); + }; + } +}); + +tape( 'the function throws an error if provided a nonnegative number which does not reside on the interval `[0,1]`', function test( t ) { + var values; + var i; + + values = [ + 1.5, + 3.14, + 1.0001, + 1.0e300 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), RangeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanewmean( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanewmean( 0.5 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanewmean( 0.5 ); + t.equal( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes an exponentially weighted mean', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 2.0, NaN, 4.0, NaN, 3.0, 4.0 ]; + N = data.length; + + expected = [ 2.0, 2.5, 2.25, 2.25, 3.125, 3.125, 3.0625, 3.53125 ]; + actual = []; + + acc = incrnanewmean( 0.5 ); + + for ( i = 0; i < N; i++ ) { + actual.push(acc( data[ i ] )); + } + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean', function test( t ) { + var data; + var acc; + var i; + + data = [ NaN, 3.0, 1.0 ]; + acc = incrnanewmean( 0.5 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 2.0, 'returns the current accumulated mean' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/README.md b/lib/node_modules/@stdlib/stats/incr/nanewstdev/README.md new file mode 100644 index 000000000000..4aa1d8baaefc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/README.md @@ -0,0 +1,156 @@ + + +# incrnanewstdev + +> Compute an [exponentially weighted standard deviation][moving-average] incrementally, ignoring `NaN` values. + +
+ +An [exponentially weighted variance][moving-average] can be defined recursively as + + + +```math +S_n = \begin{cases} 0 & \textrm{if}\ n = 0 \\ (1 - \alpha) (S_{n-1} + \alpha(x_n - \mu_{n-1})^2) & \textrm{if}\ n > 0 \end{cases} +``` + + + + + +where `μ` is the [exponentially weighted mean][@stdlib/stats/incr/ewmean]. The [exponentially weighted standard deviation][moving-average] is the square root of the [exponentially weighted variance][moving-average]. + +
+ + + +
+ +## Usage + +```javascript +var incrnanewstdev = require( '@stdlib/stats/incr/nanewstdev' ); +``` + +#### incrnanewstdev( alpha ) + +Returns an accumulator `function` which incrementally computes an [exponentially weighted standard deviation][moving-average], where `alpha` is a smoothing factor between `0` and `1`, ignoring `NaN` values. + +```javascript +var accumulator = incrnanewstdev( 0.5 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated standard deviation. If not provided an input value `x`, the accumulator function returns the current standard deviation. + +```javascript +var accumulator = incrnanewstdev( 0.5 ); + +var s = accumulator(); +// returns null + +s = accumulator( 2.0 ); +// returns 0.0 + +s = accumulator( 1.0 ); +// returns 0.5 + +s = accumulator( NaN ); +// returns 0.5 + +s = accumulator( 3.0 ); +// returns ~0.83 + +s = accumulator(); +// returns ~0.83 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanewstdev = require( '@stdlib/stats/incr/nanewstdev' ); + +var accumulator; +var s; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanewstdev( 0.5 ); + +// For each simulated datum, update the exponentially weighted standard deviation... +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.1 ) ? NaN : randu() * 100.0; + s = accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[moving-average]: https://en.wikipedia.org/wiki/Moving_average + +[@stdlib/stats/incr/ewmean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/ewmean + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanewstdev/benchmark/benchmark.js new file mode 100644 index 000000000000..843d2d95f1d9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanewstdev = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanewstdev( 0.5 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanewstdev( 0.5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/img/equation_exponentially_weighted_variance.svg b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/img/equation_exponentially_weighted_variance.svg new file mode 100644 index 000000000000..ec759179e837 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/img/equation_exponentially_weighted_variance.svg @@ -0,0 +1,89 @@ + +upper S Subscript n Baseline equals StartLayout Enlarged left-brace 1st Row 1st Column 0 2nd Column if n equals 0 2nd Row 1st Column left-parenthesis 1 minus alpha right-parenthesis left-parenthesis upper S Subscript n minus 1 Baseline plus alpha left-parenthesis x Subscript n Baseline minus mu Subscript n minus 1 Baseline right-parenthesis squared right-parenthesis 2nd Column if n greater-than 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/repl.txt new file mode 100644 index 000000000000..963c62d036c8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/repl.txt @@ -0,0 +1,37 @@ + +{{alias}}( α ) + Returns an accumulator function which incrementally computes an + exponentially weighted standard deviation, where α is a smoothing factor + between 0 and 1, ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated standard + deviation. If not provided a value, the accumulator function returns the + current standard deviation. + + Parameters + ---------- + α: number + Smoothing factor (value between 0 and 1). + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 0.5 ); + > var s = accumulator() + null + > s = accumulator( 2.0 ) + 0.0 + > s = accumulator( NaN ) + 0.0 + > s = accumulator( -5.0 ) + 3.5 + > s = accumulator() + 3.5 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/types/index.d.ts new file mode 100644 index 000000000000..fb39f89b5b59 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/types/index.d.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated standard deviation. If not provided a value, the accumulator function returns the current standard deviation. +* +* @param x - value +* @returns standard deviation or null +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes an exponentially weighted standard deviation, ignoring `NaN` values. +* +* @param alpha - smoothing factor +* @throws must be on the interval `[0,1]` +* @returns accumulator function +* +* @example +* var accumulator = incrnanewstdev( 0.5 ); +* +* var s = accumulator(); +* // returns null +* +* s = accumulator( 2.0 ); +* // returns 0.0 +* +* s = accumulator( NaN ); +* // returns 0.0 +* +* s = accumulator( -5.0 ); +* // returns 3.5 +* +* s = accumulator(); +* // returns 3.5 +*/ +declare function incrnanewstdev( alpha: number ): accumulator; + + +// EXPORTS // + +export = incrnanewstdev; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/types/test.ts new file mode 100644 index 000000000000..f8fe122a22c3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/docs/types/test.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanewstdev = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanewstdev( 0.5 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanewstdev( '5' ); // $ExpectError + incrnanewstdev( true ); // $ExpectError + incrnanewstdev( false ); // $ExpectError + incrnanewstdev( null ); // $ExpectError + incrnanewstdev( undefined ); // $ExpectError + incrnanewstdev( [] ); // $ExpectError + incrnanewstdev( {} ); // $ExpectError + incrnanewstdev( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanewstdev( 0.5 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanewstdev( 0.5 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanewstdev/examples/index.js new file mode 100644 index 000000000000..9eb5296f9793 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/examples/index.js @@ -0,0 +1,37 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanewstdev = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanewstdev( 0.5 ); + +// For each simulated datum, update the exponentially weighted standard deviation... +console.log( '\nValue\tStDev\n' ); +var s; +var v; +var i; +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.1 ) ? NaN : randu() * 100.0; // 10% chance of a NaN + s = accumulator( v ); + console.log( '%s\t%s', v.toFixed( 4 ), ( s === null ) ? NaN : s.toFixed( 4 ) ); +} +console.log( '\nFinal StDev: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/index.js new file mode 100644 index 000000000000..aa08a08da761 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute an exponentially weighted standard deviation incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanewstdev +* +* @example +* var incrnanewstdev = require( '@stdlib/stats/incr/nanewstdev' ); +* +* var accumulator = incrnanewstdev( 0.5 ); +* +* var s = accumulator(); +* // returns null +* +* s = accumulator( 2.0 ); +* // returns 0.0 +* +* s = accumulator( NaN ); +* // returns 0.0 +* +* s = accumulator( -5.0 ); +* // returns 3.5 +* +* s = accumulator(); +* // returns 3.5 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/main.js new file mode 100644 index 000000000000..f6d760b5fc1c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/lib/main.js @@ -0,0 +1,79 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var increwstdev = require( '@stdlib/stats/incr/ewstdev' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes an exponentially weighted standard deviation, ignoring `NaN` values. +* +* @param {NonNegativeNumber} alpha - smoothing factor +* @throws {TypeError} must provide a nonnegative number +* @throws {RangeError} must be on the interval `[0,1]` +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanewstdev( 0.5 ); +* +* var s = accumulator(); +* // returns null +* +* s = accumulator( 2.0 ); +* // returns 0.0 +* +* s = accumulator( NaN ); +* // returns 0.0 +* +* s = accumulator( -5.0 ); +* // returns 3.5 +* +* s = accumulator(); +* // returns 3.5 +*/ +function incrnanewstdev( alpha ) { + var ewstdev; + + ewstdev = increwstdev( alpha ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated standard deviation. If not provided a value, the accumulator function returns the current standard deviation. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} standard deviation or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return ewstdev(); + } + return ewstdev( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanewstdev; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/package.json b/lib/node_modules/@stdlib/stats/incr/nanewstdev/package.json new file mode 100644 index 000000000000..fa5b93747fed --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/stats/incr/nanewstdev", + "version": "0.0.0", + "description": "Compute an exponentially weighted standard deviation incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "stdev", + "std", + "variance", + "var", + "standard", + "deviation", + "dispersion", + "weighted", + "exponential", + "emsd", + "emv", + "ewmv", + "ewmsd", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanewstdev/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanewstdev/test/test.js new file mode 100644 index 000000000000..30f54b8e7e07 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewstdev/test/test.js @@ -0,0 +1,158 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var incrnanewstdev = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanewstdev, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a nonnegative number', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanewstdev( value ); + }; + } +}); + +tape( 'the function throws an error if provided a nonnegative number which does not reside on the interval `[0,1]`', function test( t ) { + var values; + var i; + + values = [ + 1.5, + 3.14, + 1.0001, + 1.0e300 + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), RangeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanewstdev( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanewstdev( 0.5 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanewstdev( 0.5 ); + t.equal( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes an exponentially weighted standard deviation', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ + 2.0, + NaN, + 3.0, + 2.0, + 4.0, + NaN, + 3.0, + 4.0 + ]; + N = data.length; + + // Note: manually computed using the recurrence relation S_n = (1-α)(S_{n-1} + α(x_n - mu_{n-1})^2) = S_n = (1-α)S_{n-1} + α(1-α)(x_n - mu_{n-1})^2 + expected = [ + 0.0, // m = 2.0, s2 = 0.0 + 0.0, // Ignore NaN values + sqrt( (0.5*0.0) + (0.25*pow( 3.0-2.0, 2 )) ), // m = 2.5, s2 = 0.25 + sqrt( (0.5*0.25) + (0.25*pow( 2.0-2.5, 2 )) ), // m = 2.25, s2 = 0.1875 + sqrt( (0.5*0.1875) + (0.25*pow( 4.0-2.25, 2 )) ), // m = 3.125, s2 = 0.859375 + sqrt( (0.5*0.1875) + (0.25*pow( 4.0-2.25, 2 )) ), // Ignore NaN values + sqrt( (0.5*0.859375) + (0.25*pow( 3.0-3.125, 2 )) ), // m = 3.0625, s2 = 0.43359375 + sqrt( (0.5*0.43359375) + (0.25*pow( 4.0-3.0625, 2 )) ) // m = 3.53125, s2 = 0.4365234375 + ]; + actual = []; + + acc = incrnanewstdev( 0.5 ); + + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current standard deviation', function test( t ) { + var data; + var acc; + var i; + + data = [ + 2.0, // m = 2.0, s2 = 0.0 + 3.0, // m = 2.5, s2 = 0.25 + NaN, // Ignore NaN values + 1.0 // m = 1.75, s2 = 0.6875 + ]; + acc = incrnanewstdev( 0.5 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), sqrt( 0.6875 ), 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/README.md b/lib/node_modules/@stdlib/stats/incr/nanewvariance/README.md new file mode 100644 index 000000000000..c65abc49c7c3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/README.md @@ -0,0 +1,148 @@ + + +# incrnanewvariance + +> Compute an [exponentially weighted variance][exponentially weighted variance] incrementally, ignoring `NaN` values. + +
+ +The [exponentially weighted variance][exponentially weighted variance] is defined as + + + +```math +S_n = \begin{cases} 0 & \textrm{if}\ n = 0 \\ (1 - \alpha) (S_{n-1} + \alpha(x_n - \mu_{n-1})^2) & \textrm{if}\ n > 0 \end{cases} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' ); +``` + +#### incrnanewvariance( alpha ) + +Returns an accumulator function which incrementally computes an [exponentially weighted variance][exponentially weighted variance], ignoring `NaN` values. + +```javascript +var accumulator = incrnanewvariance( 0.5 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated exponentially weighted variance. If not provided an input value `x`, the accumulator function returns the current exponentially weighted variance. + +```javascript +var accumulator = incrnanewvariance( 0.5 ); + +var v = accumulator(); +// returns null + +v = accumulator( 2.0 ); +// returns 0 + +v = accumulator( 4.0 ); +// returns 1 + +v = accumulator( NaN ); +// returns 1 + +v = accumulator( 5.0 ); +// returns 1.5 + +v = accumulator(); +// returns 1.5 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator with smoothing factor α = 0.5: +accumulator = incrnanewvariance( 0.5 ); + +// For each simulated datum, update the exponentially weighted variance... +for ( i = 0; i < 100; i++ ) { + // With a 20% chance, provide NaN to test that invalid inputs are ignored: + v = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[exponentially weighted variance]: https://en.wikipedia.org/wiki/EWMA_chart + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/benchmark/benchmark.js new file mode 100644 index 000000000000..ee2fc06627cb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/benchmark/benchmark.js @@ -0,0 +1,68 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanewvariance = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanewvariance( 0.5 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + acc = incrnanewvariance( 0.5 ); + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/img/equation_exponentially_weighted_variance.svg b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/img/equation_exponentially_weighted_variance.svg new file mode 100644 index 000000000000..ec759179e837 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/img/equation_exponentially_weighted_variance.svg @@ -0,0 +1,89 @@ + +upper S Subscript n Baseline equals StartLayout Enlarged left-brace 1st Row 1st Column 0 2nd Column if n equals 0 2nd Row 1st Column left-parenthesis 1 minus alpha right-parenthesis left-parenthesis upper S Subscript n minus 1 Baseline plus alpha left-parenthesis x Subscript n Baseline minus mu Subscript n minus 1 Baseline right-parenthesis squared right-parenthesis 2nd Column if n greater-than 0 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/repl.txt new file mode 100644 index 000000000000..8a7fe4f004c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/repl.txt @@ -0,0 +1,42 @@ + +{{alias}}( α ) + Returns an accumulator function which incrementally computes an + exponentially weighted variance, where α is a smoothing factor between 0 and + 1. This accumulator ignores any input values that are `NaN`. + + If provided a value, the accumulator function returns an updated variance. + If not provided a value, the accumulator function returns the current + variance. + + If provided `NaN` or a value which, when used in computations, results in + `NaN`, that input is ignored and the accumulated variance remains unchanged. + + Parameters + ---------- + α: number + Smoothing factor (value between 0 and 1). + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 0.5 ); + > var v = accumulator() + null + > v = accumulator( 2.0 ) + 0 + > v = accumulator( 4.0 ) + 1 + > v = accumulator( NaN ) + 1 + > v = accumulator( 5.0 ) + 1.5 + > v = accumulator() + 1.5 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/index.d.ts new file mode 100644 index 000000000000..d352ce759321 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/index.d.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated variance. If not provided a value, the accumulator function returns the current variance. +* +* ## Notes +* +* - If provided `NaN`, the input is ignored and the accumulated value remains unchanged. +* +* @param x - value +* @returns variance or null +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes an exponentially weighted variance, ignoring `NaN` values. +* +* @param alpha - smoothing factor +* @throws must provide a nonnegative number +* @throws must be on the interval `[0,1]` +* @returns accumulator function +* +* @example +* var accumulator = incrnanewvariance( 0.5 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 0 +* +* v = accumulator( 4.0 ); +* // returns 1.0 +* +* v = accumulator( NaN ); +* // returns 1.0 +* +* v = accumulator( 5.0 ); +* // returns 1.5 +* +* v = accumulator(); +* // returns 1.5 +*/ +declare function incrnanewvariance( alpha: number ): accumulator; + + +// EXPORTS // + +export = incrnanewvariance; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/test.ts new file mode 100644 index 000000000000..01fbe4b7aed5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/docs/types/test.ts @@ -0,0 +1,58 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanewvariance = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanewvariance( 0.5 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanewvariance( '5' ); // $ExpectError + incrnanewvariance( true ); // $ExpectError + incrnanewvariance( false ); // $ExpectError + incrnanewvariance( null ); // $ExpectError + incrnanewvariance( undefined ); // $ExpectError + incrnanewvariance( [] ); // $ExpectError + incrnanewvariance( {} ); // $ExpectError + incrnanewvariance( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanewvariance( 0.5 ); + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanewvariance( 0.5 ); + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/examples/index.js new file mode 100644 index 000000000000..c417adf8909a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanewvariance = require( './..' ); + +var accumulator; +var s2; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanewvariance( 0.5 ); + +// For each simulated datum, update the exponentially weighted variance... +console.log( '\nValue\tVariance\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + s2 = accumulator( v ); + console.log( '%s\t%s', ( isnan( v ) ) ? 'NaN' : v.toFixed( 4 ), ( s2 === null ) ? 'null' : s2.toFixed( 4 ) ); +} +console.log( '\nFinal variance: %s\n', ( accumulator() === null ) ? 'null' : accumulator().toFixed( 4 ) ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/index.js new file mode 100644 index 000000000000..2470b910ecf1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute an exponentially weighted variance incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanewvariance +* +* @example +* var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' ); +* +* var accumulator = incrnanewvariance( 0.5 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 0 +* +* v = accumulator( 4.0 ); +* // returns 1.0 +* +* v = accumulator( NaN ); +* // returns 1.0 +* +* v = accumulator( 5.0 ); +* // returns 1.5 +* +* v = accumulator(); +* // returns 1.5 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/main.js new file mode 100644 index 000000000000..8df03ffe3dfc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/lib/main.js @@ -0,0 +1,83 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var increwvariance = require( '@stdlib/stats/incr/ewvariance' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes an exponentially weighted variance, ignoring `NaN` values. +* +* @param {NonNegativeNumber} alpha - smoothing factor +* @throws {TypeError} must provide a nonnegative number +* @throws {RangeError} must be on the interval `[0,1]` +* @returns {Function} accumulator function +* +* @example +* var incrnanewvariance = require( '@stdlib/stats/incr/nanewvariance' ); +* +* var accumulator = incrnanewvariance( 0.5 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 0 +* +* v = accumulator( 4.0 ); +* // returns 1.0 +* +* v = accumulator( NaN ); +* // returns 1.0 +* +* v = accumulator( 5.0 ); +* // returns 1.5 +* +* v = accumulator(); +* // returns 1.5 +*/ +function incrnanewvariance( alpha ) { + var acc = increwvariance( alpha ); + return accumulator; + + /** + * Updates and returns the exponentially weighted variance when provided a numeric input. + * If no input is provided, returns the current exponentially weighted variance. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} updated exponentially weighted variance or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return acc(); + } + return acc( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanewvariance; diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/package.json b/lib/node_modules/@stdlib/stats/incr/nanewvariance/package.json new file mode 100644 index 000000000000..fb7d368454f2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/stats/incr/nanewvariance", + "version": "0.0.0", + "description": "Compute an exponentially weighted variance incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "weighted variance", + "ewvariance", + "variance", + "exponential", + "smoothing factor", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanewvariance/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanewvariance/test/test.js new file mode 100644 index 000000000000..2ab82afe8045 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanewvariance/test/test.js @@ -0,0 +1,94 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var incrnanewvariance = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanewvariance( 0.5 ); + t.strictEqual( acc(), null, 'returns null initially' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes an exponentially weighted variance', function test( t ) { + var expected; + var actual; + var data; + var acc; + var i; + + data = [ 2.0, 3.0, 2.0, 4.0, 3.0, 4.0 ]; + expected = [ + 0.0, // after 1st input + 0.25, // after 2nd input + 0.1875, // after 3rd input + 0.859375, // after 4th input + 0.43359375, // after 5th input + 0.4365234375 // after 6th input + ]; + + actual = []; + acc = incrnanewvariance( 0.5 ); + for ( i = 0; i < data.length; i++ ) { + actual.push( acc( data[ i ] ) ); + } + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'if not provided an input value, accumulator returns current variance', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, 3.0, 1.0 ]; + acc = incrnanewvariance( 0.5 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.strictEqual( acc(), 0.6875, 'returns expected variance' ); + t.end(); +}); + +tape( 'the accumulator function skips NaN inputs', function test( t ) { + var acc = incrnanewvariance( 0.5 ); + var v; + + v = acc( 2.0 ); + t.strictEqual( v, 0.0, 'returns 0.0 with one valid value' ); + + v = acc( NaN ); + t.strictEqual( v, 0.0, 'still returns 0.0 after NaN input' ); + + v = acc( 4.0 ); + t.strictEqual( v, 1.0, 'returns correct variance after second valid input' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/README.md b/lib/node_modules/@stdlib/stats/incr/nankurtosis/README.md new file mode 100644 index 000000000000..3df9eb687b76 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/README.md @@ -0,0 +1,197 @@ + + +# incrnankurtosis + +> Compute a [corrected sample excess kurtosis][sample-excess-kurtosis] incrementally, ignoring `NaN` values. + +
+ +The [kurtosis][sample-excess-kurtosis] for a random variable `X` is defined as + + + +```math +\mathop{\mathrm{Kurtosis}}[X] = \mathrm{E}\biggl[ \biggl( \frac{X - \mu}{\sigma} \biggr)^4 \biggr] +``` + + + + + +Using a univariate normal distribution as the standard of comparison, the [excess kurtosis][sample-excess-kurtosis] is the kurtosis minus `3`. + +For a sample of `n` values, the [sample excess kurtosis][sample-excess-kurtosis] is + + + +```math +g_2 = \frac{m_4}{m_2^2} - 3 = \frac{\frac{1}{n} \displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\frac{1}{n} \displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} +``` + + + + + +where `m_4` is the sample fourth central moment and `m_2` is the sample second central moment. + +The previous equation is, however, a biased estimator of the population excess kurtosis. An alternative estimator which is unbiased under normality is + + + +```math +G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnankurtosis = require( '@stdlib/stats/incr/nankurtosis' ); +``` + +#### incrnankurtosis() + +Returns an accumulator function which incrementally computes a [corrected sample excess kurtosis][sample-excess-kurtosis], ignoring `NaN` values. + +```javascript +var accumulator = incrnankurtosis(); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated [corrected sample excess kurtosis][sample-excess-kurtosis]. If not provided an input value `x`, the accumulator function returns the current [corrected sample excess kurtosis][sample-excess-kurtosis]. + +```javascript +var accumulator = incrnankurtosis(); + +var kurtosis = accumulator( 2.0 ); +// returns null + +kurtosis = accumulator( 2.0 ); +// returns null + +kurtosis = accumulator( -4.0 ); +// returns null + +kurtosis = accumulator( -4.0 ); +// returns -6.0 + +kurtosis = accumulator( NaN ); +// returns -6.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnankurtosis = require( '@stdlib/stats/incr/nankurtosis' ); + +var accumulator; +var kurtosis; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnankurtosis(); + +// For each simulated datum, update the corrected sample excess kurtosis... +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.2 ) ? NaN : randu() * 100.0; // 20% chance of NaN + kurtosis = accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + +* * * + +
+ +## References + +- Joanes, D. N., and C. A. Gill. 1998. "Comparing measures of sample skewness and kurtosis." _Journal of the Royal Statistical Society: Series D (The Statistician)_ 47 (1). Blackwell Publishers Ltd: 183–89. doi:[10.1111/1467-9884.00122][@joanes:1998]. + +
+ + + + + +
+ +
+ + + + + +
+ +[sample-excess-kurtosis]: https://en.wikipedia.org/wiki/Kurtosis + +[@joanes:1998]: http://onlinelibrary.wiley.com/doi/10.1111/1467-9884.00122/ + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nankurtosis/benchmark/benchmark.js new file mode 100644 index 000000000000..ab650b641c56 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnankurtosis = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnankurtosis(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnankurtosis(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_corrected_sample_excess_kurtosis.svg b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_corrected_sample_excess_kurtosis.svg new file mode 100644 index 000000000000..60f0e10c944d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_corrected_sample_excess_kurtosis.svg @@ -0,0 +1,153 @@ + +upper G 2 equals StartFraction left-parenthesis n plus 1 right-parenthesis n Over left-parenthesis n minus 1 right-parenthesis left-parenthesis n minus 2 right-parenthesis left-parenthesis n minus 3 right-parenthesis EndFraction StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis Superscript 4 Baseline Over left-parenthesis sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared right-parenthesis squared EndFraction minus 3 StartFraction left-parenthesis n minus 1 right-parenthesis squared Over left-parenthesis n minus 2 right-parenthesis left-parenthesis n minus 3 right-parenthesis EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_kurtosis.svg b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_kurtosis.svg new file mode 100644 index 000000000000..49e80f11cb5b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_kurtosis.svg @@ -0,0 +1,60 @@ + +upper K u r t o s i s left-bracket upper X right-bracket equals normal upper E left-bracket left-parenthesis StartFraction upper X minus mu Over sigma EndFraction right-parenthesis Superscript 4 Baseline right-bracket + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_sample_excess_kurtosis.svg b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_sample_excess_kurtosis.svg new file mode 100644 index 000000000000..e9c08dadc077 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/img/equation_sample_excess_kurtosis.svg @@ -0,0 +1,125 @@ + +g 2 equals StartFraction m 4 Over m 2 squared EndFraction minus 3 equals StartStartFraction StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis Superscript 4 Baseline OverOver left-parenthesis StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared right-parenthesis squared EndEndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/repl.txt new file mode 100644 index 000000000000..d162dec6c70c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/repl.txt @@ -0,0 +1,29 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes a corrected + sample excess kurtosis, ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated corrected + sample excess kurtosis. If not provided a value, the accumulator function + returns the current corrected sample excess kurtosis. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var v = accumulator( 2.0 ) + null + > v = accumulator( 2.0 ) + null + > v = accumulator( -4.0 ) + null + > v = accumulator( -4.0 ) + -6.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/types/index.d.ts new file mode 100644 index 000000000000..c6b02101efd0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated corrected sample excess kurtosis; otherwise, returns the current corrected sample excess kurtosis, ignoring `NaN` values. +* +* @param x - value +* @returns corrected sample excess kurtosis +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a corrected sample excess kurtosis, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnankurtosis(); +* +* var kurtosis = accumulator(); +* // returns null +* +* kurtosis = accumulator( 2.0 ); +* // returns null +* +* kurtosis = accumulator( 2.0 ); +* // returns null +* +* kurtosis = accumulator( -4.0 ); +* // returns null +* +* kurtosis = accumulator( -4.0 ); +* // returns -6.0 +* +* kurtosis = accumulator( NaN ); +* // returns -6.0 +*/ +declare function incrnankurtosis(): accumulator; + + +// EXPORTS // + +export = incrnankurtosis; diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/types/test.ts new file mode 100644 index 000000000000..817c47fafa74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnankurtosis = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnankurtosis(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnankurtosis( '5' ); // $ExpectError + incrnankurtosis( 5 ); // $ExpectError + incrnankurtosis( true ); // $ExpectError + incrnankurtosis( false ); // $ExpectError + incrnankurtosis( null ); // $ExpectError + incrnankurtosis( undefined ); // $ExpectError + incrnankurtosis( [] ); // $ExpectError + incrnankurtosis( {} ); // $ExpectError + incrnankurtosis( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnankurtosis(); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnankurtosis(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nankurtosis/examples/index.js new file mode 100644 index 000000000000..78295302aa94 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnankurtosis = require( './../lib' ); + +var accumulator; +var kurtosis; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnankurtosis(); + +// For each simulated datum, update the corrected sample excess kurtosis... +console.log( '\nValue\tKurtosis\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.2 ) ? NaN : randu() * 100.0; // 20% chance of `NaN` + kurtosis = accumulator( v ); + if ( i < 3 ) { + console.log( '%d\t%s', v.toFixed( 4 ), kurtosis ); + } else { + console.log( '%d\t%d', v.toFixed( 4 ), ( kurtosis === null ) ? kurtosis : kurtosis.toFixed( 4 ) ); + } +} +console.log( '\nFinal excess kurtosis: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nankurtosis/lib/index.js new file mode 100644 index 000000000000..0b61ef2c177c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a corrected sample excess kurtosis incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nankurtosis +* +* @example +* var incrnankurtosis = require( '@stdlib/stats/incr/nankurtosis' ); +* +* var accumulator = incrnankurtosis(); +* +* var kurtosis = accumulator( 2.0 ); +* // returns null +* +* kurtosis = accumulator( 2.0 ); +* // returns null +* +* kurtosis = accumulator( -4.0 ); +* // returns null +* +* kurtosis = accumulator( -4.0 ); +* // returns -6.0 +* +* kurtosis = accumulator( NaN ); +* // returns -6.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nankurtosis/lib/main.js new file mode 100644 index 000000000000..dbdb468f511e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/lib/main.js @@ -0,0 +1,87 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrkurtosis = require( '@stdlib/stats/incr/kurtosis' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a corrected sample excess kurtosis, ignoring `NaN` values. +* +* ## Method +* +* The algorithm computes the sample excess kurtosis using the formula for `G_2` in [Joanes and Gill 1998][@joanes:1998]. In contrast to alternatives for calculating a sample kurtosis, `G_2` is an unbiased estimator under normality. +* +* ## References +* +* - Joanes, D. N., and C. A. Gill. 1998. "Comparing measures of sample skewness and kurtosis." _Journal of the Royal Statistical Society: Series D (The Statistician)_ 47 (1). Blackwell Publishers Ltd: 183–89. doi:[10.1111/1467-9884.00122][@joanes:1998]. +* +* [@joanes:1998]: http://dx.doi.org/10.1111/1467-9884.00122 +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnankurtosis(); +* +* var kurtosis = accumulator(); +* // returns null +* +* kurtosis = accumulator( 2.0 ); +* // returns null +* +* kurtosis = accumulator( 2.0 ); +* // returns null +* +* kurtosis = accumulator( -4.0 ); +* // returns null +* +* kurtosis = accumulator( -4.0 ); +* // returns -6.0 +* +* kurtosis = accumulator( NaN ); +* // returns -6.0 +*/ +function incrnankurtosis() { + var kurtosis = incrkurtosis(); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated corrected sample excess kurtosis. If not provided a value, the accumulator function returns the current corrected sample excess kurtosis. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} corrected sample excess kurtosis + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return kurtosis(); + } + return kurtosis( x ); + } +} + + +// EXPORTS // + +module.exports = incrnankurtosis; diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/package.json b/lib/node_modules/@stdlib/stats/incr/nankurtosis/package.json new file mode 100644 index 000000000000..3aa1157edde1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/package.json @@ -0,0 +1,66 @@ +{ + "name": "@stdlib/stats/incr/nankurtosis", + "version": "0.0.0", + "description": "Compute a corrected sample excess kurtosis incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "kurtosis", + "sample kurtosis", + "shape", + "kurt", + "corrected", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nankurtosis/test/test.js b/lib/node_modules/@stdlib/stats/incr/nankurtosis/test/test.js new file mode 100644 index 000000000000..cdd1601b32e7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nankurtosis/test/test.js @@ -0,0 +1,118 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnankurtosis = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnankurtosis, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnankurtosis(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a corrected sample excess kurtosis', function test( t ) { + var expected; + var actual; + var delta; + var data; + var tol; + var acc; + var i; + + data = [ 2.0, NaN, 2.0, -4.0, -4.0, 1.5, NaN, -10 ]; + + // Check against the kurtosis function of the `e1071` R package: + expected = [ + null, + null, + null, + null, + -6, + -3.309339678762642, + -3.309339678762642, + -0.1906596382525679 + ]; + + acc = incrnankurtosis(); + + for ( i = 0; i < data.length; i++ ) { + actual = acc( data[ i ] ); + if ( expected[i] === null ) { + t.equal( actual, null, 'returns null' ); + } else { + delta = abs( actual - expected[ i ] ); + tol = 1.5 * EPS * abs( expected[ i ] ); + t.ok( delta <= tol, 'within tolerance. actual: '+actual+'. E: '+expected[i]+' Δ: '+delta+'. tol: '+tol ); + } + } + + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current corrected sample excess kurtosis', function test( t ) { + var data; + var acc; + var i; + + data = [ -10.0, NaN, -10.0, 10.0, NaN, 10.0 ]; + acc = incrnankurtosis(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + + t.equal( acc(), -6.0, 'returns the current accumulated corrected sample excess kurtosis' ); + t.end(); +}); + +tape( 'the corrected sample excess kurtosis is `null` until at least 4 datums have been provided', function test( t ) { + var acc; + var out; + + acc = incrnankurtosis(); + + out = acc(); + t.equal( out, null, 'returns null' ); + + out = acc( 2.0 ); + t.equal( out, null, 'returns null' ); + + out = acc( 8.0 ); + t.equal( out, null, 'returns null' ); + + out = acc( -4.0 ); + t.equal( out, null, 'returns null' ); + + out = acc( 3.0 ); + t.notEqual( out, null, 'does not return null' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/README.md b/lib/node_modules/@stdlib/stats/incr/nanmae/README.md new file mode 100644 index 000000000000..77f56ebacdc2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/README.md @@ -0,0 +1,158 @@ + + +# incrnanmae + +> Compute the [mean absolute error][mean-absolute-error] (MAE) incrementally, ignoring `NaN` values. + +
+ +The [mean absolute error][mean-absolute-error] is defined as + + + +```math +\mathop{\mathrm{MAE}} = \frac{\displaystyle\sum_{i=0}^{n-1} |y_i - x_i|}{n} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmae = require( '@stdlib/stats/incr/nanmae' ); +``` + +#### incrnanmae() + +Returns an accumulator `function` which incrementally computes the [mean absolute error][mean-absolute-error] ignoring NaN values. + +```javascript +var accumulator = incrnanmae(); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated [mean absolute error][mean-absolute-error]. If not provided input values `x` and `y`, the accumulator function returns the current [mean absolute error][mean-absolute-error]. + +```javascript +var accumulator = incrnanmae(); + +var m = accumulator(); +// returns null + +m = accumulator( 2.0, 3.0 ); +// returns 1.0 + +m = accumulator( NaN, 2.0 ); +// returns 1.0 + +m = accumulator( -5.0, NaN ); +// returns 1.0 + +m = accumulator( NaN, NaN ); +// returns 1.0 + +m = accumulator( -5.0, 2.0 ); +// returns 4.0 + +m = accumulator(); +// returns 4.0 +``` + +
+ + + +
+ +## Notes + +- Input values are not type checked beyond checking for NaN. If provided values which are not numbers or NaN (e.g., strings, booleans), the behavior of the accumulator is undefined. If non-numeric inputs are possible, you are advised to type check and handle accordingly before passing the value to the accumulator function. +- If both provided values are NaN, the accumulated value is unchanged. The accumulator only updates when both inputs are valid numbers. +- **Warning**: the [mean absolute error][mean-absolute-error] is scale-dependent and, thus, the measure should **not** be used to make comparisons between datasets having different scales. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmae = require( '@stdlib/stats/incr/nanmae' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmae(); + +// For each simulated datum, update the mean absolute error... +for ( i = 0; i < 100; i++ ) { + v1 = ( randu() < 0.2 ) ? NaN : ( randu()*100.0 ) - 50.0; + v2 = ( randu() < 0.2 ) ? NaN : ( randu()*100.0 ) - 50.0; + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mean-absolute-error]: https://en.wikipedia.org/wiki/Mean_absolute_error + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmae/benchmark/benchmark.js new file mode 100644 index 000000000000..1ea993ea3813 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/benchmark/benchmark.js @@ -0,0 +1,106 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmae = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmae(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + var x; + var y; + + acc = incrnanmae(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + x = ( randu() < 0.2 ) ? NaN : randu()-0.5; + y = ( randu() < 0.2 ) ? NaN : randu()-0.5; + v = acc( x, y ); + if ( v !== v && !isnan( x ) && !isnan( y ) ) { + b.fail( 'should not return NaN when inputs are not NaN' ); + } + } + b.toc(); + if ( v !== v && !isnan( x ) && !isnan( y ) ) { + b.fail( 'should not return NaN when inputs are not NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,nan_handling', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + acc = incrnanmae(); // Reset accumulator for each iteration + v = acc(); // Initial state + if ( v !== null ) { + b.fail( 'initial value should be null' ); + } + acc( 2.0, 3.0 ); // Set a baseline MAE + v = acc( NaN, randu()-0.5 ); + if ( typeof v !== 'number' || isnan( v ) ) { + b.fail( 'should return a number when one input is NaN' ); + } + v = acc( randu()-0.5, NaN ); + if ( typeof v !== 'number' || isnan( v ) ) { + b.fail( 'should return a number when one input is NaN' ); + } + v = acc( NaN, NaN ); + if ( typeof v !== 'number' || isnan( v ) ) { + b.fail( 'should return a number when both inputs are NaN' ); + } + } + b.toc(); + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/docs/img/equation_mean_absolute_error.svg b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/img/equation_mean_absolute_error.svg new file mode 100644 index 000000000000..8ca0b90df05f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/img/equation_mean_absolute_error.svg @@ -0,0 +1,54 @@ + +upper M upper A upper E equals StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts StartAbsoluteValue y Subscript i Baseline minus x Subscript i Baseline EndAbsoluteValue Over n EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/repl.txt new file mode 100644 index 000000000000..7c907d14fe40 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes the mean + absolute error, ignoring `NaN` values. + + If provided two values, the accumulator function returns an updated mean + absolute error. If not provided values, the accumulator function returns + the current mean absolute error. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var incrnanmae = require( '@stdlib/stats/incr/nanmae' ); + > var accumulator = incrnanmae(); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + 1.0 + > m = accumulator( NaN, 2.0 ) + 1.0 + > m = accumulator( -5.0, NaN ) + 1.0 + > m = accumulator( NaN, NaN ) + 1.0 + > m = accumulator( -5.0, 2.0 ) + 4.0 + > m = accumulator() + 4.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/types/index.d.ts new file mode 100644 index 000000000000..877bc85a82d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/types/index.d.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided input values, the accumulator function returns an updated mean absolute error. If not provided input values, the accumulator function returns the current mean absolute error. +* +* ## Notes +* +* - If either provided value is `NaN`, the accumulated value is unchanged and remains the current mean absolute error (or `null` if no valid values have been provided). +* +* @param x - input value +* @param y - input value +* @returns mean absolute error or null +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes the mean absolute error, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanmae(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( NaN, 2.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, NaN ); +* // returns 1.0 +* +* m = accumulator( NaN, NaN ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator(); +* // returns 4.0 +*/ +declare function incrnanmae(): accumulator; + + +// EXPORTS // + +export = incrnanmae; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/types/test.ts new file mode 100644 index 000000000000..2801d23c606b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/docs/types/test.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmae = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmae(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanmae( '5' ); // $ExpectError + incrnanmae( 5 ); // $ExpectError + incrnanmae( true ); // $ExpectError + incrnanmae( false ); // $ExpectError + incrnanmae( null ); // $ExpectError + incrnanmae( undefined ); // $ExpectError + incrnanmae( [] ); // $ExpectError + incrnanmae( {} ); // $ExpectError + incrnanmae( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmae(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null + acc( NaN, 2.0 ); // $ExpectType number | null + acc( -5.0, NaN ); // $ExpectType number | null + acc( NaN, NaN ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmae(); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmae/examples/index.js new file mode 100644 index 000000000000..0c1affd8d865 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmae = require( './../lib' ); + +var accumulator; +var err; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmae(); + +// For each simulated datum, update the mean absolute error... +console.log( '\nValue\tValue\tMean\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( randu() < 0.2 ) ? NaN : ( randu()*100.0 ) - 50.0; + v2 = ( randu() < 0.2 ) ? NaN : ( randu()*100.0 ) - 50.0; + err = accumulator( v1, v2 ); + console.log( '%s\t%s\t%s', v1.toFixed( 3 ), v2.toFixed( 3 ), ( err === null ) ? NaN : err.toFixed( 3 ) ); +} +console.log( '\nFinal MAE: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmae/lib/index.js new file mode 100644 index 000000000000..fddc60d2484e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the mean absolute error incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmae +* +* @example +* var incrnanmae = require( '@stdlib/stats/incr/nanmae' ); +* +* var accumulator = incrnanmae(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( NaN, 2.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, NaN ); +* // returns 1.0 +* +* m = accumulator( NaN, NaN ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator(); +* // returns 4.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmae/lib/main.js new file mode 100644 index 000000000000..ffdef717e694 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/lib/main.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmae = require( '@stdlib/stats/incr/mae' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes the mean absolute error, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmae(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( NaN, 2.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, NaN ); +* // returns 1.0 +* +* m = accumulator( NaN, NaN ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator(); +* // returns 4.0 +*/ +function incrnanmae() { + var mae = incrmae(); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated mean absolute error. If not provided input values, the accumulator function returns the current mean absolute error. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} mean absolute error or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 ) { + return mae(); + } + if ( isnan( x ) || isnan( y ) ) { + return mae(); + } + return mae( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmae; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/package.json b/lib/node_modules/@stdlib/stats/incr/nanmae/package.json new file mode 100644 index 000000000000..4487fb71e202 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/package.json @@ -0,0 +1,67 @@ +{ + "name": "@stdlib/stats/incr/nanmae", + "version": "0.0.0", + "description": "Compute the mean absolute error incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "absolute", + "avg", + "mean", + "arithmetic mean", + "central tendency", + "error", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmae/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmae/test/test.js new file mode 100644 index 000000000000..53b84d6151a1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmae/test/test.js @@ -0,0 +1,116 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmae = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmae, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmae(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanmae(); + t.equal( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes the mean absolute error, ignoring NaN values', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var sum; + var tol; + var N; + var n; + var x; + var y; + var i; + + data = [ + [ 2.0, 3.0 ], // MAE = |2-3| / 1 = 1.0 + [ 3.0, NaN ], // Ignored, MAE = 1.0 + [ NaN, 5.0 ], // Ignored, MAE = 1.0 + [ 4.0, -4.0 ], // MAE = (1 + |4-(-4)|) / 2 = 4.5 + [ NaN, NaN ], // Ignored, MAE = 4.5 + [ -4.0, 5.0 ] // MAE = (1 + 8 + |-4-5|) / 3 = 6.0 + ]; + N = data.length; + + acc = incrnanmae(); + + sum = 0; + n = 0; // Count of valid pairs + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + sum += abs( y-x ); + n += 1; + expected = sum / n; + } else { + expected = ( n === 0 ) ? null : sum / n; + } + actual = acc( x, y ); + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value' ); + } else { + delta = abs( expected - actual ); + tol = 1.0 * EPS * abs( expected ); + t.equal( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean absolute error', function test( t ) { + var data; + var acc; + var i; + + data = [ + [ 2.0, 3.0 ], // MAE = 1.0 + [ NaN, -5.0 ], // Ignored, MAE = 1.0 + [ 1.0, NaN ], // Ignored, MAE = 1.0 + [ 1.0, 10.0 ] // MAE = (1 + |1-10|) / 2 = 5.0 + ]; + acc = incrnanmae(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + t.equal( acc(), 5.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/README.md b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/README.md new file mode 100644 index 000000000000..ec69157edaae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/README.md @@ -0,0 +1,194 @@ + + +# incrnanmapcorr + +> Compute a moving sample absolute [Pearson product-moment correlation coefficient][pearson-correlation] incrementally, ignoring `NaN` values. + +
+ +The [Pearson product-moment correlation coefficient][pearson-correlation] between random variables `X` and `Y` is defined as + + + +```math +\rho_{X,Y} = \frac{\mathop{\mathrm{cov}}(X,Y)}{\sigma_X \sigma_Y} +``` + + + + + +where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations. + +For a sample of size `W`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as + + + +```math +r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}} +``` + + + + + +The sample **absolute** [Pearson product-moment correlation coefficient][pearson-correlation] is thus defined as the absolute value of the sample [Pearson product-moment correlation coefficient][pearson-correlation]. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmapcorr = require( '@stdlib/stats/incr/nanmapcorr' ); +``` + +#### incrnanmapcorr( window\[, mx, my] ) + +Returns an accumulator `function` which incrementally computes a moving sample absolute [Pearson product-moment correlation coefficient][pearson-correlation]. The `window` parameter defines the number of values over which to compute the moving sample absolute [Pearson product-moment correlation coefficient][pearson-correlation]. + +```javascript +var accumulator = incrnanmapcorr( 3 ); +``` + +If means are already known, provide `mx` and `my` arguments. + +```javascript +var accumulator = incrnanmapcorr( 3, 5.0, -3.14 ); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated accumulated value. If not provided input values `x` and `y`, the accumulator function returns the current accumulated value. + +```javascript +var accumulator = incrnanmapcorr( 3 ); + +var ar = accumulator(); +// returns null + +// Fill the window... +ar = accumulator( 2.0, 1.0 ); // [(2.0, 1.0)] +// returns 0.0 + +ar = accumulator( -5.0, 3.14 ); // [(2.0, 1.0), (-5.0, 3.14)] +// returns ~1.0 + +ar = accumulator( 3.0, -1.0 ); // [(2.0, 1.0), (-5.0, 3.14), (3.0, -1.0)] +// returns ~0.925 + +ar = accumulator( 3.0, NaN ); // [(2.0, 1.0), (-5.0, 3.14), (3.0, -1.0)] +// returns ~0.925 + +// Window begins sliding... +ar = accumulator( 5.0, -9.5 ); // [(-5.0, 3.14), (3.0, -1.0), (5.0, -9.5)] +// returns ~0.863 + +ar = accumulator( -5.0, 1.5 ); // [(3.0, -1.0), (5.0, -9.5), (-5.0, 1.5)] +// returns ~0.803 + +ar = accumulator(); +// returns ~0.803 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN` for either input value, the value is ignored and the accumulator function returns the current sample absolute correlation coefficient without updating the window. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +- In comparison to the sample [Pearson product-moment correlation coefficient][pearson-correlation], the sample absolute [Pearson product-moment correlation coefficient][pearson-correlation] is useful when only concerned with the strength of the correlation and not the direction. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmapcorr = require( '@stdlib/stats/incr/nanmapcorr' ); + +var accumulator; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmapcorr( 5 ); + +// For each simulated datum, update the moving sample absolute correlation coefficient... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } else { + y = randu() * 100.0; + } + accumulator( x, y ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +[covariance]: https://en.wikipedia.org/wiki/Covariance + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/benchmark/benchmark.js new file mode 100644 index 000000000000..1c7c6cb5d760 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/benchmark/benchmark.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmapcorr = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmapcorr( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmapcorr( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmapcorr( 5, 3.0, -1.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/img/equation_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/img/equation_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..61e3ef3e3500 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/img/equation_pearson_correlation_coefficient.svg @@ -0,0 +1,48 @@ + +rho Subscript upper X comma upper Y Baseline equals StartFraction c o v left-parenthesis upper X comma upper Y right-parenthesis Over sigma Subscript upper X Baseline sigma Subscript upper Y Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..31facfed161b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg @@ -0,0 +1,126 @@ + +r equals StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis Over StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis squared EndRoot EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/repl.txt new file mode 100644 index 000000000000..c39a229c2a02 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/repl.txt @@ -0,0 +1,55 @@ + +{{alias}}( W[, mx, my] ) + Returns an accumulator function which incrementally computes a moving + sample absolute Pearson product-moment correlation coefficient, + ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving sample absolute correlation coefficient. + + If provided values, the accumulator function returns an updated moving + sample absolute correlation coefficient. If not provided values, the + accumulator function returns the current moving sample absolute correlation + coefficient. + + As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + mx: number (optional) + Known mean. + + my: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var ar = accumulator() + null + > ar = accumulator( 2.0, 1.0 ) + 0.0 + > ar = accumulator( -5.0, 3.14 ) + ~1.0 + > ar = accumulator( 3.0, -1.0 ) + ~0.925 + > ar = accumulator( 3.0, NaN ) + ~0.925 + > ar = accumulator( 5.0, -9.5 ) + ~0.863 + > ar = accumulator() + ~0.863 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/types/index.d.ts new file mode 100644 index 000000000000..52604a694c32 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/types/index.d.ts @@ -0,0 +1,80 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated accumulated value. If not provided a value, the accumulator function returns the current accumulated value. +* +* @param x - input value +* @param y - input value +* @returns sample absolute correlation coefficient or null +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving sample absolute Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @param W - window size +* @param meanx - mean value +* @param meany - mean value +* @returns accumulator function +* +* @example +* var accumulator = incrnanmapcorr( 3, -2.0, 10.0 ); +*/ +declare function incrnanmapcorr( W: number, meanx: number, meany: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes a moving sample absolute Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @param W - window size +* @returns accumulator function +* +* @example +* var accumulator = incrnanmapcorr( 3 ); +* +* var ar = accumulator(); +* // returns null +* +* ar = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* ar = accumulator( -5.0, 3.14 ); +* // returns ~1.0 +* +* ar = accumulator( 3.0, -1.0 ); +* // returns ~0.925 +* +* ar = accumulator( 3.0, NaN ); +* // returns ~0.925 +* +* ar = accumulator( 5.0, -9.5 ); +* // returns ~0.863 +* +* ar = accumulator(); +* // returns ~0.863 +*/ +declare function incrnanmapcorr( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmapcorr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/types/test.ts new file mode 100644 index 000000000000..7ceb1341a928 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/docs/types/test.ts @@ -0,0 +1,123 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmapcorr = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmapcorr( 3 ); // $ExpectType accumulator + incrnanmapcorr( 3, 2.5, 4.5 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided non-numeric arguments... +{ + incrnanmapcorr( 2, '5' ); // $ExpectError + incrnanmapcorr( 2, true ); // $ExpectError + incrnanmapcorr( 2, false ); // $ExpectError + incrnanmapcorr( 2, null ); // $ExpectError + incrnanmapcorr( 2, undefined ); // $ExpectError + incrnanmapcorr( 2, [] ); // $ExpectError + incrnanmapcorr( 2, {} ); // $ExpectError + incrnanmapcorr( 2, ( x: number ): number => x ); // $ExpectError + + incrnanmapcorr( '5', 4 ); // $ExpectError + incrnanmapcorr( true, 4 ); // $ExpectError + incrnanmapcorr( false, 4 ); // $ExpectError + incrnanmapcorr( null, 4 ); // $ExpectError + incrnanmapcorr( undefined, 4 ); // $ExpectError + incrnanmapcorr( [], 4 ); // $ExpectError + incrnanmapcorr( {}, 4 ); // $ExpectError + incrnanmapcorr( ( x: number ): number => x, 4 ); // $ExpectError + + incrnanmapcorr( '5', 2.5, 3.5 ); // $ExpectError + incrnanmapcorr( true, 2.5, 3.5 ); // $ExpectError + incrnanmapcorr( false, 2.5, 3.5 ); // $ExpectError + incrnanmapcorr( null, 2.5, 3.5 ); // $ExpectError + incrnanmapcorr( undefined, 2.5, 3.5 ); // $ExpectError + incrnanmapcorr( [], 2.5, 3.5 ); // $ExpectError + incrnanmapcorr( {}, 2.5, 3.5 ); // $ExpectError + incrnanmapcorr( ( x: number ): number => x, 2.5, 3.5 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmapcorr(); // $ExpectError + incrnanmapcorr( 2, 2 ); // $ExpectError + incrnanmapcorr( 2, 2, 3, 4 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmapcorr( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The function returns an accumulator function which returns an accumulated result (known means)... +{ + const acc = incrnanmapcorr( 3, 2, -3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmapcorr( 3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)... +{ + const acc = incrnanmapcorr( 3, 2, -3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/examples/index.js new file mode 100644 index 000000000000..0ed5db0c741f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/examples/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmapcorr = require( './../lib' ); + +var accumulator; +var ar; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmapcorr( 5 ); + +// For each simulated datum, update the moving sample absolute correlation coefficient... +console.log( '\nx\ty\t|r|\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } else { + y = randu() * 100.0; + } + ar = accumulator( x, y ); + console.log( '%d\t%d\t%s', x.toFixed( 4 ), y.toFixed( 4 ), ( ar === null ) ? 'null' : ar.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/lib/index.js new file mode 100644 index 000000000000..d34604bb1c3b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving sample absolute Pearson product-moment correlation coefficient incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmapcorr +* +* @example +* var incrnanmapcorr = require( '@stdlib/stats/incr/nanmapcorr' ); +* +* var accumulator = incrnanmapcorr( 3 ); +* +* var ar = accumulator(); +* // returns null +* +* ar = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* ar = accumulator( -5.0, 3.14 ); +* // returns ~1.0 +* +* ar = accumulator( 3.0, -1.0 ); +* // returns ~0.925 +* +* ar = accumulator( 3.0, NaN ); +* // returns ~0.925 +* +* ar = accumulator( 5.0, -9.5 ); +* // returns ~0.863 +* +* ar = accumulator(); +* // returns ~0.863 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/lib/main.js new file mode 100644 index 000000000000..e60773962725 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/lib/main.js @@ -0,0 +1,95 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmapcorr = require( '@stdlib/stats/incr/mapcorr' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving sample absolute Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @param {number} [meanx] - mean value +* @param {number} [meany] - mean value +* @throws {TypeError} first argument must be a positive integer +* @throws {TypeError} second argument must be a number +* @throws {TypeError} third argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmapcorr( 3 ); +* +* var ar = accumulator(); +* // returns null +* +* ar = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* ar = accumulator( -5.0, 3.14 ); +* // returns ~1.0 +* +* ar = accumulator( 3.0, -1.0 ); +* // returns ~0.925 +* +* ar = accumulator( 3.0, NaN ); +* // returns ~0.925 +* +* ar = accumulator( 5.0, -9.5 ); +* // returns ~0.863 +* +* ar = accumulator(); +* // returns ~0.863 +* +* @example +* var accumulator = incrnanmapcorr( 3, -2.0, 10.0 ); +*/ +function incrnanmapcorr( W, meanx, meany ) { + var acc; + if ( arguments.length > 1 ) { + acc = incrmapcorr( W, meanx, meany ); + } else { + acc = incrmapcorr( W ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated accumulated value. If not provided a value, the accumulator function returns the current accumulated value. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} sample absolute correlation coefficient or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return acc(); + } + return acc( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmapcorr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/package.json b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/package.json new file mode 100644 index 000000000000..c2c321a7b102 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/package.json @@ -0,0 +1,82 @@ +{ + "name": "@stdlib/stats/incr/nanmapcorr", + "version": "0.0.0", + "description": "Compute a moving sample absolute Pearson product-moment correlation coefficient incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "covariance", + "sample covariance", + "variance", + "unbiased", + "var", + "correlation", + "corr", + "apcorr", + "pearson", + "product-moment", + "absolute", + "value", + "abs", + "bivariate", + "incremental", + "accumulator", + "moving covariance", + "moving correlation", + "sliding window", + "sliding", + "window", + "moving", + "rolling" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmapcorr/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/test/test.js new file mode 100644 index 000000000000..695c7c865fb0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmapcorr/test/test.js @@ -0,0 +1,639 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmapcorr = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Computes sample means using Welford's algorithm. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @returns {Array} output array +*/ +function mean( out, arr ) { + var delta; + var mx; + var my; + var N; + var i; + + mx = 0.0; + my = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[i][0] - mx; + mx += delta / N; + delta = arr[i][1] - my; + my += delta / N; + } + out[ 0 ] = mx; + out[ 1 ] = my; + return out; +} + +/** +* Computes standard deviations. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute a biased standard deviation +* @returns {Array} output array +*/ +function stdev( out, arr, mx, my, bool ) { + var delta; + var M2x; + var M2y; + var N; + var i; + + M2x = 0.0; + M2y = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[i][0] - mx; + M2x += delta * delta; + delta = arr[i][1] - my; + M2y += delta * delta; + } + if ( bool ) { + out[ 0 ] = sqrt( M2x / N ); + out[ 1 ] = sqrt( M2y / N ); + return out; + } + if ( N < 2 ) { + out[ 0 ] = 0.0; + out[ 1 ] = 0.0; + return out; + } + out[ 0 ] = sqrt( M2x / (N-1) ); + out[ 1 ] = sqrt( M2y / (N-1) ); + return out; +} + +/** +* Computes the covariance using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population covariance +* @returns {number} covariance +*/ +function covariance( arr, mx, my, bool ) { + var N; + var C; + var i; + + N = arr.length; + C = 0.0; + for ( i = 0; i < N; i++ ) { + C += ( arr[i][0]-mx ) * ( arr[i][1]-my ); + } + if ( bool ) { + return C / N; + } + if ( N === 1 ) { + return 0.0; + } + return C / (N-1); +} + +/** +* Computes the sample absolute Pearson product-moment correlation coefficient using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population correlation coefficient +* @returns {number} absolute correlation coefficient +*/ +function apcorr( arr, mx, my, bool ) { + var cov; + var sd; + if ( bool === false && arr.length < 2 ) { + return 0.0; + } + sd = stdev( [ 0.0, 0.0 ], arr, mx, my, bool ); + cov = covariance( arr, mx, my, bool ); + return abs( cov / ( sd[0]*sd[1] ) ); +} + +/** +* Generates a set of sample datasets. +* +* @private +* @param {PositiveInteger} N - number of datasets +* @param {PositiveInteger} M - dataset length +* @param {PositiveInteger} [seed] - PRNG seed +* @returns {ArrayArray} sample datasets +*/ +function datasets( N, M, seed ) { + var data; + var rand; + var tmp; + var i; + var j; + var x; + var y; + + rand = randu.factory({ + 'seed': seed || ( randu()*pow( 2.0, 31 ) )|0 + }); + + // Generate datasets consisting of (x,y) pairs of varying value ranges... + data = []; + for ( i = 0; i < N; i++ ) { + tmp = []; + for ( j = 0; j < M; j++ ) { + x = ( rand() < 0.1 ) ? NaN : rand() * pow( 10.0, i ); + y = ( rand() < 0.1 ) ? NaN : rand() * pow( 10.0, i ); + tmp.push( [ x, y ] ); + } + data.push( tmp ); + } + return data; +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmapcorr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmapcorr( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (known means)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmapcorr( value, 3.0, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmapcorr( 3, value, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmapcorr( 3, 3.14, value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmapcorr( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known means)', function test( t ) { + t.equal( typeof incrnanmapcorr( 3, 3.0, 3.14 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving sample absolute Pearson product-moment correlation coefficient incrementally and skip NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var delta; + var means; + var prev; + var data; + var acc; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var x; + var y; + + N = 10; + M = 100; + data = datasets( N, M, randu.seed ); + + // Define the window size: + W = 10; + + // For each dataset, compute the actual and expected correlation coefficients... + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + acc = incrnanmapcorr( W ); + validData = []; + prev = null; + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + means = mean( [ 0.0, 0.0 ], validData ); + expected = apcorr( validData, means[0], means[1], false ); + prev = expected; + } + if ( isnan( expected ) ) { + t.equal( isnan( actual ), true, 'returns NaN for window: '+i ); + } else if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. dataset: '+i+'. window: '+j+'.' ); + } else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.equal( delta < tol, true, 'dataset: '+i+'. window: '+j+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + } + t.end(); +}); + +tape( 'the accumulator function computes a moving sample absolute Pearson product-moment correlation coefficient incrementally (known means) and skip NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var means; + var delta; + var data; + var prev; + var acc; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var x; + var y; + + N = 10; + M = 100; + data = datasets( N, M, randu.seed ); + validData = []; + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + } + } + } + means = mean([0.0, 0.0], validData); + W = 10; + + // For each dataset, compute the actual and expected correlation coefficients... + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + means = mean( [ 0.0, 0.0 ], d ); + acc = incrnanmapcorr( W, means[ 0 ], means[ 1 ] ); + validData = []; + prev = null; + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + expected = apcorr(validData, means[0], means[1], true); + prev = expected; + } + if ( isnan( expected ) ) { + t.equal( isnan( actual ), true, 'dataset: '+i+', window: '+j+' returns NaN as expected' ); + } else if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. dataset: '+i+'. window: '+j+'.' ); + } else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.equal( delta < tol, true, 'dataset: '+i+'. window: '+j+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample absolute correlation coefficient (unknown means) and skips NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var means; + var delta; + var prev; + var data; + var tol; + var acc; + var W; + var N; + var i; + var x; + var y; + + data = [ + [ 2.0, 1.0 ], + [ NaN, 3.14 ], + [ 3.0, -1.0 ], + [ 5.0, -9.5 ] + ]; + N = data.length; + + // Window size: + W = 3; + acc = incrnanmapcorr( W ); + validData = []; + prev = null; + + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + means = mean( [ 0.0, 0.0 ], validData ); + expected = apcorr( validData, means[ 0 ], means[ 1 ], false ); + prev = expected; + } + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. window: '+i+'.' ); + } else { + delta = abs( actual - expected ); + tol = 2.0 * EPS * abs( expected ); + t.equal( delta < tol, true, 'window: '+i+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample absolute correlation coefficient (known means) and skips NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var means; + var delta; + var prev; + var data; + var tol; + var acc; + var W; + var N; + var i; + var x; + var y; + + data = [ + [ 2.0, 1.0 ], + [ NaN, 3.14 ], + [ 3.0, -1.0 ], + [ 5.0, -9.5 ] + ]; + N = data.length; + validData = []; + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + } + } + means = mean( [ 0.0, 0.0 ], validData ); + + // Window size: + W = 3; + acc = incrnanmapcorr( W, means[ 0 ], means[ 1 ] ); + validData = []; + prev = null; + + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + expected = apcorr( validData, means[ 0 ], means[ 1 ], true ); + prev = expected; + } + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. window: '+i+'.' ); + } else { + delta = abs( actual - expected ); + tol = 2.0 * EPS * abs( expected ); + t.equal( delta < tol, true, 'window: '+i+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmapcorr( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null` (known means)', function test( t ) { + var acc = incrnanmapcorr( 3, 3.0, 3.14 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are unknown, the accumulator function returns `0`', function test( t ) { + var acc = incrnanmapcorr( 3 ); + acc( 2.0, 3.14 ); + t.equal( acc(), 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are known, the accumulator function may not return `0`', function test( t ) { + var acc = incrnanmapcorr( 3, 30.0, -100.0 ); + acc( 2.0, 1.0 ); + t.notEqual( acc(), 0.0, 'does not return 0' ); + t.end(); +}); + +tape( 'if the window size is `1` and the means are unknown, the accumulator function always returns `0`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmapcorr( 1 ); + for ( i = 0; i < 100; i++ ) { + r = acc( randu()*100.0, randu()*100.0 ); + t.equal( r, 0.0, 'returns 0' ); + } + t.end(); +}); + +tape( 'if the window size is `1` and the means are known, the accumulator function may not always return `0`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmapcorr( 1, 500.0, -500.0 ); // means are outside the range of simulated values so the correlation should never be zero + for ( i = 0; i < 100; i++ ) { + r = acc( randu()*100.0, randu()*100.0 ); + t.notEqual( r, 0.0, 'does not return 0' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/README.md b/lib/node_modules/@stdlib/stats/incr/nanmape/README.md new file mode 100644 index 000000000000..6937246e9b71 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/README.md @@ -0,0 +1,160 @@ + + +# incrnanmape + +> Compute the [mean absolute percentage error][mean-absolute-percentage-error] (MAPE) incrementally, ignoring `NaN` values. + +
+ +The [mean absolute percentage error][mean-absolute-percentage-error] is defined as + + + +```math +\mathop{\mathrm{MAPE}} = \frac{100}{n} \sum_{i=0}^{n-1} \biggl| \frac{a_i - f_i}{a_i} \biggr| +``` + + + + + +where `f_i` is the forecast value and `a_i` is the actual value. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmape = require( '@stdlib/stats/incr/nanmape' ); +``` + +#### incrnanmape() + +Returns an accumulator `function` which incrementally computes the [mean absolute percentage error][mean-absolute-percentage-error], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmape(); +``` + +#### accumulator( \[f, a] ) + +If provided input values `f` and `a`, the accumulator function returns an updated [mean absolute percentage error][mean-absolute-percentage-error]. If not provided input values `f` and `a`, the accumulator function returns the current [mean absolute percentage error][mean-absolute-percentage-error]. + +```javascript +var accumulator = incrnanmape(); + +var m = accumulator( 2.0, 3.0 ); +// returns ~33.33 + +m = accumulator( 1.0, 4.0 ); +// returns ~54.17 + +m = accumulator( NaN, 4.0 ); +// returns ~54.17 + +m = accumulator( 3.0, 5.0 ); +// returns ~49.44 + +m = accumulator( 3.0, NaN ); +// returns ~49.44 + +m = accumulator( NaN, NaN ); +// returns ~49.44 + +m = accumulator(); +// returns ~49.44 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +- **Warning**: the [mean absolute percentage error][mean-absolute-percentage-error] has several shortcomings: + + - The measure is **not** suitable for intermittent demand patterns (i.e., when `a_i` is `0`). + - The [mean absolute percentage error][mean-absolute-percentage-error] is not symmetrical, as the measure cannot exceed 100% for forecasts which are too "low" and has no limit for forecasts which are too "high". + - When used to compare the accuracy of forecast models (e.g., predicting demand), the measure is biased toward forecasts which are too low. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmape = require( '@stdlib/stats/incr/nanmape' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmape(); + +// For each simulated datum, update the mean absolute percentage error... +for ( i = 0; i < 100; i++ ) { + v1 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + v2 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mean-absolute-percentage-error]: https://en.wikipedia.org/wiki/Mean_absolute_percentage_error + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmape/benchmark/benchmark.js new file mode 100644 index 000000000000..a3ab41f86c46 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmape = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmape(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmape(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i + 0.5, i + 0.5 ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/docs/img/equation_mean_absolute_percentage_error.svg b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/img/equation_mean_absolute_percentage_error.svg new file mode 100644 index 000000000000..9367280b2aae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/img/equation_mean_absolute_percentage_error.svg @@ -0,0 +1,87 @@ + +upper M upper A upper P upper E equals StartFraction 100 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts StartAbsoluteValue StartFraction a Subscript i Baseline minus f Subscript i Baseline Over a Subscript i Baseline EndFraction EndAbsoluteValue + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/repl.txt new file mode 100644 index 000000000000..cca9d3c3847f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes the mean + absolute percentage error (MAPE), ignoring `NaN` values. + + If provided input values, the accumulator function returns an updated mean + absolute percentage error. If not provided input values, the accumulator + function returns the current mean absolute percentage error. + + If provided `NaN` for either input value, the value is ignored and the + accumulator function returns the current mean absolute percentage error. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + ~33.33 + > m = accumulator( 5.0, 2.0 ) + ~91.67 + > m = accumulator( 5.0, NaN ) + ~91.67 + > m = accumulator() + ~91.67 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/types/index.d.ts new file mode 100644 index 000000000000..c32eb439f8f8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/types/index.d.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided input values, the accumulator function returns an updated mean absolute percentage error. If not provided input values, the accumulator function returns the current mean absolute percentage error. +* +* ## Notes +* +* - If provided `NaN`, it simply ignores that input. +* +* @param f - input value +* @param a - input value +* @returns mean absolute percentage error or null +*/ +type accumulator = ( f?: number, a?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes the mean absolute percentage error, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanmape(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( NaN, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( 2.0, NaN ); +* // returns ~33.33 +* +* m = accumulator( NaN, NaN ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~91.67 +* +* m = accumulator(); +* // returns ~91.67 +*/ +declare function incrnanmape(): accumulator; + + +// EXPORTS // + +export = incrnanmape; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/types/test.ts new file mode 100644 index 000000000000..4ff3e83c0bff --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/docs/types/test.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmape = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmape(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanmape( '5' ); // $ExpectError + incrnanmape( 5 ); // $ExpectError + incrnanmape( true ); // $ExpectError + incrnanmape( false ); // $ExpectError + incrnanmape( null ); // $ExpectError + incrnanmape( undefined ); // $ExpectError + incrnanmape( [] ); // $ExpectError + incrnanmape( {} ); // $ExpectError + incrnanmape( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmape(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null + acc( NaN, 2.0 ); // $ExpectType number | null + acc( 3.14, NaN ); // $ExpectType number | null + acc( NaN, NaN ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmape(); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmape/examples/index.js new file mode 100644 index 000000000000..63f147c33eae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmape = require( './../lib' ); + +var accumulator; +var err; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmape(); + +// For each simulated datum, update the mean absolute percentage error... +console.log( '\nValue\tValue\tMAPE\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + v2 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + err = accumulator( v1, v2 ); + if ( err !== null ) { + console.log( '%d\t%d\t%d', v1.toFixed( 3 ), v2.toFixed( 3 ), err.toFixed( 3 ) ); + } +} +console.log( '\nFinal MAPE: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmape/lib/index.js new file mode 100644 index 000000000000..a32218f80dd8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the mean absolute percentage error incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmape +* +* @example +* var incrnanmape = require( '@stdlib/stats/incr/nanmape' ); +* +* var accumulator = incrnanmape(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( NaN, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~91.67 +* +* m = accumulator(); +* // returns ~91.67 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmape/lib/main.js new file mode 100644 index 000000000000..0ff359fcf156 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/lib/main.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmape = require( '@stdlib/stats/incr/mape' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes the mean absolute percentage error, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmape(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( NaN, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( 2.0, NaN ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~91.67 +* +* m = accumulator(); +* // returns ~91.67 +*/ +function incrnanmape() { + var acc = incrmape(); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated mean absolute percentage error. If not provided input values, the accumulator function returns the current mean absolute percentage error. + * + * @private + * @param {number} [f] - input value + * @param {number} [a] - input value + * @returns {(number|null)} mean absolute percentage error or null + */ + function accumulator( f, a ) { + if ( arguments.length === 0 || isnan( f ) || isnan( a ) ) { + return acc(); + } + return acc( f, a ); + } +} + + +// EXPORTS // + +module.exports = incrnanmape; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/package.json b/lib/node_modules/@stdlib/stats/incr/nanmape/package.json new file mode 100644 index 000000000000..3fcd1a48acc7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/package.json @@ -0,0 +1,81 @@ +{ + "name": "@stdlib/stats/incr/nanmape", + "version": "0.0.0", + "description": "Compute the mean absolute percentage error (MAPE) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "error", + "err", + "absolute", + "abs", + "percentage", + "percent", + "mape", + "deviation", + "difference", + "diff", + "delta", + "incremental", + "accumulator", + "time series", + "timeseries", + "demand", + "forecasting", + "forecast" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmape/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmape/test/test.js new file mode 100644 index 000000000000..472b899294d7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmape/test/test.js @@ -0,0 +1,155 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmape = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmape, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmape(), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanmape(); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes the mean absolute percentage error', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var sum; + var tol; + var N; + var x; + var y; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, 1.0 ], + [ 2.0, 5.0 ], + [ 4.0, 4.0 ], + [ 3.0, 10.0 ], + [ 4.0, 5.0 ] + ]; + N = data.length; + + acc = incrnanmape(); + + sum = 0; + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + sum += abs( ( y-x ) / y ); + expected = 100.0 * ( sum/(i+1) ); + actual = acc( x, y ); + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value' ); + } else { + delta = abs( expected - actual ); + tol = 1.0 * EPS * abs( expected ); + t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if provided `NaN`, the value is ignored', function test( t ) { + var expected; + var actual; + var delta; + var data; + var tol; + var acc; + var i; + + acc = incrnanmape(); + + data = [ + [ 2.0, 3.0 ], + [ NaN, 3.0 ], + [ 2.0, NaN ], + [ NaN, NaN ], + [ 5.0, 2.0 ] + ]; + + expected = [ + 100.0 * ( 1.0/3.0 ), + 100.0 * ( 1.0/3.0 ), + 100.0 * ( 1.0/3.0 ), + 100.0 * ( 1.0/3.0 ), + 100.0 * ( ( (1.0/3.0) + 1.5 ) / 2.0 ) + ]; + + for ( i = 0; i < data.length; i++ ) { + actual = acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + if ( actual === expected[ i ] ) { + t.strictEqual( actual, expected[ i ], 'returns expected value'); + } else { + delta = abs( actual - expected[ i ] ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected[ i ]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean absolute percentage error', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, 5.0 ], + [ 10.0, 1.0 ] + ]; + acc = incrnanmape(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + actual = acc(); + expected = 100.0 / 3.0 * ((1.0/3.0) + (2.0/5.0) + (9.0/1.0)); + delta = abs( expected - actual ); + tol = 1.0 * EPS * abs( expected ); + t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected+'. Delta: '+delta+'. Tol: '+tol+'.' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/README.md b/lib/node_modules/@stdlib/stats/incr/nanmax/README.md new file mode 100644 index 000000000000..b6fd07ac5841 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/README.md @@ -0,0 +1,129 @@ + + +# incrnanmax + +> Compute a maximum value incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanmax = require( '@stdlib/stats/incr/nanmax' ); +``` + +#### incrnanmax() + +Returns an accumulator `function` which incrementally computes a maximum value, ignoring `NaN` values. + +```javascript +var accumulator = incrnanmax(); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated maximum value. If not provided an input value `x`, the accumulator function returns the current maximum value. + +```javascript +var accumulator = incrnanmax(); + +var max = accumulator( 2.0 ); +// returns 2.0 + +max = accumulator( 1.0 ); +// returns 2.0 + +max = accumulator( NaN ); +// returns 2.0 + +max = accumulator( 3.0 ); +// returns 3.0 + +max = accumulator(); +// returns 3.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmax = require( '@stdlib/stats/incr/nanmax' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmax(); + +// For each simulated datum, update the max... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmax/benchmark/benchmark.js new file mode 100644 index 000000000000..cd8425d3e315 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnanmax = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmax(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmax(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmax/docs/repl.txt new file mode 100644 index 000000000000..def772da7585 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/docs/repl.txt @@ -0,0 +1,33 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes a maximum + value, ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated maximum + value. If not provided a value, the accumulator function returns the current + maximum value. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var m = accumulator() + null + > m = accumulator( 3.14 ) + 3.14 + > m = accumulator( NaN ) + 3.14 + > m = accumulator( -5.0 ) + 3.14 + > m = accumulator( 10.1 ) + 10.1 + > m = accumulator() + 10.1 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmax/docs/types/index.d.ts new file mode 100644 index 000000000000..7b9432f937ff --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated maximum value; otherwise, returns the current maximum value. +* +* @param x - value +* @returns maximum value +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a maximum value, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanmax(); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( -4.0 ); +* // returns 2.0 +* +* v = accumulator( NaN ); +* // returns 2.0 +* +* v = accumulator( 3.0 ); +* // returns 3.0 +* +* v = accumulator(); +* // returns 3.0 +*/ +declare function incrnanmax(): accumulator; + + +// EXPORTS // + +export = incrnanmax; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmax/docs/types/test.ts new file mode 100644 index 000000000000..4ccf952c5ae6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmax = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmax(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanmax( '5' ); // $ExpectError + incrnanmax( 5 ); // $ExpectError + incrnanmax( true ); // $ExpectError + incrnanmax( false ); // $ExpectError + incrnanmax( null ); // $ExpectError + incrnanmax( undefined ); // $ExpectError + incrnanmax( [] ); // $ExpectError + incrnanmax( {} ); // $ExpectError + incrnanmax( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmax(); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmax(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmax/examples/index.js new file mode 100644 index 000000000000..adb2f9ec68f5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmax = require( './../lib' ); + +var accumulator; +var max; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmax(); + +// For each simulated datum, update the max... +console.log( '\nValue\tMax\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + max = accumulator( v ); + console.log( '%s\t%s', ( v === v ) ? v.toFixed( 4 ) : 'NaN', ( max === null ) ? 'null' : max.toFixed( 4 ) ); +} +console.log( '\nFinal max: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmax/lib/index.js new file mode 100644 index 000000000000..1e0021df8f0d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a maximum value incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmax +* +* @example +* var incrnanmax = require( '@stdlib/stats/incr/nanmax' ); +* +* var accumulator = incrnanmax(); +* +* var max = accumulator(); +* // returns null +* +* max = accumulator( 3.14 ); +* // returns 3.14 +* +* max = accumulator( NaN ); +* // returns 3.14 +* +* max = accumulator( -5.0 ); +* // returns 3.14 +* +* max = accumulator( 10.1 ); +* // returns 10.1 +* +* max = accumulator(); +* // returns 10.1 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmax/lib/main.js new file mode 100644 index 000000000000..b1c462a79af1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/lib/main.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmax = require( '@stdlib/stats/incr/max' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a maximum value, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmax(); +* +* var max = accumulator(); +* // returns null +* +* max = accumulator( 3.14 ); +* // returns 3.14 +* +* max = accumulator( NaN ); +* // returns 3.14 +* +* max = accumulator( -5.0 ); +* // returns 3.14 +* +* max = accumulator( 10.1 ); +* // returns 10.1 +* +* max = accumulator(); +* // returns 10.1 +*/ +function incrnanmax() { + var max = incrmax(); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated maximum value. If not provided a value, the accumulator function returns the current max, while ignoring `NaN` values. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} max value or null + */ + function accumulator( x ) { + if ( arguments.length === 0 ) { + return max(); + } + if ( isnan( x ) ) { + return max(); + } + return max( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmax; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/package.json b/lib/node_modules/@stdlib/stats/incr/nanmax/package.json new file mode 100644 index 000000000000..89e854bb779c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/stats/incr/nanmax", + "version": "0.0.0", + "description": "Compute a maximum value incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "range", + "extremes", + "domain", + "extent", + "incremental", + "accumulator", + "nan", + "ignore" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmax/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmax/test/test.js new file mode 100644 index 000000000000..c74c242f4a0e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmax/test/test.js @@ -0,0 +1,131 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var incrnanmax = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmax(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if not provided any values, the initial returned maximum value is `null`', function test( t ) { + var acc = incrnanmax(); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if all provided values are `NaN`, the accumulator function returns `null`', function test( t ) { + var data; + var acc; + var i; + + data = [ NaN, NaN, NaN ]; + acc = incrnanmax(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a maximum value, ignoring NaN values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var d; + var i; + + data = [ 2.0, NaN, 3.0, NaN, 4.0, 3.0, NaN, 4.0 ]; + N = data.length; + + expected = [ 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 4.0, 4.0 ]; + actual = []; + + acc = incrnanmax(); + + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + actual.push( acc( d ) ); + } + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current maximum value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, 3.0, NaN, 1.0 ]; + acc = incrnanmax(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 3.0, 'returns the current accumulated maximum value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var acc; + var v; + + acc = incrnanmax(); + + v = acc( -0.0 ); + t.equal( isNegativeZero( v ), true, 'returns expected value' ); + + v = acc( 0.0 ); + t.equal( isPositiveZero( v ), true, 'returns expected value' ); + + v = acc( -0.0 ); + t.equal( isPositiveZero( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function ignores it and continues computing max value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + acc = incrnanmax(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 7.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/README.md b/lib/node_modules/@stdlib/stats/incr/nanmda/README.md new file mode 100644 index 000000000000..7d8ed35b1c08 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/README.md @@ -0,0 +1,160 @@ + + +# incrnanmda + +> Compute the [mean directional accuracy][mean-directional-accuracy] (MDA) incrementally, ignoring `NaN` values. + +
+ +The [mean directional accuracy][mean-directional-accuracy] is defined as + + + +```math +\mathop{\mathrm{MDA}} = \begin{cases} 1 & \textrm{if}\ N = 1 \\\frac{1}{N} \sum_{i=1}^{N} \delta_{\mathop{\mathrm{sgn}}(\Delta f_{i,i-1}),\ \mathop{\mathrm{sgn}}(\Delta a_{i,i-1})} & \textrm{if}\ N > 1 \end{cases} +``` + + + + + +where `f_i` is the forecast value, `a_i` is the actual value, `sgn(x)` is the [signum][@stdlib/math/base/special/signum] function, and `δ` is the [Kronecker delta][@stdlib/math/base/special/kronecker-delta]. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmda = require( '@stdlib/stats/incr/nanmda' ); +``` + +#### incrnanmda() + +Returns an accumulator `function` which incrementally computes the [mean directional accuracy][mean-directional-accuracy], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmda(); +``` + +#### accumulator( \[f, a] ) + +If provided input values `f` and `a`, the accumulator function returns an updated [mean directional accuracy][mean-directional-accuracy]. If not provided input values `f` and `a`, the accumulator function returns the current [mean directional accuracy][mean-directional-accuracy]. + +```javascript +var accumulator = incrnanmda(); + +var m = accumulator( 2.0, 3.0 ); +// returns 1.0 + +m = accumulator( -1.0, 4.0 ); +// returns 0.5 + +m = accumulator( NaN, 4.0 ); +// returns 0.5 + +m = accumulator( -3.0, -2.0 ); +// returns ~0.67 + +m = accumulator(); +// returns ~0.67 +``` + +
+ + + +
+ +## Notes + +- Input values are type checked. If provided a NaN or a non-numeric value, the update is skipped and the accumulator returns the previously computed mean directional accuracy. If non-numeric inputs are possible, you are advised to type check and handle accordingly before passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmda = require( '@stdlib/stats/incr/nanmda' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmda(); + +// For each simulated datum, update the mean directional accuracy... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v1 = NaN; + } else { + v1 = ( randu()*100.0 ) - 50.0; + } + if ( randu() < 0.2 ) { + v2 = NaN; + } else { + v2 = ( randu()*100.0 ) - 50.0; + } + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mean-directional-accuracy]: https://en.wikipedia.org/wiki/Mean_Directional_Accuracy_%28MDA%29 + +[@stdlib/math/base/special/signum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/signum + +[@stdlib/math/base/special/kronecker-delta]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/kronecker-delta + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmda/benchmark/benchmark.js new file mode 100644 index 000000000000..8e8121b41d90 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmda = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmda(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmda(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()-0.5, randu()-0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/docs/img/equation_mean_directional_accuracy.svg b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/img/equation_mean_directional_accuracy.svg new file mode 100644 index 000000000000..c289bdf791d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/img/equation_mean_directional_accuracy.svg @@ -0,0 +1,115 @@ + +upper M upper D upper A equals StartLayout Enlarged left-brace 1st Row 1st Column 1 2nd Column if upper N equals 1 2nd Row 1st Column StartFraction 1 Over upper N EndFraction sigma-summation Underscript i equals 1 Overscript upper N Endscripts delta Subscript s g n left-parenthesis normal upper Delta f Sub Subscript i comma i minus 1 Subscript right-parenthesis comma s g n left-parenthesis normal upper Delta a Sub Subscript i comma i minus 1 Subscript right-parenthesis Baseline 2nd Column if upper N greater-than 1 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/repl.txt new file mode 100644 index 000000000000..3f54003a0a49 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/repl.txt @@ -0,0 +1,31 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes the mean + directional accuracy (MDA), ignoring `NaN` values. + + If provided input values, the accumulator function returns an updated mean + directional accuracy. If not provided input values, the accumulator function + returns the current mean directional accuracy. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + 1.0 + > m = accumulator( -5.0, 4.0 ) + 0.5 + > m = accumulator( NaN, 4.0 ) + 0.5 + > m = accumulator() + 0.5 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/types/index.d.ts new file mode 100644 index 000000000000..7c75195e84b8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/types/index.d.ts @@ -0,0 +1,60 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated mean directional accuracy. If not provided a value, the accumulator function returns the current mean directional accuracy. +* +* @param f - forecast value +* @param a - actual value +* @returns mean directional accuracy or null +*/ +type accumulator = ( f?: number, a?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes the mean directional accuracy, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanmda(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 4.0 ); +* // returns 0.5 +* +* m = accumulator( NaN, 4.0 ); +* // returns 0.5 +* +* m = accumulator(); +* // returns 0.5 +*/ +declare function incrnanmda(): accumulator; + + +// EXPORTS // + +export = incrnanmda; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/types/test.ts new file mode 100644 index 000000000000..cb6dc8ea3ad7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/docs/types/test.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmda = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmda(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanmda( '5' ); // $ExpectError + incrnanmda( 5 ); // $ExpectError + incrnanmda( true ); // $ExpectError + incrnanmda( false ); // $ExpectError + incrnanmda( null ); // $ExpectError + incrnanmda( undefined ); // $ExpectError + incrnanmda( [] ); // $ExpectError + incrnanmda( {} ); // $ExpectError + incrnanmda( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmda(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmda(); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmda/examples/index.js new file mode 100644 index 000000000000..bdc96cb6078d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/examples/index.js @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmda = require( './../lib' ); + +var accumulator; +var v2; +var v1; +var m; +var i; + +// Initialize an accumulator: +accumulator = incrnanmda(); + +// For each simulated datum, update the mean directional accuracy... +console.log( '\nValue\tValue\tMDA\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.1 ) { + v1 = NaN; + } else { + v1 = ( randu()*100.0 ) - 50.0; + } + if ( randu() < 0.1 ) { + v2 = NaN; + } else { + v2 = ( randu()*100.0 ) - 50.0; + } + m = accumulator( v1, v2 ); + console.log( '%d\t%d\t%s', v1.toFixed( 3 ), v2.toFixed( 3 ), ( m === null ) ? 'null' : m.toFixed( 3 ) ); +} +console.log( '\nFinal MDA: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmda/lib/index.js new file mode 100644 index 000000000000..7f1a00956e23 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the mean directional accuracy (MDA) incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmda +* +* @example +* var incrnanmda = require( '@stdlib/stats/incr/nanmda' ); +* +* var accumulator = incrnanmda(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 4.0 ); +* // returns 0.5 +* +* m = accumulator( NaN, 4.0 ); +* // returns 0.5 +* +* m = accumulator(); +* // returns 0.5 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmda/lib/main.js new file mode 100644 index 000000000000..176d91e89321 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/lib/main.js @@ -0,0 +1,76 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmda = require( '@stdlib/stats/incr/mda' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes the mean directional accuracy, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmda(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 4.0 ); +* // returns 0.5 +* +* m = accumulator( NaN, 4.0 ); +* // returns 0.5 +* +* m = accumulator(); +* // returns 0.5 +*/ +function incrnanmda() { + var mda = incrmda(); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated mean directional accuracy. If not provided a value, the accumulator function returns the current mean directional accuracy. + * + * @private + * @param {number} [f] - forecast value + * @param {number} [a] - actual value + * @returns {(number|null)} mean directional accuracy or null + */ + function accumulator( f, a ) { + if ( arguments.length === 0 || isnan( f ) || isnan( a ) || !isNumber( f ) || !isNumber( a ) ) { + return mda(); + } + return mda( f, a ); + } +} + + +// EXPORTS // + +module.exports = incrnanmda; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/package.json b/lib/node_modules/@stdlib/stats/incr/nanmda/package.json new file mode 100644 index 000000000000..921e11b5c6e7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/stats/incr/nanmda", + "version": "0.0.0", + "description": "Compute the mean directional accuracy (MDA) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "direction", + "directional", + "accuracy", + "trend", + "incremental", + "accumulator", + "time series", + "timeseries", + "demand", + "forecasting", + "forecast", + "economics", + "econ", + "finance" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmda/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmda/test/test.js new file mode 100644 index 000000000000..68ae5f192e57 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmda/test/test.js @@ -0,0 +1,110 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmda = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmda, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmda(), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanmda(); + t.equal( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes the mean directional accuracy', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var N; + var i; + + data = [ + [ 2.0, -3.0 ], // +,+ + [ 3.0, 1.0 ], // +,+ + [ NaN, 1.0 ], // +,+ + [ 2.0, 5.0 ], // -,+ + [ 4.0, -4.0 ], // +,- + [ -3.0, -1.0 ], // -,+ + [ 4.0, 5.0 ] // +,+ + ]; + N = data.length; + + expected = [ + 1.0, + 2.0/2.0, + 2.0/2.0, + 2.0/3.0, + 2.0/4.0, + 2.0/5.0, + 3.0/6.0 + ]; + + acc = incrnanmda(); + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + if ( actual === expected[ i ] ) { + t.equal( actual, expected[ i ], 'returns expected value' ); + } else { + delta = abs( expected[ i ] - actual ); + tol = 1.0 * EPS * abs( expected[ i ] ); + t.equal( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected[ i ]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean directional accuracy', function test( t ) { + var data; + var acc; + var i; + + data = [ + [ 2.0, -3.0 ], // +,+ + [ NaN, -3.0 ], // +,+ + [ -3.0, 5.0 ], // -,+ + [ -1.0, 14.0 ] // +,+ + ]; + acc = incrnanmda(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + t.equal( acc(), 2.0/3.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/README.md b/lib/node_modules/@stdlib/stats/incr/nanme/README.md new file mode 100644 index 000000000000..b389f9f809b1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/README.md @@ -0,0 +1,157 @@ + + +# incrnanme + +> Compute the [mean error][mean-absolute-error] (ME) incrementally, ignoring `NaN` values. + +
+ +The [mean error][mean-absolute-error] is defined as + + + +```math +\mathop{\mathrm{ME}} = \frac{1}{n} \sum_{i=0}^{n-1} (y_i - x_i) +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanme = require( '@stdlib/stats/incr/nanme' ); +``` + +#### incrnanme() + +Returns an accumulator `function` which incrementally computes the [mean error][mean-absolute-error], ignoring `NaN` values. + +```javascript +var accumulator = incrnanme(); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated [mean error][mean-absolute-error]. If not provided input values `x` and `y`, the accumulator function returns the current [mean error][mean-absolute-error]. + +```javascript +var accumulator = incrnanme(); + +var m = accumulator( 2.0, 3.0 ); +// returns 1.0 + +m = accumulator( -5.0, 2.0 ); +// returns 4.0 + +m = accumulator( -3.0, NaN ); +// returns 4.0 + +m = accumulator( NaN, 2.0 ); +// returns 4.0 + +m = accumulator(); +// returns 4.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- Be careful when interpreting the [mean error][mean-absolute-error] as errors can cancel. This stated, that errors can cancel makes the [mean error][mean-absolute-error] suitable for measuring the bias in forecasts. +- **Warning**: the [mean error][mean-absolute-error] is scale-dependent and, thus, the measure should **not** be used to make comparisons between datasets having different scales. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanme = require( '@stdlib/stats/incr/nanme' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanme(); + +// For each simulated datum, update the mean error... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v1 = NaN; + v2 = NaN; + } else { + v1 = ( randu()*100.0 ) - 50.0; + v2 = ( randu()*100.0 ) - 50.0; + } + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mean-absolute-error]: https://en.wikipedia.org/wiki/Mean_absolute_error + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanme/benchmark/benchmark.js new file mode 100644 index 000000000000..f57139866d7e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var incrnanme = require( './../lib' ); +var pkg = require( './../package.json' ).name; + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanme(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanme(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()-0.5, randu()-0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/docs/img/equation_mean_error.svg b/lib/node_modules/@stdlib/stats/incr/nanme/docs/img/equation_mean_error.svg new file mode 100644 index 000000000000..b32b18b9d926 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/docs/img/equation_mean_error.svg @@ -0,0 +1,53 @@ + +upper M upper E equals StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis y Subscript i Baseline minus x Subscript i Baseline right-parenthesis Over n EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanme/docs/repl.txt new file mode 100644 index 000000000000..78fce86e90a9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/docs/repl.txt @@ -0,0 +1,33 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes the mean error + (ME), ignoring NaN values. + + If provided input values, the accumulator function returns an updated mean + error. If not provided input values, the accumulator function returns the + current mean error. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + 1.0 + > m = accumulator( -5.0, 2.0 ) + 4.0 + > m = accumulator( -3.0, NaN ) + 4.0 + > m = accumulator( NaN, 2.0 ) + 4.0 + > m = accumulator() + 4.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanme/docs/types/index.d.ts new file mode 100644 index 000000000000..831e6d554998 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided input values, the accumulator function returns an updated mean error. If not provided input values, the accumulator function returns the current mean error. +* +* @param x - input value +* @param y - input value +* @returns mean error or null +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes the mean error, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanme(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator( -3.0, NaN ); +* // returns 4.0 +* +* m = accumulator( NaN, 2.0 ); +* // returns 4.0 +* +* m = accumulator(); +* // returns 4.0 +*/ +declare function incrnanme(): accumulator; + + +// EXPORTS // + +export = incrnanme; diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanme/docs/types/test.ts new file mode 100644 index 000000000000..e86ea21789f1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/docs/types/test.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanme = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanme(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanme( '5' ); // $ExpectError + incrnanme( 5 ); // $ExpectError + incrnanme( true ); // $ExpectError + incrnanme( false ); // $ExpectError + incrnanme( null ); // $ExpectError + incrnanme( undefined ); // $ExpectError + incrnanme( [] ); // $ExpectError + incrnanme( {} ); // $ExpectError + incrnanme( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanme(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanme(); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanme/examples/index.js new file mode 100644 index 000000000000..1f93f32ac7a3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/examples/index.js @@ -0,0 +1,46 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanme = require( './../lib' ); + +var accumulator; +var err; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanme(); + +// For each simulated datum, update the mean error... +console.log( '\nValue\tValue\tMean\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v1 = NaN; + v2 = NaN; + } else { + v1 = ( randu()*100.0 ) - 50.0; + v2 = ( randu()*100.0 ) - 50.0; + } + err = accumulator( v1, v2 ); + console.log( '%s\t%s\t%s', v1.toFixed( 3 ), v2.toFixed( 3 ), ( err === null ) ? NaN : err.toFixed( 3 ) ); +} +console.log( '\nFinal ME: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanme/lib/index.js new file mode 100644 index 000000000000..9c00ea73861b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the mean error incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanme +* +* @example +* var incrnanme = require( '@stdlib/stats/incr/nanme' ); +* +* var accumulator = incrnanme(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator( -3.0, NaN ); +* // returns 4.0 +* +* m = accumulator( NaN, 2.0 ); +* // returns 4.0 +* +* m = accumulator(); +* // returns 4.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanme/lib/main.js new file mode 100644 index 000000000000..d3d0d7e00f45 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/lib/main.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrme = require( '@stdlib/stats/incr/me' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes the mean error, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanme(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator( -3.0, NaN ); +* // returns 4.0 +* +* m = accumulator( NaN, 2.0 ); +* // returns 4.0 +* +* m = accumulator(); +* // returns 4.0 +*/ +function incrnanme() { + var me = incrme(); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated mean error. If not provided input values, the accumulator function returns the current mean error. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} mean error or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return me(); + } + return me( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanme; diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/package.json b/lib/node_modules/@stdlib/stats/incr/nanme/package.json new file mode 100644 index 000000000000..d4f78b2f85b7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/package.json @@ -0,0 +1,79 @@ +{ + "name": "@stdlib/stats/incr/nanme", + "version": "0.0.0", + "description": "Compute the mean error (ME) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "error", + "err", + "nan", + "me", + "msd", + "signed", + "deviation", + "difference", + "diff", + "delta", + "incremental", + "accumulator", + "time series", + "timeseries", + "forecasting", + "forecast" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanme/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanme/test/test.js new file mode 100644 index 000000000000..2cab0268bbf4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanme/test/test.js @@ -0,0 +1,133 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanme = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanme, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanme(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanme(); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes the mean error', function test( t ) { + var expected; + var actual; + var delta; + var count; + var data; + var acc; + var sum; + var tol; + var N; + var x; + var y; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, -1.0 ], + [ 2.0, 5.0 ], + [ NaN, -4.0 ], + [ NaN, NaN ], + [ 3.0, 0.0 ], + [ -4.0, NaN ] + ]; + N = data.length; + + acc = incrnanme(); + + sum = 0; + count = 0; + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( isnan( x ) === false && isnan( y ) === false ) { + sum += ( y-x ); + count += 1; + } + expected = ( count > 0 ) ? sum / count : null; + actual = acc( x, y ); + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value' ); + } else { + delta = abs( expected - actual ); + tol = 6.0 * EPS * abs( expected ); + t.equal( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean error', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 4.0, NaN ], + [ 3.0, -5.0 ], + [ NaN, -3.0 ], + [ 1.0, 10.0 ] + ]; + acc = incrnanme(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + actual = acc(); + expected = 2.0 / 3.0; + delta = abs( expected - actual ); + tol = 3.0 * EPS * abs( expected ); + t.equal( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected+'. Delta: '+delta+'. Tol: '+tol+'.' ); + t.end(); +}); + +tape( 'if only NaN values have been provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanme(); + t.strictEqual( acc( NaN, NaN ), null, 'returns expected value' ); + t.strictEqual( acc( NaN, 3.0 ), null, 'returns expected value' ); + t.strictEqual( acc( 2.0, NaN ), null, 'returns expected value' ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/README.md b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/README.md new file mode 100644 index 000000000000..1ed5ceab22f6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/README.md @@ -0,0 +1,218 @@ + + +# incrnanmeanstdev + +> Compute an [arithmetic mean][arithmetic-mean] and a [corrected sample standard deviation][sample-stdev] incrementally, ignoring `NaN` values. + +
+ +The [arithmetic mean][arithmetic-mean] is defined as + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +and the [corrected sample standard deviation][sample-stdev] is defined as + + + +```math +s = \sqrt{\frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmeanstdev = require( '@stdlib/stats/incr/nanmeanstdev' ); +``` + +#### incrnanmeanstdev( \[out] ) + +Returns an accumulator `function` which incrementally computes an [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][sample-stdev], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmeanstdev(); +``` + +By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var accumulator = incrnanmeanstdev( new Float64Array( 2 ) ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values. + +```javascript +var accumulator = incrnanmeanstdev(); + +var ms = accumulator(); +// returns null + +ms = accumulator( NaN ); +// returns null + +ms = accumulator( 2.0 ); +// returns [ 2.0, 0.0 ] + +ms = accumulator( 1.0 ); +// returns [ 1.5, ~0.71 ] + +ms = accumulator( 3.0 ); +// returns [ 2.0, 1.0 ] + +ms = accumulator( -7.0 ); +// returns [ -0.25, ~4.57 ] + +ms = accumulator( -5.0 ); +// returns [ -1.2, ~4.49 ] + +ms = accumulator(); +// returns [ -1.2, ~4.49 ] +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmeanstdev = require( '@stdlib/stats/incr/nanmeanstdev' ); + +var offset; +var acc; +var buf; +var out; +var ms; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmeanstdev( out ) ); +} + +// Simulate data and update the sample means and standard deviations... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + if ( randu() < 0.1 ) { + v = NaN; + } else { + v = randu() * 100.0 * (j+1); + } + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tStDev' ); +for ( i = 0; i < N; i++ ) { + ms = acc[ i ](); + console.log( '%d\t%d', ms[ 0 ].toFixed( 3 ), ms[ 1 ].toFixed( 3 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean + +[sample-stdev]: https://en.wikipedia.org/wiki/Standard_deviation + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/benchmark/benchmark.js new file mode 100644 index 000000000000..2f03624d69f2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmeanstdev = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmeanstdev(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmeanstdev(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v.length !== 2 ) { + b.fail( 'should contain two elements' ); + } + } + b.toc(); + if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/img/equation_arithmetic_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/img/equation_arithmetic_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/img/equation_corrected_sample_standard_deviation.svg b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/img/equation_corrected_sample_standard_deviation.svg new file mode 100644 index 000000000000..6af85c9d5732 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/img/equation_corrected_sample_standard_deviation.svg @@ -0,0 +1,73 @@ + +s equals StartRoot StartFraction 1 Over n minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/repl.txt new file mode 100644 index 000000000000..30e1e690ca6a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/repl.txt @@ -0,0 +1,36 @@ + +{{alias}}( [out] ) + Returns an accumulator function which incrementally computes an arithmetic + mean and corrected sample standard deviation, ignoring `NaN` values. + + If provided a value, the accumulator function returns updated accumulated + values. If not provided a value, the accumulator function returns the + current accumulated values. + + If provided `NaN`, the update is skipped and the accumulator continues to + return the previous accumulated values. + + Parameters + ---------- + out: Array|TypedArray (optional) + Output array. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var ms = accumulator() + null + > accumulator( 2.0 ); + > accumulator( NaN ); + > accumulator( -5.0 ); + > ms = accumulator() + [ -1.5, ~4.95 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/types/index.d.ts new file mode 100644 index 000000000000..e3ae29b4aef5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/types/index.d.ts @@ -0,0 +1,70 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; + +/** +* If provided a value, the accumulator function returns updated results. If not provided a value, the accumulator function returns the current results. +* +* ## Notes +* +* @param x - input value +* @returns output array or null +*/ +type accumulator = ( x?: number ) => ArrayLike | null; + +/** +* Returns an accumulator function which incrementally computes an arithmetic mean and corrected sample standard deviation, ignoring `NaN` values. +* +* @param out - output array +* @returns accumulator function +* +* @example +* var accumulator = incrnanmeanstdev(); +* +* var ms = accumulator(); +* // returns null +* +* ms = accumulator( NaN ); +* // returns null +* +* ms = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* ms = accumulator( -5.0 ); +* // returns [ -1.5, ~4.95 ] +* +* ms = accumulator( 3.0 ); +* // returns [ 0.0, ~4.36 ] +* +* ms = accumulator( 5.0 ); +* // returns [ 1.25, ~4.35 ] +* +* ms = accumulator(); +* // returns [ 1.25, ~4.35 ] +*/ +declare function incrnanmeanstdev( out?: ArrayLike ): accumulator; + + +// EXPORTS // + +export = incrnanmeanstdev; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/types/test.ts new file mode 100644 index 000000000000..4598dac8e37f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmeanstdev = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmeanstdev(); // $ExpectType accumulator + const out = [ 0.0, 0.0 ]; + incrnanmeanstdev( out ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not an array-like object of numbers... +{ + incrnanmeanstdev( '5' ); // $ExpectError + incrnanmeanstdev( 5 ); // $ExpectError + incrnanmeanstdev( true ); // $ExpectError + incrnanmeanstdev( false ); // $ExpectError + incrnanmeanstdev( null ); // $ExpectError + incrnanmeanstdev( {} ); // $ExpectError + incrnanmeanstdev( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmeanstdev(); + + acc(); // $ExpectType ArrayLike | null + acc( 3.14 ); // $ExpectType ArrayLike | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmeanstdev(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/examples/index.js new file mode 100644 index 000000000000..a2af2326a3de --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/examples/index.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmeanstdev = require( './../lib' ); + +var offset; +var acc; +var buf; +var out; +var ms; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmeanstdev( out ) ); +} + +// Simulate data and update the sample means and standard deviations... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + if ( randu() < 0.1 ) { + v = NaN; + } else { + v = randu() * 100.0 * (j+1); + } + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tStDev' ); +for ( i = 0; i < N; i++ ) { + ms = acc[ i ](); + console.log( '%d\t%d', ms[ 0 ].toFixed( 3 ), ms[ 1 ].toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/lib/index.js new file mode 100644 index 000000000000..693b2dbbcb63 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute an arithmetic mean and corrected sample standard deviation incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmeanstdev +* +* @example +* var incrnanmeanstdev = require( '@stdlib/stats/incr/nanmeanstdev' ); +* +* var accumulator = incrnanmeanstdev(); +* +* var ms = accumulator(); +* // returns null +* +* ms = accumulator( NaN ); +* // returns null +* +* ms = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* ms = accumulator( -5.0 ); +* // returns [ -1.5, ~4.95 ] +* +* ms = accumulator( 3.0 ); +* // returns [ 0.0, ~4.36 ] +* +* ms = accumulator( 5.0 ); +* // returns [ 1.25, ~4.35 ] +* +* ms = accumulator(); +* // returns [ 1.25, ~4.35 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/lib/main.js new file mode 100644 index 000000000000..d540cf26ca2d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/lib/main.js @@ -0,0 +1,87 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmeanstdev = require( '@stdlib/stats/incr/meanstdev' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes an arithmetic mean and corrected sample standard deviation, ignoring `NaN` values. +* +* @param {Collection} [out] - output array +* @throws {TypeError} output argument must be array-like +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmeanstdev(); +* +* var ms = accumulator(); +* // returns null +* +* ms = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* ms = accumulator( NaN ); +* // returns [ 2.0, 0.0 ] +* +* ms = accumulator( -5.0 ); +* // returns [ -1.5, ~4.95 ] +* +* ms = accumulator( 3.0 ); +* // returns [ 0.0, ~4.36 ] +* +* ms = accumulator( 5.0 ); +* // returns [ 1.25, ~4.35 ] +* +* ms = accumulator(); +* // returns [ 1.25, ~4.35 ] +*/ +function incrnanmeanstdev( out ) { + var meanstdev; + if ( arguments.length > 0 ) { + meanstdev = incrmeanstdev( out ); + } else { + meanstdev = incrmeanstdev(); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns updated accumulated values. If not provided a value, the accumulator function returns the current accumulated values. + * + * @private + * @param {number} [x] - input value + * @returns {(ArrayLikeObject|null)} output array or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return meanstdev(); + } + return meanstdev( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmeanstdev; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/package.json b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/package.json new file mode 100644 index 000000000000..0e31ec9c21ba --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nanmeanstdev", + "version": "0.0.0", + "description": "Compute an arithmetic mean and corrected sample standard deviation incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "variance", + "sample variance", + "unbiased", + "var", + "dispersion", + "standard deviation", + "stdev", + "central tendency", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/test/test.js new file mode 100644 index 000000000000..790bf9987435 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanstdev/test/test.js @@ -0,0 +1,185 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var incrnanmeanstdev = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmeanstdev, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + NaN, + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmeanstdev( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmeanstdev(), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (output)', function test( t ) { + t.strictEqual( typeof incrnanmeanstdev( [ 0.0, 0.0 ] ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes an arithmetic mean and corrected sample standard deviation', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 2.0, NaN, 4.0, NaN, 3.0, 4.0 ]; + N = data.length; + + // Test against Julia: + expected = [ + [ 2.0, 0.0 ], + [ 2.5, sqrt( 0.5 ) ], + [ 7.0/3.0, sqrt( 0.33333333333333337 ) ], + [ 7.0/3.0, sqrt( 0.33333333333333337 ) ], + [ 11.0/4.0, sqrt( 0.9166666666666666 ) ], + [ 11.0/4.0, sqrt( 0.9166666666666666 ) ], + [ 14.0/5.0, sqrt( 0.7 ) ], + [ 18.0/6.0, sqrt( 0.8 ) ] + ]; + + acc = incrnanmeanstdev(); + + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the accumulator function incrementally computes an arithmetic mean and corrected sample standard deviation (output)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var out; + var N; + var i; + + data = [ 2.0, 3.0, 2.0, NaN, 4.0, NaN, 3.0, 4.0 ]; + N = data.length; + + // Test against Julia: + expected = [ + [ 2.0, 0.0 ], + [ 2.5, sqrt( 0.5 ) ], + [ 7.0/3.0, sqrt( 0.33333333333333337 ) ], + [ 7.0/3.0, sqrt( 0.33333333333333337 ) ], + [ 11.0/4.0, sqrt( 0.9166666666666666 ) ], + [ 11.0/4.0, sqrt( 0.9166666666666666 ) ], + [ 14.0/5.0, sqrt( 0.7 ) ], + [ 18.0/6.0, sqrt( 0.8 ) ] + ]; + out = [ 0.0, 0.0 ]; + acc = incrnanmeanstdev( out ); + + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.strictEqual( actual, out, 'returns output array' ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean and corrected sample standard deviation', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 3.0, NaN, 1.0 ]; + acc = incrnanmeanstdev(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.deepEqual( acc(), [ 2.0, 1.0 ], 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmeanstdev(); + t.strictEqual( acc(), null, 'returns null' ); + t.strictEqual( acc(), null, 'returns null' ); + t.strictEqual( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the sample standard deviation is `0` until at least 2 datums have been provided', function test( t ) { + var acc; + var ms; + + acc = incrnanmeanstdev(); + + ms = acc(); + t.strictEqual( ms, null, 'returns null' ); + + ms = acc( 3.0 ); + t.strictEqual( ms[ 1 ], 0.0, 'returns expected value' ); + + ms = acc(); + t.strictEqual( ms[ 1 ], 0.0, 'returns expected value' ); + + ms = acc( 5.0 ); + t.notEqual( ms[ 1 ], 0.0, 'does not return 0' ); + + ms = acc(); + t.notEqual( ms[ 1 ], 0.0, 'does not return 0' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/README.md b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/README.md new file mode 100644 index 000000000000..66c1ec851e1a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/README.md @@ -0,0 +1,214 @@ + + +# incrnanmeanvar + +> Compute an [arithmetic mean][arithmetic-mean] and an [unbiased sample variance][sample-variance] incrementally, ignoring `NaN` values. + +
+ +The [arithmetic mean][arithmetic-mean] is defined as + + + +```math +\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i +``` + + + + + +and the [unbiased sample variance][sample-variance] is defined as + + + +```math +s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2 +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' ); +``` + +#### incrnanmeanvar( \[out] ) + +Returns an accumulator `function` which incrementally computes an [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmeanvar(); +``` + +By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var accumulator = incrnanmeanvar( new Float64Array( 2 ) ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values. + +```javascript +var accumulator = incrnanmeanvar(); + +var mv = accumulator(); +// returns null + +mv = accumulator( 2.0 ); +// returns [ 2.0, 0.0 ] + +mv = accumulator( 1.0 ); +// returns [ 1.5, 0.5 ] + +mv = accumulator( 3.0 ); +// returns [ 2.0, 1.0 ] + +mv = accumulator( NaN ); +// returns [ 2.0, 1.0 ] + +mv = accumulator( -7.0 ); +// returns [ -0.25, ~20.92 ] + +mv = accumulator( -5.0 ); +// returns [ -1.2, 20.2 ] + +mv = accumulator(); +// returns [ -1.2, 20.2 ] +``` + +
+ + + +
+ +## Notes + +- Input values are type checked; if a NaN value is provided, the accumulator skips the update and continues to return the previous state. If non-numeric inputs are possible, you are advised to type check and handle them accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' ); + +var offset; +var acc; +var buf; +var out; +var mv; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmeanvar( out ) ); +} + +// Simulate data and update the sample means and variances... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0 * (j+1); + } + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tVariance' ); +for ( i = 0; i < N; i++ ) { + mv = acc[ i ](); + console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean + +[sample-variance]: https://en.wikipedia.org/wiki/Variance + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/benchmark/benchmark.js new file mode 100644 index 000000000000..fb58216a6107 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmeanvar = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmeanvar(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmeanvar(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v.length !== 2 ) { + b.fail( 'should contain two elements' ); + } + } + b.toc(); + if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_arithmetic_mean.svg new file mode 100644 index 000000000000..aea7a5f6687a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_arithmetic_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_unbiased_sample_variance.svg b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_unbiased_sample_variance.svg new file mode 100644 index 000000000000..1ae1283e7fb1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/img/equation_unbiased_sample_variance.svg @@ -0,0 +1,61 @@ + +s squared equals StartFraction 1 Over n minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/repl.txt new file mode 100644 index 000000000000..1862fbb8518d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( [out] ) + Returns an accumulator function which incrementally computes an arithmetic + mean and unbiased sample variance, ignoring `NaN` values. + + If provided a value, the accumulator function returns updated accumulated + values. If not provided a value, the accumulator function returns the + current accumulated values. + + If provided `NaN`, the update is skipped and the accumulator continues to + return the previous accumulated values. + + Parameters + ---------- + out: Array|TypedArray (optional) + Output array. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var mv = accumulator() + null + > mv = accumulator( 2.0 ) + [ 2.0, 0.0 ] + > mv = accumulator( -5.0 ) + [ -1.5, 24.5 ] + > mv = accumulator( 3.0 ) + [ 0.0, 19.0 ] + > mv = accumulator( NaN ) + [ 0.0, 19.0 ] + > mv = accumulator( 5.0 ) + [ 1.25, ~18.92 ] + > mv = accumulator() + [ 1.25, ~18.92 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/index.d.ts new file mode 100644 index 000000000000..541dd125700c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/index.d.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; + +/** +* If provided a value, the accumulator function returns updated results. If not provided a value, the accumulator function returns the current results. +* +* ## Notes +* +* - If provided `NaN`, the value is ignored and the accumulator function returns the current accumulated values. +* +* @param x - input value +* @returns output array or null +*/ +type accumulator = ( x?: number ) => ArrayLike | null; + +/** +* Returns an accumulator function which incrementally computes an arithmetic mean and unbiased sample variance, ignoring `NaN` values. +* +* @param out - output array +* @returns accumulator function +* +* @example +* var accumulator = incrnanmeanvar(); +* +* var mv = accumulator(); +* // returns null +* +* mv = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* mv = accumulator( -5.0 ); +* // returns [ -1.5, 24.5 ] +* +* mv = accumulator( 3.0 ); +* // returns [ 0.0, 19.0 ] +* +* mv = accumulator( NaN ); +* // returns [ 0.0, 19.0 ] +* +* mv = accumulator( 5.0 ); +* // returns [ 1.25, ~18.92 ] +* +* mv = accumulator(); +* // returns [ 1.25, ~18.92 ] +*/ +declare function incrnanmeanvar( out?: ArrayLike ): accumulator; + + +// EXPORTS // + +export = incrnanmeanvar; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/test.ts new file mode 100644 index 000000000000..4b6565bbc5da --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmeanvar = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmeanvar(); // $ExpectType accumulator + const out = [ 0.0, 0.0 ]; + incrnanmeanvar( out ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not an array-like object of numbers... +{ + incrnanmeanvar( '5' ); // $ExpectError + incrnanmeanvar( 5 ); // $ExpectError + incrnanmeanvar( true ); // $ExpectError + incrnanmeanvar( false ); // $ExpectError + incrnanmeanvar( null ); // $ExpectError + incrnanmeanvar( {} ); // $ExpectError + incrnanmeanvar( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmeanvar(); + + acc(); // $ExpectType ArrayLike | null + acc( 3.14 ); // $ExpectType ArrayLike | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmeanvar(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/examples/index.js new file mode 100644 index 000000000000..99ec426463e2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/examples/index.js @@ -0,0 +1,72 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmeanvar = require( './../lib' ); + +var offset; +var acc; +var buf; +var out; +var mv; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmeanvar( out ) ); +} + +// Simulate data and update the sample means and variances... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0 * (j+1); + } + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tVariance' ); +for ( i = 0; i < N; i++ ) { + mv = acc[ i ](); + console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/index.js new file mode 100644 index 000000000000..6c8b4e3d3f81 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute an arithmetic mean and unbiased sample variance incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmeanvar +* +* @example +* var incrnanmeanvar = require( '@stdlib/stats/incr/nanmeanvar' ); +* +* var accumulator = incrnanmeanvar(); +* +* var mv = accumulator(); +* // returns null +* +* mv = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* mv = accumulator( -5.0 ); +* // returns [ -1.5, 24.5 ] +* +* mv = accumulator( 3.0 ); +* // returns [ 0.0, 19.0 ] +* +* mv = accumulator( NaN ); +* // returns [ 0.0, 19.0 ] +* +* mv = accumulator( 5.0 ); +* // returns [ 1.25, ~18.92 ] +* +* mv = accumulator(); +* // returns [ 1.25, ~18.92 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/main.js new file mode 100644 index 000000000000..6e566e6a3d09 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/lib/main.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var incrmeanvar = require( '@stdlib/stats/incr/meanvar' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes an arithmetic mean and unbiased sample variance, ignoring `NaN` values. +* +* ## References +* +* - Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022). +* - van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961). +* +* @param {Collection} [out] - output array +* @throws {TypeError} output argument must be array-like +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmeanvar(); +* +* var mv = accumulator(); +* // returns null +* +* mv = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* mv = accumulator( -5.0 ); +* // returns [ -1.5, 24.5 ] +* +* mv = accumulator( 3.0 ); +* // returns [ 0.0, 19.0 ] +* +* mv = accumulator( NaN ); +* // returns [ 0.0, 19.0 ] +* +* mv = accumulator( 5.0 ); +* // returns [ 1.25, ~18.92 ] +* +* mv = accumulator(); +* // returns [ 1.25, ~18.92 ] +*/ +function incrnanmeanvar( out ) { + var meanvar; + if ( arguments.length > 0 ) { + meanvar = incrmeanvar( out ); + } else { + meanvar = incrmeanvar(); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns updated results. If not provided a value, the accumulator function returns the current results. + * + * @private + * @param {number} [x] - input value + * @returns {(ArrayLikeObject|null)} output array or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) || !isNumber( x ) ) { + return meanvar(); + } + return meanvar( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmeanvar; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/package.json b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/package.json new file mode 100644 index 000000000000..5bed2d9904f1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nanmeanvar", + "version": "0.0.0", + "description": "Compute an arithmetic mean and unbiased sample variance incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "variance", + "sample variance", + "unbiased", + "var", + "dispersion", + "standard deviation", + "stdev", + "central tendency", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmeanvar/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/test/test.js new file mode 100644 index 000000000000..5f2a526e7bf9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmeanvar/test/test.js @@ -0,0 +1,203 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var incrnanmeanvar = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmeanvar, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + NaN, + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmeanvar( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmeanvar(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (output)', function test( t ) { + t.equal( typeof incrnanmeanvar( [ 0.0, 0.0 ] ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes an arithmetic mean and unbiased sample variance', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, 4.0 ]; + N = data.length; + + // Test against Julia: + expected = [ + [ 2.0, 0.0 ], + [ 2.0, 0.0 ], + [ 2.5, 0.5 ], + [ 7.0/3.0, 0.33333333333333337 ], + [ 7.0/3.0, 0.33333333333333337 ], + [ 11.0/4.0, 0.9166666666666666 ], + [ 14.0/5.0, 0.7 ], + [ 18.0/6.0, 0.8 ] + ]; + + acc = incrnanmeanvar(); + + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the accumulator function incrementally computes an arithmetic mean and unbiased sample variance (output)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var out; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, 4.0 ]; + N = data.length; + + // Test against Julia: + expected = [ + [ 2.0, 0.0 ], + [ 2.0, 0.0 ], + [ 2.5, 0.5 ], + [ 7.0/3.0, 0.33333333333333337 ], + [ 7.0/3.0, 0.33333333333333337 ], + [ 11.0/4.0, 0.9166666666666666 ], + [ 14.0/5.0, 0.7 ], + [ 18.0/6.0, 0.8 ] + ]; + out = [ 0.0, 0.0 ]; + acc = incrnanmeanvar( out ); + + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.equal( actual, out, 'returns output array' ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean and unbiased sample variance', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, 3.0, NaN, 1.0 ]; + acc = incrnanmeanvar(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.deepEqual( acc(), [ 2.0, 1.0 ], 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmeanvar(); + t.equal( acc(), null, 'returns null' ); + t.equal( acc(), null, 'returns null' ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the sample variance is `0` until at least 2 datums have been provided', function test( t ) { + var acc; + var mv; + + acc = incrnanmeanvar(); + + mv = acc(); + t.equal( mv, null, 'returns null' ); + + mv = acc( 3.0 ); + t.equal( mv[ 1 ], 0.0, 'returns expected value' ); + + mv = acc(); + t.equal( mv[ 1 ], 0.0, 'returns expected value' ); + + mv = acc( 5.0 ); + t.notEqual( mv[ 1 ], 0.0, 'does not return 0' ); + + mv = acc(); + t.notEqual( mv[ 1 ], 0.0, 'does not return 0' ); + + t.end(); +}); + +tape( 'if the first value is NaN, the accumulator returns its initial state', function test( t ) { + var state; + var acc; + + acc = incrnanmeanvar(); + + // First update is NaN, so no valid update occurs: + state = acc( NaN ); + t.equal( state, null, 'returns null for initial state when first input is NaN' ); + + // Subsequent call without an update should still return null: + state = acc(); + t.equal( state, null, 'remains at initial state (null) when no valid update is provided' ); + + // Now provide a valid update to see the state change: + state = acc( 2.0 ); + t.deepEqual( state, [ 2.0, 0.0 ], 'updates state correctly after a valid input following an initial NaN' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/README.md b/lib/node_modules/@stdlib/stats/incr/nanmgmean/README.md new file mode 100644 index 000000000000..d2cf0fb5082e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/README.md @@ -0,0 +1,160 @@ + + +# incrnanmgmean + +> Compute a moving [geometric mean][geometric-mean] incrementally, ignoring `NaN` values. + +
+ +The [geometric mean][geometric-mean] is defined as the nth root of a product of _n_ numbers. + + + +```math +\biggl( \prod_{i=0}^{n-1} \biggr)^{\frac{1}{n}} = \sqrt[n]{x_0 x_1 \cdots x_{n-1}} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmgmean = require( '@stdlib/stats/incr/nanmgmean' ); +``` + +#### incrnanmgmean( window ) + +Returns an accumulator `function` which incrementally computes a moving [geometric mean][geometric-mean]. The `window` parameter defines the number of values over which to compute the moving [geometric mean][geometric-mean]. + +```javascript +var accumulator = incrnanmgmean( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated [geometric mean][geometric-mean]. If not provided an input value `x`, the accumulator function returns the current [geometric mean][geometric-mean]. + +```javascript +var accumulator = incrnanmgmean( 3 ); + +var v = accumulator(); +// returns null + +// Fill the window... +v = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +v = accumulator( 1.0 ); // [2.0, 1.0] +// returns ~1.41 + +v = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns ~1.82 + +v = accumulator( NaN ); // [2.0, 1.0, 3.0] +// returns ~1.82 + +// Window begins sliding... +v = accumulator( 7.0 ); // [1.0, 3.0, 7.0] +// returns ~2.76 + +v = accumulator( 5.0 ); // [3.0, 7.0, 5.0] +// returns ~4.72 + +v = accumulator(); +// returns ~4.72 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If a NaN value is provided, the accumulator skips the update and continues to return the previous state. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmgmean = require( '@stdlib/stats/incr/nanmgmean' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmgmean( 5 ); + +// For each simulated datum, update the moving geometric mean... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[geometric-mean]: https://en.wikipedia.org/wiki/Geometric_mean + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmgmean/benchmark/benchmark.js new file mode 100644 index 000000000000..c82d4bae372b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmgmean = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmgmean( ( i%5 )+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmgmean( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/img/equation_geometric_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/img/equation_geometric_mean.svg new file mode 100644 index 000000000000..09660f01bb97 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/img/equation_geometric_mean.svg @@ -0,0 +1,68 @@ + +left-parenthesis product Underscript i equals 0 Overscript n minus 1 Endscripts right-parenthesis Superscript StartFraction 1 Over n EndFraction Baseline equals RootIndex n StartRoot x 0 x 1 midline-horizontal-ellipsis x Subscript n minus 1 Baseline EndRoot + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/repl.txt new file mode 100644 index 000000000000..0af26f0e67d7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + geometric mean, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving geometric mean. + + If provided a value, the accumulator function returns an updated moving + geometric mean. If not provided a value, the accumulator function returns + the current moving geometric mean. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var v = accumulator() + null + > v = accumulator( 2.0 ) + 2.0 + > v = accumulator( 5.0 ) + ~3.16 + > v = accumulator( 3.0 ) + ~3.11 + > v = accumulator( NaN ) + ~3.11 + > v = accumulator( 5.0 ) + ~4.22 + > v = accumulator() + ~4.22 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/types/index.d.ts new file mode 100644 index 000000000000..e6f431263b86 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/types/index.d.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated geometric mean; otherwise, returns the current geometric mean. +* +* @param x - value +* @returns geometric mean +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving geometric mean, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving geometric mean. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmgmean( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( 5.0 ); +* // returns ~3.16 +* +* v = accumulator( 3.0 ); +* // returns ~3.11 +* +* v = accumulator( NaN ); +* // returns ~3.11 +* +* v = accumulator( 5.0 ); +* // returns ~4.22 +* +* v = accumulator(); +* // returns ~4.22 +*/ +declare function incrnanmgmean( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmgmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/types/test.ts new file mode 100644 index 000000000000..73ab0a9ddd0b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmgmean = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmgmean( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmgmean( '5' ); // $ExpectError + incrnanmgmean( true ); // $ExpectError + incrnanmgmean( false ); // $ExpectError + incrnanmgmean( null ); // $ExpectError + incrnanmgmean( undefined ); // $ExpectError + incrnanmgmean( [] ); // $ExpectError + incrnanmgmean( {} ); // $ExpectError + incrnanmgmean( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmgmean(); // $ExpectError + incrnanmgmean( 5, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmgmean( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmgmean( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmgmean/examples/index.js new file mode 100644 index 000000000000..0c4da638571c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmgmean = require( './../lib' ); + +var accumulator; +var m; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmgmean( 5 ); + +// For each simulated datum, update the moving geometric mean... +console.log( '\nValue\tGeometric Mean\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.1 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + m = accumulator( v ); + console.log( '%d\t%d', v.toFixed( 4 ), ( m === null ) ? NaN : m.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmgmean/lib/index.js new file mode 100644 index 000000000000..839b390602d8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving geometric mean incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmgmean +* +* @example +* var incrnanmgmean = require( '@stdlib/stats/incr/nanmgmean' ); +* +* var accumulator = incrnanmgmean( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( 5.0 ); +* // returns ~3.16 +* +* v = accumulator( 3.0 ); +* // returns ~3.11 +* +* v = accumulator( NaN ); +* // returns ~3.11 +* +* v = accumulator( 5.0 ); +* // returns ~4.22 +* +* v = accumulator(); +* // returns ~4.22 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmgmean/lib/main.js new file mode 100644 index 000000000000..0dde34a96c07 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/lib/main.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmgmean = require( '@stdlib/stats/incr/mgmean' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving geometric mean, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmgmean( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( 5.0 ); +* // returns ~3.16 +* +* v = accumulator( 3.0 ); +* // returns ~3.11 +* +* v = accumulator( NaN ); +* // returns ~3.11 +* +* v = accumulator( 5.0 ); +* // returns ~4.22 +* +* v = accumulator(); +* // returns ~4.22 +*/ +function incrnanmgmean( W ) { + var acc = incrmgmean( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated geometric mean. If not provided a value, the accumulator function returns the current geometric mean. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} geometric mean or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return acc(); + } + return acc( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmgmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/package.json b/lib/node_modules/@stdlib/stats/incr/nanmgmean/package.json new file mode 100644 index 000000000000..fcda85da227c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/package.json @@ -0,0 +1,75 @@ +{ + "name": "@stdlib/stats/incr/nanmgmean", + "version": "0.0.0", + "description": "Compute a moving geometric mean incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "geometric", + "mean", + "geometric mean", + "product", + "prod", + "central tendency", + "incremental", + "accumulator", + "moving mean", + "moving average", + "sliding window", + "sliding", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmgmean/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmgmean/test/test.js new file mode 100644 index 000000000000..b963cf96b463 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmgmean/test/test.js @@ -0,0 +1,140 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPSILON = require( '@stdlib/constants/float64/eps' ); +var incrnanmgmean = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmgmean, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmgmean( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmgmean( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving geometric mean incrementally', function test( t ) { + var expected; + var actual; + var delta; + var data; + var tol; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, NaN, 2.0, 4.0, 3.0, 4.0 ]; + N = data.length; + + acc = incrnanmgmean( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + // Note: computed by hand using textbook formula: + expected = [ + 2.0, + 2.449489742783178, + 2.449489742783178, + 2.2894284851066637, + 2.8844991406148166, + 2.8844991406148166, + 3.634241185664279 + ]; + + for ( i = 0; i < N; i++ ) { + if ( actual[ i ] === expected[ i ] ) { + t.equal( actual[ i ], expected[ i ], 'returns expected value' ); + } else { + delta = abs( expected[ i ] - actual[ i ] ); + tol = 1.2 * EPSILON * abs( expected[ i ] ); + t.equal( delta <= tol, true, 'within tolerance. Expected: '+expected[ i ]+'. Actual: '+actual[ i ]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current geometric mean', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var i; + + data = [ 2.0, NaN, 3.0, 5.0 ]; + acc = incrnanmgmean( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + actual = acc(); + expected = 3.872983346207417; // Note: computed by hand using textbook formula + delta = abs( expected - actual ); + tol = 1.0 * EPSILON * abs( expected ); + t.equal( delta <= tol, true, 'within tolerance. Expected: '+expected+'. Actual: '+actual+'. Delta: '+delta+'. Tol: '+tol+'.' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmgmean( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/README.md b/lib/node_modules/@stdlib/stats/incr/nanmhmean/README.md new file mode 100644 index 000000000000..312c1a225bea --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/README.md @@ -0,0 +1,164 @@ + + +# incrnanmhmean + +> Compute a moving [harmonic mean][harmonic-mean] incrementally, ignoring `NaN` values. + +
+ +The [harmonic mean][harmonic-mean] of positive real numbers `x_0, x_1, ..., x_{n-1}` is defined as + + + +```math +\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmhmean = require( '@stdlib/stats/incr/nanmhmean' ); +``` + +#### incrnanmhmean( window ) + +Returns an accumulator `function` which incrementally computes a moving [harmonic mean][harmonic-mean], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [harmonic mean][harmonic-mean]. + +```javascript +var accumulator = incrnanmhmean( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated [harmonic mean][harmonic-mean], ignoring `NaN` values. If not provided an input value `x`, the accumulator function returns the current [harmonic mean][harmonic-mean]. + +```javascript +var accumulator = incrnanmhmean( 3 ); + +var v = accumulator(); +// returns null + +// Fill the window... +v = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +v = accumulator( 1.0 ); // [2.0, 1.0] +// returns ~1.33 + +v = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns ~1.64 + +// Window begins sliding... +v = accumulator( 7.0 ); // [1.0, 3.0, 7.0] +// returns ~2.03 + +v = accumulator( NaN ); // [1.0, 3.0, 7.0] +// returns ~2.03 + +v = accumulator( 5.0 ); // [3.0, 7.0, 5.0] +// returns ~4.44 + +v = accumulator(); +// returns ~4.44 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmhmean = require( '@stdlib/stats/incr/nanmhmean' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmhmean( 5 ); + +// For each simulated datum, update the moving harmonic mean... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[harmonic-mean]: https://en.wikipedia.org/wiki/Harmonic_mean + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmhmean/benchmark/benchmark.js new file mode 100644 index 000000000000..1e62f76162a9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmhmean = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmhmean( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmhmean( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/img/equation_harmonic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/img/equation_harmonic_mean.svg new file mode 100644 index 000000000000..73b075001d8f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/img/equation_harmonic_mean.svg @@ -0,0 +1,148 @@ + +StartLayout 1st Row 1st Column upper H 2nd Column equals StartStartFraction n OverOver StartFraction 1 Over x 0 EndFraction plus StartFraction 1 Over x 1 EndFraction plus midline-horizontal-ellipsis plus StartFraction 1 Over x Subscript n minus 1 Baseline EndFraction EndEndFraction 2nd Row 1st Column Blank 2nd Column equals StartStartFraction n OverOver sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts StartFraction 1 Over x Subscript i Baseline EndFraction EndEndFraction 3rd Row 1st Column Blank 2nd Column equals left-parenthesis StartStartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts StartFraction 1 Over x Subscript i Baseline EndFraction OverOver n EndEndFraction right-parenthesis Superscript negative 1 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/repl.txt new file mode 100644 index 000000000000..122edbe6710f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/repl.txt @@ -0,0 +1,49 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + harmonic mean, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving harmonic mean. + + If provided a value, the accumulator function returns an updated moving + harmonic mean. If not provided a value, the accumulator function returns the + current moving harmonic mean. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var v = accumulator() + null + > v = accumulator( 2.0 ) + 2.0 + > v = accumulator( 5.0 ) + ~2.86 + > v = accumulator( NaN ) + ~2.86 + > v = accumulator( 3.0 ) + ~2.90 + > v = accumulator( 5.0 ) + ~4.09 + > v = accumulator( NaN ) + ~4.09 + > v = accumulator() + ~4.09 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/types/index.d.ts new file mode 100644 index 000000000000..a49979d4ad52 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/types/index.d.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated harmonic mean; otherwise, returns the current harmonic mean, ignoring `NaN` values. +* +* @param x - value +* @returns harmonic mean +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving harmonic mean, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving harmonic mean. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmhmean( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( 5.0 ); +* // returns ~2.86 +* +* v = accumulator( NaN ); +* // returns ~2.86 +* +* v = accumulator( 3.0 ); +* // returns ~2.90 +* +* v = accumulator( 5.0 ); +* // returns ~4.09 +* +* v = accumulator( NaN ); +* // returns ~4.09 +* +* v = accumulator(); +* // returns ~4.09 +*/ +declare function incrnanmhmean( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmhmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/types/test.ts new file mode 100644 index 000000000000..1803a634f0ad --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmhmean = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmhmean( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmhmean( '5' ); // $ExpectError + incrnanmhmean( true ); // $ExpectError + incrnanmhmean( false ); // $ExpectError + incrnanmhmean( null ); // $ExpectError + incrnanmhmean( undefined ); // $ExpectError + incrnanmhmean( [] ); // $ExpectError + incrnanmhmean( {} ); // $ExpectError + incrnanmhmean( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmhmean(); // $ExpectError + incrnanmhmean( 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmhmean( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmhmean( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmhmean/examples/index.js new file mode 100644 index 000000000000..894ca091197b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmhmean = require( './../lib' ); + +var accumulator; +var m; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmhmean( 5 ); + +// For each simulated datum, update the moving harmonic mean... +console.log( '\nValue\tHarmonic Mean\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + m = accumulator( v ); + console.log( '%s\t%s', v.toFixed( 4 ), ( m === null ) ? NaN : m.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmhmean/lib/index.js new file mode 100644 index 000000000000..b9256c61807f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving harmonic mean incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmhmean +* +* @example +* var incrnanmhmean = require( '@stdlib/stats/incr/nanmhmean' ); +* +* var accumulator = incrnanmhmean( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( 5.0 ); +* // returns ~2.86 +* +* v = accumulator( NaN ); +* // returns ~2.86 +* +* v = accumulator( 3.0 ); +* // returns ~2.90 +* +* v = accumulator( 5.0 ); +* // returns ~4.09 +* +* v = accumulator( NaN ); +* // returns ~4.09 +* +* v = accumulator(); +* // returns ~4.09 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmhmean/lib/main.js new file mode 100644 index 000000000000..a46636ec9c76 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/lib/main.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmhmean = require( '@stdlib/stats/incr/mhmean' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving harmonic mean, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmhmean( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( 5.0 ); +* // returns ~2.86 +* +* v = accumulator( NaN ); +* // returns ~2.86 +* +* v = accumulator( 3.0 ); +* // returns ~2.90 +* +* v = accumulator( 5.0 ); +* // returns ~4.09 +* +* v = accumulator( NaN ); +* // returns ~4.09 +* +* v = accumulator(); +* // returns ~4.09 +*/ +function incrnanmhmean( W ) { + var mhmean = incrmhmean( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated harmonic mean. If not provided a value, the accumulator function returns the current harmonic mean. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} harmonic mean or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return mhmean(); + } + return mhmean( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmhmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/package.json b/lib/node_modules/@stdlib/stats/incr/nanmhmean/package.json new file mode 100644 index 000000000000..5313bc9393fe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/stats/incr/nanmhmean", + "version": "0.0.0", + "description": "Compute a moving harmonic mean incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "harmonic", + "mean", + "nan", + "harmonic mean", + "central tendency", + "incremental", + "accumulator", + "moving mean", + "moving average", + "sliding window", + "sliding", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmhmean/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmhmean/test/test.js new file mode 100644 index 000000000000..d3e902278b0a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmhmean/test/test.js @@ -0,0 +1,158 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPSILON = require( '@stdlib/constants/float64/eps' ); +var incrnanmhmean = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmhmean, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmhmean( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmhmean( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving harmonic mean incrementally', function test( t ) { + var expected; + var actual; + var delta; + var data; + var tol; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, NaN, 2.0, 4.0, 3.0, NaN, 4.0 ]; + N = data.length; + + acc = incrnanmhmean( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + // Note: computed by hand using textbook formula: + expected = [ + 2.0, + 2.4, + 2.4, + 2.25, + 2.7692307692307696, + 2.7692307692307696, + 2.7692307692307696, + 3.6 + ]; + + for ( i = 0; i < N; i++ ) { + if ( actual[ i ] === expected[ i ] ) { + t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' ); + } else { + delta = abs( expected[ i ] - actual[ i ] ); + tol = EPSILON * abs( expected[ i ] ); + t.equal( delta <= tol, true, 'within tolerance. Expected: '+expected[ i ]+'. Actual: '+actual[ i ]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current harmonic mean', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var i; + + data = [ 2.0, NaN, 3.0, NaN, 5.0 ]; + acc = incrnanmhmean( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + actual = acc(); + expected = 3.75; // Note: computed by hand using textbook formula + delta = abs( expected - actual ); + tol = 1.1 * EPSILON * abs( expected ); + t.equal( delta <= tol, true, 'within tolerance. Expected: '+expected+'. Actual: '+actual+'. Delta: '+delta+'. Tol: '+tol+'.' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmhmean( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if only NaN values have been provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmhmean( 3 ); + t.strictEqual( acc( NaN ), null, 'returns expected value' ); + t.strictEqual( acc( NaN ), null, 'returns expected value' ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided NaN as the first value, the accumulator function returns `null` and then handles subsequent non-NaN values', function test( t ) { + var acc = incrnanmhmean( 3 ); + t.strictEqual( acc( NaN ), null, 'returns expected value' ); + t.strictEqual( acc( 2.0 ), 2.0, 'returns expected value' ); + t.strictEqual( acc( NaN ), 2.0, 'returns expected value' ); + t.strictEqual( acc( 4.0 ), 2.6666666666666665, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/README.md b/lib/node_modules/@stdlib/stats/incr/nanmidrange/README.md new file mode 100644 index 000000000000..01c619e1d344 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/README.md @@ -0,0 +1,141 @@ + + +# incrnanmidrange + +> Compute a [mid-range][mid-range] incrementally, ignoring `NaN` values. + +
+ +The [**mid-range**][mid-range], or **mid-extreme**, is the arithmetic mean of maximum and minimum values. Accordingly, the [mid-range][mid-range] is the midpoint of the [range][range] and a measure of central tendency. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmidrange = require( '@stdlib/stats/incr/nanmidrange' ); +``` + +#### incrnanmidrange() + +Returns an accumulator `function` which incrementally computes a [mid-range][mid-range], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmidrange(); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated [mid-range][mid-range]. If not provided an input value `x`, the accumulator function returns the current [mid-range][mid-range]. + +```javascript +var accumulator = incrnanmidrange(); + +var midrange = accumulator(); +// returns null + +midrange = accumulator( -2.0 ); +// returns -2.0 + +midrange = accumulator( NaN ); +// returns -2.0 + +midrange = accumulator( 1.0 ); +// returns -0.5 + +midrange = accumulator( 3.0 ); +// returns 0.5 + +midrange = accumulator(); +// returns 0.5 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmidrange = require( '@stdlib/stats/incr/nanmidrange' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmidrange(); + +// For each simulated datum, update the mid-range... +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[range]: https://en.wikipedia.org/wiki/Range_%28statistics%29 + +[mid-range]: https://en.wikipedia.org/wiki/Mid-range + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmidrange/benchmark/benchmark.js new file mode 100644 index 000000000000..94d5e736778e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnanmidrange = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmidrange(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmidrange(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/repl.txt new file mode 100644 index 000000000000..1e575b964272 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/repl.txt @@ -0,0 +1,37 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes a mid-range, + ignoring `NaN` values. + + The mid-range is the arithmetic mean of maximum and minimum values. + Accordingly, the mid-range is the midpoint of the range and a measure of + central tendency. + + If provided a value, the accumulator function returns an updated mid-range. + If not provided a value, the accumulator function returns the current mid- + range. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var v = accumulator() + null + > v = accumulator( 3.14 ) + 3.14 + > v = accumulator( NaN ) + 3.14 + > v = accumulator( -5.0 ) + ~-0.93 + > v = accumulator( 10.1 ) + 2.55 + > v = accumulator() + 2.55 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/types/index.d.ts new file mode 100644 index 000000000000..9d2763fa865e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/types/index.d.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated mid-range; otherwise, returns the current mid-range. +* +* ## Notes +* +* - The mid-range is the arithmetic mean of maximum and minimum values. Accordingly, the mid-range is the midpoint of the range and a measure of central tendency. +* +* @param x - value +* @returns mid-range +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a mid-range, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanmidrange(); +* +* var midrange = accumulator(); +* // returns null +* +* midrange = accumulator( 3.14 ); +* // returns 3.14 +* +* midrange = accumulator( -5.0 ); +* // returns ~-0.93 +* +* midrange = accumulator( 10.1 ); +* // returns 2.55 +* +* midrange = accumulator(); +* // returns 2.55 +*/ +declare function incrnanmidrange(): accumulator; + + +// EXPORTS // + +export = incrnanmidrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/types/test.ts new file mode 100644 index 000000000000..daa7cb3d0663 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/docs/types/test.ts @@ -0,0 +1,63 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmidrange = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmidrange(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanmidrange( '5' ); // $ExpectError + incrnanmidrange( 5 ); // $ExpectError + incrnanmidrange( true ); // $ExpectError + incrnanmidrange( false ); // $ExpectError + incrnanmidrange( null ); // $ExpectError + incrnanmidrange( undefined ); // $ExpectError + incrnanmidrange( [] ); // $ExpectError + incrnanmidrange( {} ); // $ExpectError + incrnanmidrange( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmidrange(); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null + acc( 5 ); // $ExpectType number | null + acc( -2 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmidrange(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmidrange/examples/index.js new file mode 100644 index 000000000000..b1e9baf81c7d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmidrange = require( './../lib' ); + +var accumulator; +var midrange; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmidrange(); + +// For each simulated datum, update the mid-range... +console.log( '\nValue\tMid-range\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + midrange = accumulator( v ); + console.log( '%s\t%s', ( v === v ) ? v.toFixed( 4 ) : 'NaN', ( midrange === null ) ? 'null' : midrange.toFixed( 4 ) ); +} +console.log( '\nFinal mid-range: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmidrange/lib/index.js new file mode 100644 index 000000000000..8617a753f29a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a mid-range incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmidrange +* +* @example +* var incrnanmidrange = require( '@stdlib/stats/incr/nanmidrange' ); +* +* var accumulator = incrnanmidrange(); +* +* var midrange = accumulator(); +* // returns null +* +* midrange = accumulator( 3.14 ); +* // returns 3.14 +* +* midrange = accumulator( NaN ); +* // returns 3.14 +* +* midrange = accumulator( -5.0 ); +* // returns ~-0.93 +* +* midrange = accumulator( 10.1 ); +* // returns 2.55 +* +* midrange = accumulator(); +* // returns 2.55 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmidrange/lib/main.js new file mode 100644 index 000000000000..e05833db3f8b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/lib/main.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmidrange = require( '@stdlib/stats/incr/midrange' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a mid-range, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmidrange(); +* +* var midrange = accumulator(); +* // returns null +* +* midrange = accumulator( 3.14 ); +* // returns 3.14 +* +* midrange = accumulator( NaN ); +* // returns 3.14 +* +* midrange = accumulator( -5.0 ); +* // returns ~-0.93 +* +* midrange = accumulator( 10.1 ); +* // returns 2.55 +* +* midrange = accumulator(); +* // returns 2.55 +*/ +function incrnanmidrange() { + var midrange = incrmidrange(); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated mid-range. If not provided a value, the accumulator function returns the current mid-range. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} mid-range or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return midrange(); + } + return midrange( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmidrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/package.json b/lib/node_modules/@stdlib/stats/incr/nanmidrange/package.json new file mode 100644 index 000000000000..135a071d71ee --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nanmidrange", + "version": "0.0.0", + "description": "Compute a mid-range incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "minimum", + "min", + "mid", + "range", + "mid-range", + "mid-extreme", + "mean", + "central tendency", + "incremental", + "accumulator", + "nan", + "ignore" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmidrange/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmidrange/test/test.js new file mode 100644 index 000000000000..d609935310e8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmidrange/test/test.js @@ -0,0 +1,108 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmidrange = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmidrange, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmidrange(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if not provided any values, the initial returned mid-range is `null`', function test( t ) { + var acc = incrnanmidrange(); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a mid-range', function test( t ) { + var expected; + var actual; + var data; + var acc; + var max; + var min; + var N; + var d; + var i; + + data = [ 2.0, NaN, 3.0, -2.0, NaN, 4.0, -3.0, 4.0 ]; + N = data.length; + + expected = []; + actual = []; + + acc = incrnanmidrange(); + + max = null; + min = null; + + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + + if ( !isnan( d ) ) { + if ( max === null || d > max ) { + max = d; + } + if ( min === null || d < min ) { + min = d; + } + } + + if ( max !== null && min !== null ) { + expected.push( ( max + min ) / 2.0 ); + } else { + expected.push( null ); + } + + actual.push( acc( d ) ); + } + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mid-range', function test( t ) { + var data; + var acc; + var i; + + data = [ -2.0, 3.0, NaN, 1.0 ]; + acc = incrnanmidrange(); + + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + + t.equal( acc(), 0.5, 'returns the current accumulated mid-range' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/README.md b/lib/node_modules/@stdlib/stats/incr/nanminabs/README.md new file mode 100644 index 000000000000..b05d605c3774 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/README.md @@ -0,0 +1,129 @@ + + +# incrnanminabs + +> Compute a minimum absolute value incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanminabs = require( '@stdlib/stats/incr/nanminabs' ); +``` + +#### incrnanminabs() + +Returns an accumulator `function` which incrementally computes a minimum absolute value, ignoring `NaN` values. + +```javascript +var accumulator = incrnanminabs(); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated minimum absolute value. If not provided an input value `x`, the accumulator function returns the current minimum absolute value. + +```javascript +var accumulator = incrnanminabs(); + +var min = accumulator( 2.0 ); +// returns 2.0 + +min = accumulator( 1.0 ); +// returns 1.0 + +min = accumulator( NaN ); +// returns 1.0 + +min = accumulator( -3.0 ); +// returns 1.0 + +min = accumulator(); +// returns 1.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanminabs = require( '@stdlib/stats/incr/nanminabs' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanminabs(); + +// For each simulated datum, update the minimum absolute value... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = ( randu() * 100.0 ) - 50.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanminabs/benchmark/benchmark.js new file mode 100644 index 000000000000..402cd30ef2ae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanminabs = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanminabs(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanminabs(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()-0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/repl.txt new file mode 100644 index 000000000000..8fd45bc6b2de --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/repl.txt @@ -0,0 +1,32 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes a minimum + absolute value, ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated minimum + absolute value. If not provided a value, the accumulator function returns + the current minimum absolute value. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var m = accumulator() + null + > m = accumulator( 3.14 ) + 3.14 + > m = accumulator( NaN ) + 3.14 + > m = accumulator( -5.0 ) + 3.14 + > m = accumulator( 10.1 ) + 3.14 + > m = accumulator() + 3.14 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/types/index.d.ts new file mode 100644 index 000000000000..8cac49af9919 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated minimum absolute value; otherwise, returns the current minimum absolute value. +* +* @param x - value +* @returns minimum absolute value +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a minimum absolute value, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanminabs(); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( -3.0 ); +* // returns 2.0 +* +* v = accumulator( NaN ); +* // returns 2.0 +* +* v = accumulator( 1.0 ); +* // returns 1.0 +* +* v = accumulator(); +* // returns 1.0 +*/ +declare function incrnanminabs(): accumulator; + + +// EXPORTS // + +export = incrnanminabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/types/test.ts new file mode 100644 index 000000000000..2e667c97dc84 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanminabs = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanminabs(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanminabs( '5' ); // $ExpectError + incrnanminabs( 5 ); // $ExpectError + incrnanminabs( true ); // $ExpectError + incrnanminabs( false ); // $ExpectError + incrnanminabs( null ); // $ExpectError + incrnanminabs( undefined ); // $ExpectError + incrnanminabs( [] ); // $ExpectError + incrnanminabs( {} ); // $ExpectError + incrnanminabs( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanminabs(); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanminabs(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanminabs/examples/index.js new file mode 100644 index 000000000000..4f65bd05cdfa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/examples/index.js @@ -0,0 +1,44 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanminabs = require( './../lib' ); + +var accumulator; +var min; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanminabs(); + +// For each simulated datum, update the min absolute value... +console.log( '\nValue\tMinAbs\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = ( randu() * 100.0 ) - 50.0; + } + min = accumulator( v ); + console.log( '%s\t%s', ( isnan( v ) ) ? 'NaN' : v.toFixed( 3 ), ( min === null ) ? 'null' : min.toFixed( 3 ) ); +} +console.log( '\nFinal minimum absolute value: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanminabs/lib/index.js new file mode 100644 index 000000000000..00ddb7c20929 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a minimum absolute value incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanminabs +* +* @example +* var incrnanminabs = require( '@stdlib/stats/incr/nanminabs' ); +* +* var accumulator = incrnanminabs(); +* +* var min = accumulator(); +* // returns null +* +* min = accumulator( 3.14 ); +* // returns 3.14 +* +* min = accumulator( NaN ); +* // returns 3.14 +* +* min = accumulator( -5.0 ); +* // returns 3.14 +* +* min = accumulator( 10.1 ); +* // returns 3.14 +* +* min = accumulator(); +* // returns 3.14 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanminabs/lib/main.js new file mode 100644 index 000000000000..21c57e587d16 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/lib/main.js @@ -0,0 +1,77 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrminabs = require( '@stdlib/stats/incr/minabs' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a minimum absolute value, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanminabs(); +* +* var min = accumulator(); +* // returns null +* +* min = accumulator( 3.14 ); +* // returns 3.14 +* +* min = accumulator( NaN ); +* // returns 3.14 +* +* min = accumulator( -5.0 ); +* // returns 3.14 +* +* min = accumulator( 10.1 ); +* // returns 3.14 +* +* min = accumulator(); +* // returns 3.14 +*/ +function incrnanminabs() { + var minabs = incrminabs(); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated minimum absolute value. If not provided a value, the accumulator function returns the current minimum absolute value. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} minimum absolute value or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return minabs(); + } + return minabs( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanminabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/package.json b/lib/node_modules/@stdlib/stats/incr/nanminabs/package.json new file mode 100644 index 000000000000..89506b567c56 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/stats/incr/nanminabs", + "version": "0.0.0", + "description": "Compute a minimum absolute value incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "minimum", + "min", + "abs", + "absolute", + "range", + "extremes", + "domain", + "extent", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanminabs/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanminabs/test/test.js new file mode 100644 index 000000000000..c4d5562eec95 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminabs/test/test.js @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var incrnanminabs = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanminabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanminabs(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if not provided any values, the initial returned minimum absolute value is `null`', function test( t ) { + var acc = incrnanminabs(); + t.strictEqual( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a minimum absolute value', function test( t ) { + var expected; + var actual; + var data; + var acc; + var min; + var ad; + var N; + var d; + var i; + + data = [ 2.0, -3.0, 2.0, -4.0, 3.0, 4.0 ]; + N = data.length; + + expected = []; + actual = []; + + acc = incrnanminabs(); + + min = data[ 0 ]; + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + ad = abs( d ); + if ( ad < min ) { + min = ad; + } + expected.push( min ); + actual.push( acc( d ) ); + } + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current minimum absolute value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, -3.0, 1.0 ]; + acc = incrnanminabs(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.strictEqual( acc(), 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var acc; + var v; + + acc = incrnanminabs(); + + v = acc( -0.0 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + v = acc( 0.0 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + v = acc( -0.0 ); + t.strictEqual( isPositiveZero( v ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function ignores `NaN` values and returns current minimum absolute value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 1.0, 7.0, NaN ]; + acc = incrnanminabs(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.strictEqual( acc(), 1.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/README.md b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/README.md new file mode 100644 index 000000000000..ba341c13399d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/README.md @@ -0,0 +1,136 @@ + + +# incrnanminmaxabs + +> Compute minimum and maximum absolute values incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanminmaxabs = require( '@stdlib/stats/incr/nanminmaxabs' ); +``` + +#### incrnanminmaxabs( \[out] ) + +Returns an accumulator `function` which incrementally computes minimum and maximum absolute values, ignoring `NaN` values. + +```javascript +var accumulator = incrnanminmaxabs(); +``` + +By default, the returned accumulator `function` returns the minimum and maximum absolute values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var accumulator = incrnanminmaxabs( new Float64Array( 2 ) ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns updated minimum and maximum absolute values. If not provided an input value `x`, the accumulator function returns the current minimum and maximum absolute values. + +```javascript +var accumulator = incrnanminmaxabs(); + +var mm = accumulator(); +// returns null + +mm = accumulator( 2.0 ); +// returns [ 2.0, 2.0 ] + +mm = accumulator( NaN ); +// returns [ 2.0, 2.0 ] + +mm = accumulator( 1.0 ); +// returns [ 1.0, 2.0 ] + +mm = accumulator( 3.0 ); +// returns [ 1.0, 3.0 ] + +mm = accumulator( -7.0 ); +// returns [ 1.0, 7.0 ] + +mm = accumulator(); +// returns [ 1.0, 7.0 ] +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN`, the value is **ignored** and does **not** affect the accumulated result. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanminmaxabs = require( '@stdlib/stats/incr/nanminmaxabs' ); + +// Initialize an accumulator: +var accumulator = incrnanminmaxabs(); + +// For each simulated datum, update the minimum and maximum absolute values... +var i; +for ( i = 0; i < 100; i++ ) { + accumulator( ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ) ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/benchmark/benchmark.js new file mode 100644 index 000000000000..4c2647bdc85c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/benchmark/benchmark.js @@ -0,0 +1,81 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanminmaxabs = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanminmaxabs(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var x; + var v; + var i; + + acc = incrnanminmaxabs(); + + x = new Float64Array( b.iterations ); + for ( i = 0; i < b.iterations; i++ ) { + if ( ( i & 7 ) === 7 ) { + x[ i ] = NaN; + } else { + x[ i ] = uniform( -100.0, 100.0 ); + } + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( x[ i ] ); + if ( v !== null && v.length !== 2 ) { + b.fail( 'should contain two elements' ); + } + } + b.toc(); + if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/repl.txt new file mode 100644 index 000000000000..1905e6b93b57 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/repl.txt @@ -0,0 +1,40 @@ + +{{alias}}( [out] ) + Returns an accumulator function which incrementally computes a minimum and + maximum absolute value, ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated minimum + and maximum. If not provided a value, the accumulator function returns the + current minimum and maximum. + + Any `NaN` values provided to the accumulator are ignored, and do not + affect the accumulated result. + + Parameters + ---------- + out: Array|TypedArray (optional) + Output array. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var mm = accumulator() + null + > mm = accumulator( 2.0 ); + > mm = accumulator( -5.0 ) + [ 2.0, 5.0 ] + > mm = accumulator( NaN ) + [ 2.0, 5.0 ] + > mm = accumulator( 3.0 ) + [ 2.0, 5.0 ] + > mm = accumulator() + [ 2.0, 5.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/types/index.d.ts new file mode 100644 index 000000000000..ded3f492a292 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/types/index.d.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; + +/** +* If provided a value, the accumulator function returns updated minimum and maximum absolute values. If not provided a value, the accumulator function returns the current minimum and maximum absolute values. +* +* ## Notes +* +* - If provided `NaN`, the value is ignored and does not affect the accumulated result. +* +* @param x - input value +* @returns output array or null +*/ +type accumulator = ( x?: number ) => ArrayLike | null; + +/** +* Returns an accumulator function which incrementally computes minimum and maximum absolute values, ignoring `NaN` values. +* +* @param out - output array +* @returns accumulator function +* +* @example +* var accumulator = incrnanminmaxabs(); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( NaN ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 3.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ 2.0, 5.0 ] +*/ +declare function incrnanminmaxabs( out?: ArrayLike ): accumulator; + + +// EXPORTS // + +export = incrnanminmaxabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/types/test.ts new file mode 100644 index 000000000000..6299455b4788 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanminmaxabs = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanminmaxabs(); // $ExpectType accumulator + const out = [ 0.0, 0.0 ]; + incrnanminmaxabs( out ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not an array-like object of numbers... +{ + incrnanminmaxabs( '5' ); // $ExpectError + incrnanminmaxabs( 5 ); // $ExpectError + incrnanminmaxabs( true ); // $ExpectError + incrnanminmaxabs( false ); // $ExpectError + incrnanminmaxabs( null ); // $ExpectError + incrnanminmaxabs( {} ); // $ExpectError + incrnanminmaxabs( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanminmaxabs(); + + acc(); // $ExpectType ArrayLike | null + acc( 3.14 ); // $ExpectType ArrayLike | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanminmaxabs(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/examples/index.js new file mode 100644 index 000000000000..7293c1286144 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanminmaxabs = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanminmaxabs(); + +// For each simulated datum, update the minimum and maximum absolute values... +console.log( '\nValue\tMin\tMax\n' ); +var mm; +var v; +var i; +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + mm = accumulator( v ); + if ( mm === null ) { + console.log( '%d\t--\t--', v.toFixed( 3 ) ); + } else { + console.log( '%d\t%d\t%d', v.toFixed( 3 ), mm[ 0 ].toFixed( 3 ), mm[ 1 ].toFixed( 3 ) ); + } +} +console.log( '\nFinal min/max: %s\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/lib/index.js new file mode 100644 index 000000000000..1726b4ef5aa0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute minimum and maximum absolute values incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanminmaxabs +* +* @example +* var incrnanminmaxabs = require( '@stdlib/stats/incr/nanminmaxabs' ); +* +* var accumulator = incrnanminmaxabs(); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( NaN ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 3.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ 2.0, 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/lib/main.js new file mode 100644 index 000000000000..8a0c193761c9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/lib/main.js @@ -0,0 +1,84 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrminmaxabs = require( '@stdlib/stats/incr/minmaxabs' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes minimum and maximum absolute values, ignoring `NaN` values. +* +* @param {Collection} [out] - output array +* @throws {TypeError} output argument must be array-like +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanminmaxabs(); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( NaN ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 3.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ 2.0, 5.0 ] +*/ +function incrnanminmaxabs( out ) { + var minmax; + if ( arguments.length > 0 ) { + minmax = incrminmaxabs( out ); + } else { + minmax = incrminmaxabs(); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns updated minimum and maximum absolute values. If not provided a value, the accumulator function returns the current minimum and maximum absolute values. + * + * @private + * @param {number} [x] - input value + * @returns {(ArrayLikeObject|null)} output array or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return minmax(); + } + return minmax( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanminmaxabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/package.json b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/package.json new file mode 100644 index 000000000000..4095b8597daf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/package.json @@ -0,0 +1,72 @@ +{ + "name": "@stdlib/stats/incr/nanminmaxabs", + "version": "0.0.0", + "description": "Compute minimum and maximum absolute values incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "minimum", + "min", + "absolute", + "value", + "abs", + "math.abs", + "range", + "extent", + "extrema", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/test/test.js new file mode 100644 index 000000000000..352ebd79bd52 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanminmaxabs/test/test.js @@ -0,0 +1,262 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var incrnanminmaxabs = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanminmaxabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + NaN, + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanminmaxabs( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanminmaxabs(), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (output)', function test( t ) { + t.strictEqual( typeof incrnanminmaxabs( [ 0.0, 0.0 ] ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a minimum and maximum absolute value incrementally, ignoring `NaN` values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ + 2.0, + NaN, + -3.0, + -2.0, + 4.0, + -3.0, + NaN, + -4.0, + -2.0, + 2.0, + -2.0, + 1.0, + -0.0, + 4.0, + -1.0 + ]; + N = data.length; + + acc = incrnanminmaxabs(); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( ( acc( data[ i ] ) ).slice() ); + } + expected = [ + [ 2.0, 2.0 ], + [ 2.0, 2.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 1.0, 4.0 ], + [ 0.0, 4.0 ], + [ 0.0, 4.0 ], + [ 0.0, 4.0 ] + ]; + + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'the accumulator function computes a minimum and maximum absolute value incrementally, ignoring `NaN` values (output)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var out; + var N; + var i; + + data = [ + 2.0, + NaN, + -3.0, + -2.0, + 4.0, + -3.0, + -4.0, + -2.0, + 2.0, + -2.0, + 1.0, + -0.0, + 4.0, + -1.0 + ]; + N = data.length; + + out = [ 0.0, 0.0 ]; + acc = incrnanminmaxabs( out ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + t.strictEqual( actual[ i ], out, 'returns output array' ); + actual[ i ] = actual[ i ].slice(); + } + expected = [ + [ 2.0, 2.0 ], + [ 2.0, 2.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 1.0, 4.0 ], + [ 0.0, 4.0 ], + [ 0.0, 4.0 ], + [ 0.0, 4.0 ] + ]; + + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current minimum and maximum absolute values', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, -3.0, -5.0, 4.0 ]; + acc = incrnanminmaxabs(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.deepEqual( acc(), [ 2.0, 5.0 ], 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanminmaxabs(); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if `NaN` is provided before any other values, the accumulator function returns `null`', function test( t ) { + var acc = incrnanminmaxabs(); + t.strictEqual( acc( NaN ), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var acc; + var v; + + acc = incrnanminmaxabs(); + + v = acc( 0.0 ); + t.strictEqual( isPositiveZero( v[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isPositiveZero( v[ 1 ] ), true, 'returns expected value' ); + + v = acc( -0.0 ); + t.strictEqual( isPositiveZero( v[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isPositiveZero( v[ 1 ] ), true, 'returns expected value' ); + + v = acc( 0.0 ); + t.strictEqual( isPositiveZero( v[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isPositiveZero( v[ 1 ] ), true, 'returns expected value' ); + + acc = incrnanminmaxabs(); + + v = acc( -0.0 ); + t.strictEqual( isPositiveZero( v[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isPositiveZero( v[ 1 ] ), true, 'returns expected value' ); + + v = acc( 0.0 ); + t.strictEqual( isPositiveZero( v[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isPositiveZero( v[ 1 ] ), true, 'returns expected value' ); + + v = acc( -0.0 ); + t.strictEqual( isPositiveZero( v[ 0 ] ), true, 'returns expected value' ); + t.strictEqual( isPositiveZero( v[ 1 ] ), true, 'returns expected value' ); + + t.end(); +}); + +tape( 'if provided `NaN`, the accumulator function ignores the value and continues computing minimum and maximum absolute values', function test( t ) { + var data; + var acc; + var v; + var i; + + data = [ 2.0, NaN, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, -7.0 ]; + acc = incrnanminmaxabs(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + v = acc(); + t.strictEqual( v[ 0 ], 1.0, 'returns expected value' ); + t.strictEqual( v[ 1 ], 7.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmape/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmape/package.json index 04e7ccc12d92..77adf6d4dcaf 100644 --- a/lib/node_modules/@stdlib/stats/incr/nanmmape/package.json +++ b/lib/node_modules/@stdlib/stats/incr/nanmmape/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/incr/nanmmape", "version": "0.0.0", - "description": "Compute a moving mean absolute percentage error (MAPE) incrementally, ignoring `NaN` values.", + "description": "Compute a moving mean absolute percentage error (MAPE) incrementally, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmax/README.md new file mode 100644 index 000000000000..28c3992d4b77 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/README.md @@ -0,0 +1,137 @@ + + +# incrnanmmax + +> Compute a moving maximum value incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanmmax = require( '@stdlib/stats/incr/nanmmax' ); +``` + +#### incrnanmmax( window ) + +Returns an accumulator `function` which incrementally computes a moving maximum value. The `window` parameter defines the number of values over which to compute the moving maximum, ignoring `NaN` values. + +```javascript +var accumulator = incrnanmmax( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated maximum value. If not provided an input value `x`, the accumulator function returns the current maximum value. + +```javascript +var accumulator = incrnanmmax( 3 ); + +var m = accumulator(); +// returns null + +// Fill the window... +m = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +m = accumulator( 1.0 ); // [2.0, 1.0] +// returns 2.0 + +m = accumulator( NaN ); +// returns 2.0 + +m = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns 3.0 + +// Window begins sliding... +m = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns 3.0 + +m = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns 3.0 + +m = accumulator(); +// returns 3.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmmax = require( '@stdlib/stats/incr/nanmmax' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmax( 5 ); + +// For each simulated datum, update the moving maximum... +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.1 ) ? NaN : randu() * 100.0; + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmax/benchmark/benchmark.js new file mode 100644 index 000000000000..6d22f0ea58e4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmmax = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmax( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmax( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/repl.txt new file mode 100644 index 000000000000..188b182ef050 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/repl.txt @@ -0,0 +1,47 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + maximum value, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving maximum. + + If provided a value, the accumulator function returns an updated moving + maximum. If not provided a value, the accumulator function returns the + current moving maximum. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var m = accumulator() + null + > m = accumulator( 2.0 ) + 2.0 + > m = accumulator( NaN ) + 2.0 + > m = accumulator( -5.0 ) + 2.0 + > m = accumulator( 3.0 ) + 3.0 + > m = accumulator( 5.0 ) + 5.0 + > m = accumulator() + 5.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/types/index.d.ts new file mode 100644 index 000000000000..091a20128c03 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/types/index.d.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated maximum value; otherwise, returns the current maximum value. +* +* @param x - value +* @returns maximum value +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving maximum value, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving maximum. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmax( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 2.0 +* +* m = accumulator( 3.0 ); +* // returns 3.0 +* +* m = accumulator( 5.0 ); +* // returns 5.0 +* +* m = accumulator(); +* // returns 5.0 +*/ +declare function incrnanmmax( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmax; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/types/test.ts new file mode 100644 index 000000000000..cb62c22c0173 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmax = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmax( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument which is not a number... +{ + incrnanmmax( '5' ); // $ExpectError + incrnanmmax( true ); // $ExpectError + incrnanmmax( false ); // $ExpectError + incrnanmmax( null ); // $ExpectError + incrnanmmax( undefined ); // $ExpectError + incrnanmmax( [] ); // $ExpectError + incrnanmmax( {} ); // $ExpectError + incrnanmmax( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmmax(); // $ExpectError + incrnanmmax( 3, 2 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmax( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmax( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmax/examples/index.js new file mode 100644 index 000000000000..7bae9a56854b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/examples/index.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmmax = require( './../lib' ); + +var accumulator; +var m; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmax( 5 ); + +// For each simulated datum, update the moving maximum... +console.log( '\nValue\tMax\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.1 ) ? NaN : randu() * 100.0; + m = accumulator( v ); + console.log( '%s\t%s', ( isnan( v ) ) ? 'NaN' : v.toFixed( 4 ), ( m === null ) ? 'null' : m.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmax/lib/index.js new file mode 100644 index 000000000000..da486a3c9b01 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving maximum incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmax +* +* @example +* var incrnanmmax = require( '@stdlib/stats/incr/nanmmax' ); +* +* var accumulator = incrnanmmax( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 2.0 +* +* m = accumulator( 3.0 ); +* // returns 3.0 +* +* m = accumulator( NaN ); +* // returns 3.0 +* +* m = accumulator( 5.0 ); +* // returns 5.0 +* +* m = accumulator(); +* // returns 5.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmax/lib/main.js new file mode 100644 index 000000000000..c9ba37bff164 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/lib/main.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmmax = require( '@stdlib/stats/incr/mmax' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving maximum value, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmax( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 2.0 +* +* m = accumulator( 3.0 ); +* // returns 3.0 +* +* m = accumulator( NaN ); +* // returns 3.0 +* +* m = accumulator( 5.0 ); +* // returns 5.0 +* +* m = accumulator(); +* // returns 5.0 +*/ +function incrnanmmax( W ) { + var acc = incrmmax( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated maximum. If not provided a value, the accumulator function returns the current maximum. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} maximum value or null + */ + function accumulator( x ) { + if ( arguments.length === 0 ) { + return acc(); + } + if ( isnan( x ) ) { + return acc(); + } + return acc( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmax; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmax/package.json new file mode 100644 index 000000000000..48999e9f1d44 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nanmmax", + "version": "0.0.0", + "description": "Compute a moving maximum incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "extreme", + "extent", + "range", + "incremental", + "accumulator", + "moving max", + "sliding window", + "sliding", + "window", + "moving", + "nan", + "ignore" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmax/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmax/test/test.js new file mode 100644 index 000000000000..c3aec991e2bc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmax/test/test.js @@ -0,0 +1,200 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmmax = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmmax( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if not provided any values, the initial returned maximum value is `null`', function test( t ) { + var acc = incrnanmmax( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmax( value ); + }; + } +}); + +tape( 'the accumulator function computes a moving maximum incrementally, ignoring NaN values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 5.0, NaN, 3.0, 2.0, NaN, 4.0, 1.0, NaN, 2.0, 1.0, 6.0, NaN, 2.0, 3.0 ]; + N = data.length; + + acc = incrnanmmax( 3 ); // Moving window of size 3 + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + + // Expected maximum values, ignoring NaN + expected = [ + 5.0, // [ 5.0 ] + 5.0, // [ 5.0 ] (NaN ignored) + 5.0, // [ 5.0, 3.0 ] + 5.0, // [ 5.0, 3.0, 2.0 ] + 5.0, // [ 5.0, 3.0, 2.0 ] (NaN ignored) + 4.0, // [ 3.0, 2.0, 4.0 ] (window moves) + 4.0, // [ 2.0, 4.0, 1.0 ] + 4.0, // [ 2.0, 4.0, 1.0 ] (NaN ignored) + 4.0, // [ 4.0, 1.0, 2.0 ] + 2.0, // [ 1.0, 2.0, 1.0 ] + 6.0, // [ 2.0, 1.0, 6.0 ] + 6.0, // [ 2.0, 1.0, 6.0 ] (NaN ignored) + 6.0, // [ 1.0, 6.0, 2.0 ] + 6.0 // [ 6.0, 2.0, 3.0 ] + ]; + + // Check the computed values against the expected values + for ( i = 0; i < N; i++ ) { + t.equal( actual[ i ], expected[ i ], 'returns expected value at index ' + i ); + } + + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current maximum value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 1.0, NaN, 3.0 ]; + acc = incrnanmmax( 3 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 3.0, 'returns the current accumulated maximum value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmax( 3 ); + + data = [ + -0.0, // -0 + 0.0, // -0, 0 + -0.0, // -0, 0, -0 + -0.0, // 0, -0, -0 + -0.0, // -0, -0, -0 + 0.0, // -0, -0, 0 + -0.0, // -0, 0, -0 + -0.0, // 0, -0, -0 + -0.0, // -0, -0, -0 + 0.0, // -0, -0, 0 + 0.0, // -0, 0, 0 + 0.0, // 0, 0, 0 + -0.0 // 0, 0, -0 + ]; + expected = [ + -0.0, + 0.0, + 0.0, + 0.0, + -0.0, + 0.0, + 0.0, + 0.0, + -0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( isPositiveZero( expected[ i ] ) ) { + t.strictEqual( isPositiveZero( v ), true, 'returns expected value for window '+i ); + } else { + t.strictEqual( isNegativeZero( v ), true, 'returns expected value for window '+i ); + } + } + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function ignores it and maintains the current maximum', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 1.0, 2.0, 3.0, NaN, 5.0, 6.0, 7.0 ]; + acc = incrnanmmax( 3 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( isnan( acc() ), false, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/README.md new file mode 100644 index 000000000000..ed76af5a0e29 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/README.md @@ -0,0 +1,127 @@ + + +# incrnanmmaxabs + +> Compute a moving maximum absolute value incrementally ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanmmaxabs = require( '@stdlib/stats/incr/nanmmaxabs' ); +``` + +#### incrnanmmaxabs( window ) + +Returns an accumulator `function` which incrementally computes a moving maximum absolute value. The `window` parameter defines the number of values over which to compute the moving maximum absolute value. + +```javascript +var accumulator = incrnanmmaxabs( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated maximum absolute value. If not provided an input value `x`, the accumulator function returns the current maximum absolute value. + +```javascript +var accumulator = incrnanmmaxabs( 3 ); + +var m = accumulator(); +// returns null + +// Fill the window... +m = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +m = accumulator( NaN ); // [2.0] +// returns 2.0 + +m = accumulator( -5.0 ); // [2.0, -5.0] +// returns 5.0 + +m = accumulator( -7.0 ); // [2.0, -5.0, -7.0] +// returns 7.0 + +m = accumulator( NaN ); // [2.0, -5.0, -7.0] +// returns 7.0 + +m = accumulator(); +// returns 7.0 +``` + +
+ + + +
+ +## Notes + +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmaxabs = require( '@stdlib/stats/incr/nanmmaxabs' ); + +// Initialize an accumulator: +var accumulator = incrnanmmaxabs( 5 ); + +// For each simulated datum, update the moving maximum absolute value... +var v; +var i; +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/benchmark/benchmark.js new file mode 100644 index 000000000000..59adfd484459 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/benchmark/benchmark.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var Float64Array = require( '@stdlib/array/float64' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmmaxabs = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmaxabs( ( i % 5 ) + 1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var x; + var i; + + acc = incrnanmmaxabs( 5 ); + + x = new Float64Array( b.iterations ); + for ( i = 0; i < b.iterations; i++ ) { + if ( ( i & 7 ) === 0 ) { + x[ i ] = NaN; + } else { + x[ i ] = uniform( -100.0, 100.0 ); + } + } + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( x[ i ] ); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( isnan( v ) ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/repl.txt new file mode 100644 index 000000000000..fee81205525c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/repl.txt @@ -0,0 +1,47 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + maximum absolute value while ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving maximum absolute value. + + If provided a value, the accumulator function returns an updated moving + maximum absolute value. If not provided a value, the accumulator function + returns the current moving maximum absolute value. + + Any `NaN` values provided to the accumulator are ignored, and do not + affect the accumulated result. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided non-NaN values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var m = accumulator() + null + > m = accumulator( 2.0 ) + 2.0 + > m = accumulator( NaN ) + 2.0 + > m = accumulator( -5.0 ) + 5.0 + > m = accumulator( 3.0 ) + 5.0 + > m = accumulator() + 5.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/types/index.d.ts new file mode 100644 index 000000000000..eb6696d1d283 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/types/index.d.ts @@ -0,0 +1,67 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated moving maximum absolute value; otherwise, returns the current maximum absolute value. +* +* +* @param x - value +* @returns moving maximum absolute value +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving maximum absolute value while ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving maximum absolute value. +* - Until the window is full, each returned value is calculated from all non-NaN values received so far. `NaN` values are skipped and do not enter the moving window. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmaxabs( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 5.0 +* +* m = accumulator( NaN ); +* // returns 5.0 +*/ +declare function incrnanmmaxabs( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmaxabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/types/test.ts new file mode 100644 index 000000000000..b17a4494e59e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmaxabs = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmaxabs( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmmaxabs( '5' ); // $ExpectError + incrnanmmaxabs( true ); // $ExpectError + incrnanmmaxabs( false ); // $ExpectError + incrnanmmaxabs( null ); // $ExpectError + incrnanmmaxabs( undefined ); // $ExpectError + incrnanmmaxabs( [] ); // $ExpectError + incrnanmmaxabs( {} ); // $ExpectError + incrnanmmaxabs( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmmaxabs(); // $ExpectError + incrnanmmaxabs( 2, 5 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmaxabs( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmaxabs( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/examples/index.js new file mode 100644 index 000000000000..a67c3da482fa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmaxabs = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanmmaxabs( 5 ); + +// For each simulated datum, update the moving maximum absolute value... +console.log( '\nValue\tMaxAbs\n' ); +var max; +var v; +var i; +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + max = accumulator( v ); + console.log( '%d\t%d', v.toFixed( 4 ), ( max === null ) ? NaN : max.toFixed( 3 ) ); +} +console.log( '\nFinal maximum absolute value: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/lib/index.js new file mode 100644 index 000000000000..6d7b94391561 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving maximum absolute value incrementally while ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmaxabs +* +* @example +* var incrnanmmaxabs = require( '@stdlib/stats/incr/nanmmaxabs' ); +* +* var accumulator = incrnanmmaxabs( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // ignores NaN +* +* m = accumulator( -5.0 ); +* // returns 5.0 +* +* m = accumulator( 3.0 ); +* // returns 5.0 +* +* m = accumulator(); +* // returns 5.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/lib/main.js new file mode 100644 index 000000000000..2d108987a532 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/lib/main.js @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isPositiveInteger = require( '@stdlib/assert/is-positive-integer' ).isPrimitive; +var incrmmaxabs = require( '@stdlib/stats/incr/mmaxabs' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var format = require( '@stdlib/string/format' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving maximum absolute value while ignoring NaN values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmaxabs( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 5.0 +* +* m = accumulator( 3.0 ); +* // returns 5.0 +* +* m = accumulator( NaN ); +* // returns 5.0 +* +* m = accumulator( 5.0 ); +* // returns 5.0 +* +* m = accumulator(); +* // returns 5.0 +*/ +function incrnanmmaxabs( W ) { + var max; + if ( !isPositiveInteger( W ) ) { + throw new TypeError( format( 'invalid argument. Must provide a positive integer. Value: `%s`.', W ) ); + } + max = incrmmaxabs( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated maximum absolute value. If not provided a value, the accumulator function returns the current maximum absolute value. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} maximum absolute value or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return max(); + } + return max( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmaxabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/package.json new file mode 100644 index 000000000000..26a45b681551 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/stats/incr/nanmmaxabs", + "version": "0.0.0", + "description": "Compute a moving maximum absolute value incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "absolute", + "abs", + "magnitude", + "extreme", + "extent", + "range", + "incremental", + "accumulator", + "moving max", + "sliding window", + "sliding", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/test/test.js new file mode 100644 index 000000000000..813a1556be11 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmaxabs/test/test.js @@ -0,0 +1,209 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmmaxabs = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmaxabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmaxabs( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmmaxabs( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving maximum absolute value incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, -3.0, 2.0, -4.0, 3.0, 4.0, -2.0, 2.0, -2.0, 1.0 ]; + N = data.length; + + acc = incrnanmmaxabs( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + expected = [ 2.0, 3.0, 3.0, 4.0, 4.0, 4.0, 4.0, 4.0, 2.0, 2.0 ]; + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current maximum absolute value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, -3.0, -5.0, 4.0 ]; + acc = incrnanmmaxabs( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.strictEqual( acc(), 5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmaxabs( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmaxabs( 3 ); + + data = [ + -0.0, // -0 + 0.0, // -0, 0 + -0.0, // -0, 0, -0 + -0.0, // 0, -0, -0 + -0.0, // -0, -0, -0 + 0.0, // -0, -0, 0 + -0.0, // -0, 0, -0 + -0.0, // 0, -0, -0 + -0.0, // -0, -0, -0 + 0.0, // -0, -0, 0 + 0.0, // -0, 0, 0 + 0.0, // 0, 0, 0 + -0.0 // 0, 0, -0 + ]; + expected = [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( isPositiveZero( expected[ i ] ) ) { + t.strictEqual( isPositiveZero( v ), true, 'returns expected value for window '+i ); + } else { + t.strictEqual( isNegativeZero( v ), true, 'returns expected value for window '+i ); + } + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulator function ignores it and returns the current maximum value', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmaxabs( 3 ); + + data = [ + NaN, + 3.14, + NaN, + NaN, + 2.0, + NaN, + -4.0, + NaN, + 1.0, + NaN + ]; + expected = [ + null, // [] + 3.14, // [3.14] + 3.14, // [3.14] + 3.14, // [3.14] + 3.14, // [3.14, 2.0] + 3.14, // [3.14, 2.0] + 4.0, // [3.14, 2.0, -4.0] + 4.0, // [3.14, 2.0, -4.0] + 4.0, // [2.0, -4.0, 1.0] + 4.0 // [2.0, -4.0, 1.0] + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( isnan( expected[ i ] ) ) { + t.strictEqual( isnan( v ), true, 'returns expected value for window '+i ); + } else { + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmda/README.md new file mode 100644 index 000000000000..c780c0b94040 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/README.md @@ -0,0 +1,173 @@ + + +# incrnanmmda + +> Compute a moving [mean directional accuracy][mean-directional-accuracy] (MDA) incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [mean directional accuracy][mean-directional-accuracy] is defined as + + + +```math +\mathop{\mathrm{MDA}} = \begin{cases} 1 & \textrm{if}\ W = 1 \\ \frac{1}{W} \sum_{i=1}^{W} \delta_{\mathop{\mathrm{sgn}}(\Delta f_{i,i-1}),\ \mathop{\mathrm{sgn}}(\Delta a_{i,i-1})} & \textrm{if}\ W > 1 \end{cases} +``` + + + + + +where `f_i` is the forecast value, `a_i` is the actual value, `sgn(x)` is the [signum][@stdlib/math/base/special/signum] function, and `δ` is the [Kronecker delta][@stdlib/math/base/special/kronecker-delta]. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmmda = require( '@stdlib/stats/incr/nanmmda' ); +``` + +#### incrnanmmda( window ) + +Returns an accumulator `function` which incrementally computes a moving [mean directional accuracy][mean-directional-accuracy], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [mean directional accuracy][mean-directional-accuracy]. + +```javascript +var accumulator = incrnanmmda( 3 ); +``` + +#### accumulator( \[f, a] ) + +If provided input values `f` and `a`, the accumulator function returns an updated [mean directional accuracy][mean-directional-accuracy]. If not provided input values `f` and `a`, the accumulator function returns the current [mean directional accuracy][mean-directional-accuracy]. + +```javascript +var accumulator = incrnanmmda( 3 ); + +var m = accumulator(); +// returns null + +m = accumulator( NaN, 4.0 ); +// returns null + +// Fill the window... +m = accumulator( 2.0, 3.0 ); // [(+,+)] +// returns 1.0 + +m = accumulator( 1.0, 4.0 ); // [(+,+), (-,+)] +// returns 0.5 + +m = accumulator( 3.0, NaN ); // [(+,+), (-,+)] +// returns 0.5 + +m = accumulator( 3.0, 9.0 ); // [(+,+), (-,+), (+,+)] +// returns ~0.67 + +// Window begins sliding... +m = accumulator( 7.0, 3.0 ); // [(-,+), (+,+), (+,-)] +// returns ~0.33 + +m = accumulator( NaN, NaN ); // [(-,+), (+,+), (+,-)] +// returns ~0.33 + +m = accumulator( 5.0, 3.0 ); // [(+,+), (+,-), (-,0)] +// returns ~0.33 + +m = accumulator(); +// returns ~0.33 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is **not** changed and the current input values get **ignored**. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmmda = require( '@stdlib/stats/incr/nanmmda' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmda( 5 ); + +// For each simulated datum, update the moving mean directional accuracy... +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.1 ) ) ? NaN : ( randu()*100.0 ) - 50.0; + v2 = ( bernoulli( 0.1 ) ) ? NaN : ( randu()*100.0 ) - 50.0; + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ + +
+ + + + + +
+ +[mean-directional-accuracy]: https://en.wikipedia.org/wiki/Mean_Directional_Accuracy_%28MDA%29 + +[@stdlib/math/base/special/signum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/signum + +[@stdlib/math/base/special/kronecker-delta]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/math/base/special/kronecker-delta + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmda/benchmark/benchmark.js new file mode 100644 index 000000000000..12f0016db125 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmmda = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmda( ( i % 5 ) + 1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmda( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() - 0.5, randu() - 0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/img/equation_mean_directional_accuracy.svg b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/img/equation_mean_directional_accuracy.svg new file mode 100644 index 000000000000..266057954f27 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/img/equation_mean_directional_accuracy.svg @@ -0,0 +1,115 @@ + +upper M upper D upper A equals StartLayout Enlarged left-brace 1st Row 1st Column 1 2nd Column if upper W equals 1 2nd Row 1st Column StartFraction 1 Over upper W EndFraction sigma-summation Underscript i equals 1 Overscript upper W Endscripts delta Subscript s g n left-parenthesis normal upper Delta f Sub Subscript i comma i minus 1 Subscript right-parenthesis comma s g n left-parenthesis normal upper Delta a Sub Subscript i comma i minus 1 Subscript right-parenthesis Baseline 2nd Column if upper W greater-than 1 EndLayout + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/repl.txt new file mode 100644 index 000000000000..1639f016da83 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/repl.txt @@ -0,0 +1,50 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + mean directional accuracy (MDA), ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving mean directional accuracy. + + If provided input values, the accumulator function returns an updated moving + mean directional accuracy. If not provided input values or if either of the + provided values is `NaN`, the accumulator function returns the current + moving mean directional accuracy. + + As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + 1.0 + > m = accumulator( 5.0, 2.0 ) + 0.5 + > m = accumulator( NaN, NaN ) + 0.5 + > m = accumulator( 3.0, 2.0 ) + ~0.33 + > m = accumulator( 4.0, NaN ) + ~0.33 + > m = accumulator( 4.0, 5.0 ) + ~0.33 + > m = accumulator() + ~0.33 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/types/index.d.ts new file mode 100644 index 000000000000..a6e8e1a38f1b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/types/index.d.ts @@ -0,0 +1,83 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, the accumulator function returns an updated mean directional accuracy. If not provided a value or if either of the provided values is `NaN`, the accumulator function returns the current mean directional accuracy. +* +* ## Notes +* +* - If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is not updated and the current value is returned. +* +* @param f - forecast value +* @param a - actual value +* @returns mean directional accuracy or null +*/ +type accumulator = ( f?: number, a?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving mean directional accuracy, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving mean directional accuracy. +* - As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmda( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( NaN, 4.0 ); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( 5.0, 2.0 ); +* // returns 0.5 +* +* m = accumulator( NaN, NaN ); +* // returns 0.5 +* +* m = accumulator( 3.0, 2.0 ); +* // returns ~0.33 +* +* m = accumulator( 4.0, NaN ); +* // returns ~0.33 +* +* m = accumulator( 4.0, 5.0 ); +* // returns ~0.33 +* +* m = accumulator(); +* // returns ~0.33 +*/ +declare function incrnanmmda( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmda; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/types/test.ts new file mode 100644 index 000000000000..37b924ac00c1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmda = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmda( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmmda( '5' ); // $ExpectError + incrnanmmda( true ); // $ExpectError + incrnanmmda( false ); // $ExpectError + incrnanmmda( null ); // $ExpectError + incrnanmmda( undefined ); // $ExpectError + incrnanmmda( [] ); // $ExpectError + incrnanmmda( {} ); // $ExpectError + incrnanmmda( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmmda(); // $ExpectError + incrnanmmda( 3, 2 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmda( 3 ); + + acc(); // $ExpectType number | null + acc( NaN, 2.0 ); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmda( 3 ); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmda/examples/index.js new file mode 100644 index 000000000000..e4f4bd6fb706 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmmda = require( './../lib' ); + +var accumulator; +var v1; +var v2; +var m; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmda( 5 ); + +// For each simulated datum, update the moving mean directional accuracy... +console.log( '\nValue\tValue\tMDA\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.1 ) ) ? NaN : ( randu()*100.0 ) - 50.0; + v2 = ( bernoulli( 0.1 ) ) ? NaN : ( randu()*100.0 ) - 50.0; + m = accumulator( v1, v2 ); + if ( m === null ) { + console.log( '%d\t%d\t%s', v1.toFixed( 3 ), v2.toFixed( 3 ), m ); + } else { + console.log( '%d\t%d\t%d', v1.toFixed( 3 ), v2.toFixed( 3 ), m.toFixed( 3 ) ); + } +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmda/lib/index.js new file mode 100644 index 000000000000..32193652b804 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/lib/index.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving mean directional accuracy incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmda +* +* @example +* var incrnanmmda = require( '@stdlib/stats/incr/nanmmda' ); +* +* var accumulator = incrnanmmda( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( NaN, 4.0 ); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( 5.0, 2.0 ); +* // returns 0.5 +* +* m = accumulator( NaN, NaN ); +* // returns 0.5 +* +* m = accumulator( 3.0, 2.0 ); +* // returns ~0.33 +* +* m = accumulator( 4.0, NaN ); +* // returns ~0.33 +* +* m = accumulator( 4.0, 5.0 ); +* // returns ~0.33 +* +* m = accumulator(); +* // returns ~0.33 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmda/lib/main.js new file mode 100644 index 000000000000..8c63cb6441ed --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/lib/main.js @@ -0,0 +1,86 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmmda = require( '@stdlib/stats/incr/mmda' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving mean directional accuracy, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmda( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( 5.0, 2.0 ); +* // returns 0.5 +* +* m = accumulator( NaN, NaN ); +* // returns 0.5 +* +* m = accumulator( 3.0, 2.0 ); +* // returns ~0.33 +* +* m = accumulator( 4.0, NaN ); +* // returns ~0.33 +* +* m = accumulator( 4.0, 5.0 ); +* // returns ~0.33 +* +* m = accumulator(); +* // returns ~0.33 +*/ +function incrnanmmda( W ) { + var mmda = incrmmda( W ); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated mean directional accuracy. If not provided input values or if either of the values provided is NaN, the accumulator function returns the current mean directional accuracy. + * + * @private + * @param {number} [f] - forecast value + * @param {number} [a] - actual value + * @returns {(number|null)} mean directional accuracy or null + */ + function accumulator( f, a ) { + if ( arguments.length === 0 || isnan( f ) || isnan( a ) ) { + return mmda(); + } + return mmda( f, a ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmda; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmda/package.json new file mode 100644 index 000000000000..cf4ea7537fa8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/package.json @@ -0,0 +1,82 @@ +{ + "name": "@stdlib/stats/incr/nanmmda", + "version": "0.0.0", + "description": "Compute a moving mean directional accuracy (MDA) incrementally, ignoring `NaN` values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "direction", + "directional", + "accuracy", + "trend", + "incremental", + "accumulator", + "moving mean", + "moving average", + "sliding window", + "sliding", + "window", + "moving", + "time series", + "timeseries", + "demand", + "forecasting", + "forecast", + "economics", + "econ", + "finance" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmda/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmda/test/test.js new file mode 100644 index 000000000000..331063ad8a6a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmda/test/test.js @@ -0,0 +1,152 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmmda = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmda, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmda( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmmda( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving mean directional accuracy incrementally', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var N; + var i; + + data = [ + [ 2.0, 3.0 ], // +,+ + [ 3.0, 1.0 ], // +,- + [ 5.0, 2.0 ], // +,+ + [ NaN, 2.0 ], // 0,0 + [ 4.0, 4.0 ], // -,+ + [ -3.0, 10.0 ], // -,+ + [ 3.0, NaN ], // 0,0 + [ 4.0, -5.0 ], // +,- + [ NaN, NaN ], // 0,0 + [ 4.0, -5.0 ], // 0,0 + [ -4.0, -6.0 ] // -,- + ]; + N = data.length; + + acc = incrnanmmda( 3 ); + + // Note: manually computed + expected = [ + 1.0, + 1.0/2.0, + 2.0/3.0, + 2.0/3.0, + 1.0/3.0, + 1.0/3.0, + 1.0/3.0, + 0.0/3.0, + 0.0/3.0, + 1.0/3.0, + 2.0/3.0 + ]; + for ( i = 0; i < N; i++ ) { + actual = acc( data[i][0], data[i][1] ); + if ( actual === expected[i] ) { + t.equal( actual, expected[i], 'returns expected value' ); + } else { + delta = abs( expected[i] - actual ); + tol = 1.0 * EPS * abs( expected[i] ); + t.equal( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected[i]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean directional accuracy', function test( t ) { + var data; + var acc; + var i; + + data = [ + [ NaN, NaN ], // 0,0 + [ 2.0, 3.0 ], // +,+ + [ 3.0, 5.0 ], // +,+ + [ NaN, 2.0 ], // 0,0 + [ 1.0, 10.0 ] // -,+ + ]; + acc = incrnanmmda( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[i][0], data[i][1] ); + } + t.equal( acc(), 0.5, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmda( 3 ); + t.equal( acc(), null, 'returns null' ); + acc( NaN, 1.0 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/README.md b/lib/node_modules/@stdlib/stats/incr/nanmme/README.md new file mode 100644 index 000000000000..048af3f45c7f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/README.md @@ -0,0 +1,154 @@ + + +# incrnanmme + +> Compute a moving [mean error][mean-absolute-error] (ME) incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [mean error][mean-absolute-error] is defined as + + + +```math +\mathop{\mathrm{ME}} = \frac{1}{W} \sum_{i=0}^{W-1} (y_i - x_i) +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmme = require( '@stdlib/stats/incr/nanmme' ); +``` + +#### incrnanmme( window ) + +Returns an accumulator `function` which incrementally computes a moving [mean error][mean-absolute-error], ignoring any `(x, y)` pairs containing `NaN`. The `window` parameter defines the number of values over which to compute the moving [mean error][mean-absolute-error]. + +```javascript +var accumulator = incrnanmme( 3 ); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated [mean error][mean-absolute-error]. If not provided input values `x` and `y`, the accumulator function returns the current [mean error][mean-absolute-error]. + +```javascript +var accumulator = incrnanmme( 3 ); + +var m = accumulator(); +// returns null + +// Fill the window... +m = accumulator( 2.0, 3.0 ); // [(2.0, 3.0)] +// returns 1.0 + +m = accumulator( -5.0, 2.0 ); // [(2.0, 3.0), (-5.0, 2.0)] +// returns 4.0 + +m = accumulator( 3.0, NaN ); // NaN pair ignored: [(2.0, 3.0), (-5.0, 2.0)] +// returns 4.0 + +// Window begins sliding... +m = accumulator( -7.0, 3.0 ); // [(2.0, 3.0), (-5.0, 2.0), (-7.0, 3.0)] +// returns 6.0 + +m = accumulator( -5.0, -3.0 ); // [(-5.0, 2.0), (-7.0, 3.0), (-5.0, -3.0)] +// returns ~6.33 + +m = accumulator(); +// returns ~6.33 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. Any `(x, y)` pair containing `NaN` is ignored and does **not** update the window. +- As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +- Be careful when interpreting the [mean error][mean-absolute-error] as errors can cancel. This stated, that errors can cancel makes the [mean error][mean-absolute-error] suitable for measuring the bias in forecasts. +- **Warning**: the [mean error][mean-absolute-error] is scale-dependent and, thus, the measure should **not** be used to make comparisons between datasets having different scales. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmme = require( '@stdlib/stats/incr/nanmme' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmme( 5 ); + +// For each simulated datum, update the moving mean error... +for ( i = 0; i < 100; i++ ) { + v1 = ( randu()*100.0 ) - 50.0; + v2 = ( randu()*100.0 ) - 50.0; + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +[mean-absolute-error]: https://en.wikipedia.org/wiki/Mean_absolute_error + + + + + +
+ + + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmme/benchmark/benchmark.js new file mode 100644 index 000000000000..3a9319853010 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/benchmark/benchmark.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmme = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmme( ( i % 5 ) + 1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmme( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() - 0.5, randu() - 0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator-nan', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmme( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + if ( i % 10 === 0 ) { + v = acc( NaN, randu() - 0.5 ); + } else { + v = acc( randu() - 0.5, randu() - 0.5 ); + } + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/docs/img/equation_mean_error.svg b/lib/node_modules/@stdlib/stats/incr/nanmme/docs/img/equation_mean_error.svg new file mode 100644 index 000000000000..e69de29bb2d1 diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmme/docs/repl.txt new file mode 100644 index 000000000000..a24b4f5113cd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/docs/repl.txt @@ -0,0 +1,46 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + mean error (ME), ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving mean error. + + If provided input values, the accumulator function returns an updated + moving mean error. If not provided input values, the accumulator function + returns the current moving mean error. + + As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values which + are not `NaN`. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + 1.0 + > m = accumulator( -5.0, NaN ) + 1.0 + > m = accumulator( 3.0, 2.0 ) + 0.0 + > m = accumulator( 5.0, -2.0 ) + ~-2.33 + > m = accumulator() + ~-2.33 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmme/docs/types/index.d.ts new file mode 100644 index 000000000000..851e1fd908c3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/docs/types/index.d.ts @@ -0,0 +1,77 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided input values, the accumulator function returns an updated mean error. If not provided input values, the accumulator function returns the current mean error. +* +* ## Notes +* +* - If either `x` or `y` is `NaN`, the pair is ignored and the accumulator returns the previously accumulated value. +* +* @param x - input value +* @param y - input value +* @returns mean error or null +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving mean error (ME), ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving mean error. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmme( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator( 3.0, NaN ); +* // returns 4.0 +* +* m = accumulator( -7.0, 3.0 ); +* // returns 6.0 +* +* m = accumulator( -5.0, -3.0 ); +* // returns ~6.33 +* +* m = accumulator(); +* // returns ~6.33 +*/ +declare function incrnanmme( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmme; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmme/docs/types/test.ts new file mode 100644 index 000000000000..0e545472064b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/docs/types/test.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmme = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmme( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmme( '5' ); // $ExpectError + incrnanmme( true ); // $ExpectError + incrnanmme( false ); // $ExpectError + incrnanmme( null ); // $ExpectError + incrnanmme( undefined ); // $ExpectError + incrnanmme( [] ); // $ExpectError + incrnanmme( {} ); // $ExpectError + incrnanmme( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmme(); // $ExpectError + incrnanmme( 5, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmme( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmme( 3 ); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmme/examples/index.js new file mode 100644 index 000000000000..0940c00f5eb7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmme = require( './../lib' ); + +var accumulator; +var err; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmme( 5 ); + +// For each simulated datum, update the moving mean error... +console.log( '\nValue\tValue\tME\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( randu()*100.0 ) - 50.0; + v2 = ( i%10 === 0 ) ? NaN : ( ( randu()*100.0 ) - 50.0 ); + err = accumulator( v1, v2 ); + console.log( '%s\t%s\t%s', v1.toFixed( 3 ), ( isnan( v2 ) ) ? 'NaN' : v2.toFixed( 3 ), ( err === null ) ? 'null' : err.toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmme/lib/index.js new file mode 100644 index 000000000000..f78b1e5a46c5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving mean error (ME) incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmme +* +* @example +* var incrnanmme = require( '@stdlib/stats/incr/nanmme' ); +* +* var accumulator = incrnanmme( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator( 3.0, NaN ); +* // returns 4.0 +* +* m = accumulator( -7.0, 3.0 ); +* // returns 6.0 +* +* m = accumulator( -5.0, -3.0 ); +* // returns ~6.33 +* +* m = accumulator(); +* // returns ~6.33 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmme/lib/main.js new file mode 100644 index 000000000000..4fe69eb129f9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/lib/main.js @@ -0,0 +1,86 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmme = require( '@stdlib/stats/incr/mme' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving mean error (ME), ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmme( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* m = accumulator( -5.0, 2.0 ); +* // returns 4.0 +* +* m = accumulator( 3.0, NaN ); +* // returns 4.0 +* +* m = accumulator( -7.0, 3.0 ); +* // returns 6.0 +* +* m = accumulator( NaN, -3.0 ); +* // returns 6.0 +* +* m = accumulator( -5.0, -3.0 ); +* // returns ~6.33 +* +* m = accumulator(); +* // returns ~6.33 +*/ +function incrnanmme( W ) { + var acc = incrmme( W ); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated mean error. If not provided input values, the accumulator function returns the current mean error. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} mean error or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return acc(); + } + return acc( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmme; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/package.json b/lib/node_modules/@stdlib/stats/incr/nanmme/package.json new file mode 100644 index 000000000000..d8f43a414873 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/package.json @@ -0,0 +1,83 @@ +{ + "name": "@stdlib/stats/incr/nanmme", + "version": "0.0.0", + "description": "Compute a moving mean error (ME) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "error", + "err", + "me", + "incremental", + "accumulator", + "moving mean", + "moving average", + "sliding window", + "sliding", + "window", + "moving", + "time series", + "timeseries", + "forecasting", + "forecast", + "difference", + "diff", + "delta", + "bias", + "nan", + "ignorenan" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmme/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmme/test/test.js new file mode 100644 index 000000000000..a8c306cf9318 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmme/test/test.js @@ -0,0 +1,136 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmme = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmme, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5, + 0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmme( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmme( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving mean error incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var i; + + data = [ + [ 2, 3 ], + [ 3, -1 ], + [ 2, 5 ], + [ 4, -4 ], + [ 3, 0 ], + [ -4, 5 ] + ]; + expected = [ 1, -1.5, 0, -3, -8/3, -2/3 ]; + acc = incrnanmme( 3 ); + + for ( i = 0; i < data.length; i++ ) { + actual = acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + if ( actual === expected[ i ] ) { + t.strictEqual( actual, expected[ i ], 'returns expected value' ); + } else { + t.strictEqual( isnan( actual ), false, 'does not return NaN' ); + } + } + t.end(); +}); + +tape( 'the accumulator function returns the current mean error if not provided input values', function test( t ) { + var acc = incrnanmme( 2 ); + acc( 2, 3 ); + acc( 3, -5 ); + acc( 1, 10 ); + t.strictEqual( acc(), 0.5, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function returns `null` if no data has been provided', function test( t ) { + var acc = incrnanmme( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function ignores NaN inputs', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + data = [ + [ NaN, 1 ], + [ 1, NaN ], + [ NaN, NaN ], + [ 2, 2 ], + [ NaN, 3 ] + ]; + expected = [ null, null, null, 0, 0 ]; + acc = incrnanmme( 3 ); + + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + t.strictEqual( v, expected[ i ], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmean/README.md new file mode 100644 index 000000000000..3190f2692f41 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/README.md @@ -0,0 +1,161 @@ + + +# incrnanmmean + +> Compute a moving [arithmetic mean][arithmetic-mean] incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [arithmetic mean][arithmetic-mean] is defined as + + + +```math +\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmmean = require( '@stdlib/stats/incr/nanmmean' ); +``` + +#### incrnanmmean( window ) + +Returns an accumulator `function` which incrementally computes a moving [arithmetic mean][arithmetic-mean], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving mean. + +```javascript +var accumulator = incrnanmmean( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated mean. If not provided an input value `x`, the accumulator function returns the current mean. + +```javascript +var accumulator = incrnanmmean( 3 ); + +var mu = accumulator(); +// returns null + +// Fill the window... +mu = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +mu = accumulator( 1.0 ); // [2.0, 1.0] +// returns 1.5 + +mu = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns 2.0 + +// Window begins sliding... +mu = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns -1.0 + +mu = accumulator( NaN ); // [1.0, 3.0, -7.0] +// returns -1.0 + +mu = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns -3.0 + +mu = accumulator(); +// returns -3.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmean = require( '@stdlib/stats/incr/nanmmean' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmean( 5 ); + +// For each simulated datum, update the moving mean... +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmean/benchmark/benchmark.js new file mode 100644 index 000000000000..d364403a72c5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmmean = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmean( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmean( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/img/equation_arithmetic_mean.svg new file mode 100644 index 000000000000..1a89a2bfb996 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/img/equation_arithmetic_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over upper W EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/repl.txt new file mode 100644 index 000000000000..e6060ed3a9ef --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/repl.txt @@ -0,0 +1,49 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + arithmetic mean, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving mean. + + If provided a value, the accumulator function returns an updated moving + mean. If not provided a value, the accumulator function returns the current + moving mean. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var mu = accumulator() + null + > mu = accumulator( 2.0 ) + 2.0 + > mu = accumulator( -5.0 ) + -1.5 + > mu = accumulator( NaN ) + -1.5 + > mu = accumulator( 3.0 ) + 0.0 + > mu = accumulator( 5.0 ) + 1.0 + > mu = accumulator( NaN ) + 1.0 + > mu = accumulator() + 1.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/types/index.d.ts new file mode 100644 index 000000000000..146cce3794e4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/types/index.d.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated arithmetic mean; otherwise, returns the current arithmetic mean. +* +* @param x - value +* @returns arithmetic mean +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving mean. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmean( 3 ); +* +* var mu = accumulator(); +* // returns null +* +* mu = accumulator( 2.0 ); +* // returns 2.0 +* +* mu = accumulator( -5.0 ); +* // returns -1.5 +* +* mu = accumulator( NaN ); +* // returns -1.5 +* +* mu = accumulator( 3.0 ); +* // returns 0.0 +* +* mu = accumulator( 5.0 ); +* // returns 1.0 +* +* mu = accumulator( NaN ); +* // returns 1.0 +* +* mu = accumulator(); +* // returns 1.0 +*/ +declare function incrnanmmean( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/types/test.ts new file mode 100644 index 000000000000..ebb4a7699a70 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmean = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmean( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmmean( '5' ); // $ExpectError + incrnanmmean( true ); // $ExpectError + incrnanmmean( false ); // $ExpectError + incrnanmmean( null ); // $ExpectError + incrnanmmean( undefined ); // $ExpectError + incrnanmmean( [] ); // $ExpectError + incrnanmmean( {} ); // $ExpectError + incrnanmmean( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmmean(); // $ExpectError + incrnanmmean( 2, 5 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmean( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmean( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmean/examples/index.js new file mode 100644 index 000000000000..517931d9bc99 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/examples/index.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmean = require( './../lib' ); + +var accumulator; +var mu; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmean( 5 ); + +// For each simulated datum, update the moving mean... +console.log( '\nValue\tMean\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + mu = accumulator( v ); + console.log( '%s\t%s', v.toFixed( 4 ), ( mu === null ) ? NaN : mu.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmean/lib/index.js new file mode 100644 index 000000000000..96871322a682 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving arithmetic mean incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmean +* +* @example +* var incrnanmmean = require( '@stdlib/stats/incr/nanmmean' ); +* +* var accumulator = incrnanmmean( 3 ); +* +* var mu = accumulator(); +* // returns null +* +* mu = accumulator( 2.0 ); +* // returns 2.0 +* +* mu = accumulator( -5.0 ); +* // returns -1.5 +* +* mu = accumulator( NaN ); +* // returns -1.5 +* +* mu = accumulator( 3.0 ); +* // returns 0.0 +* +* mu = accumulator( 5.0 ); +* // returns 1.0 +* +* mu = accumulator( NaN ); +* // returns 1.0 +* +* mu = accumulator(); +* // returns 1.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmean/lib/main.js new file mode 100644 index 000000000000..6c3f5a2c3d39 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/lib/main.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmmean = require( '@stdlib/stats/incr/mmean' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmean( 3 ); +* +* var mu = accumulator(); +* // returns null +* +* mu = accumulator( 2.0 ); +* // returns 2.0 +* +* mu = accumulator( -5.0 ); +* // returns -1.5 +* +* mu = accumulator( NaN ); +* // returns -1.5 +* +* mu = accumulator( 3.0 ); +* // returns 0.0 +* +* mu = accumulator( 5.0 ); +* // returns 1.0 +* +* mu = accumulator( NaN ); +* // returns 1.0 +* +* mu = accumulator(); +* // returns 1.0 +*/ +function incrnanmmean( W ) { + var mmean = incrmmean( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated mean. If not provided a value, the accumulator function returns the current mean. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} mean or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return mmean(); + } + return mmean( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmean; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmean/package.json new file mode 100644 index 000000000000..6a3d32a383cc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nanmmean", + "version": "0.0.0", + "description": "Compute a moving arithmetic mean incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "central tendency", + "incremental", + "accumulator", + "moving mean", + "moving average", + "sliding window", + "sliding", + "nan", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmean/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmean/test/test.js new file mode 100644 index 000000000000..c3dbcda193a0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmean/test/test.js @@ -0,0 +1,130 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var incrnanmmean = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmean, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmean( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmmean( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving arithmetic mean incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 2.0, NaN, 4.0, 3.0, 4.0 ]; + N = data.length; + + acc = incrnanmmean( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + expected = [ 2.0, 2.5, 7.0/3.0, 7.0/3.0, 3.0, 3.0, 11.0/3.0 ]; + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, 3.0, NaN, 5.0 ]; + acc = incrnanmmean( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.strictEqual( acc(), 4.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmean( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if only NaN values have been provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmean( 3 ); + acc( NaN ); + acc( NaN ); + acc( NaN ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided NaN, the accumulator function ignores it and returns the previous result', function test( t ) { + var acc = incrnanmmean( 3 ); + t.strictEqual( acc( NaN ), null, 'returns expected value' ); + t.strictEqual( acc( 2.0 ), 2.0, 'returns expected value' ); + t.strictEqual( acc( NaN ), 2.0, 'returns expected value' ); + t.strictEqual( acc( NaN ), 2.0, 'returns expected value' ); + t.strictEqual( acc( 4.0 ), 3.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/README.md new file mode 100644 index 000000000000..ab1210776dce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/README.md @@ -0,0 +1,218 @@ + + +# incrnanmmeanstdev + +> Compute a moving [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][standard-deviation] incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [arithmetic mean][arithmetic-mean] is defined as + + + +```math +\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i +``` + + + + + +and the [corrected sample standard deviation][standard-deviation] is defined as + + + +```math +s = \sqrt{\frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmmeanstdev = require( '@stdlib/stats/incr/nanmmeanstdev' ); +``` + +#### incrnanmmeanstdev( \[out,] window ) + +Returns an accumulator function which incrementally computes a moving [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][standard-deviation], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [arithmetic mean][arithmetic-mean] and [corrected sample standard deviation][standard-deviation]. + +```javascript +var accumulator = incrnanmmeanstdev( 3 ); +``` + +By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var accumulator = incrnanmmeanstdev( new Float64Array( 2 ), 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values. + +```javascript +var accumulator = incrnanmmeanstdev( 3 ); + +var out = accumulator(); +// returns null + +// Fill the window... +out = accumulator( 2.0 ); // [2.0] +// returns [ 2.0, 0.0 ] + +out = accumulator( 1.0 ); // [2.0, 1.0] +// returns [ 1.5, ~0.71 ] + +out = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns [ 2.0, 1.0 ] + +out = accumulator( NaN ); // [2.0, 1.0, 3.0] +// returns [ 2.0, 1.0 ] + +// Window begins sliding... +out = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns [ -1.0, ~5.29 ] + +out = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns [ -3.0, ~5.29 ] + +out = accumulator(); +// returns [ -3.0, ~5.29 ] +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmmeanstdev = require( '@stdlib/stats/incr/nanmmeanstdev' ); + +var offset; +var acc; +var buf; +var out; +var ms; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmmeanstdev( out, 5 ) ); +} + +// Simulate data and update the moving sample means and standard deviations... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0*(j+1) ); + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tStDev' ); +for ( i = 0; i < N; i++ ) { + ms = acc[ i ](); + console.log( '%d\t%d', ms[ 0 ].toFixed( 3 ), ms[ 1 ].toFixed( 3 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean + +[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/benchmark/benchmark.js new file mode 100644 index 000000000000..81e30e2d301f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmmeanstdev = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmeanstdev( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmeanstdev( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i ); + if ( v.length !== 2 ) { + b.fail( 'should contain two elements' ); + } + } + b.toc(); + if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/img/equation_arithmetic_mean.svg new file mode 100644 index 000000000000..1a89a2bfb996 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/img/equation_arithmetic_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over upper W EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/img/equation_corrected_sample_standard_deviation.svg b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/img/equation_corrected_sample_standard_deviation.svg new file mode 100644 index 000000000000..dfe5a3d60cbb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/img/equation_corrected_sample_standard_deviation.svg @@ -0,0 +1,73 @@ + +s equals StartRoot StartFraction 1 Over upper W minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/repl.txt new file mode 100644 index 000000000000..8402f19a104c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/repl.txt @@ -0,0 +1,45 @@ + +{{alias}}( [out,] W ) + Returns an accumulator function which incrementally computes a moving + arithmetic mean and corrected sample standard deviation, ignoring `NaN` + values. + + The `W` parameter defines the number of values over which to compute the + moving arithmetic mean and corrected sample standard deviation. + + If provided a value, the accumulator function returns updated accumulated + values. If provided `NaN` or no value, the accumulator function returns the + current moving accumulated values. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + accumulated values are calculated from smaller sample sizes. Until the + window is full, each returned accumulated value is calculated from all + provided values. + + Parameters + ---------- + out: Array|TypedArray (optional) + Output array. + + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var v = accumulator() + null + > accumulator( 2.0 ); + > accumulator( NaN ); + > accumulator( -5.0 ); + > v = accumulator() + [ -1.5, ~4.95 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/types/index.d.ts new file mode 100644 index 000000000000..fc5436e50ad9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/types/index.d.ts @@ -0,0 +1,94 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; + +/** +* If provided a value, the accumulator function returns an updated moving arithmetic mean and corrected sample standard deviation. If provided NaN or no value, the accumulator function returns the current moving arithmetic mean and corrected sample standard deviation. +* +* @param x - input value +* @returns output array or null +*/ +type accumulator = ( x?: number ) => ArrayLike | null; + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean and corrected sample standard deviation, ignoring NaN values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving arithmetic mean and corrected sample standard deviation. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned moving arithmetic mean and corrected sample standard deviation are calculated from smaller sample sizes. Until the window is full, each returned moving arithmetic mean and corrected sample standard deviation is calculated from all provided values. +* +* @param out - output array +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var accumulator = incrnanmmeanstdev( new Float64Array( 2 ), 3 ); +* +* var mm = accumulator(); +* // returns null +*/ +declare function incrnanmmeanstdev( out: ArrayLike, window: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean and corrected sample standard deviation, ignoring NaN values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving arithmetic mean and corrected sample standard deviation. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned moving arithmetic mean and corrected sample standard deviation are calculated from smaller sample sizes. Until the window is full, each returned moving arithmetic mean and corrected sample standard deviation is calculated from all provided values. +* +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmeanstdev( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( NaN ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( -5.0 ); +* // returns [ -1.5, ~4.95 ] +* +* v = accumulator( 3.0 ); +* // returns [ 0.0, ~4.36 ] +* +* v = accumulator(); +* // returns [ 0.0, ~4.36 ] +*/ +declare function incrnanmmeanstdev( window: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmeanstdev; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/types/test.ts new file mode 100644 index 000000000000..31a177e354f9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/docs/types/test.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmeanstdev = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmeanstdev( 3 ); // $ExpectType accumulator + const out = [ 0.0, 0.0 ]; + incrnanmmeanstdev( out, 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided a last argument that is not a number... +{ + incrnanmmeanstdev( '5' ); // $ExpectError + incrnanmmeanstdev( true ); // $ExpectError + incrnanmmeanstdev( false ); // $ExpectError + incrnanmmeanstdev( null ); // $ExpectError + incrnanmmeanstdev( {} ); // $ExpectError + incrnanmmeanstdev( ( x: number ): number => x ); // $ExpectError + + const out = [ 0.0, 0.0 ]; + incrnanmmeanstdev( out, '5' ); // $ExpectError + incrnanmmeanstdev( out, true ); // $ExpectError + incrnanmmeanstdev( out, false ); // $ExpectError + incrnanmmeanstdev( out, null ); // $ExpectError + incrnanmmeanstdev( out, {} ); // $ExpectError + incrnanmmeanstdev( out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an output array that is not an array-like object of numbers... +{ + incrnanmmeanstdev( '5', 3 ); // $ExpectError + incrnanmmeanstdev( true, 3 ); // $ExpectError + incrnanmmeanstdev( false, 3 ); // $ExpectError + incrnanmmeanstdev( null, 3 ); // $ExpectError + incrnanmmeanstdev( {}, 3 ); // $ExpectError + incrnanmmeanstdev( ( x: number ): number => x, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmeanstdev( 3 ); + + acc(); // $ExpectType ArrayLike | null + acc( 3.14 ); // $ExpectType ArrayLike | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmeanstdev( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/examples/index.js new file mode 100644 index 000000000000..7f196ee2409d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/examples/index.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmmeanstdev = require( './../lib' ); + +var offset; +var acc; +var buf; +var out; +var ms; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmmeanstdev( out, 5 ) ); +} + +// Simulate data and update the moving sample means and standard deviations... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0*(j+1) ); + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tStDev' ); +for ( i = 0; i < N; i++ ) { + ms = acc[ i ](); + console.log( '%d\t%d', ms[ 0 ].toFixed( 3 ), ms[ 1 ].toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/lib/index.js new file mode 100644 index 000000000000..57e1144136b4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving arithmetic mean and corrected sample standard deviation incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmeanstdev +* +* @example +* var incrnanmmeanstdev = require( '@stdlib/stats/incr/nanmmeanstdev' ); +* +* var accumulator = incrnanmmeanstdev( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( NaN ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( -5.0 ); +* // returns [ -1.5, ~4.95 ] +* +* v = accumulator( 3.0 ); +* // returns [ 0.0, ~4.36 ] +* +* v = accumulator(); +* // returns [ 0.0, ~4.36 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/lib/main.js new file mode 100644 index 000000000000..fab46dea0a74 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/lib/main.js @@ -0,0 +1,87 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmmeanstdev = require( '@stdlib/stats/incr/mmeanstdev' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean and corrected sample standard deviation, ignoring `NaN` values. +* +* @param {Collection} [out] - output array +* @param {PositiveInteger} window - window size +* @throws {TypeError} output argument must be array-like +* @throws {TypeError} window size must be a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmeanstdev( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( NaN ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( -5.0 ); +* // returns [ -1.5, ~4.95 ] +* +* v = accumulator( 3.0 ); +* // returns [ 0.0, ~4.36 ] +* +* v = accumulator(); +* // returns [ 0.0, ~4.36 ] +*/ +function incrnanmmeanstdev( out, window ) { + var mmeanstdev; + + if ( arguments.length === 1 ) { + mmeanstdev = incrmmeanstdev( out ); + } else { + mmeanstdev = incrmmeanstdev( out, window ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns updated accumulated values. If provided `NaN` or no value, the accumulator function returns the current accumulated values. + * + * @private + * @param {number} [x] - input value + * @returns {(ArrayLikeObject|null)} output array or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return mmeanstdev(); + } + return mmeanstdev( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmeanstdev; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/package.json new file mode 100644 index 000000000000..0910f60c20ad --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/package.json @@ -0,0 +1,80 @@ +{ + "name": "@stdlib/stats/incr/nanmmeanstdev", + "version": "0.0.0", + "description": "Compute a moving arithmetic mean and corrected sample standard deviation incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "central tendency", + "moving mean", + "moving average", + "variance", + "sample", + "sample variance", + "unbiased", + "stdev", + "standard", + "deviation", + "dispersion", + "incremental", + "accumulator", + "sliding window", + "sliding", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/test/test.js new file mode 100644 index 000000000000..ee1dbc1bf3f4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanstdev/test/test.js @@ -0,0 +1,437 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmmeanstdev = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmeanstdev, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmeanstdev( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmeanstdev( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (output)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmeanstdev( [ 0.0, 0.0 ], value ); + }; + } +}); + +tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + NaN, + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmeanstdev( value, 3 ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmmeanstdev( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (output)', function test( t ) { + t.strictEqual( typeof incrnanmmeanstdev( [ 0.0, 0.0 ], 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving arithmetic mean and corrected sample standard deviation incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ]; + N = data.length; + + acc = incrnanmmeanstdev( 3 ); + + expected = [ + [ 2.0, 0.0 ], + [ 2.5, sqrt( 0.5 ) ], + [ 3.0, sqrt( 1.0 ) ], + [ 2.0, sqrt( 7.0 ) ], + [ 2.0, sqrt( 7.0 ) ], + [ 1.0, sqrt( 4.0 ) ] + ]; + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the accumulator function computes a moving arithmetic mean and corrected sample standard deviation incrementally (output)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var out; + var N; + var i; + + data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ]; + N = data.length; + + out = [ 0.0, 0.0 ]; + acc = incrnanmmeanstdev( out, 3 ); + + expected = [ + [ 2.0, 0.0 ], + [ 2.5, sqrt( 0.5 ) ], + [ 3.0, sqrt( 1.0 ) ], + [ 2.0, sqrt( 7.0 ) ], + [ 2.0, sqrt( 7.0 ) ], + [ 1.0, sqrt( 4.0 ) ] + ]; + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current arithmetic mean and corrected sample standard deviation', function test( t ) { + var expected; + var actual; + var delta; + var data; + var tol; + var acc; + var i; + + data = [ 2.0, 3.0, 10.0 ]; + acc = incrnanmmeanstdev( 3 ); + for ( i = 0; i < data.length-1; i++ ) { + acc( data[ i ] ); + } + t.deepEqual( acc(), [ 2.5, sqrt( 0.5 ) ], 'returns expected value' ); + + acc( data[ data.length-1 ] ); + + expected = [ 5.0, sqrt( 19.0 ) ]; + actual = acc(); + + t.strictEqual( actual[ 0 ], expected[ 0 ], 'returns expected value' ); + + delta = abs( actual[ 1 ] - expected[ 1 ] ); + tol = EPS * expected[ 1 ]; + t.strictEqual( delta < tol, true, 'expected: '+expected[ 1 ]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmeanstdev( 3 ); + t.strictEqual( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if only one datum has been provided, the accumulator function returns `0` for the sample standard deviation', function test( t ) { + var acc = incrnanmmeanstdev( 3 ); + var v = acc( 2.0 ); + t.strictEqual( v[ 0 ], 2.0, 'returns expected value' ); + t.strictEqual( v[ 1 ], 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if the window size is `1`, the accumulator functions always returns `0` for the sample standard deviation', function test( t ) { + var acc; + var out; + var v; + var i; + + acc = incrnanmmeanstdev( 1 ); + for ( i = 0; i < 100; i++ ) { + v = randu() * 100.0; + out = acc( v ); + t.strictEqual( out[ 0 ], v, 'returns expected value' ); + t.strictEqual( out[ 1 ], 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulator returns current values or null', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmeanstdev( 3 ); + + data = [ + NaN, + 3.14, // 3.14 + 3.14, // 3.14, 3.14 + NaN, // 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 + 3.14 // 3.14, 3.14, 3.14 + ]; + expected = [ + null, + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ] + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( i === 0 && isnan( data[ i ] ) ) { + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + + v = acc(); + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + } else { + if ( isnan( data[ i ] ) ) { + t.strictEqual( isnan( v[ 0 ] ), false, 'returns expected value for window '+i ); + t.strictEqual( isnan( v[ 1 ] ), false, 'returns expected value for window '+i ); + } + + t.strictEqual( v[ 0 ], expected[ i ][ 0 ], 'returns expected value for window '+i ); + t.strictEqual( v[ 1 ], expected[ i ][ 1 ], 'returns expected value for window '+i ); + + v = acc(); + t.strictEqual( v[ 0 ], expected[ i ][ 0 ], 'returns expected value for window '+i ); + t.strictEqual( v[ 1 ], expected[ i ][ 1 ], 'returns expected value for window '+i ); + } + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulator returns current values or null (W=1)', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmeanstdev( 1 ); + + data = [ + NaN, + 3.14, + 3.14, + NaN, + 3.14, + 3.14, + 3.14, + NaN, + 3.14, + 3.14, + 3.14, + NaN, + 3.14, + 3.14, + NaN, + NaN, + NaN, + NaN, + 3.14 + ]; + expected = [ + null, + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ], + [ 3.14, 0.0 ] + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( i === 0 && isnan( data[ i ] ) ) { + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + + v = acc(); + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + } else { + if ( isnan( data[ i ] ) ) { + t.strictEqual( isnan( v[ 0 ] ), false, 'returns expected value for window '+i ); + t.strictEqual( isnan( v[ 1 ] ), false, 'returns expected value for window '+i ); + } + + t.strictEqual( v[ 0 ], expected[ i ][ 0 ], 'returns expected value for window '+i ); + t.strictEqual( v[ 1 ], expected[ i ][ 1 ], 'returns expected value for window '+i ); + + v = acc(); + t.strictEqual( v[ 0 ], expected[ i ][ 0 ], 'returns expected value for window '+i ); + t.strictEqual( v[ 1 ], expected[ i ][ 1 ], 'returns expected value for window '+i ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/README.md new file mode 100644 index 000000000000..ae24a208892e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/README.md @@ -0,0 +1,218 @@ + + +# incrnanmmeanvar + +> Compute a moving [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance] incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [arithmetic mean][arithmetic-mean] is defined as + + + +```math +\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i +``` + + + + + +and the [unbiased sample variance][sample-variance] is defined as + + + +```math +s^2 = \frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2 +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmmeanvar = require( '@stdlib/stats/incr/nanmmeanvar' ); +``` + +#### incrnanmmeanvar( \[out,] window ) + +Returns an accumulator function which incrementally computes a moving [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance]. + +```javascript +var accumulator = incrnanmmeanvar( 3 ); +``` + +By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var accumulator = incrnanmmeanvar( new Float64Array( 2 ), 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values. + +```javascript +var accumulator = incrnanmmeanvar( 3 ); + +var out = accumulator(); +// returns null + +// Fill the window... +out = accumulator( 2.0 ); // [2.0] +// returns [ 2.0, 0.0 ] + +out = accumulator( NaN ); // [2.0] +// returns [ 2.0, 0.0 ] + +out = accumulator( 1.0 ); // [2.0, 1.0] +// returns [ 1.5, 0.5 ] + +out = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns [ 2.0, 1.0 ] + +// Window begins sliding... +out = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns [ -1.0, 28.0 ] + +out = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns [ -3.0, 28.0 ] + +out = accumulator(); +// returns [ -3.0, 28.0 ] +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmmeanvar = require( '@stdlib/stats/incr/nanmmeanvar' ); + +var offset; +var acc; +var buf; +var out; +var mv; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmmeanvar( out, 5 ) ); +} + +// Simulate data and update the moving sample means and variances... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0*(j+1) ); + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tVariance' ); +for ( i = 0; i < N; i++ ) { + mv = acc[ i ](); + console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean + +[sample-variance]: https://en.wikipedia.org/wiki/Variance + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/benchmark/benchmark.js new file mode 100644 index 000000000000..af47d929f77a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmmeanvar = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmeanvar( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmeanvar( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i ); + if ( v.length !== 2 ) { + b.fail( 'should contain two elements' ); + } + } + b.toc(); + if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/img/equation_arithmetic_mean.svg new file mode 100644 index 000000000000..1a89a2bfb996 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/img/equation_arithmetic_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over upper W EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/img/equation_unbiased_sample_variance.svg b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/img/equation_unbiased_sample_variance.svg new file mode 100644 index 000000000000..f4722f986a70 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/img/equation_unbiased_sample_variance.svg @@ -0,0 +1,61 @@ + +s squared equals StartFraction 1 Over upper W minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/repl.txt new file mode 100644 index 000000000000..6ff55f9c214b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/repl.txt @@ -0,0 +1,44 @@ + +{{alias}}( [out,] W ) + Returns an accumulator function which incrementally computes a moving + arithmetic mean and unbiased sample variance, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving arithmetic mean and unbiased sample variance. + + If provided a value, the accumulator function returns updated accumulated + values. If provided `NaN` or no value, the accumulator function returns the + current moving accumulated values. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + accumulated values are calculated from smaller sample sizes. Until the + window is full, each returned accumulated value is calculated from all + provided values. + + Parameters + ---------- + out: Array|TypedArray (optional) + Output array. + + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var v = accumulator() + null + > accumulator( 2.0 ); + > accumulator( NaN ); + > accumulator( -5.0 ); + > v = accumulator() + [ -1.5, 24.5 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/types/index.d.ts new file mode 100644 index 000000000000..54ca15f8b576 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/types/index.d.ts @@ -0,0 +1,94 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; + +/** +* If provided a value, the accumulator function returns an updated moving arithmetic mean and unbiased sample variance. If provided `NaN` or no value, the accumulator function returns the current moving arithmetic mean and unbiased sample variance. +* +* @param x - input value +* @returns output array or null +*/ +type accumulator = ( x?: number ) => ArrayLike | null; + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean and unbiased sample variance, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving arithmetic mean and unbiased sample variance. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned moving arithmetic mean and unbiased sample variance are calculated from smaller sample sizes. Until the window is full, each returned moving arithmetic mean and unbiased sample variance is calculated from all provided values. +* +* @param out - output array +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var accumulator = incrnanmmeanvar( new Float64Array( 2 ), 3 ); +* +* var mv = accumulator(); +* // returns null +*/ +declare function incrnanmmeanvar( out: ArrayLike, window: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean and unbiased sample variance, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving arithmetic mean and unbiased sample variance. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned moving arithmetic mean and unbiased sample variance are calculated from smaller sample sizes. Until the window is full, each returned moving arithmetic mean and unbiased sample variance is calculated from all provided values. +* +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmeanvar( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( NaN ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( -5.0 ); +* // returns [ -1.5, 24.5 ] +* +* v = accumulator( 3.0 ); +* // returns [ 0.0, 19.0 ] +* +* v = accumulator(); +* // returns [ 0.0, 19.0 ] +*/ +declare function incrnanmmeanvar( window: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmeanvar; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/types/test.ts new file mode 100644 index 000000000000..a623f157c2da --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/docs/types/test.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmeanvar = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmeanvar( 3 ); // $ExpectType accumulator + const out = [ 0.0, 0.0 ]; + incrnanmmeanvar( out, 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided a last argument that is not a number... +{ + incrnanmmeanvar( '5' ); // $ExpectError + incrnanmmeanvar( true ); // $ExpectError + incrnanmmeanvar( false ); // $ExpectError + incrnanmmeanvar( null ); // $ExpectError + incrnanmmeanvar( {} ); // $ExpectError + incrnanmmeanvar( ( x: number ): number => x ); // $ExpectError + + const out = [ 0.0, 0.0 ]; + incrnanmmeanvar( out, '5' ); // $ExpectError + incrnanmmeanvar( out, true ); // $ExpectError + incrnanmmeanvar( out, false ); // $ExpectError + incrnanmmeanvar( out, null ); // $ExpectError + incrnanmmeanvar( out, {} ); // $ExpectError + incrnanmmeanvar( out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an output array which is not an array-like object of numbers... +{ + incrnanmmeanvar( '5', 3 ); // $ExpectError + incrnanmmeanvar( true, 3 ); // $ExpectError + incrnanmmeanvar( false, 3 ); // $ExpectError + incrnanmmeanvar( null, 3 ); // $ExpectError + incrnanmmeanvar( {}, 3 ); // $ExpectError + incrnanmmeanvar( ( x: number ): number => x, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmeanvar( 3 ); + + acc(); // $ExpectType ArrayLike | null + acc( 3.14 ); // $ExpectType ArrayLike | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmeanvar( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/examples/index.js new file mode 100644 index 000000000000..efb26f8156c4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/examples/index.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var Float64Array = require( '@stdlib/array/float64' ); +var ArrayBuffer = require( '@stdlib/array/buffer' ); +var incrnanmmeanvar = require( './../lib' ); + +var offset; +var acc; +var buf; +var out; +var mv; +var N; +var v; +var i; +var j; + +// Define the number of accumulators: +N = 5; + +// Create an array buffer for storing accumulator output: +buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element + +// Initialize accumulators: +acc = []; +for ( i = 0; i < N; i++ ) { + // Compute the byte offset: + offset = i * 2 * 8; // stride=2, bytes_per_element=8 + + // Create a new view for storing accumulated values: + out = new Float64Array( buf, offset, 2 ); + + // Initialize an accumulator which will write results to the view: + acc.push( incrnanmmeanvar( out, 5 ) ); +} + +// Simulate data and update the moving sample means and variances... +for ( i = 0; i < 100; i++ ) { + for ( j = 0; j < N; j++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0*(j+1) ); + acc[ j ]( v ); + } +} + +// Print the final results: +console.log( 'Mean\tVariance' ); +for ( i = 0; i < N; i++ ) { + mv = acc[ i ](); + console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/lib/index.js new file mode 100644 index 000000000000..1002a765a4ab --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving arithmetic mean and unbiased sample variance incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmeanvar +* +* @example +* var incrnanmmeanvar = require( '@stdlib/stats/incr/nanmmeanvar' ); +* +* var accumulator = incrnanmmeanvar( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( NaN ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( -5.0 ); +* // returns [ -1.5, 24.5 ] +* +* v = accumulator( 3.0 ); +* // returns [ 0.0, 19.0 ] +* +* v = accumulator(); +* // returns [ 0.0, 19.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/lib/main.js new file mode 100644 index 000000000000..e5d2fbeced8e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/lib/main.js @@ -0,0 +1,86 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmmeanvar = require( '@stdlib/stats/incr/mmeanvar' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving arithmetic mean and unbiased sample variance, ignoring `NaN` values. +* +* @param {Collection} [out] - output array +* @param {PositiveInteger} window - window size +* @throws {TypeError} output argument must be array-like +* @throws {TypeError} window size must be a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmeanvar( 3 ); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( NaN ); +* // returns [ 2.0, 0.0 ] +* +* v = accumulator( -5.0 ); +* // returns [ -1.5, 24.5 ] +* +* v = accumulator( 3.0 ); +* // returns [ 0.0, 19.0 ] +* +* v = accumulator(); +* // returns [ 0.0, 19.0 ] +*/ +function incrnanmmeanvar( out, window ) { + var mmeanvar; + if ( arguments.length > 1 ) { + mmeanvar = incrmmeanvar( out, window ); + } else { + mmeanvar = incrmmeanvar( out ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns updated accumulated values. If provided `NaN` or no value, the accumulator function returns the current accumulated values. + * + * @private + * @param {number} [x] - input value + * @returns {(ArrayLikeObject|null)} output array or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return mmeanvar(); + } + return mmeanvar( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmeanvar; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/package.json new file mode 100644 index 000000000000..b1b33a35f1f8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/package.json @@ -0,0 +1,80 @@ +{ + "name": "@stdlib/stats/incr/nanmmeanvar", + "version": "0.0.0", + "description": "Compute a moving arithmetic mean and unbiased sample variance incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "central tendency", + "moving mean", + "moving average", + "variance", + "sample", + "sample variance", + "unbiased", + "stdev", + "standard", + "deviation", + "dispersion", + "incremental", + "accumulator", + "sliding window", + "sliding", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/test/test.js new file mode 100644 index 000000000000..3da5bae7628d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmeanvar/test/test.js @@ -0,0 +1,306 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmmeanvar = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmeanvar, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmeanvar( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (output)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmeanvar( [ 0.0, 0.0 ], value ); + }; + } +}); + +tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + NaN, + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmeanvar( value, 3 ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmmeanvar( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (output)', function test( t ) { + t.strictEqual( typeof incrnanmmeanvar( [ 0.0, 0.0 ], 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving arithmetic mean and unbiased sample variance incrementally, ignoring `NaN` values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 4.0, NaN, -1.0, 3.0, 1.0 ]; + N = data.length; + + acc = incrnanmmeanvar( 3 ); + + expected = [ + [ 2.0, 0.0 ], + [ 2.0, 0.0 ], + [ 2.5, 0.5 ], + [ 3.0, 1.0 ], + [ 3.0, 1.0 ], + [ 2.0, 7.0 ], + [ 2.0, 7.0 ], + [ 1.0, 4.0 ] + ]; + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'the accumulator function computes a moving arithmetic mean and unbiased sample variance incrementally, ignoring `NaN` values (output)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var out; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 4.0, NaN, -1.0, 3.0, 1.0 ]; + N = data.length; + + out = [ 0.0, 0.0 ]; + acc = incrnanmmeanvar( out, 3 ); + + expected = [ + [ 2.0, 0.0 ], + [ 2.0, 0.0 ], + [ 2.5, 0.5 ], + [ 3.0, 1.0 ], + [ 3.0, 1.0 ], + [ 2.0, 7.0 ], + [ 2.0, 7.0 ], + [ 1.0, 4.0 ] + ]; + for ( i = 0; i < N; i++ ) { + actual = acc( data[ i ] ); + t.strictEqual( actual, out, 'returns expected value' ); + t.deepEqual( actual, expected[ i ], 'returns expected value' ); + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current accumulated values', function test( t ) { + var expected; + var actual; + var delta; + var data; + var tol; + var acc; + var i; + + data = [ 2.0, NaN, 3.0, 10.0 ]; + acc = incrnanmmeanvar( 3 ); + for ( i = 0; i < data.length-1; i++ ) { + acc( data[ i ] ); + } + t.deepEqual( acc(), [ 2.5, 0.5 ], 'returns expected value' ); + + acc( data[ data.length-1 ] ); + + expected = [ 5.0, 19.0 ]; + actual = acc(); + + t.strictEqual( actual[ 0 ], expected[ 0 ], 'returns expected value' ); + + delta = abs( actual[ 1 ] - expected[ 1 ] ); + tol = EPS * expected[ 1 ]; + t.strictEqual( delta < tol, true, 'expected: '+expected[ 1 ]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmeanvar( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if only `NaN` values have been provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmeanvar( 3 ); + acc( NaN ); + acc( NaN ); + acc( NaN ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided `NaN`, the accumulator function ignores the value and returns the previous accumulated values', function test( t ) { + var acc = incrnanmmeanvar( 3 ); + t.strictEqual( acc( NaN ), null, 'returns expected value' ); + t.deepEqual( acc( 2.0 ), [ 2.0, 0.0 ], 'returns expected value' ); + t.deepEqual( acc( NaN ), [ 2.0, 0.0 ], 'returns expected value' ); + t.deepEqual( acc( NaN ), [ 2.0, 0.0 ], 'returns expected value' ); + t.deepEqual( acc( 4.0 ), [ 3.0, 2.0 ], 'returns expected value' ); + t.end(); +}); + +tape( 'if only one datum has been provided, the accumulator function returns `0` for the sample variance', function test( t ) { + var acc = incrnanmmeanvar( 3 ); + var v = acc( 2.0 ); + t.strictEqual( v[ 0 ], 2.0, 'returns expected value' ); + t.strictEqual( v[ 1 ], 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if the window size is `1`, the accumulator function always returns `0` for the sample variance', function test( t ) { + var acc; + var out; + var v; + var i; + + acc = incrnanmmeanvar( 1 ); + for ( i = 0; i < 100; i++ ) { + v = randu() * 100.0; + out = acc( v ); + t.strictEqual( out[ 0 ], v, 'returns expected value' ); + t.strictEqual( out[ 1 ], 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'if the window size is `1`, the accumulator function ignores `NaN` values and returns the previous value and `0` for the sample variance', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmeanvar( 1 ); + + data = [ NaN, 7.2, NaN, 12.8, NaN, NaN, 4.6, NaN, 9.9 ]; + expected = [ + null, + [ 7.2, 0.0 ], + [ 7.2, 0.0 ], + [ 12.8, 0.0 ], + [ 12.8, 0.0 ], + [ 12.8, 0.0 ], + [ 4.6, 0.0 ], + [ 4.6, 0.0 ], + [ 9.9, 0.0 ] + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.deepEqual( v, expected[ i ], 'returns expected value' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/README.md new file mode 100644 index 000000000000..da3d662e1b95 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/README.md @@ -0,0 +1,150 @@ + + +# incrnanmmidrange + +> Compute a moving [mid-range][mid-range] incrementally, ignoring `NaN` values. + +
+ +The [**mid-range**][mid-range], or **mid-extreme**, is the arithmetic mean of maximum and minimum values. Accordingly, the [mid-range][mid-range] is the midpoint of the [range][range] and a measure of central tendency. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmmidrange = require( '@stdlib/stats/incr/nanmmidrange' ); +``` + +#### incrnanmmidrange( window ) + +Returns an accumulator `function` which incrementally computes a moving [mid-range][mid-range], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [mid-range][mid-range]. + +```javascript +var accumulator = incrnanmmidrange( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated [mid-range][mid-range]. If not provided an input value `x`, the accumulator function returns the current [mid-range][mid-range]. + +```javascript +var accumulator = incrnanmmidrange( 3 ); + +var mr = accumulator(); +// returns null + +// Fill the window... +mr = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +mr = accumulator( 1.0 ); // [2.0, 1.0] +// returns 1.5 + +mr = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns 2.0 + +// Window begins sliding... +mr = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns -2.0 + +mr = accumulator( NaN ); // [1.0, 3.0, -7.0] +// returns -2.0 + +mr = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns -2.0 + +mr = accumulator(); +// returns -2.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmidrange = require( '@stdlib/stats/incr/nanmmidrange' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmidrange( 5 ); + +// For each simulated datum, update the moving mid-range... +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[range]: https://en.wikipedia.org/wiki/Range_%28statistics%29 + +[mid-range]: https://en.wikipedia.org/wiki/Mid-range + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/benchmark/benchmark.js new file mode 100644 index 000000000000..679c7d381483 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnanmmidrange = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmidrange( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmidrange( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/repl.txt new file mode 100644 index 000000000000..a1a05c76c224 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/repl.txt @@ -0,0 +1,51 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving mid- + range, ignoring `NaN` values. + + The mid-range is the arithmetic mean of maximum and minimum values. + Accordingly, the mid-range is the midpoint of the range and a measure of + central tendency. + + The `W` parameter defines the number of values over which to compute + the moving mid-range. + + If provided a value, the accumulator function returns an updated moving mid- + range. If not provided a value, the accumulator function returns the current + moving mid-range. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var mr = accumulator() + null + > mr = accumulator( 2.0 ) + 2.0 + > mr = accumulator( -5.0 ) + -1.5 + > mr = accumulator( 3.0 ) + -1.0 + > mr = accumulator( 5.0 ) + 0.0 + > mr = accumulator( NaN ) + 0.0 + > mr = accumulator() + 0.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/types/index.d.ts new file mode 100644 index 000000000000..ba735ae4e094 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/types/index.d.ts @@ -0,0 +1,76 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated mid-range; otherwise, returns the current mid-range. +* +* ## Notes +* +* - The mid-range is the arithmetic mean of maximum and minimum values. Accordingly, the mid-range is the midpoint of the range and a measure of central tendency. +* +* @param x - value +* @returns mid-range +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving mid-range, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving mid-range. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmidrange( 3 ); +* +* var mr = accumulator(); +* // returns null +* +* mr = accumulator( 2.0 ); +* // returns 2.0 +* +* mr = accumulator( -5.0 ); +* // returns -1.5 +* +* mr = accumulator( 3.0 ); +* // returns -1.0 +* +* mr = accumulator( 5.0 ); +* // returns 0.0 +* +* mr = accumulator( NaN ); +* // returns 0.0 +* +* mr = accumulator(); +* // returns 0.0 +*/ +declare function incrnanmmidrange( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmidrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/types/test.ts new file mode 100644 index 000000000000..19f3665ad227 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/docs/types/test.ts @@ -0,0 +1,68 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmidrange = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmidrange( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmmidrange( '5' ); // $ExpectError + incrnanmmidrange( true ); // $ExpectError + incrnanmmidrange( false ); // $ExpectError + incrnanmmidrange( null ); // $ExpectError + incrnanmmidrange( undefined ); // $ExpectError + incrnanmmidrange( [] ); // $ExpectError + incrnanmmidrange( {} ); // $ExpectError + incrnanmmidrange( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmmidrange(); // $ExpectError + incrnanmmidrange( 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmidrange( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null + acc( 5 ); // $ExpectType number | null + acc( -2 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmidrange( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/examples/index.js new file mode 100644 index 000000000000..a6f4bf0699b2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/examples/index.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmidrange = require( './../lib' ); + +var accumulator; +var mr; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmidrange( 5 ); + +// For each simulated datum, update the moving mid-range... +console.log( '\nValue\tMid-Range\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + mr = accumulator( v ); + console.log( '%s\t%s', v.toFixed( 4 ), ( mr === null ) ? NaN : mr.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/lib/index.js new file mode 100644 index 000000000000..e46c2a8332e5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving mid-range incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmidrange +* +* @example +* var incrnanmmidrange = require( '@stdlib/stats/incr/nanmmidrange' ); +* +* var accumulator = incrnanmmidrange( 3 ); +* +* var mr = accumulator(); +* // returns null +* +* mr = accumulator( 2.0 ); +* // returns 2.0 +* +* mr = accumulator( -5.0 ); +* // returns -1.5 +* +* mr = accumulator( 3.0 ); +* // returns -1.0 +* +* mr = accumulator( 5.0 ); +* // returns 0.0 +* +* mr = accumulator( NaN ); +* // returns 0.0 +* +* mr = accumulator(); +* // returns 0.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/lib/main.js new file mode 100644 index 000000000000..65fff749e2fe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/lib/main.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmmidrange = require( '@stdlib/stats/incr/mmidrange' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving mid-range, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmidrange( 3 ); +* +* var mr = accumulator(); +* // returns null +* +* mr = accumulator( 2.0 ); +* // returns 2.0 +* +* mr = accumulator( -5.0 ); +* // returns -1.5 +* +* mr = accumulator( 3.0 ); +* // returns -1.0 +* +* mr = accumulator( 5.0 ); +* // returns 0.0 +* +* mr = accumulator( NaN ); +* // returns 0.0 +* +* mr = accumulator(); +* // returns 0.0 +*/ +function incrnanmmidrange( W ) { + var mmidrange = incrmmidrange( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated mid-range. If not provided a value, the accumulator function returns the current mid-range. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} mid-range or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return mmidrange(); + } + return mmidrange( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmidrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/package.json new file mode 100644 index 000000000000..6462024b48de --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/stats/incr/nanmmidrange", + "version": "0.0.0", + "description": "Compute a moving mid-range incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "minimum", + "min", + "mid", + "range", + "mid-range", + "mid-extreme", + "mean", + "central tendency", + "incremental", + "accumulator", + "sliding window", + "sliding", + "nan", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmidrange/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/test/test.js new file mode 100644 index 000000000000..0c74e55ec21c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmidrange/test/test.js @@ -0,0 +1,389 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var incrnanmmidrange = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmidrange, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmidrange( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmmidrange( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving mid-range incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 2.0, 4.0, 3.0, NaN, 4.0, NaN, 2.0, 2.0, 2.0, NaN, 1.0, 0.0, 4.0, -1.0 ]; + N = data.length; + + acc = incrnanmmidrange( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + expected = [ + 2.0, + 2.5, + 2.5, + 3.0, + 3.0, + 3.0, + 3.5, + 3.5, + 3.0, + 3.0, + 2.0, + 2.0, + 1.5, + 1.0, + 2.0, + 1.5 + ]; + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mid-range', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, 3.0, 5.0, 4.0 ]; + acc = incrnanmmidrange( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 4.5, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmidrange( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if only NaN values have been provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmidrange( 3 ); + acc( NaN ); + acc( NaN ); + acc( NaN ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if provided NaN, the accumulator function ignores it and returns the previous result', function test( t ) { + var acc = incrnanmmidrange( 3 ); + t.strictEqual( acc( NaN ), null, 'returns expected value' ); + t.strictEqual( acc( 2.0 ), 2.0, 'returns expected value' ); + t.strictEqual( acc( NaN ), 2.0, 'returns expected value' ); + t.strictEqual( acc( NaN ), 2.0, 'returns expected value' ); + t.strictEqual( acc( 4.0 ), 3.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmidrange( 3 ); + + data = [ + 0.0, // 0 => min: 0.0, max: 0.0 (0) + -0.0, // 0, -0 => min: -0.0, max: 0.0 (1) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (2) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (3) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (4) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (5) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (6) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (7) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (8) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (9) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (10) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (11) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (12) + + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (13) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (14) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (15) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (16) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (17) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (18) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (19) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (20) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (21) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (22) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (23) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (24) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (25) + + // Case 1: out: -0, in: +0, cnt: 1 + 3.14, // 0, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 2: out: +0, in: -0, cnt: 1 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 3: out: -0, in: -0, cnt: 1 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 4: out: -0, in: +0, cnt: 2 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + -0.0, // -0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 5: out: +0, in: +0, cnt: 1 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 6: out: +0, in: -0, cnt: 2 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + -0.0, // 0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 7: out: +0, in: +0, cnt: 2 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 0.0, // 0, 3.14, 0 => min: 0.0, max: 3.14 + 0.0, // 3.14, 0, 0 => min: 0.0, max: 3.14 + + // Reset: + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 + + // Case 8: out: -0, in: +0, cnt: 1 + -3.14, // 0, -0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 9: out: +0, in: -0, cnt: 1 + -3.14, // -3.14, 0, 3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 10: out: -0, in: -0, cnt: 1 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -3.14, // -0, -3.14, -3.14 => min: -3.14, max: -0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 11: out: -0, in: +0, cnt: 2 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -0.0, // -0, -3.14, -0 => min: -3.14, max: -0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 12: out: +0, in: +0, cnt: 1 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 13: out: +0, in: -0, cnt: 2 + -3.14, // -3.14, 0, -3.14 => min: -3.14, max: 0.0 + -0.0, // 0, -3.14, -0 => min: -3.14, max: 0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 14: out: +0, in: +0, cnt: 2 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + 0.0, // -3.14, 0, 0 => min: -3.14, max: 0.0 + + // Reset: + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 + + // Case 15: out: +0, in: -0, cnt: 2 + -3.14, // 0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + -0.0 // -3.14, 0, -0 => min: -3.14, max: 0.0 + ]; + expected = [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + + // Case 1: + 1.57, + 1.57, + 1.57, + + // Case 2: + 1.57, + 1.57, + 1.57, + + // Case 3: + 1.57, + 1.57, + 1.57, + + // Case 4: + 1.57, + 1.57, + 1.57, + + // Case 5: + 1.57, + 1.57, + 1.57, + + // Case 6: + 1.57, + 1.57, + 1.57, + + // Case 7: + 1.57, + 1.57, + 1.57, + + // Reset: + 0.0, + + // Case 8: + -1.57, + -1.57, + -1.57, + + // Case 9: + -1.57, + -1.57, + -1.57, + + // Case 10: + -1.57, + -1.57, + -1.57, + + // Case 11: + -1.57, + -1.57, + -1.57, + + // Case 12: + -1.57, + -1.57, + -1.57, + + // Case 13: + -1.57, + -1.57, + -1.57, + + // Case 14: + -1.57, + -1.57, + -1.57, + + // Reset: + 0.0, + + // Case 15: + -1.57, + -1.57, + -1.57 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( expected[ i ] === 0.0 ) { + t.equal( isNegativeZero( v ), isNegativeZero( expected[ i ] ), 'returns expected value for window '+i ); + } else { + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmin/README.md new file mode 100644 index 000000000000..340f2a0fb95e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/README.md @@ -0,0 +1,137 @@ + + +# incrnanmmin + +> Compute a moving minimum value incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanmmin = require( '@stdlib/stats/incr/nanmmin' ); +``` + +#### incrnanmmin( window ) + +Returns an accumulator `function` which incrementally computes a moving minimum value. The `window` parameter defines the number of values over which to compute the moving minimum, ignoring `NaN` values. + +```javascript +var accumulator = incrnanmmin( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated minimum value. If not provided an input value `x`, the accumulator function returns the current minimum value. + +```javascript +var accumulator = incrnanmmin( 3 ); + +var m = accumulator(); +// returns null + +// Fill the window... +m = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +m = accumulator( 1.0 ); // [2.0, 1.0] +// returns 1.0 + +m = accumulator( NaN ); +// returns 1.0 + +m = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns 1.0 + +// Window begins sliding... +m = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns -7.0 + +m = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns -7.0 + +m = accumulator(); +// returns -7.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmmin = require( '@stdlib/stats/incr/nanmmin' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmin( 5 ); + +// For each simulated datum, update the moving minimum... +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.1 ) ? NaN : randu() * 100.0; + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmin/benchmark/benchmark.js new file mode 100644 index 000000000000..e34ef5dc8264 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnanmmin = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmin( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmin( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/repl.txt new file mode 100644 index 000000000000..8535a6724eb1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/repl.txt @@ -0,0 +1,47 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + minimum value, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving minimum. + + If provided a value, the accumulator function returns an updated moving + minimum. If not provided a value, the accumulator function returns the + current moving minimum. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var m = accumulator() + null + > m = accumulator( 2.0 ) + 2.0 + > m = accumulator( -5.0 ) + -5.0 + > m = accumulator( NaN ) + -5.0 + > m = accumulator( 3.0 ) + -5.0 + > m = accumulator( 5.0 ) + -5.0 + > m = accumulator() + -5.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/types/index.d.ts new file mode 100644 index 000000000000..2082bb3df042 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/types/index.d.ts @@ -0,0 +1,72 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated minimum value; otherwise, returns the current minimum value. +* +* @param x - value +* @returns minimum value +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving minimum value, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving minimum. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmin( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns -5.0 +* +* m = accumulator( 3.0 ); +* // returns -5.0 +* +* m = accumulator( 5.0 ); +* // returns -5.0 +* +* m = accumulator(); +* // returns -5.0 +*/ +declare function incrnanmmin( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmin; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/types/test.ts new file mode 100644 index 000000000000..6b76b0fb95d4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmin = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmin( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument which is not a number... +{ + incrnanmmin( '5' ); // $ExpectError + incrnanmmin( true ); // $ExpectError + incrnanmmin( false ); // $ExpectError + incrnanmmin( null ); // $ExpectError + incrnanmmin( undefined ); // $ExpectError + incrnanmmin( [] ); // $ExpectError + incrnanmmin( {} ); // $ExpectError + incrnanmmin( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmmin(); // $ExpectError + incrnanmmin( 3, 2 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmin( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmin( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmin/examples/index.js new file mode 100644 index 000000000000..055b6adb14d4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/examples/index.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmmin = require( './../lib' ); + +var accumulator; +var m; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmin( 5 ); + +// For each simulated datum, update the moving minimum... +console.log( '\nValue\tMin\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( randu() < 0.1 ) ? NaN : randu() * 100.0; + m = accumulator( v ); + console.log( '%s\t%s', ( isnan( v ) ) ? 'NaN' : v.toFixed( 4 ), ( m === null ) ? 'null' : m.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmin/lib/index.js new file mode 100644 index 000000000000..4e887104775c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving minimum incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmin +* +* @example +* var incrnanmmin = require( '@stdlib/stats/incr/nanmmin' ); +* +* var accumulator = incrnanmmin( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns -5.0 +* +* m = accumulator( 3.0 ); +* // returns -5.0 +* +* m = accumulator( 5.0 ); +* // returns -5.0 +* +* m = accumulator(); +* // returns -5.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmin/lib/main.js new file mode 100644 index 000000000000..0852f2f2ea5d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/lib/main.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmmin = require( '@stdlib/stats/incr/mmin' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving minimum value, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmin( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns -5.0 +* +* m = accumulator( 3.0 ); +* // returns -5.0 +* +* m = accumulator( 5.0 ); +* // returns -5.0 +* +* m = accumulator(); +* // returns -5.0 +*/ +function incrnanmmin( W ) { + var acc = incrmmin( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated moving minimum. If not provided a value, the accumulator function returns the current moving minimum. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} moving minimum or null + */ + function accumulator( x ) { + if ( arguments.length === 0 ) { + return acc(); + } + if ( isnan( x ) ) { + return acc(); + } + return acc( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmin; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmin/package.json new file mode 100644 index 000000000000..62d41741547e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nanmmin", + "version": "0.0.0", + "description": "Compute a moving minimum incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "minimum", + "min", + "extreme", + "extent", + "range", + "incremental", + "accumulator", + "moving min", + "sliding window", + "sliding", + "window", + "moving", + "nan", + "ignore" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmin/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmin/test/test.js new file mode 100644 index 000000000000..b17d5d62e3d4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmin/test/test.js @@ -0,0 +1,211 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var incrnanmmin = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmin, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + values.forEach( function( value ) { + t.throws( function() { incrnanmmin( value ); }, TypeError, 'throws an error when provided ' + value ); + }); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmmin( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving minimum incrementally, ignoring NaN values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, 4.0, 2.0, NaN, 2.0, 2.0, 2.0, 1.0, 4.0 ]; + N = data.length; + + acc = incrnanmmin( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + expected = [ 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 2.0, 3.0, 2.0, 2.0, 2.0, 2.0, 2.0, 1.0, 1.0 ]; + + t.deepEqual( actual, expected, 'returns expected incremental results while ignoring NaN values' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current minimum value while ignoring NaN values', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 3.0, NaN, 5.0, 4.0 ]; + acc = incrnanmmin( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 4.0, 'returns expected value while ignoring NaN values' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmin( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving minimum incrementally, ignoring NaN values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, NaN, 4.0, 2.0, 2.0, NaN, 1.0, 4.0 ]; + N = data.length; + + acc = incrnanmmin( 3 ); // Moving window of size 3 + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + + // Expected minimum values, ignoring NaN + expected = [ + 2.0, // [ 2.0 ] + 2.0, // [ 2.0 ] (NaN ignored) + 2.0, // [ 2.0, 3.0 ] + 2.0, // [ 2.0, 3.0, 2.0 ] + 2.0, // [ 2.0, 3.0, 2.0 ] (NaN ignored) + 2.0, // [ 3.0, 2.0, 4.0 ] (window moves) + 2.0, // [ 2.0, 4.0, 3.0 ] + 2.0, // [ 2.0, 4.0, 3.0 ] (NaN ignored) + 3.0, // [ 4.0, 3.0, 4.0 ] + 2.0, // [ 3.0, 4.0, 2.0 ] + 2.0, // [ 4.0, 2.0, 2.0 ] + 2.0, // [ 4.0, 2.0, 2.0 ] (NaN ignored) + 1.0, // [ 2.0, 2.0, 1.0 ] + 1.0 // [ 2.0, 1.0, 4.0 ] + ]; + + // Check the computed values against the expected values + for ( i = 0; i < N; i++ ) { + t.equal( actual[ i ], expected[ i ], 'returns expected value at index ' + i ); + } + + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value ignores `NaN` and computes the minimum over valid values', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmmin( 3 ); + + data = [ + NaN, // ignored + 3.14, // 3.14 + 3.14, // 3.14, 3.14 + NaN, // 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14 (NaN ignored) + NaN, // 3.14 (NaN ignored) + NaN, // (NaN ignored) + NaN, // (NaN ignored) + 3.14 // 3.14 + ]; + + expected = [ + null, // No valid numbers yet + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14 + ]; + + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( expected[ i ] === null ) { + t.equal( v, null, 'returns expected value for window ' + i ); + } else { + t.equal( v, expected[ i ], 'returns expected value for window ' + i ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/README.md b/lib/node_modules/@stdlib/stats/incr/nanmminabs/README.md new file mode 100644 index 000000000000..3876d53d9707 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/README.md @@ -0,0 +1,141 @@ + + +# incrnanmminabs + +> Compute a moving minimum absolute value incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanmminabs = require( '@stdlib/stats/incr/nanmminabs' ); +``` + +#### incrnanmminabs( window ) + +Returns an accumulator `function` which incrementally computes a moving minimum absolute value, ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving minimum absolute value. + +```javascript +var accumulator = incrnanmminabs( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated minimum absolute value. If not provided an input value `x`, the accumulator function returns the current minimum absolute value. + +```javascript +var accumulator = incrnanmminabs( 3 ); + +var m = accumulator(); +// returns null + +// Fill the window... +m = accumulator( 2.0 ); // [2.0] +// returns 2.0 + +m = accumulator( NaN ); // [2.0] +// returns 2.0 + +m = accumulator( 1.0 ); // [2.0, 1.0] +// returns 1.0 + +m = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns 1.0 + +// Window begins sliding... +m = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns 1.0 + +m = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns 3.0 + +m = accumulator(); +// returns 3.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmminabs = require( '@stdlib/stats/incr/nanmminabs' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmminabs( 5 ); + +// For each simulated datum, update the moving minimum absolute value... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = ( randu()*100.0 ) - 50.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmminabs/benchmark/benchmark.js new file mode 100644 index 000000000000..73be2df05c14 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmminabs = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmminabs( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmminabs( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()-0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/repl.txt new file mode 100644 index 000000000000..956ce646f6d7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/repl.txt @@ -0,0 +1,46 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + minimum absolute value, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving minimum absolute value. + + If provided a value, the accumulator function returns an updated moving + minimum absolute value. If not provided a value, the accumulator function + returns the current moving minimum absolute value. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var m = accumulator() + null + > m = accumulator( 2.0 ) + 2.0 + > m = accumulator( NaN ) + 2.0 + > m = accumulator( -5.0 ) + 2.0 + > m = accumulator( 3.0 ) + 2.0 + > m = accumulator( 5.0 ) + 3.0 + > m = accumulator() + 3.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/types/index.d.ts new file mode 100644 index 000000000000..22396086dad1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/types/index.d.ts @@ -0,0 +1,75 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated minimum absolute value; otherwise, returns the current minimum absolute value. +* +* @param x - value +* @returns minimum absolute value +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving minimum absolute value, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving minimum absolute value. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmminabs( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 2.0 +* +* m = accumulator( 3.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( 5.0 ); +* // returns 3.0 +* +* m = accumulator(); +* // returns 3.0 +*/ +declare function incrnanmminabs( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmminabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/types/test.ts new file mode 100644 index 000000000000..9479b6e9c389 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmminabs = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmminabs( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument which is not a number... +{ + incrnanmminabs( '5' ); // $ExpectError + incrnanmminabs( true ); // $ExpectError + incrnanmminabs( false ); // $ExpectError + incrnanmminabs( null ); // $ExpectError + incrnanmminabs( undefined ); // $ExpectError + incrnanmminabs( [] ); // $ExpectError + incrnanmminabs( {} ); // $ExpectError + incrnanmminabs( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmminabs(); // $ExpectError + incrnanmminabs( 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmminabs( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmminabs( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmminabs/examples/index.js new file mode 100644 index 000000000000..88ef47f48f54 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmminabs = require( './../lib' ); + +var accumulator; +var m; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmminabs( 5 ); + +// For each simulated datum, update the moving minimum absolute value... +console.log( '\nValue\tMinAbs\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = ( randu()*100.0 ) - 50.0; + } + m = accumulator( v ); + console.log( '%d\t%d', v.toFixed( 3 ), ( m === null ) ? NaN : m.toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmminabs/lib/index.js new file mode 100644 index 000000000000..7284142a2f46 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving minimum absolute value incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmminabs +* +* @example +* var incrnanmminabs = require( '@stdlib/stats/incr/nanmminabs' ); +* +* var accumulator = incrnanmminabs( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 2.0 +* +* m = accumulator( 3.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( 5.0 ); +* // returns 3.0 +* +* m = accumulator(); +* // returns 3.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmminabs/lib/main.js new file mode 100644 index 000000000000..426e2305ee56 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/lib/main.js @@ -0,0 +1,85 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmminabs = require( '@stdlib/stats/incr/mminabs' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving minimum absolute value, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmminabs( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( -5.0 ); +* // returns 2.0 +* +* m = accumulator( 3.0 ); +* // returns 2.0 +* +* m = accumulator( NaN ); +* // returns 2.0 +* +* m = accumulator( 5.0 ); +* // returns 3.0 +* +* m = accumulator(); +* // returns 3.0 +*/ +function incrnanmminabs( W ) { + var mminabs = incrmminabs( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated minimum absolute value. If not provided a value, the accumulator function returns the current minimum absolute value. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} minimum absolute value or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return mminabs(); + } + return mminabs( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmminabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/package.json b/lib/node_modules/@stdlib/stats/incr/nanmminabs/package.json new file mode 100644 index 000000000000..537166f585d8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/package.json @@ -0,0 +1,74 @@ +{ + "name": "@stdlib/stats/incr/nanmminabs", + "version": "0.0.0", + "description": "Compute a moving minimum absolute value incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "minimum", + "min", + "absolute", + "abs", + "magnitude", + "extreme", + "extent", + "range", + "incremental", + "accumulator", + "moving min", + "sliding window", + "sliding", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminabs/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmminabs/test/test.js new file mode 100644 index 000000000000..42eab2ed8948 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminabs/test/test.js @@ -0,0 +1,222 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var incrnanmminabs = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmminabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmminabs( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmminabs( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving minimum absolute value incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, -3.0, 2.0, -4.0, 3.0, 4.0, -2.0, 2.0, -2.0, 1.0 ]; + N = data.length; + + acc = incrnanmminabs( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + expected = [ 2.0, 2.0, 2.0, 2.0, 2.0, 3.0, 2.0, 2.0, 2.0, 1.0 ]; + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current minimum absolute value', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, -3.0, -5.0, 4.0 ]; + acc = incrnanmminabs( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.strictEqual( acc(), 4.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmminabs( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmminabs( 3 ); + + data = [ + -0.0, // -0 + 0.0, // -0, 0 + -0.0, // -0, 0, -0 + -0.0, // 0, -0, -0 + -0.0, // -0, -0, -0 + 0.0, // -0, -0, 0 + -0.0, // -0, 0, -0 + -0.0, // 0, -0, -0 + -0.0, // -0, -0, -0 + 0.0, // -0, -0, 0 + 0.0, // -0, 0, 0 + 0.0, // 0, 0, 0 + -0.0 // 0, 0, -0 + ]; + expected = [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( isPositiveZero( expected[ i ] ) ) { + t.strictEqual( isPositiveZero( v ), true, 'returns expected value for window '+i ); + } else { + t.strictEqual( isNegativeZero( v ), true, 'returns expected value for window '+i ); + } + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulator function still returns the current minimum absolute value', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmminabs( 3 ); + + data = [ + NaN, // ignored + 3.14, // 3.14 + 3.14, // 3.14, 3.14 + NaN, // 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14 // 3.14, 3.14, 3.14 + ]; + expected = [ + null, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14, + 3.14 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.strictEqual( v, expected[ i ], 'returns expected value for window '+i ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/README.md b/lib/node_modules/@stdlib/stats/incr/nanmminmax/README.md new file mode 100644 index 000000000000..63a9ba1d2003 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/README.md @@ -0,0 +1,149 @@ + + +# incrnanmminmax + +> Compute a moving minimum and maximum incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanmminmax = require( '@stdlib/stats/incr/nanmminmax' ); +``` + +#### incrnanmminmax( \[out,] window ) + +Returns an accumulator `function` which incrementally computes a moving minimum and maximum, ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving minimum and maximum. + +```javascript +var accumulator = incrnanmminmax( 3 ); +``` + +By default, the returned accumulator `function` returns the minimum and maximum as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var accumulator = incrnanmminmax( new Float64Array( 2 ), 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns updated minimum and maximum values. If not provided an input value `x`, the accumulator function returns the current minimum and maximum values. + +```javascript +var accumulator = incrnanmminmax( 3 ); + +var mm = accumulator(); +// returns null + +// Fill the window... +mm = accumulator( 2.0 ); // [2.0] +// returns [ 2.0, 2.0 ] + +mm = accumulator( 1.0 ); // [2.0, 1.0] +// returns [ 1.0, 2.0 ] + +mm = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns [ 1.0, 3.0 ] + +// Window begins sliding... +mm = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns [ -7.0, 3.0 ] + +mm = accumulator( NaN ); // [1.0, 3.0, -7.0] +// returns [ -7.0, 3.0 ] + +mm = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns [ -7.0, 3.0 ] + +mm = accumulator(); +// returns [ -7.0, 3.0 ] +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned minimum and maximum values are calculated from smaller sample sizes. Until the window is full, each returned minimum and maximum is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmminmax = require( '@stdlib/stats/incr/nanmminmax' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmminmax( 5 ); + +// For each simulated datum, update the moving minimum and maximum... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmminmax/benchmark/benchmark.js new file mode 100644 index 000000000000..988b0ee165a6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmminmax = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmminmax( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmminmax( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v.length !== 2 ) { + b.fail( 'should contain two elements' ); + } + } + b.toc(); + if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/repl.txt new file mode 100644 index 000000000000..a955ce060a32 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/repl.txt @@ -0,0 +1,48 @@ + +{{alias}}( [out,] W ) + Returns an accumulator function which incrementally computes a moving + minimum and maximum, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving minimum and maximum. + + If provided a value, the accumulator function returns an updated moving + minimum and maximum. If not provided a value, the accumulator function + returns the current moving minimum and maximum. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + minimum and maximum values are calculated from smaller sample sizes. Until + the window is full, each returned minimum and maximum is calculated from all + provided values. + + Parameters + ---------- + out: Array|TypedArray (optional) + Output array. + + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var mm = accumulator() + null + > mm = accumulator( 2.0 ); + > mm = accumulator( -5.0 ) + [ -5.0, 2.0 ] + > mm = accumulator( NaN ) + [ -5.0, 2.0 ] + > mm = accumulator( 1.0 ) + [ -5.0, 2.0 ] + > mm = accumulator() + [ -5.0, 2.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/types/index.d.ts new file mode 100644 index 000000000000..2927d9508052 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/types/index.d.ts @@ -0,0 +1,109 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; + +/** +* If provided a value, the accumulator function returns updated minimum and maximum values. If not provided a value, the accumulator function returns the current minimum and maximum values. +* +* @param x - input value +* @returns output array or null +*/ +type accumulator = ( x?: number ) => ArrayLike | null; + +/** +* Returns an accumulator function which incrementally computes moving minimum and maximum values, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving minimum and maximum. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned minimum and maximum values are calculated from smaller sample sizes. Until the window is full, each returned minimum and maximum is calculated from all provided values. +* +* @param out - output array +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var Float64Array = require( '@stdlib/array/float64' ); +* +* var accumulator = incrnanmminmax( new Float64Array( 2 ), 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( NaN ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ -5.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ -5.0, 5.0 ] +*/ +declare function incrnanmminmax( out: ArrayLike, window: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes moving minimum and maximum values, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving minimum and maximum. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned minimum and maximum values are calculated from smaller sample sizes. Until the window is full, each returned minimum and maximum is calculated from all provided values. +* +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmminmax( 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( NaN ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ -5.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ -5.0, 5.0 ] +*/ +declare function incrnanmminmax( window: number ): accumulator; + + +// EXPORTS // + +export = incrnanmminmax; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/types/test.ts new file mode 100644 index 000000000000..7cc4d1b43314 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/docs/types/test.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmminmax = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmminmax( 3 ); // $ExpectType accumulator + const out = [ 0.0, 0.0 ]; + incrnanmminmax( out, 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided a last argument that is not a number... +{ + incrnanmminmax( '5' ); // $ExpectError + incrnanmminmax( true ); // $ExpectError + incrnanmminmax( false ); // $ExpectError + incrnanmminmax( null ); // $ExpectError + incrnanmminmax( {} ); // $ExpectError + incrnanmminmax( ( x: number ): number => x ); // $ExpectError + + const out = [ 0.0, 0.0 ]; + incrnanmminmax( out, '5' ); // $ExpectError + incrnanmminmax( out, true ); // $ExpectError + incrnanmminmax( out, false ); // $ExpectError + incrnanmminmax( out, null ); // $ExpectError + incrnanmminmax( out, {} ); // $ExpectError + incrnanmminmax( out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an output array that is not an array-like object of numbers... +{ + incrnanmminmax( '5', 3 ); // $ExpectError + incrnanmminmax( true, 3 ); // $ExpectError + incrnanmminmax( false, 3 ); // $ExpectError + incrnanmminmax( null, 3 ); // $ExpectError + incrnanmminmax( {}, 3 ); // $ExpectError + incrnanmminmax( ( x: number ): number => x, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmminmax( 3 ); + + acc(); // $ExpectType ArrayLike | null + acc( 3.14 ); // $ExpectType ArrayLike | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmminmax( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmminmax/examples/index.js new file mode 100644 index 000000000000..4bdfbb79e547 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmminmax = require( './../lib' ); + +var accumulator; +var mm; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmminmax( 5 ); + +// For each simulated datum, update the moving minimum and maximum... +console.log( '\nValue\tMin\tMax\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + mm = accumulator( v ); + console.log( '%s\t%s\t%s', v.toFixed( 4 ), ( mm === null ) ? NaN : mm[ 0 ].toFixed( 4 ), ( mm === null ) ? NaN : mm[ 1 ].toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmminmax/lib/index.js new file mode 100644 index 000000000000..682f6cfa14cc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving minimum and maximum incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmminmax +* +* @example +* var incrnanmminmax = require( '@stdlib/stats/incr/nanmminmax' ); +* +* var accumulator = incrnanmminmax( 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( NaN ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ -5.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ -5.0, 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmminmax/lib/main.js new file mode 100644 index 000000000000..8fe1e6c81c41 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/lib/main.js @@ -0,0 +1,86 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmminmax = require( '@stdlib/stats/incr/mminmax' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes moving minimum and maximum values, ignoring `NaN` values. +* +* @param {Collection} [out] - output array +* @param {PositiveInteger} window - window size +* @throws {TypeError} output argument must be array-like +* @throws {TypeError} window size must be a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmminmax( 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( NaN ); +* // returns [ -5.0, 2.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ -5.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ -5.0, 5.0 ] +*/ +function incrnanmminmax( out, window ) { + var mminmax; + if ( arguments.length === 1 ) { + mminmax = incrmminmax( out ); + } else { + mminmax = incrmminmax( out, window ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns updated minimum and maximum values. If not provided a value, the accumulator function returns the current minimum and maximum values. + * + * @private + * @param {number} [x] - new value + * @returns {(ArrayLikeObject|null)} min/max array or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return mminmax(); + } + return mminmax( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmminmax; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/package.json b/lib/node_modules/@stdlib/stats/incr/nanmminmax/package.json new file mode 100644 index 000000000000..6f9d14a3f962 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/package.json @@ -0,0 +1,76 @@ +{ + "name": "@stdlib/stats/incr/nanmminmax", + "version": "0.0.0", + "description": "Compute a moving minimum and maximum incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "minimum", + "min", + "dispersion", + "variance", + "range", + "extent", + "extrema", + "incremental", + "accumulator", + "sliding window", + "sliding", + "window", + "moving", + "nan", + "ignore" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmax/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmminmax/test/test.js new file mode 100644 index 000000000000..fe8d3083db36 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmax/test/test.js @@ -0,0 +1,492 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var incrnanmminmax = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmminmax, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmminmax( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (output argument)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmminmax( [ 0.0, 0.0 ], value ); + }; + } +}); + +tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + NaN, + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmminmax( value, 3 ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmminmax( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (output)', function test( t ) { + t.strictEqual( typeof incrnanmminmax( [ 0.0, 0.0 ], 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving minimum and maximum incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, NaN, 4.0, 2.0, 2.0, 1.0, 0.0 ]; + N = data.length; + + acc = incrnanmminmax( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( ( acc( data[ i ] ) ).slice() ); + } + expected = [ + [ 2.0, 2.0 ], + [ 2.0, 2.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 3.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 1.0, 2.0 ], + [ 0.0, 2.0 ] + ]; + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving minimum and maximum incrementally (output)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var out; + var N; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, 4.0, NaN, 2.0, 2.0, 1.0, 0.0 ]; + N = data.length; + + out = [ 0.0, 0.0 ]; + acc = incrnanmminmax( out, 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + t.strictEqual( actual[ i ], out, 'returns output array' ); + actual[ i ] = actual[ i ].slice(); + } + expected = [ + [ 2.0, 2.0 ], + [ 2.0, 2.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 3.0, 4.0 ], + [ 3.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 1.0, 2.0 ], + [ 0.0, 2.0 ] + ]; + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current minimum and maximum values', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, 3.0, 5.0, 4.0 ]; + acc = incrnanmminmax( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.deepEqual( acc(), [ 4.0, 5.0 ], 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmminmax( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if only `NaN` values have been provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmminmax( 3 ); + acc( NaN ); + acc( NaN ); + acc( NaN ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var expected; + var data; + var sgn1; + var sgn2; + var acc; + var v; + var i; + + acc = incrnanmminmax( 3 ); + + data = [ + 0.0, // 0 => min: 0.0, max: 0.0 (0) + -0.0, // 0, -0 => min: -0.0, max: 0.0 (1) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (2) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (3) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (4) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (5) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (6) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (7) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (8) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (9) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (10) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (11) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (12) + + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (13) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (14) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (15) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (16) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (17) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (18) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (19) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (20) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (21) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (22) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (23) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (24) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (25) + + // Case 1: out: -0, in: +0, cnt: 1 + 3.14, // 0, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 2: out: +0, in: -0, cnt: 1 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 3: out: -0, in: -0, cnt: 1 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 4: out: -0, in: +0, cnt: 2 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + -0.0, // -0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 5: out: +0, in: +0, cnt: 1 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 6: out: +0, in: -0, cnt: 2 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + -0.0, // 0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 7: out: +0, in: +0, cnt: 2 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 0.0, // 0, 3.14, 0 => min: 0.0, max: 3.14 + 0.0, // 3.14, 0, 0 => min: 0.0, max: 3.14 + + // Reset: + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 + + // Case 8: out: -0, in: +0, cnt: 1 + -3.14, // 0, -0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 9: out: +0, in: -0, cnt: 1 + -3.14, // -3.14, 0, 3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 10: out: -0, in: -0, cnt: 1 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -3.14, // -0, -3.14, -3.14 => min: -3.14, max: -0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 11: out: -0, in: +0, cnt: 2 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -0.0, // -0, -3.14, -0 => min: -3.14, max: -0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 12: out: +0, in: +0, cnt: 1 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 13: out: +0, in: -0, cnt: 2 + -3.14, // -3.14, 0, -3.14 => min: -3.14, max: 0.0 + -0.0, // 0, -3.14, -0 => min: -3.14, max: 0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 14: out: +0, in: +0, cnt: 2 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + 0.0, // -3.14, 0, 0 => min: -3.14, max: 0.0 + + // Reset: + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 + + // Case 15: out: +0, in: -0, cnt: 2 + -3.14, // 0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + -0.0 // -3.14, 0, -0 => min: -3.14, max: 0.0 + ]; + expected = [ + [ 0.0, 0.0, 0 ], + [ -0.0, 0.0, 1 ], + [ -0.0, 0.0, 2 ], + [ -0.0, 0.0, 3 ], + [ 0.0, 0.0, 4 ], + [ -0.0, 0.0, 5 ], + [ -0.0, 0.0, 6 ], + [ -0.0, 0.0, 7 ], + [ 0.0, 0.0, 8 ], + [ -0.0, 0.0, 9 ], + [ -0.0, 0.0, 10 ], + [ -0.0, -0.0, 11 ], + [ -0.0, 0.0, 12 ], + + [ -0.0, 0.0, 13 ], + [ -0.0, 0.0, 14 ], + [ -0.0, 0.0, 15 ], + [ -0.0, 0.0, 16 ], + [ -0.0, -0.0, 17 ], + [ -0.0, 0.0, 18 ], + [ -0.0, 0.0, 19 ], + [ -0.0, 0.0, 20 ], + [ -0.0, -0.0, 21 ], + [ -0.0, 0.0, 22 ], + [ -0.0, 0.0, 23 ], + [ 0.0, 0.0, 24 ], + [ -0.0, 0.0, 25 ], + + // Case 1: + [ -0.0, 3.14, 26 ], + [ -0.0, 3.14, 27 ], + [ 0.0, 3.14, 28 ], + + // Case 2: + [ 0.0, 3.14, 29 ], + [ 0.0, 3.14, 30 ], + [ -0.0, 3.14, 31 ], + + // Case 3: + [ -0.0, 3.14, 32 ], + [ -0.0, 3.14, 33 ], + [ -0.0, 3.14, 34 ], + + // Case 4: + [ -0.0, 3.14, 35 ], + [ -0.0, 3.14, 36 ], + [ -0.0, 3.14, 37 ], + + // Case 5: + [ -0.0, 3.14, 38 ], + [ 0.0, 3.14, 39 ], + [ 0.0, 3.14, 40 ], + + // Case 6: + [ 0.0, 3.14, 41 ], + [ -0.0, 3.14, 42 ], + [ -0.0, 3.14, 43 ], + + // Case 7: + [ -0.0, 3.14, 44 ], + [ 0.0, 3.14, 45 ], + [ 0.0, 3.14, 46 ], + + // Reset: + [ -0.0, 0.0, 47 ], + + // Case 8: + [ -3.14, 0.0, 48 ], + [ -3.14, -0.0, 49 ], + [ -3.14, 0.0, 50 ], + + // Case 9: + [ -3.14, 0.0, 51 ], + [ -3.14, 0.0, 52 ], + [ -3.14, -0.0, 53 ], + + // Case 10: + [ -3.14, -0.0, 54 ], + [ -3.14, -0.0, 55 ], + [ -3.14, -0.0, 56 ], + + // Case 11: + [ -3.14, -0.0, 57 ], + [ -3.14, -0.0, 58 ], + [ -3.14, 0.0, 59 ], + + // Case 12: + [ -3.14, 0.0, 60 ], + [ -3.14, 0.0, 61 ], + [ -3.14, 0.0, 62 ], + + // Case 13: + [ -3.14, 0.0, 63 ], + [ -3.14, 0.0, 64 ], + [ -3.14, 0.0, 65 ], + + // Case 14: + [ -3.14, 0.0, 66 ], + [ -3.14, 0.0, 67 ], + [ -3.14, 0.0, 68 ], + + // Reset: + [ 0.0, 0.0, 69 ], + + // Case 15: + [ -3.14, 0.0, 70 ], + [ -3.14, 0.0, 71 ], + [ -3.14, 0.0, 72 ] + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( expected[ i ][ 0 ] === 0.0 ) { + sgn1 = isNegativeZero( v[ 0 ] ); + sgn2 = isNegativeZero( expected[ i ][ 0 ] ); + t.strictEqual( sgn1, sgn2, 'returns expected signed zero minimum for window '+i+'. v: '+( ( isNegativeZero( data[ i ] ) ) ? '-' : '+' )+data[ i ]+'. actual: '+( ( sgn1 ) ? '-' : '+' )+v[ 0 ]+'. expected: '+( ( sgn2 ) ? '-' : '+' )+expected[ i ][ 0 ]+'.' ); + } else { + t.strictEqual( v[ 0 ], expected[ i ][ 0 ], 'returns expected minimum for window '+i+'. v: '+data[ i ]+'. actual: '+v[ 0 ]+'. expected: '+expected[ i ][ 0 ]+'.' ); + } + if ( expected[ i ][ 1 ] === 0.0 ) { + sgn1 = isNegativeZero( v[ 1 ] ); + sgn2 = isNegativeZero( expected[ i ][ 1 ] ); + t.strictEqual( sgn1, sgn2, 'returns expected signed zero maximum for window '+i+'. v: '+( ( isNegativeZero( data[ i ] ) ) ? '-' : '+' )+data[ i ]+'. actual: '+( ( sgn1 ) ? '-' : '+' )+v[ 1 ]+'. expected: '+( ( sgn2 ) ? '-' : '+' )+expected[ i ][ 1 ]+'.' ); + } else { + t.strictEqual( v[ 1 ], expected[ i ][ 1 ], 'returns expected maximum for window '+i+'. v: '+data[ i ]+'. actual: '+v[ 1 ]+'. expected: '+expected[ i ][ 1 ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/README.md b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/README.md new file mode 100644 index 000000000000..ba2ed2b361e9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/README.md @@ -0,0 +1,145 @@ + + +# incrnanmminmaxabs + +> Compute moving minimum and maximum absolute values incrementally, ignoring `NaN` values. + +
+ +## Usage + +```javascript +var incrnanmminmaxabs = require( '@stdlib/stats/incr/nanmminmaxabs' ); +``` + +#### incrnanmminmaxabs( \[out,] window ) + +Returns an accumulator `function` which incrementally computes moving minimum and maximum absolute values, ignoring `NaN` values. The `window` parameter defines the number of values over which to compute moving minimum and maximum absolute values. + +```javascript +var accumulator = incrnanmminmaxabs( 3 ); +``` + +By default, the returned accumulator `function` returns the minimum and maximum as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object. + +```javascript +var Float64Array = require( '@stdlib/array/float64' ); + +var accumulator = incrnanmminmaxabs( new Float64Array( 2 ), 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns updated minimum and maximum absolute values. If not provided an input value `x`, the accumulator function returns the current minimum and maximum absolute values. + +```javascript +var accumulator = incrnanmminmaxabs( 3 ); + +var mm = accumulator(); +// returns null + +// Fill the window... +mm = accumulator( 2.0 ); // [2.0] +// returns [ 2.0, 2.0 ] + +mm = accumulator( 1.0 ); // [2.0, 1.0] +// returns [ 1.0, 2.0 ] + +mm = accumulator( NaN ); // [2.0, 1.0] +// returns [ 1.0, 2.0 ] + +mm = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns [ 1.0, 3.0 ] + +// Window begins sliding... +mm = accumulator( -7.0 ); // [1.0, 3.0, -7.0] +// returns [ 1.0, 7.0 ] + +mm = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns [ 3.0, 7.0 ] + +mm = accumulator(); +// returns [ 3.0, 7.0 ] +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned minimum and maximum values are calculated from smaller sample sizes. Until the window is full, each returned minimum and maximum is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmminmaxabs = require( '@stdlib/stats/incr/nanmminmaxabs' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmminmaxabs( 5 ); + +// For each simulated datum, update the moving minimum and maximum absolute values... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = ( randu()*100.0 ) - 50.0; + } + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/benchmark/benchmark.js new file mode 100644 index 000000000000..ebdaaf499ab9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmminmaxabs = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmminmaxabs( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmminmaxabs( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() ); + if ( v.length !== 2 ) { + b.fail( 'should contain two elements' ); + } + } + b.toc(); + if ( v[ 0 ] !== v[ 0 ] || v[ 1 ] !== v[ 1 ] ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/repl.txt new file mode 100644 index 000000000000..5b05564bdd88 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/repl.txt @@ -0,0 +1,48 @@ + +{{alias}}( [out,] W ) + Returns an accumulator function which incrementally computes moving minimum + and maximum absolute values, ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute moving + minimum and maximum absolute values. + + If provided a value, the accumulator function returns an updated moving + minimum and maximum. If not provided a value, the accumulator function + returns the current moving minimum and maximum. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + minimum and maximum values are calculated from smaller sample sizes. Until + the window is full, each returned minimum and maximum is calculated from all + provided values. + + Parameters + ---------- + out: Array|TypedArray (optional) + Output array. + + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var mm = accumulator() + null + > mm = accumulator( 2.0 ); + > mm = accumulator( -5.0 ) + [ 2.0, 5.0 ] + > mm = accumulator( NaN ) + [ 2.0, 5.0 ] + > mm = accumulator( 3.0 ) + [ 2.0, 5.0 ] + > mm = accumulator() + [ 2.0, 5.0 ] + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/types/index.d.ts new file mode 100644 index 000000000000..94e8d1aad26c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/types/index.d.ts @@ -0,0 +1,113 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +import { ArrayLike } from '@stdlib/types/array'; + +/** +* If provided a value, the accumulator function returns updated minimum and maximum absolute values. If not provided a value, the accumulator function returns the current minimum and maximum absolute values. +* +* @param x - input value +* @returns output array or null +*/ +type accumulator = ( x?: number ) => ArrayLike | null; + +/** +* Returns an accumulator function which incrementally computes moving minimum and maximum absolute values, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute moving minimum and maximum absolute values. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned minimum and maximum values are calculated from smaller sample sizes. Until the window is full, each returned minimum and maximum is calculated from all provided values. +* +* @param out - output array +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmminmaxabs( [ 0.0, 0.0 ], 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( NaN ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 3.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ 3.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ 3.0, 5.0 ] +*/ +declare function incrnanmminmaxabs( out: ArrayLike, window: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes moving minimum and maximum absolute values, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute moving minimum and maximum absolute values. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned minimum and maximum values are calculated from smaller sample sizes. Until the window is full, each returned minimum and maximum is calculated from all provided values. +* +* @param window - window size +* @throws window size must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmminmaxabs( 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( NaN ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 3.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ 3.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ 3.0, 5.0 ] +*/ +declare function incrnanmminmaxabs( window: number ): accumulator; + + +// EXPORTS // + +export = incrnanmminmaxabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/types/test.ts new file mode 100644 index 000000000000..0c06985d6055 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/docs/types/test.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmminmaxabs = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmminmaxabs( 3 ); // $ExpectType accumulator + const out = [ 0.0, 0.0 ]; + incrnanmminmaxabs( out, 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided a last argument that is not a number... +{ + incrnanmminmaxabs( '5' ); // $ExpectError + incrnanmminmaxabs( true ); // $ExpectError + incrnanmminmaxabs( false ); // $ExpectError + incrnanmminmaxabs( null ); // $ExpectError + incrnanmminmaxabs( {} ); // $ExpectError + incrnanmminmaxabs( ( x: number ): number => x ); // $ExpectError + + const out = [ 0.0, 0.0 ]; + incrnanmminmaxabs( out, '5' ); // $ExpectError + incrnanmminmaxabs( out, true ); // $ExpectError + incrnanmminmaxabs( out, false ); // $ExpectError + incrnanmminmaxabs( out, null ); // $ExpectError + incrnanmminmaxabs( out, {} ); // $ExpectError + incrnanmminmaxabs( out, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an output array that is not an array-like object of numbers... +{ + incrnanmminmaxabs( '5', 3 ); // $ExpectError + incrnanmminmaxabs( true, 3 ); // $ExpectError + incrnanmminmaxabs( false, 3 ); // $ExpectError + incrnanmminmaxabs( null, 3 ); // $ExpectError + incrnanmminmaxabs( {}, 3 ); // $ExpectError + incrnanmminmaxabs( ( x: number ): number => x, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmminmaxabs( 3 ); + + acc(); // $ExpectType ArrayLike | null + acc( 3.14 ); // $ExpectType ArrayLike | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmminmaxabs( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/examples/index.js new file mode 100644 index 000000000000..1960348a5b13 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmminmaxabs = require( './../lib' ); + +var accumulator; +var mm; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanmminmaxabs( 5 ); + +// For each simulated datum, update the moving minimum and maximum absolute values... +console.log( '\nValue\tMin Abs\tMax Abs\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = ( randu()*100.0 ) - 50.0; + } + mm = accumulator( v ); + console.log( '%d\t%s\t%s', v.toFixed( 3 ), ( mm === null ) ? NaN : mm[ 0 ].toFixed( 3 ), ( mm === null ) ? NaN : mm[ 1 ].toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/lib/index.js new file mode 100644 index 000000000000..355a6d1cd1a7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute moving minimum and maximum absolute values incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmminmaxabs +* +* @example +* var incrnanmminmaxabs = require( '@stdlib/stats/incr/nanmminmaxabs' ); +* +* var accumulator = incrnanmminmaxabs( 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( NaN ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 3.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ 3.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ 3.0, 5.0 ] +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/lib/main.js new file mode 100644 index 000000000000..c04b3ecf8b15 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/lib/main.js @@ -0,0 +1,89 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmminmaxabs = require( '@stdlib/stats/incr/mminmaxabs' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes moving minimum and maximum absolute values, ignoring `NaN` values. +* +* @param {Collection} [out] - output array +* @param {PositiveInteger} window - window size +* @throws {TypeError} output argument must be array-like +* @throws {TypeError} window size must be a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmminmaxabs( 3 ); +* +* var mm = accumulator(); +* // returns null +* +* mm = accumulator( 2.0 ); +* // returns [ 2.0, 2.0 ] +* +* mm = accumulator( -5.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( NaN ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 3.0 ); +* // returns [ 2.0, 5.0 ] +* +* mm = accumulator( 5.0 ); +* // returns [ 3.0, 5.0 ] +* +* mm = accumulator(); +* // returns [ 3.0, 5.0 ] +*/ +function incrnanmminmaxabs( out, window ) { + var minmax; + if ( arguments.length > 1 ) { + minmax = incrmminmaxabs( out, window ); + } else { + minmax = incrmminmaxabs( out ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns updated minimum and maximum absolute values. If not provided a value, the accumulator function returns the current minimum and maximum absolute values. + * + * @private + * @param {number} [x] - input value + * @returns {(ArrayLikeObject|null)} output array or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return minmax(); + } + return minmax( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmminmaxabs; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/package.json b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/package.json new file mode 100644 index 000000000000..9320a4666f0b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/package.json @@ -0,0 +1,80 @@ +{ + "name": "@stdlib/stats/incr/nanmminmaxabs", + "version": "0.0.0", + "description": "Compute moving minimum and maximum absolute values incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "minimum", + "min", + "absolute", + "value", + "abs", + "magnitude", + "dispersion", + "variance", + "range", + "extent", + "extrema", + "incremental", + "accumulator", + "sliding window", + "sliding", + "window", + "moving", + "rolling", + "nan" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/test/test.js new file mode 100644 index 000000000000..15dbb578f100 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmminmaxabs/test/test.js @@ -0,0 +1,530 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var incrnanmminmaxabs = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmminmaxabs, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmminmaxabs( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (output argument)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmminmaxabs( [ 0.0, 0.0 ], value ); + }; + } +}); + +tape( 'the function throws an error if not provided an array-like object for an output argument', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + true, + false, + null, + void 0, + NaN, + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmminmaxabs( value, 3 ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmminmaxabs( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (output)', function test( t ) { + t.strictEqual( typeof incrnanmminmaxabs( [ 0.0, 0.0 ], 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes moving minimum and maximum absolute values incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ + 2.0, + NaN, + -3.0, + -2.0, + 4.0, + -3.0, + 4.0, + NaN, + -2.0, + 2.0, + -2.0, + -1.0, + 0.0, + NaN, + 4.0, + -1.0 + ]; + N = data.length; + + acc = incrnanmminmaxabs( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( ( acc( data[ i ] ) ).slice() ); + } + expected = [ + [ 2.0, 2.0 ], + [ 2.0, 2.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 3.0, 4.0 ], + [ 3.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 2.0 ], + [ 1.0, 2.0 ], + [ 0.0, 2.0 ], + [ 0.0, 2.0 ], + [ 0.0, 4.0 ], + [ 0.0, 4.0 ] + ]; + + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'the accumulator function computes moving minimum and maximum absolute values incrementally (output)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var out; + var N; + var i; + + data = [ + 2.0, + NaN, + -3.0, + -2.0, + 4.0, + -3.0, + 4.0, + NaN, + -2.0, + 2.0, + -2.0, + -1.0, + 0.0, + NaN, + 4.0, + -1.0 + ]; + N = data.length; + + out = [ 0.0, 0.0 ]; + acc = incrnanmminmaxabs( out, 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + t.strictEqual( actual[ i ], out, 'returns output array' ); + actual[ i ] = actual[ i ].slice(); + } + expected = [ + [ 2.0, 2.0 ], + [ 2.0, 2.0 ], + [ 2.0, 3.0 ], + [ 2.0, 3.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 3.0, 4.0 ], + [ 3.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 4.0 ], + [ 2.0, 2.0 ], + [ 1.0, 2.0 ], + [ 0.0, 2.0 ], + [ 0.0, 2.0 ], + [ 0.0, 4.0 ], + [ 0.0, 4.0 ] + ]; + + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current minimum and maximum absolute values', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, -3.0, -5.0, 4.0 ]; + acc = incrnanmminmaxabs( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.deepEqual( acc(), [ 4.0, 5.0 ], 'returns expected value' ); + t.end(); +}); + +tape( 'if no valid data has been provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmminmaxabs( 3 ); + + t.strictEqual( acc(), null, 'returns expected value' ); + + acc( NaN ); + acc( NaN ); + acc( NaN ); + + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var expected; + var data; + var sgn1; + var sgn2; + var acc; + var v; + var i; + + acc = incrnanmminmaxabs( 3 ); + + data = [ + 0.0, // 0 => min: 0.0, max: 0.0 (0) + -0.0, // 0, -0 => min: -0.0, max: 0.0 (1) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (2) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (3) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (4) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (5) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (6) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (7) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (8) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (9) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (10) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (11) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (12) + + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (13) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (14) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (15) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (16) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (17) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (18) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (19) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (20) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (21) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (22) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (23) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (24) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (25) + + // Case 1: out: -0, in: +0, cnt: 1 + 3.14, // 0, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 2: out: +0, in: -0, cnt: 1 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 3: out: -0, in: -0, cnt: 1 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 4: out: -0, in: +0, cnt: 2 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + -0.0, // -0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 5: out: +0, in: +0, cnt: 1 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 6: out: +0, in: -0, cnt: 2 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + -0.0, // 0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 7: out: +0, in: +0, cnt: 2 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 0.0, // 0, 3.14, 0 => min: 0.0, max: 3.14 + 0.0, // 3.14, 0, 0 => min: 0.0, max: 3.14 + + // Reset: + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 + + // Case 8: out: -0, in: +0, cnt: 1 + -3.14, // 0, -0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 9: out: +0, in: -0, cnt: 1 + -3.14, // -3.14, 0, 3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 10: out: -0, in: -0, cnt: 1 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -3.14, // -0, -3.14, -3.14 => min: -3.14, max: -0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 11: out: -0, in: +0, cnt: 2 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -0.0, // -0, -3.14, -0 => min: -3.14, max: -0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 12: out: +0, in: +0, cnt: 1 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 13: out: +0, in: -0, cnt: 2 + -3.14, // -3.14, 0, -3.14 => min: -3.14, max: 0.0 + -0.0, // 0, -3.14, -0 => min: -3.14, max: 0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 14: out: +0, in: +0, cnt: 2 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + 0.0, // -3.14, 0, 0 => min: -3.14, max: 0.0 + + // Reset: + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 + + // Case 15: out: +0, in: -0, cnt: 2 + -3.14, // 0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + -0.0 // -3.14, 0, -0 => min: -3.14, max: 0.0 + ]; + expected = [ + [ 0.0, 0.0, 0 ], + [ 0.0, 0.0, 1 ], + [ 0.0, 0.0, 2 ], + [ 0.0, 0.0, 3 ], + [ 0.0, 0.0, 4 ], + [ 0.0, 0.0, 5 ], + [ 0.0, 0.0, 6 ], + [ 0.0, 0.0, 7 ], + [ 0.0, 0.0, 8 ], + [ 0.0, 0.0, 9 ], + [ 0.0, 0.0, 10 ], + [ 0.0, 0.0, 11 ], + [ 0.0, 0.0, 12 ], + + [ 0.0, 0.0, 13 ], + [ 0.0, 0.0, 14 ], + [ 0.0, 0.0, 15 ], + [ 0.0, 0.0, 16 ], + [ 0.0, 0.0, 17 ], + [ 0.0, 0.0, 18 ], + [ 0.0, 0.0, 19 ], + [ 0.0, 0.0, 20 ], + [ 0.0, 0.0, 21 ], + [ 0.0, 0.0, 22 ], + [ 0.0, 0.0, 23 ], + [ 0.0, 0.0, 24 ], + [ 0.0, 0.0, 25 ], + + // Case 1: + [ 0.0, 3.14, 26 ], + [ 0.0, 3.14, 27 ], + [ 0.0, 3.14, 28 ], + + // Case 2: + [ 0.0, 3.14, 29 ], + [ 0.0, 3.14, 30 ], + [ 0.0, 3.14, 31 ], + + // Case 3: + [ 0.0, 3.14, 32 ], + [ 0.0, 3.14, 33 ], + [ 0.0, 3.14, 34 ], + + // Case 4: + [ 0.0, 3.14, 35 ], + [ 0.0, 3.14, 36 ], + [ 0.0, 3.14, 37 ], + + // Case 5: + [ 0.0, 3.14, 38 ], + [ 0.0, 3.14, 39 ], + [ 0.0, 3.14, 40 ], + + // Case 6: + [ 0.0, 3.14, 41 ], + [ 0.0, 3.14, 42 ], + [ 0.0, 3.14, 43 ], + + // Case 7: + [ 0.0, 3.14, 44 ], + [ 0.0, 3.14, 45 ], + [ 0.0, 3.14, 46 ], + + // Reset: + [ 0.0, 0.0, 47 ], + + // Case 8: + [ 0.0, 3.14, 48 ], + [ 0.0, 3.14, 49 ], + [ 0.0, 3.14, 50 ], + + // Case 9: + [ 0.0, 3.14, 51 ], + [ 0.0, 3.14, 52 ], + [ 0.0, 3.14, 53 ], + + // Case 10: + [ 0.0, 3.14, 54 ], + [ 0.0, 3.14, 55 ], + [ 0.0, 3.14, 56 ], + + // Case 11: + [ 0.0, 3.14, 57 ], + [ 0.0, 3.14, 58 ], + [ 0.0, 3.14, 59 ], + + // Case 12: + [ 0.0, 3.14, 60 ], + [ 0.0, 3.14, 61 ], + [ 0.0, 3.14, 62 ], + + // Case 13: + [ 0.0, 3.14, 63 ], + [ 0.0, 3.14, 64 ], + [ 0.0, 3.14, 65 ], + + // Case 14: + [ 0.0, 3.14, 66 ], + [ 0.0, 3.14, 67 ], + [ 0.0, 3.14, 68 ], + + // Reset: + [ 0.0, 0.0, 69 ], + + // Case 15: + [ 0.0, 3.14, 70 ], + [ 0.0, 3.14, 71 ], + [ 0.0, 3.14, 72 ] + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( expected[ i ][ 0 ] === 0.0 ) { + sgn1 = isNegativeZero( v[ 0 ] ); + sgn2 = isNegativeZero( expected[ i ][ 0 ] ); + t.strictEqual( sgn1, sgn2, 'returns expected signed zero minimum for window '+i+'. v: '+( ( isNegativeZero( data[ i ] ) ) ? '-' : '+' )+data[ i ]+'. actual: '+( ( sgn1 ) ? '-' : '+' )+v[ 0 ]+'. expected: '+( ( sgn2 ) ? '-' : '+' )+expected[ i ][ 0 ]+'.' ); + } else { + t.strictEqual( v[ 0 ], expected[ i ][ 0 ], 'returns expected minimum for window '+i+'. v: '+data[ i ]+'. actual: '+v[ 0 ]+'. expected: '+expected[ i ][ 0 ]+'.' ); + } + if ( expected[ i ][ 1 ] === 0.0 ) { + sgn1 = isNegativeZero( v[ 1 ] ); + sgn2 = isNegativeZero( expected[ i ][ 1 ] ); + t.strictEqual( sgn1, sgn2, 'returns expected signed zero maximum for window '+i+'. v: '+( ( isNegativeZero( data[ i ] ) ) ? '-' : '+' )+data[ i ]+'. actual: '+( ( sgn1 ) ? '-' : '+' )+v[ 1 ]+'. expected: '+( ( sgn2 ) ? '-' : '+' )+expected[ i ][ 1 ]+'.' ); + } else { + t.strictEqual( v[ 1 ], expected[ i ][ 1 ], 'returns expected maximum for window '+i+'. v: '+data[ i ]+'. actual: '+v[ 1 ]+'. expected: '+expected[ i ][ 1 ]+'.' ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/README.md b/lib/node_modules/@stdlib/stats/incr/nanmmpe/README.md new file mode 100644 index 000000000000..683b4694c32a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/README.md @@ -0,0 +1,166 @@ + + +# incrnanmmpe + +> Compute a moving [mean percentage error][mean-percentage-error] (MPE) incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [mean percentage error][mean-percentage-error] is defined as + + + +```math +\mathop{\mathrm{MPE}} = \frac{100}{W} \sum_{i=0}^{W-1} \frac{a_i - f_i}{a_i} +``` + + + + + +where `f_i` is the forecast value and `a_i` is the actual value. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmmpe = require( '@stdlib/stats/incr/nanmmpe' ); +``` + +#### incrnanmmpe( window ) + +Returns an accumulator `function` which incrementally computes a moving [mean percentage error][mean-percentage-error]. The `window` parameter defines the number of values over which to compute the moving [mean percentage error][mean-percentage-error], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmmpe( 3 ); +``` + +#### accumulator( \[f, a] ) + +If provided input values `f` and `a`, the accumulator function returns an updated [mean percentage error][mean-percentage-error]. If not provided input values `f` and `a`, the accumulator function returns the current [mean percentage error][mean-percentage-error]. + +```javascript +var accumulator = incrnanmmpe( 3 ); + +var m = accumulator(); +// returns null + +// Fill the window... +m = accumulator( 2.0, 3.0 ); // [(2.0,3.0)] +// returns ~33.33 + +m = accumulator( 1.0, 4.0 ); // [(2.0,3.0), (1.0,4.0)] +// returns ~54.17 + +m = accumulator( NaN, 1.0 ); // [(2.0,3.0), (1.0,4.0)] +// returns ~54.17 + +m = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (1.0,4.0), (3.0,9.0)] +// returns ~58.33 + +// Window begins sliding... +m = accumulator( 7.0, 3.0 ); // [(1.0,4.0), (3.0,9.0), (7.0,3.0)] +// returns ~2.78 + +m = accumulator( 7.0, NaN ); // [(1.0,4.0), (3.0,9.0), (7.0,3.0)] +// returns ~2.78 + +m = accumulator( 5.0, 3.0 ); // [(3.0,9.0), (7.0,3.0), (5.0,3.0)] +// returns ~-44.44 + +m = accumulator(); +// returns ~-44.44 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +- Be careful when interpreting the [mean percentage error][mean-percentage-error] as errors can cancel. This stated, that errors can cancel makes the [mean percentage error][mean-percentage-error] suitable for measuring the bias in forecasts. +- **Warning**: the [mean percentage error][mean-percentage-error] is **not** suitable for intermittent demand patterns (i.e., when `a_i` is `0`). Interpretation is most straightforward when actual and forecast values are positive valued (e.g., number of widgets sold). + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmpe = require( '@stdlib/stats/incr/nanmmpe' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmpe( 5 ); + +// For each simulated datum, update the moving mean percentage error... +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mean-percentage-error]: https://en.wikipedia.org/wiki/Mean_percentage_error + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmmpe/benchmark/benchmark.js new file mode 100644 index 000000000000..f1176bddfed3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmmpe = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmmpe( ( i % 5 ) + 1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmmpe( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() + 0.5, randu() + 0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/img/equation_mean_percentage_error.svg b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/img/equation_mean_percentage_error.svg new file mode 100644 index 000000000000..db2d43ae137d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/img/equation_mean_percentage_error.svg @@ -0,0 +1,65 @@ + +upper M upper P upper E equals StartFraction 100 Over upper W EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts StartFraction a Subscript i Baseline minus f Subscript i Baseline Over a Subscript i Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/repl.txt new file mode 100644 index 000000000000..19d44176f87a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/repl.txt @@ -0,0 +1,49 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + mean percentage error (MPE), ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving mean percentage error. + + If provided input values, the accumulator function returns an updated moving + mean percentage error. If not provided input values, the accumulator + function returns the current moving mean percentage error. + + As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + ~33.33 + > m = accumulator( 5.0, 2.0 ) + ~-58.33 + > m = accumulator( NaN, 2.0 ) + ~-58.33 + > m = accumulator( 3.0, 2.0 ) + ~-55.56 + > m = accumulator( 2.0, 5.0 ) + ~-46.67 + > m = accumulator( 2.0, NaN ) + ~-46.67 + > m = accumulator() + ~-46.67 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/types/index.d.ts new file mode 100644 index 000000000000..20cc147f1abb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/types/index.d.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/** +* If provided input values, the accumulator function returns an updated mean percentage error. If not provided input values, the accumulator function returns the current mean percentage error. +* +* ## Notes +* +* - If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulator ignores the `NaN` value and returns the current mean percentage error. +* +* @param f - input value +* @param a - input value +* @returns mean percentage error or null +*/ +type accumulator = ( f?: number, a?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving mean percentage error, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving mean percentage error. +* - As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmmpe( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator( NaN, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator( 3.0, 2.0 ); +* // returns ~-55.56 +* +* m = accumulator( 2.0, 5.0 ); +* // returns ~-46.67 +* +* m = accumulator( 2.0, NaN ); +* // returns ~-46.67 +* +* m = accumulator(); +* // returns ~-46.67 +*/ +declare function incrnanmmpe( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmmpe; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/types/test.ts new file mode 100644 index 000000000000..8f86463fe524 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/docs/types/test.ts @@ -0,0 +1,74 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmmpe = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmmpe( 2 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument which is not a number... +{ + incrnanmmpe( '5' ); // $ExpectError + incrnanmmpe( true ); // $ExpectError + incrnanmmpe( false ); // $ExpectError + incrnanmmpe( null ); // $ExpectError + incrnanmmpe( undefined ); // $ExpectError + incrnanmmpe( [] ); // $ExpectError + incrnanmmpe( {} ); // $ExpectError + incrnanmmpe( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmmpe(); // $ExpectError + incrnanmmpe( 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmmpe( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmmpe( 3 ); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmpe/examples/index.js new file mode 100644 index 000000000000..b554cd4c4495 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/examples/index.js @@ -0,0 +1,41 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmmpe = require( './../lib' ); + +var accumulator; +var err; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmmpe( 5 ); + +// For each simulated datum, update the moving mean percentage error... +console.log( '\nValue\tValue\tPercentage\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : ( randu()*100.0 ) + 50.0; + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : ( randu()*100.0 ) + 50.0; + err = accumulator( v1, v2 ); + console.log( '%s\t%s\t%s', v1.toFixed( 3 ), v2.toFixed( 3 ), ( err === null ) ? 'null' : err.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmmpe/lib/index.js new file mode 100644 index 000000000000..df0e48d829ec --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving mean percentage error incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmmpe +* +* @example +* var incrnanmmpe = require( '@stdlib/stats/incr/nanmmpe' ); +* +* var accumulator = incrnanmmpe( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator( NaN, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator( 2.0, NaN ); +* // returns ~-58.33 +* +* m = accumulator( 3.0, 2.0 ); +* // returns ~-55.56 +* +* m = accumulator( 2.0, 5.0 ); +* // returns ~-46.67 +* +* m = accumulator(); +* // returns ~-46.67 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmmpe/lib/main.js new file mode 100644 index 000000000000..6a8159858985 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/lib/main.js @@ -0,0 +1,86 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmmpe = require( '@stdlib/stats/incr/mmpe' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving mean percentage error, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmmpe( 3 ); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator( NaN, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator( 2.0, NaN ); +* // returns ~-58.33 +* +* m = accumulator( 3.0, 2.0 ); +* // returns ~-55.56 +* +* m = accumulator( 2.0, 5.0 ); +* // returns ~-46.67 +* +* m = accumulator(); +* // returns ~-46.67 +*/ +function incrnanmmpe( W ) { + var m = incrmmpe( W ); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated mean percentage error. If not provided input values, the accumulator function returns the current mean percentage error. + * + * @private + * @param {number} [f] - input value + * @param {number} [a] - input value + * @returns {(number|null)} mean percentage error or null + */ + function accumulator( f, a ) { + if ( arguments.length === 0 || isnan( f ) || isnan( a ) ) { + return m(); + } + return m( f, a ); + } +} + + +// EXPORTS // + +module.exports = incrnanmmpe; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/package.json b/lib/node_modules/@stdlib/stats/incr/nanmmpe/package.json new file mode 100644 index 000000000000..c27d7eb81506 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/package.json @@ -0,0 +1,83 @@ +{ + "name": "@stdlib/stats/incr/nanmmpe", + "version": "0.0.0", + "description": "Compute a moving mean percentage error (MPE) incrementally, ignoring `NaN` values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "error", + "err", + "mpe", + "percentage", + "percent", + "incremental", + "accumulator", + "moving mean", + "moving average", + "sliding window", + "sliding", + "window", + "moving", + "time series", + "timeseries", + "forecasting", + "forecast", + "difference", + "diff", + "delta", + "bias" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmmpe/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmmpe/test/test.js new file mode 100644 index 000000000000..29bf5da69012 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmmpe/test/test.js @@ -0,0 +1,262 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmmpe = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmmpe, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmmpe( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmmpe( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving mean percentage error incrementally', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var N; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, 1.0 ], + [ 2.0, 5.0 ], + [ 4.0, 4.0 ], + [ 3.0, 10.0 ], + [ 4.0, 5.0 ] + ]; + N = data.length; + + acc = incrnanmmpe( 3 ); + + // Note: manually computed + expected = [ + (100.0/1.0)*( ((3.0-2.0)/3.0) ), + (100.0/2.0)*( ((3.0-2.0)/3.0)+((1.0-3.0)/1.0) ), + (100.0/3.0)*( ((3.0-2.0)/3.0)+((1.0-3.0)/1.0)+((5.0-2.0)/5.0) ), + (100.0/3.0)*( ((1.0-3.0)/1.0)+((5.0-2.0)/5.0)+((4.0-4.0)/4.0) ), + (100.0/3.0)*( ((5.0-2.0)/5.0)+((4.0-4.0)/4.0)+((10.0-3.0)/10.0) ), + (100.0/3.0)*( ((4.0-4.0)/4.0)+((10.0-3.0)/10.0)+((5.0-4.0)/5.0) ) + ]; + for ( i = 0; i < N; i++ ) { + actual = acc( data[i][0], data[i][1] ); + if ( actual === expected[i] ) { + t.equal( actual, expected[i], 'returns expected value' ); + } else { + delta = abs( expected[i] - actual ); + tol = 1.0 * EPS * abs( expected[i] ); + t.equal( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected[i]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean percentage error', function test( t ) { + var data; + var acc; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, 5.0 ], + [ 1.0, 10.0 ] + ]; + acc = incrnanmmpe( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[i][0], data[i][1] ); + } + t.equal( acc(), 65.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmmpe( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is current non-NaN mean percentage error', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + expected = [ + null, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0, + -214.0 + ]; + + data = [ + [ NaN, 1.0 ], // NaN + [ 3.14, 1.0 ], // NaN, 3.14 + [ 3.14, 1.0 ], // NaN, 3.14, 3.14 + [ NaN, 1.0 ], // 3.14, 3.14, NaN + [ 3.14, 1.0 ], // 3.14, NaN, 3.14 + [ 3.14, 1.0 ], // NaN, 3.14, 3.14 + [ 3.14, 1.0 ], // 3.14, 3.14, 3.14 + [ NaN, 1.0 ], // 3.14, 3.14, NaN + [ 3.14, 1.0 ], // 3.14, NaN, 3.14 + [ 3.14, 1.0 ], // NaN, 3.14, 3.14 + [ 3.14, 1.0 ], // 3.14, 3.14, 3.14 + [ NaN, 1.0 ], // 3.14, 3.14, NaN + [ 3.14, 1.0 ], // 3.14, NaN, 3.14 + [ 3.14, 1.0 ], // NaN, 3.14, 3.14 + [ NaN, 1.0 ], // 3.14, 3.14, NaN + [ NaN, 1.0 ], // 3.14, NaN, NaN + [ NaN, 1.0 ], // NaN, NaN, NaN + [ NaN, 1.0 ], // NaN, NaN, NaN + [ 3.14, 1.0 ] // NaN, NaN, 3.14 + ]; + + acc = incrnanmmpe( 3 ); + + for ( i = 0; i < data.length; i++ ) { + v = acc( data[i][0], data[i][1] ); + if ( isnan( expected[ i ] ) ) { + t.equal( isnan( v ), true, 'returns expected value for window '+i ); + t.equal( isnan( acc() ), true, 'returns expected value for window '+i ); + } else { + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + t.equal( acc(), expected[ i ], 'returns expected value for window '+i ); + } + } + + expected = [ + null, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14, + 214.0 / 3.14 + ]; + + data = [ + [ 1.0, NaN ], // NaN + [ 1.0, 3.14 ], // NaN, 3.14 + [ 1.0, 3.14 ], // NaN, 3.14, 3.14 + [ 1.0, NaN ], // 3.14, 3.14, NaN + [ 1.0, 3.14 ], // 3.14, NaN, 3.14 + [ 1.0, 3.14 ], // NaN, 3.14, 3.14 + [ 1.0, 3.14 ], // 3.14, 3.14, 3.14 + [ 1.0, NaN ], // 3.14, 3.14, NaN + [ 1.0, 3.14 ], // 3.14, NaN, 3.14 + [ 1.0, 3.14 ], // NaN, 3.14, 3.14 + [ 1.0, 3.14 ], // 3.14, 3.14, 3.14 + [ 1.0, NaN ], // 3.14, 3.14, NaN + [ 1.0, 3.14 ], // 3.14, NaN, 3.14 + [ 1.0, 3.14 ], // NaN, 3.14, 3.14 + [ 1.0, NaN ], // 3.14, 3.14, NaN + [ 1.0, NaN ], // 3.14, NaN, NaN + [ 1.0, NaN ], // NaN, NaN, NaN + [ 1.0, NaN ], // NaN, NaN, NaN + [ 1.0, 3.14 ] // NaN, NaN, 3.14 + ]; + + acc = incrnanmmpe( 3 ); + + for ( i = 0; i < data.length; i++ ) { + v = acc( data[i][0], data[i][1] ); + if ( isnan( expected[ i ] ) ) { + t.equal( isnan( v ), true, 'returns expected value for window '+i ); + t.equal( isnan( acc() ), true, 'returns expected value for window '+i ); + } else { + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + t.equal( acc(), expected[ i ], 'returns expected value for window '+i ); + } + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/README.md b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/README.md new file mode 100644 index 000000000000..5c494c75356e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/README.md @@ -0,0 +1,194 @@ + + +# incrnanmpcorr + +> Compute a moving [sample Pearson product-moment correlation coefficient][pearson-correlation] incrementally, ignoring `NaN` values. + +
+ +The [Pearson product-moment correlation coefficient][pearson-correlation] between random variables `X` and `Y` is defined as + + + +```math +\rho_{X,Y} = \frac{\mathop{\mathrm{cov}}(X,Y)}{\sigma_X \sigma_Y} +``` + + + + + +where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations. + +For a sample of size `W`, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is defined as + + + +```math +r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \displaystyle\sqrt{\displaystyle\sum_{i=0}^{n-1} (y_i - \bar{y})^2}} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmpcorr = require( '@stdlib/stats/incr/nanmpcorr' ); +``` + +#### incrnanmpcorr( window\[, mx, my] ) + +Returns an accumulator `function` which incrementally computes a moving [sample Pearson product-moment correlation coefficient][pearson-correlation]. The `window` parameter defines the number of values over which to compute the moving [sample Pearson product-moment correlation coefficient][pearson-correlation]. + +```javascript +var accumulator = incrnanmpcorr( 3 ); +``` + +If means are already known, provide `mx` and `my` arguments. + +```javascript +var accumulator = incrnanmpcorr( 3, 5.0, -3.14 ); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated [sample Pearson product-moment correlation coefficient][pearson-correlation]. If not provided input values `x` and `y`, the accumulator function returns the current [sample Pearson product-moment correlation coefficient][pearson-correlation]. + +```javascript +var accumulator = incrnanmpcorr( 3 ); + +var r = accumulator(); +// returns null + +// Fill the window... +r = accumulator( 2.0, 1.0 ); // [(2.0, 1.0)] +// returns 0.0 + +r = accumulator( -2.0, NaN ); // [(2.0, 1.0)] +// returns 0.0 + +r = accumulator( -5.0, 3.14 ); // [(2.0, 1.0), (-5.0, 3.14)] +// returns ~-1.0 + +r = accumulator( NaN, 2.71 ); // [(2.0, 1.0), (-5.0, 3.14)] +// returns ~-1.0 + +r = accumulator( 3.0, -1.0 ); // [(2.0, 1.0), (-5.0, 3.14), (3.0, -1.0)] +// returns ~-0.925 + +// Window begins sliding... +r = accumulator( 5.0, -9.5 ); // [(-5.0, 3.14), (3.0, -1.0), (5.0, -9.5)] +// returns ~-0.863 + +r = accumulator( -5.0, 1.5 ); // [(3.0, -1.0), (5.0, -9.5), (-5.0, 1.5)] +// returns ~-0.803 + +r = accumulator(); +// returns ~-0.803 +``` + +
+ + + +
+ +## Notes + +- Input values are type checked. If a non-numeric value or NaN is provided, the accumulator returns the current sample correlation coefficient without updating its internal state. +- As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmpcorr = require( '@stdlib/stats/incr/nanmpcorr' ); + +var accumulator; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmpcorr( 5 ); + +// For each simulated datum, update the moving sample correlation coefficient... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } else { + y = randu() * 100.0; + } + accumulator( x, y ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +[covariance]: https://en.wikipedia.org/wiki/Covariance + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/benchmark/benchmark.js new file mode 100644 index 000000000000..3396e92bb828 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/benchmark/benchmark.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmpcorr = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmpcorr( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmpcorr( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmpcorr( 5, 3.0, -1.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/img/equation_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/img/equation_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..61e3ef3e3500 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/img/equation_pearson_correlation_coefficient.svg @@ -0,0 +1,48 @@ + +rho Subscript upper X comma upper Y Baseline equals StartFraction c o v left-parenthesis upper X comma upper Y right-parenthesis Over sigma Subscript upper X Baseline sigma Subscript upper Y Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..31facfed161b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg @@ -0,0 +1,126 @@ + +r equals StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis Over StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis squared EndRoot EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/repl.txt new file mode 100644 index 000000000000..cc5ceccbb243 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/repl.txt @@ -0,0 +1,56 @@ + +{{alias}}( W[, mx, my] ) + Returns an accumulator function which incrementally computes a moving + sample Pearson product-moment correlation coefficient, + ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving sample correlation coefficient. + + If provided values, the accumulator function returns an updated moving + sample correlation coefficient. If not provided values, the accumulator + function returns the current moving sample correlation coefficient. + + As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + mx: number (optional) + Known mean. + + my: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var r = accumulator() + null + > r = accumulator( 2.0, 1.0 ) + 0.0 + > r = accumulator( -2.0, NaN ) + 0.0 + > r = accumulator( -5.0, 3.14 ) + ~-1.0 + > r = accumulator( NaN, 2.71 ) + ~-1.0 + > r = accumulator( 3.0, -1.0 ) + ~-0.925 + > r = accumulator( 5.0, -9.5 ) + ~-0.863 + > r = accumulator() + ~-0.863 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/types/index.d.ts new file mode 100644 index 000000000000..9de5aec4d79d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/types/index.d.ts @@ -0,0 +1,95 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated moving sample correlation coefficient; otherwise, returns the current moving sample correlation coefficient. +* +* @param x - value +* @param y - value +* @returns updated moving sample correlation coefficient or null +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes an updated moving sample correlation coefficient, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving sample correlation coefficient. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @param meanx - mean value +* @param meany - mean value +* @throws first argument must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmpcorr( 3, -2.0, 10.0 ); +*/ +declare function incrnanmpcorr( W: number, meanx: number, meany: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes an updated moving sample correlation coefficient, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving sample correlation coefficient. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws first argument must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmpcorr( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r = accumulator( -2.0, NaN ); +* // returns 0.0 +* +* r = accumulator( -5.0, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator( NaN, 2.71 ); +* // returns ~-1.0 +* +* r = accumulator( 3.0, -1.0 ); +* // returns ~-0.925 +* +* r = accumulator( 5.0, -9.5 ); +* // returns ~-0.863 +* +* r = accumulator(); +* // returns ~-0.863 +*/ +declare function incrnanmpcorr( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmpcorr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/types/test.ts new file mode 100644 index 000000000000..e8b604dbfafe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/docs/types/test.ts @@ -0,0 +1,123 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmpcorr = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmpcorr( 3 ); // $ExpectType accumulator + incrnanmpcorr( 3, 1.5, 2.5 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided non-numeric arguments... +{ + incrnanmpcorr( 2, '5' ); // $ExpectError + incrnanmpcorr( 2, true ); // $ExpectError + incrnanmpcorr( 2, false ); // $ExpectError + incrnanmpcorr( 2, null ); // $ExpectError + incrnanmpcorr( 2, undefined ); // $ExpectError + incrnanmpcorr( 2, [] ); // $ExpectError + incrnanmpcorr( 2, {} ); // $ExpectError + incrnanmpcorr( 2, ( x: number ): number => x ); // $ExpectError + + incrnanmpcorr( '5', 4 ); // $ExpectError + incrnanmpcorr( true, 4 ); // $ExpectError + incrnanmpcorr( false, 4 ); // $ExpectError + incrnanmpcorr( null, 4 ); // $ExpectError + incrnanmpcorr( undefined, 4 ); // $ExpectError + incrnanmpcorr( [], 4 ); // $ExpectError + incrnanmpcorr( {}, 4 ); // $ExpectError + incrnanmpcorr( ( x: number ): number => x, 4 ); // $ExpectError + + incrnanmpcorr( '5', 2.5, 4 ); // $ExpectError + incrnanmpcorr( true, 2.5, 4 ); // $ExpectError + incrnanmpcorr( false, 2.5, 4 ); // $ExpectError + incrnanmpcorr( null, 2.5, 4 ); // $ExpectError + incrnanmpcorr( undefined, 2.5, 4 ); // $ExpectError + incrnanmpcorr( [], 2.5, 4 ); // $ExpectError + incrnanmpcorr( {}, 2.5, 4 ); // $ExpectError + incrnanmpcorr( ( x: number ): number => x, 2.5, 4 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmpcorr( ); // $ExpectError + incrnanmpcorr( 2, 3 ); // $ExpectError + incrnanmpcorr( 2, 2, 3, 4 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmpcorr( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The function returns an accumulator function which returns an accumulated result (known means)... +{ + const acc = incrnanmpcorr( 3, 2, -3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmpcorr( 3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)... +{ + const acc = incrnanmpcorr( 3, 2, -3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/examples/index.js new file mode 100644 index 000000000000..5c9aa2e095d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/examples/index.js @@ -0,0 +1,48 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmpcorr = require( './../lib' ); + +var accumulator; +var r; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmpcorr( 3 ); + +// For each simulated datum, update the moving sample correlation coefficient... +console.log( '\nx\ty\tCorrelation Coefficient\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } else { + y = randu() * 100.0; + } + r = accumulator( x, y ); + console.log( '%d\t%d\t%s', x.toFixed( 4 ), y.toFixed( 4 ), ( r === null ) ? 'null' : r.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/lib/index.js new file mode 100644 index 000000000000..cb83d640411d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving sample Pearson product-moment correlation coefficient incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmpcorr +* +* @example +* var incrnanmpcorr = require( '@stdlib/stats/incr/nanmpcorr' ); +* +* var accumulator = incrnanmpcorr( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r = accumulator( -2.0, NaN ); +* // returns 0.0 +* +* r = accumulator( -5.0, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator( NaN, 2.71 ); +* // returns ~-1.0 +* +* r = accumulator( 3.0, -1.0 ); +* // returns ~-0.925 +* +* r = accumulator( 5.0, -9.5 ); +* // returns ~-0.863 +* +* r = accumulator(); +* // returns ~-0.863 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/lib/main.js new file mode 100644 index 000000000000..f15338c0b16a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/lib/main.js @@ -0,0 +1,105 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var incrmpcorr = require( '@stdlib/stats/incr/mpcorr' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @param {number} [meanx] - mean value +* @param {number} [meany] - mean value +* @throws {TypeError} first argument must be a positive integer +* @throws {TypeError} second argument must be a number +* @throws {TypeError} third argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmpcorr( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r = accumulator( -2.0, NaN ); +* // returns 0.0 +* +* r = accumulator( -5.0, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator( NaN, 2.71 ); +* // returns ~-1.0 +* +* r = accumulator( 3.0, -1.0 ); +* // returns ~-0.925 +* +* r = accumulator( 5.0, -9.5 ); +* // returns ~-0.863 +* +* r = accumulator(); +* // returns ~-0.863 +* +* @example +* var accumulator = incrnanmpcorr( 3, -2.0, 10.0 ); +*/ +function incrnanmpcorr( W, meanx, meany ) { + var mpcorr; + if ( arguments.length > 1 ) { + mpcorr = incrmpcorr( W, meanx, meany ); + } else { + mpcorr = incrmpcorr( W ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated sample correlation coefficient. If not provided a value, the accumulator function returns the current sample correlation coefficient. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} sample correlation coefficient or null + */ + function accumulator( x, y ) { + if ( + arguments.length === 0 || + !isNumber( x ) || + !isNumber( y ) || + isnan( x ) || + isnan( y ) + ) { + return mpcorr(); + } + return mpcorr( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmpcorr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/package.json b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/package.json new file mode 100644 index 000000000000..b3268b2729b1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/package.json @@ -0,0 +1,79 @@ +{ + "name": "@stdlib/stats/incr/nanmpcorr", + "version": "0.0.0", + "description": "Compute a moving sample Pearson product-moment correlation coefficient incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "covariance", + "sample covariance", + "variance", + "unbiased", + "var", + "correlation", + "corr", + "pcorr", + "pearson", + "product-moment", + "bivariate", + "incremental", + "accumulator", + "moving covariance", + "moving correlation", + "sliding window", + "sliding", + "window", + "moving", + "rolling" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/test/test.js new file mode 100644 index 000000000000..0f876228cd67 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr/test/test.js @@ -0,0 +1,653 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmpcorr = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Computes sample means using Welford's algorithm. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @returns {Array} output array +*/ +function mean( out, arr ) { + var delta; + var mx; + var my; + var N; + var i; + + mx = 0.0; + my = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[i][0] - mx; + mx += delta / N; + delta = arr[i][1] - my; + my += delta / N; + } + out[ 0 ] = mx; + out[ 1 ] = my; + return out; +} + +/** +* Computes standard deviations. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute a biased standard deviation +* @returns {Array} output array +*/ +function stdev( out, arr, mx, my, bool ) { + var delta; + var M2x; + var M2y; + var N; + var i; + + M2x = 0.0; + M2y = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[i][0] - mx; + M2x += delta * delta; + delta = arr[i][1] - my; + M2y += delta * delta; + } + if ( bool ) { + out[ 0 ] = sqrt( M2x / N ); + out[ 1 ] = sqrt( M2y / N ); + return out; + } + if ( N < 2 ) { + out[ 0 ] = 0.0; + out[ 1 ] = 0.0; + return out; + } + out[ 0 ] = sqrt( M2x / (N-1) ); + out[ 1 ] = sqrt( M2y / (N-1) ); + return out; +} + +/** +* Computes the covariance using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population covariance +* @returns {number} covariance +*/ +function covariance( arr, mx, my, bool ) { + var N; + var C; + var i; + + N = arr.length; + C = 0.0; + for ( i = 0; i < N; i++ ) { + C += ( arr[i][0]-mx ) * ( arr[i][1]-my ); + } + if ( bool ) { + return C / N; + } + if ( N === 1 ) { + return 0.0; + } + return C / (N-1); +} + +/** +* Computes the sample Pearson product-moment correlation coefficient using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population correlation coefficient +* @returns {number} correlation coefficient +*/ +function pcorr( arr, mx, my, bool ) { + var cov; + var sd; + if ( bool === false && arr.length < 2 ) { + return 0.0; + } + sd = stdev( [ 0.0, 0.0 ], arr, mx, my, bool ); + cov = covariance( arr, mx, my, bool ); + return cov / ( sd[0]*sd[1] ); +} + +/** +* Generates a set of sample datasets. +* +* @private +* @param {PositiveInteger} N - number of datasets +* @param {PositiveInteger} M - dataset length +* @param {PositiveInteger} [seed] - PRNG seed +* @returns {ArrayArray} sample datasets +*/ +function datasets( N, M, seed ) { + var data; + var rand; + var tmp; + var i; + var j; + var x; + var y; + + rand = randu.factory({ + 'seed': seed || ( randu()*pow( 2.0, 31 ) )|0 + }); + + // Generate datasets consisting of (x,y) pairs of varying value ranges... + data = []; + for ( i = 0; i < N; i++ ) { + tmp = []; + for ( j = 0; j < M; j++ ) { + x = ( rand() < 0.1 ) ? NaN : rand() * pow( 10.0, i ); + y = ( rand() < 0.1 ) ? NaN : rand() * pow( 10.0, i ); + tmp.push( [ x, y ] ); + } + data.push( tmp ); + } + return data; +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmpcorr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (known means)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr( value, 3.0, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr( 3, value, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr( 3, 3.14, value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmpcorr( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known means)', function test( t ) { + t.equal( typeof incrnanmpcorr( 3, 3.0, 3.14 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving sample Pearson product-moment correlation coefficient incrementally and skip NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var delta; + var means; + var prev; + var data; + var acc; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var x; + var y; + + N = 10; + M = 100; + data = datasets( N, M, randu.seed ); + + // Define the window size: + W = 10; + + // For each dataset, compute the actual and expected correlation coefficients... + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + acc = incrnanmpcorr( W ); + validData = []; + prev = null; + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + means = mean( [ 0.0, 0.0 ], validData ); + expected = pcorr( validData, means[0], means[1], false ); + prev = expected; + } + if ( isnan( expected ) ) { + t.equal( isnan( actual ), true, 'returns NaN for window: '+i ); + } else if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. dataset: '+i+'. window: '+j+'.' ); + } else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.equal( delta < tol, true, 'dataset: '+i+'. window: '+j+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + } + t.end(); +}); + +tape( 'the accumulator function computes a moving sample Pearson product-moment correlation coefficient incrementally (known means) and skip NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var means; + var delta; + var data; + var prev; + var acc; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var x; + var y; + + N = 10; + M = 100; + data = datasets( N, M, randu.seed ); + validData = []; + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + } + } + } + means = mean([0.0, 0.0], validData); + W = 10; + + // For each dataset, compute the actual and expected correlation coefficients... + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + means = mean( [ 0.0, 0.0 ], d ); + acc = incrnanmpcorr( W, means[ 0 ], means[ 1 ] ); + validData = []; + prev = null; + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + expected = pcorr(validData, means[0], means[1], true); + prev = expected; + } + if ( isnan( expected ) ) { + t.equal( isnan( actual ), true, 'dataset: '+i+', window: '+j+' returns NaN as expected' ); + } else if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. dataset: '+i+'. window: '+j+'.' ); + } else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.equal( delta < tol, true, 'dataset: '+i+'. window: '+j+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation coefficient (unknown means) and skips NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var means; + var delta; + var prev; + var data; + var tol; + var acc; + var W; + var N; + var i; + var x; + var y; + + data = [ + [ 2.0, 1.0 ], + [ NaN, 3.14 ], + [ 3.0, -1.0 ], + [ 5.0, -9.5 ] + ]; + N = data.length; + + // Window size: + W = 3; + acc = incrnanmpcorr( W ); + validData = []; + prev = null; + + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + means = mean( [ 0.0, 0.0 ], validData ); + expected = pcorr( validData, means[ 0 ], means[ 1 ], false ); + prev = expected; + } + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. window: '+i+'.' ); + } else { + delta = abs( actual - expected ); + tol = 2.0 * EPS * abs( expected ); + t.equal( delta < tol, true, 'window: '+i+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation coefficient (known means) and skips NaN updates', function test( t ) { + var validData; + var expected; + var actual; + var means; + var delta; + var prev; + var data; + var tol; + var acc; + var W; + var N; + var i; + var x; + var y; + + data = [ + [ 2.0, 1.0 ], + [ NaN, 3.14 ], + [ 3.0, -1.0 ], + [ 5.0, -9.5 ] + ]; + N = data.length; + validData = []; + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + } + } + means = mean( [ 0.0, 0.0 ], validData ); + + // Window size: + W = 3; + acc = incrnanmpcorr( W, means[ 0 ], means[ 1 ] ); + validData = []; + prev = null; + + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( !isnan( x ) && !isnan( y ) ) { + validData.push( [ x, y ] ); + if ( validData.length > W ) { + validData.shift(); + } + } + actual = acc( x, y ); + if ( isnan( x ) || isnan( y ) ) { + expected = prev; + } else { + expected = pcorr( validData, means[ 0 ], means[ 1 ], true ); + prev = expected; + } + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. window: '+i+'.' ); + } else { + delta = abs( actual - expected ); + tol = 2.0 * EPS * abs( expected ); + t.equal( delta < tol, true, 'window: '+i+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmpcorr( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null` (known means)', function test( t ) { + var acc = incrnanmpcorr( 3, 3.0, 3.14 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are unknown, the accumulator function returns `0`', function test( t ) { + var acc = incrnanmpcorr( 3 ); + acc( 2.0, 3.14 ); + t.equal( acc(), 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are known, the accumulator function may not return `0`', function test( t ) { + var acc = incrnanmpcorr( 3, 30.0, -100.0 ); + acc( 2.0, 1.0 ); + t.notEqual( acc(), 0.0, 'does not return 0' ); + t.end(); +}); + +tape( 'if the window size is `1` and the means are unknown, the accumulator function always returns `0`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmpcorr( 1 ); + for ( i = 0; i < 100; i++ ) { + r = acc( randu()*100.0, randu()*100.0 ); + t.equal( r, 0.0, 'returns 0' ); + } + t.end(); +}); + +tape( 'if the window size is `1` and the means are known, the accumulator function may not always return `0`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmpcorr( 1, 500.0, -500.0 ); // means are outside the range of simulated values so the correlation should never be zero + for ( i = 0; i < 100; i++ ) { + r = acc( randu()*100.0, randu()*100.0 ); + t.notEqual( r, 0.0, 'does not return 0' ); + } + t.end(); +}); + +tape( 'the accumulator function skips updates when provided a non-numeric value', function test( t ) { + var acc = incrnanmpcorr( 3 ); + var r; + + acc( 2.0, 1.0 ); + r = acc(); + + t.equal( acc( '5.0', 1.0 ), r, 'returns current value when provided a non-numeric x' ); + t.equal( acc( 5.0, true ), r, 'returns current value when provided a non-numeric y' ); + t.equal( acc( [ 1.0 ], [ 2.0 ] ), r, 'returns current value when provided array values' ); + t.equal( acc( {}, {} ), r, 'returns current value when provided object values' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/README.md b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/README.md new file mode 100644 index 000000000000..b9aae5ebdf8c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/README.md @@ -0,0 +1,209 @@ + + +# incrnanmpcorr2 + +> Compute a moving squared sample [Pearson product-moment correlation coefficient][pearson-correlation] incrementally, ignoring `NaN` values. + +
+ +The [Pearson product-moment correlation coefficient][pearson-correlation] between random variables `X` and `Y` is defined as + + + +```math +\rho_{X,Y} = \frac{\mathop{\mathrm{cov}}(X,Y)}{\sigma_X \sigma_Y} +``` + + + + + +where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations. + +For a sample of size `W`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as + + + +```math +r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \displaystyle\sqrt{\displaystyle\sum_{i=0}^{n-1} (y_i - \bar{y})^2}} +``` + + + + + +The squared sample [Pearson product-moment correlation coefficient][pearson-correlation] is thus defined as the square of the sample [Pearson product-moment correlation coefficient][pearson-correlation]. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmpcorr2 = require( '@stdlib/stats/incr/nanmpcorr2' ); +``` + +#### incrnanmpcorr2( window\[, mx, my] ) + +Returns an accumulator `function` which incrementally computes a moving squared sample [Pearson product-moment correlation coefficient][pearson-correlation], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving squared sample [Pearson product-moment correlation coefficient][pearson-correlation]. + +```javascript +var accumulator = incrnanmpcorr2( 3 ); +``` + +If means are already known, provide `mx` and `my` arguments. + +```javascript +var accumulator = incrnanmpcorr2( 3, 5.0, -3.14 ); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated accumulated value. If not provided input values `x` and `y`, the accumulator function returns the current accumulated value. + +```javascript +var accumulator = incrnanmpcorr2( 3 ); + +var r2 = accumulator(); +// returns null + +// Fill the window with valid pairs: +r2 = accumulator( 2.0, 1.0 ); // [(2.0, 1.0)] +// returns 0.0 + +r2 = accumulator( -5.0, 3.14 ); // [(2.0, 1.0), (-5.0, 3.14)] +// returns ~1.0 + +// NaN input is ignored (window unchanged): +r2 = accumulator( NaN, 3.14 ); // [(2.0, 1.0), (-5.0, 3.14)] +// returns ~1.0 + +// NaN input is ignored (window unchanged): +r2 = accumulator( -5.0, NaN ); // [(2.0, 1.0), (-5.0, 3.14)] +// returns ~1.0 + +// NaN input is ignored (window unchanged): +r2 = accumulator( NaN, NaN ); // [(2.0, 1.0), (-5.0, 3.14)] +// returns ~1.0 + +// Window reaches size W: +r2 = accumulator( 3.0, -1.0 ); // [(2.0, 1.0), (-5.0, 3.14), (3.0, -1.0)] +// returns ~0.86 + +// Window begins sliding (valid pairs only): +r2 = accumulator( 5.0, -9.5 ); // [(-5.0, 3.14), (3.0, -1.0), (5.0, -9.5)] +// returns ~0.74 + +r2 = accumulator( -5.0, 1.5 ); // [(3.0, -1.0), (5.0, -9.5), (-5.0, 1.5)] +// returns ~0.64 + +r2 = accumulator(); +// returns ~0.64 + +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN` for either input value, the update is ignored and the accumulated value remains unchanged. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` valid (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +- In comparison to the sample [Pearson product-moment correlation coefficient][pearson-correlation], the squared sample [Pearson product-moment correlation coefficient][pearson-correlation] is useful for emphasizing strong correlations. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmpcorr2 = require( '@stdlib/stats/incr/nanmpcorr2' ); + +var accumulator; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmpcorr2( 5 ); + +// For each simulated datum, update the moving squared sample correlation coefficient... +for ( i = 0; i < 100; i++ ) { + x = randu() * 100.0; + y = randu() * 100.0; + accumulator( x, y ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +* * * + +## See Also + +- [`@stdlib/stats/incr/mpcorr2`][@stdlib/stats/incr/mpcorr2]: compute a moving squared sample Pearson product-moment correlation coefficient incrementally. + +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +[covariance]: https://en.wikipedia.org/wiki/Covariance + + + +[@stdlib/stats/incr/mpcorr2]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/mpcorr2 + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/benchmark/benchmark.js new file mode 100644 index 000000000000..e1b507e09c8f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/benchmark/benchmark.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmpcorr2 = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmpcorr2( ( i % 5 ) + 1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmpcorr2( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmpcorr2( 5, 3.0, -1.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/img/equation_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/img/equation_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..61e3ef3e3500 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/img/equation_pearson_correlation_coefficient.svg @@ -0,0 +1,48 @@ + +rho Subscript upper X comma upper Y Baseline equals StartFraction c o v left-parenthesis upper X comma upper Y right-parenthesis Over sigma Subscript upper X Baseline sigma Subscript upper Y Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..31facfed161b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg @@ -0,0 +1,126 @@ + +r equals StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis Over StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis squared EndRoot EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/repl.txt new file mode 100644 index 000000000000..b5f2610c7fef --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/repl.txt @@ -0,0 +1,59 @@ + +{{alias}}( W[, mx, my] ) + Returns an accumulator function which incrementally computes a moving + squared sample Pearson product-moment correlation coefficient, ignoring + `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving squared sample correlation coefficient. + + If provided values, the accumulator function returns an updated moving + squared sample correlation coefficient. If not provided values, the + accumulator function returns the current moving squared sample correlation + coefficient. + + As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + mx: number (optional) + Known mean. + + my: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var r2 = accumulator() + null + > r2 = accumulator( 2.0, 1.0 ) + 0.0 + > r2 = accumulator( -5.0, 3.14 ) + ~1.0 + > r2 = accumulator( NaN, 3.14 ) + ~1.0 + > r2 = accumulator( -5.0, NaN ) + ~1.0 + > r2 = accumulator( NaN, NaN ) + ~1.0 + > r2 = accumulator( 3.0, -1.0 ) + ~0.86 + > r2 = accumulator( 5.0, -9.5 ) + ~0.74 + > r2 = accumulator() + ~0.74 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/types/index.d.ts new file mode 100644 index 000000000000..cc6789fb131e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/types/index.d.ts @@ -0,0 +1,98 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated moving squared sample correlation coefficient. +* +* @param x - value +* @param y - value +* @returns updated moving squared sample correlation coefficient +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving squared sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving squared sample correlation coefficient. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @param meanx - mean value +* @param meany - mean value +* @throws first argument must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmpcorr2( 3, -2.0, 10.0 ); +*/ +declare function incrnanmpcorr2( W: number, meanx: number, meany: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes a moving squared sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving squared sample correlation coefficient. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws first argument must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmpcorr2( 3 ); +* +* var r2 = accumulator(); +* // returns null +* +* r2 = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r2 = accumulator( -5.0, 3.14 ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, 3.14 ); +* // returns ~1.0 +* +* r2 = accumulator( -5.0, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( 3.0, -1.0 ); +* // returns ~0.86 +* +* r2 = accumulator( 5.0, -9.5 ); +* // returns ~0.74 +* +* r2 = accumulator(); +* // returns ~0.74 +*/ +declare function incrnanmpcorr2( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmpcorr2; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/types/test.ts new file mode 100644 index 000000000000..9463d8d23d11 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/docs/types/test.ts @@ -0,0 +1,123 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmpcorr2 = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmpcorr2( 3 ); // $ExpectType accumulator + incrnanmpcorr2( 3, 2.5, 4.5 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided non-numeric arguments... +{ + incrnanmpcorr2( 2, '5' ); // $ExpectError + incrnanmpcorr2( 2, true ); // $ExpectError + incrnanmpcorr2( 2, false ); // $ExpectError + incrnanmpcorr2( 2, null ); // $ExpectError + incrnanmpcorr2( 2, undefined ); // $ExpectError + incrnanmpcorr2( 2, [] ); // $ExpectError + incrnanmpcorr2( 2, {} ); // $ExpectError + incrnanmpcorr2( 2, ( x: number ): number => x ); // $ExpectError + + incrnanmpcorr2( '5', 4 ); // $ExpectError + incrnanmpcorr2( true, 4 ); // $ExpectError + incrnanmpcorr2( false, 4 ); // $ExpectError + incrnanmpcorr2( null, 4 ); // $ExpectError + incrnanmpcorr2( undefined, 4 ); // $ExpectError + incrnanmpcorr2( [], 4 ); // $ExpectError + incrnanmpcorr2( {}, 4 ); // $ExpectError + incrnanmpcorr2( ( x: number ): number => x, 4 ); // $ExpectError + + incrnanmpcorr2( '5', 2.5, 3.5 ); // $ExpectError + incrnanmpcorr2( true, 2.5, 3.5 ); // $ExpectError + incrnanmpcorr2( false, 2.5, 3.5 ); // $ExpectError + incrnanmpcorr2( null, 2.5, 3.5 ); // $ExpectError + incrnanmpcorr2( undefined, 2.5, 3.5 ); // $ExpectError + incrnanmpcorr2( [], 2.5, 3.5 ); // $ExpectError + incrnanmpcorr2( {}, 2.5, 3.5 ); // $ExpectError + incrnanmpcorr2( ( x: number ): number => x, 2.5, 3.5 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmpcorr2(); // $ExpectError + incrnanmpcorr2( 2, 3 ); // $ExpectError + incrnanmpcorr2( 2, 2, 3, 4 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmpcorr2( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The function returns an accumulator function which returns an accumulated result (known means)... +{ + const acc = incrnanmpcorr2( 3, 2, -3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmpcorr2( 3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)... +{ + const acc = incrnanmpcorr2( 3, 2, -3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/examples/index.js new file mode 100644 index 000000000000..1a43ab49ada4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/examples/index.js @@ -0,0 +1,45 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmpcorr2 = require( './../lib' ); + +var accumulator; +var r2; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmpcorr2( 5 ); + +// For each simulated datum, update the moving squared sample correlation coefficient... +console.log( '\nx\ty\tr^2\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + y = randu() * 100.0; + } else { + x = randu() * 100.0; + y = randu() * 100.0; + } + r2 = accumulator( x, y ); + console.log( '%d\t%d\t%d', x.toFixed( 4 ), y.toFixed( 4 ), (r2 === null) ? NaN : r2.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/lib/index.js new file mode 100644 index 000000000000..311d10efd6db --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/lib/index.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving squared sample Pearson product-moment correlation coefficient incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmpcorr2 +* +* @example +* var incrnanmpcorr2 = require( '@stdlib/stats/incr/nanmpcorr2' ); +* +* var accumulator = incrnanmpcorr2( 3 ); +* +* var r2 = accumulator(); +* // returns null +* +* r2 = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r2 = accumulator( -5.0, 3.14 ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, 3.14 ); +* // returns ~1.0 +* +* r2 = accumulator( -5.0, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( 3.0, -1.0 ); +* // returns ~0.86 +* +* r2 = accumulator( 5.0, -9.5 ); +* // returns ~0.74 +* +* r2 = accumulator(); +* // returns ~0.74 +*/ + +// MODULES // + +var incrnanmpcorr2 = require( './main.js' ); + + +// EXPORTS // + +module.exports = incrnanmpcorr2; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/lib/main.js new file mode 100644 index 000000000000..15c2f3e0c1d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/lib/main.js @@ -0,0 +1,104 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmpcorr2 = require( '@stdlib/stats/incr/mpcorr2' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving squared sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @param {number} [meanx] - mean value +* @param {number} [meany] - mean value +* @throws {TypeError} first argument must be a positive integer +* @throws {TypeError} second argument must be a number +* @throws {TypeError} third argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmpcorr2( 3 ); +* +* var r2 = accumulator(); +* // returns null +* +* r2 = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r2 = accumulator( -5.0, 3.14 ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, 3.14 ); +* // returns ~1.0 +* +* r2 = accumulator( -5.0, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( 3.0, -1.0 ); +* // returns ~0.86 +* +* r2 = accumulator( 5.0, -9.5 ); +* // returns ~0.74 +* +* r2 = accumulator(); +* // returns ~0.74 +* +* @example +* var accumulator = incrnanmpcorr2( 3, -2.0, 10.0 ); +*/ +function incrnanmpcorr2( W, meanx, meany ) { + var acc; + if ( arguments.length > 2 ) { + acc = incrmpcorr2( W, meanx, meany ); + } else { + acc = incrmpcorr2( W ); + } + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated accumulated value. If not provided input values, the accumulator function returns the current accumulated value. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} squared sample correlation coefficient or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 ) { + return acc(); + } + if ( arguments.length < 2 || isnan( x ) || isnan( y ) ) { + return acc(); + } + return acc( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmpcorr2; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/package.json b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/package.json new file mode 100644 index 000000000000..5655d1ba2c4d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/package.json @@ -0,0 +1,82 @@ +{ + "name": "@stdlib/stats/incr/nanmpcorr2", + "version": "0.0.0", + "description": "Compute a moving squared sample Pearson product-moment correlation coefficient incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "covariance", + "sample covariance", + "variance", + "unbiased", + "var", + "correlation", + "corr", + "pcorr", + "pearson", + "product-moment", + "r-squared", + "r2", + "bivariate", + "incremental", + "accumulator", + "moving covariance", + "moving correlation", + "sliding window", + "sliding", + "window", + "moving", + "rolling", + "nan" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/test/test.js new file mode 100644 index 000000000000..8e90798cfeb9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorr2/test/test.js @@ -0,0 +1,667 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var zeros = require( '@stdlib/array/base/zeros' ); +var incrnanmpcorr2 = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Computes sample means using Welford's algorithm. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @returns {Array} output array +*/ +function mean( out, arr ) { + var delta; + var mx; + var my; + var N; + var i; + + mx = 0.0; + my = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[i][0] - mx; + mx += delta / N; + delta = arr[i][1] - my; + my += delta / N; + } + out[ 0 ] = mx; + out[ 1 ] = my; + return out; +} + +/** +* Computes standard deviations. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute a biased standard deviation +* @returns {Array} output array +*/ +function stdev( out, arr, mx, my, bool ) { + var delta; + var M2x; + var M2y; + var N; + var i; + + M2x = 0.0; + M2y = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[i][0] - mx; + M2x += delta * delta; + delta = arr[i][1] - my; + M2y += delta * delta; + } + if ( bool ) { + out[ 0 ] = sqrt( M2x / N ); + out[ 1 ] = sqrt( M2y / N ); + return out; + } + if ( N < 2 ) { + out[ 0 ] = 0.0; + out[ 1 ] = 0.0; + return out; + } + out[ 0 ] = sqrt( M2x / (N-1) ); + out[ 1 ] = sqrt( M2y / (N-1) ); + return out; +} + +/** +* Computes the covariance using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population covariance +* @returns {number} covariance +*/ +function covariance( arr, mx, my, bool ) { + var N; + var C; + var i; + + N = arr.length; + C = 0.0; + for ( i = 0; i < N; i++ ) { + C += ( arr[i][0]-mx ) * ( arr[i][1]-my ); + } + if ( bool ) { + return C / N; + } + if ( N === 1 ) { + return 0.0; + } + return C / (N-1); +} + +/** +* Computes the squared sample Pearson product-moment correlation coefficient using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population correlation coefficient +* @returns {number} squared correlation coefficient +*/ +function pcorr2( arr, mx, my, bool ) { + var cov; + var sd; + var r; + if ( bool === false && arr.length < 2 ) { + return 0.0; + } + sd = stdev( [ 0.0, 0.0 ], arr, mx, my, bool ); + cov = covariance( arr, mx, my, bool ); + r = cov / ( sd[0]*sd[1] ); + return r * r; +} + +/** +* Generates a set of sample datasets. +* +* @private +* @param {PositiveInteger} N - number of datasets +* @param {PositiveInteger} M - dataset length +* @param {PositiveInteger} [seed] - PRNG seed +* @returns {ArrayArray} sample datasets +*/ +function datasets( N, M, seed ) { + var data; + var rand; + var tmp; + var i; + var j; + + rand = randu.factory({ + 'seed': seed || ( randu()*pow( 2.0, 31 ) )|0 + }); + + // Generate datasets consisting of (x,y) pairs of varying value ranges... + data = zeros( N ); + for ( i = 0; i < N; i++ ) { + tmp = zeros( M ); + for ( j = 0; j < M; j++ ) { + tmp[ j ] = [ + rand() * pow( 10.0, i ), + rand() * pow( 10.0, i ) + ]; + } + data[ i ] = tmp; + } + return data; +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmpcorr2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr2( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (known means)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr2( value, 3.0, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr2( 3, value, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorr2( 3, 3.14, value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmpcorr2( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known means)', function test( t ) { + t.strictEqual( typeof incrnanmpcorr2( 3, 3.0, 3.14 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving squared sample Pearson product-moment correlation coefficient incrementally', function test( t ) { + var expected; + var actual; + var delta; + var means; + var valid; + var data; + var acc; + var arr; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var x; + var y; + + N = 10; + M = 100; + data = datasets( N, M, 123456 ); + + // Define the window size: + W = 10; + + // For each dataset, compute the actual and expected squared correlation coefficients... + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + valid = []; + + acc = incrnanmpcorr2( W ); + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + + // Inject NaN: + if ( j % 7 === 0 ) { + x = NaN; + } + if ( j % 11 === 0 ) { + y = NaN; + } + + actual = acc( x, y ); + + // Track valid (x,y) pairs: + if ( x === x && y === y ) { + valid.push( [ x, y ] ); + } + + // Determine expected window: + if ( valid.length > W ) { + arr = valid.slice( valid.length - W ); + } else { + arr = valid; + } + + // If insufficient data, expect null: + if ( arr.length === 0 ) { + t.strictEqual( actual, null, 'returns null when insufficient valid data. dataset: '+i+'. step: '+j+'.' ); + continue; + } + + means = mean( [ 0.0, 0.0 ], arr ); + expected = pcorr2( arr, means[ 0 ], means[ 1 ], false ); + + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value. dataset: '+i+'. window: '+j+'.' ); + } else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.strictEqual( delta < tol, true, 'dataset: '+i+'. window: '+j+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + } + t.end(); +}); + +tape( 'the accumulator function computes a moving squared sample Pearson product-moment correlation coefficient incrementally (known means)', function test( t ) { + var expected; + var actual; + var means; + var delta; + var valid; + var data; + var acc; + var arr; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var x; + var y; + + N = 10; + M = 100; + data = datasets( N, M, 123456 ); + + // Define the window size: + W = 10; + + // For each dataset, compute the actual and expected squared correlation coefficients... + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + valid = []; + means = mean( [ 0.0, 0.0 ], d ); + acc = incrnanmpcorr2( W, means[ 0 ], means[ 1 ] ); + for ( j = 0; j < M; j++ ) { + x = d[ j ][ 0 ]; + y = d[ j ][ 1 ]; + + // Inject NaNs: + if ( j % 7 === 0 ) { + x = NaN; + } + if ( j % 11 === 0 ) { + y = NaN; + } + + actual = acc( x, y ); + + // Track valid (x,y) pairs: + if ( x === x && y === y ) { + valid.push( [ x, y ] ); + } + + // Determine expected window: + if ( valid.length > W ) { + arr = valid.slice( valid.length - W ); + } + else { + arr = valid; + } + + // Insufficient valid data: + if ( arr.length === 0 ) { + t.strictEqual( actual, null, 'returns null when insufficient valid data. dataset: '+i+'. step: '+j+'.' ); + continue; + } + + expected = pcorr2( arr, means[ 0 ], means[ 1 ], true ); + + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value. dataset: '+i+'. step: '+j+'.' ); + } + else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.strictEqual( delta < tol, true, 'dataset: '+i+'. step: '+j+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current squared sample correlation coefficient (unknown means)', function test( t ) { + var expected; + var actual; + var means; + var delta; + var data; + var tol; + var acc; + var W; + var N; + var d; + var i; + + data = [ + [ 2.0, 1.0 ], + [ -5.0, 3.14 ], + [ 3.0, -1.0 ], + [ 5.0, -9.5 ] + ]; + N = data.length; + + // Window size: + W = 3; + + acc = incrnanmpcorr2( W ); + for ( i = 0; i < N; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + actual = acc(); + if ( i < W-1 ) { + d = data.slice( 0, i+1 ); + } else { + d = data.slice( i-W+1, i+1 ); + } + means = mean( [ 0.0, 0.0 ], d ); + expected = pcorr2( d, means[ 0 ], means[ 1 ], false ); + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value. window: '+i+'.' ); + } else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.strictEqual( delta < tol, true, 'window: '+i+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current squared sample correlation coefficient (unknown means, ignoring NaNs)', function test( t ) { + var expected; + var actual; + var means; + var delta; + var valid; + var tol; + var acc; + var arr; + var d; + var W; + var N; + var i; + var x; + var y; + + d = [ + [ 2.0, 1.0 ], + [ -5.0, 3.14 ], + [ 3.0, -1.0 ], + [ 5.0, -9.5 ] + ]; + N = d.length; + + // Window size: + W = 3; + + acc = incrnanmpcorr2( W ); + valid = []; + + for ( i = 0; i < N; i++ ) { + x = d[ i ][ 0 ]; + y = d[ i ][ 1 ]; + + // Inject NaN: + if ( i === 1 ) { + x = NaN; + } + + acc( x, y ); + actual = acc(); + + // Track valid pairs: + if ( x === x && y === y ) { + valid.push( [ x, y ] ); + } + + // Determine expected window: + if ( valid.length > W ) { + arr = valid.slice( valid.length - W ); + } + else { + arr = valid; + } + + // No valid data: + if ( arr.length === 0 ) { + t.strictEqual( actual, null, 'returns null when insufficient valid data. step: '+i+'.' ); + continue; + } + + // One valid pair (unknown means → 0): + if ( arr.length === 1 ) { + t.strictEqual( actual, 0.0, 'returns 0 when only one valid observation is available. step: '+i+'.' ); + continue; + } + + means = mean( [ 0.0, 0.0 ], arr ); + expected = pcorr2( arr, means[ 0 ], means[ 1 ], false ); + + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value. step: '+i+'.' ); + } + else { + delta = abs( actual - expected ); + tol = 5.0e5 * EPS * abs( expected ); + t.strictEqual( delta < tol, true, 'step: '+i+'. expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmpcorr2( 3 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null` (known means)', function test( t ) { + var acc = incrnanmpcorr2( 3, 3.0, 3.14 ); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are unknown, the accumulator function returns `0`', function test( t ) { + var acc = incrnanmpcorr2( 3 ); + acc( 2.0, 3.14 ); + t.strictEqual( acc(), 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are known, the accumulator function may not return `0`', function test( t ) { + var acc = incrnanmpcorr2( 3, 30.0, -100.0 ); + acc( 2.0, 1.0 ); + t.notEqual( acc(), 0.0, 'does not return 0' ); + t.end(); +}); + +tape( 'if the window size is `1` and the means are unknown, the accumulator function always returns `0`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmpcorr2( 1 ); + for ( i = 0; i < 100; i++ ) { + r = acc( randu()*100.0, randu()*100.0 ); + t.strictEqual( r, 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'if the window size is `1` and the means are known, the accumulator function may not always return `0`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmpcorr2( 1, 500.0, -500.0 ); // means are outside the range of simulated values so the correlation should never be zero + for ( i = 0; i < 100; i++ ) { + r = acc( randu()*100.0, randu()*100.0 ); + t.notEqual( r, 0.0, 'does not return 0' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/README.md b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/README.md new file mode 100644 index 000000000000..8e9a2c512dab --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/README.md @@ -0,0 +1,168 @@ + + +# incrnanmpcorrdist + +> Compute a moving [sample Pearson product-moment correlation distance][pearson-correlation] incrementally, ignoring `NaN` values. + +
+ +The [sample Pearson product-moment correlation distance][pearson-correlation] is defined as + + + +```math +d_{x,y} = 1 - r_{x,y} = 1 - \frac{\mathop{\mathrm{cov_n(x,y)}}}{\sigma_x \sigma_y} +``` + + + +where `r` is the [sample Pearson product-moment correlation coefficient][pearson-correlation], `cov(x,y)` is the sample covariance, and `σ` corresponds to the sample standard deviation. As `r` resides on the interval `[-1,1]`, `d` resides on the interval `[0,2]`. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmpcorrdist = require( '@stdlib/stats/incr/nanmpcorrdist' ); +``` + +#### incrnanmpcorrdist( window\[, mx, my] ) + +Returns an accumulator `function` which incrementally computes a moving [sample Pearson product-moment correlation distance][pearson-correlation], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [sample Pearson product-moment correlation distance][pearson-correlation]. + +```javascript +var accumulator = incrnanmpcorrdist( 3 ); +``` + +If means are already known, provide `mx` and `my` arguments. + +```javascript +var accumulator = incrnanmpcorrdist( 3, 5.0, -3.14 ); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated [sample Pearson product-moment correlation distance][pearson-correlation]. If not provided input values `x` and `y`, the accumulator function returns the current [sample Pearson product-moment correlation distance][pearson-correlation]. + +```javascript +var accumulator = incrnanmpcorrdist( 3 ); + +var r = accumulator(); +// returns null + +// Fill the window... +r = accumulator( 2.0, 1.0 ); // [(2.0, 1.0)] +// returns 1.0 + +r = accumulator( NaN, 3.0 ); // [(2.0, 1.0)] +// returns 1.0 + +r = accumulator( 4.0, NaN ); // [(2.0, 1.0)] +// returns 1.0 + +r = accumulator( NaN, NaN ); // [(2.0, 1.0)] +// returns 1.0 + +r = accumulator( 5.0, 2.0 ); // [(2.0, 1.0), (5.0, 2.0)] +// returns 0.0 + +r = accumulator(); +// returns 0.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN`, the value is ignored and the accumulated value is the current accumulated value. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +- Due to limitations inherent in representing numeric values using floating-point format (i.e., the inability to represent numeric values with infinite precision), the [sample correlation distance][pearson-correlation] between perfectly correlated random variables may **not** be `0` or `2`. In fact, the [sample correlation distance][pearson-correlation] is **not** guaranteed to be strictly on the interval `[0,2]`. Any computed distance should, however, be within floating-point roundoff error. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmpcorrdist = require( '@stdlib/stats/incr/nanmpcorrdist' ); + +var accumulator; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmpcorrdist( 5 ); + +// For each simulated datum, update the moving sample correlation distance... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } + else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } + else { + y = randu() * 100.0; + } + accumulator( x, y ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/benchmark/benchmark.js new file mode 100644 index 000000000000..a6f827abbe60 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/benchmark/benchmark.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmpcorrdist = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmpcorrdist( ( i % 5 ) + 1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmpcorrdist( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmpcorrdist( 5, 3.0, -1.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/img/equation_pearson_distance.svg b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/img/equation_pearson_distance.svg new file mode 100644 index 000000000000..6df633f17b81 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/img/equation_pearson_distance.svg @@ -0,0 +1,70 @@ + +d Subscript x comma y Baseline equals 1 minus r Subscript x comma y Baseline equals 1 minus StartFraction normal c normal o normal v Subscript normal n Baseline left-parenthesis normal x comma normal y right-parenthesis Over sigma Subscript x Baseline sigma Subscript y Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/repl.txt new file mode 100644 index 000000000000..e9488748c4ce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/repl.txt @@ -0,0 +1,64 @@ + +{{alias}}( W[, mx, my] ) + Returns an accumulator function which incrementally computes a moving + sample Pearson product-moment correlation distance, ignoring + `NaN` values. + + The correlation distance is defined as one minus the Pearson product-moment + correlation coefficient and, thus, resides on the interval [0,2]. + + However, due to limitations inherent in representing numeric values using + floating-point format (i.e., the inability to represent numeric values with + infinite precision), the correlation distance between perfectly correlated + random variables may *not* be `0` or `2`. In fact, the correlation distance + is *not* guaranteed to be strictly on the interval [0,2]. Any computed + distance should, however, be within floating-point roundoff error. + + The `W` parameter defines the number of values over which to compute the + moving sample correlation distance. + + If provided values, the accumulator function returns an updated moving + sample correlation distance. If not provided values, the accumulator + function returns the current moving sample correlation distance. + + As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + mx: number (optional) + Known mean. + + my: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var d = accumulator() + null + > d = accumulator( 2.0, 1.0 ) + 1.0 + > d = accumulator( NaN, 3.0 ) + 1.0 + > d = accumulator( 4.0, NaN ) + 1.0 + > d = accumulator( NaN, NaN ) + 1.0 + > d = accumulator( 5.0, 2.0 ) + 0.0 + > d = accumulator() + 0.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/types/index.d.ts new file mode 100644 index 000000000000..537a720deaca --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/types/index.d.ts @@ -0,0 +1,97 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided input values, the accumulator function returns an updated moving sample Pearson product-moment correlation distance. If not provided input values, the accumulator function returns the current moving sample correlation distance. +* +* ## Notes +* +* - The correlation distance is defined as one minus the Pearson product-moment correlation coefficient and, thus, resides on the interval [0,2]. +* - If provided `NaN`, the value is ignored and the returned value is the current accumulated value. +* +* @param x - value +* @param y - value +* @returns updated moving sample correlation distance +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving sample Pearson product-moment correlation distance, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving sample correlation distance. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @param mx - known mean of `x` +* @param my - known mean of `y` +* @throws first argument must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmpcorrdist( 3, -2.0, 10.0 ); +*/ +declare function incrnanmpcorrdist( W: number, mx: number, my: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes a moving sample Pearson product-moment correlation distance, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving sample correlation distance. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws first argument must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmpcorrdist( 3 ); +* +* var d = accumulator(); +* // returns null +* +* d = accumulator( 2.0, 1.0 ); +* // returns 1.0 +* +* d = accumulator( NaN, 3.0 ); +* // returns 1.0 +* +* d = accumulator( 4.0, NaN ); +* // returns 1.0 +* +* d = accumulator( NaN, NaN ); +* // returns 1.0 +* +* d = accumulator( 5.0, 2.0 ); +* // returns 0.0 +* +* d = accumulator(); +* // returns 0.0 +*/ +declare function incrnanmpcorrdist( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmpcorrdist; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/types/test.ts new file mode 100644 index 000000000000..44b64f20f08c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/docs/types/test.ts @@ -0,0 +1,123 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmpcorrdist = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmpcorrdist( 3 ); // $ExpectType accumulator + incrnanmpcorrdist( 3, 2.5, 4.5 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided non-numeric arguments... +{ + incrnanmpcorrdist( 2, '5' ); // $ExpectError + incrnanmpcorrdist( 2, true ); // $ExpectError + incrnanmpcorrdist( 2, false ); // $ExpectError + incrnanmpcorrdist( 2, null ); // $ExpectError + incrnanmpcorrdist( 2, undefined ); // $ExpectError + incrnanmpcorrdist( 2, [] ); // $ExpectError + incrnanmpcorrdist( 2, {} ); // $ExpectError + incrnanmpcorrdist( 2, ( x: number ): number => x ); // $ExpectError + + incrnanmpcorrdist( '5', 4 ); // $ExpectError + incrnanmpcorrdist( true, 4 ); // $ExpectError + incrnanmpcorrdist( false, 4 ); // $ExpectError + incrnanmpcorrdist( null, 4 ); // $ExpectError + incrnanmpcorrdist( undefined, 4 ); // $ExpectError + incrnanmpcorrdist( [], 4 ); // $ExpectError + incrnanmpcorrdist( {}, 4 ); // $ExpectError + incrnanmpcorrdist( ( x: number ): number => x, 4 ); // $ExpectError + + incrnanmpcorrdist( '5', 2.5, 3.5 ); // $ExpectError + incrnanmpcorrdist( true, 2.5, 3.5 ); // $ExpectError + incrnanmpcorrdist( false, 2.5, 3.5 ); // $ExpectError + incrnanmpcorrdist( null, 2.5, 3.5 ); // $ExpectError + incrnanmpcorrdist( undefined, 2.5, 3.5 ); // $ExpectError + incrnanmpcorrdist( [], 2.5, 3.5 ); // $ExpectError + incrnanmpcorrdist( {}, 2.5, 3.5 ); // $ExpectError + incrnanmpcorrdist( ( x: number ): number => x, 2.5, 3.5 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmpcorrdist(); // $ExpectError + incrnanmpcorrdist( 2, 2 ); // $ExpectError + incrnanmpcorrdist( 2, 2, 3, 4 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmpcorrdist( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The function returns an accumulator function which returns an accumulated result (known means)... +{ + const acc = incrnanmpcorrdist( 3, 2, -3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmpcorrdist( 3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)... +{ + const acc = incrnanmpcorrdist( 3, 2, -3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/examples/index.js new file mode 100644 index 000000000000..ff2990e75235 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/examples/index.js @@ -0,0 +1,51 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmpcorrdist = require( './../lib' ); + +var accumulator; +var d; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanmpcorrdist( 5 ); + +// For each simulated datum, update the moving sample correlation distance... +console.log( '\nx\ty\tCorrelation Distance\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } + else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } + else { + y = randu() * 100.0; + } + d = accumulator( x, y ); + console.log( '%s\t%s\t%s', ( isnan( x ) ) ? 'NaN' : x.toFixed( 4 ), ( isnan( y ) ) ? 'NaN' : y.toFixed( 4 ), ( d === null ) ? 'null' : d.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/lib/index.js new file mode 100644 index 000000000000..bcf10fcfa925 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving sample Pearson product-moment correlation distance incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmpcorrdist +* +* @example +* var incrnanmpcorrdist = require( '@stdlib/stats/incr/nanmpcorrdist' ); +* +* var accumulator = incrnanmpcorrdist( 3 ); +* +* var d = accumulator(); +* // returns null +* +* d = accumulator( 2.0, 1.0 ); +* // returns 1.0 +* +* d = accumulator( NaN, 3.0 ); +* // returns 1.0 +* +* d = accumulator( 4.0, NaN ); +* // returns 1.0 +* +* d = accumulator( NaN, NaN ); +* // returns 1.0 +* +* d = accumulator( 5.0, 2.0 ); +* // returns 0.0 +* +* d = accumulator(); +* // returns 0.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/lib/main.js new file mode 100644 index 000000000000..661b0ce98644 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/lib/main.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmpcorrdist = require( '@stdlib/stats/incr/mpcorrdist' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving sample Pearson product-moment correlation distance, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @param {number} [mx] - known mean of `x` +* @param {number} [my] - known mean of `y` +* @throws {TypeError} first argument must be a positive integer +* @throws {TypeError} second argument must be a number +* @throws {TypeError} third argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmpcorrdist( 3 ); +* +* var d = accumulator(); +* // returns null +* +* d = accumulator( 2.0, 1.0 ); +* // returns 1.0 +* +* d = accumulator( NaN, 3.0 ); +* // returns 1.0 +* +* d = accumulator( 4.0, NaN ); +* // returns 1.0 +* +* d = accumulator( NaN, NaN ); +* // returns 1.0 +* +* d = accumulator( 5.0, 2.0 ); +* // returns 0.0 +* +* d = accumulator(); +* // returns 0.0 +* +* @example +* var accumulator = incrnanmpcorrdist( 3, -2.0, 10.0 ); +*/ +function incrnanmpcorrdist( W, mx, my ) { + var d; + if ( arguments.length > 2 ) { + d = incrmpcorrdist( W, mx, my ); + } else { + d = incrmpcorrdist( W ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated moving sample Pearson product-moment correlation distance. If not provided a value, the accumulator function returns the current moving sample Pearson product-moment correlation distance. + * + * @private + * @param {number} [x] - new value + * @param {number} [y] - new value + * @returns {(number|null)} moving sample Pearson product-moment correlation distance or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return d(); + } + + return d( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmpcorrdist; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/package.json b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/package.json new file mode 100644 index 000000000000..b6c26b50d0d6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/package.json @@ -0,0 +1,78 @@ +{ + "name": "@stdlib/stats/incr/nanmpcorrdist", + "version": "0.0.0", + "description": "Compute a moving sample Pearson product-moment correlation distance incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "covariance", + "sample covariance", + "variance", + "correlation", + "corr", + "pcorrdist", + "pearson", + "product-moment", + "distance", + "bivariate", + "incremental", + "accumulator", + "moving correlation", + "sliding window", + "sliding", + "window", + "moving", + "rolling", + "nan" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/test/test.js new file mode 100644 index 000000000000..e157c60eb45e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpcorrdist/test/test.js @@ -0,0 +1,671 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var pow = require( '@stdlib/math/base/special/pow' ); +var sqrt = require( '@stdlib/math/base/special/sqrt' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var min = require( '@stdlib/math/base/special/min' ); +var incrnanmpcorrdist = require( './../lib' ); + + +// FUNCTIONS // + +/** +* Computes sample means using Welford's algorithm. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @returns {Array} output array +*/ +function mean( out, arr ) { + var delta; + var mx; + var my; + var N; + var i; + + mx = 0.0; + my = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[ i ][ 0 ] - mx; + mx += delta / N; + delta = arr[ i ][ 1 ] - my; + my += delta / N; + } + out[ 0 ] = mx; + out[ 1 ] = my; + return out; +} + +/** +* Computes standard deviations. +* +* @private +* @param {Array} out - output array +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute a biased standard deviation +* @returns {Array} output array +*/ +function stdev( out, arr, mx, my, bool ) { + var delta; + var M2x; + var M2y; + var N; + var i; + + M2x = 0.0; + M2y = 0.0; + + N = 0; + for ( i = 0; i < arr.length; i++ ) { + N += 1; + delta = arr[ i ][ 0 ] - mx; + M2x += delta * delta; + delta = arr[ i ][ 1 ] - my; + M2y += delta * delta; + } + if ( bool ) { + out[ 0 ] = sqrt( M2x / N ); + out[ 1 ] = sqrt( M2y / N ); + return out; + } + if ( N < 2 ) { + out[ 0 ] = 0.0; + out[ 1 ] = 0.0; + return out; + } + out[ 0 ] = sqrt( M2x / ( N - 1 ) ); + out[ 1 ] = sqrt( M2y / ( N - 1 ) ); + return out; +} + +/** +* Computes the covariance using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population covariance +* @returns {number} covariance +*/ +function covariance( arr, mx, my, bool ) { + var N; + var C; + var i; + + N = arr.length; + C = 0.0; + for ( i = 0; i < N; i++ ) { + C += ( arr[ i ][ 0 ] - mx ) * ( arr[ i ][ 1 ] - my ); + } + if ( bool ) { + return C / N; + } + if ( N === 1 ) { + return 0.0; + } + return C / ( N - 1 ); +} + +/** +* Computes the sample Pearson product-moment correlation distance using textbook formula. +* +* @private +* @param {ArrayArray} arr - input array +* @param {number} mx - `x` mean +* @param {number} my - `y` mean +* @param {boolean} bool - boolean indicating whether to compute the population correlation distance +* @returns {number} correlation distance +*/ +function pcorrdist( arr, mx, my, bool ) { + var cov; + var sd; + var d; + if ( bool === false && arr.length < 2 ) { + return 1.0; + } + sd = stdev( [ 0.0, 0.0 ], arr, mx, my, bool ); + cov = covariance( arr, mx, my, bool ); + d = 1.0 - ( cov / ( sd[ 0 ] * sd[ 1 ] ) ); + if ( d < 0.0 ) { + return 0.0; + } + if ( d > 2.0 ) { + return 2.0; + } + return d; +} + +/** +* Generates a set of sample datasets. +* +* @private +* @param {PositiveInteger} N - number of datasets +* @param {PositiveInteger} M - dataset length +* @param {PositiveInteger} [seed] - PRNG seed +* @returns {ArrayArray} sample datasets +*/ +function nandatasets( N, M, seed ) { + var data; + var rand; + var tmp; + var i; + var j; + + rand = randu.factory({ + 'seed': seed || ( randu() * pow( 2.0, 31 ) )|0 + }); + + // Generate datasets consisting of (x,y) pairs of varying value ranges, where some of the pairs may contain `(NaN, y)`, `(x, NaN)`, or `(NaN, NaN)`... + data = []; + for ( i = 0; i < N; i++ ) { + tmp = []; + for ( j = 0; j < M; j++ ) { + tmp.push([ + ( rand() < 0.2 ) ? NaN : rand() * pow( 10.0, i ), + ( rand() < 0.2 ) ? NaN : rand() * pow( 10.0, i ) + ]); + } + data.push( tmp ); + } + return data; +} + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmpcorrdist, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorrdist( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (known means)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorrdist( value, 3.0, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorrdist( 3, value, 3.14 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided '+values[ i ] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmpcorrdist( 3, 3.14, value ); + }; + } +}); + +tape( 'the function properly ignores NaN values in x and y inputs', function test( t ) { + var result; + var acc; + + acc = incrnanmpcorrdist( 3, 3.14, 0.0 ); + result = acc(); + + t.ok( !isnan( result ), 'result should not be NaN' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmpcorrdist( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known means)', function test( t ) { + t.equal( typeof incrnanmpcorrdist( 3, 3.0, 3.14 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving sample Pearson product-moment correlation distance incrementally', function test( t ) { + var countNonNanPairs; + var expected; + var actual; + var delta; + var means; + var data; + var acc; + var arr; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var k; + + N = 10; + M = 100; + data = nandatasets( N, M, randu.seed ); + + t.pass( 'seed: ' + randu.seed ); + + // Define the window size: + W = 10; + + // For each dataset, compute the actual and expected correlation distances... + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + + acc = incrnanmpcorrdist( W ); + countNonNanPairs = 0; + for ( j = 0; j < M; j++ ) { + actual = acc( d[ j ][ 0 ], d[ j ][ 1 ] ); + countNonNanPairs += ( !isnan( d[ j ][ 0 ] ) && !isnan( d[ j ][ 1 ] ) ) ? 1 : 0; + + arr = []; + k = j; + while ( arr.length < min( countNonNanPairs, W ) && k >= 0 ) { + if ( !isnan( d[ k ][ 0 ] ) && !isnan( d[ k ][ 1 ] ) ) { + arr.push( d[ k ] ); + } + k -= 1; + } + + if ( arr.length > 0 ) { + means = mean( [ 0.0, 0.0 ], arr ); + } else { + means = null; + } + + if ( arr.length > 0 ) { + expected = pcorrdist( arr, means[ 0 ], means[ 1 ], false ); + } else { + expected = null; + } + + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. dataset: ' + i + '. window: ' + j + '.' ); + } else { + if ( actual < 0.0 ) { + actual = 0.0; // NOTE: this addresses occasional negative values due to accumulated floating-point error. Based on observation, typically `|actual| ≅ |expected|`, but `actual < 0` and `expected > 0`, suggesting that a sign got "flipped" along the way due to, e.g., operations which theoretically should compute to the same value, but do not due to floating-point error. + } + delta = abs( actual - expected ); + if ( expected === 0.0 || actual === 0.0 ) { + tol = 10.0 * EPS; + } else { + tol = 1.0e6 * EPS * abs( expected ); + } + t.equal( delta <= tol, true, 'dataset: ' + i + '. window: ' + j + '. expected: ' + expected + '. actual: ' + actual + '. tol: ' + tol + '. delta: ' + delta + '.' ); + } + } + } + t.end(); +}); + +tape( 'the accumulator function computes a moving sample Pearson product-moment correlation distance incrementally (known means)', function test( t ) { + var countNonNanPairs; + var filteredArr; + var expected; + var actual; + var means; + var delta; + var data; + var acc; + var arr; + var tol; + var d; + var N; + var M; + var W; + var i; + var j; + var k; + + N = 10; + M = 100; + data = nandatasets( N, M, randu.seed ); + + t.pass( 'seed: ' + randu.seed ); + + // Define the window size: + W = 10; + + // For each dataset, compute the actual and expected correlation distances... + function isNotNaN( pair ) { + return !isnan( pair[ 0 ] ) && !isnan( pair[ 1 ] ); + } + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + filteredArr = d.filter( isNotNaN ); + if ( filteredArr.length > 0 ) { + means = mean( [ 0.0, 0.0 ], filteredArr ); + } else { + means = null; + } + acc = incrnanmpcorrdist( W, means[ 0 ], means[ 1 ] ); + countNonNanPairs = 0; + for ( j = 0; j < M; j++ ) { + actual = acc( d[ j ][ 0 ], d[ j ][ 1 ] ); + countNonNanPairs += ( !isnan( d[ j ][ 0 ] ) && !isnan( d[ j ][ 1 ] ) ) ? 1 : 0; + + arr = []; + k = j; + while ( arr.length < min( countNonNanPairs, W ) && k >= 0 ) { + if ( !isnan( d[ k ][ 0 ] ) && !isnan( d[ k ][ 1 ] ) ) { + arr.push( d[ k ] ); + } + k -= 1; + } + + if ( means !== null && arr.length > 0 ) { + expected = pcorrdist( arr, means[ 0 ], means[ 1 ], true ); + } else { + expected = null; + } + + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. dataset: ' + i + '. window: ' + j + '.' ); + } else { + delta = abs( actual - expected ); + tol = 1.0e6 * EPS * abs( expected ); + t.equal( delta <= tol, true, 'dataset: ' + i + '. window: ' + j + '. expected: ' + expected + '. actual: ' + actual + '. tol: ' + tol + '. delta: ' + delta + '.' ); + } + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation distance (unknown means)', function test( t ) { + var expected; + var actual; + var means; + var delta; + var data; + var tol; + var acc; + var W; + var N; + var d; + var i; + + data = [ + [ 2.0, 1.0 ], + [ -5.0, NaN ], + [ 3.0, -1.0 ], + [ NaN, NaN ] + ]; + N = data.length; + + // Window size: + W = 4; + + acc = incrnanmpcorrdist( W ); + for ( i = 0; i < N; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + actual = acc(); + if ( i < W - 1 ) { + d = data.slice( 0, i + 1 ); + } else { + d = data.slice( i - W + 1, i + 1 ); + } + d = d.filter( function isNotNaN( pair ) { + return !isnan( pair[ 0 ] ) && !isnan( pair[ 1 ] ); + }); + + if ( d.length > 0 ) { + means = mean( [ 0.0, 0.0 ], d ); + } else { + means = null; + } + + if ( means !== null ) { + expected = pcorrdist( d, means[ 0 ], means[ 1 ], false ); + } + + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. window: ' + i + '.' ); + } else { + delta = abs( actual - expected ); + tol = 1.0 * EPS * abs( expected ); + t.equal( delta < tol, true, 'window: ' + i + '. expected: ' + expected + '. actual: ' + actual + '. tol: ' + tol + '. delta: ' + delta + '.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation distance (known means)', function test( t ) { + var filteredArr; + var expected; + var actual; + var means; + var delta; + var data; + var tol; + var acc; + var W; + var N; + var d; + var i; + + data = [ + [ 2.0, 1.0 ], + [ -5.0, NaN ], + [ 3.0, -1.0 ], + [ NaN, NaN ] + ]; + + N = data.length; + function isNotNaN( pair ) { + return !isnan( pair[ 0 ] ) && !isnan( pair[ 1 ] ); + } + filteredArr = data.filter( isNotNaN ); + if ( filteredArr.length > 0 ) { + means = mean( [ 0.0, 0.0 ], filteredArr ); + } else { + means = null; + } + + // Window size: + W = 4; + + acc = incrnanmpcorrdist( W, means[ 0 ], means[ 1 ] ); + for ( i = 0; i < N; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + actual = acc(); + if ( i < W - 1 ) { + d = data.slice( 0, i + 1 ); + } else { + d = data.slice( i - W + 1, i + 1 ); + } + + d = d.filter( function isNotNaN( pair ) { + return !isnan( pair[ 0 ] ) && !isnan( pair[ 1 ] ); + }); + if ( means === null ) { + expected = null; + } else { + expected = pcorrdist( d, means[ 0 ], means[ 1 ], true ); + } + + if ( actual === expected ) { + t.equal( actual, expected, 'returns expected value. window: ' + i + '.' ); + } else { + delta = abs( actual - expected ); + tol = 1.0 * EPS * abs( expected ); + t.equal( delta < tol, true, 'window: ' + i + '. expected: ' + expected + '. actual: ' + actual + '. tol: ' + tol + '. delta: ' + delta + '.' ); + } + } + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmpcorrdist( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null` (known means)', function test( t ) { + var acc = incrnanmpcorrdist( 3, 3.0, 3.14 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are unknown, the accumulator function returns `1`', function test( t ) { + var acc = incrnanmpcorrdist( 3 ); + acc( 2.0, 3.14 ); + t.equal( acc(), 1.0, 'returns 1' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the means are known, the accumulator function may not return `1`', function test( t ) { + var acc = incrnanmpcorrdist( 3, 30.0, -100.0 ); + acc( 2.0, 1.0 ); + t.notEqual( acc(), 1.0, 'does not return 1' ); + t.end(); +}); + +tape( 'if the window size is `1` and the means are unknown, the accumulator function always returns `1`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmpcorrdist( 1 ); + for ( i = 0; i < 100; i++ ) { + r = acc( randu() * 100.0, randu() * 100.0 ); + t.equal( r, 1.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'if the window size is `1` and the means are known, the accumulator function may not always return `1`', function test( t ) { + var acc; + var r; + var i; + + acc = incrnanmpcorrdist( 1, 500.0, -500.0 ); // means are outside the range of simulated values so the correlation should never be zero + for ( i = 0; i < 100; i++ ) { + r = acc( randu() * 100.0, randu() * 100.0 ); + t.notEqual( r, 1.0, 'does not return 1' ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/README.md b/lib/node_modules/@stdlib/stats/incr/nanmpe/README.md new file mode 100644 index 000000000000..d9ae143bf4ed --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/README.md @@ -0,0 +1,153 @@ + + +# incrnanmpe + +> Compute the [mean percentage error][mean-percentage-error] (MPE) incrementally, ignoring `NaN` values. + +
+ +The [mean percentage error][mean-percentage-error] is defined as + + + +```math +\mathop{\mathrm{MPE}} = \frac{100}{n} \sum_{i=0}^{n-1} \frac{a_i - f_i}{a_i} +``` + + + + + +where `f_i` is the forecast value and `a_i` is the actual value. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmpe = require( '@stdlib/stats/incr/nanmpe' ); +``` + +#### incrnanmpe() + +Returns an accumulator `function` which incrementally computes the [mean percentage error][mean-percentage-error], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmpe(); +``` + +#### accumulator( \[f, a] ) + +If provided input values `f` and `a`, the accumulator function returns an updated [mean percentage error][mean-percentage-error]. If not provided input values `f` and `a`, the accumulator function returns the current [mean percentage error][mean-percentage-error]. + +```javascript +var accumulator = incrnanmpe(); + +var m = accumulator( 2.0, 3.0 ); +// returns ~33.33 + +m = accumulator( NaN, 4.0 ); +// returns ~33.33 + +m = accumulator( 1.0, 4.0 ); +// returns ~54.17 + +m = accumulator( 3.0, NaN ); +// returns ~54.17 + +m = accumulator( 3.0, 5.0 ); +// returns ~49.44 + +m = accumulator(); +// returns ~49.44 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN`, the value is ignored and the accumulator function returns the current [mean percentage error][mean-percentage-error]. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- If either `f` or `a` is `NaN`, the input value pair is **skipped** (i.e., the pair does not contribute to the accumulated value). +- Be careful when interpreting the [mean percentage error][mean-percentage-error] as errors can cancel. This stated, that errors can cancel makes the [mean percentage error][mean-percentage-error] suitable for measuring the bias in forecasts. +- **Warning**: the [mean percentage error][mean-percentage-error] is **not** suitable for intermittent demand patterns (i.e., when `a_i` is `0`). Interpretation is most straightforward when actual and forecast values are positive valued (e.g., number of widgets sold). + +
+ + + +
+ +## Examples + + + +```javascript +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var incrnanmpe = require( '@stdlib/stats/incr/nanmpe' ); + +// Initialize an accumulator: +var accumulator = incrnanmpe(); + +// For each simulated datum, update the mean percentage error... +var v1; +var v2; +var i; +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[mean-percentage-error]: https://en.wikipedia.org/wiki/Mean_percentage_error + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmpe/benchmark/benchmark.js new file mode 100644 index 000000000000..6a1fd714eae6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmpe = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmpe(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmpe(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()+0.5, randu()+0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/img/equation_mean_percentage_error.svg b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/img/equation_mean_percentage_error.svg new file mode 100644 index 000000000000..2c910ba5e5de --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/img/equation_mean_percentage_error.svg @@ -0,0 +1,65 @@ + +upper M upper P upper E equals StartFraction 100 Over n EndFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts StartFraction a Subscript i Baseline minus f Subscript i Baseline Over a Subscript i Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/repl.txt new file mode 100644 index 000000000000..80a95757bc7c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/repl.txt @@ -0,0 +1,31 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes the mean + percentage error (MPE), ignoring `NaN` values. + + If provided input values, the accumulator function returns an updated mean + percentage error. If not provided input values, the accumulator function + returns the current mean percentage error. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var m = accumulator() + null + > m = accumulator( 2.0, 3.0 ) + ~33.33 + > m = accumulator( 2.0, NaN ) + ~33.33 + > m = accumulator( 5.0, 2.0 ) + ~-58.33 + > m = accumulator() + ~-58.33 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/types/index.d.ts new file mode 100644 index 000000000000..84ae2435aab2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/types/index.d.ts @@ -0,0 +1,64 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided input values, the accumulator function returns an updated mean percentage error. If not provided input values, the accumulator function returns the current mean percentage error. +* +* ## Notes +* +* - If either `f` or `a` is `NaN`, the input value pair is skipped (i.e., the pair does not contribute to the accumulated value). +* +* @param f - input value (forecast) +* @param a - input value (actual) +* @returns mean percentage error or null +*/ +type accumulator = ( f?: number, a?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes the mean percentage error, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanmpe(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( NaN, 5.0 ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator(); +* // returns ~-58.33 +*/ +declare function incrnanmpe(): accumulator; + + +// EXPORTS // + +export = incrnanmpe; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/types/test.ts new file mode 100644 index 000000000000..67d242a5d13f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/docs/types/test.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmpe = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmpe(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanmpe( '5' ); // $ExpectError + incrnanmpe( 5 ); // $ExpectError + incrnanmpe( true ); // $ExpectError + incrnanmpe( false ); // $ExpectError + incrnanmpe( null ); // $ExpectError + incrnanmpe( undefined ); // $ExpectError + incrnanmpe( [] ); // $ExpectError + incrnanmpe( {} ); // $ExpectError + incrnanmpe( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmpe(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmpe(); + + acc( '5', 2.0 ); // $ExpectError + acc( true, 2.0 ); // $ExpectError + acc( false, 2.0 ); // $ExpectError + acc( null, 2.0 ); // $ExpectError + acc( [], 2.0 ); // $ExpectError + acc( {}, 2.0 ); // $ExpectError + acc( ( x: number ): number => x, 2.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpe/examples/index.js new file mode 100644 index 000000000000..ea1c42620190 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var uniform = require( '@stdlib/random/base/uniform' ); +var incrnanmpe = require( './../lib' ); + +var accumulator; +var err; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmpe(); + +// For each simulated datum, update the mean percentage error... +console.log( '\nForecast\tActual\tMPE\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + err = accumulator( v1, v2 ); + console.log( '%d\t%d\t%d', v1.toFixed( 3 ), v2.toFixed( 3 ), ( err === null ) ? NaN : err.toFixed( 3 ) ); +} +console.log( '\nFinal MPE: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmpe/lib/index.js new file mode 100644 index 000000000000..6184c52a450d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the mean percentage error incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmpe +* +* @example +* var incrnanmpe = require( '@stdlib/stats/incr/nanmpe' ); +* +* var accumulator = incrnanmpe(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( NaN, 5.0 ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator(); +* // returns ~-58.33 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmpe/lib/main.js new file mode 100644 index 000000000000..ca2a1305fd42 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/lib/main.js @@ -0,0 +1,75 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmpe = require( '@stdlib/stats/incr/mpe' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes the mean percentage error, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmpe(); +* +* var m = accumulator(); +* // returns null +* +* m = accumulator( 2.0, 3.0 ); +* // returns ~33.33 +* +* m = accumulator( NaN, 5.0 ); +* // returns ~33.33 +* +* m = accumulator( 5.0, 2.0 ); +* // returns ~-58.33 +* +* m = accumulator(); +* // returns ~-58.33 +*/ +function incrnanmpe() { + var mpe = incrmpe(); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated mean percentage error. If not provided input values, the accumulator function returns the current mean percentage error. + * + * @private + * @param {number} [f] - input value (forecast) + * @param {number} [a] - input value (actual) + * @returns {(number|null)} mean percentage error or null + */ + function accumulator( f, a ) { + if ( arguments.length === 0 || isnan( f ) || isnan( a ) ) { + return mpe(); + } + return mpe( f, a ); + } +} + + +// EXPORTS // + +module.exports = incrnanmpe; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/package.json b/lib/node_modules/@stdlib/stats/incr/nanmpe/package.json new file mode 100644 index 000000000000..7acc416c8562 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/package.json @@ -0,0 +1,80 @@ +{ + "name": "@stdlib/stats/incr/nanmpe", + "version": "0.0.0", + "description": "Compute the mean percentage error (MPE) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "average", + "avg", + "mean", + "arithmetic mean", + "error", + "err", + "percentage", + "percent", + "mpe", + "deviation", + "difference", + "diff", + "delta", + "incremental", + "accumulator", + "time series", + "timeseries", + "forecasting", + "forecast", + "nan", + "ignore" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmpe/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmpe/test/test.js new file mode 100644 index 000000000000..c5b5a60c38e5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmpe/test/test.js @@ -0,0 +1,124 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmpe = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmpe, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanmpe(), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanmpe(); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes the mean percentage error, ignoring NaN values', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var sum; + var tol; + var cnt; + var N; + var x; + var y; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, NaN ], // NaN in actual - should be skipped + [ 3.0, 5.0 ], + [ NaN, 4.0 ], // NaN in forecast - should be skipped + [ 1.0, 10.0 ], + [ NaN, NaN ] // NaN in both - should be skipped + ]; + N = data.length; + + acc = incrnanmpe(); + + sum = 0; + cnt = 0; + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + actual = acc( x, y ); + if ( isnan( x ) === false && isnan( y ) === false ) { + sum += ( y-x ) / y; + cnt += 1; + expected = 100.0 * ( sum/cnt ); + } + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value' ); + } else { + delta = abs( expected - actual ); + tol = 10.0 * EPS * abs( expected ); + t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current mean percentage error', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var i; + + data = [ + [ 2.0, 3.0 ], + [ NaN, 5.0 ], // Should be skipped + [ 3.0, 5.0 ], + [ 1.0, 10.0 ] + ]; + acc = incrnanmpe(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + actual = acc(); + + // Only counting non-NaN: [2.0, 3.0], [3.0, 5.0], [1.0, 10.0] + expected = 100.0 / 3.0 * ((1.0/3.0) + (2.0/5.0) + (9.0/10.0)); + delta = abs( expected - actual ); + tol = 1.0 * EPS * abs( expected ); + t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected+'. Delta: '+delta + '. Tol: '+tol+'.' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/README.md b/lib/node_modules/@stdlib/stats/incr/nanmrange/README.md new file mode 100644 index 000000000000..2d31351a669e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/README.md @@ -0,0 +1,143 @@ + + +# incrnanmrange + +> Compute a moving [range][range] incrementally, ignoring `NaN` values. + +
+ +The [**range**][range] is defined as the difference between the maximum and minimum values. + +
+ + + +
+ +## Usage + +```javascript +var incrnanmrange = require( '@stdlib/stats/incr/nanmrange' ); +``` + +#### incrnanmrange( window ) + +Returns an accumulator `function` which incrementally computes a moving [range][range], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [range][range]. + +```javascript +var accumulator = incrnanmrange( 3 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated [range][range]. If not provided an input value `x`, the accumulator function returns the current [range][range]. + +```javascript +var accumulator = incrnanmrange( 3 ); + +var r = accumulator(); +// returns null + +// Fill the window... +r = accumulator( 2.0 ); // [2.0] +// returns 0.0 + +r = accumulator( 1.0 ); // [2.0, 1.0] +// returns 1.0 + +r = accumulator( NaN ); // [2.0, 1.0, NaN] +// returns 1.0 + +r = accumulator( 3.0 ); // [1.0, NaN, 3.0] +// returns 2.0 + +// Window begins sliding... +r = accumulator( -7.0 ); // [NaN, 3.0, -7.0] +// returns 10.0 + +r = accumulator( -5.0 ); // [3.0, -7.0, -5.0] +// returns 10.0 + +r = accumulator(); +// returns 10.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN`, the value is ignored. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmrange = require( '@stdlib/stats/incr/nanmrange' ); + +// Initialize an accumulator: +var accumulator = incrnanmrange( 5 ); + +// For each simulated datum, update the moving range... +var i; +for ( i = 0; i < 100; i++ ) { + accumulator( ( randu() < 0.2 ) ? NaN : randu()*100.0 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[range]: https://en.wikipedia.org/wiki/Range_%28statistics%29 + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmrange/benchmark/benchmark.js new file mode 100644 index 000000000000..679716dc340a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmrange = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmrange( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmrange( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/repl.txt new file mode 100644 index 000000000000..9429fa265647 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/repl.txt @@ -0,0 +1,52 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving range, + ignoring NaN values. + + The `W` parameter defines the number of values over which to compute the + moving range. + + If provided a value, the accumulator function returns an updated moving + range. If not provided a value, the accumulator function returns the current + moving range. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + NaN values are ignored during computation. If provided NaN, the accumulator + returns the current range. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var r = accumulator() + null + > r = accumulator( 2.0 ) + 0.0 + > r = accumulator( NaN ) + 0.0 + > r = accumulator( -5.0 ) + 7.0 + > r = accumulator( 3.0 ) + 8.0 + > r = accumulator( NaN ) + 8.0 + > r = accumulator( 5.0 ) + 10.0 + > r = accumulator() + 10.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/types/index.d.ts new file mode 100644 index 000000000000..cee56b052fcd --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/types/index.d.ts @@ -0,0 +1,77 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated range; otherwise, returns the current range. +* +* ## Notes +* +* - If provided `NaN`, the `NaN` value is ignored. +* - If no non-NaN values have been provided, the function returns `null`. +* +* @param x - value +* @returns range +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving range, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving range. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmrange( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0 ); +* // returns 0.0 +* +* r = accumulator( -5.0 ); +* // returns 7.0 +* +* r = accumulator( NaN ); +* // returns 7.0 +* +* r = accumulator( 3.0 ); +* // returns 8.0 +* +* r = accumulator( 5.0 ); +* // returns 10.0 +* +* r = accumulator(); +* // returns 10.0 +*/ +declare function incrnanmrange( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/types/test.ts new file mode 100644 index 000000000000..9a9f17dd1b00 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/docs/types/test.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmrange = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmrange( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument which is not a number... +{ + incrnanmrange( '5' ); // $ExpectError + incrnanmrange( true ); // $ExpectError + incrnanmrange( false ); // $ExpectError + incrnanmrange( null ); // $ExpectError + incrnanmrange( undefined ); // $ExpectError + incrnanmrange( [] ); // $ExpectError + incrnanmrange( {} ); // $ExpectError + incrnanmrange( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmrange(); // $ExpectError + incrnanmrange( 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmrange( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmrange( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmrange/examples/index.js new file mode 100644 index 000000000000..16674bde7887 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmrange = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanmrange( 5 ); + +// For each simulated datum, update the moving range... +console.log( '\nValue\tRange\n' ); +var r; +var v; +var i; +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + r = accumulator( v ); + console.log( '%d\t%d', v.toFixed( 4 ), ( r === null ) ? NaN : r.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmrange/lib/index.js new file mode 100644 index 000000000000..4ea9e42eb1ce --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/lib/index.js @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving range incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmrange +* +* @example +* var incrnanmrange = require( '@stdlib/stats/incr/nanmrange' ); +* +* var accumulator = incrnanmrange( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0 ); +* // returns 0.0 +* +* r = accumulator( -5.0 ); +* // returns 7.0 +* +* r = accumulator( NaN ); +* // returns 7.0 +* +* r = accumulator( 3.0 ); +* // returns 8.0 +* +* r = accumulator( 5.0 ); +* // returns 10.0 +* +* r = accumulator(); +* // returns 10.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmrange/lib/main.js new file mode 100644 index 000000000000..b4b9b0d8d392 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/lib/main.js @@ -0,0 +1,82 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var mrange = require( '@stdlib/stats/incr/mrange' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving range, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmrange( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0 ); +* // returns 0.0 +* +* r = accumulator( -5.0 ); +* // returns 7.0 +* +* r = accumulator( NaN ); +* // returns 7.0 +* +* r = accumulator( 3.0 ); +* // returns 8.0 +* +* r = accumulator( 5.0 ); +* // returns 10.0 +* +* r = accumulator(); +* // returns 10.0 +*/ +function incrnanmrange( W ) { + var acc = mrange( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated range. If not provided a value, the accumulator function returns the current range. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} range or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return acc(); + } + return acc( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/package.json b/lib/node_modules/@stdlib/stats/incr/nanmrange/package.json new file mode 100644 index 000000000000..8a4efd952781 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/package.json @@ -0,0 +1,75 @@ +{ + "name": "@stdlib/stats/incr/nanmrange", + "version": "0.0.0", + "description": "Compute a moving range incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "minimum", + "min", + "range", + "dispersion", + "variance", + "domain", + "extent", + "incremental", + "accumulator", + "sliding window", + "sliding", + "window", + "moving", + "nan" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrange/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmrange/test/test.js new file mode 100644 index 000000000000..808fc293dd92 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrange/test/test.js @@ -0,0 +1,419 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var incrnanmrange = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmrange, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + false, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmrange( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmrange( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving range incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 2.0, 4.0, 3.0, 4.0, 2.0, 2.0, 2.0, 1.0, 0.0, 4.0, -1.0 ]; + N = data.length; + + acc = incrnanmrange( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + expected = [ + 0.0, + 1.0, + 1.0, + 2.0, + 2.0, + 1.0, + 2.0, + 2.0, + 0.0, + 1.0, + 2.0, + 4.0, + 5.0 + ]; + + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current range', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, 3.0, 5.0, 4.0 ]; + acc = incrnanmrange( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmrange( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function correctly handles signed zeros', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmrange( 3 ); + + data = [ + 0.0, // 0 => min: 0.0, max: 0.0 (0) + -0.0, // 0, -0 => min: -0.0, max: 0.0 (1) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (2) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (3) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (4) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (5) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (6) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (7) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (8) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (9) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (10) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (11) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (12) + + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (13) + 0.0, // 0, -0, 0 => min: -0.0, max: 0.0 (14) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (15) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (16) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (17) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (18) + -0.0, // -0, 0, -0 => min: -0.0, max: 0.0 (19) + -0.0, // 0, -0, -0 => min: -0.0, max: 0.0 (20) + -0.0, // -0, -0, -0 => min: -0.0, max: -0.0 (21) + 0.0, // -0, -0, 0 => min: -0.0, max: 0.0 (22) + 0.0, // -0, 0, 0 => min: -0.0, max: 0.0 (23) + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 (24) + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 (25) + + // Case 1: out: -0, in: +0, cnt: 1 + 3.14, // 0, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 2: out: +0, in: -0, cnt: 1 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 3: out: -0, in: -0, cnt: 1 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + 3.14, // -0, 3.14, 3.14 => min: -0.0, max: 3.14 + -0.0, // 3.14, 3.14, -0 => min: -0.0, max: 3.14 + + // Case 4: out: -0, in: +0, cnt: 2 + 3.14, // 3.14, -0, 3.14 => min: -0.0, max: 3.14 + -0.0, // -0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 5: out: +0, in: +0, cnt: 1 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 3.14, // 0, 3.14, 3.14 => min: 0.0, max: 3.14 + 0.0, // 3.14, 3.14, 0 => min: 0.0, max: 3.14 + + // Case 6: out: +0, in: -0, cnt: 2 + 3.14, // 3.14, 0, 3.14 => min: 0.0, max: 3.14 + -0.0, // 0, 3.14, -0 => min: -0.0, max: 3.14 + 0.0, // 3.14, -0, 0 => min: -0.0, max: 3.14 + + // Case 7: out: +0, in: +0, cnt: 2 + 3.14, // -0, 0, 3.14 => min: -0.0, max: 3.14 + 0.0, // 0, 3.14, 0 => min: 0.0, max: 3.14 + 0.0, // 3.14, 0, 0 => min: 0.0, max: 3.14 + + // Reset: + -0.0, // 0, 0, -0 => min: -0.0, max: 0.0 + + // Case 8: out: -0, in: +0, cnt: 1 + -3.14, // 0, -0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 9: out: +0, in: -0, cnt: 1 + -3.14, // -3.14, 0, 3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 10: out: -0, in: -0, cnt: 1 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -3.14, // -0, -3.14, -3.14 => min: -3.14, max: -0.0 + -0.0, // -3.14, -3.14, -0 => min: -3.14, max: -0.0 + + // Case 11: out: -0, in: +0, cnt: 2 + -3.14, // -3.14, -0, -3.14 => min: -3.14, max: -0.0 + -0.0, // -0, -3.14, -0 => min: -3.14, max: -0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 12: out: +0, in: +0, cnt: 1 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + -3.14, // 0, -3.14, -3.14 => min: -3.14, max: 0.0 + 0.0, // -3.14, -3.14, 0 => min: -3.14, max: 0.0 + + // Case 13: out: +0, in: -0, cnt: 2 + -3.14, // -3.14, 0, -3.14 => min: -3.14, max: 0.0 + -0.0, // 0, -3.14, -0 => min: -3.14, max: 0.0 + 0.0, // -3.14, -0, 0 => min: -3.14, max: 0.0 + + // Case 14: out: +0, in: +0, cnt: 2 + -3.14, // -0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + 0.0, // -3.14, 0, 0 => min: -3.14, max: 0.0 + + // Reset: + 0.0, // 0, 0, 0 => min: 0.0, max: 0.0 + + // Case 15: out: +0, in: -0, cnt: 2 + -3.14, // 0, 0, -3.14 => min: -3.14, max: 0.0 + 0.0, // 0, -3.14, 0 => min: -3.14, max: 0.0 + -0.0 // -3.14, 0, -0 => min: -3.14, max: 0.0 + ]; + expected = [ + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + + // Case 1: + 3.14, + 3.14, + 3.14, + + // Case 2: + 3.14, + 3.14, + 3.14, + + // Case 3: + 3.14, + 3.14, + 3.14, + + // Case 4: + 3.14, + 3.14, + 3.14, + + // Case 5: + 3.14, + 3.14, + 3.14, + + // Case 6: + 3.14, + 3.14, + 3.14, + + // Case 7: + 3.14, + 3.14, + 3.14, + + // Reset: + 0.0, + + // Case 8: + 3.14, + 3.14, + 3.14, + + // Case 9: + 3.14, + 3.14, + 3.14, + + // Case 10: + 3.14, + 3.14, + 3.14, + + // Case 11: + 3.14, + 3.14, + 3.14, + + // Case 12: + 3.14, + 3.14, + 3.14, + + // Case 13: + 3.14, + 3.14, + 3.14, + + // Case 14: + 3.14, + 3.14, + 3.14, + + // Reset: + 0.0, + + // Case 15: + 3.14, + 3.14, + 3.14 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( expected[ i ] === 0.0 ) { + t.equal( isNegativeZero( v ), isNegativeZero( expected[ i ] ), 'returns expected value for window '+i ); + } else { + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + } + } + t.end(); +}); + +tape( 'if provided NaN, the accumulator function ignores it and returns the previous result', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmrange( 3 ); + + data = [ + 3.14, // [3.14] -> range: 0.0 (single value) + NaN, // [3.14] -> range: 0.0 (NaN ignored) + 5.0, // [3.14, 5.0] -> range: 1.86 + 7.0, // [3.14, 5.0, 7.0] -> range: 3.86 + NaN, // [3.14, 5.0, 7.0] -> range: 3.86 (NaN ignored) + NaN, // [3.14, 5.0, 7.0] -> range: 3.86 (NaN ignored) + 2.0, // [5.0, 7.0, 2.0] -> range: 5.0 + NaN, // [5.0, 7.0, 2.0] -> range: 5.0 (NaN ignored) + 1.0, // [7.0, 2.0, 1.0] -> range: 6.0 + 10.0 // [2.0, 1.0, 10.0] -> range: 9.0 + ]; + expected = [ + 0.0, // single value has range 0 + 0.0, // NaN ignored, previous value returned + 1.86, // range between 3.14 and 5.0 + 3.86, // range between 3.14 and 7.0 + 3.86, // NaN ignored, previous value returned + 3.86, // NaN ignored, previous value returned + 5.0, // range between 2.0 and 7.0 + 5.0, // NaN ignored, previous value returned + 6.0, // range between 1.0 and 7.0 + 9.0 // range between 1.0 and 10.0 + ]; + + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + if ( isnan( expected[ i ] ) ) { + t.equal( isnan( v ), true, 'returns expected value for window '+i ); + } else if ( i === 2 ) { + t.ok( abs(v - expected[i]) < 0.01, 'returns expected value for window '+i ); + } else { + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + } + } + + t.equal( acc(), 9.0, 'returns current range when called without arguments' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/README.md b/lib/node_modules/@stdlib/stats/incr/nanmrss/README.md new file mode 100644 index 000000000000..b6abc1c6d872 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/README.md @@ -0,0 +1,169 @@ + + +# incrnanmrss + +> Compute a moving [residual sum of squares][residual-sum-of-squares] (RSS) incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [residual sum of squares][residual-sum-of-squares] (also referred to as the **sum of squared residuals** (SSR) and the **sum of squared errors** (SSE)) is defined as + + + +```math +\mathop{\mathrm{RSS}} = \sum_{i=0}^{W-1} (y_i - x_i)^2 +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmrss = require( '@stdlib/stats/incr/nanmrss' ); +``` + +#### incrnanmrss( window ) + +Returns an accumulator `function` which incrementally computes a moving [residual sum of squares][residual-sum-of-squares]. The `window` parameter defines the number of values over which to compute the moving [residual sum of squares][residual-sum-of-squares], ignoring `NaN` values. + +```javascript +var accumulator = incrnanmrss( 3 ); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated [residual sum of squares][residual-sum-of-squares]. If not provided input values `x` and `y`, the accumulator function returns the current [residual sum of squares][residual-sum-of-squares]. + +```javascript +var accumulator = incrnanmrss( 3 ); + +var r = accumulator(); +// returns null + +// Fill the window... +r = accumulator( 2.0, 3.0 ); // [(2.0,3.0)] +// returns 1.0 + +r = accumulator( NaN, 3.0 ); // [(2.0,3.0)] (NaN pair ignored) +// returns 1.0 + +r = accumulator( 2.0, NaN ); // [(2.0,3.0)] (NaN pair ignored) +// returns 1.0 + +r = accumulator( NaN, NaN ); // [(2.0,3.0)] (NaN pair ignored) +// returns 1.0 + +r = accumulator( -1.0, 4.0 ); // [(2.0,3.0), (-1.0,4.0)] +// returns 26.0 + +r = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (-1.0,4.0), (3.0,9.0)] +// returns 62.0 + +// Window begins sliding... +r = accumulator( -7.0, 3.0 ); // [(-1.0,4.0), (3.0,9.0), (-7.0,3.0)] +// returns 161.0 + +r = accumulator( -5.0, -3.0 ); // [(3.0,9.0), (-7.0,3.0), (-5.0,-3.0)] +// returns 140.0 + +r = accumulator(); +// returns 140.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN` for either value, the pair is ignored and the accumulator function returns the current [residual sum of squares][residual-sum-of-squares] without updating the window. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values (excluding NaN values). + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanmrss = require( '@stdlib/stats/incr/nanmrss' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmrss( 5 ); + +// For each simulated datum, update the moving residual sum of squares... +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[residual-sum-of-squares]: https://en.wikipedia.org/wiki/Residual_sum_of_squares + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmrss/benchmark/benchmark.js new file mode 100644 index 000000000000..5307ddb1b9c5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnanmrss = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmrss( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmrss( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()-0.5, randu()-0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/img/equation_residual_sum_of_squares.svg b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/img/equation_residual_sum_of_squares.svg new file mode 100644 index 000000000000..3d39639ab430 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/img/equation_residual_sum_of_squares.svg @@ -0,0 +1,52 @@ + +upper R upper S upper S equals sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts left-parenthesis y Subscript i Baseline minus x Subscript i Baseline right-parenthesis squared + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/repl.txt new file mode 100644 index 000000000000..256b89602fbc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/repl.txt @@ -0,0 +1,51 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving + residual sum of squares (RSS), ignoring `NaN` values. + + The `W` parameter defines the number of values over which to compute the + moving residual sum of squares. + + If provided a value, the accumulator function returns an updated moving + residual sum of squares. If not provided a value, the accumulator function + returns the current moving residual sum of squares. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var r = accumulator() + null + > r = accumulator( 2.0, 3.0 ) + 1.0 + > r = accumulator( NaN, 3.0 ) + 1.0 + > r = accumulator( 2.0, NaN ) + 1.0 + > r = accumulator( NaN, NaN ) + 1.0 + > r = accumulator( -5.0, 2.0 ) + 50.0 + > r = accumulator( 3.0, 2.0 ) + 51.0 + > r = accumulator( 5.0, -2.0 ) + 99.0 + > r = accumulator() + 99.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/types/index.d.ts new file mode 100644 index 000000000000..5dcff9ccd768 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/types/index.d.ts @@ -0,0 +1,79 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated residual sum of squares; otherwise, returns the current residual sum of squares, ignoring `NaN` values. +* +* @param x - value +* @param y - value +* @returns residual sum of squares +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving residual sum of squares, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of values over which to compute the moving residual sum of squares. +* - As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmrss( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* r = accumulator( NaN, NaN ); +* // returns 1.0 +* +* r = accumulator( 2.0, NaN ); +* // returns 1.0 +* +* r = accumulator( NaN, 3.0 ); +* // returns 1.0 +* +* r = accumulator( -5.0, 2.0 ); +* // returns 50.0 +* +* r = accumulator( 3.0, 2.0 ); +* // returns 51.0 +* +* r = accumulator( 5.0, -2.0 ); +* // returns 99.0 +* +* r = accumulator(); +* // returns 99.0 +*/ +declare function incrnanmrss( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmrss; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/types/test.ts new file mode 100644 index 000000000000..92a6979d5a1d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/docs/types/test.ts @@ -0,0 +1,74 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmrss = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmrss( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmrss( '5' ); // $ExpectError + incrnanmrss( true ); // $ExpectError + incrnanmrss( false ); // $ExpectError + incrnanmrss( null ); // $ExpectError + incrnanmrss( undefined ); // $ExpectError + incrnanmrss( [] ); // $ExpectError + incrnanmrss( {} ); // $ExpectError + incrnanmrss( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmrss(); // $ExpectError + incrnanmrss( 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmrss( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmrss( 3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmrss/examples/index.js new file mode 100644 index 000000000000..ecc887c5730b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/examples/index.js @@ -0,0 +1,42 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanmrss = require( './../lib' ); + +var accumulator; +var rss; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanmrss( 5 ); + +// For each simulated datum, update the moving residual sum of squares... +console.log( '\nValue\tValue\tRSS\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + rss = accumulator( v1, v2 ); + console.log( '%s\t%s\t%s', ( isnan( v1 ) ) ? 'NaN' : v1.toFixed( 3 ), ( isnan( v2 ) ) ? 'NaN' : v2.toFixed( 3 ), ( rss === null ) ? 'null' : rss.toFixed( 3 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmrss/lib/index.js new file mode 100644 index 000000000000..be109341039c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/lib/index.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving residual sum of squares (RSS) incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmrss +* +* @example +* var incrnanmrss = require( '@stdlib/stats/incr/nanmrss' ); +* +* var accumulator = incrnanmrss( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* r = accumulator( NaN, 3.0 ); +* // returns 1.0 +* +* r = accumulator( 2.0, NaN ); +* // returns 1.0 +* +* r = accumulator( NaN, NaN ); +* // returns 1.0 +* +* r = accumulator( -5.0, 2.0 ); +* // returns 50.0 +* +* r = accumulator( 3.0, 2.0 ); +* // returns 51.0 +* +* r = accumulator( 5.0, -2.0 ); +* // returns 99.0 +* +* r = accumulator(); +* // returns 99.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmrss/lib/main.js new file mode 100644 index 000000000000..331e0b4c3010 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/lib/main.js @@ -0,0 +1,89 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrmrss = require( '@stdlib/stats/incr/mrss' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving residual sum of squares, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmrss( 3 ); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* r = accumulator( NaN, 3.0 ); +* // returns 1.0 +* +* r = accumulator( 2.0, NaN ); +* // returns 1.0 +* +* r = accumulator( NaN, NaN ); +* // returns 1.0 +* +* r = accumulator( -5.0, 2.0 ); +* // returns 50.0 +* +* r = accumulator( 3.0, 2.0 ); +* // returns 51.0 +* +* r = accumulator( 5.0, -2.0 ); +* // returns 99.0 +* +* r = accumulator(); +* // returns 99.0 +*/ +function incrnanmrss( W ) { + var mrss = incrmrss( W ); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated residual sum of squares. If not provided input values, the accumulator function returns the current residual sum of squares. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} residual sum of squares or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return mrss(); + } + return mrss( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmrss; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/package.json b/lib/node_modules/@stdlib/stats/incr/nanmrss/package.json new file mode 100644 index 000000000000..5c3b864d3ded --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/package.json @@ -0,0 +1,91 @@ +{ + "name": "@stdlib/stats/incr/nanmrss", + "version": "0.0.0", + "description": "Compute a moving residual sum of squares (RSS) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "error", + "err", + "rss", + "ssr", + "sse", + "residuals", + "sum", + "total", + "squares", + "deviation", + "difference", + "diff", + "delta", + "incremental", + "accumulator", + "sliding window", + "sliding", + "window", + "moving", + "time series", + "timeseries", + "forecasting", + "forecast", + "model", + "selection", + "evaluation", + "prediction", + "manhattan", + "cityblock", + "city-block", + "distance", + "dist" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmrss/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmrss/test/test.js new file mode 100644 index 000000000000..c21d6c435cd9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmrss/test/test.js @@ -0,0 +1,135 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanmrss = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmrss, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmrss( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmrss( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving residual sum of squares incrementally', function test( t ) { + var expected; + var actual; + var delta; + var data; + var acc; + var tol; + var N; + var i; + + data = [ + [ 2.0, 3.0 ], + [ NaN, 3.0 ], + [ 2.0, NaN ], + [ 3.0, -1.0 ], + [ 2.0, 5.0 ], + [ 4.0, -4.0 ], + [ NaN, NaN ], + [ 3.0, 0.0 ], + [ -4.0, 5.0 ] + ]; + N = data.length; + + acc = incrnanmrss( 3 ); + + expected = [ 1.0, 1.0, 1.0, 17.0, 26.0, 89.0, 89.0, 82.0, 154.0 ]; + for ( i = 0; i < N; i++ ) { + actual = acc( data[i][0], data[i][1] ); + if ( actual === expected[i] ) { + t.equal( actual, expected[i], 'returns expected value' ); + } else { + delta = abs( expected[i] - actual ); + tol = 1.0 * EPS * abs( expected[i] ); + t.equal( delta <= tol, true, 'within tolerance. Actual: '+actual+'. Expected: '+expected[i]+'. Delta: '+delta+'. Tol: '+tol+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current residual sum of squares', function test( t ) { + var data; + var acc; + var i; + + data = [ + [ 2.0, 3.0 ], + [ NaN, 5.0 ], + [ 3.0, -5.0 ], + [ 1.0, NaN ], + [ 1.0, 10.0 ] + ]; + acc = incrnanmrss( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[i][0], data[i][1] ); + } + t.equal( acc(), 145.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmrss( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/README.md b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/README.md new file mode 100644 index 000000000000..85945a49b068 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/README.md @@ -0,0 +1,162 @@ + + +# incrnanmsumprod + +> Compute a moving sum of products incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the moving sum of products is defined as + + + +```math +s = \sum_{i=0}^{W-1} x_i y_i +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmsumprod = require( '@stdlib/stats/incr/nanmsumprod' ); +``` + +#### incrnanmsumprod( window ) + +Returns an accumulator function which incrementally computes a moving sum of products. The `window` parameter defines the number of values over which to compute the moving sum of products, ignoring `NaN` values. + +```javascript +var accumulator = incrnanmsumprod( 4 ); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated sum. If not provided input values `x` and `y`, the accumulator function returns the current sum. + +```javascript +var accumulator = incrnanmsumprod( 3 ); + +var sum = accumulator(); +// returns null + +// Fill the window... +sum = accumulator( 2.0, 3.0 ); // [(2.0,3.0)] +// returns 6.0 + +sum = accumulator( 1.0, -1.0 ); // [(2.0,3.0), (1.0,-1.0)] +// returns 5.0 + +sum = accumulator( NaN, -1.0 ); +// returns 5.0 + +sum = accumulator( -3.0, 5.0 ); // [(2.0,3.0), (1.0,-1.0), (-3.0,5.0)] +// returns -10.0 + +// Window begins sliding... +sum = accumulator( -7.0, -1.0 ); // [(1.0,-1.0), (-3.0,5.0), (-7.0,-1.0)] +// returns -9.0 + +sum = accumulator( 5.0, 4.0 ); // [(-3.0,5.0), (-7.0,-1.0), (5.0,4.0)] +// returns 12.0 + +sum = accumulator( 5.0, NaN ); +// returns 12.0 + +sum = accumulator(); +// returns 12.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmsumprod = require( '@stdlib/stats/incr/nanmsumprod' ); + +// Initialize an accumulator: +var accumulator = incrnanmsumprod( 5 ); + +// For each simulated datum, update the moving sum-product... +console.log( '\nValue\tValue\tSum\n' ); +var v1; +var v2; +var i; +for ( i = 0; i < 100; i++ ) { + v1 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + v2 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/benchmark/benchmark.js new file mode 100644 index 000000000000..4d5d8960e2ac --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmsumprod = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmsumprod( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanmsumprod( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i, i ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/img/equation_moving_sum_product.svg b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/img/equation_moving_sum_product.svg new file mode 100644 index 000000000000..2cdc3bec3c27 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/img/equation_moving_sum_product.svg @@ -0,0 +1,40 @@ + +s equals sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts x Subscript i Baseline y Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/repl.txt new file mode 100644 index 000000000000..09575b649cb9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/repl.txt @@ -0,0 +1,51 @@ + +{{alias}}( W ) + Returns an accumulator function which incrementally computes a moving sum of + products, ignoring `NaN` values. + + The `W` parameter defines the number of (x,y) pairs over which to compute + the moving sum of products. + + If provided input values, the accumulator function returns an updated moving + sum. If not provided input values, the accumulator function returns the + current moving sum. + + As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` + returned values are calculated from smaller sample sizes. Until the window + is full, each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var s = accumulator() + null + > s = accumulator( 2.0, 3.0 ) + 6.0 + > s = accumulator( NaN, 3.0 ) + 6.0 + > s = accumulator( -5.0, 2.0 ) + -4.0 + > s = accumulator( -5.0, NaN ) + -4.0 + > s = accumulator( 3.0, -2.0 ) + -10.0 + > s = accumulator( NaN, NaN ) + -10.0 + > s = accumulator( 5.0, 3.0 ) + -1.0 + > s = accumulator() + -1.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/types/index.d.ts new file mode 100644 index 000000000000..f4b9b5dfb8b2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/types/index.d.ts @@ -0,0 +1,79 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated sum of products; otherwise, returns the current sum of products. +* +* @param x - value +* @param y - value +* @returns sum of products +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving sum of products, ignoring `NaN` values. +* +* ## Notes +* +* - The `W` parameter defines the number of (x,y) pairs over which to compute the moving sum of products. +* - As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values. +* +* @param W - window size +* @throws must provide a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmsumprod( 3 ); +* +* var sum = accumulator(); +* // returns null +* +* sum = accumulator( 2.0, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( NaN, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( -5.0, 2.0 ); +* // returns -4.0 +* +* sum = accumulator( -5.0, NaN ); +* // returns -4.0 +* +* sum = accumulator( 3.0, -2.0 ); +* // returns -10.0 +* +* sum = accumulator( NaN, NaN ); +* // returns -10.0 +* +* sum = accumulator( 5.0, 3.0 ); +* // returns -1.0 +* +* sum = accumulator(); +* // returns -1.0 +*/ +declare function incrnanmsumprod( W: number ): accumulator; + + +// EXPORTS // + +export = incrnanmsumprod; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/types/test.ts new file mode 100644 index 000000000000..cd15e2a6150d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/docs/types/test.ts @@ -0,0 +1,74 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmsumprod = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmsumprod( 3 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided an argument that is not a number... +{ + incrnanmsumprod( '5' ); // $ExpectError + incrnanmsumprod( true ); // $ExpectError + incrnanmsumprod( false ); // $ExpectError + incrnanmsumprod( null ); // $ExpectError + incrnanmsumprod( undefined ); // $ExpectError + incrnanmsumprod( [] ); // $ExpectError + incrnanmsumprod( {} ); // $ExpectError + incrnanmsumprod( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmsumprod(); // $ExpectError + incrnanmsumprod( 3, 5 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmsumprod( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmsumprod( 3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/examples/index.js new file mode 100644 index 000000000000..31e551065536 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/examples/index.js @@ -0,0 +1,38 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmsumprod = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanmsumprod( 5 ); + +// For each simulated datum, update the moving sum-product... +console.log( '\nValue\tValue\tSum\n' ); +var sum; +var v1; +var v2; +var i; +for ( i = 0; i < 100; i++ ) { + v1 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + v2 = ( randu() < 0.2 ) ? NaN : randu() * 100.0; + sum = accumulator( v1, v2 ); + console.log( '%d\t%d\t%d', v1.toFixed( 4 ), v2.toFixed( 4 ), ( sum === null ) ? NaN : sum.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/lib/index.js new file mode 100644 index 000000000000..3ebdf97cf320 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/lib/index.js @@ -0,0 +1,66 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving sum of products incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmsumprod +* +* @example +* var incrnanmsumprod = require( '@stdlib/stats/incr/nanmsumprod' ); +* +* var accumulator = incrnanmsumprod( 3 ); +* +* var sum = accumulator(); +* // returns null +* +* sum = accumulator( 2.0, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( NaN, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( -5.0, 2.0 ); +* // returns -4.0 +* +* sum = accumulator( -5.0, NaN ); +* // returns -4.0 +* +* sum = accumulator( 3.0, -2.0 ); +* // returns -10.0 +* +* sum = accumulator( NaN, NaN ); +* // returns -10.0 +* +* sum = accumulator( 5.0, 3.0 ); +* // returns -1.0 +* +* sum = accumulator(); +* // returns -1.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/lib/main.js new file mode 100644 index 000000000000..6d66c66fd68b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/lib/main.js @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmsumprod = require( '@stdlib/stats/incr/msumprod' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving sum of products, ignoring `NaN` values. +* +* @param {PositiveInteger} W - window size +* @throws {TypeError} must provide a positive integer +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmsumprod( 3 ); +* +* var sum = accumulator(); +* // returns null +* +* sum = accumulator( 2.0, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( NaN, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( -5.0, 2.0 ); +* // returns -4.0 +* +* sum = accumulator( -5.0, NaN ); +* // returns -4.0 +* +* sum = accumulator( 3.0, -2.0 ); +* // returns -10.0 +* +* sum = accumulator( NaN, NaN ); +* // returns -10.0 +* +* sum = accumulator( 5.0, 3.0 ); +* // returns -1.0 +* +* sum = accumulator(); +* // returns -1.0 +*/ +function incrnanmsumprod( W ) { + var msumprod; + + msumprod = incrmsumprod( W ); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated sum. If not provided a value, the accumulator function returns the current sum. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} sum or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return msumprod(); + } + return msumprod( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanmsumprod; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/package.json b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/package.json new file mode 100644 index 000000000000..ce3f79141e37 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/package.json @@ -0,0 +1,73 @@ +{ + "name": "@stdlib/stats/incr/nanmsumprod", + "version": "0.0.0", + "description": "Compute a moving sum of products incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "sum", + "total", + "product", + "prod", + "dot", + "dot product", + "sum-product", + "incremental", + "accumulator", + "moving sum", + "sliding window", + "sliding", + "window", + "moving" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmsumprod/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/test/test.js new file mode 100644 index 000000000000..794cda5349df --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmsumprod/test/test.js @@ -0,0 +1,147 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var incrnanmsumprod = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmsumprod, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmsumprod( value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmsumprod( 3 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving sum of products incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, -1.0 ], + [ 3.0, NaN ], + [ 2.0, 5.0 ], + [ NaN, 5.0 ], + [ 4.0, -4.0 ], + [ 3.0, 0.0 ], + [ NaN, NaN ], + [ -4.0, 5.0 ] + ]; + N = data.length; + + acc = incrnanmsumprod( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ][ 0 ], data[ i ][ 1 ] ) ); + } + expected = [ 6.0, 3.0, 3.0, 13.0, 13.0, -9.0, -6.0, -6.0, -36.0 ]; + + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sum of products', function test( t ) { + var data; + var acc; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 2.0, NaN ], + [ 3.0, -5.0 ], + [ NaN, 3.0 ], + [ NaN, NaN ], + [ 1.0, 10.0 ] + ]; + acc = incrnanmsumprod( 2 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + t.equal( acc(), -5.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmsumprod( 3 ); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function only provided `NaN` values returns `null` for the current sum of products', function test( t ) { + var data; + var acc; + var i; + data = [ + [ 1.0, NaN ], + [ NaN, NaN ], + [ NaN, 4.0 ], + [ NaN, NaN ], + [ NaN, 2.0 ] + ]; + acc = incrnanmsumprod( 3 ); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + t.equal( acc(), null, 'returns null' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/README.md b/lib/node_modules/@stdlib/stats/incr/nanmvmr/README.md new file mode 100644 index 000000000000..fae35aae85f9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/README.md @@ -0,0 +1,225 @@ + + +# incrnanmvmr + +> Compute a moving [variance-to-mean ratio][variance-to-mean-ratio] (VMR) incrementally, ignoring `NaN` values. + +
+ +For a window of size `W`, the [unbiased sample variance][sample-variance] is defined as + + + +```math +s^2 = \frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2 +``` + + + + + +and the [arithmetic mean][arithmetic-mean] is defined as + + + +```math +\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i +``` + + + + + +The [variance-to-mean ratio][variance-to-mean-ratio] (VMR) is thus defined as + + + +```math +F = \frac{s^2}{\bar{x}} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanmvmr = require( '@stdlib/stats/incr/nanmvmr' ); +``` + +#### incrnanmvmr( window\[, mean] ) + +Returns an accumulator `function` which incrementally computes a moving [variance-to-mean ratio][variance-to-mean-ratio], ignoring `NaN` values. The `window` parameter defines the number of values over which to compute the moving [variance-to-mean ratio][variance-to-mean-ratio]. + +```javascript +var accumulator = incrnanmvmr( 3 ); +``` + +If the mean is already known, provide a `mean` argument. + +```javascript +var accumulator = incrnanmvmr( 3, 5.0 ); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated accumulated value. If not provided an input value `x`, the accumulator function returns the current accumulated value. If provided `NaN`, the accumulator function ignores the value and returns the current accumulated value without updating the window. + +```javascript +var accumulator = incrnanmvmr( 3 ); + +var F = accumulator(); +// returns null + +// Fill the window with non-NaN values... +F = accumulator( 2.0 ); // [2.0] +// returns 0.0 + +F = accumulator( NaN ); // [2.0] +// returns 0.0 + +F = accumulator( 1.0 ); // [2.0, 1.0] +// returns ~0.33 + +F = accumulator( 3.0 ); // [2.0, 1.0, 3.0] +// returns 0.5 + +// Window begins sliding... +F = accumulator( 7.0 ); // [1.0, 3.0, 7.0] +// returns ~2.55 + +F = accumulator( NaN ); // [1.0, 3.0, 7.0] +// returns ~2.55 + +F = accumulator( 5.0 ); // [3.0, 7.0, 5.0] +// returns ~0.80 + +F = accumulator(); +// returns ~0.80 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN`, the value is ignored and the accumulator function returns the current [variance-to-mean ratio][variance-to-mean-ratio] without updating the window. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +- As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values (excluding NaN values). + +- The following table summarizes how to interpret the [variance-to-mean ratio][variance-to-mean-ratio]: + + | VMR | Description | Example Distribution | + | :---------------: | :-------------: | :--------------------------: | + | 0 | not dispersed | constant | + | 0 < VMR < 1 | under-dispersed | binomial | + | 1 | -- | Poisson | + | >1 | over-dispersed | geometric, negative-binomial | + + Accordingly, one can use the [variance-to-mean ratio][variance-to-mean-ratio] to assess whether observed data can be modeled as a Poisson process. When observed data is "under-dispersed", observed data may be more regular than as would be the case for a Poisson process. When observed data is "over-dispersed", observed data may contain clusters (i.e., clumped, concentrated data). + +- The [variance-to-mean ratio][variance-to-mean-ratio] is typically computed on nonnegative values. The measure may lack meaning for data which can assume both positive and negative values. + +- The [variance-to-mean ratio][variance-to-mean-ratio] is also known as the **index of dispersion**, **dispersion index**, **coefficient of dispersion**, **relative variance**, and the [**Fano factor**][fano-factor]. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmvmr = require( '@stdlib/stats/incr/nanmvmr' ); + +// Initialize an accumulator: +var accumulator = incrnanmvmr( 5 ); + +// For each simulated datum, update the moving variance-to-mean ratio... +console.log( '\nValue\tVMR\n' ); +var F; +var v; +var i; +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + F = accumulator( v ); + console.log( '%d\t%d', v.toFixed( 4 ), ( F === null ) ? NaN : F.toFixed( 4 ) ); +} +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[variance-to-mean-ratio]: https://en.wikipedia.org/wiki/Index_of_dispersion + +[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean + +[sample-variance]: https://en.wikipedia.org/wiki/Variance + +[fano-factor]: https://en.wikipedia.org/wiki/Fano_factor + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmvmr/benchmark/benchmark.js new file mode 100644 index 000000000000..e06ce02c02f4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/benchmark/benchmark.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var poisson = require( '@stdlib/random/array/poisson' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanmvmr = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanmvmr( (i%5)+1 ); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var values; + var acc; + var v; + var i; + + values = poisson( 100, 10.0 ); + acc = incrnanmvmr( 5 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( values[ i%values.length ] ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_mean', pkg ), function benchmark( b ) { + var values; + var acc; + var v; + var i; + + values = poisson( 100, 10.0 ); + acc = incrnanmvmr( 5, 10.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( values[ i%values.length ] ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_arithmetic_mean.svg new file mode 100644 index 000000000000..1a89a2bfb996 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_arithmetic_mean.svg @@ -0,0 +1,43 @@ + +x overbar equals StartFraction 1 Over upper W EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts x Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_unbiased_sample_variance.svg b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_unbiased_sample_variance.svg new file mode 100644 index 000000000000..f4722f986a70 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_unbiased_sample_variance.svg @@ -0,0 +1,61 @@ + +s squared equals StartFraction 1 Over upper W minus 1 EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_variance_to_mean_ratio.svg b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_variance_to_mean_ratio.svg new file mode 100644 index 000000000000..d7318aa42b21 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/img/equation_variance_to_mean_ratio.svg @@ -0,0 +1,28 @@ + +upper F equals StartFraction s squared Over x overbar EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/repl.txt new file mode 100644 index 000000000000..0da71893da2b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/repl.txt @@ -0,0 +1,52 @@ + +{{alias}}( W[, mean] ) + Returns an accumulator function which incrementally computes a moving + variance-to-mean ratio (VMR) while ignoring NaN values. + + The `W` parameter defines the number of values over which to compute the + moving variance-to-mean ratio. + + If provided a value, the accumulator function returns an updated moving + variance-to-mean ratio. If not provided a value, the accumulator function + returns the current moving variance-to-mean ratio. + + As `W` values are needed to fill the window buffer, the first `W-1` returned + values are calculated from smaller sample sizes. Until the window is full, + each returned value is calculated from all provided values. + + Parameters + ---------- + W: integer + Window size. + + mean: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}( 3 ); + > var F = accumulator() + null + > F = accumulator( 2.0 ) + 0.0 + > F = accumulator( NaN ) + 0.0 + > F = accumulator( 1.0 ) + ~0.33 + > F = accumulator( 3.0 ) + 0.5 + > F = accumulator( NaN ) + 0.5 + > F = accumulator( 7.0 ) + ~2.55 + > F = accumulator() + ~2.55 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/types/index.d.ts new file mode 100644 index 000000000000..61f92e74a6a2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/types/index.d.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated moving variance-to-mean ratio; otherwise, returns the current moving variance-to-mean ratio. +* +* ## Notes +* +* - If provided `NaN`, the accumulated value is not updated (i.e., `NaN` values are ignored). +* +* @param x - value +* @returns accumulated value or null +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a moving variance-to-mean ratio (VMR) while ignoring `NaN` values. +* +* @param W - window size +* @param mean - mean value +* @throws first argument must be a positive integer +* @returns accumulator function +* +* @example +* var accumulator = incrnanmvmr( 3 ); +* +* var F = accumulator(); +* // returns null +* +* F = accumulator( 2.0 ); +* // returns 0.0 +* +* F = accumulator( NaN ); +* // returns 0.0 +* +* F = accumulator( 1.0 ); +* // returns ~0.33 +* +* F = accumulator( 3.0 ); +* // returns 0.5 +* +* F = accumulator( NaN ); +* // returns 0.5 +* +* F = accumulator( 7.0 ); +* // returns ~2.55 +* +* F = accumulator(); +* // returns ~2.55 +* +* @example +* var accumulator = incrnanmvmr( 3, 2.0 ); +*/ +declare function incrnanmvmr( W: number, mean?: number ): accumulator; + + +// EXPORTS // + +export = incrnanmvmr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/types/test.ts new file mode 100644 index 000000000000..9046fa581e59 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/docs/types/test.ts @@ -0,0 +1,77 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanmvmr = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanmvmr( 3 ); // $ExpectType accumulator + incrnanmvmr( 3, 0.0 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided a first argument that is not a number... +{ + incrnanmvmr( '5' ); // $ExpectError + incrnanmvmr( true ); // $ExpectError + incrnanmvmr( false ); // $ExpectError + incrnanmvmr( null ); // $ExpectError + incrnanmvmr( [] ); // $ExpectError + incrnanmvmr( {} ); // $ExpectError + incrnanmvmr( ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument that is not a number... +{ + incrnanmvmr( 2, '5' ); // $ExpectError + incrnanmvmr( 2, true ); // $ExpectError + incrnanmvmr( 2, false ); // $ExpectError + incrnanmvmr( 2, null ); // $ExpectError + incrnanmvmr( 2, [] ); // $ExpectError + incrnanmvmr( 2, {} ); // $ExpectError + incrnanmvmr( 2, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanmvmr(); // $ExpectError + incrnanmvmr( 2, 3, 4 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanmvmr( 3 ); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanmvmr( 3 ); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmvmr/examples/index.js new file mode 100644 index 000000000000..7f080b2bcceb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanmvmr = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanmvmr( 5 ); + +// For each simulated datum, update the moving variance-to-mean ratio... +console.log( '\nValue\tVMR\n' ); +var F; +var v; +var i; +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + F = accumulator( v ); + console.log( '%d\t%d', v.toFixed( 4 ), ( F === null ) ? NaN : F.toFixed( 4 ) ); +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmvmr/lib/index.js new file mode 100644 index 000000000000..841428ad5317 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/lib/index.js @@ -0,0 +1,63 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a moving variance-to-mean ratio (VMR) incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanmvmr +* +* @example +* var incrnanmvmr = require( '@stdlib/stats/incr/nanmvmr' ); +* +* var accumulator = incrnanmvmr( 3 ); +* +* var F = accumulator(); +* // returns null +* +* F = accumulator( 2.0 ); +* // returns 0.0 +* +* F = accumulator( NaN ); +* // returns 0.0 +* +* F = accumulator( 1.0 ); +* // returns ~0.33 +* +* F = accumulator( 3.0 ); +* // returns 0.5 +* +* F = accumulator( NaN ); +* // returns 0.5 +* +* F = accumulator( 7.0 ); +* // returns ~2.55 +* +* F = accumulator(); +* // returns ~2.55 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmvmr/lib/main.js new file mode 100644 index 000000000000..8050faf815f4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/lib/main.js @@ -0,0 +1,162 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrmvmr = require( '@stdlib/stats/incr/mvmr' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a moving variance-to-mean ratio (VMR) while ignoring `NaN` values. +* +* ## Method +* +* - Let \\(W\\) be a window of \\(N\\) elements over which we want to compute a variance-to-mean ratio (VMR). +* +* - The difference between the unbiased sample variance in a window \\(W_i\\) and the unbiased sample variance in a window \\(W_{i+1})\\) is given by +* +* ```tex +* \Delta s^2 = s_{i+1}^2 - s_{i}^2 +* ``` +* +* - If we multiply both sides by \\(N-1\\), +* +* ```tex +* (N-1)(\Delta s^2) = (N-1)s_{i+1}^2 - (N-1)s_{i}^2 +* ``` +* +* - If we substitute the definition of the unbiased sample variance having the form +* +* ```tex +* \begin{align*} +* s^2 &= \frac{1}{N-1} \biggl( \sum_{i=1}^{N} (x_i - \bar{x})^2 \biggr) \\ +* &= \frac{1}{N-1} \biggl( \sum_{i=1}^{N} (x_i^2 - 2\bar{x}x_i + \bar{x}^2) \biggr) \\ +* &= \frac{1}{N-1} \biggl( \sum_{i=1}^{N} x_i^2 - 2\bar{x} \sum_{i=1}^{N} x_i + \sum_{i=1}^{N} \bar{x}^2) \biggr) \\ +* &= \frac{1}{N-1} \biggl( \sum_{i=1}^{N} x_i^2 - \frac{2N\bar{x}\sum_{i=1}^{N} x_i}{N} + N\bar{x}^2 \biggr) \\ +* &= \frac{1}{N-1} \biggl( \sum_{i=1}^{N} x_i^2 - 2N\bar{x}^2 + N\bar{x}^2 \biggr) \\ +* &= \frac{1}{N-1} \biggl( \sum_{i=1}^{N} x_i^2 - N\bar{x}^2 \biggr) +* \end{align*} +* ``` +* +* we return +* +* ```tex +* (N-1)(\Delta s^2) = \biggl(\sum_{k=1}^N x_k^2 - N\bar{x}_{i+1}^2 \biggr) - \biggl(\sum_{k=0}^{N-1} x_k^2 - N\bar{x}_{i}^2 \biggr) +* ``` +* +* - This can be further simplified by recognizing that subtracting the sums reduces to \\(x_N^2 - x_0^2\\); in which case, +* +* ```tex +* \begin{align*} +* (N-1)(\Delta s^2) &= x_N^2 - x_0^2 - N\bar{x}_{i+1}^2 + N\bar{x}_{i}^2 \\ +* &= x_N^2 - x_0^2 - N(\bar{x}_{i+1}^2 - \bar{x}_{i}^2) \\ +* &= x_N^2 - x_0^2 - N(\bar{x}_{i+1} - \bar{x}_{i})(\bar{x}_{i+1} + \bar{x}_{i}) +* \end{align*} +* ``` +* +* - Recognizing that the difference of means can be expressed +* +* ```tex +* \bar{x}_{i+1} - \bar{x}_i = \frac{1}{N} \biggl( \sum_{k=1}^N x_k - \sum_{k=0}^{N-1} x_k \biggr) = \frac{x_N - x_0}{N} +* ``` +* +* and substituting into the equation above +* +* ```tex +* (N-1)(\Delta s^2) = x_N^2 - x_0^2 - (x_N - x_0)(\bar{x}_{i+1} + \bar{x}_{i}) +* ``` +* +* - Rearranging terms gives us the update equation for the unbiased sample variance +* +* ```tex +* \begin{align*} +* (N-1)(\Delta s^2) &= (x_N - x_0)(x_N + x_0) - (x_N - x_0)(\bar{x}_{i+1} + \bar{x}_{i}) \\ +* &= (x_N - x_0)(x_N + x_0 - \bar{x}_{i+1} - \bar{x}_{i}) \\ +* &= (x_N - x_0)(x_N - \bar{x}_{i+1} + x_0 - \bar{x}_{i}) +* \end{align*} +* ``` +* +* @param {PositiveInteger} W - window size +* @param {number} [mean] - mean value +* @throws {TypeError} first argument must be a positive integer +* @throws {TypeError} second argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanmvmr( 3 ); +* +* var F = accumulator(); +* // returns null +* +* F = accumulator( 2.0 ); +* // returns 0.0 +* +* F = accumulator( NaN ); +* // returns 0.0 +* +* F = accumulator( 1.0 ); +* // returns ~0.33 +* +* F = accumulator( 3.0 ); +* // returns 0.5 +* +* F = accumulator( NaN ); +* // returns 0.5 +* +* F = accumulator( 7.0 ); +* // returns ~2.55 +* +* F = accumulator(); +* // returns ~2.55 +* +* @example +* var accumulator = incrnanmvmr( 3, 2.0 ); +*/ +function incrnanmvmr( W, mean ) { + var acc; + if ( arguments.length > 1 ) { + acc = incrmvmr( W, mean ); + } else { + acc = incrmvmr( W ); + } + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated accumulated value. If not provided a value, the accumulator function returns the current accumulated value. + * + * @private + * @param {number} [x] - input value + * @returns {(number|null)} accumulated value or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return acc(); + } + return acc( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanmvmr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/package.json b/lib/node_modules/@stdlib/stats/incr/nanmvmr/package.json new file mode 100644 index 000000000000..f22709614459 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/package.json @@ -0,0 +1,79 @@ +{ + "name": "@stdlib/stats/incr/nanmvmr", + "version": "0.0.0", + "description": "Compute a moving variance-to-mean ratio (VMR) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "variance", + "sample", + "sample variance", + "unbiased", + "dispersion", + "index of dispersion", + "fano factor", + "fano", + "dispersion index", + "relative variance", + "vmr", + "mean", + "ratio", + "incremental", + "accumulator", + "sliding window", + "sliding", + "window", + "moving", + "nan" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanmvmr/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmvmr/test/test.js new file mode 100644 index 000000000000..2c64b8efe9d4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanmvmr/test/test.js @@ -0,0 +1,523 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var randu = require( '@stdlib/random/base/randu' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var incrnanmvmr = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanmvmr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmvmr( value ); + }; + } +}); + +tape( 'the function throws an error if not provided a positive integer for the window size (known mean)', function test( t ) { + var values; + var i; + + values = [ + '5', + -5.0, + 0.0, + 3.14, + true, + null, + void 0, + NaN, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmvmr( value, 3.0 ); + }; + } +}); + +tape( 'the function throws an error if not provided a number as the mean value', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanmvmr( 3, value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanmvmr( 3 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known mean)', function test( t ) { + t.equal( typeof incrnanmvmr( 3, 3.0 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving variance-to-mean ratio incrementally', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ]; + N = data.length; + + expected = [ + 0.0/2.0, + 0.5/2.5, + 1.0/3.0, + 7.0/2.0, + 7.0/2.0, + 4.0/1.0 + ]; + + acc = incrnanmvmr( 3 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + t.deepEqual( actual, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function computes a moving variance-to-mean ratio incrementally (known mean)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var N; + var i; + + data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ]; + N = data.length; + + acc = incrnanmvmr( 3, 2.0 ); + + actual = []; + for ( i = 0; i < N; i++ ) { + actual.push( acc( data[ i ] ) ); + } + expected = [ + 0.0/2.0, + 0.5/2.0, + 1.6666666666666667/2.0, + 4.666666666666667/2.0, + 4.666666666666667/2.0, + 3.6666666666666665/2.0 + ]; + t.deepEqual( actual, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current accumulated value', function test( t ) { + var expected; + var actual; + var data; + var acc; + var i; + + data = [ 2.0, 3.0, 10.0 ]; + acc = incrnanmvmr( 3 ); + for ( i = 0; i < data.length-1; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 0.5/2.5, 'returns expected value' ); + + acc( data[ data.length-1 ] ); + + expected = 19.0/5.0; + actual = acc(); + t.strictEqual( isAlmostSameValue( actual, expected, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current accumulated value (known mean)', function test( t ) { + var expected; + var actual; + var data; + var acc; + var i; + + data = [ 2.0, 3.0, 10.0 ]; + acc = incrnanmvmr( 3, 5.0 ); + for ( i = 0; i < data.length-1; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 6.5/5.0, 'returns expected value' ); + + acc( data[ data.length-1 ] ); + + expected = 12.666666666666666/5.0; + actual = acc(); + t.strictEqual( isAlmostSameValue( actual, expected, 2 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) { + var acc = incrnanmvmr( 3 ); + t.equal( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if data has yet to be provided, the accumulator function returns `null` (known mean)', function test( t ) { + var acc = incrnanmvmr( 3, 3.0 ); + t.equal( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the mean is unknown, the accumulator function returns `0`', function test( t ) { + var acc = incrnanmvmr( 3 ); + acc( 2.0 ); + t.equal( acc(), 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if only one datum has been provided and the mean is known, the accumulator function may not return `0`', function test( t ) { + var acc = incrnanmvmr( 3, 30 ); + acc( 2.0 ); + t.notEqual( acc(), 0.0, 'returns expected value' ); + t.end(); +}); + +tape( 'if the window size is `1` and the mean is unknown, the accumulator function always returns `0`', function test( t ) { + var acc; + var F; + var i; + + acc = incrnanmvmr( 1 ); + for ( i = 0; i < 100; i++ ) { + F = acc( randu() * 100.0 ); + t.equal( F, 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'if the window size is `1` and the mean is known, the accumulator function may not always return `0`', function test( t ) { + var acc; + var F; + var i; + + acc = incrnanmvmr( 1, 500.0 ); // mean is outside the range of simulated values so the variance should never be zero + for ( i = 0; i < 100; i++ ) { + F = acc( randu() * 100.0 ); + t.notEqual( F, 0.0, 'returns expected value' ); + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is not affected (unknown mean)', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmvmr( 3 ); + + data = [ + NaN, // NaN (ignored) + 3.14, // 3.14 + 3.14, // 3.14, 3.14 + NaN, // 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14 // 3.14, 3.14, 3.14 + ]; + expected = [ + null, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + t.equal( acc(), expected[ i ], 'returns expected value for window '+i ); + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is not affected (known mean)', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmvmr( 3, 3.14 ); + + data = [ + NaN, // NaN (ignored) + 3.14, // 3.14 + 3.14, // 3.14, 3.14 + NaN, // 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14, // 3.14, 3.14, 3.14 + 3.14, // 3.14, 3.14, 3.14 + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + NaN, // 3.14, 3.14, 3.14 (NaN ignored) + 3.14 // 3.14, 3.14, 3.14 + ]; + expected = [ + null, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + t.equal( acc(), expected[ i ], 'returns expected value for window '+i ); + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is not affected (unknown mean, W=1)', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmvmr( 1 ); + + data = [ + NaN, // NaN (ignored) + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + 3.14, // 3.14 + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + 3.14, // 3.14 + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + NaN, // 3.14 (NaN ignored) + NaN, // 3.14 (NaN ignored) + NaN, // 3.14 (NaN ignored) + 3.14 // 3.14 + ]; + expected = [ + null, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + t.equal( acc(), expected[ i ], 'returns expected value for window '+i ); + } + t.end(); +}); + +tape( 'if provided `NaN`, the accumulated value is not affected (known mean, W=1)', function test( t ) { + var expected; + var data; + var acc; + var v; + var i; + + acc = incrnanmvmr( 1, 3.14 ); + + data = [ + NaN, // NaN (ignored) + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + 3.14, // 3.14 + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + 3.14, // 3.14 + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + 3.14, // 3.14 + 3.14, // 3.14 + NaN, // 3.14 (NaN ignored) + NaN, // 3.14 (NaN ignored) + NaN, // 3.14 (NaN ignored) + NaN, // 3.14 (NaN ignored) + 3.14 // 3.14 + ]; + expected = [ + null, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0, + 0.0 + ]; + for ( i = 0; i < data.length; i++ ) { + v = acc( data[ i ] ); + t.equal( v, expected[ i ], 'returns expected value for window '+i ); + t.equal( acc(), expected[ i ], 'returns expected value for window '+i ); + } + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/README.md b/lib/node_modules/@stdlib/stats/incr/nanpcorr/README.md new file mode 100644 index 000000000000..e226e7fdcb8c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/README.md @@ -0,0 +1,180 @@ + + +# incrnanpcorr + +> Compute a [sample Pearson product-moment correlation coefficient][pearson-correlation] incrementally, ignoring `NaN` values. + +
+ +The [Pearson product-moment correlation coefficient][pearson-correlation] between random variables `X` and `Y` is defined as + + + +```math +\rho_{X,Y} = \frac{\mathop{\mathrm{cov}}(X,Y)}{\sigma_X \sigma_Y} +``` + + + + + +where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations. + +For a sample of size `n`, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is defined as + + + +```math +r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}} +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanpcorr = require( '@stdlib/stats/incr/nanpcorr' ); +``` + +#### incrnanpcorr( \[mx, my] ) + +Returns an accumulator function which incrementally computes a [sample Pearson product-moment correlation coefficient][pearson-correlation], ignoring `NaN` values. + +```javascript +var accumulator = incrnanpcorr(); +``` + +If the means are already known, provide `mx` and `my` arguments. + +```javascript +var accumulator = incrnanpcorr( 3.0, -5.5 ); +``` + +#### accumulator( \[x, y] ) + +If provided input value `x` and `y`, the accumulator function returns an updated [sample correlation coefficient][pearson-correlation]. If not provided input values `x` and `y`, the accumulator function returns the current [sample correlation coefficient][pearson-correlation]. + +```javascript +var accumulator = incrnanpcorr(); + +var v = accumulator( 2.0, 1.0 ); +// returns 0.0 + +v = accumulator( NaN, 1.0 ); +// returns 0.0 + +v = accumulator( 1.0, -5.0 ); +// returns 1.0 + +v = accumulator( 1.0, NaN ); +// returns 1.0 + +v = accumulator( 3.0, 3.14 ); +// returns ~0.965 + +v = accumulator(); +// returns ~0.965 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanpcorr = require( '@stdlib/stats/incr/nanpcorr' ); + +var accumulator; +var r; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanpcorr(); + +// For each simulated datum, update the sample Pearson correlation coefficient... +console.log( '\nx\ty\tCorrelation Coefficient\n' ); +for ( i = 0; i < 100; i++ ) { + x = ( randu() < 0.2 ) ? NaN : randu()*100.0; // ~20% NaN values assigned to `x` + y = ( randu() < 0.2 ) ? NaN : randu()*100.0; // ~20% NaN values assigned to `y` + r = accumulator( x, y ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +[covariance]: https://en.wikipedia.org/wiki/Covariance + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr/benchmark/benchmark.js new file mode 100644 index 000000000000..56568445d5c3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/benchmark/benchmark.js @@ -0,0 +1,91 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanpcorr = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanpcorr(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanpcorr(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i, i ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanpcorr( 3.0, -2.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( i, i ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/img/equation_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/img/equation_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..61e3ef3e3500 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/img/equation_pearson_correlation_coefficient.svg @@ -0,0 +1,48 @@ + +rho Subscript upper X comma upper Y Baseline equals StartFraction c o v left-parenthesis upper X comma upper Y right-parenthesis Over sigma Subscript upper X Baseline sigma Subscript upper Y Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..31facfed161b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg @@ -0,0 +1,126 @@ + +r equals StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis Over StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis squared EndRoot EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/repl.txt new file mode 100644 index 000000000000..8b28f55b3e85 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/repl.txt @@ -0,0 +1,41 @@ + +{{alias}}( [mx, my] ) + Returns an accumulator function which incrementally computes a sample + Pearson product-moment correlation coefficient, ignoring `NaN` values. + + If provided values, the accumulator function returns an updated sample + correlation coefficient. If not provided values, the accumulator function + returns the current sample correlation coefficient. + + Parameters + ---------- + mx: number (optional) + Known mean. + + my: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var r = accumulator() + null + > r = accumulator( 2.0, 1.0 ) + 0.0 + > r = accumulator( NaN, 1.0 ) + 0.0 + > r = accumulator( -5.0, 3.14 ) + ~-1.0 + > r = accumulator( -5.0, NaN ) + ~-1.0 + > r = accumulator() + ~-1.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/types/index.d.ts new file mode 100644 index 000000000000..8386d7168f1e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/types/index.d.ts @@ -0,0 +1,69 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated sample correlation coefficient. +* +* @param x - value +* @param y - value +* @returns updated sample correlation coefficient +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes an updated sample correlation coefficient, ignoring `NaN` values. +* +* @param meanx - mean value +* @param meany - mean value +* @returns accumulator function +* +* @example +* var accumulator = incrnanpcorr( 2.0, -3.0 ); +*/ +declare function incrnanpcorr( meanx: number, meany: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes an updated sample correlation coefficient, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanpcorr(); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r = accumulator( -5.0, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator(); +* // returns ~-1.0 +*/ +declare function incrnanpcorr(): accumulator; + + +// EXPORTS // + +export = incrnanpcorr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/types/test.ts new file mode 100644 index 000000000000..f9ac670620d5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/docs/types/test.ts @@ -0,0 +1,113 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanpcorr = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanpcorr(); // $ExpectType accumulator + incrnanpcorr( 2, 4 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided non-numeric arguments... +{ + incrnanpcorr( 2, '5' ); // $ExpectError + incrnanpcorr( 2, true ); // $ExpectError + incrnanpcorr( 2, false ); // $ExpectError + incrnanpcorr( 2, null ); // $ExpectError + incrnanpcorr( 2, undefined ); // $ExpectError + incrnanpcorr( 2, [] ); // $ExpectError + incrnanpcorr( 2, {} ); // $ExpectError + incrnanpcorr( 2, ( x: number ): number => x ); // $ExpectError + + incrnanpcorr( '5', 4 ); // $ExpectError + incrnanpcorr( true, 4 ); // $ExpectError + incrnanpcorr( false, 4 ); // $ExpectError + incrnanpcorr( null, 4 ); // $ExpectError + incrnanpcorr( undefined, 4 ); // $ExpectError + incrnanpcorr( [], 4 ); // $ExpectError + incrnanpcorr( {}, 4 ); // $ExpectError + incrnanpcorr( ( x: number ): number => x, 4 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanpcorr( 1 ); // $ExpectError + incrnanpcorr( 2, 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanpcorr(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The function returns an accumulator function which returns an accumulated result (known means)... +{ + const acc = incrnanpcorr( 2, -3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanpcorr(); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)... +{ + const acc = incrnanpcorr( 2, -3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr/examples/index.js new file mode 100644 index 000000000000..e216af051205 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/examples/index.js @@ -0,0 +1,39 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanpcorr = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanpcorr(); + +// For each simulated datum, update the sample Pearson correlation coefficient... +console.log( '\nx\ty\tCorrelation Coefficient\n' ); +var r; +var x; +var y; +var i; +for ( i = 0; i < 100; i++ ) { + x = ( randu() < 0.2 ) ? NaN : randu() * 100.0; // ~20% NaN values assigned to `x` + y = ( randu() < 0.2 ) ? NaN : randu() * 100.0; // ~20% NaN values assigned to `y` + r = accumulator( x, y ); + console.log( '%d\t%d\t%d', x.toFixed( 4 ), y.toFixed( 4 ), ( r === null ) ? NaN : r.toFixed( 4 ) ); +} +console.log( '\nFinal r: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr/lib/index.js new file mode 100644 index 000000000000..4f20d7e10e41 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a sample Pearson product-moment correlation coefficient incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanpcorr +* +* @example +* var incrnanpcorr = require( '@stdlib/stats/incr/nanpcorr' ); +* +* var accumulator = incrnanpcorr(); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r = accumulator( -5.0, NaN ); +* // returns 0.0 +* +* r = accumulator( -5.0, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator( NaN, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator(); +* // returns ~-1.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr/lib/main.js new file mode 100644 index 000000000000..13b224c80139 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/lib/main.js @@ -0,0 +1,205 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrpcorr = require( '@stdlib/stats/incr/pcorr' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* ## Method +* +* - We begin by defining the co-moment \\(C_n\\) +* +* ```tex +* C_n = \sum_{i=1}^{n} ( x_i - \bar{x}_n ) ( y_i - \bar{y}_n ) +* ``` +* +* where \\(\bar{x}_n\\) and \\(\bar{y}_n\\) are the sample means for \\(x\\) and \\(y\\), respectively. +* +* - Based on Welford's method, we know the update formulas for the sample means are given by +* +* ```tex +* \bar{x}_n = \bar{x}_{n-1} + \frac{x_n - \bar{x}_{n-1}}{n} +* ``` +* +* and +* +* ```tex +* \bar{y}_n = \bar{y}_{n-1} + \frac{y_n - \bar{y}_{n-1}}{n} +* ``` +* +* - Substituting into the equation for \\(C_n\\) and rearranging terms +* +* ```tex +* C_n = C_{n-1} + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1}) +* ``` +* +* where the apparent asymmetry arises from +* +* ```tex +* x_n - \bar{x}_n = \frac{n-1}{n} (x_n - \bar{x}_{n-1}) +* ``` +* +* and, hence, the update term can be equivalently expressed +* +* ```tex +* \frac{n-1}{n} (x_n - \bar{x}_{n-1}) (y_n - \bar{y}_{n-1}) +* ``` +* +* - The covariance can be defined +* +* ```tex +* \begin{align*} +* \operatorname{cov}_n(x,y) &= \frac{C_n}{n} \\ +* &= \frac{C_{n-1} + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n} \\ +* &= \frac{(n-1)\operatorname{cov}_{n-1}(x,y) + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n} +* \end{align*} +* ``` +* +* - Applying Bessel's correction, we arrive at an update formula for calculating an unbiased sample covariance +* +* ```tex +* \begin{align*} +* \operatorname{cov}_n(x,y) &= \frac{n}{n-1}\cdot\frac{(n-1)\operatorname{cov}_{n-1}(x,y) + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n} \\ +* &= \operatorname{cov}_{n-1}(x,y) + \frac{(x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n-1} \\ +* &= \frac{C_{n-1} + (x_n - \bar{x}_n) (y_n - \bar{y}_{n-1})}{n-1} +* &= \frac{C_{n-1} + (x_n - \bar{x}_{n-1}) (y_n - \bar{y}_n)}{n-1} +* \end{align*} +* ``` +* +* - To calculate the corrected sample standard deviation, we can use Welford's method, which can be derived as follows. We can express the variance as +* +* ```tex +* \begin{align*} +* S_n &= n \sigma_n^2 \\ +* &= \sum_{i=1}^{n} (x_i - \mu_n)^2 \\ +* &= \biggl(\sum_{i=1}^{n} x_i^2 \biggr) - n\mu_n^2 +* \end{align*} +* ``` +* +* Accordingly, +* +* ```tex +* \begin{align*} +* S_n - S_{n-1} &= \sum_{i=1}^{n} x_i^2 - n\mu_n^2 - \sum_{i=1}^{n-1} x_i^2 + (n-1)\mu_{n-1}^2 \\ +* &= x_n^2 - n\mu_n^2 + (n-1)\mu_{n-1}^2 \\ +* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1}^2 - \mu_n^2) \\ +* &= x_n^2 - \mu_{n-1}^2 + n(\mu_{n-1} - \mu_n)(\mu_{n-1} + \mu_n) \\ +* &= x_n^2 - \mu_{n-1}^2 + (\mu_{n-1} - x_n)(\mu_{n-1} + \mu_n) \\ +* &= x_n^2 - \mu_{n-1}^2 + \mu_{n-1}^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ +* &= x_n^2 - x_n\mu_n - x_n\mu_{n-1} + \mu_n\mu_{n-1} \\ +* &= (x_n - \mu_{n-1})(x_n - \mu_n) \\ +* &= S_{n-1} + (x_n - \mu_{n-1})(x_n - \mu_n) +* \end{align*} +* ``` +* +* where we use the identity +* +* ```tex +* x_n - \mu_{n-1} = n (\mu_n - \mu_{n-1}) +* ``` +* +* - To compute the corrected sample standard deviation, we apply Bessel's correction and take the square root. +* +* - The sample Pearson product-moment correlation coefficient can thus be calculated as +* +* ```tex +* r = \frac{\operatorname{cov}_n(x,y)}{\sigma_x \sigma_y} +* ``` +* +* where \\(\sigma_x\\) and \\(\sigma_y\\) are the corrected sample standard deviations for \\(x\\) and \\(y\\), respectively. +* +* @param {number} [meanx] - mean value +* @param {number} [meany] - mean value +* @throws {TypeError} first argument must be a number +* @throws {TypeError} second argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanpcorr(); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r = accumulator( -5.0, NaN ); +* // returns 0.0 +* +* r = accumulator( -5.0, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator( NaN, 3.14 ); +* // returns ~-1.0 +* +* r = accumulator(); +* // returns ~-1.0 +* +* @example +* var accumulator = incrnanpcorr( 2.0, -3.0 ); +*/ +function incrnanpcorr( meanx, meany ) { + var pcorr; + var N; + + if ( arguments.length ) { + pcorr = incrpcorr( meanx, meany ); + } else { + pcorr = incrpcorr(); + } + + N = 0; + + return accumulator; + + /** + * Accumulator function that updates the sample correlation coefficient, ignoring `NaN` values. + * + * @private + * @param {number} [x] - new value + * @param {number} [y] - new value + * @returns {(number|null)} sample correlation coefficient or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 ) { + if ( N === 0 ) { + return null; + } + return pcorr(); + } + if ( isnan( x ) || isnan( y ) ) { + return pcorr(); + } + N += 1; + return pcorr( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanpcorr; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/package.json b/lib/node_modules/@stdlib/stats/incr/nanpcorr/package.json new file mode 100644 index 000000000000..c8151f432419 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/incr/nanpcorr", + "version": "0.0.0", + "description": "Compute a sample Pearson product-moment correlation coefficient, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "covariance", + "sample covariance", + "variance", + "unbiased", + "var", + "correlation", + "corr", + "pearson", + "product-moment", + "bivariate", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr/test/test.js new file mode 100644 index 000000000000..abd31aeceb31 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr/test/test.js @@ -0,0 +1,270 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanpcorr = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanpcorr, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a non-numeric value for the first argument', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanpcorr( value, 5.0 ); + }; + } +}); + +tape( 'the function throws an error if provided a non-numeric value for the second argument', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanpcorr( 3.0, value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanpcorr(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known means)', function test( t ) { + t.equal( typeof incrnanpcorr( 3.0, -5.0 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a sample correlation coefficient', function test( t ) { + var expected; + var actual; + var delta; + var tol; + var acc; + var x; + var y; + var i; + + x = [ 2.0, NaN, 3.0, 2.0, 2.0, 4.0, 3.0, NaN, 4.0 ]; + y = [ 1.5, 1.5, -0.6, 3.14, NaN, 4.0, -2.0, NaN, 10.0 ]; + + // Test against Julia: (sum((x[1:n]-mean(x[1:n])).*(y[1:n]-mean(y[1:n]))[:])/(n-1))/(std(x[1:n])*std(y[1:n])) + expected = [ + 0.0, + 0.0, + -1.0, + -0.8992664495010921, + -0.8992664495010921, + 0.23547201823172273, + 0.06765492498103522, + 0.06765492498103522, + 0.4944446711225878 + ]; + + acc = incrnanpcorr(); + + for ( i = 0; i < x.length; i++ ) { + actual = acc( x[ i ], y[ i ] ); + if ( actual === expected[ i ] ) { + t.strictEqual( actual, expected[ i ], 'returns expected result. x: '+x[i]+'. y: '+y[i]+'.' ); + } else { + delta = abs( expected[ i ] - actual ); + tol = 3.7 * EPS * abs( expected[ i ] ); + t.equal( delta <= tol, true, 'x: '+x[i]+'. y: '+y[i]+'. expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the accumulator function incrementally computes a sample correlation coefficient (known means)', function test( t ) { + var expected; + var actual; + var delta; + var tol; + var acc; + var x; + var y; + var i; + + x = [ 2.0, NaN, 3.0, 2.0, 2.0, 4.0, 3.0, NaN, 4.0 ]; + y = [ 1.5, -0.6, -0.6, 3.14, NaN, 4.0, -2.0, NaN, 10.0 ]; + + // Test against Julia: (sum((x[1:n]-3.0).*(y[1:n]-2.6733333333333333)[:])/(n-1))/(stdm(x[1:n],3.0)*stdm(y[1:n],2.6733333333333333)) + expected = [ + 1.0, + 1.0, + 0.337429241307504, + 0.14242449698664145, + 0.14242449698664145, + 0.31297710227544034, + 0.19590456246309015, + 0.19590456246309015, + 0.4944446711225878 + ]; + + acc = incrnanpcorr( 3.0, 2.6733333333333333 ); + + for ( i = 0; i < x.length; i++ ) { + actual = acc( x[ i ], y[ i ] ); + if ( actual === expected[ i ] ) { + t.strictEqual( actual, expected[ i ], 'returns expected result. x: '+x[i]+'. y: '+y[i]+'.' ); + } else { + delta = abs( expected[ i ] - actual ); + tol = EPS * abs( expected[ i ] ); + t.equal( delta <= tol, true, 'x: '+x[i]+'. y: '+y[i]+'. expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation coefficient', function test( t ) { + var acc; + var x; + var y; + var i; + + x = [ 2.0, NaN, 3.0, 3.0, 1.0 ]; + y = [ 3.14, -1.0, -1.0, NaN, 2.4 ]; + + acc = incrnanpcorr(); + for ( i = 0; i < x.length; i++ ) { + acc( x[ i ], y[ i ] ); + } + t.equal( acc(), -0.7699852380946451, 'returns expected result' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation coefficient (known means)', function test( t ) { + var acc; + var x; + var y; + var i; + + x = [ 2.0, NaN, 3.0, 3.0, 1.0 ]; + y = [ 3.14, -1.0, -1.0, NaN, 2.4 ]; + + acc = incrnanpcorr( 2.0, 1.5133333333333334 ); + for ( i = 0; i < x.length; i++ ) { + acc( x[ i ], y[ i ] ); + } + t.equal( acc(), -0.7699852380946453, 'returns expected result' ); + t.end(); +}); + +tape( 'the sample correlation coefficient is `null` until at least 1 datum has been provided (unknown means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorr(); + + v = acc(); + t.equal( v, null, 'returns null' ); + + v = acc( 2.0, 10.0 ); + t.notEqual( v, null, 'does not return null' ); + + v = acc(); + t.notEqual( v, null, 'does not return null' ); + + t.end(); +}); + +tape( 'the sample correlation coefficient is `null` until at least 1 datum has been provided (known means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorr( 3.0, -5.0 ); + + v = acc(); + t.equal( v, null, 'returns null' ); + + v = acc( 2.0, 10.0 ); + t.notEqual( v, null, 'does not return null' ); + + v = acc(); + t.notEqual( v, null, 'does not return null' ); + + t.end(); +}); + +tape( 'the sample correlation coefficient is `0` until at least 2 datums have been provided (unknown means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorr(); + + v = acc( 2.0, 10.0 ); + t.equal( v, 0.0, 'returns 0' ); + + v = acc(); + t.equal( v, 0.0, 'returns 0' ); + + v = acc( 3.0, -3.14 ); + t.notEqual( v, 0.0, 'does not return 0' ); + + v = acc(); + t.notEqual( v, 0.0, 'does not return 0' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/README.md b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/README.md new file mode 100644 index 000000000000..e8faf3c9a598 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/README.md @@ -0,0 +1,180 @@ + + +# incrnanpcorr2 + +> Compute a squared sample [Pearson product-moment correlation coefficient][pearson-correlation] incrementally, ignoring `NaN` values. + +
+ +The [Pearson product-moment correlation coefficient][pearson-correlation] between random variables `X` and `Y` is defined as + + + +```math +\rho_{X,Y} = \frac{\mathop{\mathrm{cov}}(X,Y)}{\sigma_X \sigma_Y} +``` + + + + + +where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations. + +For a sample of size `n`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as + + + +```math +r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}} +``` + + + + + +The squared sample [Pearson product-moment correlation coefficient][pearson-correlation] is thus defined as the square of the sample [Pearson product-moment correlation coefficient][pearson-correlation]. + +
+ + + +
+ +## Usage + +```javascript +var incrnanpcorr2 = require( '@stdlib/stats/incr/nanpcorr2' ); +``` + +#### incrnanpcorr2( \[mx, my] ) + +Returns an accumulator `function` which incrementally computes a squared sample [Pearson product-moment correlation coefficient][pearson-correlation]. + +```javascript +var accumulator = incrnanpcorr2(); +``` + +If the means are already known, provide `mx` and `my` arguments. + +```javascript +var accumulator = incrnanpcorr2( 3.0, -5.5 ); +``` + +#### accumulator( \[x, y] ) + +If provided input value `x` and `y`, the accumulator function returns an updated accumulated value. If not provided input values `x` and `y`, the accumulator function returns the current accumulated value. + +```javascript +var accumulator = incrnanpcorr2(); + +var r2 = accumulator( 2.0, 1.0 ); +// returns 0.0 + +r2 = accumulator( 1.0, 90.0 ); +// returns 1.0 + +r2 = accumulator( NaN, NaN ); +// returns ~1.0 + +r2 = accumulator( 8.0, NaN ); +// returns ~1.0 + +r2 = accumulator(); +// returns ~1.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN`, the `NaN` value is ignored. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- In comparison to the sample [Pearson product-moment correlation coefficient][pearson-correlation], the squared sample [Pearson product-moment correlation coefficient][pearson-correlation] is useful for emphasizing strong correlations. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanpcorr2 = require( '@stdlib/stats/incr/nanpcorr2' ); + +// Initialize an accumulator: +var accumulator = incrnanpcorr2(); + +// For each simulated datum, update the squared sample correlation coefficient... +console.log( '\nx\ty\tr^2\n' ); +var r2; +var x; +var y; +var i; +for ( i = 0; i < 100; i++ ) { + x = ( randu() < 0.9 ) ? ( randu() * 100.0 ) : NaN; + y = ( randu() < 0.9 ) ? ( randu() * 100.0 ) : NaN; + r2 = accumulator( x, y ); + console.log( '%s\t%s\t%s', ( isnan( x ) ) ? 'NaN' : x.toFixed( 4 ), ( isnan( y ) ) ? 'NaN' : y.toFixed( 4 ), ( r2 === null ) ? 'null' : r2.toFixed( 4 ) ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +[covariance]: https://en.wikipedia.org/wiki/Covariance + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/benchmark/benchmark.js new file mode 100644 index 000000000000..4f0301bc35af --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/benchmark/benchmark.js @@ -0,0 +1,96 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var uniform = require( '@stdlib/random/array/uniform' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanpcorr2 = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanpcorr2(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var values; + var acc; + var v; + var i; + + values = uniform( 100, -100.0, 100.0 ); + acc = incrnanpcorr2(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( values[ i%values.length ], values[ (i+1)%values.length ] ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { + var values; + var acc; + var v; + var i; + + values = uniform( 100, -100.0, 100.0 ); + acc = incrnanpcorr2( 3.0, -2.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( values[ i%values.length ], values[ (i+1)%values.length ] ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/img/equation_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/img/equation_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..61e3ef3e3500 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/img/equation_pearson_correlation_coefficient.svg @@ -0,0 +1,48 @@ + +rho Subscript upper X comma upper Y Baseline equals StartFraction c o v left-parenthesis upper X comma upper Y right-parenthesis Over sigma Subscript upper X Baseline sigma Subscript upper Y Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg new file mode 100644 index 000000000000..31facfed161b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg @@ -0,0 +1,126 @@ + +r equals StartFraction sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis Over StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis x Subscript i Baseline minus x overbar right-parenthesis squared EndRoot StartRoot sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis y Subscript i Baseline minus y overbar right-parenthesis squared EndRoot EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/repl.txt new file mode 100644 index 000000000000..0acb28ddd56b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/repl.txt @@ -0,0 +1,43 @@ + +{{alias}}( [mx, my] ) + Returns an accumulator function which incrementally computes the squared + sample Pearson product-moment correlation coefficient ignoring NaN values. + + If provided values, the accumulator function returns an updated accumulated + value. If not provided values, the accumulator function returns the current + accumulated value. + + Parameters + ---------- + mx: number (optional) + Known mean. + + my: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var r2 = accumulator() + null + > r2 = accumulator( 2.0, 1.0 ) + 0.0 + > r2 = accumulator( 1.0, 90.0 ) + 1.0 + > r2 = accumulator( -5.0, NaN ) + ~1.0 + > r2 = accumulator( NaN, NaN ) + ~1.0 + > r2 = accumulator( NaN, -8.0 ) + ~1.0 + > r2 = accumulator() + ~1.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/types/index.d.ts new file mode 100644 index 000000000000..584c166acbeb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/types/index.d.ts @@ -0,0 +1,78 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated squared sample correlation coefficient. +* +* @param x - value +* @param y - value +* @returns updated squared sample correlation coefficient +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a squared sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @param meanx - mean value +* @param meany - mean value +* @returns accumulator function +* +* @example +* var accumulator = incrnanpcorr2( 2.0, -3.0 ); +*/ +declare function incrnanpcorr2( meanx: number, meany: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes a squared sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanpcorr2(); +* +* var r2 = accumulator(); +* // returns null +* +* r2 = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r2 = accumulator( 1.0, 90.0 ); +* // returns 1.0 +* +* r2 = accumulator( -5.0, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, 8.0 ); +* // returns ~1.0 +* +* r2 = accumulator(); +* // returns ~1.0 +*/ +declare function incrnanpcorr2(): accumulator; + + +// EXPORTS // + +export = incrnanpcorr2; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/types/test.ts new file mode 100644 index 000000000000..7498472005cb --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/docs/types/test.ts @@ -0,0 +1,113 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanpcorr2 = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanpcorr2(); // $ExpectType accumulator + incrnanpcorr2( 2, 4 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided non-numeric arguments... +{ + incrnanpcorr2( 2, '5' ); // $ExpectError + incrnanpcorr2( 2, true ); // $ExpectError + incrnanpcorr2( 2, false ); // $ExpectError + incrnanpcorr2( 2, null ); // $ExpectError + incrnanpcorr2( 2, undefined ); // $ExpectError + incrnanpcorr2( 2, [] ); // $ExpectError + incrnanpcorr2( 2, {} ); // $ExpectError + incrnanpcorr2( 2, ( x: number ): number => x ); // $ExpectError + + incrnanpcorr2( '5', 4 ); // $ExpectError + incrnanpcorr2( true, 4 ); // $ExpectError + incrnanpcorr2( false, 4 ); // $ExpectError + incrnanpcorr2( null, 4 ); // $ExpectError + incrnanpcorr2( undefined, 4 ); // $ExpectError + incrnanpcorr2( [], 4 ); // $ExpectError + incrnanpcorr2( {}, 4 ); // $ExpectError + incrnanpcorr2( ( x: number ): number => x, 4 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanpcorr2( 1 ); // $ExpectError + incrnanpcorr2( 2, 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanpcorr2(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The function returns an accumulator function which returns an accumulated result (known means)... +{ + const acc = incrnanpcorr2( 2, -3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanpcorr2(); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)... +{ + const acc = incrnanpcorr2( 2, -3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/examples/index.js new file mode 100644 index 000000000000..0ce7708f4ea2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanpcorr2 = require( './../lib' ); + +// Initialize an accumulator: +var accumulator = incrnanpcorr2(); + +// For each simulated datum, update the squared sample Pearson correlation coefficient... +console.log( '\nx\ty\tr^2\n' ); +var r2; +var x; +var y; +var i; +for ( i = 0; i < 100; i++ ) { + x = ( randu() < 0.9 ) ? ( randu() * 100.0 ) : NaN; + y = ( randu() < 0.9 ) ? ( randu() * 100.0 ) : NaN; + r2 = accumulator( x, y ); + console.log( '%s\t%s\t%s', ( isnan( x ) ) ? 'NaN' : x.toFixed( 4 ), ( isnan( y ) ) ? 'NaN' : y.toFixed( 4 ), ( r2 === null ) ? 'null' : r2.toFixed( 4 ) ); +} +console.log( '\nFinal r^2: %s\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/index.js new file mode 100644 index 000000000000..5c1475f1361a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a squared sample Pearson product-moment correlation coefficient incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanpcorr2 +* +* @example +* var incrnanpcorr2 = require( '@stdlib/stats/incr/nanpcorr2' ); +* +* var accumulator = incrnanpcorr2(); +* +* var r2 = accumulator(); +* // returns null +* +* r2 = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r2 = accumulator( -5.0, NaN ); +* // returns ~0.0 +* +* r2 = accumulator( NaN, NaN ); +* // returns ~0.0 +* +* r2 = accumulator( NaN, 8.0 ); +* // returns ~0.0 +* +* r2 = accumulator(); +* // returns ~0.0 +*/ + +// MODULES // + +var incrnanpcorr2 = require( './main.js' ); + + +// EXPORTS // + +module.exports = incrnanpcorr2; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/main.js new file mode 100644 index 000000000000..3864dbebbdfa --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/lib/main.js @@ -0,0 +1,93 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrpcorr2 = require( '@stdlib/stats/incr/pcorr2' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a squared sample Pearson product-moment correlation coefficient, ignoring `NaN` values. +* +* @param {number} [meanx] - mean value +* @param {number} [meany] - mean value +* @throws {TypeError} first argument must be a number +* @throws {TypeError} second argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanpcorr2(); +* +* var r2 = accumulator(); +* // returns null +* +* r2 = accumulator( 2.0, 1.0 ); +* // returns 0.0 +* +* r2 = accumulator( 1.0, 90.0 ); +* // returns 1.0 +* +* r2 = accumulator( -5.0, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, NaN ); +* // returns ~1.0 +* +* r2 = accumulator( NaN, 8.0 ); +* // returns ~1.0 +* +* r2 = accumulator(); +* // returns ~1.0 +* +* @example +* var accumulator = incrnanpcorr2( 2.0, -3.0 ); +*/ +function incrnanpcorr2( meanx, meany ) { + var pcorr2; + if ( arguments.length === 0 ) { + pcorr2 = incrpcorr2(); + } else { + pcorr2 = incrpcorr2( meanx, meany ); + } + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated accumulated value. If not provided input values, the accumulator function returns the current accumulate value. + * + * @private + * @param {number} [x] - new value + * @param {number} [y] - new value + * @returns {(number|null)} squared sample correlation coefficient or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return pcorr2(); + } + return pcorr2( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanpcorr2; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/package.json b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/package.json new file mode 100644 index 000000000000..4be0ded63453 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/package.json @@ -0,0 +1,75 @@ +{ + "name": "@stdlib/stats/incr/nanpcorr2", + "version": "0.0.0", + "description": "Compute a squared sample Pearson product-moment correlation coefficient, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "covariance", + "sample covariance", + "variance", + "unbiased", + "var", + "correlation", + "corr", + "pearson", + "product-moment", + "r-squared", + "r2", + "value", + "bivariate", + "nan", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorr2/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/test/test.js new file mode 100644 index 000000000000..0dd8cb0cc145 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorr2/test/test.js @@ -0,0 +1,289 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isAlmostSameValue = require( '@stdlib/assert/is-almost-same-value' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanpcorr2 = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanpcorr2, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a non-numeric value for the first argument', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanpcorr2( value, 5.0 ); + }; + } +}); + +tape( 'the function throws an error if provided a non-numeric value for the second argument', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanpcorr2( 3.0, value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanpcorr2(), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known means)', function test( t ) { + t.equal( typeof incrnanpcorr2( 3.0, -5.0 ), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a square sample correlation coefficient', function test( t ) { + var expected; + var actual; + var acc; + var x; + var y; + var i; + + x = [ 2.0, 3.0, 2.0, 4.0, 3.0, 4.0 ]; + y = [ 1.5, -0.6, 3.14, 4.0, -2.0, 10.0 ]; + + // Test against Julia: ((sum((x[1:n]-mean(x[1:n])).*(y[1:n]-mean(y[1:n]))[:])/(n-1))/(std(x[1:n])*std(y[1:n]))) + expected = [ + 0.0, + -1.0 * -1.0, + -0.8992664495010921 * -0.8992664495010921, + 0.23547201823172273 * 0.23547201823172273, + 0.06765492498103522 * 0.06765492498103522, + 0.4944446711225878 * 0.4944446711225878 + ]; + + acc = incrnanpcorr2(); + + for ( i = 0; i < x.length; i++ ) { + actual = acc( x[ i ], y[ i ] ); + t.strictEqual( isAlmostSameValue( actual, expected[ i ], 8 ), true, 'returns expected value. x: '+x[i]+'. y: '+y[i]+'.' ); + } + t.end(); +}); + +tape( 'the accumulator function incrementally computes a squared sample correlation coefficient (known means)', function test( t ) { + var expected; + var actual; + var acc; + var x; + var y; + var i; + + x = [ 2.0, 3.0, 2.0, 4.0, 3.0, 4.0 ]; + y = [ 1.5, -0.6, 3.14, 4.0, -2.0, 10.0 ]; + + // Test against Julia: (sum((x[1:n]-3.0).*(y[1:n]-2.6733333333333333)[:])/(n-1))/(stdm(x[1:n],3.0)*stdm(y[1:n],2.6733333333333333)) + expected = [ + 1.0, + 0.337429241307504 * 0.337429241307504, + 0.14242449698664145 * 0.14242449698664145, + 0.31297710227544034 * 0.31297710227544034, + 0.19590456246309015 * 0.19590456246309015, + 0.4944446711225878 * 0.4944446711225878 + ]; + + acc = incrnanpcorr2( 3.0, 2.6733333333333333 ); + + for ( i = 0; i < x.length; i++ ) { + actual = acc( x[ i ], y[ i ] ); + t.strictEqual( isAlmostSameValue( actual, expected[ i ], 3 ), true, 'returns expected value. x: '+x[i]+'. y: '+y[i]+'.' ); + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current squared sample correlation coefficient', function test( t ) { + var acc; + var x; + var y; + var i; + + x = [ 2.0, 3.0, 1.0 ]; + y = [ 3.14, -1.0, 2.4 ]; + + acc = incrnanpcorr2(); + for ( i = 0; i < x.length; i++ ) { + acc( x[ i ], y[ i ] ); + } + t.equal( acc(), 0.7699852380946451 * 0.7699852380946451, 'returns expected value' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current squared sample correlation coefficient (known means)', function test( t ) { + var acc; + var x; + var y; + var i; + + x = [ 2.0, 3.0, 1.0 ]; + y = [ 3.14, -1.0, 2.4 ]; + + acc = incrnanpcorr2( 2.0, 1.5133333333333334 ); + for ( i = 0; i < x.length; i++ ) { + acc( x[ i ], y[ i ] ); + } + t.equal( acc(), 0.7699852380946453 * 0.7699852380946453, 'returns expected value' ); + t.end(); +}); + +tape( 'the squared sample correlation coefficient is `null` until at least 1 datum has been provided (unknown means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorr2(); + + v = acc(); + t.equal( v, null, 'returns expected value' ); + + v = acc( 2.0, 10.0 ); + t.notEqual( v, null, 'returns expected value' ); + + v = acc(); + t.notEqual( v, null, 'returns expected value' ); + + t.end(); +}); + +tape( 'the squared sample correlation coefficient is `null` until at least 1 datum has been provided (known means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorr2( 3.0, -5.0 ); + + v = acc(); + t.equal( v, null, 'returns expected value' ); + + v = acc( 2.0, 10.0 ); + t.notEqual( v, null, 'returns expected value' ); + + v = acc(); + t.notEqual( v, null, 'returns expected value' ); + + t.end(); +}); + +tape( 'the squared sample correlation coefficient is `0` until at least 2 datums have been provided (unknown means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorr2(); + + v = acc( 2.0, 10.0 ); + t.equal( v, 0.0, 'returns expected value' ); + + v = acc(); + t.equal( v, 0.0, 'returns expected value' ); + + v = acc( 3.0, -3.14 ); + t.notEqual( v, 0.0, 'returns expected value' ); + + v = acc(); + t.notEqual( v, 0.0, 'returns expected value' ); + + t.end(); +}); + +tape( 'the accumulated result ignores NaN values', function test( t ) { + var expected; + var actual; + var acc; + var x; + var y; + var i; + + // Data with NaN values: + x = [ 2.0, NaN, 3.0, 4.0, NaN, 5.0 ]; + y = [ 1.5, 2.0, NaN, 4.0, 5.0, NaN ]; + + // Effective data: [ [2.0, 1.5], [4.0, 4.0] ] + expected = 1.0; // Perfect correlation with only these two points + + acc = incrnanpcorr2(); + + for ( i = 0; i < x.length; i++ ) { + acc( x[ i ], y[ i ] ); + } + actual = acc(); + t.strictEqual( isAlmostSameValue( actual, expected, 4 ), true, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulated result ignores NaN values (known means)', function test( t ) { + var acc; + + // Create accumulator with known means + acc = incrnanpcorr2( 3.0, 2.0 ); + + acc( 2.0, 1.0 ); + acc( NaN, 3.0 ); + acc( 4.0, NaN ); + acc( 4.0, 3.0 ); + + // NaN values should be ignored in the calculation: + t.strictEqual( isnan( acc() ), false, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/README.md b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/README.md new file mode 100644 index 000000000000..75766bb16f19 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/README.md @@ -0,0 +1,165 @@ + + +# incrnanpcorrdist + +> Compute a [sample Pearson product-moment correlation distance][pearson-correlation] incrementally, ignoring `NaN` values. + +
+ +The [sample Pearson product-moment correlation distance][pearson-correlation] is defined as + + + +```math +d_{x,y} = 1 - r_{x,y} = 1 - \frac{\mathop{\mathrm{cov_n(x,y)}}}{\sigma_x \sigma_y} +``` + + + + + +where `r` is the [sample Pearson product-moment correlation coefficient][pearson-correlation], `cov(x,y)` is the sample covariance, and `σ` corresponds to the sample standard deviation. As `r` resides on the interval `[-1,1]`, `d` resides on the interval `[0,2]`. + +
+ + + +
+ +## Usage + +```javascript +var incrnanpcorrdist = require( '@stdlib/stats/incr/nanpcorrdist' ); +``` + +#### incrnanpcorrdist( \[mx, my] ) + +Returns an accumulator `function` which incrementally computes a [sample Pearson product-moment correlation distance][pearson-correlation], ignoring `NaN` values. + +```javascript +var accumulator = incrnanpcorrdist(); +``` + +If the means are already known, provide `mx` and `my` arguments. + +```javascript +var accumulator = incrnanpcorrdist( 3.0, -5.5 ); +``` + +#### accumulator( \[x, y] ) + +If provided input value `x` and `y`, the accumulator function returns an updated [sample correlation coefficient][pearson-correlation]. If not provided input values `x` and `y`, the accumulator function returns the current [sample correlation coefficient][pearson-correlation]. + +```javascript +var accumulator = incrnanpcorrdist(); + +var d = accumulator( 2.0, 1.0 ); +// returns 1.0 + +d = accumulator( NaN, 1.0 ); +// returns 1.0 + +d = accumulator( 1.0, -5.0 ); +// returns 0.0 + +d = accumulator( 1.0, NaN ); +// returns 0.0 + +d = accumulator( 3.0, 3.14 ); +// returns ~0.035 + +d = accumulator(); +// returns ~0.035 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulator function skips updating its state and continues to return the most recent valid accumulated value. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanpcorrdist = require( '@stdlib/stats/incr/nanpcorrdist' ); + +var accumulator; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanpcorrdist(); + +// For each simulated datum, update the sample correlation distance... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } else { + y = randu() * 100.0; + } + accumulator( x, y ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/benchmark/benchmark.js new file mode 100644 index 000000000000..b016c9556b1f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/benchmark/benchmark.js @@ -0,0 +1,92 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanpcorrdist = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanpcorrdist(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanpcorrdist(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator,known_means', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanpcorrdist( 3.0, -2.0 ); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu(), randu() ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/img/equation_pearson_distance.svg b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/img/equation_pearson_distance.svg new file mode 100644 index 000000000000..6df633f17b81 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/img/equation_pearson_distance.svg @@ -0,0 +1,70 @@ + +d Subscript x comma y Baseline equals 1 minus r Subscript x comma y Baseline equals 1 minus StartFraction normal c normal o normal v Subscript normal n Baseline left-parenthesis normal x comma normal y right-parenthesis Over sigma Subscript x Baseline sigma Subscript y Baseline EndFraction + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/repl.txt new file mode 100644 index 000000000000..c8eda0652460 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/repl.txt @@ -0,0 +1,44 @@ + +{{alias}}( [mx, my] ) + Returns an accumulator function which incrementally computes a sample + Pearson product-moment correlation distance, ignoring `NaN` values. + + The correlation distance is defined as one minus the Pearson product-moment + correlation coefficient and, thus, resides on the interval [0,2]. + + If provided values, the accumulator function returns an updated sample + correlation distance. If not provided values, the accumulator function + returns the current sample correlation distance. + + Parameters + ---------- + mx: number (optional) + Known mean. + + my: number (optional) + Known mean. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var d = accumulator() + null + > d = accumulator( 2.0, 1.0 ) + 1.0 + > d = accumulator( NaN, 1.0 ) + 1.0 + > d = accumulator( -5.0, 3.14 ) + ~2.0 + > d = accumulator( -5.0, NaN ) + ~2.0 + > d = accumulator() + ~2.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/index.d.ts new file mode 100644 index 000000000000..313963dcd6b4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/index.d.ts @@ -0,0 +1,79 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided input values, the accumulator function returns an updated sample correlation distance. If not provided input values, the accumulator function returns the current sample correlation distance. +* +* ## Notes +* +* - The correlation distance is defined as one minus the Pearson product-moment correlation coefficient and, thus, resides on the interval [0,2]. +* +* @param x - value +* @param y - value +* @returns updated sample correlation distance +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation distance, ignoring `NaN` values. +* +* @param meanx - mean value +* @param meany - mean value +* @returns accumulator function +* +* @example +* var accumulator = incrnanpcorrdist( 2.0, -3.0 ); +*/ +declare function incrnanpcorrdist( meanx: number, meany: number ): accumulator; + +/** +* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation distance, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanpcorrdist(); +* +* var d = accumulator(); +* // returns null +* +* d = accumulator( 2.0, 1.0 ); +* // returns 1.0 +* +* d = accumulator( NaN, 1.0 ); +* // returns 1.0 +* +* d = accumulator( -5.0, 3.14 ); +* // returns ~2.0 +* +* d = accumulator( -5.0, NaN ); +* // returns ~2.0 +* +* d = accumulator(); +* // returns ~2.0 +*/ +declare function incrnanpcorrdist(): accumulator; + + +// EXPORTS // + +export = incrnanpcorrdist; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/test.ts new file mode 100644 index 000000000000..356fc5f642ae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/docs/types/test.ts @@ -0,0 +1,113 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanpcorrdist = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanpcorrdist(); // $ExpectType accumulator + incrnanpcorrdist( 2, 4 ); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided non-numeric arguments... +{ + incrnanpcorrdist( 2, '5' ); // $ExpectError + incrnanpcorrdist( 2, true ); // $ExpectError + incrnanpcorrdist( 2, false ); // $ExpectError + incrnanpcorrdist( 2, null ); // $ExpectError + incrnanpcorrdist( 2, undefined ); // $ExpectError + incrnanpcorrdist( 2, [] ); // $ExpectError + incrnanpcorrdist( 2, {} ); // $ExpectError + incrnanpcorrdist( 2, ( x: number ): number => x ); // $ExpectError + + incrnanpcorrdist( '5', 4 ); // $ExpectError + incrnanpcorrdist( true, 4 ); // $ExpectError + incrnanpcorrdist( false, 4 ); // $ExpectError + incrnanpcorrdist( null, 4 ); // $ExpectError + incrnanpcorrdist( undefined, 4 ); // $ExpectError + incrnanpcorrdist( [], 4 ); // $ExpectError + incrnanpcorrdist( {}, 4 ); // $ExpectError + incrnanpcorrdist( ( x: number ): number => x, 4 ); // $ExpectError +} + +// The compiler throws an error if the function is provided an invalid number of arguments... +{ + incrnanpcorrdist( 1 ); // $ExpectError + incrnanpcorrdist( 2, 2, 3 ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanpcorrdist(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The function returns an accumulator function which returns an accumulated result (known means)... +{ + const acc = incrnanpcorrdist( 2, -3 ); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanpcorrdist(); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments (known means)... +{ + const acc = incrnanpcorrdist( 2, -3 ); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/examples/index.js new file mode 100644 index 000000000000..c04b731ea1c1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/examples/index.js @@ -0,0 +1,49 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanpcorrdist = require( './../lib' ); + +var accumulator; +var d; +var x; +var y; +var i; + +// Initialize an accumulator: +accumulator = incrnanpcorrdist(); + +// For each simulated datum, update the sample Pearson correlation distance... +console.log( '\nx\ty\tCorrelation Distance\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + x = NaN; + } else { + x = randu() * 100.0; + } + if ( randu() < 0.2 ) { + y = NaN; + } else { + y = randu() * 100.0; + } + d = accumulator( x, y ); + console.log( '%d\t%d\t%s', x.toFixed( 4 ), y.toFixed( 4 ), ( d === null ) ? 'null' : d.toFixed( 4 ) ); +} +console.log( '\nFinal 1-r: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/index.js new file mode 100644 index 000000000000..d4dc73377b8a --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a sample Pearson product-moment correlation distance incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanpcorrdist +* +* @example +* var incrnanpcorrdist = require( '@stdlib/stats/incr/nanpcorrdist' ); +* +* var accumulator = incrnanpcorrdist(); +* +* var d = accumulator(); +* // returns null +* +* d = accumulator( 2.0, 1.0 ); +* // returns 1.0 +* +* d = accumulator( NaN, 1.0 ); +* // returns 1.0 +* +* d = accumulator( -5.0, 3.14 ); +* // returns ~2.0 +* +* d = accumulator( -5.0, NaN ); +* // returns ~2.0 +* +* d = accumulator(); +* // returns ~2.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/main.js new file mode 100644 index 000000000000..79f5980631d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/lib/main.js @@ -0,0 +1,101 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive; +var incrpcorrdist = require( '@stdlib/stats/incr/pcorrdist' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a sample Pearson product-moment correlation distance, ignoring `NaN` values. +* +* ## Method +* +* - The sample Pearson product-moment correlation distance is defined as +* +* ```tex +* d = 1 - r = 1 - \frac{\operatorname{cov}_n(x,y)}{\sigma_x \sigma_y} +* ``` +* +* - The implementation thus computes the sample Pearson product-moment correlation coefficient \\(r\\) and subtracts the coefficient from 1. +* +* @param {number} [meanx] - mean value +* @param {number} [meany] - mean value +* @throws {TypeError} first argument must be a number +* @throws {TypeError} second argument must be a number +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanpcorrdist(); +* +* var d = accumulator(); +* // returns null +* +* d = accumulator( 2.0, 1.0 ); +* // returns 1.0 +* +* d = accumulator( NaN, 1.0 ); +* // returns 1.0 +* +* d = accumulator( -5.0, 3.14 ); +* // returns ~2.0 +* +* d = accumulator( -5.0, NaN ); +* // returns ~2.0 +* +* d = accumulator(); +* // returns ~2.0 +* +* @example +* var accumulator = incrnanpcorrdist( 2.0, -3.0 ); +*/ +function incrnanpcorrdist( meanx, meany ) { + var pcorrdist; + if ( arguments.length > 0 ) { + pcorrdist = incrpcorrdist( meanx, meany ); + } else { + pcorrdist = incrpcorrdist(); + } + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated sample correlation distance. If not provided input values, the accumulator function returns the current sample correlation distance. + * + * @private + * @param {number} [x] - new value + * @param {number} [y] - new value + * @returns {(number|null)} sample correlation distance or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || !isNumber( x ) || isnan( y ) || !isNumber( y ) ) { + return pcorrdist(); + } + return pcorrdist( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanpcorrdist; diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/package.json b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/package.json new file mode 100644 index 000000000000..53c37d955ae7 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/package.json @@ -0,0 +1,71 @@ +{ + "name": "@stdlib/stats/incr/nanpcorrdist", + "version": "0.0.0", + "description": "Compute a sample Pearson product-moment correlation distance incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "correlation", + "corr", + "pcorr", + "ppmcc", + "pcc", + "pearson", + "product-moment", + "bivariate", + "distance", + "dist", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/test/test.js new file mode 100644 index 000000000000..1f825b43c4e9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanpcorrdist/test/test.js @@ -0,0 +1,324 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var EPS = require( '@stdlib/constants/float64/eps' ); +var incrnanpcorrdist = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanpcorrdist, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function throws an error if provided a non-numeric value for the first argument', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanpcorrdist( value, 5.0 ); + }; + } +}); + +tape( 'the function throws an error if provided a non-numeric value for the second argument', function test( t ) { + var values; + var i; + + values = [ + '5', + true, + false, + null, + void 0, + [], + {}, + function noop() {} + ]; + for ( i = 0; i < values.length; i++ ) { + t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] ); + } + t.end(); + + function badValue( value ) { + return function badValue() { + incrnanpcorrdist( 3.0, value ); + }; + } +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanpcorrdist(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function (known means)', function test( t ) { + t.equal( typeof incrnanpcorrdist( 3.0, -5.0 ), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a sample correlation distance', function test( t ) { + var expected; + var actual; + var delta; + var tol; + var acc; + var x; + var y; + var i; + + x = [ 2.0, 3.0, NaN, 2.0, 4.0, 3.0, 4.0 ]; + y = [ 1.5, -0.6, 3.14, 3.14, 4.0, -2.0, 10.0 ]; + + // Test against Julia: 1.0-(sum((x[1:n]-mean(x[1:n])).*(y[1:n]-mean(y[1:n]))[:])/(n-1))/(std(x[1:n])*std(y[1:n])) + expected = [ + 1.0, + 2.0, + 2.0, + 1.8992664495010921, + 0.7645279817682773, + 0.9323450750189648, + 0.5055553288774122 + ]; + + acc = incrnanpcorrdist(); + + for ( i = 0; i < x.length; i++ ) { + actual = acc( x[ i ], y[ i ] ); + if ( actual === expected[ i ] ) { + t.strictEqual( actual, expected[ i ], 'returns expected result. x: '+x[i]+'. y: '+y[i]+'.' ); + } else { + delta = abs( expected[ i ] - actual ); + tol = 3.7 * EPS * abs( expected[ i ] ); + t.equal( delta <= tol, true, 'x: '+x[i]+'. y: '+y[i]+'. expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'the accumulator function incrementally computes a sample correlation distance (known means)', function test( t ) { + var expected; + var actual; + var delta; + var tol; + var acc; + var x; + var y; + var i; + + x = [ 2.0, 3.0, NaN, 2.0, 4.0, 3.0, 4.0 ]; + y = [ 1.5, -0.6, 3.12, 3.14, 4.0, -2.0, 10.0 ]; + + // Test against Julia: 1.0-(sum((x[1:n]-3.0).*(y[1:n]-2.6733333333333333)[:])/(n-1))/(stdm(x[1:n],3.0)*stdm(y[1:n],2.6733333333333333)) + expected = [ + 0.0, + 0.662570758692496, + 0.662570758692496, + 0.8575755030133585, + 0.6870228977245596, + 0.8040954375369098, + 0.5055553288774122 + ]; + + acc = incrnanpcorrdist( 3.0, 2.6733333333333333 ); + + for ( i = 0; i < x.length; i++ ) { + actual = acc( x[ i ], y[ i ] ); + if ( actual === expected[ i ] ) { + t.strictEqual( actual, expected[ i ], 'returns expected result. x: '+x[i]+'. y: '+y[i]+'.' ); + } else { + delta = abs( expected[ i ] - actual ); + tol = EPS * abs( expected[ i ] ); + t.equal( delta <= tol, true, 'x: '+x[i]+'. y: '+y[i]+'. expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation distance', function test( t ) { + var acc; + var x; + var y; + var i; + + x = [ 2.0, NaN, 3.0, 1.0 ]; + y = [ 3.14, 2.14, -1.0, 2.4 ]; + + acc = incrnanpcorrdist(); + for ( i = 0; i < x.length; i++ ) { + acc( x[ i ], y[ i ] ); + } + t.equal( acc(), 1.7699852380946451, 'returns expected result' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sample correlation distance (known means)', function test( t ) { + var acc; + var x; + var y; + var i; + + x = [ 2.0, NaN, 3.0, 1.0 ]; + y = [ 3.14, 2.2, -1.0, 2.4 ]; + + acc = incrnanpcorrdist( 2.0, 1.5133333333333334 ); + for ( i = 0; i < x.length; i++ ) { + acc( x[ i ], y[ i ] ); + } + t.equal( acc(), 1.7699852380946453, 'returns expected result' ); + t.end(); +}); + +tape( 'the sample correlation distance is `null` until at least 1 datum has been provided (unknown means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorrdist(); + + v = acc(); + t.equal( v, null, 'returns null' ); + + v = acc( 3.0, -3.14 ); + t.notEqual( v, null, 'does not return null' ); + + t.end(); +}); + +tape( 'the sample correlation distance is `null` until at least 1 datum has been provided (known means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorrdist( 3.0, -5.0 ); + + v = acc(); + t.equal( v, null, 'returns null' ); + + v = acc( 3.0, -3.14 ); + t.notEqual( v, null, 'does not return null' ); + + t.end(); +}); + +tape( 'the sample correlation distance is `1` until at least 2 datums have been provided (unknown means)', function test( t ) { + var acc; + var v; + + acc = incrnanpcorrdist(); + + v = acc( 2.0, 10.0 ); + t.equal( v, 1.0, 'returns 1' ); + + v = acc( 3.0, -3.14 ); + t.notEqual( v, 1.0, 'does not return 1' ); + + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function skips updating its state (unknown means)', function test( t ) { + var data; + var prev; + var acc; + var v; + + data = [ + [ 2.0, 1.0 ], + [ 1.0, 2.0 ], + [ NaN, 1.0 ], + [ 1.0, 2.0 ], + [ 3.0, 4.0 ], + [ 5.0, 6.0 ], + [ 7.0, 0.0 ] + ]; + acc = incrnanpcorrdist(); + + v = acc( data[ 0 ][ 0 ], data[ 0 ][ 1 ] ); + v = acc( data[ 1 ][ 0 ], data[ 1 ][ 1 ] ); + prev = acc(); + + v = acc( data[ 2 ][ 0 ], data[ 2 ][ 1 ] ); + t.equal( v, prev, 'skips update when first parameter is NaN' ); + t.equal( acc(), prev, 'state remains unchanged' ); + + v = acc( data[ 3 ][ 0 ], data[ 3 ][ 1 ] ); + prev = v; + + v = acc( 4.0, NaN ); + t.equal( v, prev, 'skips update when second parameter is NaN' ); + t.equal( acc(), prev, 'state remains unchanged' ); + + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function skips updating its state (known means)', function test( t ) { + var data; + var prev; + var acc; + var v; + + data = [ + [ 2.0, 1.0 ], + [ 1.0, 2.0 ], + [ NaN, 1.0 ], + [ 1.0, 2.0 ], + [ 3.0, 4.0 ], + [ 5.0, 6.0 ], + [ 7.0, 0.0 ] + ]; + acc = incrnanpcorrdist( 3.14, 1.0 ); + + v = acc( data[ 0 ][ 0 ], data[ 0 ][ 1 ] ); + v = acc( data[ 1 ][ 0 ], data[ 1 ][ 1 ] ); + prev = acc(); + + v = acc( data[ 2 ][ 0 ], data[ 2 ][ 1 ] ); + t.equal( v, prev, 'skips update when first parameter is NaN' ); + t.equal( acc(), prev, 'state remains unchanged' ); + + v = acc( data[ 3 ][ 0 ], data[ 3 ][ 1 ] ); + prev = v; + + v = acc( 4.0, NaN ); + t.equal( v, prev, 'skips update when second parameter is NaN' ); + t.equal( acc(), prev, 'state remains unchanged' ); + + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/README.md b/lib/node_modules/@stdlib/stats/incr/nanprod/README.md new file mode 100644 index 000000000000..027d5d882b75 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/README.md @@ -0,0 +1,198 @@ + + +# incrnanprod + +> Compute a product incrementally, ignoring `NaN` values. + +
+ +The product is defined as + + + +```math +p = \prod_{i=0}^{n-1} x_i +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanprod = require( '@stdlib/stats/incr/nanprod' ); +``` + +#### incrnanprod() + +Returns an accumulator `function` which incrementally computes a product, ignoring `NaN` values. + +```javascript +var accumulator = incrnanprod(); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated product. If not provided an input value `x`, the accumulator function returns the current product. + +```javascript +var accumulator = incrnanprod(); + +var prod = accumulator( 2.0 ); +// returns 2.0 + +prod = accumulator( NaN ); +// returns 2.0 + +prod = accumulator( 1.0 ); +// returns 2.0 + +prod = accumulator( 3.0 ); +// returns 6.0 + +prod = accumulator(); +// returns 6.0 +``` + +Under certain conditions, overflow may be transient. + +```javascript +// Large values: +var x = 5.0e+300; +var y = 1.0e+300; + +// Tiny value: +var z = 2.0e-302; + +// Initialize an accumulator: +var accumulator = incrnanprod(); + +var prod = accumulator( x ); +// returns 5.0e+300 + +// Transient overflow: +prod = accumulator( y ); +// returns Infinity + +// Recover a finite result: +prod = accumulator( z ); +// returns 1.0e+299 +``` + +Similarly, under certain conditions, underflow may be transient. + +```javascript +// Tiny values: +var x = 4.0e-302; +var y = 9.0e-303; + +// Large value: +var z = 2.0e+300; + +// Initialize an accumulator: +var accumulator = incrnanprod(); + +var prod = accumulator( x ); +// returns 4.0e-302 + +// Transient underflow: +prod = accumulator( y ); +// returns 0.0 + +// Recover a non-zero result: +prod = accumulator( z ); +// returns 7.2e-304 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- For long running accumulations or accumulations of either large or small numbers, care should be taken to prevent overflow and underflow. Note, however, that overflow/underflow may be transient, as the accumulator does not use a double-precision floating-point number to store an accumulated product. Instead, the accumulator splits an accumulated product into a normalized **fraction** and **exponent** and updates each component separately. Doing so guards against a loss in precision. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanprod = require( '@stdlib/stats/incr/nanprod' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanprod(); + +// For each simulated value, update the product... +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanprod/benchmark/benchmark.js new file mode 100644 index 000000000000..9e9c5a74613e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnanprod = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanprod(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanprod(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()*10.0 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanprod/docs/repl.txt new file mode 100644 index 000000000000..4094ae4e0b7b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/docs/repl.txt @@ -0,0 +1,38 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes a + product, ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated product. If + not provided a value, the accumulator function returns the current product. + + For long running accumulations or accumulations of large numbers, care + should be taken to prevent overflow. Note, however, that overflow/underflow + may be transient, as the accumulator does not use a double-precision + floating-point number to store an accumulated product. Instead, the + accumulator splits an accumulated product into a normalized fraction and + exponent and updates each component separately. Doing so guards against a + loss in precision. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var v = accumulator() + null + > v = accumulator( 2.0 ) + 2.0 + > v = accumulator( NaN ) + 2.0 + > v = accumulator( -5.0 ) + -10.0 + > v = accumulator() + -10.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanprod/docs/types/index.d.ts new file mode 100644 index 000000000000..a708b9f7dda3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/docs/types/index.d.ts @@ -0,0 +1,66 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated product; otherwise, returns the current product. +* +* ## Notes +* +* - For long running accumulations or accumulations of large numbers, care should be taken to prevent overflow. Note, however, that overflow/underflow may be transient, as the accumulator does not use a double-precision floating-point number to store an accumulated product. Instead, the accumulator splits an accumulated product into a normalized fraction and exponent and updates each component separately. Doing so guards against a loss in precision. +* +* @param x - value +* @returns product +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a product, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanprod(); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 2.0 +* +* v = accumulator( NaN ); +* // returns 2.0 +* +* v = accumulator( 3.0 ); +* // returns 6.0 +* +* v = accumulator( 4.0 ); +* // returns 24.0 +* +* v = accumulator(); +* // returns 24.0 +*/ +declare function incrnanprod(): accumulator; + + +// EXPORTS // + +export = incrnanprod; diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanprod/docs/types/test.ts new file mode 100644 index 000000000000..ea52ed039bf5 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanprod = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanprod(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanprod( '5' ); // $ExpectError + incrnanprod( 5 ); // $ExpectError + incrnanprod( true ); // $ExpectError + incrnanprod( false ); // $ExpectError + incrnanprod( null ); // $ExpectError + incrnanprod( undefined ); // $ExpectError + incrnanprod( [] ); // $ExpectError + incrnanprod( {} ); // $ExpectError + incrnanprod( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanprod(); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanprod(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanprod/examples/index.js new file mode 100644 index 000000000000..fbc95c874d0b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/examples/index.js @@ -0,0 +1,40 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanprod = require( './../lib' ); + +var accumulator; +var prod; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanprod(); + +// For each simulated value, update the product... +console.log( '\nValue\tProduct\n' ); +for ( i = 0; i < 100; i++ ) { + v = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( 0.0, 100.0 ); + prod = accumulator( v ); + console.log( '%s\t%s', ( v === v ) ? v.toFixed( 4 ) : 'NaN', ( prod === null ) ? 'null' : prod.toFixed( 4 ) ); +} +console.log( '\nFinal product: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanprod/lib/index.js new file mode 100644 index 000000000000..c405aeba148b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a product incrementally, while ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanprod +* +* @example +* var incrnanprod = require( '@stdlib/stats/incr/nanprod' ); +* +* var accumulator = incrnanprod(); +* +* var prod = accumulator(); +* // returns null +* +* prod = accumulator( 2.0 ); +* // returns 2.0 +* +* prod = accumulator( NaN ); +* // returns 2.0 +* +* prod = accumulator( -5.0 ); +* // returns -10.0 +* +* prod = accumulator(); +* // returns -10.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanprod/lib/main.js new file mode 100644 index 000000000000..7cf427dad326 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/lib/main.js @@ -0,0 +1,74 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrprod = require( '@stdlib/stats/incr/prod' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a product, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanprod(); +* +* var prod = accumulator(); +* // returns null +* +* prod = accumulator( 2.0 ); +* // returns 2.0 +* +* prod = accumulator( NaN ); +* // returns 2.0 +* +* prod = accumulator( -5.0 ); +* // returns -10.0 +* +* prod = accumulator(); +* // returns -10.0 +*/ +function incrnanprod() { + var prod = incrprod(); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated product. If not provided a value, the accumulator function returns the current product. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} product or null + */ + function accumulator( x ) { + if ( arguments.length === 0 || isnan( x ) ) { + return prod(); + } + return prod( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanprod; diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/package.json b/lib/node_modules/@stdlib/stats/incr/nanprod/package.json new file mode 100644 index 000000000000..6cb9ddb39f86 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/package.json @@ -0,0 +1,65 @@ +{ + "name": "@stdlib/stats/incr/nanprod", + "version": "0.0.0", + "description": "Compute a product incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib.git", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "multiplication", + "mult", + "product", + "prod", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanprod/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanprod/test/test.js new file mode 100644 index 000000000000..a275b34031cf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanprod/test/test.js @@ -0,0 +1,326 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var PINF = require( '@stdlib/constants/float64/pinf' ); +var NINF = require( '@stdlib/constants/float64/ninf' ); +var EPSILON = require( '@stdlib/constants/float64/eps' ); +var normal = require( '@stdlib/random/base/normal' ); +var ldexp = require( '@stdlib/math/base/special/ldexp' ); +var abs = require( '@stdlib/math/base/special/abs' ); +var isnan = require( '@stdlib/assert/is-nan' ); +var isEven = require( '@stdlib/math/base/assert/is-even' ); +var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); +var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' ); +var incrnanprod = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanprod, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanprod(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the initial accumulator value is `null`', function test( t ) { + var acc = incrnanprod(); + t.strictEqual( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a product', function test( t ) { + var expected; + var actual; + var data; + var prod; + var acc; + var N; + var d; + var i; + + data = [ 2.0, NaN, 3.0, 2.0, NaN, 4.0, 3.0, 4.0 ]; + N = data.length; + + expected = []; + actual = []; + + acc = incrnanprod(); + + prod = 1.0; + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + if ( !isnan( d ) ) { + prod *= d; + } + expected[ i ] = prod; + actual[ i ] = acc( d ); + } + t.deepEqual( actual, expected, 'returns expected value' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current product', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 3.0, 1.0 ]; + + acc = incrnanprod(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.strictEqual( acc(), 6.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a product (special series)', function test( t ) { + var acc; + var x; + var i; + + acc = incrnanprod(); + x = 2; + + // A series of reciprocals having an even number of terms is equal to unity... + for ( i = 0; i < 150; i++ ) { + if ( isEven( i ) ) { + acc( x ); + } else { + acc( 1.0/x ); + } + if ( i % 10 === 0 ) { + acc( NaN ); + } + } + t.strictEqual( acc(), 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function can return a result which overflows', function test( t ) { + var acc = incrnanprod(); + + acc( 5.0e300 ); + acc( NaN ); + acc( 1.0e300 ); + + t.strictEqual( acc(), PINF, 'returns infinity' ); + t.end(); +}); + +tape( 'overflow may be transient', function test( t ) { + var expected; + var delta; + var tol; + var acc; + var x; + var y; + var z; + + expected = ldexp( 0.01, 1000 ); + + acc = incrnanprod(); + + x = ldexp( 0.5, 1000 ); // ~5.4e300 + y = ldexp( 0.1, 1000 ); // ~1.1e300 + z = ldexp( 0.2, -1000 ); // ~1.87e-302 + + acc( x ); + acc( NaN ); + acc( y ); + acc( z ); + + delta = abs( expected - acc() ); + tol = EPSILON * abs( expected ); + + t.strictEqual( delta <= tol, true, 'within tolerance. Expected: '+expected+'. Actual: '+acc()+'. Delta: '+delta+'. Tol: '+tol+'.' ); + t.end(); +}); + +tape( 'the accumulator function can return a result which underflows', function test( t ) { + var acc = incrnanprod(); + + acc( 4.0e-302 ); + acc( NaN ); + acc( 9.0e-303 ); + + t.strictEqual( acc(), 0.0, 'returns 0' ); + t.end(); +}); + +tape( 'underflow may be transient', function test( t ) { + var expected; + var delta; + var tol; + var acc; + var x; + var y; + var z; + + expected = ldexp( 0.01, -1000 ); + + acc = incrnanprod(); + + x = ldexp( 0.5, -1000 ); // ~4.67e-302 + y = ldexp( 0.1, -1000 ); // ~9.33e-303 + z = ldexp( 0.2, 1000 ); // ~2.14e300 + + acc( x ); + acc( NaN ); + acc( y ); + + t.strictEqual( acc(), 0.0, 'returns 0 due to underflow' ); + + acc( z ); + + delta = abs( acc() - expected ); + tol = EPSILON * abs( expected ); + + t.strictEqual( delta <= tol, true, 'within tolerance. Expected: '+expected+'. Actual: '+acc()+'. Delta: '+delta+'. Tol: '+tol+'.' ); + t.end(); +}); + +tape( 'if provided `+infinity`, the accumulator function always returns `NaN` if also provided a `0`', function test( t ) { + var acc; + var p; + var i; + + acc = incrnanprod(); + acc( 5.0 ); + + t.strictEqual( acc(), 5.0, 'returns expected value' ); + + acc( PINF ); + t.strictEqual( acc(), PINF, 'returns +infinity' ); + + acc( NaN ); + t.strictEqual( acc(), PINF, 'ignores NaN and retains +infinity' ); + + acc( 0.0 ); + t.strictEqual( isnan( acc() ), true, 'returns NaN' ); + + for ( i = 0; i < 1000; i++ ) { + p = acc( i + 1 ); + t.strictEqual( isnan( p ), true, 'returns NaN' ); + } + t.end(); +}); + +tape( 'if provided `-infinity`, the accumulator function always returns `NaN` if also provided a `0`', function test( t ) { + var acc; + var p; + var i; + + acc = incrnanprod(); + acc( 5.0 ); + + t.strictEqual( acc(), 5.0, 'returns expected value' ); + + acc( NINF ); + t.strictEqual( acc(), NINF, 'returns -infinity' ); + + acc( NaN ); + t.strictEqual( acc(), NINF, 'ignores NaN and retains -infinity' ); + + acc( 0.0 ); + t.strictEqual( isnan( acc() ), true, 'returns NaN' ); + + for ( i = 0; i < 1000; i++ ) { + p = acc( i+1 ); + t.strictEqual( isnan( p ), true, 'returns NaN' ); + } + t.end(); +}); + +tape( 'if provided `0`, the accumulator function always returns `0` (no +-infinity)', function test( t ) { + var acc; + var p; + var i; + + acc = incrnanprod(); + acc( 5.0 ); + + t.strictEqual( acc(), 5.0, 'returns expected value' ); + + acc( NaN ); + t.strictEqual( acc(), 5.0, 'ignores NaN and retains product' ); + + acc( 0.0 ); + t.strictEqual( acc(), 0.0, 'returns 0.0' ); + + for ( i = 0; i < 1000; i++ ) { + p = acc( i+1 ); + t.strictEqual( p, 0.0, 'returns 0.0' ); + } + t.end(); +}); + +tape( 'the accumulator function returns a signed zero', function test( t ) { + var acc; + var p; + var i; + + acc = incrnanprod(); + acc( -0.0 ); + for ( i = 0; i < 100; i++ ) { + acc( NaN ); + p = acc( -0.0 ); + if ( isEven( i ) ) { + t.strictEqual( isPositiveZero( p ), true, 'returns +0' ); + } else { + t.strictEqual( isNegativeZero( p ), true, 'returns -0' ); + } + } + t.end(); +}); + +tape( 'if provided values of normal magnitude (i.e., far away from the extremes), the accumulator function returns results matching naive multiplication', function test( t ) { + var randn; + var prod; + var acc; + var r; + var i; + + acc = incrnanprod(); + + randn = normal.factory( 50.0, 10.0, { + 'seed': 1234 + }); + + prod = 1.0; + for ( i = 0; i < 1000; i++ ) { + r = randn(); + if ( isnan( r ) ) { + continue; + } + acc( r ); + prod *= r; + } + t.strictEqual( acc(), prod, 'equals native multiplication' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/README.md b/lib/node_modules/@stdlib/stats/incr/nanrange/README.md new file mode 100644 index 000000000000..f7eebb3bf21f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/README.md @@ -0,0 +1,136 @@ + + +# incrnanrange + +> Compute a [range][range] incrementally, ignoring `NaN` values. + +
+ +The [**range**][range] is defined as the difference between the maximum and minimum values. This implementation ignores `NaN` values. + +
+ + + +
+ +## Usage + +```javascript +var incrnanrange = require( '@stdlib/stats/incr/nanrange' ); +``` + +#### incrnanrange() + +Returns an accumulator `function` which incrementally computes a [range][range], ignoring `NaN` values. + +```javascript +var accumulator = incrnanrange(); +``` + +#### accumulator( \[x] ) + +If provided an input value `x`, the accumulator function returns an updated [range][range], ignoring `NaN` values. If not provided an input value `x`, the accumulator function returns the current [range][range]. + +```javascript +var accumulator = incrnanrange(); + +var range = accumulator( -2.0 ); +// returns 0.0 + +range = accumulator( NaN ); +// returns 0.0 (ignores NaN) + +range = accumulator( 1.0 ); +// returns 3.0 + +range = accumulator( 3.0 ); +// returns 5.0 + +range = accumulator(); +// returns 5.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- Unlike `incrrange`, `incrnanrange` ignores `NaN` values, ensuring they do not affect the computed range. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnanrange = require( '@stdlib/stats/incr/nanrange' ); + +var accumulator; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanrange(); + +// For each simulated datum, update the range... +for ( i = 0; i < 100; i++ ) { + v = ( randu() > 0.1 ) ? ( randu() * 100.0 ) : NaN; + accumulator( v ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[range]: https://en.wikipedia.org/wiki/Range_%28statistics%29 + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanrange/benchmark/benchmark.js new file mode 100644 index 000000000000..91da704f24c2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/benchmark/benchmark.js @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var pkg = require( './../package.json' ).name; +var incrnanrange = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanrange(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( pkg+'::accumulator', function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanrange(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()*10.0 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanrange/docs/repl.txt new file mode 100644 index 000000000000..c399e95ae1cf --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/docs/repl.txt @@ -0,0 +1,30 @@ +{{alias}}() + Returns an accumulator function which incrementally computes a range, + ignoring `NaN` values. + + If provided a value, the accumulator function returns an updated range. If + not provided a value, the accumulator function returns the current range. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var v = accumulator() + null + > v = accumulator( -2.0 ) + 0.0 + > v = accumulator( NaN ) + 0.0 + > v = accumulator( 3.0 ) + 5.0 + > v = accumulator( 1.0 ) + 5.0 + > v = accumulator() + 5.0 + + See Also + -------- diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanrange/docs/types/index.d.ts new file mode 100644 index 000000000000..f2bfddc1cb7c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/docs/types/index.d.ts @@ -0,0 +1,62 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided a value, returns an updated range; otherwise, returns the current range. +* +* @param x - value +* @returns range +*/ +type accumulator = ( x?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a range, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanrange(); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0 ); +* // returns 0.0 +* +* v = accumulator( -1.0 ); +* // returns 3.0 +* +* v = accumulator( NaN ); +* // returns 3.0 +* +* v = accumulator( -3.0 ); +* // returns 5.0 +* +* v = accumulator(); +* // returns 5.0 +*/ +declare function incrnanrange(): accumulator; + + +// EXPORTS // + +export = incrnanrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanrange/docs/types/test.ts new file mode 100644 index 000000000000..89dbb8a8e8d4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/docs/types/test.ts @@ -0,0 +1,61 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanrange = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanrange(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanrange( '5' ); // $ExpectError + incrnanrange( 5 ); // $ExpectError + incrnanrange( true ); // $ExpectError + incrnanrange( false ); // $ExpectError + incrnanrange( null ); // $ExpectError + incrnanrange( undefined ); // $ExpectError + incrnanrange( [] ); // $ExpectError + incrnanrange( {} ); // $ExpectError + incrnanrange( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanrange(); + + acc(); // $ExpectType number | null + acc( 3.14 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanrange(); + + acc( '5' ); // $ExpectError + acc( true ); // $ExpectError + acc( false ); // $ExpectError + acc( null ); // $ExpectError + acc( [] ); // $ExpectError + acc( {} ); // $ExpectError + acc( ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanrange/examples/index.js new file mode 100644 index 000000000000..8f50e060944e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var randu = require( '@stdlib/random/base/randu' ); +var incrnanrange = require( './../lib' ); + +var accumulator; +var range; +var v; +var i; + +// Initialize an accumulator: +accumulator = incrnanrange(); + +// For each simulated datum, update the range... +console.log( '\nValue\tRange\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v = NaN; + } else { + v = randu() * 100.0; + } + range = accumulator( v ); + console.log( '%s\t%s', ( v === v ) ? v.toFixed( 4 ) : 'NaN', ( range === null ) ? 'null' : range.toFixed( 4 ) ); +} +console.log( '\nFinal range: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanrange/lib/index.js new file mode 100644 index 000000000000..8f38d8a67dfe --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a range incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanrange +* +* @example +* var incrnanrange = require( '@stdlib/stats/incr/nanrange' ); +* +* var accumulator = incrnanrange(); +* +* var range = accumulator(); +* // returns null +* +* range = accumulator( 3.14 ); +* // returns 0.0 +* +* range = accumulator( NaN ); +* // returns 0.0 +* +* range = accumulator( -5.0 ); +* // returns 8.14 +* +* range = accumulator( 10.1 ); +* // returns 15.1 +* +* range = accumulator(); +* // returns 15.1 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanrange/lib/main.js new file mode 100644 index 000000000000..8cb9ef8b635d --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/lib/main.js @@ -0,0 +1,80 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrrange = require( '@stdlib/stats/incr/range' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a range, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanrange(); +* +* var range = accumulator(); +* // returns null +* +* range = accumulator( 3.14 ); +* // returns 0.0 +* +* range = accumulator( NaN ); +* // returns 0.0 +* +* range = accumulator( -5.0 ); +* // returns 8.14 +* +* range = accumulator( 10.1 ); +* // returns 15.1 +* +* range = accumulator(); +* // returns 15.1 +*/ +function incrnanrange() { + var acc = incrrange(); + return accumulator; + + /** + * If provided a value, the accumulator function returns an updated range. If not provided a value, the accumulator function returns the current range. + * + * @private + * @param {number} [x] - new value + * @returns {(number|null)} range or null + */ + function accumulator( x ) { + if ( arguments.length === 0 ) { + return acc(); + } + if ( isnan( x ) ) { + return acc(); + } + return acc( x ); + } +} + + +// EXPORTS // + +module.exports = incrnanrange; diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/package.json b/lib/node_modules/@stdlib/stats/incr/nanrange/package.json new file mode 100644 index 000000000000..2d294343cff9 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/package.json @@ -0,0 +1,70 @@ +{ + "name": "@stdlib/stats/incr/nanrange", + "version": "0.0.0", + "description": "Compute a range incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "maximum", + "max", + "minimum", + "min", + "range", + "dispersion", + "variance", + "domain", + "extent", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanrange/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanrange/test/test.js new file mode 100644 index 000000000000..b2f01b0908a8 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrange/test/test.js @@ -0,0 +1,125 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanrange = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanrange, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnanrange(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'if not provided any values, the initial returned range is `null`', function test( t ) { + var acc = incrnanrange(); + t.equal( acc(), null, 'returns null' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a range while ignoring NaN values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var max; + var min; + var N; + var d; + var i; + + data = [ 2.0, NaN, 3.0, NaN, 4.0, 43.0, NaN, 4.0 ]; + N = data.length; + + expected = []; + actual = []; + + acc = incrnanrange(); + + max = null; + min = null; + for ( i = 0; i < N; i++ ) { + d = data[ i ]; + if ( !isnan( d ) ) { + if ( max === null || d > max ) { + max = d; + } + if ( min === null || d < min ) { + min = d; + } + } + expected.push( ( max !== null && min !== null ) ? ( max - min ) : null ); + actual.push( acc( d ) ); + } + t.deepEqual( actual, expected, 'returns expected incremental results' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current range while ignoring the NaN value', function test( t ) { + var data; + var acc; + var i; + + data = [ NaN, -2.0, NaN, 3.0, 1.0 ]; + acc = incrnanrange(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), 5.0, 'returns the current accumulated range' ); + t.end(); +}); + +tape( 'if provided a `NaN`, the accumulator function ignores the value and does not return `NaN`', function test( t ) { + var data; + var acc; + var i; + + data = [ 2.0, NaN, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]; + acc = incrnanrange(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( isnan( acc() ), false, 'returns expected value' ); + t.end(); +}); + +tape( 'if all provided values are `NaN`, the accumulator function returns `null`', function test( t ) { + var data; + var acc; + var i; + + data = [ NaN, NaN, NaN ]; + acc = incrnanrange(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ] ); + } + t.equal( acc(), null, 'returns null' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/README.md b/lib/node_modules/@stdlib/stats/incr/nanrss/README.md new file mode 100644 index 000000000000..537cfff39d8e --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/README.md @@ -0,0 +1,151 @@ + + +# incrnanrss + +> Compute the [residual sum of squares][residual-sum-of-squares] (RSS) incrementally, ignoring `NaN` values. + +
+ +The [**residual sum of squares**][residual-sum-of-squares] (also referred to as the **sum of squared residuals** (SSR) and the **sum of squared errors** (SSE)) is defined as + + + +```math +\mathop{\mathrm{RSS}} = \sum_{i=0}^{n-1} (y_i - x_i)^2 +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnanrss = require( '@stdlib/stats/incr/nanrss' ); +``` + +#### incrnanrss() + +Returns an accumulator `function` which incrementally computes the [residual sum of squares][residual-sum-of-squares], ignoring `NaN` values. + +```javascript +var accumulator = incrnanrss(); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated [residual sum of squares][residual-sum-of-squares]. If not provided input values `x` and `y`, the accumulator function returns the current [residual sum of squares][residual-sum-of-squares]. + +```javascript +var accumulator = incrnanrss(); + +var r = accumulator( 2.0, 3.0 ); +// returns 1.0 + +r = accumulator( -1.0, -4.0 ); +// returns 10.0 + +r = accumulator( -3.0, 5.0 ); +// returns 74.0 + +r = accumulator( NaN, 3.0 ); +// returns 74.0 + +r = accumulator(); +// returns 74.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. + +
+ + + +
+ +## Examples + + + +```javascript +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var incrnanrss = require( '@stdlib/stats/incr/nanrss' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanrss(); + +// For each simulated datum, update the residual sum of squares... +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +
+ + + + + +
+ +[residual-sum-of-squares]: https://en.wikipedia.org/wiki/Residual_sum_of_squares + + + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanrss/benchmark/benchmark.js new file mode 100644 index 000000000000..e0b5fdfa28a4 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnanrss = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnanrss(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnanrss(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu()-0.5, randu()-0.5 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/docs/img/equation_residual_sum_of_squares.svg b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/img/equation_residual_sum_of_squares.svg new file mode 100644 index 000000000000..5a7aac9d4628 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/img/equation_residual_sum_of_squares.svg @@ -0,0 +1,52 @@ + +upper R upper S upper S equals sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts left-parenthesis y Subscript i Baseline minus x Subscript i Baseline right-parenthesis squared + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/repl.txt new file mode 100644 index 000000000000..a12b06711f7b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes the residual + sum of squares (RSS), ignoring `NaN` values. + + If provided input values, the accumulator function returns an updated + residual sum of squares. If not provided input values, the accumulator + function returns the current residual sum of squares. + + If provided `NaN`, the value is ignored, and the accumulator function + returns the current residual sum of squares. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var r = accumulator() + null + > r = accumulator( 2.0, 3.0 ) + 1.0 + > r = accumulator( NaN, 3.0 ) + 1.0 + > r = accumulator( -5.0, 2.0 ) + 50.0 + > r = accumulator() + 50.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/types/index.d.ts new file mode 100644 index 000000000000..5b10c831c71f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/types/index.d.ts @@ -0,0 +1,67 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated residual sum of squares; otherwise, returns the current residual sum of squares. +* +* ## Notes +* +* - If provided `NaN`, the value is ignored, and the accumulator function returns the current residual sum of squares. +* +* @param x - value +* @param y - value +* @returns residual sum of squares +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes the residual sum of squares, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnanrss(); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* r = accumulator( -5.0, 2.0 ); +* // returns 50.0 +* +* r = accumulator( NaN, 3.0 ); +* // returns 50.0 +* +* r = accumulator( 5.0, NaN ); +* // returns 50.0 +* +* r = accumulator(); +* // returns 50.0 +*/ +declare function incrnanrss(): accumulator; + + +// EXPORTS // + +export = incrnanrss; diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/types/test.ts new file mode 100644 index 000000000000..fd0a136de7d2 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/docs/types/test.ts @@ -0,0 +1,73 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnanrss = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnanrss(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnanrss( '5' ); // $ExpectError + incrnanrss( 5 ); // $ExpectError + incrnanrss( true ); // $ExpectError + incrnanrss( false ); // $ExpectError + incrnanrss( null ); // $ExpectError + incrnanrss( undefined ); // $ExpectError + incrnanrss( [] ); // $ExpectError + incrnanrss( {} ); // $ExpectError + incrnanrss( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnanrss(); + + acc( 2.0, 3.0 ); // $ExpectType number | null + acc( NaN, 3.0 ); // ok + acc( 5.0, NaN ); // ok + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnanrss(); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanrss/examples/index.js new file mode 100644 index 000000000000..149269c21489 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/examples/index.js @@ -0,0 +1,43 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var uniform = require( '@stdlib/random/base/uniform' ); +var bernoulli = require( '@stdlib/random/base/bernoulli' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnanrss = require( './../lib' ); + +var accumulator; +var rss; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnanrss(); + +// For each simulated datum, update the residual sum of squares... +console.log( '\nValue\tValue\tRSS\n' ); +for ( i = 0; i < 100; i++ ) { + v1 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + v2 = ( bernoulli( 0.8 ) < 1 ) ? NaN : uniform( -50.0, 50.0 ); + rss = accumulator( v1, v2 ); + console.log( '%s\t%s\t%s', ( isnan( v1 ) ) ? 'NaN' : v1.toFixed( 3 ), ( isnan( v2 ) ) ? 'NaN' : v2.toFixed( 3 ), ( rss === null ) ? 'null' : rss.toFixed( 3 ) ); +} +console.log( '\nFinal RSS: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanrss/lib/index.js new file mode 100644 index 000000000000..c1498ee153d1 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/lib/index.js @@ -0,0 +1,54 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute the residual sum of squares incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nanrss +* +* @example +* var incrnanrss = require( '@stdlib/stats/incr/nanrss' ); +* +* var accumulator = incrnanrss(); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* r = accumulator( -5.0, 2.0 ); +* // returns 50.0 +* +* r = accumulator( NaN, 3.0 ); +* // returns 50.0 +* +* r = accumulator(); +* // returns 50.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanrss/lib/main.js new file mode 100644 index 000000000000..8f2cd0fbb2c6 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/lib/main.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrrss = require( '@stdlib/stats/incr/rss' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes the residual sum of squares, ignoring `NaN` values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnanrss(); +* +* var r = accumulator(); +* // returns null +* +* r = accumulator( 2.0, 3.0 ); +* // returns 1.0 +* +* r = accumulator( -5.0, 2.0 ); +* // returns 50.0 +* +* r = accumulator( NaN, 3.0 ); +* // returns 50.0 +* +* r = accumulator( 5.0, NaN ); +* // returns 50.0 +* +* r = accumulator(); +* // returns 50.0 +*/ +function incrnanrss() { + var rss = incrrss(); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated residual sum of squares. If not provided input values, the accumulator function returns the current residual sum of squares. + * + * @private + * @param {number} [x] - input value + * @param {number} [y] - input value + * @returns {(number|null)} residual sum of squares or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return rss(); + } + return rss( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnanrss; diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/package.json b/lib/node_modules/@stdlib/stats/incr/nanrss/package.json new file mode 100644 index 000000000000..d05305abef5b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/package.json @@ -0,0 +1,84 @@ +{ + "name": "@stdlib/stats/incr/nanrss", + "version": "0.0.0", + "description": "Compute the residual sum of squares (RSS) incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "error", + "err", + "rss", + "ssr", + "sse", + "residuals", + "deviation", + "difference", + "diff", + "delta", + "incremental", + "accumulator", + "time series", + "timeseries", + "forecasting", + "forecast", + "model", + "selection", + "evaluation", + "prediction", + "manhattan", + "cityblock", + "city-block", + "distance", + "dist" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nanrss/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanrss/test/test.js new file mode 100644 index 000000000000..e8374337d657 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nanrss/test/test.js @@ -0,0 +1,134 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var ulpdiff = require( '@stdlib/number/float64/base/ulp-difference' ); +var incrnanrss = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnanrss, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.strictEqual( typeof incrnanrss(), 'function', 'returns expected value' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnanrss(); + t.strictEqual( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes the residual sum of squares', function test( t ) { + var expected; + var actual; + var diff; + var data; + var acc; + var sum; + var i; + var N; + var r; + var x; + var y; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, -1.0 ], + [ 2.0, 5.0 ], + [ 4.0, -4.0 ], + [ 3.0, 0.0 ], + [ -4.0, 5.0 ] + ]; + N = data.length; + + acc = incrnanrss(); + + sum = 0; + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + r = y - x; + sum += r * r; + expected = sum; + actual = acc( x, y ); + if ( actual === expected ) { + t.strictEqual( actual, expected, 'returns expected value' ); + } else { + diff = ulpdiff( actual, expected ); + t.strictEqual( diff <= 1, true, 'within 1 ulp. Actual: '+actual+'. Expected: '+expected+'. ULP diff: '+diff ); + } + } + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current residual sum of squares', function test( t ) { + var expected; + var actual; + var diff; + var data; + var acc; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, -5.0 ], + [ 1.0, 10.0 ] + ]; + acc = incrnanrss(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + actual = acc(); + expected = 1.0 + 64.0 + 81.0; + diff = ulpdiff( actual, expected ); + t.strictEqual( diff <= 1, true, 'within 1 ulp. Actual: '+actual+'. Expected: '+expected+'. ULP diff: '+diff ); + t.end(); +}); + +tape( 'the accumulator function ignores `NaN` values', function test( t ) { + var acc = incrnanrss(); + + acc( 2.0, 3.0 ); + acc( NaN, 3.0 ); + acc( 3.0, NaN ); + + t.strictEqual( acc(), 1.0, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function ignores `NaN` value pairs', function test( t ) { + var acc = incrnanrss(); + + acc( 1.0, 2.0 ); // 1 + acc( NaN, NaN ); // ignored + acc( 2.0, 4.0 ); // +4 + + t.strictEqual( acc(), 5.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/README.md b/lib/node_modules/@stdlib/stats/incr/nansumprod/README.md new file mode 100644 index 000000000000..2d5c51275515 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/README.md @@ -0,0 +1,178 @@ + + +# incrnansumprod + +> Compute a sum of products incrementally, ignoring `NaN` values. + +
+ +The sum of products is defined as + + + +```math +s = \sum_{i=0}^{n-1} x_i y_i +``` + + + + + +
+ + + +
+ +## Usage + +```javascript +var incrnansumprod = require( '@stdlib/stats/incr/nansumprod' ); +``` + +#### incrnansumprod() + +Returns an accumulator `function` which incrementally computes a sum of products, ignoring `NaN` values. + +```javascript +var accumulator = incrnansumprod(); +``` + +#### accumulator( \[x, y] ) + +If provided input values `x` and `y`, the accumulator function returns an updated sum. If not provided input value `x` and `y`, the accumulator function returns the current sum. + +```javascript +var accumulator = incrnansumprod(); + +var sum = accumulator( 2.0, 3.0 ); +// returns 6.0 + +sum = accumulator( 1.0, -1.0 ); +// returns 5.0 + +sum = accumulator( NaN, NaN ); +// returns 5.0 + +sum = accumulator( 3, NaN ); +// returns 5.0 + +sum = accumulator( 3.0, 4.0 ); +// returns 17.0 + +sum = accumulator(); +// returns 17.0 +``` + +
+ + + +
+ +## Notes + +- Input values are **not** type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function. +- For long running accumulations or accumulations of large numbers, care should be taken to prevent overflow. + +
+ + + +
+ +## Examples + + + +```javascript +var randu = require( '@stdlib/random/base/randu' ); +var incrnansumprod = require( '@stdlib/stats/incr/nansumprod' ); + +var accumulator; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnansumprod(); + +// For each simulated datum, update the sum-product... +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v1 = NaN; + v2 = NaN; + } else if ( randu() < 0.3 ) { + v1 = NaN; + v2 = randu() * 100.0; + } else { + v1 = randu() * 100.0; + v2 = randu() * 100.0; + } + accumulator( v1, v2 ); +} +console.log( accumulator() ); +``` + +
+ + + + + +
+ +* * * + +## See Also + +- [`@stdlib/stats/incr/sumprod`][@stdlib/stats/incr/sumprod]: Compute a sum of products incrementally. +- [`@stdlib/stats/incr/nansum`][@stdlib/stats/incr/nansum]: Compute a sum incrementally, ignoring `NaN` values. +- [`@stdlib/stats/incr/prod`][@stdlib/stats/incr/prod]: compute a product incrementally. +- [`@stdlib/stats/incr/sum`][@stdlib/stats/incr/sum]: compute a sum incrementally. + + +
+ + + + + +
+ + + +[@stdlib/stats/incr/sumprod]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/sumprod + +[@stdlib/stats/incr/prod]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/prod + +[@stdlib/stats/incr/sum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/sum + +[@stdlib/stats/incr/nansum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr/nansum + + + +
+ + diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nansumprod/benchmark/benchmark.js new file mode 100644 index 000000000000..29edbf27b6bc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/benchmark/benchmark.js @@ -0,0 +1,70 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var bench = require( '@stdlib/bench' ); +var randu = require( '@stdlib/random/base/randu' ); +var format = require( '@stdlib/string/format' ); +var pkg = require( './../package.json' ).name; +var incrnansumprod = require( './../lib' ); + + +// MAIN // + +bench( pkg, function benchmark( b ) { + var f; + var i; + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + f = incrnansumprod(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + } + b.toc(); + if ( typeof f !== 'function' ) { + b.fail( 'should return a function' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); + +bench( format( '%s::accumulator', pkg ), function benchmark( b ) { + var acc; + var v; + var i; + + acc = incrnansumprod(); + + b.tic(); + for ( i = 0; i < b.iterations; i++ ) { + v = acc( randu() * 10.0, randu() * 10.0 ); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + } + b.toc(); + if ( v !== v ) { + b.fail( 'should not return NaN' ); + } + b.pass( 'benchmark finished' ); + b.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/img/equation_sum_product.svg b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/img/equation_sum_product.svg new file mode 100644 index 000000000000..3e2856635040 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/img/equation_sum_product.svg @@ -0,0 +1,40 @@ + +s equals sigma-summation Underscript i equals 0 Overscript n minus 1 Endscripts x Subscript i Baseline y Subscript i + + + \ No newline at end of file diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/repl.txt new file mode 100644 index 000000000000..0aedf70e24cc --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/repl.txt @@ -0,0 +1,34 @@ + +{{alias}}() + Returns an accumulator function which incrementally computes a sum of + products, ignoring `NaN` values. + + If provided input values, the accumulator function returns an updated sum. + If not provided input values, the accumulator function returns the current + sum. + + For long running accumulations or accumulations of large numbers, care + should be taken to prevent overflow. + + Returns + ------- + acc: Function + Accumulator function. + + Examples + -------- + > var accumulator = {{alias}}(); + > var s = accumulator() + null + > s = accumulator( 2.0, 3.0 ) + 6.0 + > s = accumulator( -5.0, 2.0 ) + -4.0 + > s = accumulator( NaN, 6.0 ) + -4.0 + > s = accumulator() + -4.0 + + See Also + -------- + diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/types/index.d.ts new file mode 100644 index 000000000000..1dfde894d61b --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/types/index.d.ts @@ -0,0 +1,60 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +// TypeScript Version: 4.1 + +/// + +/** +* If provided arguments, returns an updated sum of products; otherwise, returns the current sum of products. +* +* @param x - value +* @param y - value +* @returns sum of products +*/ +type accumulator = ( x?: number, y?: number ) => number | null; + +/** +* Returns an accumulator function which incrementally computes a sum of products, ignoring `NaN` values. +* +* @returns accumulator function +* +* @example +* var accumulator = incrnansumprod(); +* +* var v = accumulator(); +* // returns null +* +* v = accumulator( 2.0, 3.0 ); +* // returns 6.0 +* +* v = accumulator( -5.0, 2.0 ); +* // returns -4.0 +* +* v = accumulator( NaN, 6.0 ); +* // returns -4.0 +* +* v = accumulator(); +* // returns -4.0 +*/ +declare function incrnansumprod(): accumulator; + + +// EXPORTS // + +export = incrnansumprod; diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/types/test.ts new file mode 100644 index 000000000000..d9b1effa4bae --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/docs/types/test.ts @@ -0,0 +1,69 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import incrnansumprod = require( './index' ); + + +// TESTS // + +// The function returns an accumulator function... +{ + incrnansumprod(); // $ExpectType accumulator +} + +// The compiler throws an error if the function is provided arguments... +{ + incrnansumprod( '5' ); // $ExpectError + incrnansumprod( 5 ); // $ExpectError + incrnansumprod( true ); // $ExpectError + incrnansumprod( false ); // $ExpectError + incrnansumprod( null ); // $ExpectError + incrnansumprod( undefined ); // $ExpectError + incrnansumprod( [] ); // $ExpectError + incrnansumprod( {} ); // $ExpectError + incrnansumprod( ( x: number ): number => x ); // $ExpectError +} + +// The function returns an accumulator function which returns an accumulated result... +{ + const acc = incrnansumprod(); + + acc(); // $ExpectType number | null + acc( 3.14, 2.0 ); // $ExpectType number | null +} + +// The compiler throws an error if the returned accumulator function is provided invalid arguments... +{ + const acc = incrnansumprod(); + + acc( '5', 1.0 ); // $ExpectError + acc( true, 1.0 ); // $ExpectError + acc( false, 1.0 ); // $ExpectError + acc( null, 1.0 ); // $ExpectError + acc( [], 1.0 ); // $ExpectError + acc( {}, 1.0 ); // $ExpectError + acc( ( x: number ): number => x, 1.0 ); // $ExpectError + + acc( 3.14, '5' ); // $ExpectError + acc( 3.14, true ); // $ExpectError + acc( 3.14, false ); // $ExpectError + acc( 3.14, null ); // $ExpectError + acc( 3.14, [] ); // $ExpectError + acc( 3.14, {} ); // $ExpectError + acc( 3.14, ( x: number ): number => x ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nansumprod/examples/index.js new file mode 100644 index 000000000000..c1eeccf250db --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/examples/index.js @@ -0,0 +1,50 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var randu = require( '@stdlib/random/base/randu' ); +var incrnansumprod = require( './../lib' ); + +var accumulator; +var sum; +var v1; +var v2; +var i; + +// Initialize an accumulator: +accumulator = incrnansumprod(); + +// For each simulated datum, update the sum-product... +console.log( '\nValue\tValue\tSum-Product\n' ); +for ( i = 0; i < 100; i++ ) { + if ( randu() < 0.2 ) { + v1 = NaN; + v2 = NaN; + } else if ( randu() < 0.3 ) { + v1 = NaN; + v2 = randu() * 100.0; + } else { + v1 = randu() * 100.0; + v2 = randu() * 100.0; + } + sum = accumulator( v1, v2 ); + console.log( '%s\t%s\t%s', ( isnan( v1 ) ) ? 'NaN' : v1.toFixed( 4 ), ( isnan( v2 ) ) ? 'NaN' : v2.toFixed( 4 ), ( sum === null ) ? 'null' : sum.toFixed( 4 ) ); +} +console.log( '\nFinal sum-product: %d\n', accumulator() ); diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nansumprod/lib/index.js new file mode 100644 index 000000000000..20edff968a0f --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/lib/index.js @@ -0,0 +1,57 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +/** +* Compute a sum of products incrementally, ignoring `NaN` values. +* +* @module @stdlib/stats/incr/nansumprod +* +* @example +* var incrnansumprod = require( '@stdlib/stats/incr/nansumprod' ); +* +* var accumulator = incrnansumprod(); +* +* var sum = accumulator( 2.0, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( 1.0, -1.0 ); +* // returns 5.0 +* +* sum = accumulator( NaN, NaN ); +* // returns 5.0 +* +* sum = accumulator( 3, NaN ); +* // returns 5.0 +* +* sum = accumulator( 3.0, 4.0 ); +* // returns 17.0 +* +* sum = accumulator(); +* // returns 17.0 +*/ + +// MODULES // + +var main = require( './main.js' ); + + +// EXPORTS // + +module.exports = main; diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nansumprod/lib/main.js new file mode 100644 index 000000000000..a779dfa4a59c --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/lib/main.js @@ -0,0 +1,78 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var incrsumprod = require( '@stdlib/stats/incr/sumprod' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); + + +// MAIN // + +/** +* Returns an accumulator function which incrementally computes a sum of products, ignoring NaN values. +* +* @returns {Function} accumulator function +* +* @example +* var accumulator = incrnansumprod(); +* +* var sum = accumulator( 2.0, 3.0 ); +* // returns 6.0 +* +* sum = accumulator( 1.0, -1.0 ); +* // returns 5.0 +* +* sum = accumulator( NaN, NaN ); +* // returns 5.0 +* +* sum = accumulator( 3, NaN ); +* // returns 5.0 +* +* sum = accumulator( 3.0, 4.0 ); +* // returns 17.0 +* +* sum = accumulator(); +* // returns 17.0 +*/ +function incrnansumprod() { + var sumprod = incrsumprod(); + return accumulator; + + /** + * If provided input values, the accumulator function returns an updated sum. If not provided input values, the accumulator function returns the current sum. + * + * @private + * @param {number} [x] - first value + * @param {number} [y] - second value + * @returns {(number|null)} sum-product or null + */ + function accumulator( x, y ) { + if ( arguments.length === 0 || isnan( x ) || isnan( y ) ) { + return sumprod(); + } + return sumprod( x, y ); + } +} + + +// EXPORTS // + +module.exports = incrnansumprod; diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/package.json b/lib/node_modules/@stdlib/stats/incr/nansumprod/package.json new file mode 100644 index 000000000000..4f2ee0e19f21 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/package.json @@ -0,0 +1,69 @@ +{ + "name": "@stdlib/stats/incr/nansumprod", + "version": "0.0.0", + "description": "Compute a sum of products incrementally, ignoring NaN values.", + "license": "Apache-2.0", + "author": { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + }, + "contributors": [ + { + "name": "The Stdlib Authors", + "url": "https://github.com/stdlib-js/stdlib/graphs/contributors" + } + ], + "main": "./lib", + "directories": { + "benchmark": "./benchmark", + "doc": "./docs", + "example": "./examples", + "lib": "./lib", + "test": "./test" + }, + "types": "./docs/types", + "scripts": {}, + "homepage": "https://github.com/stdlib-js/stdlib", + "repository": { + "type": "git", + "url": "git://github.com/stdlib-js/stdlib.git" + }, + "bugs": { + "url": "https://github.com/stdlib-js/stdlib/issues" + }, + "dependencies": {}, + "devDependencies": {}, + "engines": { + "node": ">=0.10.0", + "npm": ">2.7.0" + }, + "os": [ + "aix", + "darwin", + "freebsd", + "linux", + "macos", + "openbsd", + "sunos", + "win32", + "windows" + ], + "keywords": [ + "stdlib", + "stdmath", + "statistics", + "stats", + "mathematics", + "math", + "summation", + "sum", + "total", + "product", + "prod", + "dot", + "dot product", + "sum-product", + "incremental", + "accumulator" + ] +} diff --git a/lib/node_modules/@stdlib/stats/incr/nansumprod/test/test.js b/lib/node_modules/@stdlib/stats/incr/nansumprod/test/test.js new file mode 100644 index 000000000000..fea8378ac9d3 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/incr/nansumprod/test/test.js @@ -0,0 +1,111 @@ +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var tape = require( 'tape' ); +var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var incrnansumprod = require( './../lib' ); + + +// TESTS // + +tape( 'main export is a function', function test( t ) { + t.ok( true, __filename ); + t.strictEqual( typeof incrnansumprod, 'function', 'main export is a function' ); + t.end(); +}); + +tape( 'the function returns an accumulator function', function test( t ) { + t.equal( typeof incrnansumprod(), 'function', 'returns a function' ); + t.end(); +}); + +tape( 'the initial accumulated value is `null`', function test( t ) { + var acc = incrnansumprod(); + t.equal( acc(), null, 'returns expected value' ); + t.end(); +}); + +tape( 'the accumulator function incrementally computes a sum of products (aka dot product), ignoring NaN values', function test( t ) { + var expected; + var actual; + var data; + var acc; + var sum; + var N; + var x; + var y; + var i; + var a; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, NaN ], + [ 2.0, 5.0 ], + [ NaN, -4.0 ], + [ 3.0, 0.0 ], + [ NaN, NaN ] + ]; + N = data.length; + + expected = []; + actual = []; + for ( a = 0; a < N; a++ ) { + expected.push(undefined); + actual.push(undefined); + } + + acc = incrnansumprod(); + + sum = 0; + for ( i = 0; i < N; i++ ) { + x = data[ i ][ 0 ]; + y = data[ i ][ 1 ]; + if ( isnan( x ) === false && isnan( y ) === false ) { + sum += x * y; + } + expected[ i ] = sum; + actual[ i ] = acc( x, y ); + } + t.deepEqual( actual, expected, 'returns expected values' ); + t.end(); +}); + +tape( 'if not provided an input value, the accumulator function returns the current sum of products', function test( t ) { + var data; + var acc; + var i; + + data = [ + [ 2.0, 3.0 ], + [ 3.0, NaN ], + [ 2.0, 5.0 ], + [ NaN, -4.0 ], + [ 3.0, 0.0 ], + [ NaN, NaN ] + ]; + acc = incrnansumprod(); + for ( i = 0; i < data.length; i++ ) { + acc( data[ i ][ 0 ], data[ i ][ 1 ] ); + } + t.equal( acc(), 16.0, 'returns expected value' ); + t.end(); +}); diff --git a/lib/node_modules/@stdlib/stats/nanmax/package.json b/lib/node_modules/@stdlib/stats/nanmax/package.json index e5af976d5a38..74f11d202f9a 100644 --- a/lib/node_modules/@stdlib/stats/nanmax/package.json +++ b/lib/node_modules/@stdlib/stats/nanmax/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanmax", "version": "0.0.0", - "description": "Compute the maximum value along one or more ndarray dimensions, ignoring `NaN` values.", + "description": "Compute the maximum value along one or more ndarray dimensions, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanmaxabs/package.json b/lib/node_modules/@stdlib/stats/nanmaxabs/package.json index eef544846380..6bbd2f0c8514 100644 --- a/lib/node_modules/@stdlib/stats/nanmaxabs/package.json +++ b/lib/node_modules/@stdlib/stats/nanmaxabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanmaxabs", "version": "0.0.0", - "description": "Compute the maximum absolute value along one or more ndarray dimensions, ignoring `NaN` values.", + "description": "Compute the maximum absolute value along one or more ndarray dimensions, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanmean/package.json b/lib/node_modules/@stdlib/stats/nanmean/package.json index 9dde4e7298eb..cf9510e0829f 100644 --- a/lib/node_modules/@stdlib/stats/nanmean/package.json +++ b/lib/node_modules/@stdlib/stats/nanmean/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanmean", "version": "0.0.0", - "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring `NaN` values.", + "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanmeanors/package.json b/lib/node_modules/@stdlib/stats/nanmeanors/package.json index eb0df50ab459..920a3cc9d630 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanors/package.json +++ b/lib/node_modules/@stdlib/stats/nanmeanors/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanmeanors", "version": "0.0.0", - "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring `NaN` values and using ordinary recursive summation.", + "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring NaN values and using ordinary recursive summation.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanmeanpn/package.json b/lib/node_modules/@stdlib/stats/nanmeanpn/package.json index c96a0c409bc9..9dc1743d5818 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanpn/package.json +++ b/lib/node_modules/@stdlib/stats/nanmeanpn/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanmeanpn", "version": "0.0.0", - "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring `NaN` values and using a two-pass error correction algorithm.", + "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring NaN values and using a two-pass error correction algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanmeanwd/package.json b/lib/node_modules/@stdlib/stats/nanmeanwd/package.json index 9122a6c37956..b667ab90a217 100644 --- a/lib/node_modules/@stdlib/stats/nanmeanwd/package.json +++ b/lib/node_modules/@stdlib/stats/nanmeanwd/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanmeanwd", "version": "0.0.0", - "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring `NaN` values and using Welford's algorithm.", + "description": "Compute the arithmetic mean along one or more ndarray dimensions, ignoring NaN values and using Welford's algorithm.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanmin/package.json b/lib/node_modules/@stdlib/stats/nanmin/package.json index 2a988c2f6812..ec463cbc4bab 100644 --- a/lib/node_modules/@stdlib/stats/nanmin/package.json +++ b/lib/node_modules/@stdlib/stats/nanmin/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanmin", "version": "0.0.0", - "description": "Compute the minimum value along one or more ndarray dimensions, ignoring `NaN` values.", + "description": "Compute the minimum value along one or more ndarray dimensions, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanminabs/package.json b/lib/node_modules/@stdlib/stats/nanminabs/package.json index 3caa50505e61..2c18f459fa3a 100644 --- a/lib/node_modules/@stdlib/stats/nanminabs/package.json +++ b/lib/node_modules/@stdlib/stats/nanminabs/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanminabs", "version": "0.0.0", - "description": "Compute the minimum absolute value along one or more ndarray dimensions, ignoring `NaN` values.", + "description": "Compute the minimum absolute value along one or more ndarray dimensions, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/nanrange/package.json b/lib/node_modules/@stdlib/stats/nanrange/package.json index 5687a17f9b17..9910a8dc6abb 100644 --- a/lib/node_modules/@stdlib/stats/nanrange/package.json +++ b/lib/node_modules/@stdlib/stats/nanrange/package.json @@ -1,7 +1,7 @@ { "name": "@stdlib/stats/nanrange", "version": "0.0.0", - "description": "Compute the range along one or more ndarray dimensions, ignoring `NaN` values.", + "description": "Compute the range along one or more ndarray dimensions, ignoring NaN values.", "license": "Apache-2.0", "author": { "name": "The Stdlib Authors", diff --git a/lib/node_modules/@stdlib/stats/strided/README.md b/lib/node_modules/@stdlib/stats/strided/README.md index ed9fd8378f26..2c0202d7553c 100644 --- a/lib/node_modules/@stdlib/stats/strided/README.md +++ b/lib/node_modules/@stdlib/stats/strided/README.md @@ -80,7 +80,7 @@ The namespace exports the following: - [`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/strided/dmeanvar]: calculate the mean and variance of a double-precision floating-point strided array. - [`dmeanvarpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/strided/dmeanvarpn]: calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm. - [`dmeanwd( N, x, strideX )`][@stdlib/stats/strided/dmeanwd]: calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm. -- [`dmediansorted( N, x, strideX )`][@stdlib/stats/strided/dmediansorted]: calculate the median value of a sorted double-precision floating-point strided array. +- [`dmedianSorted( N, x, strideX )`][@stdlib/stats/strided/dmedian-sorted]: calculate the median value of a sorted double-precision floating-point strided array. - [`dmidrange( N, x, strideX )`][@stdlib/stats/strided/dmidrange]: calculate the mid-range of a double-precision floating-point strided array. - [`dmidrangeabs( N, x, strideX )`][@stdlib/stats/strided/dmidrangeabs]: calculate the mid-range of absolute values of a double-precision floating-point strided array. - [`dmin( N, x, strideX )`][@stdlib/stats/strided/dmin]: calculate the minimum value of a double-precision floating-point strided array. @@ -397,7 +397,7 @@ console.log( objectKeys( ns ) ); [@stdlib/stats/strided/dmeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanwd -[@stdlib/stats/strided/dmediansorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmediansorted +[@stdlib/stats/strided/dmedian-sorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmedian-sorted [@stdlib/stats/strided/dmidrange]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmidrange diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/README.md b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/README.md similarity index 85% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/README.md rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/README.md index b7445aa17576..ecb9f22b8096 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/README.md +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/README.md @@ -18,7 +18,7 @@ limitations under the License. --> -# dmediansorted +# dmedianSorted > Calculate the median value of a sorted double-precision floating-point strided array. @@ -33,10 +33,10 @@ limitations under the License. ## Usage ```javascript -var dmediansorted = require( '@stdlib/stats/strided/dmediansorted' ); +var dmedianSorted = require( '@stdlib/stats/strided/dmedian-sorted' ); ``` -#### dmediansorted( N, x, strideX ) +#### dmedianSorted( N, x, strideX ) Computes the median value of a sorted double-precision floating-point strided array `x`. @@ -44,11 +44,11 @@ Computes the median value of a sorted double-precision floating-point strided ar var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -var v = dmediansorted( x.length, x, 1 ); +var v = dmedianSorted( x.length, x, 1 ); // returns 2.0 x = new Float64Array( [ 3.0, 2.0, 1.0 ] ); -v = dmediansorted( x.length, x, 1 ); +v = dmedianSorted( x.length, x, 1 ); // returns 2.0 ``` @@ -65,7 +65,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] ); -var v = dmediansorted( 4, x, 2 ); +var v = dmedianSorted( 4, x, 2 ); // returns 2.5 ``` @@ -79,11 +79,11 @@ var Float64Array = require( '@stdlib/array/float64' ); var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element -var v = dmediansorted( 4, x1, 2 ); +var v = dmedianSorted( 4, x1, 2 ); // returns 2.0 ``` -#### dmediansorted.ndarray( N, x, strideX, offsetX ) +#### dmedianSorted.ndarray( N, x, strideX, offsetX ) Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. @@ -92,7 +92,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); -var v = dmediansorted.ndarray( x.length, x, 1, 0 ); +var v = dmedianSorted.ndarray( x.length, x, 1, 0 ); // returns 2.0 ``` @@ -107,7 +107,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] ); -var v = dmediansorted.ndarray( 4, x, 2, 1 ); +var v = dmedianSorted.ndarray( 4, x, 2, 1 ); // returns 2.0 ``` @@ -134,7 +134,7 @@ var v = dmediansorted.ndarray( 4, x, 2, 1 ); ```javascript var linspace = require( '@stdlib/array/linspace' ); -var dmediansorted = require( '@stdlib/stats/strided/dmediansorted' ); +var dmedianSorted = require( '@stdlib/stats/strided/dmedian-sorted' ); var options = { 'dtype': 'float64' @@ -142,7 +142,7 @@ var options = { var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); -var v = dmediansorted( x.length, x, 1 ); +var v = dmedianSorted( x.length, x, 1 ); console.log( v ); ``` @@ -173,17 +173,17 @@ console.log( v ); ### Usage ```c -#include "stdlib/stats/strided/dmediansorted.h" +#include "stdlib/stats/strided/dmedian_sorted.h" ``` -#### stdlib_strided_dmediansorted( N, \*X, strideX ) +#### stdlib_strided_dmedian_sorted( N, \*X, strideX ) Computes the median value of a sorted double-precision floating-point strided array. ```c const double x[] = { 1.0, 2.0, 3.0 }; -double v = stdlib_strided_dmediansorted( 3, x, 1 ); +double v = stdlib_strided_dmedian_sorted( 3, x, 1 ); // returns 2.0 ``` @@ -194,17 +194,17 @@ The function accepts the following arguments: - **strideX**: `[in] CBLAS_INT` stride length for `X`. ```c -double stdlib_strided_dmediansorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +double stdlib_strided_dmedian_sorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); ``` -#### stdlib_strided_dmediansorted_ndarray( N, \*X, strideX, offsetX ) +#### stdlib_strided_dmedian_sorted_ndarray( N, \*X, strideX, offsetX ) Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. ```c const double x[] = { 1.0, 2.0, 3.0 }; -double v = stdlib_strided_dmediansorted_ndarray( 3, x, 1, 0 ); +double v = stdlib_strided_dmedian_sorted_ndarray( 3, x, 1, 0 ); // returns 2.0 ``` @@ -216,7 +216,7 @@ The function accepts the following arguments: - **offsetX**: `[in] CBLAS_INT` starting index for `X`. ```c -double stdlib_strided_dmediansorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +double stdlib_strided_dmedian_sorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); ``` @@ -238,7 +238,7 @@ double stdlib_strided_dmediansorted_ndarray( const CBLAS_INT N, const double *X, ### Examples ```c -#include "stdlib/stats/strided/dmediansorted.h" +#include "stdlib/stats/strided/dmedian_sorted.h" #include int main( void ) { @@ -252,7 +252,7 @@ int main( void ) { const int strideX = 2; // Compute the median value: - double v = stdlib_strided_dmediansorted( N, x, strideX ); + double v = stdlib_strided_dmedian_sorted( N, x, strideX ); // Print the result: printf( "median: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.js similarity index 95% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.js index 885fa2384691..3f07a7dc3b10 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.js @@ -26,7 +26,7 @@ var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var dmediansorted = require( './../lib/dmediansorted.js' ); +var dmedianSorted = require( './../lib/dmedian_sorted.js' ); // VARIABLES // @@ -61,7 +61,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.native.js similarity index 92% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.native.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.native.js index aa83478e641a..8fd015544d92 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.native.js @@ -32,9 +32,9 @@ var pkg = require( './../package.json' ).name; // VARIABLES // -var dmediansorted = tryRequire( resolve( __dirname, './../lib/dmediansorted.native.js' ) ); +var dmedianSorted = tryRequire( resolve( __dirname, './../lib/dmedian_sorted.native.js' ) ); var opts = { - 'skip': ( dmediansorted instanceof Error ) + 'skip': ( dmedianSorted instanceof Error ) }; var options = { 'dtype': 'float64' @@ -66,7 +66,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.ndarray.js similarity index 95% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.ndarray.js index 33d2666599ff..0a477c1e0ebf 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.ndarray.js @@ -26,7 +26,7 @@ var linspace = require( '@stdlib/array/linspace' ); var pow = require( '@stdlib/math/base/special/pow' ); var format = require( '@stdlib/string/format' ); var pkg = require( './../package.json' ).name; -var dmediansorted = require( './../lib/ndarray.js' ); +var dmedianSorted = require( './../lib/ndarray.js' ); // VARIABLES // @@ -61,7 +61,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.ndarray.native.js similarity index 93% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.ndarray.native.js index 326b33df3208..13f763391be8 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/benchmark.ndarray.native.js @@ -32,9 +32,9 @@ var pkg = require( './../package.json' ).name; // VARIABLES // -var dmediansorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var dmedianSorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { - 'skip': ( dmediansorted instanceof Error ) + 'skip': ( dmedianSorted instanceof Error ) }; var options = { 'dtype': 'float64' @@ -66,7 +66,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); if ( isnan( v ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/c/benchmark.length.c similarity index 95% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/c/benchmark.length.c rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/c/benchmark.length.c index 74779382392f..c5dfd21d081f 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/benchmark/c/benchmark.length.c @@ -16,14 +16,14 @@ * limitations under the License. */ -#include "stdlib/stats/strided/dmediansorted.h" +#include "stdlib/stats/strided/dmedian_sorted.h" #include #include #include #include #include -#define NAME "dmediansorted" +#define NAME "dmedian-sorted" #define ITERATIONS 10000000 #define REPEATS 3 #define MIN 1 @@ -109,7 +109,7 @@ static double benchmark1( int iterations, int len ) { t = tic(); for ( i = 0; i < iterations; i++ ) { // cppcheck-suppress uninitvar - v = stdlib_strided_dmediansorted( len, x, 1 ); + v = stdlib_strided_dmedian_sorted( len, x, 1 ); if ( v != v ) { printf( "should not return NaN\n" ); break; @@ -145,7 +145,7 @@ static double benchmark2( int iterations, int len ) { t = tic(); for ( i = 0; i < iterations; i++ ) { // cppcheck-suppress uninitvar - v = stdlib_strided_dmediansorted_ndarray( len, x, 1, 0 ); + v = stdlib_strided_dmedian_sorted_ndarray( len, x, 1, 0 ); if ( v != v ) { printf( "should not return NaN\n" ); break; diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/binding.gyp b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/binding.gyp similarity index 100% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/binding.gyp rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/binding.gyp diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/repl.txt similarity index 100% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/repl.txt rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/repl.txt diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/types/index.d.ts similarity index 87% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/types/index.d.ts rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/types/index.d.ts index e5711bd766c1..9aebcc44cd37 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/types/index.d.ts @@ -19,7 +19,7 @@ // TypeScript Version: 4.1 /** -* Interface describing `dmediansorted`. +* Interface describing `dmedianSorted`. */ interface Routine { /** @@ -35,7 +35,7 @@ interface Routine { * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * - * var v = dmediansorted( x.length, x, 1 ); + * var v = dmedianSorted( x.length, x, 1 ); * // returns 2.0 */ ( N: number, x: Float64Array, strideX: number ): number; @@ -54,7 +54,7 @@ interface Routine { * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * - * var v = dmediansorted.ndarray( x.length, x, 1, 0 ); + * var v = dmedianSorted.ndarray( x.length, x, 1, 0 ); * // returns 2.0 */ ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number; @@ -73,7 +73,7 @@ interface Routine { * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * -* var v = dmediansorted( x.length, x, 1 ); +* var v = dmedianSorted( x.length, x, 1 ); * // returns 2.0 * * @example @@ -81,12 +81,12 @@ interface Routine { * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * -* var v = dmediansorted.ndarray( x.length, x, 1, 0 ); +* var v = dmedianSorted.ndarray( x.length, x, 1, 0 ); * // returns 2.0 */ -declare var dmediansorted: Routine; +declare var dmedianSorted: Routine; // EXPORTS // -export = dmediansorted; +export = dmedianSorted; diff --git a/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/types/test.ts new file mode 100644 index 000000000000..6d23a39bcfac --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/docs/types/test.ts @@ -0,0 +1,157 @@ +/* +* @license Apache-2.0 +* +* Copyright (c) 2020 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +import dmedianSorted = require( './index' ); + + +// TESTS // + +// The function returns a number... +{ + const x = new Float64Array( 10 ); + + dmedianSorted( x.length, x, 1 ); // $ExpectType number +} + +// The compiler throws an error if the function is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dmedianSorted( '10', x, 1 ); // $ExpectError + dmedianSorted( true, x, 1 ); // $ExpectError + dmedianSorted( false, x, 1 ); // $ExpectError + dmedianSorted( null, x, 1 ); // $ExpectError + dmedianSorted( undefined, x, 1 ); // $ExpectError + dmedianSorted( [], x, 1 ); // $ExpectError + dmedianSorted( {}, x, 1 ); // $ExpectError + dmedianSorted( ( x: number ): number => x, x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a second argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dmedianSorted( x.length, 10, 1 ); // $ExpectError + dmedianSorted( x.length, '10', 1 ); // $ExpectError + dmedianSorted( x.length, true, 1 ); // $ExpectError + dmedianSorted( x.length, false, 1 ); // $ExpectError + dmedianSorted( x.length, null, 1 ); // $ExpectError + dmedianSorted( x.length, undefined, 1 ); // $ExpectError + dmedianSorted( x.length, [], 1 ); // $ExpectError + dmedianSorted( x.length, {}, 1 ); // $ExpectError + dmedianSorted( x.length, ( x: number ): number => x, 1 ); // $ExpectError +} + +// The compiler throws an error if the function is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dmedianSorted( x.length, x, '10' ); // $ExpectError + dmedianSorted( x.length, x, true ); // $ExpectError + dmedianSorted( x.length, x, false ); // $ExpectError + dmedianSorted( x.length, x, null ); // $ExpectError + dmedianSorted( x.length, x, undefined ); // $ExpectError + dmedianSorted( x.length, x, [] ); // $ExpectError + dmedianSorted( x.length, x, {} ); // $ExpectError + dmedianSorted( x.length, x, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the function is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dmedianSorted(); // $ExpectError + dmedianSorted( x.length ); // $ExpectError + dmedianSorted( x.length, x ); // $ExpectError + dmedianSorted( x.length, x, 1, 10 ); // $ExpectError +} + +// Attached to main export is an `ndarray` method which returns a number... +{ + const x = new Float64Array( 10 ); + + dmedianSorted.ndarray( x.length, x, 1, 0 ); // $ExpectType number +} + +// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dmedianSorted.ndarray( '10', x, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( true, x, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( false, x, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( null, x, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( undefined, x, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( [], x, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( {}, x, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( ( x: number ): number => x, x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array... +{ + const x = new Float64Array( 10 ); + + dmedianSorted.ndarray( x.length, 10, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, '10', 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, true, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, false, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, null, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, undefined, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, [], 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, {}, 1, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, ( x: number ): number => x, 1, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dmedianSorted.ndarray( x.length, x, '10', 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, true, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, false, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, null, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, undefined, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, [], 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, {}, 0 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, ( x: number ): number => x, 0 ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... +{ + const x = new Float64Array( 10 ); + + dmedianSorted.ndarray( x.length, x, 1, '10' ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, true ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, false ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, null ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, undefined ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, [] ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, {} ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, ( x: number ): number => x ); // $ExpectError +} + +// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... +{ + const x = new Float64Array( 10 ); + + dmedianSorted.ndarray(); // $ExpectError + dmedianSorted.ndarray( x.length ); // $ExpectError + dmedianSorted.ndarray( x.length, x ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1 ); // $ExpectError + dmedianSorted.ndarray( x.length, x, 1, 0, 10 ); // $ExpectError +} diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/c/Makefile b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/c/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/c/Makefile rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/c/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/c/example.c similarity index 89% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/c/example.c rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/c/example.c index 8b32fedb0e56..b4b35b53f7c0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/c/example.c +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/c/example.c @@ -16,7 +16,7 @@ * limitations under the License. */ -#include "stdlib/stats/strided/dmediansorted.h" +#include "stdlib/stats/strided/dmedian_sorted.h" #include int main( void ) { @@ -30,7 +30,7 @@ int main( void ) { const int strideX = 2; // Compute the median value: - double v = stdlib_strided_dmediansorted( N, x, strideX ); + double v = stdlib_strided_dmedian_sorted( N, x, strideX ); // Print the result: printf( "median: %lf\n", v ); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/index.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/index.js similarity index 90% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/index.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/index.js index 3dcbbbecf3ef..f00277823831 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/examples/index.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/examples/index.js @@ -19,7 +19,7 @@ 'use strict'; var linspace = require( '@stdlib/array/linspace' ); -var dmediansorted = require( './../lib' ); +var dmedianSorted = require( './../lib' ); var options = { 'dtype': 'float64' @@ -27,5 +27,5 @@ var options = { var x = linspace( -5.0, 5.0, 10, options ); console.log( x ); -var v = dmediansorted( x.length, x, 1 ); +var v = dmedianSorted( x.length, x, 1 ); console.log( v ); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/include.gypi b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/include.gypi similarity index 100% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/include.gypi rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/include.gypi diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/include/stdlib/stats/strided/dmediansorted.h b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/include/stdlib/stats/strided/dmedian_sorted.h similarity index 73% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/include/stdlib/stats/strided/dmediansorted.h rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/include/stdlib/stats/strided/dmedian_sorted.h index 32543890b269..c7124076ad45 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/include/stdlib/stats/strided/dmediansorted.h +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/include/stdlib/stats/strided/dmedian_sorted.h @@ -16,8 +16,8 @@ * limitations under the License. */ -#ifndef STDLIB_STATS_STRIDED_DMEDIANSORTED_H -#define STDLIB_STATS_STRIDED_DMEDIANSORTED_H +#ifndef STDLIB_STATS_STRIDED_DMEDIAN_SORTED_H +#define STDLIB_STATS_STRIDED_DMEDIAN_SORTED_H #include "stdlib/blas/base/shared.h" @@ -31,15 +31,15 @@ extern "C" { /** * Computes the median value of a sorted double-precision floating-point strided array. */ -double API_SUFFIX(stdlib_strided_dmediansorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); +double API_SUFFIX(stdlib_strided_dmedian_sorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ); /** * Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics. */ -double API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); +double API_SUFFIX(stdlib_strided_dmedian_sorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ); #ifdef __cplusplus } #endif -#endif // !STDLIB_STATS_STRIDED_DMEDIANSORTED_H +#endif // !STDLIB_STATS_STRIDED_DMEDIAN_SORTED_H diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/dmediansorted.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/dmedian_sorted.js similarity index 91% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/dmediansorted.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/dmedian_sorted.js index b4bfee2cfa35..93a4cdefc3e0 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/dmediansorted.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/dmedian_sorted.js @@ -39,14 +39,14 @@ var ndarray = require( './ndarray.js' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * -* var v = dmediansorted( x.length, x, 1 ); +* var v = dmedianSorted( x.length, x, 1 ); * // returns 2.0 */ -function dmediansorted( N, x, strideX ) { +function dmedianSorted( N, x, strideX ) { return ndarray( N, x, strideX, stride2offset( N, strideX ) ); } // EXPORTS // -module.exports = dmediansorted; +module.exports = dmedianSorted; diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/dmediansorted.native.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/dmedian_sorted.native.js similarity index 90% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/dmediansorted.native.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/dmedian_sorted.native.js index 38fdc86ea147..1e9fac3ada10 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/dmediansorted.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/dmedian_sorted.native.js @@ -38,14 +38,14 @@ var addon = require( './../src/addon.node' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * -* var v = dmediansorted( x.length, x, 1 ); +* var v = dmedianSorted( x.length, x, 1 ); * // returns 2.0 */ -function dmediansorted( N, x, strideX ) { +function dmedianSorted( N, x, strideX ) { return addon( N, x, strideX ); } // EXPORTS // -module.exports = dmediansorted; +module.exports = dmedianSorted; diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/index.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/index.js similarity index 80% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/index.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/index.js index f39ffb0bac60..6fabb4c6fa6c 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/index.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/index.js @@ -21,24 +21,24 @@ /** * Compute the median value of a sorted double-precision floating-point strided array. * -* @module @stdlib/stats/strided/dmediansorted +* @module @stdlib/stats/strided/dmedian-sorted * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var dmediansorted = require( '@stdlib/stats/strided/dmediansorted' ); +* var dmedianSorted = require( '@stdlib/stats/strided/dmedian-sorted' ); * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * -* var v = dmediansorted( x.length, x, 1 ); +* var v = dmedianSorted( x.length, x, 1 ); * // returns 2.0 * * @example * var Float64Array = require( '@stdlib/array/float64' ); -* var dmediansorted = require( '@stdlib/stats/strided/dmediansorted' ); +* var dmedianSorted = require( '@stdlib/stats/strided/dmedian-sorted' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * -* var v = dmediansorted.ndarray( 4, x, 2, 1 ); +* var v = dmedianSorted.ndarray( 4, x, 2, 1 ); * // returns 0.0 */ diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/main.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/main.js similarity index 85% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/main.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/main.js index da06dd22d8b9..44ce8c6a9bc9 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/main.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/main.js @@ -21,15 +21,15 @@ // MODULES // var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); -var dmediansorted = require( './dmediansorted.js' ); +var dmedianSorted = require( './dmedian_sorted.js' ); var ndarray = require( './ndarray.js' ); // MAIN // -setReadOnly( dmediansorted, 'ndarray', ndarray ); +setReadOnly( dmedianSorted, 'ndarray', ndarray ); // EXPORTS // -module.exports = dmediansorted; +module.exports = dmedianSorted; diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/native.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/native.js similarity index 85% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/native.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/native.js index 23d921869a9c..f6f3eaf38194 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/native.js @@ -21,15 +21,15 @@ // MODULES // var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' ); -var dmediansorted = require( './dmediansorted.native.js' ); +var dmedianSorted = require( './dmedian_sorted.native.js' ); var ndarray = require( './ndarray.native.js' ); // MAIN // -setReadOnly( dmediansorted, 'ndarray', ndarray ); +setReadOnly( dmedianSorted, 'ndarray', ndarray ); // EXPORTS // -module.exports = dmediansorted; +module.exports = dmedianSorted; diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/ndarray.js similarity index 92% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/ndarray.js index 06c316be96aa..caa4cd5ece7e 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/ndarray.js @@ -39,10 +39,10 @@ var floor = require( '@stdlib/math/base/special/floor' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * -* var v = dmediansorted( 4, x, 2, 1 ); +* var v = dmedianSorted( 4, x, 2, 1 ); * // returns 0.0 */ -function dmediansorted( N, x, strideX, offsetX ) { +function dmedianSorted( N, x, strideX, offsetX ) { var n; var m; @@ -62,4 +62,4 @@ function dmediansorted( N, x, strideX, offsetX ) { // EXPORTS // -module.exports = dmediansorted; +module.exports = dmedianSorted; diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/ndarray.native.js similarity index 91% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/ndarray.native.js index 4d196eeae4d2..f5fc51736b54 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/lib/ndarray.native.js @@ -39,14 +39,14 @@ var addon = require( './../src/addon.node' ); * * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] ); * -* var v = dmediansorted( 4, x, 2, 1 ); +* var v = dmedianSorted( 4, x, 2, 1 ); * // returns 0.0 */ -function dmediansorted( N, x, strideX, offsetX ) { +function dmedianSorted( N, x, strideX, offsetX ) { return addon.ndarray( N, x, strideX, offsetX ); } // EXPORTS // -module.exports = dmediansorted; +module.exports = dmedianSorted; diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/manifest.json b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/manifest.json similarity index 100% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/manifest.json rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/manifest.json diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/package.json b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/package.json similarity index 96% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/package.json rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/package.json index 1b83fa5bfb9e..465284b85245 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/package.json +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/package.json @@ -1,5 +1,5 @@ { - "name": "@stdlib/stats/strided/dmediansorted", + "name": "@stdlib/stats/strided/dmedian-sorted", "version": "0.0.0", "description": "Calculate the median value of a sorted double-precision floating-point strided array.", "license": "Apache-2.0", diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/src/Makefile b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/Makefile similarity index 100% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/src/Makefile rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/Makefile diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/src/addon.c b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/addon.c similarity index 93% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/src/addon.c rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/addon.c index 0cfce041be53..cf1b7a7aea26 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/src/addon.c +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/addon.c @@ -16,7 +16,7 @@ * limitations under the License. */ -#include "stdlib/stats/strided/dmediansorted.h" +#include "stdlib/stats/strided/dmedian_sorted.h" #include "stdlib/blas/base/shared.h" #include "stdlib/napi/export.h" #include "stdlib/napi/argv.h" @@ -37,7 +37,7 @@ static napi_value addon( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 ); STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmediansorted)( N, X, strideX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmedian_sorted)( N, X, strideX ), v ); return v; } @@ -54,7 +54,7 @@ static napi_value addon_method( napi_env env, napi_callback_info info ) { STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 ); STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 ); STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 ); - STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( N, X, strideX, offsetX ), v ); + STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_dmedian_sorted_ndarray)( N, X, strideX, offsetX ), v ); return v; } diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/src/main.c b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/main.c similarity index 80% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/src/main.c rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/main.c index f4338b73dd33..166b4c789305 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/src/main.c +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/src/main.c @@ -16,7 +16,7 @@ * limitations under the License. */ -#include "stdlib/stats/strided/dmediansorted.h" +#include "stdlib/stats/strided/dmedian_sorted.h" #include "stdlib/blas/base/shared.h" #include "stdlib/strided/base/stride2offset.h" @@ -28,9 +28,9 @@ * @param strideX stride length * @return output value */ -double API_SUFFIX(stdlib_strided_dmediansorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { +double API_SUFFIX(stdlib_strided_dmedian_sorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) { const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX ); - return API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( N, X, strideX, ox ); + return API_SUFFIX(stdlib_strided_dmedian_sorted_ndarray)( N, X, strideX, ox ); } /** @@ -42,7 +42,7 @@ double API_SUFFIX(stdlib_strided_dmediansorted)( const CBLAS_INT N, const double * @param offsetX starting index for X * @return output value */ -double API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { +double API_SUFFIX(stdlib_strided_dmedian_sorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) { CBLAS_INT n; if ( N <= 0 ) { diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.dmediansorted.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.dmedian_sorted.js similarity index 83% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.dmediansorted.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.dmedian_sorted.js index 3a34bce746bd..0abaa5e0ba3a 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.dmediansorted.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.dmedian_sorted.js @@ -24,19 +24,19 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); -var dmediansorted = require( './../lib/dmediansorted.js' ); +var dmedianSorted = require( './../lib/dmedian_sorted.js' ); // TESTS // tape( 'main export is a function', function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof dmediansorted, 'function', 'main export is a function' ); + t.strictEqual( typeof dmedianSorted, 'function', 'main export is a function' ); t.end(); }); tape( 'the function has an arity of 3', function test( t ) { - t.strictEqual( dmediansorted.length, 3, 'has expected arity' ); + t.strictEqual( dmedianSorted.length, 3, 'has expected arity' ); t.end(); }); @@ -45,47 +45,47 @@ tape( 'the function calculates the median value of a sorted strided array', func var v; x = new Float64Array( [ -3.0, -2.0, -1.0, 1.0, 2.0, 3.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ 3.0, 2.0, 1.0, -1.0, -2.0, -3.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ -4.0, -5.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, -4.5, 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, -4.0, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ 0.0, -0.0, -0.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, NaN ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ 5.0, NaN ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, 5.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -97,10 +97,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 0, x, 1 ); + v = dmedianSorted( 0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dmediansorted( -1, x, 1 ); + v = dmedianSorted( -1, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -112,7 +112,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 1, x, 1 ); + v = dmedianSorted( 1, x, 1 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -133,7 +133,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = dmediansorted( 4, x, 2 ); + v = dmedianSorted( 4, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -154,7 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = dmediansorted( 4, x, -2 ); + v = dmedianSorted( 4, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -166,7 +166,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( x.length, x, 0 ); + v = dmedianSorted( x.length, x, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -191,7 +191,7 @@ tape( 'the function supports view offsets', function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - v = dmediansorted( 4, x1, 2 ); + v = dmedianSorted( 4, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.dmediansorted.native.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.dmedian_sorted.native.js similarity index 82% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.dmediansorted.native.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.dmedian_sorted.native.js index a4d235fe97a1..e630e32895d9 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.dmediansorted.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.dmedian_sorted.native.js @@ -30,9 +30,9 @@ var tryRequire = require( '@stdlib/utils/try-require' ); // VARIABLES // -var dmediansorted = tryRequire( resolve( __dirname, './../lib/dmediansorted.native.js' ) ); +var dmedianSorted = tryRequire( resolve( __dirname, './../lib/dmedianSorted.native.js' ) ); var opts = { - 'skip': ( dmediansorted instanceof Error ) + 'skip': ( dmedianSorted instanceof Error ) }; @@ -40,12 +40,12 @@ var opts = { tape( 'main export is a function', opts, function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof dmediansorted, 'function', 'main export is a function' ); + t.strictEqual( typeof dmedianSorted, 'function', 'main export is a function' ); t.end(); }); tape( 'the function has an arity of 3', opts, function test( t ) { - t.strictEqual( dmediansorted.length, 3, 'has expected arity' ); + t.strictEqual( dmedianSorted.length, 3, 'has expected arity' ); t.end(); }); @@ -54,47 +54,47 @@ tape( 'the function calculates the median value of a sorted strided array', opts var v; x = new Float64Array( [ -3.0, -2.0, -1.0, 1.0, 2.0, 3.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ 3.0, 2.0, 1.0, -1.0, -2.0, -3.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ -4.0, -5.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, -4.5, 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( v, -4.0, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ 0.0, -0.0, -0.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, NaN ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ 5.0, NaN ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, 5.0 ] ); - v = dmediansorted( x.length, x, 1 ); + v = dmedianSorted( x.length, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -106,10 +106,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 0, x, 1 ); + v = dmedianSorted( 0, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dmediansorted( -1, x, 1 ); + v = dmedianSorted( -1, x, 1 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -121,7 +121,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 1, x, 1 ); + v = dmedianSorted( 1, x, 1 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -142,7 +142,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = dmediansorted( 4, x, 2 ); + v = dmedianSorted( 4, x, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -163,7 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = dmediansorted( 4, x, -2 ); + v = dmedianSorted( 4, x, -2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -175,7 +175,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( x.length, x, 0 ); + v = dmedianSorted( x.length, x, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -200,7 +200,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element - v = dmediansorted( 4, x1, 2 ); + v = dmedianSorted( 4, x1, 2 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.js similarity index 84% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.js index eebeb2b35587..51222e3e79b9 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.js @@ -21,18 +21,18 @@ // MODULES // var tape = require( 'tape' ); -var dmediansorted = require( './../lib' ); +var dmedianSorted = require( './../lib' ); // TESTS // tape( 'main export is a function', function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof dmediansorted, 'function', 'main export is a function' ); + t.strictEqual( typeof dmedianSorted, 'function', 'main export is a function' ); t.end(); }); tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) { - t.strictEqual( typeof dmediansorted.ndarray, 'function', 'method is a function' ); + t.strictEqual( typeof dmedianSorted.ndarray, 'function', 'method is a function' ); t.end(); }); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.ndarray.js similarity index 82% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.ndarray.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.ndarray.js index 63ed480c3d3f..e46d8a3c2763 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.ndarray.js @@ -24,19 +24,19 @@ var tape = require( 'tape' ); var isnan = require( '@stdlib/math/base/assert/is-nan' ); var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' ); var Float64Array = require( '@stdlib/array/float64' ); -var dmediansorted = require( './../lib/ndarray.js' ); +var dmedianSorted = require( './../lib/ndarray.js' ); // TESTS // tape( 'main export is a function', function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof dmediansorted, 'function', 'main export is a function' ); + t.strictEqual( typeof dmedianSorted, 'function', 'main export is a function' ); t.end(); }); tape( 'the function has an arity of 4', function test( t ) { - t.strictEqual( dmediansorted.length, 4, 'has expected arity' ); + t.strictEqual( dmedianSorted.length, 4, 'has expected arity' ); t.end(); }); @@ -45,47 +45,47 @@ tape( 'the function calculates the median value of a sorted strided array', func var v; x = new Float64Array( [ -3.0, -2.0, -1.0, 1.0, 2.0, 3.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ 3.0, 2.0, 1.0, 0.0, -1.0, -2.0, -3.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ -4.0, -5.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, -4.5, 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, -4.0, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ 0.0, -0.0, -0.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, NaN ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ 5.0, NaN ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, 5.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -97,10 +97,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 0, x, 1, 0 ); + v = dmedianSorted( 0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dmediansorted( -1, x, 1, 0 ); + v = dmedianSorted( -1, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -112,7 +112,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 1, x, 1, 0 ); + v = dmedianSorted( 1, x, 1, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -133,7 +133,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) { 2.0 ]); - v = dmediansorted( 4, x, 2, 0 ); + v = dmedianSorted( 4, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -154,7 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t ) 2.0 ]); - v = dmediansorted( 4, x, -2, 6 ); + v = dmedianSorted( 4, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -166,7 +166,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( x.length, x, 0, 0 ); + v = dmedianSorted( x.length, x, 0, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -187,7 +187,7 @@ tape( 'the function supports an `offset` parameter', function test( t ) { 4.0 // 3 ]); - v = dmediansorted( 4, x, 2, 1 ); + v = dmedianSorted( 4, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.ndarray.native.js similarity index 82% rename from lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.ndarray.native.js rename to lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.ndarray.native.js index ecd1bc06391d..6a746c8dbb52 100644 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/stats/strided/dmedian-sorted/test/test.ndarray.native.js @@ -30,9 +30,9 @@ var tryRequire = require( '@stdlib/utils/try-require' ); // VARIABLES // -var dmediansorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); +var dmedianSorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) ); var opts = { - 'skip': ( dmediansorted instanceof Error ) + 'skip': ( dmedianSorted instanceof Error ) }; @@ -40,12 +40,12 @@ var opts = { tape( 'main export is a function', opts, function test( t ) { t.ok( true, __filename ); - t.strictEqual( typeof dmediansorted, 'function', 'main export is a function' ); + t.strictEqual( typeof dmedianSorted, 'function', 'main export is a function' ); t.end(); }); tape( 'the function has an arity of 4', opts, function test( t ) { - t.strictEqual( dmediansorted.length, 4, 'has expected arity' ); + t.strictEqual( dmedianSorted.length, 4, 'has expected arity' ); t.end(); }); @@ -54,47 +54,47 @@ tape( 'the function calculates the median value of a sorted strided array', opts var v; x = new Float64Array( [ -3.0, -2.0, -1.0, 1.0, 2.0, 3.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ 3.0, 2.0, 1.0, 0.0, -1.0, -2.0, -3.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, 0.0, 'returns expected value' ); x = new Float64Array( [ -4.0, -5.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, -4.5, 'returns expected value' ); x = new Float64Array( [ -4.0, -4.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( v, -4.0, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ -0.0, -0.0, -0.0, 0.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ 0.0, -0.0, -0.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isNegativeZero( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, NaN ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ 5.0, NaN ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); x = new Float64Array( [ NaN, 5.0 ] ); - v = dmediansorted( x.length, x, 1, 0 ); + v = dmedianSorted( x.length, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -106,10 +106,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 0, x, 1, 0 ); + v = dmedianSorted( 0, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); - v = dmediansorted( -1, x, 1, 0 ); + v = dmedianSorted( -1, x, 1, 0 ); t.strictEqual( isnan( v ), true, 'returns expected value' ); t.end(); @@ -121,7 +121,7 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( 1, x, 1, 0 ); + v = dmedianSorted( 1, x, 1, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -142,7 +142,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) { 2.0 ]); - v = dmediansorted( 4, x, 2, 0 ); + v = dmedianSorted( 4, x, 2, 0 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -163,7 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test 2.0 ]); - v = dmediansorted( 4, x, -2, 6 ); + v = dmedianSorted( 4, x, -2, 6 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); @@ -175,7 +175,7 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f x = new Float64Array( [ 1.0, -2.0, -4.0, -5.0, -6.0 ] ); - v = dmediansorted( x.length, x, 0, 0 ); + v = dmedianSorted( x.length, x, 0, 0 ); t.strictEqual( v, 1.0, 'returns expected value' ); t.end(); @@ -196,7 +196,7 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) { 4.0 // 3 ]); - v = dmediansorted( 4, x, 2, 1 ); + v = dmedianSorted( 4, x, 2, 1 ); t.strictEqual( v, 2.5, 'returns expected value' ); t.end(); diff --git a/lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/types/test.ts deleted file mode 100644 index fc455ae46ce2..000000000000 --- a/lib/node_modules/@stdlib/stats/strided/dmediansorted/docs/types/test.ts +++ /dev/null @@ -1,157 +0,0 @@ -/* -* @license Apache-2.0 -* -* Copyright (c) 2020 The Stdlib Authors. -* -* Licensed under the Apache License, Version 2.0 (the "License"); -* you may not use this file except in compliance with the License. -* You may obtain a copy of the License at -* -* http://www.apache.org/licenses/LICENSE-2.0 -* -* Unless required by applicable law or agreed to in writing, software -* distributed under the License is distributed on an "AS IS" BASIS, -* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -* See the License for the specific language governing permissions and -* limitations under the License. -*/ - -import dmediansorted = require( './index' ); - - -// TESTS // - -// The function returns a number... -{ - const x = new Float64Array( 10 ); - - dmediansorted( x.length, x, 1 ); // $ExpectType number -} - -// The compiler throws an error if the function is provided a first argument which is not a number... -{ - const x = new Float64Array( 10 ); - - dmediansorted( '10', x, 1 ); // $ExpectError - dmediansorted( true, x, 1 ); // $ExpectError - dmediansorted( false, x, 1 ); // $ExpectError - dmediansorted( null, x, 1 ); // $ExpectError - dmediansorted( undefined, x, 1 ); // $ExpectError - dmediansorted( [], x, 1 ); // $ExpectError - dmediansorted( {}, x, 1 ); // $ExpectError - dmediansorted( ( x: number ): number => x, x, 1 ); // $ExpectError -} - -// The compiler throws an error if the function is provided a second argument which is not a Float64Array... -{ - const x = new Float64Array( 10 ); - - dmediansorted( x.length, 10, 1 ); // $ExpectError - dmediansorted( x.length, '10', 1 ); // $ExpectError - dmediansorted( x.length, true, 1 ); // $ExpectError - dmediansorted( x.length, false, 1 ); // $ExpectError - dmediansorted( x.length, null, 1 ); // $ExpectError - dmediansorted( x.length, undefined, 1 ); // $ExpectError - dmediansorted( x.length, [], 1 ); // $ExpectError - dmediansorted( x.length, {}, 1 ); // $ExpectError - dmediansorted( x.length, ( x: number ): number => x, 1 ); // $ExpectError -} - -// The compiler throws an error if the function is provided a third argument which is not a number... -{ - const x = new Float64Array( 10 ); - - dmediansorted( x.length, x, '10' ); // $ExpectError - dmediansorted( x.length, x, true ); // $ExpectError - dmediansorted( x.length, x, false ); // $ExpectError - dmediansorted( x.length, x, null ); // $ExpectError - dmediansorted( x.length, x, undefined ); // $ExpectError - dmediansorted( x.length, x, [] ); // $ExpectError - dmediansorted( x.length, x, {} ); // $ExpectError - dmediansorted( x.length, x, ( x: number ): number => x ); // $ExpectError -} - -// The compiler throws an error if the function is provided an unsupported number of arguments... -{ - const x = new Float64Array( 10 ); - - dmediansorted(); // $ExpectError - dmediansorted( x.length ); // $ExpectError - dmediansorted( x.length, x ); // $ExpectError - dmediansorted( x.length, x, 1, 10 ); // $ExpectError -} - -// Attached to main export is an `ndarray` method which returns a number... -{ - const x = new Float64Array( 10 ); - - dmediansorted.ndarray( x.length, x, 1, 0 ); // $ExpectType number -} - -// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number... -{ - const x = new Float64Array( 10 ); - - dmediansorted.ndarray( '10', x, 1, 0 ); // $ExpectError - dmediansorted.ndarray( true, x, 1, 0 ); // $ExpectError - dmediansorted.ndarray( false, x, 1, 0 ); // $ExpectError - dmediansorted.ndarray( null, x, 1, 0 ); // $ExpectError - dmediansorted.ndarray( undefined, x, 1, 0 ); // $ExpectError - dmediansorted.ndarray( [], x, 1, 0 ); // $ExpectError - dmediansorted.ndarray( {}, x, 1, 0 ); // $ExpectError - dmediansorted.ndarray( ( x: number ): number => x, x, 1, 0 ); // $ExpectError -} - -// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array... -{ - const x = new Float64Array( 10 ); - - dmediansorted.ndarray( x.length, 10, 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, '10', 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, true, 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, false, 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, null, 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, undefined, 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, [], 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, {}, 1, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, ( x: number ): number => x, 1, 0 ); // $ExpectError -} - -// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number... -{ - const x = new Float64Array( 10 ); - - dmediansorted.ndarray( x.length, x, '10', 0 ); // $ExpectError - dmediansorted.ndarray( x.length, x, true, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, x, false, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, x, null, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, x, undefined, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, x, [], 0 ); // $ExpectError - dmediansorted.ndarray( x.length, x, {}, 0 ); // $ExpectError - dmediansorted.ndarray( x.length, x, ( x: number ): number => x, 0 ); // $ExpectError -} - -// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... -{ - const x = new Float64Array( 10 ); - - dmediansorted.ndarray( x.length, x, 1, '10' ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, true ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, false ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, null ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, undefined ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, [] ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, {} ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, ( x: number ): number => x ); // $ExpectError -} - -// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments... -{ - const x = new Float64Array( 10 ); - - dmediansorted.ndarray(); // $ExpectError - dmediansorted.ndarray( x.length ); // $ExpectError - dmediansorted.ndarray( x.length, x ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1 ); // $ExpectError - dmediansorted.ndarray( x.length, x, 1, 0, 10 ); // $ExpectError -} diff --git a/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts index 9fe48847f390..0cbcadc180b1 100644 --- a/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts @@ -45,7 +45,7 @@ import dmeanstdevpn = require( '@stdlib/stats/strided/dmeanstdevpn' ); import dmeanvar = require( '@stdlib/stats/strided/dmeanvar' ); import dmeanvarpn = require( '@stdlib/stats/strided/dmeanvarpn' ); import dmeanwd = require( '@stdlib/stats/strided/dmeanwd' ); -import dmediansorted = require( '@stdlib/stats/strided/dmediansorted' ); +import dmedianSorted = require( '@stdlib/stats/strided/dmedian-sorted' ); import dmidrange = require( '@stdlib/stats/strided/dmidrange' ); import dmidrangeabs = require( '@stdlib/stats/strided/dmidrangeabs' ); import dmin = require( '@stdlib/stats/strided/dmin' ); @@ -1004,7 +1004,7 @@ interface Namespace { * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * - * var v = ns.dmediansorted( x.length, x, 1 ); + * var v = ns.dmedianSorted( x.length, x, 1 ); * // returns 2.0 * * @example @@ -1012,10 +1012,10 @@ interface Namespace { * * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); * - * var v = ns.dmediansorted.ndarray( x.length, x, 1, 0 ); + * var v = ns.dmedianSorted.ndarray( x.length, x, 1, 0 ); * // returns 2.0 */ - dmediansorted: typeof dmediansorted; + dmedianSorted: typeof dmedianSorted; /** * Computes the mid-range of a double-precision floating-point strided array. diff --git a/lib/node_modules/@stdlib/stats/strided/dztest/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dztest/docs/repl.txt index fbe8287d892c..b916f01185b3 100644 --- a/lib/node_modules/@stdlib/stats/strided/dztest/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/strided/dztest/docs/repl.txt @@ -49,9 +49,11 @@ > var x = new {{alias:@stdlib/array/float64}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] ); > var N = x.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}(); + > var R = {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}; + > var out = new R(); > var res = {{alias}}( N, alt, 0.05, 0.0, 1.0, x, 1, out ); > res.toString() + {{alias}}.ndarray( N, alternative, alpha, mu, sigma, x, strideX, offsetX, out ) @@ -105,9 +107,11 @@ > var x = new {{alias:@stdlib/array/float64}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] ); > var N = x.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}(); + > var R = {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}; + > var out = new R(); > var res = {{alias}}.ndarray( N, alt, 0.05, 0.0, 1.0, x, 1, 0, out ); > res.toString() + See Also -------- diff --git a/lib/node_modules/@stdlib/stats/strided/dztest2/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/dztest2/docs/repl.txt index df5eba1e51ff..18b5a1120255 100644 --- a/lib/node_modules/@stdlib/stats/strided/dztest2/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/strided/dztest2/docs/repl.txt @@ -1,10 +1,10 @@ {{alias}}( NX, NY, alt, alpha, d, sdx, x, sx, sdy, y, sy, out ) - Computes a two-sample Z-test for two double-precision floating-point - strided arrays. + Computes a two-sample Z-test for two double-precision floating-point strided + arrays. - The `N` and stride parameters determine which elements in the strided - arrays are accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,7 +17,7 @@ NY: integer Number of indexed elements in `y`. - alternative: string + alt: string Alternative hypothesis. Must be one of the following: - two-sided: `x` has the same mean as `y`. @@ -36,7 +36,7 @@ x: Float64Array First input array. - strideX: integer + sx: integer Stride length for `x`. sdy: number @@ -45,7 +45,7 @@ y: Float64Array Second input array. - strideY: integer + sy: integer Stride length for `y`. out: Object @@ -63,14 +63,16 @@ > var NX = x.length; > var NY = y.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}(); - > var res = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out ); - > res.toString() + > var R = {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}; + > var out = new R(); + > var r = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out ); + > r.toString() + {{alias}}.ndarray( NX, NY, alt, alpha, d, sdx, x, sx, ox, sdy, y, sy, oy, out ) - Computes a two-sample Z-test for two double-precision floating-point - strided arrays using alternative indexing semantics. + Computes a two-sample Z-test for two double-precision floating-point strided + arrays using alternative indexing semantics. While typed array views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting @@ -84,7 +86,7 @@ NY: integer Number of indexed elements in `y`. - alternative: string + alt: string Alternative hypothesis. Must be one of the following: - two-sided: `x` has the same mean as `y`. @@ -103,10 +105,10 @@ x: Float64Array First input array. - strideX: integer + sx: integer Stride length for `x`. - offsetX: integer + ox: integer Starting index for `x`. sdy: number @@ -115,10 +117,10 @@ y: Float64Array Second input array. - strideY: integer + sy: integer Stride length for `y`. - offsetY: integer + oy: integer Starting index for `y`. out: Object @@ -136,9 +138,11 @@ > var NX = x.length; > var NY = y.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}(); - > var res = {{alias}}.ndarray( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 0, 2.0, x, 1, 0, out ); - > res.toString() + > var R = {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}; + > var out = new R(); + > var r = {{alias}}.ndarray(NX,NY,alt,0.05,0.0, 1.0,x,1,0, 2.0,y,1,0, out); + > r.toString() + See Also -------- diff --git a/lib/node_modules/@stdlib/stats/strided/lib/index.js b/lib/node_modules/@stdlib/stats/strided/lib/index.js index 451aa6f0094d..cf2dae5570d5 100644 --- a/lib/node_modules/@stdlib/stats/strided/lib/index.js +++ b/lib/node_modules/@stdlib/stats/strided/lib/index.js @@ -262,13 +262,13 @@ setReadOnly( ns, 'dmeanvarpn', require( '@stdlib/stats/strided/dmeanvarpn' ) ); setReadOnly( ns, 'dmeanwd', require( '@stdlib/stats/strided/dmeanwd' ) ); /** -* @name dmediansorted +* @name dmedianSorted * @memberof ns * @readonly * @type {Function} -* @see {@link module:@stdlib/stats/strided/dmediansorted} +* @see {@link module:@stdlib/stats/strided/dmedian-sorted} */ -setReadOnly( ns, 'dmediansorted', require( '@stdlib/stats/strided/dmediansorted' ) ); +setReadOnly( ns, 'dmedianSorted', require( '@stdlib/stats/strided/dmedian-sorted' ) ); /** * @name dmidrange diff --git a/lib/node_modules/@stdlib/stats/strided/mediansorted/README.md b/lib/node_modules/@stdlib/stats/strided/mediansorted/README.md index 78c5e45e24c1..a0eee8c9e128 100644 --- a/lib/node_modules/@stdlib/stats/strided/mediansorted/README.md +++ b/lib/node_modules/@stdlib/stats/strided/mediansorted/README.md @@ -148,7 +148,7 @@ console.log( v ); ## See Also -- [`@stdlib/stats/strided/dmediansorted`][@stdlib/stats/strided/dmediansorted]: calculate the median value of a sorted double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmedian-sorted`][@stdlib/stats/strided/dmedian-sorted]: calculate the median value of a sorted double-precision floating-point strided array. - [`@stdlib/stats/strided/mean`][@stdlib/stats/strided/mean]: calculate the arithmetic mean of a strided array. - [`@stdlib/stats/strided/smediansorted`][@stdlib/stats/strided/smediansorted]: calculate the median value of a sorted single-precision floating-point strided array. @@ -168,7 +168,7 @@ console.log( v ); -[@stdlib/stats/strided/dmediansorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmediansorted +[@stdlib/stats/strided/dmedian-sorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmedian-sorted [@stdlib/stats/strided/mean]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mean diff --git a/lib/node_modules/@stdlib/stats/strided/smediansorted/README.md b/lib/node_modules/@stdlib/stats/strided/smediansorted/README.md index 9f8a4e949f4e..a62391fedc65 100644 --- a/lib/node_modules/@stdlib/stats/strided/smediansorted/README.md +++ b/lib/node_modules/@stdlib/stats/strided/smediansorted/README.md @@ -275,7 +275,7 @@ int main( void ) { ## See Also -- [`@stdlib/stats/strided/dmediansorted`][@stdlib/stats/strided/dmediansorted]: calculate the median value of a sorted double-precision floating-point strided array. +- [`@stdlib/stats/strided/dmedian-sorted`][@stdlib/stats/strided/dmedian-sorted]: calculate the median value of a sorted double-precision floating-point strided array. - [`@stdlib/stats/strided/mediansorted`][@stdlib/stats/strided/mediansorted]: calculate the median value of a sorted strided array. - [`@stdlib/stats/strided/smean`][@stdlib/stats/strided/smean]: calculate the arithmetic mean of a single-precision floating-point strided array. @@ -293,7 +293,7 @@ int main( void ) { -[@stdlib/stats/strided/dmediansorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmediansorted +[@stdlib/stats/strided/dmedian-sorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmedian-sorted [@stdlib/stats/strided/mediansorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/mediansorted diff --git a/lib/node_modules/@stdlib/stats/strided/sztest/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/sztest/docs/repl.txt index 6acf476d2aec..1fca62f8ae67 100644 --- a/lib/node_modules/@stdlib/stats/strided/sztest/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/strided/sztest/docs/repl.txt @@ -49,9 +49,11 @@ > var x = new {{alias:@stdlib/array/float32}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] ); > var N = x.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float32}}(); + > var R = {{alias:@stdlib/stats/base/ztest/one-sample/results/float32}}; + > var out = new R(); > var res = {{alias}}( N, alt, 0.05, 0.0, 1.0, x, 1, out ); > res.toString() + {{alias}}.ndarray( N, alternative, alpha, mu, sigma, x, strideX, offsetX, out ) @@ -105,9 +107,11 @@ > var x = new {{alias:@stdlib/array/float32}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] ); > var N = x.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float32}}(); + > var R = {{alias:@stdlib/stats/base/ztest/one-sample/results/float32}}; + > var out = new R(); > var res = {{alias}}.ndarray( N, alt, 0.05, 0.0, 1.0, x, 1, 0, out ); > res.toString() + See Also -------- diff --git a/lib/node_modules/@stdlib/stats/strided/sztest2/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/sztest2/docs/repl.txt index 0b1abf715d61..1b1ecbe2236f 100644 --- a/lib/node_modules/@stdlib/stats/strided/sztest2/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/strided/sztest2/docs/repl.txt @@ -1,10 +1,10 @@ {{alias}}( NX, NY, alt, alpha, d, sdx, x, sx, sdy, y, sy, out ) - Computes a two-sample Z-test for two single-precision floating-point - strided arrays. + Computes a two-sample Z-test for two single-precision floating-point strided + arrays. - The `N` and stride parameters determine which elements in the strided - arrays are accessed at runtime. + The `N` and stride parameters determine which elements in the strided arrays + are accessed at runtime. Indexing is relative to the first index. To introduce an offset, use a typed array view. @@ -17,7 +17,7 @@ NY: integer Number of indexed elements in `y`. - alternative: string + alt: string Alternative hypothesis. Must be one of the following: - two-sided: `x` has the same mean as `y`. @@ -36,7 +36,7 @@ x: Float32Array First input array. - strideX: integer + sx: integer Stride length for `x`. sdy: number @@ -45,7 +45,7 @@ y: Float32Array Second input array. - strideY: integer + sy: integer Stride length for `y`. out: Object @@ -63,14 +63,16 @@ > var NX = x.length; > var NY = y.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float32}}(); - > var res = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out ); - > res.toString() + > var R = {{alias:@stdlib/stats/base/ztest/two-sample/results/float32}}; + > var out = new R(); + > var r = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out ); + > r.toString() + {{alias}}.ndarray( NX, NY, alt, alpha, d, sdx, x, sx, ox, sdy, y, sy, oy, out ) - Computes a two-sample Z-test for two single-precision floating-point - strided arrays using alternative indexing semantics. + Computes a two-sample Z-test for two single-precision floating-point strided + arrays using alternative indexing semantics. While typed array views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting @@ -84,7 +86,7 @@ NY: integer Number of indexed elements in `y`. - alternative: string + alt: string Alternative hypothesis. Must be one of the following: - two-sided: `x` has the same mean as `y`. @@ -103,10 +105,10 @@ x: Float32Array First input array. - strideX: integer + sx: integer Stride length for `x`. - offsetX: integer + ox: integer Starting index for `x`. sdy: number @@ -115,10 +117,10 @@ y: Float32Array Second input array. - strideY: integer + sy: integer Stride length for `y`. - offsetY: integer + oy: integer Starting index for `y`. out: Object @@ -136,9 +138,11 @@ > var NX = x.length; > var NY = y.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float32}}(); - > var res = {{alias}}.ndarray( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 0, 2.0, x, 1, 0, out ); - > res.toString() + > var R = {{alias:@stdlib/stats/base/ztest/two-sample/results/float32}}; + > var out = new R(); + > var r = {{alias}}.ndarray(NX,NY,alt,0.05,0.0, 1.0,x,1,0, 2.0,y,1,0, out); + > r.toString() + See Also -------- diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/README.md b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/README.md index 6576a81be148..f7f995cd8cf9 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/README.md +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/README.md @@ -138,7 +138,6 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p ```javascript var Memory = require( '@stdlib/wasm/memory' ); var oneTo = require( '@stdlib/array/one-to' ); -var zeros = require( '@stdlib/array/zeros' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ @@ -176,7 +175,7 @@ The function has the following parameters: - **xp**: input [`Float64Array`][@stdlib/array/float64] pointer (i.e., byte offset). - **sx**: stride length for `x`. -#### dmeanors.Module.prototype.ndarray( N, alpha, xp, sx, ox ) +#### dmeanors.Module.prototype.ndarray( N, xp, sx, ox ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using ordinary recursive summation and alternative indexing semantics. @@ -185,7 +184,6 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p ```javascript var Memory = require( '@stdlib/wasm/memory' ); var oneTo = require( '@stdlib/array/one-to' ); -var zeros = require( '@stdlib/array/zeros' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ @@ -288,8 +286,6 @@ console.log( y ); [@stdlib/stats/strided/dmeanors]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanors - - diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js index a2d2b8f50e8d..a8ebf5ca3f8a 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js @@ -48,7 +48,6 @@ * @example * var Memory = require( '@stdlib/wasm/memory' ); * var oneTo = require( '@stdlib/array/one-to' ); -* var zeros = require( '@stdlib/array/zeros' ); * var dmeanors = require( '@stdlib/stats/strided/wasm/dmeanors' ); * * // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/src/Makefile b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/src/Makefile +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/README.md b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/README.md index 0e82f2311520..65eb8e20971c 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/README.md +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/README.md @@ -175,7 +175,7 @@ The function has the following parameters: - **xp**: input [`Float64Array`][@stdlib/array/float64] pointer (i.e., byte offset). - **sx**: stride length for `x`. -#### dmeanpw.Module.prototype.ndarray( N, alpha, xp, sx, ox ) +#### dmeanpw.Module.prototype.ndarray( N, xp, sx, ox ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics. diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/index.js index 1417ad7a1d58..f74a07704bfb 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/index.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/index.js @@ -48,7 +48,6 @@ * @example * var Memory = require( '@stdlib/wasm/memory' ); * var oneTo = require( '@stdlib/array/one-to' ); -* var zeros = require( '@stdlib/array/zeros' ); * var dmeanpw = require( '@stdlib/stats/strided/wasm/dmeanpw' ); * * // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/Makefile b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/Makefile +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/README.md b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/README.md index 451006216e62..71f5f5e2cf40 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/README.md +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/README.md @@ -138,7 +138,6 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p ```javascript var Memory = require( '@stdlib/wasm/memory' ); var oneTo = require( '@stdlib/array/one-to' ); -var zeros = require( '@stdlib/array/zeros' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ @@ -176,7 +175,7 @@ The function has the following parameters: - **xp**: input [`Float64Array`][@stdlib/array/float64] pointer (i.e., byte offset). - **sx**: stride length for `x`. -#### dmeanwd.Module.prototype.ndarray( N, alpha, xp, sx, ox ) +#### dmeanwd.Module.prototype.ndarray( N, xp, sx, ox ) Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using Welford's algorithm and alternative indexing semantics. @@ -185,7 +184,6 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p ```javascript var Memory = require( '@stdlib/wasm/memory' ); var oneTo = require( '@stdlib/array/one-to' ); -var zeros = require( '@stdlib/array/zeros' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ @@ -288,8 +286,6 @@ console.log( y ); [@stdlib/stats/strided/dmeanwd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanwd - - diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js index 99781ff9d5b8..ad19a18c79aa 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js @@ -48,7 +48,6 @@ * @example * var Memory = require( '@stdlib/wasm/memory' ); * var oneTo = require( '@stdlib/array/one-to' ); -* var zeros = require( '@stdlib/array/zeros' ); * var dmeanwd = require( '@stdlib/stats/strided/wasm/dmeanwd' ); * * // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/src/Makefile b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/src/Makefile +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/README.md b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/README.md index 7f8ab8bcb2fb..afffb70b61b0 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/README.md +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/README.md @@ -143,7 +143,6 @@ Computes the [variance][variance] of a double-precision floating-point strided a ```javascript var Memory = require( '@stdlib/wasm/memory' ); var oneTo = require( '@stdlib/array/one-to' ); -var zeros = require( '@stdlib/array/zeros' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ @@ -191,7 +190,6 @@ Computes the [variance][variance] of a double-precision floating-point strided a ```javascript var Memory = require( '@stdlib/wasm/memory' ); var oneTo = require( '@stdlib/array/one-to' ); -var zeros = require( '@stdlib/array/zeros' ); // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): var mem = new Memory({ diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js index 37e77050fa30..c0eb0ed5d898 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js @@ -48,7 +48,6 @@ * @example * var Memory = require( '@stdlib/wasm/memory' ); * var oneTo = require( '@stdlib/array/one-to' ); -* var zeros = require( '@stdlib/array/zeros' ); * var dnanvariancewd = require( '@stdlib/stats/strided/wasm/dnanvariancewd' ); * * // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB): diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/scripts/postbuild.wat.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/scripts/postbuild.wat.js new file mode 100644 index 000000000000..0d8edabe98d0 --- /dev/null +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/scripts/postbuild.wat.js @@ -0,0 +1,64 @@ +#!/usr/bin/env node + +/** +* @license Apache-2.0 +* +* Copyright (c) 2026 The Stdlib Authors. +* +* Licensed under the Apache License, Version 2.0 (the "License"); +* you may not use this file except in compliance with the License. +* You may obtain a copy of the License at +* +* http://www.apache.org/licenses/LICENSE-2.0 +* +* Unless required by applicable law or agreed to in writing, software +* distributed under the License is distributed on an "AS IS" BASIS, +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +* See the License for the specific language governing permissions and +* limitations under the License. +*/ + +'use strict'; + +// MODULES // + +var resolve = require( 'path' ).resolve; +var licenseHeader = require( '@stdlib/_tools/licenses/header' ); +var insertHeader = require( '@stdlib/_tools/licenses/insert-header-file-list' ).sync; +var currentYear = require( '@stdlib/time/current-year' ); + + +// VARIABLES // + +var wpath = resolve( __dirname, '..', 'src', 'main.wat' ); + + +// MAIN // + +/** +* Main execution sequence. +* +* @private +* @throws {Error} unexpected error +*/ +function main() { + var headers; + var files; + var err; + + files = [ + wpath + ]; + headers = { + 'wat': licenseHeader( 'Apache-2.0', 'wat', { + 'year': currentYear(), + 'copyright': 'The Stdlib Authors' + }) + }; + err = insertHeader( files, headers ); + if ( err ) { + throw err; + } +} + +main(); diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/src/Makefile b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/src/Makefile index 1b1f35347760..d263d9b6d777 100644 --- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/src/Makefile +++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/src/Makefile @@ -202,6 +202,7 @@ $(wasm_targets): #/ $(wat_targets): %.wat: %.wasm $(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets) + $(QUIET) $(NODEJS) ./../scripts/postbuild.wat.js #/ # Compiles WebAssembly binary files to JavaScript. diff --git a/lib/node_modules/@stdlib/stats/strided/ztest/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/ztest/docs/repl.txt index 5c43482134d9..ac954fe2e10e 100644 --- a/lib/node_modules/@stdlib/stats/strided/ztest/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/strided/ztest/docs/repl.txt @@ -48,9 +48,11 @@ > var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ]; > var N = x.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}(); + > var R = {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}; + > var out = new R(); > var res = {{alias}}( N, alt, 0.05, 0.0, 1.0, x, 1, out ); > res.toString() + {{alias}}.ndarray( N, alternative, alpha, mu, sigma, x, strideX, offsetX, out ) @@ -104,9 +106,11 @@ > var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ]; > var N = x.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}(); + > var R = {{alias:@stdlib/stats/base/ztest/one-sample/results/float64}}; + > var out = new R(); > var res = {{alias}}.ndarray( N, alt, 0.05, 0.0, 1.0, x, 1, 0, out ); > res.toString() + See Also -------- diff --git a/lib/node_modules/@stdlib/stats/strided/ztest2/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/ztest2/docs/repl.txt index 94065e0c6bf5..aaad2696bf99 100644 --- a/lib/node_modules/@stdlib/stats/strided/ztest2/docs/repl.txt +++ b/lib/node_modules/@stdlib/stats/strided/ztest2/docs/repl.txt @@ -16,7 +16,7 @@ NY: integer Number of indexed elements in `y`. - alternative: string + alt: string Alternative hypothesis. Must be one of the following: - two-sided: `x` has the same mean as `y`. @@ -35,7 +35,7 @@ x: Array|TypedArray|Object First input array. - strideX: integer + sx: integer Stride length for `x`. sdy: number @@ -44,7 +44,7 @@ y: Array|TypedArray|Object Second input array. - strideY: integer + sy: integer Stride length for `y`. out: Object @@ -58,13 +58,15 @@ Examples -------- > var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ]; - > var x = [ 3.0, 3.0, 5.0, 7.0, 7.0 ]; + > var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ]; > var NX = x.length; > var NY = y.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}(); - > var res = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out ); - > res.toString() + > var R = {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}; + > var out = new R(); + > var r = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out ); + > r.toString() + {{alias}}.ndarray( NX, NY, alt, alpha, d, sdx, x, sx, ox, sdy, y, sy, oy, out ) @@ -82,7 +84,7 @@ NY: integer Number of indexed elements in `y`. - alternative: string + alt: string Alternative hypothesis. Must be one of the following: - two-sided: `x` has the same mean as `y`. @@ -101,10 +103,10 @@ x: Array|TypedArray|Object First input array. - strideX: integer + sx: integer Stride length for `x`. - offsetX: integer + ox: integer Starting index for `x`. sdy: number @@ -113,10 +115,10 @@ y: Array|TypedArray|Object Second input array. - strideY: integer + sy: integer Stride length for `y`. - offsetY: integer + oy: integer Starting index for `y`. out: Object @@ -134,9 +136,11 @@ > var NX = x.length; > var NY = y.length; > var alt = 'two-sided'; - > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}(); - > var res = {{alias}}.ndarray( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, out ); - > res.toString() + > var R = {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}; + > var out = new R(); + > var r = {{alias}}.ndarray(NX,NY,alt,0.05,0.0, 1.0,x,1,0, 2.0,y,1,0, out); + > r.toString() + See Also -------- diff --git a/lib/node_modules/@stdlib/stats/ztest2/README.md b/lib/node_modules/@stdlib/stats/ztest2/README.md index 0d5da68bee4f..7cd9f5df26c1 100644 --- a/lib/node_modules/@stdlib/stats/ztest2/README.md +++ b/lib/node_modules/@stdlib/stats/ztest2/README.md @@ -138,21 +138,14 @@ table = out.print(); To test whether the difference in the population means is equal to some other value than `0`, set the `difference` option. ```javascript -var normal = require( '@stdlib/random/base/normal' ).factory; +var normal = require( '@stdlib/random/array/normal' ).factory; var rnorm = normal({ 'seed': 372 }); -var x = new Array( 100 ); -var i; -for ( i = 0; i < x.length; i++ ) { - x[ i ] = rnorm( 2.0, 1.0 ); -} -var y = new Array( 100 ); -for ( i = 0; i < x.length; i++ ) { - y[ i ] = rnorm( 1.0, 1.0 ); -} +var x = rnorm( 100, 2.0, 1.0 ); +var y = rnorm( 100, 1.0, 1.0 ); var out = ztest2( x, y, 1.0, 1.0, { 'difference': 1.0 @@ -192,28 +185,17 @@ var table = out.print(); ```javascript -var rnorm = require( '@stdlib/random/base/normal' ); +var normal = require( '@stdlib/random/array/normal' ); var ztest2 = require( '@stdlib/stats/ztest2' ); -var table; -var out; -var x; -var y; -var i; - // Values drawn from a Normal(4,2) distribution -x = new Array( 100 ); -for ( i = 0; i < 100; i++ ) { - x[ i ] = rnorm( 4.0, 2.0 ); -} +var x = normal( 100, 4.0, 2.0 ); + // Values drawn from a Normal(3,2) distribution -y = new Array( 80 ); -for ( i = 0; i < 80; i++ ) { - y[ i ] = rnorm( 3.0, 2.0 ); -} +var y = normal( 80, 3.0, 2.0 ); -out = ztest2( x, y, 2.0, 2.0 ); -table = out.print(); +var out = ztest2( x, y, 2.0, 2.0 ); +var table = out.print(); console.log( table ); out = ztest2( x, y, 2.0, 2.0, { diff --git a/lib/node_modules/@stdlib/stats/ztest2/examples/index.js b/lib/node_modules/@stdlib/stats/ztest2/examples/index.js index d49169f4fff5..7d14c40fd7ba 100644 --- a/lib/node_modules/@stdlib/stats/ztest2/examples/index.js +++ b/lib/node_modules/@stdlib/stats/ztest2/examples/index.js @@ -18,28 +18,17 @@ 'use strict'; -var rnorm = require( '@stdlib/random/base/normal' ); +var normal = require( '@stdlib/random/array/normal' ); var ztest2 = require( './../lib' ); -var table; -var out; -var x; -var y; -var i; - // Values drawn from a Normal(4,2) distribution -x = new Array( 100 ); -for ( i = 0; i < 100; i++ ) { - x[ i ] = rnorm( 4.0, 2.0 ); -} +var x = normal( 100, 4.0, 2.0 ); + // Values drawn from a Normal(3,2) distribution -y = new Array( 80 ); -for ( i = 0; i < 80; i++ ) { - y[ i ] = rnorm( 3.0, 2.0 ); -} +var y = normal( 80, 3.0, 2.0 ); -out = ztest2( x, y, 2.0, 2.0 ); -table = out.print(); +var out = ztest2( x, y, 2.0, 2.0 ); +var table = out.print(); console.log( table ); out = ztest2( x, y, 2.0, 2.0, { diff --git a/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.js b/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.js index da9a2267afa8..92bc3984d793 100644 --- a/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/base/uniform' ).factory; -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var cidentityf = require( '@stdlib/complex/float32/base/identity' ); var real = require( '@stdlib/complex/float32/real' ); @@ -69,12 +69,12 @@ function createBenchmark( len ) { for ( i = 0; i < b.iterations; i++ ) { out = cmap( x.length, x, 1, y, 1, cidentityf ); v = out.get( i%len ); - if ( isnan( real( v ) ) || isnan( imag( v ) ) ) { + if ( isnanf( real( v ) ) || isnanf( imag( v ) ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( real( v ) ) || isnan( imag( v ) ) ) { + if ( isnanf( real( v ) ) || isnanf( imag( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.ndarray.js index 93b2a621286f..d4831307e89d 100644 --- a/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/strided/base/cmap/benchmark/benchmark.ndarray.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var uniform = require( '@stdlib/random/base/uniform' ).factory; -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var cidentityf = require( '@stdlib/complex/float32/base/identity' ); var real = require( '@stdlib/complex/float32/real' ); @@ -69,12 +69,12 @@ function createBenchmark( len ) { for ( i = 0; i < b.iterations; i++ ) { out = cmap( x.length, x, 1, 0, y, 1, 0, cidentityf ); v = out.get( i%len ); - if ( isnan( real( v ) ) || isnan( imag( v ) ) ) { + if ( isnanf( real( v ) ) || isnanf( imag( v ) ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( real( v ) ) || isnan( imag( v ) ) ) { + if ( isnanf( real( v ) ) || isnanf( imag( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.accessors.js b/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.accessors.js index 69149801fdfd..894903443175 100644 --- a/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.accessors.js +++ b/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.accessors.js @@ -23,7 +23,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var bernoulli = require( '@stdlib/random/base/bernoulli' ).factory; -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var cidentityf = require( '@stdlib/complex/float32/base/identity' ); var filledarray = require( '@stdlib/array/filled' ); @@ -82,13 +82,13 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { mskunary( arrays, shape, strides, cidentityf ); - if ( isnan( ybuf[ i%(len*2) ] ) ) { + if ( isnanf( ybuf[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); v = arrays[ 2 ].get( i%len ); - if ( isnan( realf( v ) ) || isnan( imagf( v ) ) ) { + if ( isnanf( realf( v ) ) || isnanf( imagf( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.ndarray.accessors.js b/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.ndarray.accessors.js index e1e975784697..7d8469d1ea7b 100644 --- a/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.ndarray.accessors.js +++ b/lib/node_modules/@stdlib/strided/base/mskunary/benchmark/benchmark.ndarray.accessors.js @@ -23,7 +23,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; var bernoulli = require( '@stdlib/random/base/bernoulli' ).factory; -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var cidentityf = require( '@stdlib/complex/float32/base/identity' ); var filledarray = require( '@stdlib/array/filled' ); @@ -84,13 +84,13 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { mskunary( arrays, shape, strides, offsets, cidentityf ); - if ( isnan( ybuf[ i%(len*2) ] ) ) { + if ( isnanf( ybuf[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); v = arrays[ 2 ].get( i%len ); - if ( isnan( realf( v ) ) || isnan( imagf( v ) ) ) { + if ( isnanf( realf( v ) ) || isnanf( imagf( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/nullary-addon-dispatch/README.md b/lib/node_modules/@stdlib/strided/base/nullary-addon-dispatch/README.md index 86d3d2e7df95..1d3bc36eb546 100644 --- a/lib/node_modules/@stdlib/strided/base/nullary-addon-dispatch/README.md +++ b/lib/node_modules/@stdlib/strided/base/nullary-addon-dispatch/README.md @@ -105,8 +105,6 @@ where Returns a function which dispatches to a native add-on applying a nullary function using alternative indexing semantics. - - ```javascript function addon( N, dtypeX, x, strideX ) { // Call into native add-on... @@ -188,8 +186,6 @@ where ## Examples - - ```javascript diff --git a/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.accessors.js b/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.accessors.js index 7c50e9b199e9..930a228efe40 100644 --- a/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.accessors.js +++ b/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.accessors.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var constantFunction = require( '@stdlib/utils/constant-function' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); @@ -75,13 +75,13 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { nullary( arrays, shape, strides, f ); - if ( isnan( xbuf[ i%(len*2) ] ) ) { + if ( isnanf( xbuf[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); v = arrays[ 0 ].get( i%len ); - if ( isnan( realf( v ) ) || isnan( imagf( v ) ) ) { + if ( isnanf( realf( v ) ) || isnanf( imagf( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.ndarray.accessors.js b/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.ndarray.accessors.js index f89c3d48b63d..e011b018f807 100644 --- a/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.ndarray.accessors.js +++ b/lib/node_modules/@stdlib/strided/base/nullary/benchmark/benchmark.ndarray.accessors.js @@ -21,7 +21,7 @@ // MODULES // var bench = require( '@stdlib/bench' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var constantFunction = require( '@stdlib/utils/constant-function' ); var Complex64 = require( '@stdlib/complex/float32/ctor' ); @@ -77,13 +77,13 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { nullary( arrays, shape, strides, offsets, f ); - if ( isnan( xbuf[ i%(len*2) ] ) ) { + if ( isnanf( xbuf[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); v = arrays[ 0 ].get( i%len ); - if ( isnan( realf( v ) ) || isnan( imagf( v ) ) ) { + if ( isnanf( realf( v ) ) || isnanf( imagf( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/reinterpret-float16/lib/main.js b/lib/node_modules/@stdlib/strided/base/reinterpret-float16/lib/main.js index 61992bf85fdf..709e8b6a5037 100644 --- a/lib/node_modules/@stdlib/strided/base/reinterpret-float16/lib/main.js +++ b/lib/node_modules/@stdlib/strided/base/reinterpret-float16/lib/main.js @@ -16,8 +16,6 @@ * limitations under the License. */ -/* eslint-disable stdlib/jsdoc-typedef-typos */ - 'use strict'; // MODULES // diff --git a/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.js b/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.js index 01736682cce1..280f31889cb1 100644 --- a/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var identityf = require( '@stdlib/number/float32/base/identity' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -65,12 +65,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { z = smap( x.length, x, 1, y, 1, identityf ); - if ( isnan( z[ i%len ] ) ) { + if ( isnanf( z[ i%len ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( z[ i%len ] ) ) { + if ( isnanf( z[ i%len ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.ndarray.js index c873919447c0..373b7122fc21 100644 --- a/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/strided/base/smap/benchmark/benchmark.ndarray.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var randu = require( '@stdlib/random/base/randu' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var identityf = require( '@stdlib/number/float32/base/identity' ); var Float32Array = require( '@stdlib/array/float32' ); @@ -65,12 +65,12 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { z = smap( x.length, x, 1, 0, y, 1, 0, identityf ); - if ( isnan( z[ i%len ] ) ) { + if ( isnanf( z[ i%len ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( z[ i%len ] ) ) { + if ( isnanf( z[ i%len ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.accessors.js b/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.accessors.js index 02259378688d..cf47d0d33906 100644 --- a/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.accessors.js +++ b/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.accessors.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var cidentityf = require( '@stdlib/complex/float32/base/identity' ); var filledarray = require( '@stdlib/array/filled' ); @@ -78,13 +78,13 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { unary( arrays, shape, strides, cidentityf ); - if ( isnan( ybuf[ i%(len*2) ] ) ) { + if ( isnanf( ybuf[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); v = arrays[ 1 ].get( i%len ); - if ( isnan( realf( v ) ) || isnan( imagf( v ) ) ) { + if ( isnanf( realf( v ) ) || isnanf( imagf( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.ndarray.accessors.js b/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.ndarray.accessors.js index c3fa40cde140..0f9061989489 100644 --- a/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.ndarray.accessors.js +++ b/lib/node_modules/@stdlib/strided/base/unary/benchmark/benchmark.ndarray.accessors.js @@ -22,7 +22,7 @@ var bench = require( '@stdlib/bench' ); var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory; -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var pow = require( '@stdlib/math/base/special/pow' ); var cidentityf = require( '@stdlib/complex/float32/base/identity' ); var filledarray = require( '@stdlib/array/filled' ); @@ -80,13 +80,13 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { unary( arrays, shape, strides, offsets, cidentityf ); - if ( isnan( ybuf[ i%(len*2) ] ) ) { + if ( isnanf( ybuf[ i%(len*2) ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); v = arrays[ 1 ].get( i%len ); - if ( isnan( realf( v ) ) || isnan( imagf( v ) ) ) { + if ( isnanf( realf( v ) ) || isnanf( imagf( v ) ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/strided/napi/smap/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/strided/napi/smap/benchmark/benchmark.native.js index 0f0d35c11063..f030c70c0bb3 100644 --- a/lib/node_modules/@stdlib/strided/napi/smap/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/strided/napi/smap/benchmark/benchmark.native.js @@ -22,7 +22,7 @@ var resolve = require( 'path' ).resolve; var bench = require( '@stdlib/bench' ); -var isnan = require( '@stdlib/math/base/assert/is-nan' ); +var isnanf = require( '@stdlib/math/base/assert/is-nanf' ); var Float32Array = require( '@stdlib/array/float32' ); var tryRequire = require( '@stdlib/utils/try-require' ); var pkg = require( './../package.json' ).name; @@ -52,12 +52,12 @@ bench( pkg, opts, function benchmark( b ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { z = addon( len, x, 1, y, 1 ); - if ( isnan( z[ i%len ] ) ) { + if ( isnanf( z[ i%len ] ) ) { b.fail( 'should not return NaN' ); } } b.toc(); - if ( isnan( z[ i%len ] ) ) { + if ( isnanf( z[ i%len ] ) ) { b.fail( 'should not return NaN' ); } b.pass( 'benchmark finished' ); diff --git a/lib/node_modules/@stdlib/symbol/async-iterator/docs/repl.txt b/lib/node_modules/@stdlib/symbol/async-iterator/docs/repl.txt index 57fbc2dee31d..38d324ba7458 100644 --- a/lib/node_modules/@stdlib/symbol/async-iterator/docs/repl.txt +++ b/lib/node_modules/@stdlib/symbol/async-iterator/docs/repl.txt @@ -10,6 +10,7 @@ Examples -------- > var s = {{alias}} + e.g., See Also -------- diff --git a/lib/node_modules/@stdlib/symbol/ctor/docs/repl.txt b/lib/node_modules/@stdlib/symbol/ctor/docs/repl.txt index f60e6f22266a..b985bc845d28 100644 --- a/lib/node_modules/@stdlib/symbol/ctor/docs/repl.txt +++ b/lib/node_modules/@stdlib/symbol/ctor/docs/repl.txt @@ -21,6 +21,7 @@ Examples -------- > var s = ( {{alias}} ) ? {{alias}}( 'beep' ) : null + e.g., See Also -------- diff --git a/lib/node_modules/@stdlib/symbol/iterator/docs/repl.txt b/lib/node_modules/@stdlib/symbol/iterator/docs/repl.txt index 453ba4f2a448..5fe5f04c9f21 100644 --- a/lib/node_modules/@stdlib/symbol/iterator/docs/repl.txt +++ b/lib/node_modules/@stdlib/symbol/iterator/docs/repl.txt @@ -10,6 +10,7 @@ Examples -------- > var s = {{alias}} + e.g., See Also -------- diff --git a/lib/node_modules/@stdlib/types/index.d.ts b/lib/node_modules/@stdlib/types/index.d.ts index 31d6378e0abc..e5cbe5d4bfba 100644 --- a/lib/node_modules/@stdlib/types/index.d.ts +++ b/lib/node_modules/@stdlib/types/index.d.ts @@ -35,6 +35,7 @@ */ declare module '@stdlib/types/array' { import { ComplexLike, Complex32, Complex64, Complex128 } from '@stdlib/types/complex'; + import { Uint64 } from '@stdlib/types/number'; import { Remap } from '@stdlib/types/utilities'; /** @@ -129,7 +130,7 @@ declare module '@stdlib/types/array' { /** * Data type for unsigned integer typed arrays. */ - type UnsignedIntegerDataType = 'uint32' | 'uint16' | 'uint8' | 'uint8c'; // "unsigned_integer" + type UnsignedIntegerDataType = 'uint64' | 'uint32' | 'uint16' | 'uint8' | 'uint8c'; // "unsigned_integer" /** * Data type for unsigned integer typed arrays. @@ -492,7 +493,7 @@ declare module '@stdlib/types/array' { * @example * const x: UnsignedIntegerTypedArray = new Uint32Array( 10 ); */ - type UnsignedIntegerTypedArray = Uint8Array | Uint8ClampedArray | Uint16Array | Uint32Array; + type UnsignedIntegerTypedArray = Uint8Array | Uint8ClampedArray | Uint16Array | Uint32Array | Uint64Array; /** * A boolean typed array. @@ -609,7 +610,7 @@ declare module '@stdlib/types/array' { * @example * const buf = new Uint8Array( 8 ); * - * const z: Complex64Array = { + * const x: BooleanArray = { * 'byteLength': 8, * 'byteOffset': 0, * 'BYTES_PER_ELEMENT': 1, @@ -835,6 +836,114 @@ declare module '@stdlib/types/array' { set( value: ArrayLike | Complex128Array | ComplexLike, i?: number ): void; } + /** + * A 64-bit unsigned integer array-like value. + * + * @example + * const buf = new Uint32Array( 8 ); + * + * const z: Uint64ArrayLike = { + * 'byteLength': 32, + * 'byteOffset': 0, + * 'BYTES_PER_ELEMENT': 8, + * 'length': 4, + * 'get': ( i: number ): obj.Uint64 => { + * return { + * 'hi': buf[ (2*i) ], + * 'lo': buf[ (2*i)+1 ], + * 'byteLength': 8, + * 'BYTES_PER_ELEMENT': 8 + * }; + * }, + * 'set': ( value: obj.Uint64, i?: number ) => { + * i = ( i ) ? i : 0; + * buf[ (2*i) ] = value.hi; + * buf[ (2*i)+1 ] = value.lo; + * } + * }; + */ + interface Uint64ArrayLike extends AccessorArrayLike { + /** + * Length (in bytes) of the array. + */ + byteLength: number; + + /** + * Offset (in bytes) of the array from the start of its underlying `ArrayBuffer`. + */ + byteOffset: number; + + /** + * Size (in bytes) of each array element. + */ + BYTES_PER_ELEMENT: number; + + /** + * Number of array elements. + */ + length: number; + + /** + * Returns an array element. + * + * @param i - element index + * @returns array element + */ + get( i: number ): Uint64 | void; + + /** + * Sets an array element. + * + * @param value - value(s) + * @param i - element index at which to start writing values (default: 0) + */ + set( value: ArrayLike | Uint64ArrayLike | Uint64 | bigint | number, i?: number ): void; + } + + /** + * 64-bit unsigned integer array. + * + * @example + * const buf = new Uint32Array( 8 ); + * + * const z: Uint64Array = { + * 'byteLength': 32, + * 'byteOffset': 0, + * 'BYTES_PER_ELEMENT': 8, + * 'length': 4, + * 'get': ( i: number ): obj.Uint64 => { + * return { + * 'hi': buf[ (2*i) ], + * 'lo': buf[ (2*i)+1 ], + * 'byteLength': 8, + * 'BYTES_PER_ELEMENT': 8 + * }; + * }, + * 'set': ( value: obj.Uint64, i?: number ) => { + * i = ( i ) ? i : 0; + * buf[ (2*i) ] = value.hi; + * buf[ (2*i)+1 ] = value.lo; + * } + * }; + */ + interface Uint64Array extends Uint64ArrayLike { + /** + * Returns an array element. + * + * @param i - element index + * @returns array element + */ + get( i: number ): Uint64 | void; + + /** + * Sets an array element. + * + * @param value - value(s) + * @param i - element index at which to start writing values (default: 0) + */ + set( value: ArrayLike | Uint64Array | Uint64 | bigint | number, i?: number ): void; + } + /** * A collection, which is defined as either an array, typed array, or an array-like object (excluding strings and functions). * @@ -939,6 +1048,7 @@ declare module '@stdlib/types/array' { * Mapping of unsigned integer data types to array constructors. */ type UnsignedIntegerDataTypeMap = { // eslint-disable-line @typescript-eslint/consistent-type-definitions + 'uint64': Uint64Array; 'uint32': Uint32Array; 'uint16': Uint16Array; 'uint8': Uint8Array; diff --git a/lib/node_modules/@stdlib/utils/async/until/lib/main.js b/lib/node_modules/@stdlib/utils/async/until/lib/main.js index bc849497ab91..a5253d73c6ed 100644 --- a/lib/node_modules/@stdlib/utils/async/until/lib/main.js +++ b/lib/node_modules/@stdlib/utils/async/until/lib/main.js @@ -112,9 +112,9 @@ function untilAsync( predicate, fcn, done, thisArg ) { // Cache the most recent results... if ( arguments.length > 1 ) { - args = new Array( arguments.length-1 ); + args = []; for ( i = 1; i < arguments.length; i++ ) { - args[ i-1 ] = arguments[ i ]; + args.push( arguments[ i ] ); } } // Run the test condition: diff --git a/lib/node_modules/@stdlib/utils/push/lib/push_typed_array.js b/lib/node_modules/@stdlib/utils/push/lib/push_typed_array.js index 3a94c9647c11..1cba859a4c1e 100644 --- a/lib/node_modules/@stdlib/utils/push/lib/push_typed_array.js +++ b/lib/node_modules/@stdlib/utils/push/lib/push_typed_array.js @@ -45,7 +45,7 @@ var ceil2 = require( '@stdlib/math/base/special/ceil2' ); // TODO: nextpow2 * var arr = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] ); * // returns [ 1.0, 2.0, 3.0, 4.0, 5.0 ] * -* arr = push( arr, 6.0, 7.0 ); +* arr = push( arr, [ 6.0, 7.0 ] ); * // returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ] */ function push( arr, items ) {